Applying landscape metrics to species distribution model predictions to characterize internal range structure and associated changes

Type Article
Date 2023-02
Language English
Author(s) Curd AmeliaORCID1, Chevalier Mathieu1, Vasquez MickaëlORCID1, Boyé AurélienORCID1, Firth Louise B.2, Marzloff MartinORCID1, Bricheno Lucy M.3, Burrows Michael T.4, Bush Laura E.5, Cordier Celine1, Davies Andrew J.6, 7, Mattias Green J.A.8, Hawkins Stepehen J.2, 9, 10, Lima Fernando P.11, 12, Meneghesso Claudia11, 12, 13, Mieszkowska Nova10, 14, Seabra Rui11, Dubois StanislasORCID1
Affiliation(s) 1 : IFREMER, Centre de Bretagne, DYNECO LEBCO, Plouzané, France
2 : School of Biological and Marine Sciences, University of Plymouth, Drake Circus, Plymouth, UK
3 : National Oceanography Centre, Liverpool, UK
4 : Scottish Association for Marine Science, Scottish Marine Institute, Oban, UK
5 : FUGRO GB Marine Limited, Gait 8, Research Park South, Heriot-Watt University, Edinburgh, UK
6 : Department of Biological Sciences, University of Rhode Island, Kingston, Rhode Island, USA
7 : Graduate School of Oceanography, University of Rhode Island, Narragansett, Rhode Island, USA
8 : School of Ocean Sciences, Bangor University, Bangor, UK
9 : Ocean and Earth Science, National Oceanography Centre Southampton, University of Southampton, Southampton, UK
10 : The Marine Biological Association of the UK, Citadel Hill, Plymouth, UK
11 : CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Campus de Vairão, Vairão, Portugal
12 : BIOPOLIS Program in Genomics, Biodiversity and Land Planning, Campus de Vairão, Vairão, Portugal
13 : Departamento de Biologia, Faculdade de Ciências da Universidade do Porto, Porto, Portugal
14 : Department of Earth, Ocean and Ecological Sciences, School of Environmental Sciences, University of Liverpool, Liverpool, UK
Source Global Change Biology (1354-1013) (Wiley / Blackwell), 2023-02 , Vol. 29 , N. 3 , P. 631-647
DOI 10.1111/gcb.16496
WOS© Times Cited 5
Keyword(s) climate change, engineer species, landscape metrics, patch dynamics, range fragmentation, species distribution modelling, within-range structure
Abstract

Distributional shifts in species ranges provide critical evidence of ecological responses to climate change. Assessments of climate-driven changes typically focus on broad-scale range shifts (e.g. poleward or upward), with ecological consequences at regional and local scales commonly overlooked. While these changes are informative for species presenting continuous geographic ranges, many species have discontinuous distributions—both natural (e.g. mountain or coastal species) or human-induced (e.g. species inhabiting fragmented landscapes)—where within-range changes can be significant. Here, we use an ecosystem engineer species (Sabellaria alveolata) with a naturally fragmented distribution as a case study to assess climate-driven changes in within-range occupancy across its entire global distribution. To this end, we applied landscape ecology metrics to outputs from species distribution modelling (SDM) in a novel unified framework. SDM predicted a 27.5% overall increase in the area of potentially suitable habitat under RCP 4.5 by 2050, which taken in isolation would have led to the classification of the species as a climate change winner. SDM further revealed that the latitudinal range is predicted to shrink because of decreased habitat suitability in the equatorward part of the range, not compensated by a poleward expansion. The use of landscape ecology metrics provided additional insights by identifying regions that are predicted to become increasingly fragmented in the future, potentially increasing extirpation risk by jeopardising metapopulation dynamics. This increased range fragmentation could have dramatic consequences for ecosystem structure and functioning. Importantly, the proposed framework—which brings together SDM and landscape metrics—can be widely used to study currently overlooked climate-driven changes in species internal range structure, without requiring detailed empirical knowledge of the modelled species. This approach represents an important advancement beyond predictive envelope approaches and could reveal itself as paramount for managers whose spatial scale of action usually ranges from local to regional.

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Curd Amelia, Chevalier Mathieu, Vasquez Mickaël, Boyé Aurélien, Firth Louise B., Marzloff Martin, Bricheno Lucy M., Burrows Michael T., Bush Laura E., Cordier Celine, Davies Andrew J., Mattias Green J.A., Hawkins Stepehen J., Lima Fernando P., Meneghesso Claudia, Mieszkowska Nova, Seabra Rui, Dubois Stanislas (2023). Applying landscape metrics to species distribution model predictions to characterize internal range structure and associated changes. Global Change Biology, 29(3), 631-647. Publisher's official version : https://doi.org/10.1111/gcb.16496 , Open Access version : https://archimer.ifremer.fr/doc/00805/91725/