Workshops

Co-author: Reinhard Schinko

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In the run-up to the Paris negotiations and thereafter, there has been heated debate as to what the Loss and Damage debate should cover. Some analysts and observers suggest it should provide tested risk management measures including technologies to those that are in dire need for support due to increasing climate-related risk, while others suggest compensation is to be considered. Other voices consider the debate to largely be of symbolic character emphasising the need to avoid dangerous climate change by heavy mitigation. Many insiders have been wondering whether these perspectives can be disentangled and even reconciled. We suggest that there is potential for doing so and assert that the space for the Loss and Damage mechanism overall can be defined to encompass "transformative measures for avoiding and managing intolerable risks as well as curative measures for dealing with unavoided and unavoidable impacts."
The suggestions build on three lines of analysis, which have been fundamental for the debate on Loss and Damage. The first is a broad view towards jointly considering climate change and climate variability, thus providing a link to expertise around disaster risk management for managing today's adaptation deficits. The other building block is a consideration for risk preference, which in this context is framed as risk acceptance, tolerance, and intolerance in order to consider any limits to adaptation. Finally, we suggest a balance between distributive and compensatory justice as essential. This implies taking a distributive justice perspective, referring to sharing burdens in a demand-driven mode among agents without a need for causal climate attribution (the set-up in the DRM space currently), while compensatory justice, referring to the unequal levels of historical and current emissions produced, is to be upheld as well as a key principle motivating additional support and funding for managing climate-related risk. Overall, our discussion provides a principled framework for aligning perspectives and discussing policy options, incl. financing, climate-related insurance, comprehensive disaster risk management and a climate displacement facility, which are all options that are under discussion as the climate negotiations are going forward. The talk presents the rationale and some first quantification of the cost of supporting the implementation of the options discussed.

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Due to the decisions on the adoption of the Paris agreement, it has become very unlikely that measures to deal with climate loss and damage can be handled within the intuitively most plausible framings; liability and compensatory justice. From an ethical perspective, this paper argues that even in light of decision 1/CP.21 liability and compensation will have an important role to play for realizing Article 8 of the agreement. The paper shows how liability and compensation conceptually can be teared apart and why this separation is justified on ethical grounds. This opens up the space for a new way of thinking about compensatory entitlements and the distribution of liabilities. Compensatory entitlements concern the measures needed to make whole again the victims of climate loss or damage. Liability, by contrast, concerns the differentiated duties of all parties to the UNFCCC according to their varying capacities but irrespective of their contribution to climate change.

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Sea level rise and the increased frequency and intensity of coastal storms are imposing time limits - albeit of unknown duration - on the use of coastal property.  As coastal hazards escalate, the value of coastal property will fall.  However, it will not fall to zero.  There will still be demand for the use of coastal land until it is fully claimed by the sea.  Under climate change, freehold coastal property is essentially converting into a leasehold interest, where the term of the lease becomes the period of safe occupancy. 
Unabated economic development at the coasts suggests that the risk climate change poses to the world’s coastal capital stock is currently under-priced.  This presentation proposes a model for calculating the value of coastal property under climate change using a term-structure-of-lease-rates methodology.  The difference between the leasehold value and the freehold value quantifies, in today’s dollars, the loss induced by climate change on coastal property.  The model demonstrates how the value of the lease falls as escalating hazards increase the cost of occupying coastal property through: increased insurance premiums and excesses; higher loan to value ratios on mortgages; private cost sharing to support the maintenance of public infrastructure; and private property repair, accommodation and defence.  The model explores thresholds that influence the lease term including insurance retreat, mortgage retreat, infrastructure retreat and catastrophic events.
By deploying valuation methods already well established in the real estate industry, this model may provide a defensible method for quantifying potential compensation for economic loss imposed on coastal communities and nations under each of the IPCC’s four Representative Concentration Pathways.  This model may also be applicable to other resource degradation risks caused by climate change including escalating hazards from riparian flooding, land lost to desertification, and water scarcity caused by permanent snowpack loss.

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The results have several important implications concerning action area 1 of the loss and damage mechanism. I find that the significantly negative influence of tropical cy-clones on aggregate GDP growth can be attributed to contemporaneous negative ef-fects on four sector aggregates including agriculture, infrastructure, trade and tourism. The largest losses can be found in the agricultural sector, where a median storm event leads to a reduction of 58 % of the average annual per capita growth rate. In subse-quent years, tropical cyclones negatively affect the infrastructure, trade, tourism, and most surprisingly the construction sector. Developing countries seem to be more vul-nerable to the impacts of tropical cyclones than non-developing countries. In general, the results of the analyses support the ‘no recovery hypothesis’ discussed in the litera-ture, which states that natural disasters have long-lasting negative effects, from which the economy cannot recovery.

Co-author: Elisa Lanzi

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The need for integrated analysis of climate change and air pollution policies is widely acknowledged, often referred to as co-benefits. Much less is known, however, about how damages from climate change and damages from air pollution affect regional economies in the coming decades.
This paper focuses on the economic consequences of both climate change and outdoor air pollution until 2060. We build a dynamic CGE model with a common methodology for evaluating the joint economic consequences of climate change and air pollution. We use a production function approach that specifies sectoral and regional climate and air pollution impacts on specific inputs into the economy.
The modelling results highlight that despite significant climate forcing from various air pollutants, the net interaction effects through emission feedbacks are limited. Furthermore, the effect of climate damages on air pollution emissions and thus air pollution impacts, and the effect of air pollution damages on GHG emissions and thus climate damages are relatively small in comparison to the uncertainties surrounding the damage estimates.
Although the effects of climate change play out over a longer time horizon than those of air pollution, the coming decades are projected to have significant economic repercussions from both. For both cases, the majority of damages are located in relatively fragile economies in Asia and Africa. The largest percentage losses are observed in agriculture, where both climate change and air pollution have significant adverse effects. Furthermore, in the most affected regions and sectors there is a small but positive interaction effect: the damages from both types of impacts together is smaller than the sum of individual damages.
We finally quantify the non-market damages on premature deaths from heat stress and air pollution. These are not integrated in the modelling exercise, but their sheer size warrants that they are considered.

Co-authors: Francisco Estrada, Wouter Botzen

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CLIMRISK is an economic integrated assessment model for supporting decision-making at the global, national and subnational scales. This model is composed of simplified emulators of much more complex models of climate and the economy that allows for a finer spatial resolution, to include impact dynamics and to produce risk measures. Climate hazards and exposure are not uniformly distributed across and within regions and countries. As such, CLIMRISK uses a 0.5ºx0.5º spatial resolution for climate and socioeconomic variables. The climate module emulates 20 general circulation models and produces probabilistic regional projections using a range of climate sensitivity values (high, medium and low). The GDP and population projections share the same spatial resolution as the climate projections and combine information from the SSP/SRES datasets produced by a variety of leading integrated assessment modelling groups. The CLIMRISK model currently has two sets of contrasting damage functions to provide a representation of the uncertainty in the economic impact projections. The conservative set of damage functions is based on the RICE model but it was modified to be driven by changes in temperature at the gird scale, instead of at the global scale. The second set of damage functions incorporates the temporal dynamics of climate impacts and, for large changes in climate, can produce damages that are consistent in magnitude with those that can be obtained from some of the highly nonlinear functions that have been proposed in the literature. Recognizing that the estimates of economic impacts alone would hardly provide an adequate representation of the risks of climate change, CLIMRISK integrates a variety of climate, socioeconomic and damage projections to produce uni- and multivariate, dynamic risk measures that are defined by the user. The model focuses on offering decision-makers tailor-made information that can help evaluating climate policy options and developing dynamic risk-management planning.

To assess the interplay between these interlinked factors, and account for the external factors such as climate change on the Sudanese economy in a nexus (water-food-energy) context, a modeling suite capturing the theoretical nexus framework is used (Al-Riffai et al., 2017). The modeling suit comprises three components: 1) biophysical component, which couples a hydrological model, a river basin management model, and a crop model together; 2) energy component, which uses the TIMES energy model; and 3) socio-economic component, which connects the energy and biophysical components in a single-country recursive-dynamic Computable General Equilibrium model (DCGE).

Aggregation of biophysical climate impacts with multi-sector economic models

Hermann Lotze-Campen (Potsdam Institute for Climate Impact Research (PIK), Germany)

Economic impacts from natural disasters in a changing climate

Wouter Botzen (Vrije Universiteit Amsterdam, the Netherlands)

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Economic losses from natural disasters have been increasing during the last decades. This observed trend has been mainly attributed to socio-economic developments, like population and economic growth in disaster-prone areas. Future impacts from natural disasters are expected to rise in many regions around the world due to a continued increase in economic exposure and climate change. This highlights the need for policy makers to design policies that can mitigate the consequences of these disasters on the economy and society. A rapidly expanding literature has estimated the direct (e.g., property damage) and indirect economic impacts (e.g., GDP growth, regional development, trade) of natural disasters and how these may change under climate change. This talk as panelist discusses this emerging literature on both direct and indirect economic impacts of natural disasters to synthesize the main empirical and computational methods used and key findings to date. The latter include results of both economic impacts of different kinds of natural disasters and observed factors that mitigate disaster impacts. The discussed insights draw from macroeconomic models used to simulate impacts from natural disasters, including input-output models, computable general equilibrium models, and economic integrated assessment models. Moreover, main insights from the empirical literature are discussed such as main findings per disaster type and mitigating factors. The talk aims at drawing lessons for policy makers and outlining an agenda for future research in this field.

Ian Sue Wing (Boston University, United States)

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The burgeoning literature on economic modeling of the impacts of climate change considers multiple categories of impacts spanning a range of sectors. Drawing on the framework in Sue Wing and Lanzi (2014), this presentation will outline developments in sectoral and geographic scope, and the character of impact endpoints, assessed by recent economic simulation studies. Five major categories of impacts that have thus far been lacking in integrated assessment studies will then be addressed: extreme weather events that are geographically localized and of relatively short duration, inter- and intra-national migration, sub-clinical health effects and labor productivity, and non-market goods such as climate or landscape amenities and ecosystem services. For each category, the presentation will consider the spatial scale of analysis, the range of meteorological precursors and the ability of earth system models to resolve them, the empirical basis for translating impacts on biogeophysical variables into shocks into economic activities, and the promise and pitfalls of different options for connecting these shocks to models’ stylized representations of producer and consumer behavior.

It will discuss the value of impact science for addressing some of the most pressing questions in court, including: how are current and future impacts related to anthropogenic emissions? Who is most likely to be affected and when? And how do these impacts differ from emission trajectories that are in line with keeping average global temperature increase below 1.5C, or well below 2C?

Coming soon

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We intend to assess the linkage between past, current and future levels of (cumulative) greenhouse gas emissions and current and anticipated damages to coastal Bangladesh as a vulnerable delta region which undergoes the adverse effect of climate change in the form of fast onsets (flood, storm, tropical cyclones) and slow onsets (drought, sea level rise, hydro-morphological change, salinity intrusion) events. Estimation shows that during 1992 to 2012 overall 242 extreme events assault Bangladesh with total losses of USD 1833 million. In 2009, cyclone Sidr alone claimed 4,234 lives, damaged 186892 hectares crops and caused US$1.67 billion worth of economic loss in the coastal areas. The historical warming of 1^°C across Bangladesh is associated with 10% productivity loss in farming, indicates 4 million tons of food grain loss in Bangladesh, amounting to about USD 2.5 billion which is about 2% of current countries GDP. Here we apply a Regional Climate Model (RCM) to project future impacts under 2°C of global warming based on present-day management. In such a scenario salinity levels are expected to increase in most of the river basin of coastal Bangladesh and the period of salinity level above 1PPT is expected to double in Atharobanki, Baleswar and Madumati Rivers. Further, we adopted marginal productivity method to estimate the costs of adaptation measures to avoid these damages. They are estimated to reach USD 3663, 232, 831, and 3663 respectively for Saline Resistant Rice Variety, Rice-Prawn Farming, Short Duration Rice, and Land Management. Here, the share of adaptation cost on total production expenditure is estimated 4%, 10.43%, 1% and 18% for such measures. In order to reduce the loss and damages and increase the community resilience under 2°C global warming emphasize should be given on adaptation finance and innovation for the vulnerable group.

Co-authors: Gabriele Dono, Raffaele Cortignani, Dell'Unto Davide, Paola Deligios, Luca Doro, Nicola Lacetera, Laura Mula, Andrea Vitali, Pier Paolo Roggero

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We present a crop and a livestock model for the Mediterranean region as a tool to 1) separate the effects of climate variability from the effects of variations in human management across the historical period and 2) estimate productive responses and economic costs to climate change in the near term 2020-2030.

To this end we demonstrate the ability of the models to reproduce the effects of inter-annual climate variability in a diversified farming district that represents a wide range of rainfed and irrigated agricultural systems. The effects of near-term climate change on productivity are estimated based on calibrated climate scenarios for the period 2000-2010 and 2020-2030. The research focusses impacts of gradual climate change, leaving aside the role of extreme weather events which destroy the production cycles, rather than altering them.

Based on the projected changes in productivity a discrete stochastic programming (DSP) model also allows for estimating the economic impact of climate change on net income. The DSP model is structured into blocks each of which represents one of the farm types that operate in the study area. Each type has specific resources endowments, decision-making constraints and, therefore, specific economic responses to simulated climatic conditions. The adopted modelling strategy also takes into account the possibility and costs of adaptation and remaining changes in productivity after such measures are taken.  

A crucial element of differentiation was water availability, since only irrigated C3 crops took full advantage from the fertilization effect of increasing atmospheric CO2 concentration. Rainfed crop production is projected to be depressed by the expected reduction of spring rainfall associated to the higher temperatures. So, a dualism emerges between the smaller impact on crop production in the irrigated plain sub-zone, equipped with collective water networks and abundant irrigation resources, and the major negative impact in the hilly area, where these facilities and resources are absent. Intensive dairy farming is also expected to be negatively affected in terms of milk production and quality, and cattle mortality because of the increasing summer temperatures. We exemplarily estimate the economic effect of a positive anomaly of about 1°C on annual average and monthly mean peaks well above that threshold in summer.

The interdisciplinary modeling approach adopted for this study allows for the integrated assessment of the expected impacts of climate change over a wide range of farming systems under Mediterranean conditions.

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Models of marine ecosystems and fisheries often give careful consideration to the material flows within food webs and metabolic rates, and some consider other important processes such as reproduction and juvenile survival. However the prediction of changes in habitat quality, the transfer of energy across lower trophic levels, and the biogeochemical impacts of ecosystem structure remain challenging. In addition, future fishing pressure will depend strongly on complex economic, cultural and political dynamics, which are generally not included in models. I will briefly discuss to what degree these known unknowns could influence the FishMIP model projections.

Co-author: Christoph Mueller

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While great strides have been made in farm systems modeling over recent decades, significant issues still exist, especially for forecasting climate change impacts far in the future and at large spatial scales. These include data limitations (especially for farm management), missing processes (e.g. ozone damage, sterilization, pests, and diseases), limited mechanisms for representing technological change or dynamic adaptation, large uncertainties in key processes such CO2 fertilization effects, few models and assessments addressing fruits and vegetables, and feedbacks from neighboring sectors such as hydrology and labor productivity. At the same time, new opportunities are emerging to leverage new data sources (genetics, new FACE experiments, etc. ), high-performance computing, and information technologies to improve models and advance new exciting applications.

Co-authors: Wojciech Szewczyk, Luc Feyen, other JRC and HELIX colleagues

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The HELIX project has explored the biophysical and economic implications of climate change at the global scale for high-end emission scenarios. In particular, a set of climate futures consistent with the RCP8.5 have been studied with a series of climate impact models. High resolution bottom-up models (covering impacts such as river floods, agriculture, coastal areas, energy and transport infrastructure) have been run to derive biophysical impacts. An economic framework based on the computable general equilibrium methodology has been employed to integrate the various impacts under a consistent setting.
The presentation will discuss the main methodological aspects and results from the two phases in the economic analysis of the project. Particular attention will be paid to the differences between the bottom-up approach and the alternative statistical, top-down approach. Regarding the study results, firstly, the ISI-MIP fast track climate impacts (covering agriculture and river floods) will be presented. In a second part, the HELIX climate scenarios have been used to explore the implications in agriculture, river floods, coasts, energy, transport and human health.
The presentation will conclude with a series of possible research priorities in the economic analysis of climate impacts. Aspects like the difficulty in the economic modelling of adaptation, the sensitivity of the results to key CGE model assumptions and how to model non-market impacts will be considered.

Co-authors: Michael Greenstone, Solomon Hsiang, Amir Jina, Robert Kopp, Ishan Nath, James Rising, Ashwin Rode, Samuel Seo, Arvid Viaene, Jiacan Yuan, Alice Zhang

Empirically-based and plausibly causal estimates of the damages of climate change are greatly needed to inform rapidly developing global and local climate policies. To accurately reflect the costs of climate change, it is essential to estimate how much populations will adapt to a changing climate, yet adaptation remains one of the least understood aspects of social responses to climate. In this paper, we develop and implement a novel methodology to estimate climate damages globally which paves the way for the first data-driven, global social cost of carbon in which adaptation and its costs are empirically identified. We apply this method to mortality --- likely to be one of the largest losses associated with climate change. We assemble comprehensive sub-national panel data on mortality in 41countries that account for 56% of the world's population, and combine them with high resolution daily climate data to flexibly estimate the causal effect of temperature on mortality. Consistent with previous studies, we find the impacts of temperature on mortality have a U-shaped response; both hot days and cold days cause excess mortality. However, this average response obscures substantial heterogeneity, as populations are differentially adapted to extreme temperatures. We derive spatio-temporally heterogeneous mortality-temperature response functions to build a high-resolution model of adaptation in which incomes and average climate determine the sensitivity of mortality rates to changes in the climate. This model allows us to extrapolate response functions across the entire globe, as well as across time, using a range of economic, population, and climate change scenarios. Importantly, we develop and apply a revealed preference methodology to capture not only the benefits of adaptation, but also its costs. We combine these innovations to produce the first causal, micro-founded, global, empirically-derived climate damage function for human health. We project that by 2100, business-as-usual climate change is likely to incur mortality-only costs that amount to approximately 5% of global GDP for 5°C degrees of warming above pre-industrial levels. On average across model runs, we estimate that the upper bound on adaptation costs amounts to 55% of the total damages, a value that has never been estimated in the existing literature.

Co-authors: T. Carter, N. Pirttioja, R. Alkemade, E. Audsley, H. Bugmann, M. Flörke, I. Holman, Y. Honda, A. Ito, V. Janes, V. Lafond, R. Leemans, M. Mokrech, JP. Nunes, S. Nunez, D. Sandars, R. Snell, K. Takahashi, A. Tanaka, F. Wimmer, M. Yoshikawa

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Responses to future changes in climatic and socio-economic conditions can differ substantially between sectors and regions. A rich body of studies on climate change impacts, adaptation and vulnerability (CCIAV) quantifies these sensitivities for selected scenarios in sectoral and in some cases also cross-sectoral studies. Some attempts have also been made to quantify future changes of climate probabilistically and, more rarely, of socio-economic variables, but these have seldom been used in impact assessments. Here, we use a synthetic and scenario-neutral approach, impact response surfaces (IRSs), with a number of CCIAV models that illustrate a range of sectors, to address the questions: 1) What sectors and regions in Europe are most sensitive to future climate and socio-economic change and 2) how large are the risks of crossing critical impact thresholds?
A suite of nine global and regional CCIAV models has been employed to simulate the impacts of climate change on selected sectors (health, agriculture, biodiversity, forestry, hydrology and coastal flooding) in Europe. A sensitivity analysis was conducted for these models to assess changes in key climate and socio-economic variables such that two variables were modified at a time. The changes also included those implied by high-end scenarios that may lie outside the conventional application of many models. The variables modified were temperature and precipitation, sea-level rise, population, GDP, technological change and land use. Impact results were aggregated to eight European sub-regions and plotted as IRSs that depict the simulated behaviour of an impact variable in response to changes in two key explanatory variables. For selected impact variables and regions, these were overlaid with probabilistic projections of climate and population changes that enabled a quantified risk assessment.
Results clearly indicate substantial increases or decreases for different parts of each IRS. A key benefit of the IRS approach is its systematic way of analysing the sensitivities of modelled impacts. It also provides an opportunity to test model performance across a wide range of conditions, including those found at the high-end of projected changes. Examples are shown for estimating impact risks by combining the IRSs with probabilistic climate change and population projections.

