How should we approach downscaling models to predict the habitats within the future ranges of species where populations will colonize at the leading edge of an expanding range, or persist at the trailing edge? We favour a hierarchical and mechanistic modelling framework () that focuses on key processes involved in the environmental filters that determine range-wide distribution (γ-niche dimensions) and then the sometimes different processes that determine habitat selection (β-niche dimensions). Decisions on the focal processes in the model need to consider constraints that operate at different life stages including dispersal and seedling establishment (Grubb 1977
) as well as adult survival and reproduction, because early life stages are likely to be particularly sensitive to climate change (Svensson et al
. 2005, referenced in the electronic supplementary material 1). The mechanistic modelling of range-wide distributions in this hierarchical framework has begun, but needs to be refined and extended to predictions at the scale of the β-niche.
Figure 1 A conceptual framework for building species distribution models that predict occurrence in specific habitats in regions within the continental range, i.e. models to scale down from the (a) γ- (crosses, extinction; circles, possible colonization) (more ...)
The framework we propose () requires assessing the influence of traits affecting the distribution at continental versus regional scales, i.e. discriminating among possible γ- and β-traits. The mapped ecoregions of the world (Olson et al. 2001, referenced in the electronic supplementary material 1) provide a framework for doing so. The ecoregions are characterized by an assemblage of communities and species that interact dynamically in the context of environmental conditions within a geographically coherent landscape. A γ-trait would facilitate predicting in which ecoregions a species might be found. For instance, a parameter such as foliar resistance to late spring frosts can predict exclusion of a given species in an ecoregion based on seasonal temperature regimes that fall wholly outside the tolerance of the species (γ-niche, ). In ecoregions where a species is predicted to occur, a binary γ-trait such as frost tolerance can also play a significant secondary role as quantitative β-trait (i.e. degree of frost tolerance) acting through microclimatic temperature regimes to predict occurrence in different habitats along topographic gradients (β-niche). On the other hand, the ability to fix nitrogen might be a β-trait critical in predicting habitat selection within the ecoregions but insignificant in predicting occurrence in different ecoregions.
At the continental scale, it is most often γ-traits associated with climate that set limits on the distribution (Morin et al. 2007
). PHENOFIT (described in the electronic supplementary material 2) is an example of a mechanistic niche model that uses processes associated with survival and reproduction in seasonal environments to decide the fundamental climatic niche for a species, and then predict the γ-niche under current (Morin et al. 2007
) or future climate regimes (Morin et al. in press
). In our hierarchical modelling perspective, existing models such as PHENOFIT or LPJ-GUESS (Hicker et al
. 2004, referenced in the electronic supplementary material 1) can and should be scaled down to the level of the β-niche. Once an analysis at the level of the γ-niche places a species in an ecoregion within its continental range, then the processes defining the fundamental β-niche of the species must be assessed to decide its realized β-niche in that ecoregion (). Macroclimatic factors that define the γ-niche can also scale down as β-traits influencing the distribution of species along regional or local environmental gradients (Ackerly & Cornwell 2007
). For example, species in an ecoregion at their northern range edge are restricted to ridge habitats where their seedling tolerance of chilling due to cold-air drainage into downslope habitats is avoided. Ideally a fundamental β-niche model should be strictly process-based, although for some species the relevant β-traits may be as simple as tolerance of a peculiar soil type (calciphilic species) or strong dependence on a seasonal water regime (obligate wetland species). Similar categorical simplifications may be helpful in modelling the complex processes associated with life stage and colonization dynamics, which are natural foci in terms of range shifts under climate change (Thuiller et al. 2008
). Recent work shows that process-based modelling on seed dispersal and seedling establishment is feasible (Lischke et al
. 2006, referenced in the electronic supplementary material 1), and there is no reason that biotic effects cannot also be considered in modelling the realized β-niche.
In closing we note that developing and parametrizing process-based models in this hierarchical framework () requires pilot sites with characteristics such as those at the Gault Nature Reserve (www.mcgill.ca/gault/
). The reserve lies in the transition zone between two major biomes, the boreal and deciduous forests of eastern North America; both the leading and trailing edges of range shifts therefore are observable. The local topography is rugged, leading to a wide range of habitats and microenvironmental conditions in a relatively small area; environmental and biotic gradients within the reserve are well characterized, facilitating quantification of the β-niche. Finally, this site is protected and longitudinal and experimental studies can be carried out with minimal disruption. Using species at such pilot sites to develop and test hierarchical models in the framework that we discuss here should yield better predictions of the species distribution under climate change as well as advancing contemporary perspectives on the ecological niche.