Extinction risk from climate change is reduced by microclimatic buffering View Full Text


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Article Info

DATE

2018-08

AUTHORS

Andrew J. Suggitt, Robert J. Wilson, Nick J. B. Isaac, Colin M. Beale, Alistair G. Auffret, Tom August, Jonathan J. Bennie, Humphrey Q. P. Crick, Simon Duffield, Richard Fox, John J. Hopkins, Nicholas A. Macgregor, Mike D. Morecroft, Kevin J. Walker, Ilya M. D. Maclean

ABSTRACT

Protecting biodiversity against the impacts of climate change requires effective conservation strategies that safeguard species at risk of extinction1. Microrefugia allowed populations to survive adverse climatic conditions in the past2,3, but their potential to reduce extinction risk from anthropogenic warming is poorly understood3–5, hindering our capacity to develop robust in situ measures to adapt conservation to climate change6. Here, we show that microclimatic heterogeneity has strongly buffered species against regional extirpations linked to recent climate change. Using more than five million distribution records for 430 climate-threatened and range-declining species, population losses across England are found to be reduced in areas where topography generated greater variation in the microclimate. The buffering effect of topographic microclimates was strongest for those species adversely affected by warming and in areas that experienced the highest levels of warming: in such conditions, extirpation risk was reduced by 22% for plants and by 9% for insects. Our results indicate the critical role of topographic variation in creating microrefugia, and provide empirical evidence that microclimatic heterogeneity can substantially reduce extinction risk from climate change. Topographic variations result in microclimatic heterogeneity that can substantially reduce extinction risk from climate change, according to a study of 430 climate-threatened and range-declining species in England. More... »

PAGES

713-717

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/s41558-018-0231-9

DOI

http://dx.doi.org/10.1038/s41558-018-0231-9

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1105743430


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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1038/s41558-018-0231-9'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/s41558-018-0231-9'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/s41558-018-0231-9'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/s41558-018-0231-9'


 

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