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Assessing the need and potential of assisted migration using species distribution models
- Source :
- Biological Conservation. 196:60-68
- Publication Year :
- 2016
- Publisher :
- Elsevier BV, 2016.
-
Abstract
- Assisted migration (AM) has been suggested as a management strategy for aiding species in reaching newly suitable locations as climate changes. Species distribution models (SDMs) can provide important insights for decisions on whether to assist a species in its migration; however, their application includes uncertainties. In this study, we use consensus SDMs to model the future suitable areas for 13 vascular plant species with poor dispersal capacity. Based on the outputs of SDMs under different climate change scenarios and future times, we quantify the predicted changes in suitable area by calculating metrics that describe the need and potential for migration. We find that, by the end of the 21st century, one of the species would benefit from AM under mild climate change, seven under moderate change, and for 12 out of 13 species studied AM appears to be a relevant conservation method under strong climate change. We also test the effect of different modeling attributes on the metrics and find little variation between SDMs constructed using different combinations of modeling methods and variable sets. However, the choice of climate variables had a larger influence on the level of the metrics than did the modeling method. We therefore suggest that the choice of climate variables should receive ample attention when measuring climate change threat using SDMs and that experiments aiming to uncover critical environmental factors for individual species should be extensively conducted. This study illustrates that dispersal assistance may be needed for many species under a wide range of possible future climates.
- Subjects :
- 0106 biological sciences
010504 meteorology & atmospheric sciences
Range (biology)
business.industry
ta1172
Environmental resource management
Niche
Species distribution
Climate change
15. Life on land
010603 evolutionary biology
01 natural sciences
Variable (computer science)
13. Climate action
Assisted colonization
ta1181
Environmental science
Biological dispersal
business
Ecology, Evolution, Behavior and Systematics
0105 earth and related environmental sciences
Nature and Landscape Conservation
Local adaptation
Subjects
Details
- ISSN :
- 00063207
- Volume :
- 196
- Database :
- OpenAIRE
- Journal :
- Biological Conservation
- Accession number :
- edsair.doi.dedup.....5161a1a7f235c8e4099e1d2eee0b8bc7
- Full Text :
- https://doi.org/10.1016/j.biocon.2016.01.031