Co-authors: Parkinson Simon, Burek Peter, Satoh Yusuke, Langan Simon, Wada Yoshihide

Global water withdrawals for beneficial purposes have been increasing substantially in the last century, driven by the growth in population and income. The ensuing damages have been building up rapidly during recent years, with many basins around the world undergoing pervasive water scarcity conditions. Moreover, impacts of future climatic and socio-economic changes are projected to further exacerbate supply deficit in those basins. Therefore, the design of adaptation strategies to address future water challenges is needed. This task requires quantitative tools for planning and policy evaluation that integrate various metrics, reflecting decision-making objectives and processes. This study presents a global hydro-economic modeling framework newly developed at IIASA that represents water resource systems, management options and associated economic values in an integrated manner. The model incorporates an optimization procedure aimed at balancing demand and supply of water at the level of large-scale river basins worldwide. The model uses information on water demand and availability provided by existing global integrated assessment models and global hydrological models. In this study, the model is used to evaluate the effects of reduced water availability under future climate change scenarios. The model is applied to basins in Africa which provides a challenging case study. However, the modeling framework is designed to be adaptable for any basin elsewhere. Model results show the economic and environmental tradeoffs among the different adaptation policy choices and the hurdles facing these policies. Specifically, our results suggest that addressing the challenge of adaptation to growing water scarcity in Africa will require major investments in more efficient water use technologies and unconventional freshwater supply options, such as wastewater recycling and desalination, with potential consequences on water supply costs, energy use and carbon emissions.

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The Paris Agreement defines a long-term temperature goal for international climate policy: “holding the increase in the global average temperature to well below 2°C above pre-industrial levels”. Yet, still short-term policy known as NDC (Nationally Determined Contribution) is insufficient to achieve 2°C and long-term policy implementation is uncertain (e.g. US secession from Paris Agreement) and it is still highly important to understand climate change impact when the mitigation stagnates or fails. Accordingly, we launched a project named MiLAi (http://s-14.iis.u-tokyo.ac.jp/eng/) aiming at projecting an aggregated economic impact by using individual sectors estimates. In order to do that, we incorporate physical models and an economic model (AIM/CGE; Asian-Pacific Integrated Model /Computable General Equilibrium). We have quantified the impacts of 5 out of 9 sectors, so far and we did it by using five climate models provided by ISIMIP. The aggregated impact is -3.6% of GDP in 2100 under SSP2 (Shared Socioeconomic Pathway) / RCP8.5(Representative Concentration Pathways). The largest contributor is labor productivity loss which accounts for -2.6%. In contrast, the GDP change becomes -0.67% under RCP2.6. This impact depends strongly on socioeconomic assumptions and under RCP8.5, the impact has a range from -2.8 to -7.3% of GDP which are represented by SSP1 and SSP3. Compared with mitigation cost (about 2-4%), climate change impact cost is equivalent and it indicates that taking mitigation action is reasonable. Moreover, socioeconomic development is fundamental to the climate change cost and considering the risk of failing the climate mitigation, socioeconomic transition toward SSP1 like the world is desired.

Here, I motivate for this workshop with a brief introduction to the climate and conflict literature, conflict forecasting and the climate change and socioeconomic scenario framework employed by the climate research community.

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The contribution outlines a methodology to forecast internal armed conflict and related political events based on core models in empirical social science research, and presents a set of forecasts for the 2017--2100 period developed with reference to the five SSPs. Such forecasts are useful for climate change research since armed conflicts and political upheavals may critically impact the economies of affected countries as well as their capacity for adaptation and mitigation. The contribution also suggests how the forecasts can be used to adjust core input factors in Integrated Assessment Models (IAMs) that are used to evaluate climate policy and impacts. The methodology combines a set of statistical models relating the incidence of the political events to factors that have been identified in the conflict research literature. It involves a simulation tool that allows exploring the long-range implications of these models, including how conflicts diffuse over time and space, and projections for core input variables such as standard operationalizations of the SSPs.

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The quantitative study and forecast of state failure and/or political instability often relies on predictive models using a single set of variables. However, recent research suggests that state failure may be a process characterized by equifinality and that multiple alternative pathways to state failure and/or political instability may exist. This paper presents initial results using the International Futures platform that explore demographic, economic, political institutions, and structural imbalances as potentially competing accounts of why states fail.

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The potential links between climate change and conflict have gained enormous academic and public attention. Several authors and decision makers link higher temperatures, more (intense) natural disasters and forced migration to armed violence, while other remain highly sceptical about such links. But this debate has largely ignored the growing literature on disaster diplomacy and environmental peacemaking, which argues that shared environmental challenges can facilitate cooperation and eventually peace between different groups and states. After explaining the theoretical foundations of this literature, I present the results of a regression analysis and a qualitative comparative analysis (QCA) on the impact of environmental cooperation on interstate relations. Both analyses suggest that under certain circumstances, shared environmental challenges (similar to those caused by climate change) and common problem solving facilitate more peaceful international relations. Preliminary case study evidence from the Middle East and East Africa suggests that this link also holds on a subnational level.

Co-authors: Carl-Friedrich Schleussner, Reik V. Donner, Hans-Joachim Schellnhuber

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Social and political tensions keep on fueling armed conflicts around the world. Although each conflict is the result of an individual context-specific mixture of interconnected factors, ethnicity appears to play a prominent and almost ubiquitous role in many of them. This overall state of affairs is likely to be exacerbated by anthropogenic climate change and in particular climate-related natural disasters. Ethnic divides might serve as predetermined conflict lines in case of rapidly emerging societal tensions arising from disruptive events like natural disasters. Here, we hypothesize that climate-related disaster occurrence enhances armed-conflict outbreak risk in ethnically fractionalized countries. Using event coincidence analysis, we test this hypothesis based on data on armed-conflict outbreaks and climate-related natural disasters for the period 1980–2010. Globally, we find a coincidence rate of 9% regarding armed-conflict outbreak and disaster occurrence such as heat waves or droughts. Our analysis also reveals that, during the period in question, about 23% of conflict outbreaks in ethnically highly fractionalized countries robustly coincide with climatic calamities. Although we do not report evidence that climate-related disasters act as direct triggers of armed conflicts, the disruptive nature of these events seems to play out in ethnically fractionalized societies in a particularly tragic way. This observation has important implications for future security policies as several of the world’s most conflict-prone regions, including North and Central Africa as well as Central Asia, are both exceptionally vulnerable to anthropogenic climate change and characterized by deep ethnic divides.

To Conclude; the need for a descent life is another aspect of climate changes as wars and climate changes are in cause and effect relationship.

During the 12th meeting of the Conference of the Parties to the Convention on Biological Diversity, the Republic of Korea launched the Peace and Biodiversity Dialogue Initiative, as a potential solution to global concerns about conflict areas. Environmental diplomacy is drawing together agencies from the environmental, human rights and peacebuilding spheres of the UN. At the same time, there is so much to be done since it would be difficult for institutions working in isolation to succeed.

Co-authors: Uris Baldos, Frances Moore

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The climate impacts literature has emphasized the importance role of geography to climate impacts. Pattern scaling of the consequences of global warming for regional temperature and precipitation suggests that yield effects of a given level of global average warming are larger in places that are already hot, and continental interior and higher latitudes where local warming is larger. In addition, net importing and net exporting regions are expected to experience very different welfare consequences from higher food prices. However, this literature has not come to grips with the true geography of international agricultural trade, which is characterized by surprisingly rigid bilateral trade relationships stemming from proximity, transport costs, colonial relationships, common language and other geopolitical considerations. In this paper, we utilize the meta-analysis function recently published by Moore et al. (2017) to characterize global gridded climate impacts for corn, soybeans, wheat and rice in the presence of a 2 degrees C temperature increase. Yield impacts are incorporated into the GTAP model of global trade in order to evaluate the welfare impacts on 140 countries/regions. Impacts are decomposed into five components: direct, allocative efficiency, world price, export, and import-specific effects. The first three have been well-covered in the literature, but abstract from bilateral trade relationships. The latter two effects reflect the correlations between a country’s trading partners and the pattern of climate impacts. Countries which rely on imports from those regions adversely affected by climate change experience greater than average welfare losses, whereas countries exporting to these hard-hit regions benefit from increased market access. Our results characterize the interplay between geographically differentiated climate impacts on agriculture and the bilateral pattern of agricultural trade that ultimately determines the welfare effects of climate change.

Co-authors: Justin S. Baker, Petr Havlík, Robert Beach, David Leclère, Erwin Schmid, Hugo Valin

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Previous climate change impact assessments of the domestic agricultural sector have relied in part on domestic partial equilibrium models of the agriculture and other land use sectors. While such models often provide substantial detail on domestic production systems needed for climate impact assessments, these tools typically hold agricultural supply functions fixed in the rest of the world. Thus, even with endogenous trade flows, domestic partial equilibrium models ignore potential systemic productivity changes globally under assumed climate change scenarios. Country-scale assessments that do not explicitly account for global market interactions or adjust future productivity assumptions in the rest of the world to account for climate change can result in biased projections of domestic climate change impacts. These studies also explicitly focus on the adaptation issue rather from the producers than consumers perspective.
To evaluate the potential limitation of country-scale climate impact assessments, this study applies a global model of agriculture and forestry to evaluate climate change impacts on U.S. agriculture with and without accounting for climate change impacts in the rest of the world. To this team’s knowledge, this is the first attempt to quantify the relative difference in U.S. agricultural sector climate change impacts with and without directly accounting for climate change in the rest of the world. This is accomplished through a unique scenario design that first isolates several climate change scenarios and exogenous crop yield impacts to the U.S. only, followed by scenarios that extend the climate impacts to the rest of the world. Then, additional sensitivity analysis is conducted in which global agricultural trade is more rapidly liberalized, which provides a buffer against domestic productivity shocks brought on by climate change. This manuscript focuses on U.S. results to illustrate the potential importance of accounting for global climate impacts when projecting domestic impacts.

Co-author: Leonie Wenz

This paper provides a new estimate on the impacts of climate conditions on economic activity. By using Gross Regional Product (GRP) at the highest administrative level below the nation state as an indicator of the value of economic production of more than 1400 regions, we estimate direct and indirect impacts of weather and climate. We test for two main impact channels: short run -- or weather -- impacts using annual data variation as well as long-run -- or climate -- impacts using cross-regional climate data with country fixed-effects. We further test how geographic conditions and openness to trade affect these impacts.
We find that production in hot climates is reduced by annual temperature shocks whereas it increases in cold climates. This finding holds also for regions with negligible agricultural sector share. Years of excessive heat, measured by the Simplified Welt Bulb Globe Temperature-index, reduce economic activity by almost seven percent. With respect to climate conditions, we find that one degree of temperature increase reduces economic production by 1 percent approximately. Moving from temperate to hot climates reduces GRP by almost 20 percent.

Co-authors: Matt Gidden, Petr Havlik, Volker Krey, Simon Langan, Simon Parkinson, Keywan Riahi, Joeri Rogelj, Yoshi Wada

The Shared Socioeconomic Pathways (SSPs) provide a framework and projections for assessing scenarios of socioeconomic change alongside climate impacts and options for mitigation and adaptation. The development of spatial socioeconomic datasets now facilitates impacts and vulnerability assessment from climate impact models. We calculate a set of climate impact indicators covering water, energy and land sectors (e.g. changes in runoff, discharge and water scarcity, cropland change and biodiversity, energy demand change and heatwave frequency) from an ensemble of global and climate and hydrological impact models (ISIMIP). These are combined with novel spatial socioeconomic datasets of population, urbanization, income distribution and wealth projections, to investigate multiple climate impacts on the world’s poorest populations. Using policy relevant scenarios of 1.5°C, 2.0°C and 3.0°C and the 5 SSPs, we identify hotspots of vulnerable populations to climate impacts. This combination of scenarios enables us to decompose the differences between the socioeconomic and climate projections to understand the dominant drivers of vulnerability to multiple climate impacts. Threshold approaches and use of spatial data allows for novel presentation of critical hotspots and how the severity and spatial extents change with time. We then aggregate these results at relevant decision-making scales, such as country- and river basin-level, whilst the multi-model approach enables measures of model uncertainty to be incorporated into the analysis. In the near term, we find that for the majority of locations the difference between 1.5°C and 2.0°C is small and equivalent to (and sometimes outweighed) by uncertainty between different socioeconomic projections. Climate impacts at 3°C are spatially extensive and more severe, impacting larger populations and subsequently more sensitive to socioeconomic projections. The combination of these approaches to identify multi-impact vulnerabilities and multi-sector vulnerabilities not only allows crucial identification of the most critical areas, but paves the way towards joint and cost-effective adaptation across sectors.

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Hydrologic extremes are among the world’s most dangerous and costly natural hazards. Over recent decades, flood losses resulted globally in more than $1 trillion damages whilst making at least 220,000 fatalities. Droughts, on the other hand, can lead to widespread food and water crises. The recent Somalian drought led to more than 700,000 drought related displacements and put over 6.2 million people in need of humanitarian assistance.
Efforts to reduce the risks of such hydrologic extremes are essential and are key for today’s global policy agenda. Compound events - when the combination of two or more hazardous events or climate variables lead to an extreme impact - do not align neatly with traditional categories of extremes or methodologies to assess risk, are have been therefore often overlooked in global policy making. Compound events can have a multiplier effect on the risk to society, the environment and built infrastructure, though. Hence, preparedness to compound events is critical and has been identified as an important challenge by the World Climate Research Programme Grand Challenge on Extremes.
In this contribution we highlight the importance of compound events in water-related risk assessments, using recent real-world examples. Moreover, we discuss the challenges that lie ahead to improve the understanding, the ability to simulate and attribute, and the preparedness for these high impact events.

Co-authors: Gen Sakurai, Shinichiro Fujimori, Kiyoshi Takahashi, Yasuaki Hijioka, Toshihiko Masui

Future climate variability is a concern for food security. Although the uncertainty of food security under the mean climate state has been quantified in numerous studies, variability has rarely been considered. Here, we show how projections of the risk of hunger are affected by potential changes in crop yields under climate variability and other major uncertainties expected to occur by the middle of this century. The results suggest that the magnitude of uncertainty increases over time regardless of socioeconomic developments. In 2050, under a once-per-100-year extreme case under the most severe climate change pathway, an additional 0.07–0.32 billion people will face a risk of hunger, which accounts for 70-80% of the number under the mean climate state. The results also suggest that current global total food storage is quantitatively sufficient, but poorly distributed geographically. For example, a once-per-100-year extreme case under the most severe climate change scenario (RCP8.5) requires 2.2–2.3 EJ of food energy to keep the same consumption level as would be without extreme climates, which is equivalent to one-fourth of the current global cereal storage. However, the current food storage locations do not match the locations where food is needed under the extreme case. To fill this gap, a food aid system among countries or the promotion of food storage in affected regions is needed so that they can tolerate the worst case.

Co-authors: Tobias Conradt, Christoph Gornott, Frank Wechsung

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After having successfully demonstrated the capabilites of spatially distributed yield estimations by multiple regression approaches based on monthly weather data for Germany, Schauberger et al. (2017) recently presented a new study for 33 main producer countries worldwide with two-month yield forecasts additionally making use of remote sensing data (http://dx.doi.org/10.1111/gcb.13738). Out-of-sample performances typically range between one to two thirds of the observed variability, largely depending on the regional weather sensitivity of the crops. Here we present a current real-time forecast implementation of our approach.

Co-author: Luigi Nisini

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Operational crop forecasts are gaining importance in a global climate characterized by increasingly variable weather and with commodity markets that are more interconnected. Forecasting crop yield can help anticipating fluctuations in expected production levels. We assess the quality and intra-seasonal development of common wheat yield forecasts during extreme impacts for 25 European Union (EU) Member States (MS) since 1993 performed by EC-JRC-MARS, evaluating 2450 intra-seasonal forecasts for 362 wheat forecast years. Median yielding years were forecasted accurately and forecast errors were below ~2% by July, while low and high-yielding years were respectively over (~10%) and underestimated (~8%). Forecast accuracy of high yielding years improved during the season as gradual processes beneficial for crop-growth were captured by the system. Four-fifths of the years with the lowest yield at MS level had a drought driver, while a third had a wet driver. In water-limited countries (e.g. Spain, Hungary), low yields due to drought were anticipated with significant lead times (~2 months), but still underestimated. Extreme events affecting yield during the later growing stages remain difficult to forecast. Synoptic weather patterns affecting multiple-countries in 2003, ’06, ’07, ’11 and 12’, led to wheat losses of up to 8.1 Mt. In these years, single events (e.g. drought in Latvia, Lithuania, Poland in 2006), contrasting successive in-season (e.g. dry and wet in Denmark, Estonia, Sweden, in 2011), as well as spatially distant dry and wet (dry in Bulgaria, Hungary, Romania and wet in Belgium, Netherlands, France, in 2007) extremes, contributed >40% to total EU losses. June and end-of-campaign production forecasts in these years underestimated losses respectively by 10.4 to 78.4 and 4.2 to 47.9%.

Co-authors: Mike Rivingon, Keith Matthew, Mike Young, Geoff Squire

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The aim of this paper is to show how a barley yield forecast tool for Scotland is being built. We also highlight the challenge of gathering the input data and the availability of farmers’ data for further calibration/evaluation of the tool. Its planned use will span from a crop yield forecast, to an adaptation and mitigation tool to evaluate the impact of climate change in Scotland. This tool will be further expanded at global level for studying the impact of climate change on global barley production. To identify the barley growing areas the Land Capability Map for Agriculture was used and overlayed with the Scottish Soils Knowledge and Information Base in order to extract only the relevant soil types. The soil database has more than 1,000 soils for the whole Scotland. The soils that occur in the barley growing areas were 333, and these soils were described, for each soil depth to a maximum of 100 cm. Gridded daily weather data were obtained from the United Kingdom Meteorological Office, using the UKCP09: Gridded observation dataset. The Decision Support System for Agrotechnology Transfer (DSSAT) v 4.6 was utilised for modelling spring barley growth across Scotland. The model was calibrated for matching phenology (anthesis and maturity), and grain yield using barley variety trials information. The evaluation of the model was done using observed data from experimental farms, from published results of agronomic trials, from the Scottish Government National Statistics data, and by gathering detailed data from more than 100 farms from a North-South transect.

Co-authors: Frank Wechsung, Dim Coumou

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Analyzing and predicting climate phenomena are usually based on correlations of known climate indices. For example, ENSO indices are used to predict seasonal rainfall and temperatures around the globe. There exist different data driven approaches (e.g. EOF, correlation networks) to identify and improve relevant climate indices but these are usually not considering a response variably of interest. Therefore, previous studies introduced the concept of response-guided community detection. However, these do not account for spurious correlations due to common drivers or auto-correlation and are this limited in their interpretability. Combining response-guided clustering and causal discovery algorithms we overcome these problems and present an approach to objectively identify indices which help to analyze a variable of interest. We apply this method to the predict crop yield in Morocco, which is strongly linked to winter precipitation.

Co-authors: Peter Hoffmann, Katja Frieler

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The economy of Morocco is highly dependent on fluctuations in wheat yield. Since very little of the Moroccan wheat harvest is irrigated, this leaves the annual wheat yield dependent on precipitation fluctuations and large scale weather patterns over the north Atlantic. Here we suggest two predictor systems of the annual change in Moroccan wheat yield based on these relationships. The first, pre-planting indicator relies on the sea surface temperature (SST) anomalies of the north Atlantic in October through November and is reinforced by two mid-season predictors based on the weighted precipitation from October through February and March, respectively. Partial least squares regression is used to determine the three most relevant patterns of Atlantic SST  which offer an early indication of the upcoming wheat yield. The prediction is challenged and enhanced by the inclusion of the cumulative monthly precipitation weighted by the wheat cultivation areas, from October through the wheat harvest. It is not surprising that the total precipitation in Morocco influences the annual wheat yield, however it is remarkable the degree to which SST and early season precipitation sums are able to forecast the national wheat yield.

Co-authors: Wu Bingfang, Zeng Hongwei, Zhang Miao

Crop aboveground biomass (AGB) is an essential parameter for crop yield estimation in the global agriculture remote sensing community. The reliable estimation of crop aboveground biomass (AGB) during the growing season would improve planning, managing grain production, handling the grain, and marketing. Previous research has mainly focused on various vegetation indices (Vis) to estimate crop AGB for large spatial and temporal applications, and these Vis include the normalized difference VI (NDVI), wide dynamic range VI (WDRVI), transformed soil-adjusted VI (TSAVI), enhanced VI (EVI), and SAVI, which rely on multi-band reflectance values with limited angle information. However, multi-angle remote sensing can provide three-dimensional geometric structure information about crops, which is directly related to crop AGB. The surface and volume scattering components of the bidirectional reflectance distribution function (BRDF) shape constitute one of the main multi-angle information sources. Based on its physical definition, the BRDF is thought to be sensitive to dynamic crop geometric structure during all growing stages. Thus, the relationship between new multi-angle-based indices from Moderate Resolution Imaging Spectroradiometer (MODIS) MCD43 BRDF parameter data from different bands and the various field crop AGB was determined at various field sites using highly periodical field observations. The aim was to acquire different geometric factors for correlation with the field crop AGB to find out the appropriate band, crop type and parameter combination manner to estimate crop AGB at a global level. The proposed method will provide new solutions for estimating crop AGB via multi-angle remote sensing and are expected to have potential applications for crop yield monitoring and forecasting. Finally, a preliminary crop yield estimation result based on Biomass-Harvest Index Model will also be provided.

