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

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.