Designing ecological climate change impact assessments to reflect key climatic drivers

Details

• Journal Title:
  Global Change Biology
• Personal Author:
  Sofaer, Helen R. ; Barsugli, Joseph J. ; Jarnevich, Catherine S. ; Abatzoglou, John T. ; Talbert, Marian K. ; Miller, Brian W. ; Morisette, Jeffrey T.
• NOAA Program & Office:
  OAR (Oceanic and Atmospheric Research) ; CIRES (Cooperative Institute for Research in Environmental Sciences) ; ESRL (Earth System Research Laboratory)
• Description:
  Identifying the climatic drivers of an ecological system is a key step in assessing its vulnerability to climate change. The climatic dimensions to which a species or system is most sensitive – such as means or extremes – can guide methodological decisions for projections of ecological impacts and vulnerabilities. However, scientific workflows for combining climate projections with ecological models have received little explicit attention. We review Global Climate Model (GCM) performance along different dimensions of change and compare frameworks for integrating GCM output into ecological models. In systems sensitive to climatological means, it is straightforward to base ecological impact assessments on mean projected changes from several GCMs. Ecological systems sensitive to climatic extremes may benefit from what we term the ‘model space’ approach: a comparison of ecological projections based on simulated climate from historical and future time periods. This approach leverages the experimental framework used in climate modeling, in which historical climate simulations serve as controls for future projections. Moreover, it can capture projected changes in the intensity and frequency of climatic extremes, rather than assuming that future means will determine future extremes. Given the recent emphasis on the ecological impacts of climatic extremes, the strategies we describe will be applicable across species and systems. We also highlight practical considerations for the selection of climate models and data products, emphasizing that the spatial resolution of the climate change signal is generally coarser than the grid cell size of downscaled climate model output. Our review illustrates how an understanding of how climate model outputs are derived and downscaled can improve the selection and application of climatic data used in ecological modeling.
• Source:
  Global Change Biology, 23(7), 2537-2553
• DOI:
  https://doi.org/10.1111/gcb.13653
• ISSN:
  1354-1013 ; 1365-2486
• Format:
  pdf
• Publisher:
  Wiley
• Document Type:
  Journal Article-Accepted Manuscript
• Rights Information:
  Accepted Manuscript
• Rights Statement:
  The NOAA IR provides access to this content under the authority of the government's retained license to distribute publications and data resulting from federal funding. While users may legally access this content, the copyright owners retain rights that govern the reproduction, redistribution, and re-use of this work. The user is solely responsible for complying with applicable copyright law.
• Compliance:
  Library
• Main Document Checksum:
  urn:sha-512:60a79df01c19308fd6f91da3c81b2a6d3547bb0ec6dd3f47a956d4151ea16ba339b9b9c589c2ea6e9ac2f629e9bfa662de78b98986c2c5a4e4762bfebc2df669
• Download URL:
  https://repository.library.noaa.gov/view/noaa/69011/noaa_69011_DS1.pdf
• File Type:
  [PDF - 1.01 MB ]