Evaluating the Utility of Species Distribution Models in Informing Climate Change-Resilient Grassland Restoration Strategy

dc.contributor.author Lyon, Nicholas
dc.contributor.author Debinski, Diane
dc.contributor.author Debinski, Diane
dc.contributor.author Rangwala, Imtiaz
dc.contributor.department Ecology, Evolution and Organismal Biology
dc.date 2020-07-28T21:02:38.000
dc.date.accessioned 2021-02-25T18:41:52Z
dc.date.available 2021-02-25T18:41:52Z
dc.date.issued 2019-02-15
dc.description.abstract <p>Tallgrass prairie ecosystems in North America are heavily degraded and require effective restoration strategies if prairie specialist taxa are to be preserved. One common management tool used to restore grassland is the application of a seed-mix of native prairie plant species. While this technique is effective in the short-term, it is critical that species' resilience to changing climate be evaluated when designing these mixes. By utilizing species distribution models (SDMs), species' bioclimatic envelopes–and thus the geographic area suitable for them–can be quantified and predicted under various future climate regimes, and current seed-mixes may be modified to include more climate resilient species or exclude more affected species. We evaluated climate response on plant functional groups to examine the generalizability of climate response among species of particular functional groups. We selected 14 prairie species representing the functional groups of cool-season and warm-season grasses, forbs, and legumes and we modeled their responses under both a moderate and more extreme predicted future. Our functional group “composite maps” show that warm-season grasses, forbs, and legumes responded similarly to other species within their functional group, while cool-season grasses showed less inter-species concordance. The value of functional group as a rough method for evaluating climate-resilience is therefore supported, but candidate cool-season grass species will require more individualized attention. This result suggests that seed-mix designers may be able to use species with more occurrence records to generate functional group-level predictions to assess the climate response of species for which there are prohibitively few occurrence records for modeling.</p>
dc.description.comments <p>This article is published as Lyon NJ, Debinski DM and Rangwala I (2019) Evaluating the Utility of Species Distribution Models in Informing Climate Change-Resilient Grassland Restoration Strategy. <em>Front. Ecol. Evol</em>. 7:33. doi: <a href="https://doi.org/10.3389/fevo.2019.00033">10.3389/fevo.2019.00033</a>.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/eeob_ag_pubs/413/
dc.identifier.articleid 1420
dc.identifier.contextkey 18687315
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath eeob_ag_pubs/413
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/94167
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/eeob_ag_pubs/413/2019_Debinski_EvaluatingUtility.pdf|||Sat Jan 15 00:10:46 UTC 2022
dc.source.uri 10.3389/fevo.2019.00033
dc.subject.disciplines Ecology and Evolutionary Biology
dc.subject.disciplines Natural Resources Management and Policy
dc.subject.disciplines Plant Sciences
dc.subject.keywords seed-mixtures
dc.subject.keywords functional group
dc.subject.keywords climate change
dc.subject.keywords species distribution (niche) model
dc.subject.keywords bioclimatic envelope
dc.title Evaluating the Utility of Species Distribution Models in Informing Climate Change-Resilient Grassland Restoration Strategy
dc.type article
dc.type.genre article
dspace.entity.type Publication
relation.isAuthorOfPublication aecfd42d-9301-436f-bbe4-440275050da7
relation.isOrgUnitOfPublication 6fa4d3a0-d4c9-4940-945f-9e5923aed691
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