Topic
Climate change
About: Climate change is a research topic. Over the lifetime, 99222 publications have been published within this topic receiving 3572006 citations.
Papers published on a yearly basis
Papers
More filters
TL;DR: In this article, the authors report the results of a study of the impact of climate change on the US agricultural sector using the same model used by Deschenes and Greenstone (2007).
Abstract: Fisher et al. (2012) (hereafter, FHRS) have uncovered coding and data errors in our paper, Deschenes and Greenstone ( 2007) (hereafter, DG) . We acknowledge and are embarrassed by these mistakes. We are grateful to FHRS for uncovering them. We hope that this Reply will also contribute to advancing the literature on the vital question of the impact of climate change on the US agricultural sector. FHRS’ main critiques of DG are as follows: (i) there are errors in the weather data and climate change projections used by DG; (ii) the climate change projections are based on the Hadley 2 model and scenarios, rather than the more recent Hadley 3 model and scenarios; (iii) standard errors are biased due to spatial correlation; (iv ) the inclusion of state by year fixed effects does not leave enough weather variation to obtain meaningful estimates of the relationship between agriculture profits and weather; (v) storage and inventory adjustment in response to yield shocks invalidate the use of annual profit data; and (vi) FHRS argue that a better-specified hedonic model produces robust estimates, unlike the results reported in DG. Four of these critiques have little basis and we respond to them here in the introduction. Specifically, with respect to: (ii) The more recent daily climate predictions were not available when we wrote DG. Nevertheless, the most important issue is providing the reliable estimates of climate change and in this note we report estimates based on the climate model we used in DG and a more recent one that we gained access to in the meantime. (iii) In the primary table on agricultural profits, DG reports two sets of standard errors with the first clustered at the county level and the second based on a variance-covariance matrix that accounts for spatial correlation, using the method proposed in Conley (1999). Thus, the claim of FHRS 2012 seems overblown. Nevertheless, to ease comparisons of papers in this literature, this note will adopt the FHRS convention of reporting estimated standard errors clustered at the county and state levels; we find that inference is largely unaffected by the choice between these different assumptions about the variance-covariance matrix.
920 citations
TL;DR: The authors argue that climate change increasingly undermines human security in the present day, and will increasingly do so in the future, by reducing access to, and the quality of, natural resources that are important to sustain livelihoods.
920 citations
TL;DR: This review highlights research progress and gaps that have emerged during the past decade and develops a predictive framework that integrates knowledge from ecophysiology and community ecology with modeling approaches to mitigate the impacts of climate-driven disease emergence.
Abstract: Scientists have long predicted large-scale responses of infectious diseases to climate change, giving rise to a polarizing debate, especially concerning human pathogens for which socioeconomic drivers and control measures can limit the detection of climate-mediated changes. Climate change has already increased the occurrence of diseases in some natural and agricultural systems, but in many cases, outcomes depend on the form of climate change and details of the host-pathogen system. In this review, we highlight research progress and gaps that have emerged during the past decade and develop a predictive framework that integrates knowledge from ecophysiology and community ecology with modeling approaches. Future work must continue to anticipate and monitor pathogen biodiversity and disease trends in natural ecosystems and identify opportunities to mitigate the impacts of climate-driven disease emergence.
917 citations
University of Minnesota1, Leipzig University2, University College Dublin3, Centre national de la recherche scientifique4, University of Zurich5, University of Bayreuth6, Iowa State University7, Martin Luther University of Halle-Wittenberg8, University of Jena9, Swansea University10, United States Department of Agriculture11, Utrecht University12, University of Oxford13, University of Greifswald14, Sewanee: The University of the South15, University of Bern16, Technische Universität München17, Yokohama National University18, Columbia University19, University of Western Sydney20, Colorado State University21, University of California, Santa Barbara22, Virginia Tech23, Wageningen University and Research Centre24
TL;DR: Biodiversity mainly stabilizes ecosystem productivity, and productivity-dependent ecosystem services, by increasing resistance to climate events, and restoration of biodiversity to increase it, mainly by changing the resistance of ecosystem productivity toClimate events.
Abstract: It remains unclear whether biodiversity buffers ecosystems against climate extremes, which are becoming increasingly frequent worldwide1. Early results suggested that the ecosystem productivity of diverse grassland plant communities was more resistant, changing less during drought, and more resilient, recovering more quickly after drought, than that of depauperate communities2. However, subsequent experimental tests produced mixed results3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13. Here we use data from 46 experiments that manipulated grassland plant diversity to test whether biodiversity provides resistance during and resilience after climate events. We show that biodiversity increased ecosystem resistance for a broad range of climate events, including wet or dry, moderate or extreme, and brief or prolonged events. Across all studies and climate events, the productivity of low-diversity communities with one or two species changed by approximately 50% during climate events, whereas that of high-diversity communities with 16–32 species was more resistant, changing by only approximately 25%. By a year after each climate event, ecosystem productivity had often fully recovered, or overshot, normal levels of productivity in both high- and low-diversity communities, leading to no detectable dependence of ecosystem resilience on biodiversity. Our results suggest that biodiversity mainly stabilizes ecosystem productivity, and productivity-dependent ecosystem services, by increasing resistance to climate events. Anthropogenic environmental changes that drive biodiversity loss thus seem likely to decrease ecosystem stability14, and restoration of biodiversity to increase it, mainly by changing the resistance of ecosystem productivity to climate events.
917 citations