Co-author: Tamara Ben-Ari

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The principle of weather index crop insurance is to pay an indemnity to farmers as a function of some weather index. A pre-selected weather index (I) is used as a proxy for yield loss, and a payout is triggered when the value of I is lower that an index threshold, i.e. the strike (S). The choice of S is critical because its value influences the performance of the insurance system. The use of an inappropriate strike level may lead to a payout in the absence of yield loss, or to an absence of payout in case of yield loss. The first type of error (false positive) increases costs for the insurance company, while the second type of error (false negative) increases the basis risk of farmers. A difficulty is that the optimal value of S may depend both on the chosen weather index and on local characteristics (e.g., soil type, farmers practices). The optimal S value may also vary across time under the influence of climate change. There is thus a need for an operational method able to optimize the strike levels. Here, we describe a statistical method for optimizing the weather index threshold S from yield time series. The principle is to fit a statistical model relating the weather index I to a variable reflecting occurrences/non occurrences of yield loss. The fitted model is then used to compute the probabilities of true positive (payout in case of yield loss) and of true negative (no payout in case of absence of yield loss) across space and time. We show how the computed true positive and negative probabilities can be used to determine optimal values of S. The proposed method is illustrated in several examples involving different type of indices and different crops.

Co-authors: Julien Boé, Philippe Ciais, Rémi Lecerf, Marijin Van Der Velde, David Makowski

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In 2016, French wheat production suffered its most extreme loss in over half a century. In many counties of the French breadbasket, these losses exceeded 50%. France is the first wheat producer in Europe - despite limited agricultural space: the region affected by severe loss in 2016 usually produces as much wheat as Ukraine or Australia.This event, combined with other severe losses in neighboring countries (e.g., Belgium, the UK), thus had repercussions in the European Union and the Mediterranean basin.
Early warning systems failed to anticipate the spread or the magnitude of this event. Yet, there has not been any quantitative study characterizing the precise climatic conditions that led to this extreme yield loss or developing an understanding of why yield forecasts failed by such a large amount in 2016. Our study is dedicated to the understanding of the causes and implications of this extreme yield loss.
During the 2015-2016 growing season, climate was exceptional but it was not a ‘usual’ drought and heat wave known to reduce yields. Rather, 2015-2016 is a unique compound extreme with both very warm conditions in the late fall and record high precipitation in the spring. A statistical model that accounts for these two variables is capable of estimating high risk of yield loss in 2016 together with increased probability of yield losses for other key loss events since 1959. Based on climate projections, we show that the bivariate conditions that led to the 2016 wheat yield loss will become more frequent in the future.
The increased likelihood of such compound event poses a challenge not only for current yields forecasting systems but also for wheat production adaptation pathways in temperate regions.

Co-authors: Laura M. Olivieri, Matthew M. Conley, Katherine M. West, Bernhard Schauberger, Frank Wechsung

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Global climate uncertainty will undoubtedly alter thermal regimes of Earth’s major cereal grain production regions. Because semi-arid desert regions experience the widest range in ambient temperature (-2 to 42°C), intra- and inter-annual variations in temperature provides a cost effective means to assess thermal response of multiple cereal grain crops simultaneously. To refine our understanding and assess Genotype by Environment by Management (GxExM) interactions, we staggered our planting dates, from the normal cropping season in December, to be in closer intervals during the April-June time frame. We used day-neutral cultivars without any vernalization requirement to negate any photoperiod effects and ensure floral induction regardless of planting date. Our objectives were: (1) determine cereal grain crop responses to a wide range of air temperature; (2) quantify crop growth; (3) evaluate and refine thermal response on crop growth and development; (4) validate crop growth models with regard to thermal dependent processes believed to be mediated through canopy energy balance. Our materials of study included: Wheat (Tritium aestivum L.); Durum Wheat (T. durum L.); Barley (Hordeum vulgare L.); and Triticale (xTriticumSecale) WheatxRye. These four crops were planted, in four replicates, over five and eight dates (April to June) during 2016 and 2017, respectively. Hence, differently treated crop responses were assessed across a wide range in air temperature. Preliminary results will be discussed in the context of how they will impact our understanding of global climate uncertainty and how to develop adaptation and mitigation strategies that ensure global food security.

Drawing from experiences gained in recent projects (e.g. EU FP7 MODEXTREME, ERA.net RUS EXTRA), the purpose of this contribution is to review some of these issues and propose ways to improve the situation.

Co-author: Katja Frieler

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Besides agronomic management, local weather conditions largely influence inter-annual yield variability of stable crops throughout many important producer regions, particularly during extreme weather events. While yield losses are associated with important social-economic implications, current global crop models remain with limited capability to predict such year-to-year yield fluctuations. In this study, we show that national observed maize yields - the most important global staple - significantly declined during recent worldwide droughts and extreme heat between 1964 and 2007, on average by 11.9% and 15.5%, respectively. We demonstrate that accounting for geographically explicit observed phenological heat unit requirements (PHU) – which acts as a representation of local crop cultivars – substantially reduces predictive uncertainty in process-based crop growth simulation of inter-annual maize yield variability. We employ one of the leading global agro-hydrological models (LPJmL) and show that compared to the prevailing, spatially invariant PHU approach, the refined model increases explained variance in historic yields from 37.5% to 54.4% averaged across the top 10 producer countries. Above-mentioned yield losses during drought and extreme heat events can now be reproduced accurately via global mechanistic modeling. Our results may therefore help to produce more reliable projections of potential adverse climate change impacts on future crop yields.

[1] Stolbova, V., E. Surovyatkina, B. Bookhagen, and J. Kurths (2016): Tipping elements of the Indian monsoon: Prediction of onset and withdrawal. GRL 43, 1–9 [doi:10.1002/2016GL068392]

As an outcome, it is envisaged to identify opportunities as well as bottlenecks in decision making that prioritizes the needs and demands of vulnerable people.

Co-author: Brenda Mwalukanga

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African cities and towns are growing fast with large proportions of urban populations categorised as poor living and working informally. Urbanisation process in Africa has been occurring without a corresponding industrialisation and infrastructural development. There is urbanisation of poverty and concentration of climate related disaster risks. Further, in African cities, municipal decision making and urban management systems are weak and are based on non-robust climate information and scientific evidence. Thus, many people who work and live informally in African cities are more vulnerable to climate change shocks which in Lusaka typically include floods and droughts. New climate knowledge production methodologies are needed to bridge the gap between climate science and local government policy officials and systems to ensure climate science guides decisions for protecting vulnerable urban residents in African cities. In Lusaka, climate scientists, urban development researchers, decision makers and city residents are collaborating in a transdisciplinary project to ensure increased uptake of climate information in decision making at the city-region scale. The project is called Future Resilience of African Cities and Lands (FRACTAL) where innovative research and learning initiatives are being implemented to ensure a water secure future for all in Lusaka. In this research project, stakeholders have identified water insecurity (urban flooding and water rationing) as a climate change ‘burning issue’ affecting over 60% of residents in Lusaka who live and work in slums. This paper uses discourse analysis to examine how knowledge production innovations in the Fractal project are bridging the gap between climate scientists and development policy actors in the City of Lusaka to ensure development decisions are climate sensitive and inclusive for the next 10-40 years. The paper explores how the project actors are pioneering integrated climate research to ensure Lusaka City Council engages in decision-making processes that safeguard livelihoods and health of vulnerable City residents from climate related shocks in the water sector.

Co-authors: Harald A. Mieg, E. Weber

Inhabitants of Pacific Small Island States (PSIS) are facing multiple socio-ecological pressures, with climate change being one of the most prominent. The resulting alterations affect daily lives and routines as well as future plans of the local population. Nevertheless, the agency of local stakeholders in decisions on how to adapt to climate-related environmental changes has been largely underappreciated in the climate change sciences as well as in policy decisions. We, therefore, conducted a survey study in three representative PSIS (Tuvalu, Samoa, and Tonga), asking specifically how residents perceive their situation regarding climate-related challenges, what adaptation strategies they have devised and implemented, and what they expect of governmental and nongovernmental organizations in these efforts. In contrast to the common perception that PSIS are primarily threatened by rising sea levels, residents’ perceptions indicate that drought, cyclones and other flood-related problems pose a fare more imminent danger. Consequently, current coping strategies of private households involve mainly water management, planting, repairing and preparing houses and private property, waste management, and improving one’s own financial situation. In addition to that, future plans of those affected by flooding and erosion include moving inland and finding land to resettle. People’s expectations of the government and NGOs relate predominantly to funding, technical assistance, supply of materials, raising awareness, the enforcement of policies, as well as providing spiritual and practical support. The results of the study will be discussed in the context of non-economic loss and damage with a specific emphasis on communal sites and meaningful places, ecosystem services, health (including mental health), as well as potential implications for local identity, values, future development, and sustainability. Our findings suggest that further research on the perceived environmental changes as well as resulting local adaptation strategies is advisable to provide reliable data for scientific models and policy decisions.

This contribution presents the preliminary findings of the project in Morocco for the MSME sector and explores how the ECA approach can have a positive impact on all parts of the disaster risk management cycle and assist in bridging between different stakeholders from the public and private sectors.

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Zika, dengue, chikungunya, malaria, Lyme disease, bluetongue, Shmallenberg are vector-borne diseases with huge impacts on societies and they are increasingly mentioned in the news. These diseases are transmitted by exothermic arthropod vectors such as mosquitoes, midges and ticks which are extremely sensitive to external environmental conditions. Rainfall is an important factor as it provides breeding sites for larvae. Temperature impacts a broad range of factors such as vector development, its survival, vector biting rates and the time required for the pathogen to develop inside the arthropod vector. Consequently, anthropogenic climate change is expected to greatly impact the distribution and severity of these vector-borne diseases. This presentation will provide a brief overview of recent modelling studies about climate change impacts on animal and human vector-borne diseases.

Co-authors: Jing Liu-Helmersson, Mikkel Quam, Åke Brännström

Aedes aegypti has become a major public health concern. It is the vector to transmit many viral infectious diseases including dengue fever, yellow fever, chikungunya and zika. Climate change and globalization in travel and trade have made positive impact on the spread of Aedes aegypti mosquitoes to new areas where people have no immunity. It is important for us to know where this vector can establish itself once being introduced. So far, we have limited understanding on the effect of climate on establishment potential of Aedes aegypti for non-tropical areas. This study aims to estimate establishment potential in Europe.
Therefore, we suggest that efforts should be enhanced to reduce the risk of introduction of the vector during the spring and summer seasons.
Methods: Mathematical modelling was used to estimate potential for the vector establishment – growth rate r once they are introduced in a non infected area in Europe. A three-stage compartment model were developed to model the mosquito’s lifecycle - Eggs, Larva, Pupa and Female Adults in relation to variability and trends in meteorological conditions. Vector parameters include influences from rainfall and temperature. Climate change projections were established using the ISIMIP database.
Results: Currently the risk for establishment is limited in Europe - only certain southern European cities and Madeira experience weather conditions that Aedes aegypti can proliferate in already today. With climate change, particularly for high emission scenarios at the end of the 21th century the risk for establishment of the Aedes aegypti increased substantially.
Conclusion: If climate change is not controlled, and as travel and globalization becomes more frequent channels for dengue vector and virus introduction, Europe may face the reality of more frequent dengue outbreaks in areas already at risk and invasion of Aedes aegypti in the south of Europe causing risks of outbreaks of epidemic proportions.

Co-authors: Pham Thi Thanh Nga, Vu Duoc

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The research utilizes geospatial data and applies the WADI approach developed by Dickin et al. (2013) to map change of vulnerability to dengue for 13 provinces in the Mekong delta region (MDR) of Vietnam from 2002 to 2014. A range of datasets for climate variables, land cover, demographics and socio-economics were standardized and integrated into indicators of exposure and susceptibility based on the WADI approach’s existing framework and thresholds. Annual land cover and monthly precipitation were extracted from the MODIS global land cover product and GSMaP data respectively. The Pearson correlation was used to evaluate the associations between dengue rates and vulnerability values aggregated at the province level. Significant linear associations with correlation coefficient greater than 0.5 were found in most of the provinces. The produced maps help in analyzing spatial-temporal dynamic patterns of vulnerability to dengue in the region. From 2002, the vulnerability increased and reached a peak in 2008 with high and very high values observed for all provinces. Nine provinces, where the Mekong River flows through, are more vulnerable to dengue than other provinces.
For the first time in the MDR dynamic maps of vulnerability to dengue are shown to be an effective means of geospatial technology utilization to support local and regional public health authorities in disease control and intervention. The study suggests that changes in environmental, social and climate factors contribute to vulnerability to dengue in the MDR. The result of this study can be accessed at the GIS-based website http://www.apn-climateandhealth.com.

Co-author: Clémence Gatti

Ciguatera fish poisoning (CFP), arising from ciguatoxins (CTXs) produced by harmful algae blooms, is one of the most common food-borne illnesses, with annual incidences up to 500,000 worldwide. The causal toxins, the CTXs, bio-accumulate through the food chain from small herbivorous fish feeding on the coral reefs into larger-sized carnivorous fish that prey upon them. Humans get infected by consuming these contaminated fish, with symptoms such as nausea, vomiting, diarrhea, tingling, and muscle pain, lasting from several hours to several months.
Though once endemic only to small islands in tropical and subtropical areas, ciguatera has increasingly become a global human health issue. Climate change as well as its related events have been commonly hypothesized to lead to a wider presence of harmful algal blooms, hence higher risk of the disease.
Existing studies assessing the relationship between climate change and CFP are very limited. Most of them have failed to control for external factors affecting CFP incidences, such as tourism and international trade. French Polynesia is the most ideal for being selected as a case study because, (1) ciguatera is highly endemic to French Polynesia, with an average incidence rate of 16.5/10,000 people in the last decade, and despite being underreported universally, CFP cases in French Polynesia are more likely to be reported and diagnosed; (2) People consume fish caught locally. This can exclude most external factors mentioned above.
Utilizing the epidemiological data from 2007 to 2016, and climate data obtained from Climate Data Library, we performed a time-series analysis to assess the relationships between the monthly CFP incidence and climate-related indicators including sea surface temperature (SST), precipitation, cyclones, water salinity and El Niño Southern Oscillation (ENSO) events in French Polynesia. Results reveal the significant time-lagged associations between climate variables including SST anomalies, maximum SST, precipitation anomalies and ENSO indices, and the monthly CFP incidence. If this data is confirmed, this delay will allow health authorities and the general public to take appropriate actions, to avoid/limit an epidemic risk, especially on high-risk climate scenarios.
However, the public health impact of CFP is underestimated due to under-reporting, under-diagnosis, and lack of public awareness of the disease. With the burden of climate change, CFP is projected to pose significant threats to more and more previously non-endemic communities. Efforts should be concentrated on monitoring and control at national and international levels, raising awareness about public health implications of CFP, and implementation of food safety risk assessments in affected regions. Moreover, additional long-term prospective studies, relying on complementary disciplines, are needed in order to confirm and complete our findings. They would require a detailed follow-up of meteorological, epidemiological, ecological and sociological data at a global scale.

Co-authors: Luís Costa, Carsten Walther, Boris F. Prahl, Anne Holsten, Jürgen P. Kropp

Assessing the onset of excess mortality from heat is of particular interest for climate impact studies because it allows to infer the temperature above which the capacity of a city’s population to cope with heat is exhausted. Such threshold temperatures for excess mortality are given only sporadically, mostly for cities, on case study basis and usually for present-day climate conditions. This way, it is not feasible to deduce general statements from this location-specific information and it remains unclear at what city-specific temperatures future excess mortality will set in under conditions of climate change. To address these issues we elaborate a statistical model to estimate threshold temperatures for most geographic locations for the present and future climate. Estimated present-day threshold temperatures for more than 600 major European cities cover a range between 11 °C to 30 °C. When applying our model to the future (2051—2080), threshold temperatures are expected to increase in most cities, especially when using climate scenario RCP 8.5. The results for this scenario show extended "hotspot" areas in Southern and Southeastern Europe. For RCP 2.6 in comparison, which complies with the 2°C marker, these hotspot areas are smaller in number and size. Methodologically, our work is based on a meta-analysis of threshold temperatures given by epidemiological studies on heat-related mortality. Multivariate non-linear regression was used to identify relevant independent variables explaining the sample of threshold temperatures. Our work provides a novel and alternative method to derive threshold temperatures for excess mortality that does not require epidemiological records. This method can be applied to present and future climate data.

Co-author: Francesco Sera

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In addition to other indirect pathways, climate change is expected to affect health by varying the exposure to non-optimal outdoor temperatures. However, the empirical quantification of this direct impact involves several methodological issues, which have not been systematically discussed in the literature. Here we provide a critical overview, illustrating practical steps and related methodological problems.
Projections of temperature-related health burdens involve a series of steps. First, researchers need reliable estimates of location-specific exposure-response relationships, commonly obtained from observed data. These relationships are characterized by complex non-linear and delayed patterns, and alternative models can be applied, from simple linear-threshold to complex distributed lag non-linear parameterizations. Alongside, future temperature series must be projected by running climate models under various climate change scenarios. These modelled data must be calibrated with the observed series, and several bias-correction methods are available for this purpose, although little is known on their comparative performance. The health impact can then be projected, although this involves extrapolating the exposure-responses in temperature regions never observed, and separating heat/cold contributions. The associated uncertainty, arising from both exposure-response estimation and climate projections, must be quantified. Projections into the future can also account for adaptation, whose mechanisms are little known, together with demographic trends and other changes. Finally, several summary measures, such as total, heat/cold and net contributions can be defined, and the counterfactual comparisons and related interpretation are not always straightforward.
All these methodological problems, together with assumptions and limitations of alternative approaches, will be illustrated and discussed through explanatory examples of single and multi-city analyses, using data from London and from other locations in different regions of the world, respectively.
This overview will contribute to the definition of a structured methodological framework for projecting temperature-related health impacts under climate change, also clarifying limitations and future research directions.

Co-authors: David M. Hondula, Aditi Bunker, Dolores Ibarreta, Junguo Liu, Xinxin Zhang, Rainer Sauerborn

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Past climate change impact studies for temperature-related mortality have employed different methods to model statistically the potential for populations to adapt to a warming climate. The application of different methods makes it difficult to compare projections across studies because vastly different underlying assumptions are made about adaptation in each respective study. Here we address the longstanding requirement for a comprehensive and systematic comparison of the sensitivity of impacts to each adaptation modelling method. Furthermore, we quantify the relative sensitivity of heat-related mortality impacts to three key sources of uncertainty: climate model uncertainty, emissions uncertainty and “adaptation uncertainty” (i.e. the inclusion/exclusion of adaptation modelling). We compare the effect of employing six different statistical adaptation modelling methods on projected impacts in 2070-2099, for 14 European cities. The methods compared include shifting the threshold temperature, reducing the gradient of the exposure-response function, a combination of the previous two, and the analogue city method. Heat-related mortality impacts are estimated with climate projections from five climate models, run under two emissions scenarios to explore the relative effects of climate modelling and emissions uncertainty. An important finding that contextualises the results from previous studies, particularly those that have not considered adaptation, is that adaptation can be a greater source of uncertainty than emissions and climate modelling uncertainty. Moreover, the inclusion/exclusion of modelling adaptation significantly affects the impact estimates. The range of the difference (%) in impacts between including and excluding adaptation, irrespective of climate modelling and emissions uncertainty, can be as low as 28% with one method and up to 103% with another (mean across 14 cities). Thus we recommend that future assessments account for adaptation uncertainty in their approach. Furthermore, more evidence should be generated on the costs and effectiveness of the array of practical adaptation mechanisms that underlie the modelling assumptions we applied.

Co-authors: Kayo Ueda, Yasushi Honda

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The impact of heat on mortality has been well documented, particularly in temperate and subtropical areas, which were observed to manifest acutely. Further evidence have shown that these acute heat effects were also evident in tropical areas. However, there is little understanding of the future consequences of heat effects, with reference to a no-adaptation scenario, particularly in tropical low and middle-income countries. This study intends to 1) estimate the baseline risk coefficient, and further 2) estimate the excess mortality and life year lost due to heat. Daily mortality and meteorological data (both from 2006-2011), as well as the baseline mortality, population projection (2030 and 2045), were collected from the respective Philippine agencies. We used a two-stage analysis to estimate the baseline risk coefficient: city-level risk-estimates were analyzed using a distributed lag non-linear model, and the risks estimated from the first stage was then pooled via meta-analytical techniques. Excess mortality as well as life years lost were calculated based on a no-adaptation assumption, subject to different increments in the annual average temperature with reference to the baseline risk, and the baseline threshold. Heat risk coefficient from the pooled analysis was estimated to be at 0.1457 per 1℃ increase. While excess mortality under non-adaptation, with 2℃ increase in annual average temperature resulted to 132,378 and 150,077 excess deaths in 2030 and 2045, respectively. Years life lost were also magnified at 47,964,647 life years lost and 54,377,511 life years lost, in both 2030 and 2045, respectively. Non-adaptation to the increasing temperature, particularly in a tropical setting, exposes the population to greater risks, which thereby strengthens the need to evaluate the possible current and future means of adaptation in order to address the future risk gaps.

