The DOI matches its Crossref record; 180 of the 180 references it cites were found in a registry or an index.
Predicting organismal vulnerability to climate warming: roles of behaviour, physiology and adaptation
Open accessAbstract
A recently developed integrative framework proposes that the vulnerability of a species to environmental change depends on the species'exposure and sensitivity to environmental change, its resilience to perturbations and its potential to adapt to change. These vulnerability criteria require behavioural, physiological and genetic data. With this information in hand, biologists can predict organisms most at risk from environmental change. Biologists and managers can then target organisms and habitats most at risk. Unfortunately, the required data (e.g. optimal physiological temperatures) are rarely available. Here, we evaluate the reliability of potential proxies (e.g. critical temperatures) that are often available for some groups. Several proxies for ectotherms are promising, but analogous ones for endotherms are lacking. We also develop a simple graphical model of how behavioural thermoregulation, acclimation and adaptation may interact to influence vulnerability over time. After considering this model together with the proxies available for physiological sensitivity to climate change, we conclude that ectotherms sharing vulnerability traits seem concentrated in lowland tropical forests. Their vulnerability may be exacerbated by negative biotic interactions. Whether tropical forest (or other) species can adapt to warming environments is unclear, as genetic and selective data are scant. Nevertheless, the prospects for tropical forest ectotherms appear grim.
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Cited by
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Metadata
- Authors
- Huey, R. B., Kearney, M. R., Krockenberger, A., Holtum, J. A. M., Jess, M., & Williams, S. E.
- Venue
- Philosophical Transactions of the Royal Society B: Biological Sciences
- Publisher
- The Royal Society
- Published
- 2012-06-19
- Volume
- 367
- Issue
- 1596
- Pages
- 1665-1679
- ISSN
- 0962-8436 (ISSN-L)
- 1471-2970
- OpenAlex
- W2039789630
- Cited by
- 1,440
- References
- 180
- FWCI
- 54.26
- Type
- journal article
- Language
- en
- Open access
- green
- Licence
- royalsociety.org/journals/ethics-policies/data-sharing-mining/ (tdm)
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