Bioclimate envelope models: what they detect and what they hide
In a recent issue of Global Ecology and Biogeography, Pearson & Dawson (2003) provided an informative review of the use of bioclimate envelope models (BEM) for predicting future distributional ranges of temperate plant species under expected global climate change. The authors discuss several criticisms of the BEM approach and they conclude that these need not be a major drawback when applied as a starting point for predicting the impacts of potential climate change on species ranges. Here, I argue that the strongly deterministic and reductionist BEM rely on biological assumptions that are much more commonly violated in nature than Pearson & Dawson (2003) assume. Moreover, the statistical methods currently used for model validation overestimate model fits as a result of pseudoreplication. Both features make BEM prone to produce artificially optimistic scenarios of future climate change impacts on plant distributions.
Little doubt exists that climate determines the large-scale distributions of many temperate plant species (Woodward, 1987). However, ongoing range shifts are affected by a multitude of other constraints and processes acting on population performance (e.g. Ibrahim et al., 1996; Clark et al., 2001; Travis, 2003). These differ greatly across species’ ranges from their expanding to their eroding margins, and so also does the character of the respective populations (Lesica & Allendorf, 1995; Davis & Shaw, 2001). This will most probably result in geographically differential responses to changing environmental conditions, a point largely ignored by BEM approaches. In the following, I will comment on three major biological critiques of BEM that have been reviewed and downplayed by Pearson & Dawson (2003).
BEM treat species as if they were acting independently of their biotic environment, thus neglecting potential effects of predation, competition or mutualisms on range dynamics. Pearson & Dawson (2003) argue accordingly that interactions between species may shape their spatial distributions on fine geographical scales, but are of minor importance at coarse scales, which are the main focus of BEM. However biotic interactions, not climate, are commonly considered the principal determinants of low-latitude range limits (Brown et al., 1996). Moreover, ecological research on biological invasions (unintended ‘large-scale experiments’) has broadly documented that biotic interactions affect species’ performance throughout their established ranges. The release of invaders from their specialist antagonists in invaded areas underpins improved performances as compared with populations within the original range, and thus constitutes a key factor promoting the invasion process (Keane & Crawley, 2002). Range dynamics themselves are likewise affected by biotic interactions, since the absence of competitors allows pioneer populations at advancing range margins to reproduce and expand exponentially, whereas populations entering already occupied areas can only reproduce logistically and advance much slower (Ibrahim et al., 1996). Finally, many plant species rely on animals for seed dispersal and could not shift their ranges without them. Although seed dispersal mutualisms are typically not species-specific, some dispersers have probably contributed to shape major Holocene range expansions, such as the extirpated passenger pigeon (Ectopistes migratorius) in the case of North American nut-producing trees (Webb, 1986). These four examples illustrate that diverse biotic interactions may indeed influence species’ range dynamics over coarse geographical scales.
ADAPTIVE GENETIC VARIATION
BEM treat individual species as evolutionarily homogeneous and unchangeable entities across their range, arguing that the tolerance range of a species evolves too slowly to affect range shifts occurring over a few decades. Rapid in situ adaptations in response to climate change appear indeed to be a rare phenomenon, as Pearson & Dawson (2003) underline. However, the existing adaptation of populations to local environmental conditions and the resulting geographical mosaic of adaptive genetic variation challenge the BEM approach much more (Jansson & Dynesius, 2002; see also Davis & Shaw, 2001). Rear edge populations are adapted to perform in environments that are often only marginally suitable for populations from other parts of the range, while high-latitude populations tend to be vagile generalists (Jansson & Dynesius, 2002; see Hampe & Bairlein, 2000; Santamaría et al., 2003; and references therein for case studies). BEM that simply project the climatic tolerance of current rear edge populations to construct future low-latitude range limits assume inherently that these will be formed by descendants of populations from the current range periphery. This would require that peripheral populations migrate fast enough to match climate change while outcompeting previously existing conspecifics on the migration route and conserving their genetic makeup sufficiently unchanged that they maintain their previous climate tolerance. This is obviously far from realistic. It appears more likely instead that most rear edge populations will go extinct, the overall climatic tolerance of species will therefore decline and their ranges will shrink more towards higher latitudes or altitudes than predicted by BEM.
