Journal
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES
Volume 367, Issue 1586, Pages 236-246Publisher
ROYAL SOC
DOI: 10.1098/rstb.2011.0183
Keywords
biodiversity; climate change; forest dynamics; hierarchical models; model selection; risk analysis
Categories
Funding
- NSF [DDDAS054845, CDI0940671]
- Coweeta LTER
- Direct For Biological Sciences
- Emerging Frontiers [1137364, 1137309] Funding Source: National Science Foundation
- Division of Computing and Communication Foundations
- Direct For Computer & Info Scie & Enginr [0940671] Funding Source: National Science Foundation
- Division Of Environmental Biology
- Direct For Biological Sciences [823293, 0955904] Funding Source: National Science Foundation
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Anticipating how biodiversity will respond to climate change is challenged by the fact that climate variables affect individuals in competition with others, but interest lies at the scale of species and landscapes. By omitting the individual scale, models cannot accommodate the processes that determine future biodiversity. We demonstrate how individual-scale inference can be applied to the problem of anticipating vulnerability of species to climate. The approach places climate vulnerability in the context of competition for light and soil moisture. Sensitivities to climate and competition interactions aggregated from the individual tree scale provide estimates of which species are vulnerable to which variables in different habitats. Vulnerability is explored in terms of specific demographic responses (growth, fecundity and survival) and in terms of the synthetic response (the combination of demographic rates), termed climate tracking. These indices quantify risks for individuals in the context of their competitive environments. However, by aggregating in specific ways (over individuals, years, and other input variables), we provide ways to summarize and rank species in terms of their risks from climate change.
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