Integrating ecophysiology and forest landscape models to improve projections of drought effects under climate change

Fundamental drivers of ecosystem processes such as temperature and precipitation are rapidly changing and creating novel environmental conditions. Forest landscape models (FLM) are used by managers and policy‐makers to make projections of future ecosystem dynamics under alternative management or pol...

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Published inGlobal change biology Vol. 21; no. 2; pp. 843 - 856
Main Authors Gustafson, Eric J, De Bruijn, Arjan M. G, Pangle, Robert E, Limousin, Jean‐Marc, McDowell, Nate G, Pockman, William T, Sturtevant, Brian R, Muss, Jordan D, Kubiske, Mark E
Format Journal Article
LanguageEnglish
Published England Blackwell Science 01.02.2015
Blackwell Publishing Ltd
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Summary:Fundamental drivers of ecosystem processes such as temperature and precipitation are rapidly changing and creating novel environmental conditions. Forest landscape models (FLM) are used by managers and policy‐makers to make projections of future ecosystem dynamics under alternative management or policy options, but the links between the fundamental drivers and projected responses are weak and indirect, limiting their reliability for projecting the impacts of climate change. We developed and tested a relatively mechanistic method to simulate the effects of changing precipitation on species competition within the LANDIS‐II FLM. Using data from a field precipitation manipulation experiment in a piñon pine (Pinus edulis) and juniper (Juniperus monosperma) ecosystem in New Mexico (USA), we calibrated our model to measurements from ambient control plots and tested predictions under the drought and irrigation treatments against empirical measurements. The model successfully predicted behavior of physiological variables under the treatments. Discrepancies between model output and empirical data occurred when the monthly time step of the model failed to capture the short‐term dynamics of the ecosystem as recorded by instantaneous field measurements. We applied the model to heuristically assess the effect of alternative climate scenarios on the piñon–juniper ecosystem and found that warmer and drier climate reduced productivity and increased the risk of drought‐induced mortality, especially for piñon. We concluded that the direct links between fundamental drivers and growth rates in our model hold great promise to improve our understanding of ecosystem processes under climate change and improve management decisions because of its greater reliance on first principles.
Bibliography:http://dx.doi.org/10.1111/gcb.12713
US Department of Energy (BER)
ark:/67375/WNG-2P5FH8HR-5
National Science Foundation via the Sevilleta LTER program
ArticleID:GCB12713
USDA National Institute of Food and Agriculture
istex:75AF3B849549F5357D0ECF41F2929F3B1DC947AE
Northern Research Station of the USDA Forest Service and an Agriculture and Food Research Initiative Competitive Grant - No. 105321
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:1354-1013
1365-2486
DOI:10.1111/gcb.12713