Co-authors: Ana M. Vicedo-Cabrera, Christian Schindler, Martin Röösli

Designing effective public health strategies to prevent adverse health effect of hot weather is crucial in the context of global warming. The 2003 heat wave caused an estimated 7% increase in all-cause mortality. Consequently, the Swiss Federal Office of Public Health developed an information campaign to raise public awareness on heat threats and health authorities in some Swiss Cantons developed additional heat warning systems (HWS).
To explore the effectiveness in reducing temperature-related impacts of the public health measures in Switzerland, we assessed a) the variation of heat effect on daily mortality for the time periods 1995-2002 and 2004-2013, and b) the excess mortality during summer 2015 which was the second warmest summer for 150 years after 2003.
We firstly performed conditional quasi-Poisson regression with non-linear distributed lag models to estimate temperature-mortality associations in the two periods. Daily age group-, gender- and region-specific all-cause excess mortality during summer (June–August) 2015 was estimated based on predictions derived from quasi-Poisson regression models fitted to the daily mortality data for the 10 previous years.
Relative mortality risk at 32°C compared to 21°C dropped from 1.13 (95% confidence interval [CI] 1.02-1.25) in the time period 1995-2002 to 1.09 (1.00-1.18) in the more recent time period. For summer 2015, 804 excess deaths (5.4%, 95% CI 3.0-7.9%) were estimated. Temperature-adjusted analyses showed that in French speaking Cantons with HWS the excess mortality tended to be lower than expected.
Although we observed a non-significant reduction in the effect of high temperatures on mortality in the time period after 2003, estimates of excess mortality for 2015 were only a little lower compared to those of summer 2003. Cantons with HWS could reduce heat-related mortality, but high temperatures continue to be a considerable risk factor for human health in Switzerland.

Co-authors: Mark Rosegrant, Daniel Mason-D’Croz, Timothy B. Sulser, Athanasios Petsakos, Anne Terheggen, Gideon Kruseman, Tri Setiyono, Nhuong Tran, Subir Bairagi

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Global population will exceed nine billion people by 2050 and, together with rapid income growth and urbanization, will have profound effects on diets and on patterns of agricultural production. These include increased consumption of sugar, fats, and oils; growing demand for fruits and vegetables; and rapid growth in meat consumption and associated demand for livestock feeds. Sustainable food production growth also faces challenges from climate change as well as constraints on land and water resources and weakness in value chains.
Together with colleagues from across the CGIAR, we recently analyzed a broad range of scenarios to explore the impacts of alternative agricultural and rural investments to meet these challenges in the coming decades. Results provide a quantitative assessment of the impacts of alternative investment options on Sustainable Development Goals relating to poverty, food and nutrition security, and natural resources and ecosystem services, in the context of changes in population, income, technology, and climate to 2030 and 2050.
We find that scenarios which increase investment in agricultural research to enhance productivity generally offer moderate improvements in income, agricultural supply, and food security, with little impact on environmental improvement by 2030, but larger improvements by 2050, at relatively low cost. A scenario combining irrigation expansion and increased water use efficiency offers reductions in water use and small improvements in income, supply, and food security. Improved market access through investment in infrastructure to reduce marketing costs increases income, supply, and food security, but at the cost of increased conversion of forestland and greenhouse gas emissions. By contrast, a mixed portfolio of investments that combines productivity enhancement with improved resource management and market access achieves significant improvements in all outcome areas, particularly in 2050, but comes at a significantly higher cost.
These tradeoffs highlight the importance of integrated multidisciplinary analysis of the multiple goals and constraints facing decision makers at various scales. An ongoing process of dialogue with those decision makers will be essential to improve both the analysis and its value in informing policy to achieve the SDGs.

Co-authors: Jessica Bogard, Keith Lividini, Joanne Arsenault, Malcolm Riley, Timothy Sulser, Daniel Mason-D’Croz, Brendan Power, David Gustafson, Mario Herrero, Keith Wiebe, Karen Cooper, Roseline Remans, Mark Rosegrant

Research to quantify the challenges of feeding the world has focused almost exclusively on dietary energy; much less on nutrition security, especially from a whole diet perspective. Using modeling that compares effects of socioeconomic and climate change futures on nutrient availability, affordability, adequacy and diversity to 2050, this presentation includes results from a two-year research project that compares the effects of climate change and income growth on nutrient security. Results for all principal macro- and micronutrients are included.
Key messages from the research are:
First, the benefits of widely shared economic growth are much stronger than the modelled negative effects of climate change; policies that support economic growth with more even income distribution are essential now while preparing for the coming consequences of climate change.
Second, average macronutrient availability is more than adequate now and to 2050, but low availability of some micronutrients is widespread and some nutrients with negative health effects are likely to become more available. Agricultural research priorities and agricultural policy should put increased emphasis on addressing micronutrient shortages and reducing the availability of nutrients with negative health consequences.
Finally, climate change alters availability of some nutrients in some regions more than others. Efforts to increase affordability and availability of micronutrient-rich foods must be tailored to regional conditions.

Co-authors: Daniel Mason-D'Croz, Sherman Robinson, Keith Wiebe, Charles Godfray, Mike Rayner, Peter Scarborough

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The projected rise in food-related greenhouse gas emissions could seriously impede efforts to limit global warming to acceptable levels. Despite that, food production and consumption have long been excluded from climate policies, in part due to concerns about the potential impact on food security. Using a coupled agriculture and health modelling framework, we show that the global climate change mitigation potential of emissions pricing of food commodities could be substantial, and that levying greenhouse gas taxes on food commodities could, if appropriately designed, be a health-promoting climate policy in high-income countries, as well as in most low and middle-income countries. Sparing food groups known to be beneficial for health from taxation, selectively compensating for income losses associated with tax-related price increases, and using a portion of tax revenues for health promotion, are potential policy options that could help avert most of the negative health impacts experienced by vulnerable groups, whilst still promoting changes towards diets which are more environmentally sustainable.

Co-authors: Christofer Åström, Camilla Andersson, Tanel Tamm, Kristie Ebi, Bertil Forsberg

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Ozone is a highly oxidative pollutant, associated with increased mortality. All else (e.g. ozone precursors) being equal, summertime ground-level ozone will increase as temperatures increase with climate change. As a part of the ACCEPTED project we used greenhouse gas and ozone precursor emission scenarios, global and regional climate and chemistry-transport models, epidemiological data and population projections to assess ozone- and heat-related health risks under a changing climate.
European ozone concentrations were modelled at a grid size of 50x50 km using MATCH. Climate projections from the regional climate model RCA4 were used. For the surface ozone and temperatures, the global climate model EC-EARTH was used as input for the regional climate model, forced by the greenhouse gas emission scenario RCP4.5. Two periods were compared: the current climate as 1991-2000 and future climate as 2046–2055. The impacts on long- and short-term mortality due to ozone exposure and heat related premature deaths in Europe were calculated.
Currently long-term exposure to ozone causes annually around 55,000 premature deaths in Europe, of which around 26,000 deaths are expected due to short-term effects. When only taking into account the impact of changing climate on surface ozone, up to 11% increase in ozone-associated mortality is expected in some countries in Central- and Southern-Europe. However, projected decrease in ozone precursor emissions will cause much larger decrease in surface ozone (29.5% as EU average). Due to aging and increasing susceptible populations, the decrease in 2050 would be actually smaller, up to 24.2%. During summer months, ozone risks will combine with increasing temperatures, especially during hottest periods and in densely populated urban areas. While the heat burden is currently of the same order of magnitude as ozone, due to increasing temperatures and decreasing ozone precursor emission, the difference will be twice as large in 2050.
Climate and emission changes will substantially affect ozone and temperature related mortality and the ratio between them in the middle of this century in Europe.

Co-authors: Toon Vandyck, Bert Saveyn, Mike Holland, Joseph Spadaro, Kimon Keramidas, Alban Kitous

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The objective to "prevent dangerous anthropogenic interference with the climate system" (United Nations Framework Convention on Climate Change, 1992) has been pivotal in the international debate on climate change over the past decades. Where climate policies are implemented by nations for universal benefit, the co-benefits in terms of local improvements in air quality, that are sometimes overlooked, can provide a convincing complementary rationale for ambitious climate action – in particular in rapidly urbanising and industrialising regions where air quality may be severely compromised.
Here we show that the transformation of the energy system implied by individual national emission reduction pledges made in the context of the Paris Agreement on climate change (the Intended Nationally Determined Contributions or INDCs) contribute significantly to lower concentration levels of local air pollutants across the globe. We evaluate the co-benefits of climate action under 3 scenarios for air quality control: (1) emission control measures frozen at the level of 2010; (2) continued implementation of currently programmed air quality legislation; (3) implementation of maximal technically feasible measures.
As such, the INDCs could reduce the number of air-pollution induced premature deaths by 130'000 – 267'000 in 2030, compared to a reference scenario without additional climate action. Further strengthening the ambition of climate change mitigation policies to limit global warming to 2°C by the end of the century raises the avoided mortality estimate to 1.5 – 4.3 million in 2050. Moreover, accounting for the benefits of improved air quality on health and agriculture substantially reduces the cost of climate change mitigation policies. These results illustrate that discussions on climate change policy risk being framed from too narrow a perspective if co-benefits for air quality are neglected.

Co-authors: Shinichiro Fujimori, Kiyoshi Takahashi, Tokuta Yokohata, Toshihiko Masui

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This study quantified the impacts of climate change on human health through undernourishment using two economic measures. First, changes in morbidity and mortality due to nine diseases caused by being underweight as a child were analyzed using a Computable General Equilibrium (CGE) model with changes in the labor force, population, and demands for healthcare taken into consideration. Second, changes in mortality were taken from the CGE simulation and assessed economically by the value of lives lost and willingness to pay to reduce the risk. Model uncertainties in future crop yields, climate conditions, and socioeconomic conditions were considered using future projections from six global crop models and five global climate models and assuming multiple socioeconomic conditions. We found that the economic valuation of healthy lives lost due to undernourishment under climate change was equivalent to -0.4% to 0.0% of global gross domestic product (GDP) and was regionally heterogeneous, ranging from -4.0% to 0.0% of regional GDP in 2100. In contrast, the actual economic losses associated with the effects of additional health expenditure and the decrease in the labor force due to undernourishment resulting from climate change corresponded to a -0.1% to 0.0% change in GDP and a -0.2% to 0.0% change in household consumption, respectively, at the global level. These impacts can be avoided by achieving the stringent mitigation in the context of the Paris Agreement.

Co-authors: Yuming Guo, Francesco Sera, Veronika Huber, Clare Heaviside, Dann Mitchell, Andy Haines, Ben Armstrong, Kristie Ebi, Antonio Gasparrini; on behalf of the MCC Collaborative Research Network

Background/Aim: The recent international agreement reached in Paris aims at keeping the increase in global mean temperature (GMT) below 2°C, and it pursues efforts to limit it below 1.5°C. Here we provide evidence on temperature-related direct mortality impacts under these and more extreme climate change scenarios, using a worldwide multi-country dataset.

Methods: Two-stage time series analysis using distributed lag non-linear models and multivariate meta-analysis to estimate temperature-mortality relationships for 451 locations within 23 countries in 1985-2012. Future impacts, quantified as attributable risks for non-optimal temperature and for cold and heat separately, were computed under scenarios consistent with 1.5°C, 2°C, 3°C, and 4°C increase in GMT, defined by corresponding 20-year windows identified in temperature series projected along the 21st century using four global climate models.

Results: Across different regions of the world, a rise from 1.5°C to 2°C in GMT would generate 0.20%-1.38% increases in heat-related and 0.30%-0.73% decreases in cold-related mortality. Mild temperate areas such as North Europe, East Asia and Australia would experience a small net decrease (0.29%, 0.31% and 0.47%, respectively), while hotter places such as South Europe and South-East Asia would face a larger significant net increase (0.69% and 0.72%). Changes are close to null in areas characterized by diverse climatic conditions, such North America and Central Europe. More extreme scenarios with GMT rising to 3°C-4°C would present more dramatic heat-related impacts, especially in hotter places, with net increases up to 7.07% in some tropical areas.

Conclusions: This large worldwide assessment provides evidence of potential health benefits of enforcing mitigation strategies to reduce global warming. Compliance with the limits set by the Paris Agreement (2°C) would prevent dramatic increases in mortality projected in many regions, while more ambitious targets (1.5°C) would be beneficial for hotter tropical areas where a large proportion of world population lives.

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Background/Aim: Significant reductions in greenhouse gas emissions beyond the Nationally Determined Commitments coming out of the 2015 Paris Climate Agreement are required to avoid warming of 2°C above pre-industrial temperatures. Ancillary health benefits represent selected near term, positive consequences of climate policies that can offset mitigation costs in the short term, before the benefits of those policies on the magnitude of climate change are evident. 

Methods: We evaluated the range of methods and choices in modeling the health co-benefits of climate mitigation to identify opportunities for increased consistency and collaboration to better inform policy-making. We reviewed 40 studies quantifying the health co-benefits of climate change mitigation: (1) reducing the concentrations of ambient fine particulate matter (PM2.5) and secondary pollutants such as ozone; (2) increasing active transport; and (3) sustainable dietary changes, published since the 2009 Lancet Commission “Managing the health effects of climate change”. We documented approaches, methods chosen, scenarios, health-related exposures and health outcomes

Results: Air quality, transportation, and diet scenarios ranged from specific policy proposals to hypothetical scenarios, and from global recommendations to stakeholder-informed local guidance. Geographic and temporal scope as well as validity of scenarios determines policy relevance. More recent studies tended to have more sophisticated methods to address complexity in the relevant policy system.

Conclusions: Mitigation could improve health in the shorter term even as reduced emissions decrease the risks of climate change later in the century. Health co-benefits from mitigation policies in other areas are likely, with further exploration warranted to better estimate the full range of possible benefits for a basket of mitigation policies and technologies.

Co-authors: Helena Ting, Tim Swanson

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In countries where rainfed agriculture constitutes a significant portion of household livelihood, increased weather variability represents a source of vulnerability to stable consumption, food security and household well-being. Weather induced income changes affect household
consumption and saving decisions. We evaluate saving and consumption responses to weather variation in South Africa, leveraging a newly available panel of nationally representative households covering the period from 2008 to 2014 and long term climate data. We test our data
against predictions of the standard rational consumption model and some of its main extensions (i.e., precautionary saving and myopic consumption). Furthermore, we evaluate the impact of saving on household life satisfaction and health behavior. In accordance with previous literature, we find that households save in response to both transitory and permanent income change, although the proportion saved from transitory income is significantly higher. We find signs of precautionary saving driven by non-agriculture households, while we find stronger evidences of myopic consumption for agriculture households. In addition, we show that a one-unit increase in log-saving from transitory income increases the odds of a unit increase in self-reported life satisfaction of the household head by 14%, and a one unit increase in log-saving from permanent
income leads to a 6% increase in hazard ratio of having taken an HIV test. This latter result may indicate that preventative health behavior such as HIV testing requires a stronger inducement than a transitory injection of income. Further research is needed to identify the mechanisms by which saving affect life satisfaction and health seeking behavior in developing countries

Co-author: Ian S. Wing

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We use a non-parametric analysis on a city-by-week level dataset between 1970 and 2010 for 122 cities in the US to investigate the impact of temperature and specific humidity on influenza mortality. Furthermore, in order to determine the future impact of climate change on influenza mortality, we provide bias corrected projections under RCP 4.5 and RCP 8.5 scenarios for two time epochs of the 21st century (2026-2045 and 2081-2100). The climatic data comes from the GLDAS (Rodell et al., 2004), while weekly influenza mortality data was taken from the Morbidity and Mortality Weekly Report of the CDC. We utilize generalized additive and include location (city) and time (year and week) fixed effects to control for unobserved heterogeneity, thus we are measuring the excess mortality above the all-city long-run average rate for each week. For the projections, we use data from three GCMs; GISS-ER-2 3, CNRM-CM5, and NorESM1-M. We find robust non-linear effects of both temperature and specific humidity on influenza mortality rates in the U.S. We find that the risk of influenza mortality is positive between −30℃ and 5℃ but the risk becomes negative between temperature range of 5℃ and 25℃, and the effect of humidity is highest between specific humidity levels of 4 g/kg and 12 g/kg (equivalent to Relative Humidity of 20% and 35%). Our projection results suggest that the West, Midwest, and Southeastern US are at high risk of increase in per capita influenza mortality due to climate change - up to 3% by the end of the 21st century.

Co-authors: Simon Lloyd, Andy Haines

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Co-authors: Stefan Fronzek, Kirsi Mäkinen, Reija Ruuhela, Emma Terämä

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In Finland there has been less research into impacts of climate change on human health than in many other parts of Europe. However, changes in climate, combined with societal trends such as aging, urbanisation and lifestyle changes, are expected to have impacts there as well. Some impacts are likely to be positive, including a reduced burden of mortality and morbidity with less severe winters. However, there are also potential risks, including: high summer temperatures, microbial water contamination, altered air quality due to pollutants and allergenic pollen, tick-borne diseases, and moisture damage and indoor air problems in buildings.
Here, we illustrate ongoing work to assess climate-related risks to human health in Finland. We also outline the institutional and policy context in which climate change impacts and adaptation are being addressed. The two aspects are inextricably linked and both face significant challenges.

We focus on three related methodological challenges for assessing impacts and risks:
• Examining alternative approaches for modelling heat-related mortality in Finland
• Development of national scenarios for health and well-being within the RCP-SSP framework
• Risk mapping of exposure, social vulnerability and climate-related hazards, building on earlier work presented at Impacts World 2013.

Institutionally, barriers to progress in preparing for climate change include lack of awareness and complacency among some decision makers and unclear responsibilities. There has also been an absence of systematic and authoritative research, including economic assessment, to analyse and prioritise the potential risks or to identify adaptation measures. This calls for active and co-ordinated participation of all the major public health institutions along with researchers from other disciplines and including the private sector. Currently, funding is devoted to other pressing research priorities, notably a major re-structuring of national health services. Although health forms a component of Finland’s National Climate Change Adaptation Plan 2022, there is little indication that adaptation has yet been accounted for in this re-structuring.

Co-author: Paul Watkiss

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Health impacts of climate change have – to date – been estimated primarily at global and national scales, with little analysis undertaken at the scale most resonant for individual organisations. However, as the rationale for impact analysis extends beyond awareness-raising and towards a necessary input into adaptation decision-making, the need to tailor analysis to individual organisations is increasingly recognised. This paper provides a demonstration as to how an organisation – in this case, a public health provider in the UK - might wish to consider climate change impacts and their effect on its operations.
We analyse the climate change health risks that are likely to be material to the Bristol Health Partnership (BHP). BHP is interested in climate change health risks for two broad but related reasons: health risks to the general public and the subsequent impact on the demand for treatment from BHP health provision services, and risks to those services including to buildings and its workforce. Primary risks considered are those from increased frequency of flooding and extreme heat events. We quantify these risks and express these risks in monetary terms. We generate our estimates using a bottom-up method that adopts down-scaled climate scenarios, (UKCP09), projected city-level demographic data, epidemiological data derived from historical analogues, and monetary values using appropriate transfer methods. Climate risk costs are disaggregated BY cost of treatment, cost of lost productivity and pain and suffering – the latter estimated using survey data. We use ranges to capture uncertainties.
Total annual costs of flooding and heat are projected to increase by 40% (central estimate) by 2040. Approximately 50% of these costs are attributed to the financial components, the other 50% to pain and suffering. The results highlight the potential scale of resource implications for the BHP, which is consequently up-dating its risk register and developing an adaptation plan.

