Mapping climate adaptation corridors for biodiversity—A regional-scale case study in Central America

RESEARCH ARTICLE Mapping climate adaptation corridors for biodiversity—A regional-scale case study in Central America Ian M. McCulloughID1,2☯*, Christopher Beirne1,2☯, Carolina Soto-Navarro1,2,3, Andrew Whitworth1,2,4,5* 1 Osa Conservation, Washington, DC, United States of America, 2 Osa Conservation Campus, Puntarenas, Costa Rica, 3 UN Environment Programme World Conservation Monitoring Centre (UNEP-WCMC), Cambridge, United Kingdom, 4 Institute of Biodiversity, Animal Health and Comparative Medicine, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, Scotland, United Kingdom, 5 Department of Biology, Center for Energy, Environment and Sustainability, Wake Forest University, Winston-Salem, NC, United States of America ☯ These authors contributed equally to this work. * andywhitworth@osaconservation.org (AW); immccull@gmail.com (IMM) Abstract Climate adaptation corridors are widely recognized as important for promoting biodiversity resilience under climate change. Central America is part of the Mesoamerican biodiversity hotspot, but there have been no regional-scale analyses of potential climate adaptation cor- ridors in Central America. We identified 2375 potential corridors throughout Central America that link lowland protected areas (� 500 m) with intact, high-elevation forests (� 1500 m) that represent potential climate change refugia. Whereas we found potential corridors in all Central American countries, potential corridors in Panama, Belize, and Honduras were most

protected (medians = 64%, 49%, and 47%, respectively) and potential corridors in El Salva- dor were least protected (median = 10%). We also developed a corridor priority index based on the ecological characteristics and protected status of potential corridors and their associ- ated start and end points. Compared to low- and medium-priority corridors, high-priority cor- ridors (n = 160; top 7% of all corridors) were generally more protected, forested, and distributed across wider elevational gradients and more Key Biodiversity Areas, but also generally linked larger lowland protected areas to target areas that were larger, more pro- tected, and spanned wider elevational gradients. For example, based on median values, high-priority corridors were 9% more protected and overlapped with 2–3 more Key Biodiver- sity Areas than low- and medium-priority corridors. Although high-elevation targets spanned considerably wider elevational gradients than lowland protected areas (medians = 695 vs. 142 m, respectively) and thus may be more likely to support refugia, they were considerably smaller than lowland protected areas (medians = 11 vs. 50 km2 respectively) and mostly unprotected (median = 4% protection). This initial, regional assessment can help prioritize locations for finer-scale research, conservation, and restoration activities in support of cli- mate adaptation corridors throughout Central America and highlights the need for greater conservation of potential high-elevation refugia. PLOS ONE PLOS ONE | https://doi.org/10.1371/journal.pone.0304756 May 31, 2024 1 / 19

a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 OPEN ACCESS Citation: McCullough IM, Beirne C, Soto-Navarro C, Whitworth A (2024) Mapping climate adaptation corridors for biodiversity—A regional-scale case study in Central America. PLoS ONE 19(5): e0304756. https://doi.org/10.1371/journal. pone.0304756 Editor: Lyi Mingyang, Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences, CHINA Received: March 7, 2024 Accepted: May 18, 2024 Published: May 31, 2024 Peer Review History: PLOS recognizes the benefits of transparency in the peer review process; therefore, we enable the publication of all of the content of peer review and author responses alongside final, published articles. The editorial history of this article is available here: https://doi.org/10.1371/journal.pone.0304756 Copyright: © 2024 McCullough et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability Statement: Data and R code used for this study are publicly available on Zenodo: McCullough, I., & Beirne, C. (2024).