Estimating extinction risk under climate change: next-generation models simultaneously incorporate demography, dispersal, and biotic interactions

Abstract

news and update ISSN 1948-6596 commentary Estimating extinction risk under climate change: next-generation models simultaneously incorporate demography, dispersal, and biotic interactions Estimating species-level extinction risk under pro- jected future climate change is challenging. About ten years ago, Chris Thomas and colleagues used correlative species distribution models (SDMs) and future climate scenarios to estimate extinc- tion risk for >1100 animal and plant species (Thomas et al. 2004). They predicted that 15–37% of their sample species will be ‘committed to ex- tinction’ by 2050. The validity of such results is highly questionable because implausible assump- tions in correlative SDMs introduce large un- knowns into extinction risk forecasts (e.g., Dor- mann 2007). For example, a key assumption is that species’ distributions are at equilibrium with climate and that observed correlations with cli- mate will extend into the future. A further limita- tion is that population-level processes such as demographic rates, dispersal distances, and an- tagonistic or mutualistic interactions among spe- cies are not incorporated into SDMs (e.g., Hampe 2004). Nevertheless, recent biogeographical re- search may finally resolve some of these out- standing challenges (Kissling et al. 2012, Schurr et al. 2012, Travis et al. 2013, Wisz et al. 2013). In a groundbreaking addition to this grow- ing area of research, Fordham et al. (2013) pro- vide a framework for a next-generation model which simultaneously incorporates demography, dispersal, and biotic interactions into estimates of extinction risk under projected climate change. The authors apply this model to one of Europe´s most endangered mammals, the Iberian lynx (Lynx pardinus), which is restricted to isolated popula- tions in southwestern Spain. The modeling frame- work (Figure 1) is centered on demographic (metapopulation) simulations for the Iberian lynx and the European rabbit (Oryctolagus cuniculus), the latter being the main food source of the lynx. Metapopulation models were implemented as age- and sex-structured models for the Iberian lynx (with age and sex specific survival rates and fecundity estimates for age of reproduction, litter size, etc.) and as scalar type stochastic models for the rabbit (to estimate population growth rates without the need to include population age or stage structure). For both species, outputs from correlative SDMs (in annual time steps from 2000 –2100, using ensemble projections based on seven different SDM methods, seven climate change models, and two emission scenarios) were only used to estimate the carrying capacity for the demographic models. In other words, they were used as spatial layers describing climate suitabil- ity, i.e. as one of the components of habitat suit- ability for the two species (Figure 1). The coupling of SDMs with demographic models is a recent ad- vance (Keith et al. 2008), and represents a major step forward in predicting species-level extinction risk under climate change. Dispersal for both species is modelled using functions to determine the proportion of each population that disperses between grid cells or subpopulations (Figure 1). For the lynx, a declining function between subpopulations was used for distances up to 45 km; the maximum dispersal distance which has been empirically reported for this species. Furthermore, a remotely-sensed map (CORINE) was used to identify land cover types with different degrees of suitability for lynx dis- persal (from very good to highly unsuitable). Lynx dispersal was assumed to be stage-specific (young individuals versus adults) and density dependent (based on number of breeding-age individuals in a population), allowing for more detailed simulation of movement. For rabbit dispersal, a declining function up to a maximum dispersal distance of 15 km was used, closely approximating a 1% move- ment at distances of >3 km. Dispersal and move- ment data for both species were based on previ- ously published studies, highlighting the utility of empirical estimates of maximum dispersal dis- tances, movement behavior and habitat selection frontiers of biogeography 5.3, 2013 — © 2013 the authors; journal compilation © 2013 The International Biogeography Society