Co-authors: Nick Watts & the Lancet Count Down Team

The Lancet Countdown 2030: tracking progress on health and climate change is an international, multidisciplinary research collaboration between academic institutions and practitioners across the world. It follows on from the work of the 2015 Lancet Commission, which concluded that the response to climate change could be “the greatest global health opportunity of the 21st century”. The Lancet Countdown aims to track the health impacts of climate hazards; health resilience and adaptation; health co-benefits of climate change mitigation; economics and finance; and political and broader engagement. These focus areas form the five thematic working groups of the Lancet Countdown and represent different aspects of the complex association between health and climate change. These thematic groups provide indicators for a global overview of health and climate change; national case studies highlighting countries leading the way or going against the trend; and engagement with a range of stakeholders. The Lancet Countdown ultimately aims to continue its annual reports across these five working groups. This paper outlines the scope of indicators and indicator domains being or to be tracked by the collaboration. The 2017 Lancet Count Down report will be published in the fall 2017. The current indicator domains require further refinement, and mark the beginning of an ongoing consultation process to develop these domains, identify key areas not currently covered, and change indicators where necessary. This collaboration will actively seek to engage with existing monitoring processes, such as the UN Sustainable Development Goals and WHO's climate and health country profiles. The indicators will also evolve over time through ongoing collaboration with experts and a range of stakeholders, and be dependent on the emergence of new evidence and knowledge. During the course of its work, the Lancet Countdown will adopt a collaborative and iterative process, which aims to complement existing initiatives, welcome engagement with new partners, and be open to developing new research projects on health and climate change.

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There is growing recognition that climate change has the potential to trigger social ‘tipping points’, potentially involving abrupt (i.e. non-linear) increases in climate damages, even under smooth (i.e. linear) climate change. Whilst the notion of a ‘tipping point’ originated in the social sciences, in the last decade or so it has been widely used by climate scientists, referring in particular to strongly self-amplifying (positive feedback) dynamics in parts of the climate system [sensu Lenton et al. 2008]. We argue that reinvigorating the concept of social tipping points has considerable potential to help researchers understand the social impacts of climate change and consider their human consequences. Whilst feedback dynamics can also be important in social systems, here we review a broader phenomenology of social ‘tipping points’ that could give rise to abrupt changes e.g. in climate damages. We focus in particular on migration dynamics as the original example of ‘social tipping’ which can also be affected by climate change. We include the potential for the perception of climate change (as well as the actual experience of it) to trigger ‘social tipping’. We note how a lack of system resilience can increase the likelihood and magnitude of ‘social tipping’ driven by climate change, and scope out the potential for early warning signals of particular types of social tipping. We argue that in the developing world at least there is potential for social tipping points to be triggered by climate change long before potential climate tipping points unfold. Looking ahead, the application of network theory methods to social data provides a rapidly expanding opportunity to monitor and in some cases forewarn of social tipping.

At a most basic level, it is environmental factors (e.g. geomorphology, resources, climatic conditions) which determine a population’s ability and desire to remain in a given place. Economic opportunity also plays a pivotal role. However, in a European context, it is arguably governance and particularly cultural factors - including values, identity, traditions and risk-perception - which have the strongest influence on the decision to leave or remain in the face of coastal risks. This presentation explores the interplay between these different factors, supported by findings from over 150 interviews conducted with stakeholders in 10 coastal zones across Europe as part of the EU-funded RISC-KIT project.

Co-authors: William Neil Adger; Colette Mortreux, Samuel Codjoe, Tasneem Siddiqui,
Sugata Hazra

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Efforts to identify the role of environmental risks in migration and population movements have concentrated on exposure to risks at various temporal and spatial scales. Yet previous studies have shown that migration decisions involve multiple interacting factors with underlying drivers all of which are differentially sensitive to environmental changes and risks. Paradoxically environmental factors are consistently not perceived by migrants as the principal or even secondary reason for undertaking their individual movements. Here we propose that perceptions of environmental risk affect migration-decision-making through specific mechanisms such as affecting perceived future security, perceived risk of income decline, perceived well-being and perceived place attachment. We test these propositions by using data from a structured survey of households engaged in migration at varying levels of intensity in areas with established out-migration flows and stratified by level of exposure to environmental risks. The data are from low-lying coastal areas in four deltas across three countries, Ghana, Bangladesh and India and include variables capturing migration behaviour, migration intentions, and perceptions of place, well-being and risks. The analysis shows that while only a small proportion of households perceive environmental risks as the principal reason for migration, perceptions of insecurity caused by environmental factors directly correlate with observed migration behaviour. Furthermore, migration decisions are affected by perceived levels of well-being and life satisfaction, and distinctive levels of attachment to place of origin. Hence the analysis demonstrates that perceived environmental risks create the circumstances and move populations towards thresholds where migration is perceived as a feasible response to external stressors. The results reveal the role of future expected utility in migration decision-making and show that perceptions of environmental risks are a significant factor in the overall sustainability of migration flows from source areas.

Co-authors: Rukhsana Gazi, Mofizur Rahman, Peter Kim Streatfield

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According to the Germanwatch Global Climate Risk Index 2017, Bangladesh is ranked as the 6th most affected country due to extreme weather events. The low-lying coast along with its geographic location makes Bangladesh vulnerable to a number of natural disasters – flood, tropical cyclones, storm surges – some of which are projected to intensify due to climate change. Natural disasters along with rising sea levels – another feature of climate change – are projected to be a major reason for migration from coastal regions in coming years.
Using data from the 2013 Urban Health Survey (UHS) we explored whether environmental factors plays a major role in rural to urban migration at present. UHS confirms that many migrants from environmentally vulnerable regions end up in urban slums (20% Dhaka slum dwellers are from Barisal) but those migrants do not report that they migrated for environmental reasons. Only about four percent of migrants in City Corporation slums cited environment related factors as the primary reason for migration.
We then went deeper to understand the underlying process of migration of climate affected families by in-depth interviews of 20 males who had migrated in recent past in City Corporation slums and identified through the UHS. What appears to be happening is that there are many environmental events occurring in these coastal villages - rising sea levels and flooding, river erosion, and cyclones, which damage agricultural lands reducing crop yields and also fishing yields, with negative impacts on livelihoods. So while these factors may have pushed the male migrants into poverty, they are not seen as the proximate forces triggering migration. Rather the loss of livelihoods is reported as the driving force of the rural to urban migration. This raises a question about how to construct survey questions which can determine the true impact of environmental change on migration.

Co-authors: R.J. Nicholls, H. Adams, R.S. De Campos, M. Abu, S. Das, M. H. Rocky

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Delta environments in low and mid latitudes provide home for more than 500 million people world-wide. They provide fertile lands and have food security importance due to their intensive agriculture activities. At the same time, they are under pressure from multiple drivers: climate and environmental changes (sea-level rise, soil salinization, erosion, etc.) and socioeconomic factors (high population density, intensive land use). People’s livelihoods and wellbeing are at stake when conditions deteriorate and hazards become more frequent and it has been hypothesised that widespread migration may result, especially due to sea-level rise. However, significant migration is already happening for economic, education and other reasons (e.g. livelihood change, marriage, planned relocation, etc.) so environmental-induced migration needs to be placed in context.
The Deltas, Vulnerability & Climate Change: Migration & Adaptation (DECCMA) project analyses migration as part of the suite of adaptation options in three delta regions: the Ganges delta (Bangladesh/India), the Mahanadi delta (India) and the Volta delta (Ghana). One of its objectives is to develop an integrated assessment framework and model that assesses the impact of climate and environmental change, economics and governance on migration in these areas. The presentation introduces the overall integration concept and describes the household decision-making component in detail. This component is based on a detailed household survey from delta migrant sending and receiving areas. In the presentation we describe the insights gained from the analysis of survey data, the resulting model structure, and contrast the model sensitivities across the three study areas. This will illustrate some key causal relationships between changes in the environment, livelihoods and migration decision. The outputs of the integrative modelling will be used evaluate the simulated environmental, social and economic changes in policy relevant ways including the benefits and disadvantages of migration as an adaptation option.

Co-author: Daniel Lincke

Coastal flooding due to extreme sea-level events (storm surges, tropical cyclones, etc.) is currently one of the major threats to coastal settlements and, due to sea-level rise, flood risk is expected to further increase significantly over the 21st century. Despite this, coastal floodplains throughout the world are currently experiencing rapidly increasing flood exposure due to socio-economic development, coast-ward migration and urbanization. This raises the question whether coastal societies will manage to reduce flood risks and losses by either protecting the increasing exposure against rising sea-levels or by migrating away from the coastline.
This paper explores this question from the perspective of economic robustness of adaptation decisions during the 21st century. Using the DIVA framework, we assess global consequences of different plausible pathways of coastal protection and migration decisions under sea-level rise. Pathways are generated by applying a robust decision making approach at subnational levels to identify pathways that have high benefit-cost ratios under a full range of sea-level rise, socio-economic development and discount rate uncertainty. Results are presented at national and global scales in terms of people affected by flooding and migration, as well as adaptation cost and residual flood damage cost.
We find that without considering migration away from the coast, it is economically robust to protect 84% of the world's coastal population during the 21st century. Introducing migration as a further option shifts the economically robust global adaptation response significantly towards less protection, implying that a large number of people living in rural and less densely populated coastal areas would need to migrate away from the coast. These results suggest that we are likely to see increasing coastal inequality with urban and densely populated areas being protected and rural, less densely populated areas suffering from flood damages and eventually having to retreat from the coast.

However, these categories are often a poor conceptual fit with mobilities in the context of climate change, where the lines between forced and more-or-less voluntary movements are exceedingly blurry. Convoluted attempts to shoehorn policy discourse into these established categories therefore stand in the way of coherent policy contributions, whilst at the same time being required in order to be considered as ‘policy relevant’. Based on an analysis of 150 policymaking documents from 2010-2015, this article argues that whilst the distinct categories of displacement and migration continue to dominate the policymaking discourse on climate change and human mobility, a different conceptual categorisation is implicitly being used based around the concept of potentiality. Three categories - actualised mobility, potential mobility, and immobility - can be traced in this discourse. This article analyses these alternative categories and explores whether shunning established in favour of policy irrelevant research could lead to a more coherent and analytically precise understanding of human mobilities in the context of climate change with more transformative potential for policymaking.

Co-author: Matthias Kalkuhl

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Current empirical research on environmental migration primarily utilizes reduced form models and focuses on the direct effects of environmental shocks. The mechanisms, through which these shocks affect migration remain, however, locked in a black box. In this study we open the box and examine the direct and the indirect impacts of environmental (co-variate) shocks on human migration. Using representative data on households in rural India from both rounds (2004-05 and 2011-12) of the Indian Human Development Survey, cross-sectional analyses are conducted applying two logit models. The first model analyzes the relation between environment
and migration (direct effect). The second model employs interaction terms to examine the sensitivity of migration drivers, identified within the theory, to environmental shocks (indirect effects). This study also serves as the first nationally representative study on environmental migration in India at a micro-level. The results provide robust evidence that environmental shocks drive migration. Supporting the Todaro's theory, the
outcomes further reveal that the expected wage gain is positively correlated with migration. This mechanism only works in areas not affected by a co-variate shock. We find evidence for predictions of the NELM that informal insurance does not work in the presence of co-variate shocks and migration is adopted as an insurance strategy. Moreover, relative deprivation drives migration and its effect becomes weaker in the presence of co-variate shocks. With respect to the Human Capital Migration Theory and the Network Theory, we find evidence that mechanisms that decrease or increase costs of migration drive or reduce migration respectively. These mechanisms function also in the presence of co-variate shocks. The study also explores different future scenarios. One of the findings is that if all villages were affected by a co-variate shock, rural-urban migration would increase by up to 10.57 million migrants.

This presentation provides some ideas on how ABM’s can be used for simulating migration decisions in the context of environmental change. First ideas about the development of a stylized model will be presented. Other than case-study specific models, stylized models allows for applicability in various settings rather than being restricted to one specific case. Opportunities and challenges for transferring insights on migration processes from one location to another, based on a stylized ABM, will be discussed.

Co-authors: Kathleen Hermans, Ralf Seppelt

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Local case studies have proven to be an effective instrument to investigate adaptation behaviour of different population groups in the context of environmental and climate change, including migration. The knowledge generated by case studies is crucial for the strategic development of climate change adaptation measures and migration management on national level. However, given context-specific local framework conditions, case study results are rarely directly applicable to larger regions. Consequently, synthesis methods, including meta-analyses, are needed to generate transferable results that can be incorporated into political processes. A major strength of these methods is the possibility to promote an understanding of underlying processes, causal linkages and patterns while maintaining the descriptive richness of local case studies. Even though the potential of migration for adaptation and development has been recognised in the context of the Sustainable Development Goals, there is still a notable lack of synthesis studies in the field of migration that explicitly examine complex causalities.
This presentation introduces the general concept of meta-analyses and reflects on how such analyses can be used at the interface of social and environmental sciences to produce valuable results for both political decision-makers and practitioners in the field. Furthermore, a concrete example of a mixed-method meta-analytical approach will be presented. This particular study aims to produce generic knowledge on the role of migration within the context of environmentally-induced household adaptation and coping in Sub-Saharan African drylands.

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The high frequency of extreme weather and climate change events pose a serious risk to human lives and community physical infrastructure, particularly affecting the quality of life of the poorest and most vulnerable households. Unfortunately, the governments in most middle and low income countries do not have effective disaster preparedness policies to relocate rural households which are at risk from slow onset disasters. As a result, only a few resourceful families living in hazard-prone regions are able to relocate to safer areas, while most other families remain vulnerable to extreme weather and climate change events. To understand this pressing issue, the aim of this paper is to analyze the multifaceted socio-cultural, psychological, economic, geographic and political reasons due to which rural families continue to live in hazard prone areas despite knowing that their lives are at risk. The paper is part of an on-going research on the issue of climate change and human migration using a sample of 50 disaster-prone villages in northern Pakistan which are selected using comprehensive hazard vulnerability and risk assessments.

Co-authors: Nurul Islam Nazem, Md Anwar Hossain

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Dhaka, the capital of Bangladesh and with 17 million populations (2017) is one of the most densely populated cities in the world. The City is still growing at rate of over 5% annually.  Such increase takes place due to rural urban migration over last five decades.  Both rural push and urban pull factors trigger migrants to leave their places of origin. Among all push factors, climate change and environmental stresses seem to be important for the migrants’ desperations to leave.
This paper aims at providing evidences on the links between climate change and migration of the people to Dhaka City. Especially, the scale and the location of migrants, mechanism behind its occurrences and the processes of adaptation to the City along with their management was the main focus of the study.
On the basis of a recent survey on 12,078 migrants’ households in the Dhaka Metropolitan region (1560 sq km) it has been confirmed that 20.9 percent of the migrant households left their origin due to climate change induced factors.  The majority of the CC induced migrants came from southern coastal districts where cyclones, flood and river erosions trigger their movements, while the northern districts, being affected by droughts and river erosions also influence a substantial number of Dhaka’s migrants. Top five origin district of CC and non-CC migrants are different. The highest percentage of CC induced migrants are coming from Bhola (10.06 %), Barisal (9.74 %), Chandpur (7.37 %), Patuakhali (6.85 %), Gaibandha (5.86%); whereas highest percentage of non-CC migrants are from Mymensingh (8.38 %), Sherpur (4.9 %), Barisal (4.77 %) and Comilla (4.7 %), Kishoreganj (4.58 %). Dhaka Metropolitan, the centre of this megacity, is receiving fewer migrants now (both climatic and non-climatic) than before. CC induced migration rate dropped from 26 % after 1990, and settled around a rate of 20 % thereafter until now. Riverbank erosion has been identified as the top natural cause behind such migration (48.42 %), followed by flood (33.25 %), cyclone/storms (10.94 %), water logging (4.43 %) and drought (2.96 %). Dhaka attracts these migrant by providing income and job opportunity. Average decadal growth rate of the CC migration is 197 % compared to 182 % of the non-cc migration.
The CC migrants have higher rates of unemployment and illiteracy rate if compared with other migrants.  They hold significantly less job in industry and agrarian sectors compare to the non-cc migrants, and work mostly in low-income occupation. They are also found economically and socially more vulnerable. They live in houses with worst condition. 12.7 % of CC migrants live in concrete houses compare to the 22.22 % of the non-CC migrants.

Co-authors: Raphael Locham, Jürgen Scheffran

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The Horn of Africa and particularly Somalia is currently experiencing the worst drought since 1945. In addition to drought, the region is exposed to violent conflict and internal and international migration. However, little is known about how these phenomena are connected. Against this background, the presentation explores the nexus of climate, conflict and migration in the Horn of Africa. After introducing key concepts and terms, the presentation discusses two case studies. In the first one, violent conflicts and droughts are analyzed as potential drivers of migration from Somalia to Kenya. The analysis is based on quantitative conflict, climate and migration data. The second case study focuses on northwestern Kenya where pastoral groups are also exposed to strong climatic changes and violent intercommunal conflict but migration mainly takes place within country borders and it is not only a result but also a cause of conflict. This case study draws on field work conducted in Kenya between 2011 and 2017. The last part of the presentation discusses options to disrupt the nexus of climate, conflict and migration. Further, pathways are suggested which lead to sustainable conflict resolution and suitable adaptation to climate change.

Co-author: Jürgen Scheffran

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There has been much debate about possible links between climate change, migration and conflict. One of the potential pathways identified in the literature is that from climate-related disasters, forced migration and competition over scarce resources to violent conflict. This pathway has sometimes been seen as particularly dangerous, as regions receiving disaster-related migrants have little time to adapt to the increased resource demands.

The validity of this argument depends on the idea that those who migrate because of climate-related disasters move to regions with resource scarcity. One reasons for this assumption is that disasters are more damaging to living conditions where living conditions are already difficult. Furthermore, migration from disasters often is short-distanced, mostly to areas also hit by environmental disasters, though to a lesser degree. These assumptions, however, ignore the importance of humanitarian assistance which has become a regular feature in most disasters. Humanitarian assistance affects both patterns of migration and resource scarcity but may also interact with conflict, either affecting the ability to fight or becoming a conflict issue itself (e.g. on the access and allocation of assistance). Migration will be directed towards camps, and humanitarian organizations provide resources in addition to those available on the ground.

The paper provides an analytical framework and uses a number of cases of recent ecological disasters to investigate to what extent the standard argument of the pathway between disasters, forced migration and competition over scarce resources is modified by humanitarian assistance. Framework and case analysis consider the effects of humanitarian assistance on migration patterns, resource availability both in a short- and a long-term perspective.

Countries with strong institutional capacity are better placed to absorb climate shocks, respond to migration challenges and mitigate political violence risks. Countries that have the worst institutional capacity are typically mired in a vicious circle of migration, political instability and conflict that hampers the development of basic governance. Here, we measure the institutional capacity in each country by assessing the stability of the executive authority, the efficacy of the legal and regulatory practices, judicial independence, corruption and the extent to which a country's system of government is determined by the will of the populace.

Co-author: Tobias Haller

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The Yucatán peninsula is the region in Mexico most at risk in the face of climate change, and it is a focal point of sociopolitical and institutional changes like in property land rights that have led to serious environmental degradation. The northern part is recently particularly affected by irregular rainfall, droughts, tropical storms and increasing deforestation. This leads to the emigration of the local Maya population, which for decades lived on forest resources and agricultural production. Institutional changes have led to conflicts in forest use and property rights within the population as well as with government authorities and undermine afforestation efforts. These conditions affect the livelihoods of local people, forcing them to adjust and leading them to migrate for a better income mostly to the city of Cancún and the touristic coast, which shows a rapidly increasing population rate. In addition, unequal political measures in development between the wealthy Caribbean tourist coast and its rural hinterland hinder the improvement of livelihoods inland, discouraging people from investing in their location of origin. However, a stable population and long-term economic investment in agroforestry and forestry institutions could be the basis for a more climate-resilient landscape. To understand these processes, the contribution focuses on environmental and institutional transformations of exploitation, social and political marginalization, and specific adaptation strategies like seasonal or circular labor migration of the population in northeastern Yucatán. This institutional history has made the population and the landscape more vulnerable to climate change, and has made local collective action for reforestation more difficult. Environmental migration studies that take into account historical and institutional change are important in order to understand what decisions were made, by whom, and with what consequences. They must be considered not only as comparative studies, but also as sources of information for future political and economic decisions, for example, in reducing communities’ vulnerability to climate change.

By offering a frame for thinking the future, CESS is furthermore conceived as providing a powerful and critical compass for evaluating these discourses along the extreme poles of socio-ecological transformation in contrast to geopolitical interests and status quo mantainance.

