See Google Scholar for a list of published work.
See Google Scholar for a list of published work.
How will climate change affect food production, including both agriculture and fisheries?Â
How can information help reduce those effects?
How do trade and risk intersect to affect where impacts will actually be felt?
How can we best allocation conservation dollars in a dynamic world?
What role can markets play in aiding conservation goals?
How can machine learning help us better understand the impacts of environmental policies?
Can it help us better make and model dynamic decisions for environmental management?
Attempts to adapt to environmental stressors (heat, pollution, etc.) can create the conditions for contamination bias, so that if we seek to estimate the effects of vector-valued stressors (temperature bins, quadratics in pollution, heat and humidity) while ignoring heterogeneity, we can get misleading results. Fortunately, since this is a form of contamination bias, we have several options for dealing with it.