Dataset Information

Climate change effects on agriculture: economic responses to biophysical shocks.

ABSTRACT: Agricultural production is sensitive to weather and thus directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic models of agriculture represent endogenous responses to seven standardized climate change scenarios produced by two climate and five crop models. These responses include adjustments in yields, area, consumption, and international trade. We apply biophysical shocks derived from the Intergovernmental Panel on Climate Change's representative concentration pathway with end-of-century radiative forcing of 8.5 W/m(2). The mean biophysical yield effect with no incremental CO2 fertilization is a 17% reduction globally by 2050 relative to a scenario with unchanging climate. Endogenous economic responses reduce yield loss to 11%, increase area of major crops by 11%, and reduce consumption by 3%. Agricultural production, cropland area, trade, and prices show the greatest degree of variability in response to climate change, and consumption the lowest. The sources of these differences include model structure and specification; in particular, model assumptions about ease of land use conversion, intensification, and trade. This study identifies where models disagree on the relative responses to climate shocks and highlights research activities needed to improve the representation of agricultural adaptation responses to climate change.

SUBMITTER: Nelson GC

PROVIDER: S-EPMC3948295 | biostudies-literature | 2014 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Climate change effects on agriculture: economic responses to biophysical shocks.

Nelson Gerald C GC Valin Hugo H Sands Ronald D RD Havlík Petr P Ahammad Helal H Deryng Delphine D Elliott Joshua J Fujimori Shinichiro S Hasegawa Tomoko T Heyhoe Edwina E Kyle Page P Von Lampe Martin M Lotze-Campen Hermann H Mason d'Croz Daniel D van Meijl Hans H van der Mensbrugghe Dominique D Müller Christoph C Popp Alexander A Robertson Richard R Robinson Sherman S Schmid Erwin E Schmitz Christoph C Tabeau Andrzej A Willenbockel Dirk D

Proceedings of the National Academy of Sciences of the United States of America 20131216 9

Agricultural production is sensitive to weather and thus directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic mo ...[more]

PMID: 24344285

Similar Datasets

Project description:The rocky intertidal zone is a highly dynamic and thermally variable ecosystem, where the combined influences of solar radiation, air temperature and topography can lead to differences greater than 15°C over the scale of centimetres during aerial exposure at low tide. For most intertidal organisms this small-scale heterogeneity in microclimates can have enormous influences on survival and physiological performance. However, the potential ecological importance of environmental heterogeneity in determining ecological responses to climate change remains poorly understood. We present a novel framework for generating spatially explicit models of microclimate heterogeneity and patterns of thermal physiology among interacting organisms. We used drone photogrammetry to create a topographic map (digital elevation model) at a resolution of 2 × 2 cm from an intertidal site in Massachusetts, which was then fed into to a model of incident solar radiation based on sky view factor and solar position. These data were in turn used to drive a heat budget model that estimated hourly surface temperatures over the course of a year (2017). Body temperature layers were then converted to thermal performance layers for organisms, using thermal performance curves, creating 'physiological landscapes' that display spatially and temporally explicit patterns of 'microrefugia'. Our framework shows how non-linear interactions between these layers lead to predictions about organismal performance and survivorship that are distinct from those made using any individual layer (e.g. topography, temperature) alone. We propose a new metric for quantifying the 'thermal roughness' of a site (RqT, the root mean square of spatial deviations in temperature), which can be used to quantify spatial and temporal variability in temperature and performance at the site level. These methods facilitate an exploration of the role of micro-topographic variability in driving organismal vulnerability to environmental change using both spatially explicit and frequency-based approaches.

Dataset Information

Climate change effects on agriculture: economic responses to biophysical shocks.

Publications

Climate change effects on agriculture: economic responses to biophysical shocks.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets