Multi-factor, multi-state, multi-model scenarios: Exploring food and climate futures for Southeast Asia

Mason-D’Croz, Daniel; Vervoort, Joost; Palazzo, Amanda; Islam, Shayla; Lord, Steven; Helfgott, Ariella; Havlík, Petr; Peou, Rathana; Sassen, M. M. A.; Veeger, Marieke; Soesbergen, Arnout van; Arnell, Andy; Stuch, Benjamin; Arslan, Aslıhan; Lipper, Leslie

doi:10.1016/j.envsoft.2016.05.008

Cited by 55 publications

(39 citation statements)

References 46 publications

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“…In principle, underlying variables of demographic and economic development are correlated across regions (fertility rate, mortality, investment, technological adoption), however, some regional deviations are plausible, as political context also strongly influences the evolution of such variables. For easier comparability of the direct impacts of the regional drivers, we intentionally varied only the West Africa parameters, changing other parameters over time but keeping them constant across the scenarios for other regions of the world, similar to what was done in the CCAFS Southeast Asian Scenarios (Mason-D’Croz et al, 2016). The rest of the world follows the SSP2 population and economic development trajectory where, by 2050, the global population reaches 9.2 billion people (Kc and Lutz, 2014) and global average GDP per capita doubles to around 16,000 USD (Dellink et al, 2015).…”

Section: Resultsmentioning

confidence: 99%

Linking regional stakeholder scenarios and shared socioeconomic pathways: Quantified West African food and climate futures in a global context

Palazzo

Vervoort

Mason-D’Croz

et al. 2017

Global Environmental Change

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107

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Section: Resultsmentioning

confidence: 99%

Linking regional stakeholder scenarios and shared socioeconomic pathways: Quantified West African food and climate futures in a global context

Palazzo

Vervoort

Mason-D’Croz

et al. 2017

Global Environmental Change

Self Cite

111

107

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show abstract

“…Components of the modeling framework ( Figure 1) include the International Model for Policy Analysis of Agricultural Commodities and Trade (IMPACT; Robinson et al, 2015), the spatially explicit land use model LandSHIFT , and two empirical models for the analysis of land use change effects on biodiversity (Alkemade et al, 2009(Alkemade et al, , 2013Biggs et al, 2008;Jenkins et al, 2013;Scholes & Biggs, 2005) and carbon stock changes in soils and vegetation (European Commission, 2010;European Parliament and Council, 2009;IPCC, 2006;JRC, 2010;Ruesch & Gibbs, 2008). This type of IMPACT-LandSHIFT model 10.1029/2019EF001287 Earth's Future coupling was already successfully implemented and applied for other scenario studies in Southeast Asia and East Africa (e.g., Mason-D'Croz et al, 2016;van Soesbergen et al, 2017). Both models are driven by exogenous climate and socioeconomic scenario data.…”

Section: Modeling Frameworkmentioning

confidence: 99%

Agricultural Development and Land Use Change in India: A Scenario Analysis of Trade‐Offs Between UN Sustainable Development Goals (SDGs)

et al. 2020

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India has the second largest population in the world and is characterized by a broad diversity in climate, topography, flora, fauna, land use, and socioeconomic conditions. To help ensure food security in the future, agricultural systems will have to respond to global change drivers such as population growth, changing dietary habits, and climate change. However, alterations of how food is produced in the future may conflict with other UN Sustainable Development Goals (SDGs), such as the protection of land resources and climate change mitigation. It is crucial for decision‐makers to understand potential trade‐offs between these goals to find a balance of human needs and environmental impacts. In this paper, we analyze pathways of agricultural productivity, land use, and land‐cover changes in India until 2030 and their impacts on terrestrial biodiversity and carbon storage. The results show that in order to meet future food production demands, agricultural lands are likely to expand, and existing farmlands need to be intensified. However, both processes will result in biodiversity losses. At the same time, the projections reveal carbon stock increases due to intensification processes and decreases due to conversions of natural land into agriculture. On balance, we find that carbon stocks increase with the scenarios of future agricultural productivity as modeled here. In conclusion, we regard further agricultural intensification as a crucial element to help ensure food security and to slow down the expansion of cropland and pasture. At the same time, policies are required to implement this intensification in a way that minimizes biodiversity losses.

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“…Experienced shortcomings of qualitative approaches were the poor spatial explicitness and the difficulties of addressing climate change adequately, which hampers the qualitative assessment of management options. Similar to other studies, a difficulty in dealing with nonenvironmental drivers or factors such as governance was their translation from narratives into model input due to the required reduction in complexity (Walz et al 2007, Mason-D'Croz et al 2016) and the lack of time-series data to calibrate and validate the models in this regard.…”

Section: Implementing the Research Challenges In The Scenario Approachesmentioning

confidence: 97%

Systematic evaluation of scenario assessments supporting sustainable integrated natural resources management: evidence from four case studies in Africa

Reinhardt¹,

Liersch²,

Abdeladhim³

et al. 2018

E&S

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ABSTRACT. Scenarios have become a key tool for supporting sustainability research on regional and global change. In this study we evaluate four regional scenario assessments: first, to explore a number of research challenges related to sustainability science and, second, to contribute to sustainability research in the specific case studies. The four case studies used commonly applied scenario approaches that are (i) a story and simulation approach with stakeholder participation in the Oum Zessar watershed, Tunisia, (ii) a participatory scenario exploration in the Rwenzori region, Uganda, (iii) a model-based prepolicy study in the Inner Niger Delta, Mali, and (iv) a model coupling-based scenario analysis in upper Thukela basin, South Africa. The scenario assessments are evaluated against a set of known challenges in sustainability science, with each challenge represented by two indicators, complemented by a survey carried out on the perception of the scenario assessments within the case study regions. The results show that all types of scenario assessments address many sustainability challenges, but that the more complex ones based on story and simulation and model coupling are the most comprehensive. The study highlights the need to investigate abrupt system changes as well as governmental and political factors as important sources of uncertainty. For an in-depth analysis of these issues, the use of qualitative approaches and an active engagement of local stakeholders are suggested. Studying ecological thresholds for the regional scale is recommended to support research on regional sustainability. The evaluation of the scenario processes and outcomes by local researchers indicates the most transparent scenario assessments as the most useful. Focused, straightforward, yet iterative scenario assessments can be very relevant by contributing information to selected sustainability problems.

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Multi-factor, multi-state, multi-model scenarios: Exploring food and climate futures for Southeast Asia

Cited by 55 publications

References 46 publications

Linking regional stakeholder scenarios and shared socioeconomic pathways: Quantified West African food and climate futures in a global context

Linking regional stakeholder scenarios and shared socioeconomic pathways: Quantified West African food and climate futures in a global context

Agricultural Development and Land Use Change in India: A Scenario Analysis of Trade‐Offs Between UN Sustainable Development Goals (SDGs)

Systematic evaluation of scenario assessments supporting sustainable integrated natural resources management: evidence from four case studies in Africa

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