Multi-model comparison highlights consistency in predicted effect of warming on a semi-arid shrub

dc.contributor.authorRenwick, Katherine
dc.contributor.authorCurtis, Caroline
dc.contributor.authorKleinhesselink, Andrew
dc.contributor.authorSchlaepfer, Daniel
dc.contributor.authorBradley, Bethany
dc.contributor.authorAldridge, Cameron
dc.contributor.authorPoulter, Benjamin
dc.contributor.authorAdler, Peter
dc.date.accessioned2019-01-25T16:18:16Z
dc.date.available2019-01-25T16:18:16Z
dc.date.issued2017-09
dc.description.abstractA number of modeling approaches have been developed to predict the impacts of climate change on species distributions, performance, and abundance. The stronger the agreement from models that represent different processes and are based on distinct and independent sources of information, the greater the confidence we can have in their predictions. Evaluating the level of confidence is particularly important when predictions are used to guide conservation or restoration decisions. We used a multi‐model approach to predict climate change impacts on big sagebrush (Artemisia tridentata), the dominant plant species on roughly 43 million hectares in the western United States and a key resource for many endemic wildlife species. To evaluate the climate sensitivity of A. tridentata, we developed four predictive models, two based on empirically derived spatial and temporal relationships, and two that applied mechanistic approaches to simulate sagebrush recruitment and growth. This approach enabled us to produce an aggregate index of climate change vulnerability and uncertainty based on the level of agreement between models. Despite large differences in model structure, predictions of sagebrush response to climate change were largely consistent. Performance, as measured by change in cover, growth, or recruitment, was predicted to decrease at the warmest sites, but increase throughout the cooler portions of sagebrush's range. A sensitivity analysis indicated that sagebrush performance responds more strongly to changes in temperature than precipitation. Most of the uncertainty in model predictions reflected variation among the ecological models, raising questions about the reliability of forecasts based on a single modeling approach. Our results highlight the value of a multi‐model approach in forecasting climate change impacts and uncertainties and should help land managers to maximize the value of conservation investments.en_US
dc.description.sponsorshipNASA Biodiversity and Ecological Forecasting Program (NESSF: 15-EARTH15F-133) | U.S. Geological Survey (G15AP00073) | Great Basin Landscape Conservation Cooperativeen_US
dc.identifier.citationRenwick, K. M., Curtis, C., Kleinhesselink, A. R., Schlaepfer, D., Bradley, B. A., Aldridge, C. L., … Adler, P. B. (2017). Multi-model comparison highlights consistency in predicted effect of warming on a semi-arid shrub. Global Change Biology, 24(1), 424–438. doi:10.1111/gcb.13900en_US
dc.identifier.issn1354-1013
dc.identifier.urihttps://scholarworks.montana.edu/handle/1/15160
dc.language.isoenen_US
dc.rightsCC BY, This license lets you distribute, remix, tweak, and build upon this work, even commercially, as long as you credit the original creator for this work. This is the most accommodating of licenses offered. Recommended for maximum dissemination and use of licensed materials.en_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/legalcodeen_US
dc.titleMulti-model comparison highlights consistency in predicted effect of warming on a semi-arid shruben_US
dc.typeArticleen_US
mus.citation.extentfirstpage424en_US
mus.citation.extentlastpage438en_US
mus.citation.issue1en_US
mus.citation.journaltitleGlobal Change Biologyen_US
mus.citation.volume24en_US
mus.contributor.orcidPoulter, Benjamin|0000-0002-9493-8600en_US
mus.data.thumbpage10en_US
mus.identifier.categoryLife Sciences & Earth Sciencesen_US
mus.identifier.doi10.1111/gcb.13900en_US
mus.relation.collegeCollege of Letters & Scienceen_US
mus.relation.departmentEcology.en_US
mus.relation.universityMontana State University - Bozemanen_US

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