Adaptation to climate variability and change in the US Great Plains:: A multi-scale analysis of Ricardian climate sensitivities

By C. Polsky, William E. Easterling. 2001

151 citations recorded by the source corpus.

Subfields: Ecology, Evolution, Behavior and Systematics, General Agricultural and Biological Sciences, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/1a9f58b5c0bb40a3edb258bd480a75c0cc3a2a66

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In Ecology, Evolution, Behavior and Systematics

In General Agricultural and Biological Sciences

In Global and Planetary Change

Citations in the corpus

Measuring Ethiopian farmers' vulnerability to climate change across regional states: (2008, background): “For instance, the monetary impact of climate change on agriculture can be measured by modeling the relationships between climatic variables and farm income (Mendelsohn, Nordhaus, and Shaw 1994; Polsky and Esterling, 2001; Sanghi, Mendelsohn, and Dinar 1998).”
A Ricardian analysis of the impact of climate change on agriculture in Germany (2009, background): “Our approach takes only long-term climatic variables into consideration although Schlenker and Roberts (2006) indicate that already single day events can have significant influence on yields.”
An analysis of the impact of climate change on crop yields and yield variability (2006, background): “Considerable attention has been devoted to agricultural effects of climate change (Adams et al., 1998, 1999; Lewandrowski and Schimmelpfennig, 1999; Bryant et al., 2000; McCarthy et al., 2001; Polsky and Easterling, 2001).”
South African crop farming and climate change: An economic assessment of impacts (2008, background): “A more explicit spatial analytical approach is discussed by Polsky (2004) and Polsky and Easterling (2001), but the size of the data is not large enough to undertake such explicit analysis.”
Modeling the Spatial Dynamics of Regional Land Use: The CLUE-S Model (2002, methodology): “…these variables, generated by neighborhood analysis, it is also possible to use the more advanced technique of multi-level statistics (Goldstein 1995), which enable a model to include higher-level variables in a straightforward manner within the regression equation (Polsky and Easterling 2001).”
Analysis of farm performance in Europe under different climatic and management conditions to improve understanding of adaptive capacity (2007, methodology): “Polsky and Easterling (2001) accounted for this and excluded variables to minimize multicollinearity.”
Developing Credible Vulnerability Indicators for Climate Adaptation Policy Assessment (2007, background): “Scale issues become of vital importance when attempting to select indicators at levels greater than the characteristic scale of vulnerability patterns in physical and/or societal space (Turner 1991; Polsky and Easterling 2001; Stephen and Downing 2001).”
Agricultural land abandonment and natural forest re-growth in the Swiss mountains: A spatially explicit economic analysis (2007, background): “Hoshino (2001), Polsky and Easterling (2001), Pan and Bilsborrow (2005) and Overmars and Verburg (2006) used multilevel models in land-use research.”