Life history and spatial traits predict extinction risk due to climate change

Abstract

There is an urgent need to develop e ective vulnerability assessments for evaluating the conservation status of species in a changing climate 1 . Several new assessment approaches have been proposed for evaluating the vulnerability of species to climate change 2-5 based on the expectation that established assessments such as the IUCN Red List 6 need revising or superseding in light of the threat that climate change brings. However, although previous studies have identified ecological and life history attributes that characterize declining species or those listed as threatened 7-9 , no study so far has undertaken a quantitative analysis of the attributes that cause species to be at high risk of extinction specifically due to climate change. We developed a simulation approach based on generic life history types to show here that extinction risk due to climate change can be predicted using a mixture of spatial and demographic variables that can be measured in the present day without the need for complex forecasting models. Most of the variables we found to be important for predicting extinction risk, including occupied area and population size, are already used in species conservation assessments, indicating that present systems may be better able to identify species vulnerable to climate change than previously thought. Therefore, although climate change brings many new conservation challenges, we find that it may not be fundamentally di erent from other threats in terms of assessing extinction risks.Attempts to quantify the threat that climate change poses to species' survival commonly infer extinction risk from changes in the area of climatically suitable habitat (the bioclimate envelope) 10,11 , but this approach ignores important aspects of species' biology such as population dynamics, vital rates and dispersal 12-16 , leading to high uncertainty 1,17 . To address this challenge, we coupled ecological niche models (ENMs) with demographic models [13][14][15][18][19][20] and expanded this approach by developing a generic life history (GLH) method. The coupled modelling approach estimates extinction risk as the probability of abundance falling to zero by the year 2100, rather than as the proportion of species committed to extinction due to contraction of bioclimate envelopes 10 (Methods).By matching ENMs for 36 amphibian and reptile species endemic to the US with corresponding GLH models (Supplementary Table 1), we estimate mean extinction risk by 2100 to be 28 ± 7% under a high CO 2 concentration Reference climate scenario 21 and 23 ± 7% under a Policy climate scenario that assumes substantive intervention 22 (Methods). In contrast, extinction risk is estimated by the same models to be <1% without climate change, showing that the methods are not biased towards predicting high risks. The contrast between predicted extinction risk with and without climate change suggests that climate change will cause a pronounced increase in extinction risk for these taxonomic groups over the coming century. Contrary to other stud...

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Hot and bothered: Using trait-based approaches to assess climate change vulnerability in reptiles

“…At present, the most commonly identified threats to species on the IUCN Red List are habitat loss, overexploitation and invasive species (IUCN, 2015b), while only 8% of the 67,000 species assessed under the current criteria system (IUCN, 2001) are recorded as threatened by climate change (IUCN, 2015b). The IUCN Red List Criteria effectively account for climate change in threatened species (Akcakaya et al, 2014;Pearson et al, 2014), although a number of factors may still prevent the adequate listing of climate change for threatened species: species may be perceived as susceptible to climate change, but may not yet be exposed to significant changes, or vice versa ; assessors may approach climate change threats inconsistently due to uncertainties surrounding current projections of climate change and their effects on species (Keith et al, 2014;Westoby and Burgman, 2006); other threats, acting synergistically with climate change, may be more easily understood and recorded, thus underestimating the importance of climate change (Hof et al, 2011).…”

Timing and severity of immunizing diseases in rabbits is controlled by seasonal matching of host and pathogen dynamics

“…Full details of the model specification and software implementation are provided in the electronic supplementary material, appendix A. rate 0.001, tree complexity of 5, k-fold cross-validation procedure) and extinction risk (binomial error structure). Similar approaches were recently used to identify the importance of disease effects on prey availability for black-footed ferrets [47], and life-history and spatial traits on the extinction risk of vertebrates [48].…”