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Using rare mosses to resolve barriers in the use of species distribution models for climate change vulnerability assessments

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Title: Using rare mosses to resolve barriers in the use of species distribution models for climate change vulnerability assessments
Authors: Emma Menchions, G. Karen Golinski, Ilona Naujokaitis‐Lewis, Richard Caners, Jeannette Whitton
Source: Conservation Science and Practice, Vol 7, Iss 10, Pp n/a-n/a (2025)
Publisher Information: Wiley, 2025.
Publication Year: 2025
Collection: LCC:Ecology
LCC:General. Including nature conservation, geographical distribution
Subject Terms: bryophytes, climate change exposure, climate change vulnerability assessments, ecological niche modeling, ensemble of small models, microclimate, Ecology, QH540-549.5, General. Including nature conservation, geographical distribution, QH1-199.5
Description: Abstract Climate change vulnerability assessments (CCVAs) provide a framework to assess the threat of climate change and inform conservation decisions. Species distribution models (SDMs) can be informative for a primary component of CCVAs: estimating climate change exposure (hereafter exposure). Despite their utility, SDMs are inconsistently applied. Limitations of few occurrences and difficulty obtaining microclimate‐informed predictors relevant in topographically complex and heterogeneous landscapes challenge their use and may lead to inaccurate exposure estimates. To address this, we develop SDMs with a technique adapted for few occurrences for two rare mosses, Bartramia aprica and Bartramia halleriana, and use a simple method for representing microclimates for the latter, which occurs in mountainous regions. We estimate exposure from models with varying microclimatic detail, spatial resolution, and extent, and explore additional uncertainty by comparing estimate types, scenarios, and potential for extrapolation to novel climates. We found that including microclimate data, smaller spatial extents, and finer resolutions predicted less exposure and produced the best‐performing models. We additionally found that B. halleriana may face greater exposure regardless of the scenario, model, or exposure estimate used. Based on our findings, we introduce a framework suggesting approaches for these difficult cases to enhance the consistent implementation of SDMs in CCVAs.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 2578-4854
Relation: https://doaj.org/toc/2578-4854
DOI: 10.1111/csp2.70153
Access URL: https://doaj.org/article/a8b05fa554294d768fc297742ce996f6
Accession Number: edsdoj.8b05fa554294d768fc297742ce996f6
Database: Directory of Open Access Journals
Description
Abstract:Abstract Climate change vulnerability assessments (CCVAs) provide a framework to assess the threat of climate change and inform conservation decisions. Species distribution models (SDMs) can be informative for a primary component of CCVAs: estimating climate change exposure (hereafter exposure). Despite their utility, SDMs are inconsistently applied. Limitations of few occurrences and difficulty obtaining microclimate‐informed predictors relevant in topographically complex and heterogeneous landscapes challenge their use and may lead to inaccurate exposure estimates. To address this, we develop SDMs with a technique adapted for few occurrences for two rare mosses, Bartramia aprica and Bartramia halleriana, and use a simple method for representing microclimates for the latter, which occurs in mountainous regions. We estimate exposure from models with varying microclimatic detail, spatial resolution, and extent, and explore additional uncertainty by comparing estimate types, scenarios, and potential for extrapolation to novel climates. We found that including microclimate data, smaller spatial extents, and finer resolutions predicted less exposure and produced the best‐performing models. We additionally found that B. halleriana may face greater exposure regardless of the scenario, model, or exposure estimate used. Based on our findings, we introduce a framework suggesting approaches for these difficult cases to enhance the consistent implementation of SDMs in CCVAs.
ISSN:25784854
DOI:10.1111/csp2.70153