Co-authors: Kashif Majeed Salik, Muhammad Awais Umar

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This research seeks to understand how climate change can expose already vulnerable communities in semi-arid Pakistan to new risks, and explores the potential of rural to urban migration as a strategy to increase their resilience. Demographic changes resulting from human mobility have serious implications for national development if viewed within the purview of Sustainable Development Goals (particularly goals encompassing poverty, inequalities, employment and sustainable communities). Addressing the climate crisis requires a lens that is in conjunction with a people-centric, human development approach. We developed a Livelihood Resilience Index for 600 households, comparing the resilience levels of migrant and non-migrant households. Livelihood resilience is defined through indicators of adaptive, absorptive and anticipatory capacities. In addition, we used a case study approach to explain the existing scenario of income and remittances; shifts in gender roles; and perceptions, decisions and social capital that shape migration outcomes. This allows us to highlight the distributional impacts of migration on left-behind families, highlighting ‘resilience for whom and of what type’, thus identifying trade-offs and conflicts.
We conclude that migration has the potential to strengthen livelihood opportunities, social and human capital and the overall level of resilience among households, making it a viable adaptation strategy. Inflow of remittances, transfer of skills, information and technology and expansion of social network are some of the pathways that lead to enhanced resilience. However, it does not imply that merely facilitating migration would be a sustainable option for enhancing resilience. The way remittances are used up has a significant contribution to the resilience of a household. Results of this study call to revisit the government approach of viewing rural-to-urban migration in a pessimistic context. Policy focus needs to promote the positive impacts of migration while being cognizant of the negative impacts.

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This paper seeks to explore the possibility of implementing intergenerational justice integral to the SDGs through a strategy of using international courts. International climate litigation is used as a case study. The paper sketches a normative framework for such an approach, drawing on Rehfeld’s notion of representation, a minimal subsistence notion of intergenerational justice, and the ‘all affected principle’ which is integral to most theories of democracy. International tribunals such as the International Court of Justice can potentially play a catalytic role in developing international legal rules related to the SDGs. Thus the normative framework set out in the paper can usefully underpin an agenda which seeks to implement the SDGs through their incorporation - where appropriate - in international law.

The future research project analyzes the environment-security nexus in the context of the limits and pathways of human development. The new geological era, the Anthropocene marks the pivotal research focus, as it holds the discourses of environmentally induced conflict, injustice and even human species extinction. Simultaneously the acknowledgment of the Anthropocene is expected to trigger socio-ecological change towards sustainable, safe and just human futures. In between these extremes of environmental security comprehension, the analytical focus lies on the normative potential and on the implicated geopolitical interests of the environment-security nexus. The empirical analysis is dedicated among other to frameworks that support or aspire to push societal transformation towards better futures, such as the Sustainable Development Goals and the Planetary Boundaries approach. An additional research focus lies on the scientific expertise, science-policy interphase such as on the related creation process of norms and values.

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Hundreds of youth around the world fougth for the climate change paris agreement to include the recognition of intergenerational equity as a principle to act for climate change. Being the major population in world the role of youth in mainstreaming climate change is enormous and essential for being themselves the generations born with problematic. I want to use this panel to contribute my experience and insights from the international environmental activism and the multistakeholder spaces. According to my experience working in Nariño, Colombia local knowledge and.thinking are key to figth climate change. In the workshop I will explore the youth tactics and major victories in the international environmental field and also how to work with youth is an issue of climate justice specially in megadiverse countries.

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The Pemón-Arekuna Indigenous people are original inhabitants of Gran Sabana, Canaima National Park (CNP), located in the centre of Guiana Shield, Venezuela. Despite of high acidity, aluminium toxicity and low soil fertility, fragile forests ecosystems coexist with large areas of savanna, where these indigenous communities are able to maintain a sustainable management of natural resources, as part of their millenary culture. As result of global climate and socio-cultural and demographic changes a higher incidence of fires, and increased forest vulnerability, put at risk, both ecosystems and human well-being in CNP. The present work shows the results from a series of participative-action research projects with Pemón Indigenous communities, focused on the importance of the Indigenous right of keeping their daily traditional livelihood practices, especially shifting cultivation, which is the main Indigenous sustainable activity for food production and the challenges that represent the preservation of these ancient practices. Through our own systemic approach, we developed scientific ecological studies that valorise the relevance of these ancient practices for forest and biodiversity conservation as well as adaptation to climate change. We have also facilitated the process of collection, systematization and transmission of ancestral knowledge inside the very same Pemón Indigenous communities, regarding the origin, use and management techniques of shifting cultivation and use of resources. Our results reveal a sophisticated Indigenous knowledge system about the use of "conuco" for the sowing of crops in the forest area, which includes the phases of cutting, control of burning to increase soil fertility, sowing, harvesting, field abandonment and crop rotation performed in function of rain or drought, and respecting family rituals. In spite of this convincing evidence in support of of Indigenous fire practices for sustainable land management, Indigenous peoples’ involvement in policy-making is still limited. At present important efforts for the formulation of a legitimate intercultural and participative management policy in the Park based in the integration of multiple perspectives (Indigenous, academic and institutional), are carried out to enhance sustainable management, promote socially just and culturally sensitive, empowering of Indigenous communities, and strengthen their practices and cultural heritage.

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Indigenous pastoralists societies across the globe have suffered longstanding historical injustices and continue to be among the most vulnerable to human rights abuses, especially with regards to their rights to access, use and control their ancestral lands and territories. This is also the case in Uganda where pastoralism has long been portrayed as economically inefficient, ecologically destructive and socially backwards in public discourse. Accordingly, development policies and interventions by government and other actors have systematically undermined pastoralist production and land tenure patterns, gradually alienating pastoralist societies from the management of their lands and promoting the abandonment of mobile pastoralism in favour of settled agriculture. The current trend towards land tenure privatization and increase in large-scale land acquisitions in the context of investments has threatened pastoralist livelihoods even further. While some might argue that pastoralism is outdated and can no longer survive in an increasingly modern and globalised world, I want to make a case for the opposite. What policy makers have long failed to see is that pastoralism and associated land tenure practices have survived for a reason. Drawing on personal experience in the pastoralist region of Karamoja in North-Eastern Uganda from a perspective of a pastoralist and development worker in the same context, I want to stress the need for a paradigm shift in dominant discourse and shed light on the resilience of pastoralism. In doing so, I will explore the potential of pastoralist land tenure practices, conflict resolution mechanisms and coping strategies in times of crises to positively contribute to the mitigation of contemporary global challenges, most importantly climate change.

The paper will reflect on the shifting agriculture systems of the Cordillera, Philippines and present how such systems have ensured food security for generations of Igorots. It will show how climate change is impacting the systems and how this affects the issue of peace and sustainability. It will address the issue of how to strengthen these systems in the face of climate change and rapid economic development as an effective response to climate change. It will show how the resilience of the communities can be better enhanced if the traditional land use system is protected and allowed to prosper rather than being changed.

The policy making process included exercises in collaborative and inclusive practices, demonstrating how to get agreement and approval from Aboriginal leaders. My presentation will motivate the mind shift of workshop participants who will influence policy making in food security helping developing better understanding of interests of the Aboriginal people challenged by climate change.

Based on this it is critical that there is dialogue on the implications and inter-linkages between the Sustainable Development Goals and the Paris Agreement and whether communication and public education is the missing link for effective implementation of both. In order for vulnerable countries such as Small Island Developing States and its peoples to take urgent action to combat climate change greater dialogue and public participation is key. Exploration of the strategic mechanisms in place to implement both international agreements at the regional, national and community levels is also important if the changes to be implemented are to be sustained.

Co-authors: Ava-Gail Gardiner, Indi Mclymont-Lafayette

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Climate Change Communication and Education for Behaviour Change is an involved process that takes time, commitment and strategy. In Jamaica, the use of popular culture, especially contemporary music, has proven to be highly effective in raising awareness around climate change. This presentation uses case studies to illustrate how two major Climate Change Communication / Education campaigns were developed and implemented in Jamaica, and how they were scaled up and adapted to serve the Global Climate Justice Initiative of 1.5 to stay alive.

Background: Small island developing states (SIDs) are extremely vulnerable to Climate Change. In the last two decades, many SIDs in the Caribbean and Pacific have suffered massive environmental disasters, and the socio-economic fall-out has been devastating. Within the SIDs are marginalised groups such as youth, women, subsistence farmers/ fisherfolk, populations living in remote rural areas or overcrowded inner cities with poor infrastructure and limited access to resources.
Driven by a vision of “enabling Caribbean people to drive their own development agenda, Panos Caribbean has a long history working with the vulnerable using Education for Behaviour Change and Advocacy for Climate Justice as core strategies.
Drawing on The Voices for Climate Change Education project, and the subsequent 1.5 to Stay Alive Campaign, this interactive, multimedia presentation will illustrate how PANOS used a multi-layered, inclusive approach to gain high visibility and impact on the local and international stage.
There are lessons to be learnt from the process of project design and implementation, using an Education for Behaviour Change Framework such as: who to engage / who to target; what issues to focus on/ when to partner (and with whom); where to leverage resources, and how to gain maximum publicity for an initiative.

Connect. Communicate. Change

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Climate change is one of the most pressing issues at the present time, imposing great threats to human life and society. This global environmental concern has become a common topic among debates and discourses and stirred interest upon scholars. With issues surrounding climactic information, media seemed to play the most important role in addressing this problem. Specifically, covering and representing environment and climate change, as a way in creating public awareness on this issue. There is an enormous studies focusing on media content and media reception in connection to climate change. But seemingly, not in the case of the Philippines, where climate change appeared to be constrained on the utopias and heterotopias of public rhetoric despite the country being part of the Vulnerable 20.

This inadequacy has motivated the researcher to embark on this exploration of climactic coverage on leading Philippine broadsheets. Drawing inspiration from previous studies, the researcher examined how Philippine online news media cover climate change in its daily issues by determining its frequency, focus, scope of the issue and resolution, framing valence, coverage frame, source of information, article and image types and newspaper section. This content analysis compared daily coverage of online news portals (Philippine Daily Inquirer, Manila Bulletin and Philippine Star) on climate change and climactic science-related issues from 2015-2016. The results indicated that there was a relative increase on climate change coverage by the media in a span of two years. Environmental frames, government sources, the Paris Agreement, the news section, and wired photos were the dominant themes that emerged during the coding process, which reflects and resonates similar findings of research inquiries on climate change coverage.

Moreover, the results revealed how media framed the Paris Climate Agreement as a possible solution to end climate change through the reduction of carbon emissions and greenhouse gases. The extensive coverage and reportage of the Paris Accord by the Philippine media had increased its salience and importance in countering the effects and impacts of climate change. This too, created among publics the needed awareness on the benefits that this climate pact leads to and the realization that climate change is inevitable and real. Media framed and mainstreamed climate change and the climate deal on its daily online publications both as a controversial global environmental issue and as the best climactic resolution respectively. Furthermore, media coverage of climate science imposed a dichotomy as President Duterte remained skeptical in embracing the climate pact, perceiving it as a hindrance to the country’s economic growth and industrialization. Though media coverage may not have a direct impact on Duterte’s decision of later signing the Paris Accord; the frequency, the extent and the focus on the Paris deal as the desired intervention had created positive impressions and warm receptions among the public and evoked immediate actions to resolve climate change, hence, showing media’s role in influencing and persuading people’s attitudes, beliefs and behaviors. With the Filipinos on the side of the expressive climate advocates and the Duterte cabinet’s unanimous favor and support of the climate deal, this had ensured and defined the future of climate change in the Philippines. Media mainstreaming of climate change and the Paris pact had reinforced climactic-favored behaviors and actions in the country. This too, can be done in other countries around the world especially to those that are still critical and cynical toward the Paris Climate Agreement, as only 154 of the 197 parties had entered into this climate deal.

Accurate, high spatial resolution, repetitious, spatially representative agricultural productivity data remain rare in the developing world. Consequently, a great deal of empirical climate impacts and adaptation research, vital for progress towards the SDGs, relies on aggregate data sources that may mask the extent and heterogeneity of climate impacts to households. This presentation will report results of two recent projects designed to combat this deficiency by creating panel datasets of cropping and climate with household-level detail. Both approaches constructed datasets that fuse in situ, farm-level measurements of agricultural practices with remote sensing data to create spatial pseudo panel datasets (i.e. repeated measures at the same location or over the same spatial extent). First, I will present results from an analysis of the impacts of past climate shocks on rural livelihoods in Mozambique drawing on evidence from a combination of nationally representative household survey data and remote sensing indicators of well-being and crop productivity. Second, I will present results on the relationship between farm size and crop yield sensitivity to climate shocks in Brazil. This latter analysis draws on a dataset fusing a decade of agronomic rapid appraisals with government data on crop yields, remotely sensed crop and climate data, and government survey data. Together, the findings reveal notable differences in the distribution and magnitude of climate impacts and adaptive capacity vs. empirical approaches that use strictly remote sensing data or strictly in situ farm observations. I close by discussing challenges and promise of pseudo panels approaches for improved study of agriculture in developing countries in a changing climate.

Co-authors: Mark van Wijk, Joost van Heerwaarden, Sytze de Bruin, Katrien Descheemaeker, Piet van Asten, Ken Giller

Climate change impacts, e.g. unreliable rainfall, heatwaves and spread of diseases, challenge East Africa’s smallholder agriculture to achieve food security for households and regions. To plan food security investments, policy makers need information on which interventions are required where and for which households. For this, we must better understand how livelihood strategies for food security differ across regions and between households. We present new analyses for Uganda at country level to determine patterns of household food availability (approximating food security) and of related livelihood strategies that can support prioritising interventions.
We used household level data from the Living Standard Measurement Study – Integrated Survey on Agriculture (LSMS-ISA) of the World Bank to quantify potential household food availability (FA) and related livelihood strategies (the contribution of off-farm income, livestock and key crops to FA) across Uganda. We explored spatial variability of these indicators using regression kriging and climate, soil conditions, population density and market access as explaining factors.
Despite larger mean FA in Southwest (>30,000 kcal cap-1 d-1) than in Northeast Uganda (<10,000 kcal cap-1 d-1), 80% of FA variability was on short distance. FA thus varied more within regions than across agroecologies indicating that wealth inequality must be addressed country-wide beyond targeting vulnerable zones. Only crops for which temperature and rainfall determine their distribution (e.g. banana, sorghum) could be linked to food availability patterns, while other crops were ubiquitous (e.g. maize, cassava). Off-farm income was important across Uganda, while local variation in livestock overruled across-country patterns.
Our approach uses household data for country-wide analyses of farming systems and can be used for multi-step and multi-scale targeting: country-wide patterns can support decisions on which crops to select for interventions on improving crop productivity, while local information on the diversity of productive resources and livelihood strategies help to define the target household population.

Co-authors: Esther Boere, Michiel van Dijk, Aline Mosnier, Amanda Palazzo, Petr Havlík

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Through its consistent representation of systems and markets, integrated assessment models allow us to better understand the impact of human societies on the environment and their feedbacks on human welfare. However, these models often rely on a simplistic representation of human agents not only masking economic heterogeneity of decision which may affect model outputs, but also limiting the ability to assess environmental and policy impacts on different population groups within societies. We provide in this presentation two illustrations of application domains where human-environmental frameworks have been extended to better represent socioeconomic heterogeneity in impact analysis, on the production or the consumption level, using the GLOBIOM model developed at IIASA. First of all, we look at the heterogeneity in food consumption in India and show how important a role the distribution of income can play in the SSP x RCP analytical framework for climate change impact calculation. We use a module that projects food demand by population group using household data from three rounds of NSSO Consumer Expenditure Survey in India with different SSP parameters, including Gini projection. Second, we provide an illustration of the improved heterogeneity on the supply side of IAMs with an analysis of Ethiopian smallholder farms. Household data (Ethiopia Rural Socioeconomic Survey, from the LSMS-ISA project) are combined with agricultural census data to differentiate farming systems in the model according to the agro-ecological zone, farm size, main activities, and intensity of production at the third administrative level in Ethiopia. Results shown that different policy interventions lead to different ways to achieve increases in food production for different types of farming systems. Although these applications remain limited to particular regions, they allow illustrating the importance of socioeconomic heterogeneity representation to better estimate impacts of climate change and various related policies, but also to more accurately represent the contrasted socioeconomic development of the SSPs storylines and their full implications for climate change studies.

Co-author: James Hammond

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There is an urgent need to improve the characterisation of smallholder agricultural systems at household level. Survey instruments that are currently used in agricultural development projects are not harmonized in the information they collect and lack standardization of indicators. Improvement is needed both to enable more efficient assessment of the capacity for adoption of agricultural interventions (e.g. sustainable intensification, climate smart agriculture) as well as monitoring of change (e.g. assessing progress towards the Sustainable Development Goals). Local drivers and factors need to be identified that constrain or provide opportunities within a specified agricultural system, while measurements of generalizable characteristics are needed that allow for robust comparisons between locations and common trends to be identified.
Here we present our work on the Rural Household Multiple Indicator Survey (RHoMIS), a rapid (~40 – 60 minutes per household) digital farm household characterization tool that quantifies the linkage between agricultural activities, off-farm activities, and a series of welfare indicators in a standardized and harmonized way. The tool has been applied in more than 40 sites in 16 countries across the developing world by a wide range of partners and in more than 20 different development projects.
We assess the data quality of information collected with RHoMIS in comparison to other survey tools like the World Bank’s LSMS – Integrated Survey on Agriculture and ImpactLITE, and show how results obtained with the tool have been used to i) identify common pathways and thresholds in achieving food security and healthy diets across contrasting farming systems; ii) quantify trade-offs between the different welfare indicators with a special focus on gendered control information; and iii) assess drivers of change of smallholder farmers over time. The results are used to better match interventions to smallholder farmers and to assess the impact of interventions in smallholder systems across various locations in the developing world.

Coming soon

Co-authors: Andrés Cisneros-Montemayor, Wilf Swartz, William Cheung, Adam Guy, Tiff-Annie Kenny, Chris McOwen, Rebecca Asch, Jan Laurens Geffert, Colette Wabnitz, Rashid Sumaila, Quentin Hanich, Yoshitaka Ota

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Achieving the United Nations’ 17 Sustainable Development Goals (SDGs) results in many ecological, social, and economic consequences that are inter-related. Understanding relationships between sustainability goals and determining their interactions can help prioritize effective and efficient policy options. In this talk I will present a framework that integrates existing knowledge from literature and expert opinions to rapidly assess the relationships between one SDG goal and another. Specifically, given the important role of the oceans in the world's social-ecological systems, this study focuses on how SDG 14 (Life Below Water), and the targets within that goal, contributes to other SDG goals. This framework differentiates relationships based on compatibility (co-benefit, trade-off, neutral), the optional nature of achieving one goal in attaining another, and whether these relationships are context dependent. The results from applying this framework indicate that oceans SDG targets are related to all other SDG goals, with two ocean targets (of seven in total) most related across all other SDG goals. Firstly, the ocean SDG target to increase economic benefits to Small Island Developing States (SIDS) and least developed countries for sustainable marine uses has positive relationships across all SDGs. Secondly, the ocean SDG target to eliminate overfishing, illegal and destructive fishing practices is a necessary pre-condition for achieving the largest number of other SDG targets. This study highlights the importance of the oceans in achieving sustainable development. The rapid assessment framework can be applied to other SDGs to comprehensively map out the subset of targets that are also pivotal in achieving sustainable development.

Co-authors: Sebastian Unger, Stefanie Schmidt, Yvonne Waweru, Carole Durussel,
Martin Visbeck

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Though designed as an “indivisible whole”, the 2030 Agenda for Sustainable Development comes with the challenge of complex interlinkages within and among the agenda’s 17 sustainable development goals (SDGs) that require attention when implementing the 2030 Agenda and SDGs. SDG 14 aims at conserving and sustainably using oceans, seas and marine resources, and its targets and means of implementation address various human interactions with the marine and coastal environment as well as ocean governance and capacity building. But SDG14 does neither stand in isolation nor can it be achieved in isolation, as an analysis of key interactions between SDG14 and other SDGs reveals.
Applying a seven-point rating scale, the nature and intensity of interactions was assessed at target level between SDG14 and SDG1 (poverty), SDG2 (hunger), SDG8 (economic growth), SDG11 (cities and communities), SDG12 (consumption and production), and SDG13 (climate change). Ranging from +3 (reinforcing targets/goals) to -3 (conflicting targets/goals), the applied scale provides a simple typology for a systematic mapping of positive, synergistic effects as well as of trade-offs and counter-productive interlinkages. The analysis was conducted for the context in which interactions typically occur and based on literature reviews and expert knowledge, and it is complemented by selected regional and policy examples.
Here, we provide an overview over the methodology and findings of this first-order assessment. The strongest positive interlinkages were identified between SDG14 and consumption and production patterns (SDG12), fighting poverty (SDG1) and hunger (SDG2), while the central role of oceans and coasts in the climate system manifests in strong synergies between SDG13 and SDG14. We conclude with knowledge gaps and policy options and provide recommendations for applying and advancing the typology. Looking ahead from the 2017 UN Ocean Conference to COP23 in Bonn, inter alia, understanding and tackling interactions through concise mapping will be crucial for a successful implementation of both the SDGs and the Paris Agreement.

The SDGs provide a list of measures countries can follow in order to confront this and other global challenges, however, there is still little guidance available on how to ensure an adequate implementation of SDG goals and targets into domestic legal frameworks. In this context, legal studies have an important role to play. Environmental law practitioners sit in the intersection between legal analysis and environmental science. From this standpoint, legal studies can contribute to the implementation of SDG 14 in at least two ways: first, some ocean management practices proposed by other social and natural sciences can be implemented by updating existing legal instruments. Second, the role of legal scholarship is also to incorporate concepts developed by other sciences –such as the need for Ecosystem-Based Marine Management or the importance of stakeholder participation in fisheries management- and to transform those concepts into legal principles.

Co-authors: R. A. Watson, E. A. Fulton, A. Buchholz, D. Carozza, W. Cheung, L. Davidson, J. P. Dunne, N. Dulvy, T. D. Eddy, J. Elliott, E. Galbraith, S. Jennings, H. Lotze, O. Maury, C. Müller, D. Tittensor

Fish provide a crucial contribution to global food security and nutrition, but progress towards 
sustainability is challenged by cumulative impacts including overfishing, biodiversity loss, and 
climate change. To meet the increasing global demand for fish whilst reducing pressures on wild stocks, the linkages between fisheries, aquaculture and agriculture must be recognised along with their changing nature. However, societal development pathways, needed to meet 
international targets such as the UN Sustainable Development Goals, typically separate marine  and terrestrial food production sectors and ecosystems. Here, we examine the role of fish  availability in the wider context of these goals focusing on food, biodiversity and climate change. We demonstrate that some countries are likely to face double jeopardies in both fisheries and agriculture sectors under climate change, creating food challenges. The strategies to mitigate  these risks will need to account for context and trade-offs among Sustainable Development Goals, such as halting biodiversity loss and poverty reduction. Countries with low adaptive capacity but increasing demand for food will require aid to transition towards: improved management and conservation, imports and innovation in food production, and development of low input and low impact aquaculture.

Co-authors: Kirsty L. Nash, Reg A. Watson, Aysha Fleming, Elizabeth A. Fulton, Benjamin S. Halpern, Julia L. Blanchard

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Achieving zero hunger by 2050 requires a stable and predictable food supply. Yet, numerous social-ecological stressors influence food system stability, including climate variability and change. Research focussing on environmental tipping points indicates that small changes in biophysical conditions may result in disproportionately large ecosystem responses. To date no work has quantitatively identified, mapped, and explained tipping points in food production, or compared country-level risk across terrestrial and aquatic sectors. We present a framework for detecting tipping points in food systems, identifying their social-ecological drivers and exploring the nature of relationships between drivers and production response. Understanding the spatio-temporal trends of these non-linear shifts in production will help to identify global hotspots of food supply instability. Moreover, understanding the nature of the relationship between drivers and production can highlight critical thresholds – the points where non-linear shifts in supply occur. This will be crucial for understanding future risk for food systems across time and space as global change continues to influence both land and sea.

Co-authors: Andrea Buchholz, Derek Tittensor, Tyler Eddy, Eric Galbraith, William Cheung

Climate change is already affecting the abundance and distribution of marine organisms (SDG 14: Life below water) with consequences for food security (SDG 2: Zero hunger) and coastal livelihoods (SDG 3: Good health and well-being) around the world. Recent results from ensemble projections within the Fisheries and Marine Ecosystem Model Intercomparison Project (FISH-MIP) provide insight into the magnitude of projected changes in fish production on global and regional scales. These results help us to identify which regions will likely benefit from increases in fish production and its associated services over the 21st century, and which regions will be most vulnerable to losses. Results also highlight changes in trophic structure and the impact of fishing. Combining results from 7 global and 8 regional ecosystem models (EMs) driven by 2 climate models (GCMs) and 4 emission scenarios (RCPs) we can also identify the uncertainty of projections in certain areas, across different ecosystem models, and across various climate change scenarios. We will discuss how the projected changes will affect marine ecosystems, food security and coastal livelihoods on global to regional scales. We will also discuss how we could mitigate some of these changes by adjusting climate change levels (e.g. different RCPs) as well as fisheries exploitation and other drivers of environmental change (SDG 13: Climate action).

Co-authors: Constant Labintan, Melinda Noblet

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Amidst the heightened international attention for adaptation, questions arise about the practical formulation and implementation of planned adaptation in a developing country context. To be eligible for international funding, adaptation projects increasingly need to show that they address problems attributed to climate change rather than ‘general’ development problems. In practical terms this translates into an increased demand for developing countries to document full impact chains, from climate hazards, over exposure and vulnerability to ultimately identify potential impacts to its socio-ecological-technical systems. The limited scientific capacity of many LDCs to cover all aspects of these impacts chains has been widely documented. Less well discussed, is the near disconnect between policy and scientific arenas at national level within many of these countries. A weak interest of the scientific community in policy formulation processes is often mirrored by a far-reaching lack of awareness in policy spheres of the importance of scientific evidence for identifying appropriate strategies to deal with climate change impacts. We argue that repairing this connection has to be prioritised for several reasons. Firstly, to foster a much-needed strategic focus of policy makers on the longer time horizons of climate-related challenges to their country’s development path and the need for identifying and assessing medium to long term structural adaptation measures. Secondly, to develop nationally oriented policy relevant research in the context of climate change and to identify relevant adaptation measures for facilitating a more climate resilient development path and finally, to secure access to finance, by substantiating adaptation funding applications with solid scientific arguments and analyses.
The presentation will discuss our recent experiences in accompanying sub-Saharan African countries in their National Adaptation Plan formulation process, and more specifically our experiences in reinforcing national scientific capacities for the planning and programming of adaptation measures.

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Drawing from experiences with the production of the National Development Plan for The Bahamas, I elaborate upon the integration of vulnerability assessments and adaptation planning with development. This project revealed the need for in-depth stakeholder engagement to determine biophysical, socioeconomic and cultural vulnerabilities to climate change while also assessing adaptive capacity and potential for adaptation strategies to involve residents and contribute to sustainable development. Identification of practical solutions, such as community led mangrove restoration, aided in vulnerability reduction while also providing employment and a sense of ownership and involvement in adaptation and land use decisions. As a panelist for this workshop, I can contribute to discussion on the identification of adaptation and development priorities that are informed by science and stakeholder engagement.

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Coastal areas share a location of world’s major cities and a large portion of economic activities. The transition area between the land and sea creates many economic activities such as fishery and tourism while maintaining various services of ecosystem by providing habitat, securing food resources and protecting natural disasters. Nowadays challenge of accessing to coastal resources in sufficient quantity goes beyond security issue, especially in developing countries. Impact of climate change on coastal area has been evidenced through intensification of changing climate pattern and its effects on physical characteristic of the ocean, which will entail more frequent and intense precipitation as well as sea level rise. Although many stakeholders have increased awareness of coastal vulnerability and risk under climate change, it is critical not to lose sight of taking anthropogenic impact into account when evaluating coastal risk. A clearest anthropogenic impact is land uses change for local livelihoods and tourism development. The aim of paper is to project climate and land use change scenarios for assessing vulnerable of coastal cities in Thailand. In order to ensure that all socioeconomic aspect will be truly captures as much as possible, three land use scenarios are formulated by brainstorming with coastal stakeholders at the early stage and extensively analyzed by using scenario based method. Future land uses have been categorized by three scenarios; business as usual (BAU), rapid tourism development (RTD), and sustainability driven (SD) to ensure all possible development pathways. All stakeholders will get contacted and informed at research preparation stage in order to communicate, consult and brainstorm critical ideas of coastal development plans and policies, including their current adaptive capacity related to climate change. Results can be useful in term of understanding coastal vulnerability and adaptive capacity to climate change, promoting coastal sustainability and enhancing adaptive capacity and resilience to coastal community.Coastal areas share a location of world’s major cities and a large portion of economic activities. The transition area between the land and sea creates many economic activities such as fishery and tourism while maintaining various services of ecosystem by providing habitat, securing food resources and protecting natural disasters. Nowadays challenge of accessing to coastal resources in sufficient quantity goes beyond security issue, especially in developing countries. Impact of climate change on coastal area has been evidenced through intensification of changing climate pattern and its effects on physical characteristic of the ocean, which will entail more frequent and intense precipitation as well as sea level rise. Although many stakeholders have increased awareness of coastal vulnerability and risk under climate change, it is critical not to lose sight of taking anthropogenic impact into account when evaluating coastal risk. A clearest anthropogenic impact is land uses change for local livelihoods and tourism development. The aim of paper is to project climate and land use change scenarios for assessing vulnerable of coastal cities in Thailand. In order to ensure that all socioeconomic aspect will be truly captures as much as possible, three land use scenarios are formulated by brainstorming with coastal stakeholders at the early stage and extensively analyzed by using scenario based method. Future land uses have been categorized by three scenarios; business as usual (BAU), rapid tourism development (RTD), and sustainability driven (SD) to ensure all possible development pathways. All stakeholders will get contacted and informed at research preparation stage in order to communicate, consult and brainstorm critical ideas of coastal development plans and policies, including their current adaptive capacity related to climate change. Results can be useful in term of understanding coastal vulnerability and adaptive capacity to climate change, promoting coastal sustainability and enhancing adaptive capacity and resilience to coastal community.

Co-authors: James R. Butler, Amadou Sidibé, Samuel Partey, Philip K. Thornton

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Participatory scenario processes are believed to enhance participants’ systems understanding, learning, social networks and subsequent changes in practices. In spite of a plethora of theoretical reflections emphasizing the potential of these processes to catalyze individual and collective transformation and policy change, empirical evidence is limited. This study aims to fill this gap by looking at the outcomes of subnational scenario planning exercises conducted in three districts (Koutiala, Bougouni, and Segou) of Mali’s Sikasso Region, under the Climate Change, Agriculture, and Food Security (CCAFS) program, designed to facilitate the mainstreaming of climate and food security priorities into development plans and policies. Data was collected during two separate field visits (August 2015 and September 2016). Through semi-structured interviews with 26 scenario participants the study sought to gain in-depth insights into local dynamics and social transformation processes (e.g., learning across boundaries, relation building, systems understanding and change of social practices). After outlining the distinct features of the three districts and the process of scenario development around a plausible future at subnational level by 2030 to the participants, we examined whether they, by being exposed to the scenario exercise, experienced any changes and to which extent these changes could be transformative. The analysis of interviews carried out 12 months after the workshop suggested positive changes in learning and networking, but only limited influence on systems understanding. There was some limited change in practice, but these occurred at the individual and local level, and no policy outcomes were evident. However, by building the adaptive capacity of participants, the scenario process had laid the foundation for ongoing collective action, and potential institutional and policy transformation. We conclude that to enhance the resilience of agricultural and food systems which are threatened by climate change, participatory scenario processes must engage a broader range of cross-scale actors. Such process will both catalyze deeper learning and more effectively link with national level policy-making. In addition, individual scenario planning exercises are unlikely to generate sufficient learning and reflection, and instead they should form one component of more extensive and deliberate stakeholder engagement, learning and evaluation processes.

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Uncertainty dominates discussions on climate change, its impacts and adaptation. Cascading and expanding uncertainties due to climate change, together with on-going and uncertain future socio-economic change make decision making a challenge. Increasingly, knowledge co-production which takes into consideration decision-maker requirements is advocated because it addresses salience, credibility and legitimacy of assessments. Moreover, there is increasing focus on using multi-method approaches for enhancing the value of assessments for supporting long-term adaptation decision making. Decision Making Under Uncertainty (DMUU) approaches seek to address issues of future uncertainty and decision-maker relevant analysis, through stakeholder engagement and modelling. I present and reflect upon two case study applications where a DMUU method; Robust Decision Making, is being applied through a co-production approach in India and Malawi. The two case studies; Cauvery River Basin in Karnataka (CRBK), India, and Lake Malawi-Shire River Basin (LMSRB), have different climatic, socio-economic and institutional characteristics. In the CRBK, the focus is on identifying water resources management options that are relatively robust to climatic and socio-economic uncertainty. In the LMSRB, the focus is on the water energy food (WEF) nexus sectors because of the intricately linked nature of water requirements. We find that quantitative and qualitative methods provide complementary information and can usefully integrated in a coherent assessment. Moreover, greater stakeholder involvement, and therefore ownership, enhances interest amongst them and the inherent focus on the decision context enhances the value of research for them.

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Given their comprehensive nature, the UN-SDGs must be viewed in global context, yet associated policies and consequences are likely to vary greatly by locality. Therefore, comprehensive SDG analysis must engage a global community of practice, with contributors from a wide variety of disciplines and countries. Universities are uniquely positioned to foster such communities, along with developing open-source SDG analysis tools. GLASS aims to facilitate a global community of practice focusing on global-to-local-to-global (GLG) linkages underpinning management of the world’s land and water resources. Our hypothesis is that fine-scale analysis of SDGs within a global framework is required to promote responsible public and private investment, sustainable management of critical natural resources, and collective action. Testing this hypothesis requires thorough accounting of the distribution of impacts across spatial regions, temporal scales and population subgroups. Through the development of interactive tools deployed on Purdue’s GeoHub, it will allow decision makers to explore results and more clearly communicate tradeoffs. These tools will include: (i) interactive maps, (ii) annotated interactive dashboards, and (iii) data-heavy, multi-resolution tools allowing technical analysts to get “under the hood” of the models, design new scenarios and explore policy alternatives. Deployment of models and data on the GeoHub will allow for continuous testing and improvement of models and data by scientists around the world. At the outset, we are utilizing a variety of applications of SIMPLE-G, a global, gridded, partial equilibrium model of food and environmental security linked to agricultural land and water use. This open source model, currently running on the GeoHub, is easy to use and flexible enough to accommodate a wide variety of disciplinary contributions, including climate impacts, water scarcity, biodiversity, terrestrial carbon stocks and food security. This presentation will focus on flagship applications of SIMPLE-G to analyze SDG trade-offs and synergies.

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Solving complex global problems demands that researchers from different disciplines work together, and their analytical tools, models and datasets interoperate. This is especially true in the context of sustainability. For instance, multiple goals of the United Nations Sustainable Development Goals (SDGs) are closely tied to food, land, and water. Study of resource and food sustainability requires a multidisciplinary, multi-scaled approach, e.g., connecting future demands for food, fuel, and clean water to biodiversity, climate change mitigation and poverty reduction, understanding tradeoffs of conflicting goals and the global consequences of pursuing the SDGs. Many barriers exist today for collaborative research across disciplines ranging from the lack of common understanding of the datasets and models used by different groups to the lack of software transparency and reproducibility. Custom technical platforms are costly to build and often lack interoperability with other systems. To answer these challenges, we have developed an open source geospatial computational cyberinfrastructure (GeoHub). At its core is the ability to rapidly disseminate research results, including models, analysis tools, data visualization and other digital content for broader engagement. Built on the HUBzero web framework, the GeoHub is a production quality, self-serve, scientific web platform to facilitate and support integrative research activities and the broad dissemination of findings. In the context of sustainability research, the GeoHub provides a computational framework for dynamic execution of models and analytics tools in virtual containers or on remote supercomputers; an open framework where users may use their own datasets to run models and compare results with the “standard” datasets, or contribute and enhance open-sourced models; a data visualization and exploration platform (e.g., decision support tools for policy makers and education tools for the public); built-in tools for community interaction (forming groups for collaboration, wiki, discussion form, sharing digital content) and the potential for crowdsourcing of data and models; and an interactive and open source platform for broad dissemination, including use in the classroom. The presentation will include an overview of the GeoHub and demonstrations of relevant modeling and data visualization tools.

Co-authors: Till Bärnighausen, Anneliese Depoux, Ashish Jha, Maurice Yé, Rainer Sauerborn

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Massive Open Online Courses (MOOCs) offer the opportunity to engage and teach a global audience into the rationale and arguments of climate change and its impact on health. We want to describe the possibilities of MOOCs as a possible driver for change on the example of three MOOCs on climate change and health that the Institue of Public Health, Heidelberg University, offered in collaboration with the Centre Virchow-Villermé, Université Sorbonne Paris Cité and Centre de Recherche en Santé de Nouna, Burkina Faso. The MOOC Climate Change and Health is designed for a wider audience, subtitled in ten languages, not presuming prior knowledge about climate systems and climate change, teaching the nature of health impacts worldwide, best practices from around the world in adaptation strategies, as well as promoting health co-benefits and engaging participants to interact on a local level with stakeholders. The MOOC Climate Change and Health for Policy-Makers briefs policy-makers in the topics of health as a key argument in developing climate policy, the burden and benefits of climate policies, as well as the scientific evidence behind the four key climate policy arguments based on human health. The francophone MOOC Changement climatique et santé en contexte africain targets the within the African context for a francophone audience.
We have analysed retention and participant demographics of all three MOOCs and have conducted a post-evaluation of the two MOOCs to learn about user satisfaction and knowledge gain. We discuss our findings which may guide practices for employing MOOCs as an approach for climate change promotion, for developed and developing countries. Furthermore, we give an outline on the upcoming, pioneering MOOC on Research Methods for Studying Climate Change and Health, a course on research skills to advance climate change research related to any field to climate change and health nexus.

The paper will illustrate ways and means how universities can become models for society in the pursuance of reducing greenhouse gas emissions and tackling climate change as a requirement for the SDG.

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Developing effective stakeholder engagement processes is a major challenge for universities and scholars engaged in sustainability science. Significant progress has been made in this area over the last decade, especially at the local and community scale. Successful approaches include participatory science and community-based scenario processes, and tend to support either resource management decisions or strategic responses to long-term challenges like climate change. However, very little progress has been made concerning stakeholder engagement at the global scale. We present a first-of-its-kind project that merges a creative knowledge co-production process between scientists and climate negotiators on urgent questions in global climate change governance with a scientific assessment of the effectiveness of this science-policy interaction. Co-designing a technology supported serious game, we study the ensuing cognitive changes among participants as well as political dynamics following the engagement process. The topical focus of the serious game is the relationship between global temperature goals and climate tipping points. The project will provide insights into the strengths and weaknesses of serious games as stakeholder engagement and learning tools. At the same time, through direct interactions with global stakeholders, we seek to provide timely and useful scientific insights to support ongoing climate negotiation processes.

Co-authors: Bernhard Schauberger, Christoph Müller, Sotirios Archontoulis, Kenneth J. Boote, Delphine Deryng, Christian Folberth, Cesar Izaurralde, David Kelly, Thomas AM Pugh, Erwin Schmid, Xuhui Wang

Agricultural drought describes how climatological and hydrological drought conditions drive production deficits in agriculture from farm to global scales. Even the simplest measures of agricultural drought can require complex considerations such as the spatial distribution of cropping area, farm management regimes that affect soil water (e.g. irrigation, residue and drainage practices), and the timing of planting and key phenological stages such as anthesis onset and maturity.
Because of this extreme complexity, biophysical models that include detailed soil, plant and farm-management processes and their interactions with each other and the atmosphere are practical tools for defining measures of agricultural drought. Advantages to using model-based metrics of agricultural drought include the ability to directly consider 1) major differences in sensitivity to deficit conditions between crops; 2) effects of droughts occurring in months just preceding growing seasons; 3) increased sensitivity due to local conditions (e.g. shallow soil); 4) increased/decreased sensitivity due to management conditions 5) timing of anthesis and maturity; 6) rainfall distribution pattern; and finally, 7) differences in sensitivity during different growth stages for the same crop.
Model-based measures of drought also benefit from the fact that they can be defined consistently across space and time so that droughts occurring in different decades or in very different parts of the world can be quantified, compared, and tracked over time to identify trends. This is difficult or impossible with measures that use historical physical or socioeconomic production data to characterize agricultural drought severity or frequency, because changes in technology, management, and cropped area can strongly impact local and system-level sensitivity.
We report on methods and metrics developed to characterize drought events over the 20th century using a high resolution ensemble of global crop models run as part of the AgMIP Gridded Crop Model Intercomparison (GGCMI), as well as the conclusions of the resulting assessment.

Co-authors: Petr Havlik, Shinichiro Fujimori, G Page Kyle, Hermann Lotze-Campen, Daniel Mason-D'Croz, Yuki Ochi, Elke Stehfest, Jun'ya Takakura

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Cutting greenhouse gas emissions aimed at attaining the 2°C target can help maintain the crop yields. The strict emissions cuts can rely on land-based mitigation measures as bioenergy and can compete with food production. Here we explored effects of climate mitigation on food security using multi-economic models. As our results, most of the economic models agreed that the strict emissions cuts aimed at attaining the 2°C target could indirectly lead to more people at risk of hungry than if those cuts weren’t in place. The potential for a sizeable increase in the global risk of hunger in 2 °C scenario was dominated by South Asia and Sub-Saharan Africa where climate mitigation leads additional 10 to 64 and 36 to 116 million people, respectively face at risk of hunger at the intermediate scenario (SSP2) in 2050. We also found that socioeconomic assumptions such as population, economic development and equity of food distribution largely affect the magnitude of increased risk of hunger. That risk doesn't necessarily negate the need for mitigation but highlights the importance of complementary policies, such as increasing food aid, subsidy or food reallocation, when governments address climate change.