BEM ignore completely that a limited dispersal capacity may constrain future migrations of species, whereas ample ecological and phylogeographical research has underlined its key role for population and range dynamics (Cain et al., 2000; Clark et al., 2001; Jansson & Dynesius, 2002; Hampe et al., 2003). Again, a clear difference exists between populations at expanding and at retreating range margins. In the first case, changing climate increases both population fecundity and the availability of suitable establishment sites across the landscape. Both factors contribute significantly to reduce dispersal limitation. In contrast, populations at rear edges undergo successive fecundity declines, and they become highly isolated within a matrix of unsuitable habitats, so colonization events and any latitudinal migration are extremely unlikely. Phylogeographical studies show that many glacial refugia separated by only a few hundred kilometres have experienced no tangible gene flow over multiple glacial cycles, although the climatic conditions were often more favourable for population expansions and interchanges than today (Hampe et al., 2003; Petit et al., 2003). Moreover, many extant temperate European plant species have recovered their current distribution ranges from only some of their glacial refugia, while others did not contribute to the recolonization due to geographical dispersal barriers (Hewitt, 2000). Numerous species have expanded much more slowly than their climatic requirements would have allowed them or did not arrive to expand at all into formerly glaciated areas during the Holocene, yet they had been present there during previous interglacial periods (Huntley, 1990; Hewitt, 2000). In conclusion, past range shifts were less deterministic and predictable than current distribution ranges — formed after a period of relative climate stability — may suggest.
Pearson & Dawson (2003) see the realism of BEM corroborated, because these tend to detect a high concordance between simulated and real species distributions. However, present-day ranges have developed under conditions different from those that species will presumably have to face during the coming decades. For instance, both the speed of anticipated climate change and the level of habitat fragmentation are unprecedented, and their interaction severely threatens population survival and mobility (Davis & Shaw, 2001; Hannah et al., 2002; Travis, 2003). It is doubtful to what degree past range shifts can serve to allow inference of future shifts: high model fits with current ranges do not guarantee high model realism.
Moreover, the statistical methods used to date for model validation systematically overestimate the fit achieved by BEM because spatial autocorrelation exists when a given value of a variable at a given point can be predicted from its values at other points of known position. It is an inherent feature of species’ distributions across spatial scales (Koenig, 1999; Legendre et al., 2002), and climate is likewise autocorrelated over distances of up to thousands of km (Koenig, 2002). Spatially autocorrelated data are not mutually independent, and statistics that ignore this fact produce inflated type I errors as a result of pseudoreplication (Legendre et al., 2002). This means, in the present case, that model fits increase systematically with increasing size and continuity of species’ ranges: they are statistically biased. Various statistical treatments have been developed to deal with spatially autocorrelated data (Koenig, 1999; Keitt et al., 2002; Perry et al., 2002), and these need to be incorporated into BEM validations.
Anthropogenic climate change is a major threat for the maintenance of biological diversity during the coming decades, and modelling is a crucial tool for evaluating its impact. Pearson & Dawson (2003) suggest using BEM as a first approximation, but the multiple drawbacks of this approach are likely to produce more ‘wildly incorrect’ predictions than Pearson & Dawson (2003) assume. Midgley et al. (2002) provide an illustrative example of how missing criticial detail within BEM may lead to overly optimistic predictions about the maintenance of species and within-species genetic diversity in a biodiversity hotspot. The study demonstrates that future conservation strategies require models that incorporate more detail and attain greater biological realism than BEM can (so far) provide (Hannah et al., 2002).
Comments from Rémy Petit improved an earlier version of this manuscript.
|Arndt Hampe is interested in the evolutionary ecology of temperate woody plants. He is currently doing his PhD on the reproductive biology, demography and Quaternary phylogeography of the shrub Frangula alnus (Rhamnaceae).|