Estimating Economic Damage from Climate Change in the United States

Thursday, July 6, 2017

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Authors: Solomon Hsiang, Robert Kopp, Amir Jina, James Rising, Michael Delgado, Shashank Mohan, D. J. Rasmussen, Robert Muir-Wood, Paul Wilson, Michael Oppenheimer, Kate Larsen, Trevor Houser

Science  30 Jun 2017: Vol. 356, Issue 6345, pp. 1362-1369
DOI: 10.1126/science.aal4369

Costing out the effects of climate change

Episodes of severe weather in the United States, such as the present abundance of rainfall in California, are brandished as tangible evidence of the future costs of current climate trends. Hsiang et al. collected national data documenting the responses in six economic sectors to short-term weather fluctuations. These data were integrated with probabilistic distributions from a set of global climate models and used to estimate future costs during the remainder of this century across a range of scenarios (see the Perspective by Pizer). In terms of overall effects on gross domestic product, the authors predict negative impacts in the southern United States and positive impacts in some parts of the Pacific Northwest and New England.


Estimates of climate change damage are central to the design of climate policies. Here, we develop a flexible architecture for computing damages that integrates climate science, econometric analyses, and process models. We use this approach to construct spatially explicit, probabilistic, and empirically derived estimates of economic damage in the United States from climate change. The combined value of market and nonmarket damage across analyzed sectors—agriculture, crime, coastal storms, energy, human mortality, and labor—increases quadratically in global mean temperature, costing roughly 1.2% of gross domestic product per +1°C on average. Importantly, risk is distributed unequally across locations, generating a large transfer of value northward and westward that increases economic inequality. By the late 21st century, the poorest third of counties are projected to experience damages between 2 and 20% of county income (90% chance) under business-as-usual emissions (Representative Concentration Pathway 8.5).

Challenging the maximum rooting depth paradigm in grasslands and savannas

Author(s): Jesse B. Nippert and Ricardo M. Holdo
Date of Publication: January 2015

For many grassland and savanna ecosystems, water limitation is a key regulator of individual plant, community and ecosystem processes. Maximum rooting depth is commonly used to characterize the susceptibility of plant species to drought. This rests on the assumption that deep-rooted plant species would have a greater total volume of soil water to exploit and should be less susceptible to episodic changes in water availability.
Independent of maximum rooting depth, rooting strategies based on differences in biomass allocation with depth, uptake plasticity in relation to water availability and variation in water transport capability may all influence growth responses and susceptibility to drought. Many examples from grasslands and savannas reflect these rooting strategies among coexisting grass, forb and woody species.
Here, we use a dynamic model of plant water uptake and growth to show how changes in root distribution, functional plasticity and root hydraulic conductivity have the potential to influence aboveground biomass and competitive outcomes, even when maximum rooting depth remains constant. We also show theoretically that shifts in root distribution to surface soils without changes in maximum depth can potentially outweigh the benefits of increased maximum rooting depth.
Combining our current reliance on biogeographic descriptions of maximum rooting depth with insights about other, more subtle aspects of root structure and function are likely to improve our understanding of ecosystem responses to dynamic water limitation.

Citation: Nippert, J. B., Holdo, R. M. (2015), Challenging the maximum rooting depth paradigm in grasslands and savannas. Functional Ecology. doi: 10.1111/1365-2435.12390
Team(s): Plant Team