Co-authors: P. Martre, A. Maiorano, R.P. Rötter, G.J. O’Leary, G.J. Fitzgerald, C. Girousse, R. Motzo, F. Giunta, M.A. Babar, M.P. Reynolds, A.M.S. Kheir, P.J. Thorburn, K. Waha, A.C. Ruane, P.K. Aggarwal, M. Ahmed, J. Balkovič, B. Basso, C. Biernath, M. Bindi

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Protein concentration is an important nutritional food characteristic. Wheat supplies 20% of daily protein consumed in the world with the amount and concentration being key aspects of grain quality. Wheat grain protein amount and concentration, similar to yield, is affected by atmospheric CO2 concentration and the dynamics of temperature and crop water supply. Crop simulation models are a tool to assess the potential impact of future climate change scenarios on crop production, but have been less used so far for impacts on grain quality, like protein. Simulations within the Agricultural Model Intercomparison and Improvement Project resulted in a high accuracy of modeling grain protein in field experiments when using a multi-model ensemble. Applying this multi-model ensemble at global scale showed that elevated atmospheric CO2 concentration will increase the grain protein amount, but reduces grain protein concentration. While more water stress and higher temperatures will reduce the amount of protein in grain, the concentration will go up as grain yields decline. Similarly, genetic adaptations targeting grain yield to mitigate climate change impacts might be less effective for grain protein yield or even negative for grain protein concentration. The complexity of impact and response of grain protein will vary with other factors and across regions.

Co-authors: S. B. Traore, D. McCarty, P. C. T. Traore, I. Hathie

Climate risks and hazards affect crop production in most regions in the developing world. In West Africa, where rainfed agriculture dominates, agro-climatic risks are notably linked to false starts of sowing, untimely cessation of the growing season, and water stresses in the post-flowering and grain filling stages. Changes in the seasonal distribution of rainfall could be affected by a warming climate, with the expected increase in rainfall variability and the frequency of extreme events impacting agricultural productivity. This paper is about interpreting fine scale agro-climatic analyses using CMIP5 multi-model characterization mainly at the CIWARA sites in terms of stress for crops in their reproductive stages (flowering, seed set, grain filling). Stress characterization will include plant available water (dry spells) and heat stress (as a function of cardinal temperatures). Crop calendars will be only defined through agro-climatic analyses not through survey data. In this regard, crop-climate sensitivity analysis is conducted to explain in more details the variability of observed and simulated yields in the region with different future climate scenarios that can contribute to significantly lower uncertainties in climate related risks, as well as enhance the resilience of the populations to food insecurity.

Co-authors: Joshua Elliott, Thomas A. M. Pugh, Alex C. Ruane

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Agricultural production must increase to feed a growing and wealthier population, as well as to satisfy increasing demands for biomaterials and biomass-based energy. At the same time, deforestation and land-use change need to be minimized in order to preserve biodiversity and maintain carbon stores in vegetation and soils. In consequence agricultural land use needs to be intensified in the sense that more commodities need to be produced per area of land. We use simulations of AgMIP’s Global Gridded Crop Model Intercomparison phase 1 to assess implications from input-driven intensification (water, nitrogen) for crop yield stability, which is an important aspect in food security. We find region- and crop-specific responses with broadly increasing yield variability under additional nitrogen inputs and stabilizing yields under additional water inputs (irrigation). We discuss implications of input-driven intensification for yield and the trade-off of higher productivity vs. greater variability.

Co-authors: Támas Krisztin,  Petr Havlík, Stefanie Hellweg, Fulvio Di Fulvio, Michael Obersteiner

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Terrestrial biodiversity is declining at alarming rate, and the land use and land cover changes are the primary drivers of such trends. This issue is getting increasing attention, for example via the Sustainable Development Goals (SGD15, Life on Land). Over, as illustrated by other SDGs (e.g., SDG2 Zero hunger, SDG6 Clean water and sanitation, or SDG13 Climate Action among others), land use is at the center of many challenges for the coming decades. Increasing our ability to diagnose potential trade-offs between objectives and policies is a key milestone to navigate safely through these challenges. The global change research community recently provided a scenario framework and associated land use change projections quantifying potential trajectories of socioeconomic development (SSPs) and mitigation efforts (RCPs). Although an very preliminary version of such trajectories was translated into terrestrial biodiversity outcomes, the land cover and use projections suffered from many limitations.
We will present a new assessment of the terrestrial biodiversity impacts from the new generation of future land use change estimates, at global scale and high resolution. The MESSAGE-GLOBIOM integrated assessment model was used to simulate transitions between individual land cover and uses at high-resolution for a combination of socioeconomic pathways (SSP1, SSP2 and SSP3) and mitigation efforts (RCP1.8, RCP2.6, RCP3.7, RCP4.5, RCP6.0 and no mitigation). The projections were further refined with a downscaling econometric model incorporating most recent land cover change observed from remote-sensing over 1990-2015. These downscaled land cover projections were then interpreted as habitat change and translated into changes in local species richness and global threatened endemic species extinction using a Countryside Species Area Relationship model. We will present the impacts of future land use trajectories under various climate mitigation efforts on local terrestrial biodiversity and global species extinction risk.

Co-authors: Cynthia Rosenzweig, John Antle, Keith Wiebe, Joshua Elliott, Gerrit Hoogenboom, Ron Sands, Jeff White, Roberto Valdivia, Daniel Mason-D’Croz, Cheryl Porter, Christoph Mueller, Meridel Phillips

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We present results of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Coordinated Global and Regional Assessments (CGRA) of the agricultural implications of +1.5 and +2.0 ºC Warming above pre-industrial conditions. The AgMIP CGRA is a major community effort designed to allow direct connections of outputs and inputs from climate, crop, and economics models at both global and regional scales under consistent scenarios and assumptions. Coordination across multiple disciplines, scales, disciplines, models and scenarios facilitates the rapid uptake of cutting-edge results, tracking of uncertainty and the identification of feedback loops and emergent constraints as the world faces adaptation and mitigation challenges to achieve a stable climate at +1.5 or +2.0 ºC. The AgMIP CGRA utilizes HAPPI climate projections to assess differences between the current period and +1.5 and +2.0 C worlds, providing farm-level carbon and yield changes and the economic ramifications for crop production, food prices, land use, and carbon balances. This presentation will overview global patterns of maize, rice, wheat, and soy impacts (and related crop/climate model uncertainty), their implications on markets (and associated economic model uncertainty), the policy and socioeconomic shifts that crop and carbon price changes would likely drive in case regions including Senegal, Pakistan, and the United States, and potential adaptation and mitigation strategies that may result. Examines balance between drive for global mitigation and local incentives for socioeconomic development, mitigation, and adaptation.

The historical analysis suggests that countries have different temperatures at which productivity is largest. This may reflect different resilience patterns and economic structure across regions and countries. The magnitude of vulnerability is strongly dependent on levels of income. The results lead to three main conclusions. First, in a number of countries, climate change could increase the income gap between the richest and poorest, with lower inequality levels projected in the 1.5°C and 2.0°C scenarios. Second, significant benefits arise from keeping global mean temperature increase well below 2C (towards 1.5C) even in the first half of the 21st century, in comparison to a scenario leading to 4.5C warming by 2100. Third, depending on the socioeconomic trajectories and therefore vulnerability, countries could experience limited economic impacts from climate change, particularly in a scenario leading to 1.5°C by the end of the century. The research highlights the ability of economy to build resilience and catch-up with limited warming and the need to integrate income inequality in resilience planning.

Co-authors: Elisa Delpiazzo, Marinella Davide

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In September 2015, the adoption of the Sustainable Development Goals (SDGs) by the United Nations defined broad and ambitious development targets for both developed and developing countries encompassing all sustainability dimensions (economic, social, and environmental) and designing the pathway towards an inclusive green growth.
Climate change will pose serious risks for human and natural systems, hindering the already arduous way toward SDGs. Moreover, climate change impacts will not be evenly distributed within regions and across regions, poor people and developing countries will likely be affected more than the others by global warming side-effects due to their higher vulnerability and the lack of resources to invest in precautionary adaptation measures.
It is essential to quantify the heterogeneity of climate change impacts across regions not only taking into account its economic costs, but also a broader set of indicators, ranging from poverty and malnutrition prevalence to healthy life expectancy. Quantifying impacts is the prerequisite for mobilising funds for adaptation and better direct them to the more impacted areas.
This presentation will offer an ex-ante assessment of climate change impacts on the global pathway towards achieving SDGs.
Our analysis relies on a recursive-dynamic Computable General Equilibrium (CGE) model developed and enriched with indicators representative of each SDGs. These models are suited to assess the performance of economic and some environmental indicators; in order to consider some key social indicators, ICES was further developed relying on the empirical literature and directly estimating the relations between indicators and endogenous variables of the model.
Our framework considers 28 indicators covering 16 SDGs. The analysis has world coverage, but we aggregate the result in 45 countries /macro-regions. The baseline scenario reproduces a Shared Socio-economic Pathways 5 (SSP5) and it is used as a benchmark to assess the impact of climate change related shocks on agricultural sector.

Co-authors: Brian Walsh, Stefan Frank, Petr Havlík, Matthew Cantele, Junguo Liu, Amanda Palazzo, Mario Herrero, Yonglong Lu, Aline Mosnier, Hugo Valin, Keywan Riahi, Florian Kraxner, Steffen Fritz, Detlef van Vuuren

The 17 Sustainable Development Goals (SDGs) call for a comprehensive new approach to development rooted in planetary boundaries, equity, and inclusivity. The wide scope of the SDGs will necessitate unprecedented integration of siloed policy portfolios to work at international, regional, and national levels toward multiple goals and mitigate the conflicts that arise from competing resource demands. In this analysis, we adopt a comprehensive modeling approach to understand how coherent policy combinations can manage trade-offs among environmental conservation initiatives and food prices. Our scenario results indicate that SDG strategies constructed around Sustainable Consumption and Production policies can minimize problem-shifting, which has long placed global development and conservation agendas at odds. We conclude that Sustainable Consumption and Production policies (goal 12) are most effective at minimizing trade-offs and argue for their centrality to the formulation of coherent SDG strategies. We also find that alternative socioeconomic futures—mainly, population and economic growth pathways—generate smaller impacts on the eventual achievement of land resource–related SDGs than do resource-use and management policies. We expect that this and future systems analyses will allow policy-makers to negotiate trade-offs and exploit synergies as they assemble sustainable development strategies equal in scope to the ambition of the SDGs.

Co-authors: Mark Budolfson, Marc Fleurbaey, Asher Siebert, Robert Socolow

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Integrated assessment models of climate and the economy provide estimates of the social cost of carbon and inform climate policy, but they have traditionally been used in a way that ignores inequality. We have created a variant of the Regional Integrated model of Climate and the Economy (RICE) in which we introduce a more fine-grained representation of economic inequalities within the model’s regions. Specifically, we break up the original model regions into quintiles. This allows us to investigate the distributional impact mitigation cost and climate damages. The effect on inequality and on the overall optimal policy depends on the incidence of costs and damages in relation to the pre-existing income distribution, quantified by the income elasticity of the impact. With proportional impacts (elasticities equal 1) inequality remains unaffected, and optimal policy is similar to that found in the aggregate models. Regressive mitigation costs (income elasticity of mitigation cost less than 1) lead to an increase in current inequality through mitigation and lower optimal carbon prices. Regressive climate damages (income elasticity of damage less than 1) leads to a decrease in future inequality through mitigation and higher optimal prices. We find that the effect on the optimal policy is very sensitive to the elasticity parameters. The elasticity of mitigation cost is highly sensitive to the structure of policy implementation. Our results highlight the importance of considering the structure of mitigation policy along with the intensity. The income elasticity of damage less understood, with only a few incomplete estimates in the literature. Our ability to design policy that is sensitive to distributional concerns is thus strongly dependent on improving our understanding of this parameter. Estimating the (possibly regional) income elasticities of damage should be an important priority for future research.

Co-authors: Prajal Pradhan, Luis Costa, Diego Rybski, Wolfgang Lucht

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Sustainable Development Goals (SDGs) have set the 2030 agenda to transform our world by tackling multiple challenges humankind is facing to ensure well-being, economic prosperity, and environmental protection. In contrast to conventional development agendas focusing on a restricted set of dimensions, the SDGs provide a holistic and multi-dimensional view on development. However, so far no framework exists that enables an encompassing analysis of different SDSs and their efficacy, particularly not if one is interested mutual interdependencies. In this talk we introduce an approach which analyses SDG interactions on the basis of correlation analysis. As a basis the official SDG indicator set is used which is available for 227 countries. A significant positive correlation between a pair of SDG indicators is classified as a synergy while a significant negative correlation is classified as a trade-off. We rank synergies and trade-offs between SDGs pairs on global and country scales in order to identify the most frequent SDG interactions. For a given SDG, positive correlations between indicator pairs were found to outweigh the negative ones in most countries. Among SDGs the positive and negative correlations between indicator pairs allowed for the identification of particular global patterns. On one hand SDG1 (No poverty) has synergetic relationship with most of the other goals, while SDG12 (Responsible consumption and production) is the goal most commonly associated with trade-offs. This indicates that environmental and climate footprints can be clearly associated to the individual behavior of people. On the other hand SDG3 (Good health and well-being) is the goal typically related to synergies with other SDGs in most countries. For example, around 2.7 billion people (year 2015) live in countries in which ``good health and well-being" (SDG3) is positively linked with the provisioning of ``clean water and sanitation" (SDG6). However, the attainment of the SDG agenda will greatly depend on the leverage of effect of the identified synergies between the goals. In the opposite way the highlighted trade-offs, which are indeed obstacles in achieving the SDGs, need to be negotiated and made structurally non-obstructive if the defined political targets should not be threatened. The presented approach paves the road towards a systematic analysis of the performance of currently vaguely defined policy goals und identifies the thematic and regional hotspots.

Co-authors: Petr Havlik, David Leclere, Michiel Van Dijk

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Agriculture plays a key role in achieving adequate food, water, and energy security (as summarized in the Sustainable Development Goals SDGs) as populations grow and incomes rise. Yet, agriculture is confronted with an enormous challenge to produce more, while minimizing increases to the use of and the damages to land and water resources that are projected to be strongly affected by climate change. To formulate policies that contribute to achieving the SDGs, policy makers need assessments that can anticipate and navigate the trade offs within the water/land/energy domain. Assessments that identify locations or hotspots where trade offs between the multiple, competing users of resources may exist must consider both the local scale when examining the impacts of the use of resources as well as role of regional scale socioeconomic trends, policies, and international markets in further contributing to or mitigating the impacts of resource trade offs.

In this study, we quantify impacts of increased pressure on the land system to provide agricultural and bioenergy products under increasingly scarce water resources using a global economic and land use model, GLOBIOM. We model the supply and demand of agricultural products at a high spatial resolution in an integrated approach that considers the impacts of global change (socioeconomic and climatic) in the biophysical availability of water and the growing competition for water use, between irrigation on the one hand and other sectors (domestic, energy and industry) as well as freshwater ecosystems (environmental flows). We also developed a biodiversity module that relates changes in land uses to changes in local species richness and global species extinction risk.

We find that water available for agriculture and ecosystems decreases due to both climate change and a growing demand from other sectors. Climate change impacts will limit areas suitable for irrigation and may lead to an expansion of rainfed areas in biodiverse areas. Impacts on food security from climate change are significant in some regions (SSA and SA) and policies that protect environmental stream flows compound that effect.

• Jürgen Kropp (Potsdam Institute for Climate Impact Research (PIK), Germany)
• Imme Scholz (The German Development Institute (DIE), Germany)
• Leena Srivastava (TERI University, India)
• Wolfgang Lucht (Potsdam Institute for Climate Impact Research (PIK), Germany)
• Mark Lawrence (Institute for Advanced Sustainability Studies (IASS), Germany)

We have also examined the impacts of abrupt implementation and termination of SRM on ecosystems, by studying climate velocities for both temperature and precipitation. It turns out that rapid implementation is predicted to increase precipitation velocities by almost fivefold above velocities without geoengineering, using the Representative Concentration Pathway (RCP) 4.5. Sudden geoengineering termination would more than double temperature velocities for the land and ocean, and would more than triple temperature velocities in multiple global biodiversity hotspots. These geoengineering-associated velocities exceed even the most optimistic dispersal rate estimates for many species, increasing local extinction risk. In addition, with sudden termination, 29% of the global land surface is predicted to have temperature and precipitation velocity vectors that are both very high and that diverge in direction by more than 90° from each other. Such rapid climate fragmentation could pull populations in divergent directions, with high potential for the rapid disassembly of ecological communities. Rapid geoengineering implementation and termination would significantly increase the threats to global biodiversity and ecosystems from climate change. We urge more such studies using additional scenarios and examining in detail other impacts.

Co-authors: Mohammad M. Khabbazan, Hermann Held

Solar geoengineering (SGE) offers a climate policy option to alleviate anthropogenic temperature rise. However, it cannot simultaneously compensate for anthropogenic changes in further climate variables in a perfect manner. Here, we ask to what extent a proponent of the 2°C-temperature target would apply SGE in conjunction with mitigation in view of global or regional disparities in precipitation changes. We apply cost-risk analysis (CRA), which is a decision analytic framework that makes a trade-off between the expected welfare-loss from climate policy costs and the climate risks from transgressing a climate target. Here, in both global-scale and ?Giorgi?-regional-scale analyses, we evaluate the optimal mix of SGE and mitigation under probabilistic information about climate sensitivity. We generalize and regionalize CRA for the sake of including not only globally aggregated temperature risk, but also globally aggregated precipitation risk, regionally disaggregated temperature risks, and regionally disaggregated precipitation risks. Social welfare is maximized for the following three valuation scenarios: temperature-risk-only, precipitation-risk-only, and equally weighted both-risks.For now, the Giorgi regions are treated by equal weight, we find that for regionally differentiated targets, the usage of SGE will be comparably more restricted. In the course of time, a cooling of up to 1.2°C can be attributed to SGE for the latter scenario and for a median climate sensitivity of 3°C (for a global target only, this number increases by 0.5°C). Our results indicate that although SGE would almost completely substitute for mitigation in the globally aggregated analysis, it only saves 1/2 to 2/3 of the welfare-loss compared to a purely mitigation-based analysis (from economic costs and climate risks, approximately 4.2% in terms of BGE) when considering regional precipitation risks in precipitation-risk-only and both-risks scenarios. It remains to be shown how the inclusion of further risks or different regional weights would change that picture.

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Geoengineering such as solar radiation management (SRM) can be an emergent option to avoid devastating climatic warming, but its ramifications are barely understood. The perturbation of the Earth’s energy balance, atmospheric dynamics, and hydrological cycling may exert unexpected influences on natural and human systems. In this study, I evaluated the impacts of SRM deployment on terrestrial ecosystem functions using a process-based ecosystem model (VISIT) driven by the climate projections by multiple climate models. In the SRM-oriented climate projections, massive injection of sulphate aerosols into the stratosphere led to increased scattering of solar radiation and more-or-less retarded anthropogenic climate warming. The VISIT simulations showed that canopy light absorption and gross primary production were enhanced in subtropics in spite of slight decrease of total incident solar radiation. The retarded temperature rise during the deployment period led to lower respiration, and consequently, additional net terrestrial ecosystem carbon uptake by about 20%. After the SRM termination, however, along with the temperature rise, this carbon was released rapidly to the atmosphere. As a result of altered precipitation and radiation budget, simulated runoff discharge showed suppression mainly in the tropics. These SRM-induced influences on terrestrial ecosystems occurred heterogeneously over the land surface and differed among the ecosystem functions. These responses of terrestrial functions should be taken into account when discussing the costs and benefits of geoengineering.

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The impacts of solar geoengineering will depend on how it is deployed, including not only the choice of how much to deploy, but choices such as the latitude(s) at which to inject stratospheric aerosols or the locations to deploy marine cloud brightening. For example, with stratospheric aerosols, changing how much to inject into one or the other hemisphere can be used to balance the interhemispheric temperature gradient and hence the ITCZ position and associated tropical precipitation patterns; aerosol injection away from the tropics can be used to maintain the equator to pole temperature gradient and hence better manage Arctic/Antarctic impacts as well as avoiding shifts in mid-latitude storm tracks. This “design” potential is not a panacea – one cannot independently manage every climate impact to one’s liking – but it does suggest two things. First, what are the goals of a deployment (and how well can geoengineering be designed to meet those)? And second, caution is needed in assessing climate impacts – are the resulting impacts simply a result of the specific deployment scenario, or unavoidable impacts of any scenario? Impacts should ultimately be assessed in the context of a well-designed strategy intentionally chosen to manage explicitly specified climate goals.