The stability of climatic niches through time
The climatic niches of species are potentially the result of inheriting the climatic niches of their ancestors, and the result of adaptation of species to past and current climatic conditions that allow them to persist. One of the main theoretical assumptions for transferring the projections of CEMs through time is the temporal stability of climatic niches, hereafter called niche stability. We should not confuse niche stability through time with the concept of niche conservatism. Niche conservatism (Harvey & Pagel, 1991) refers to closely related species within a phylogenetic tree that are more ecologically similar than would be expected based on their phylogenetic relationships (Losos, 2008a). On the contrary, niche stability only takes into account the similarity of the climatic conditions that allows a single species to persist through time. Thus, the main theoretical assumption behind CEMs should not be phylogenetic niche conservatism (PNC) but niche stability of species through time, although PNC can provide support for niche stability. Finding PNC among phylogenetically closely related species indicates that their current niches are similar (Peterson et al., 1999; Prinzing et al., 2001), and it is assumed that their niches have also remained similar to one another in evolutionary time. However, many clades do not exhibit PNC for some ecological traits (Losos, 2008a; but see also Wiens, 2008; Losos, 2008b) and we need more research to assess the generality of PNC. Using large datasets on species distributions, climatic conditions and phylogenetic trees, we should assess not simply whether there is niche conservatism overall, but which climatic axes contribute to PNC and which ones do not.
CEMs assume non-significant evolutionary or/and ecological change in a species niche as a response to changing environmental conditions along time (Fig. 1). However, evidence suggests that niche shifts have occurred for many species (Pearman et al., 2008b), implying a questionable ability of CEMs to project climatic niches to past periods. For example, niche shifts could be the result of genetic variation for traits related to climate performance (Skelly et al., 2007; Ebeling et al., 2008), a change in the fundamental niche, or because of competition with different species during different periods of time. Whether niche shifts are a general pattern or not may well be a scale-dependent phenomenon. For example, ecological mechanisms such as competitive displacement or environmental tolerance that trigger niche shifts at a local scale might be non-significant at a regional or a continental scale (Prinzing et al., 2002). An unanswered question is whether the temporal scale (100 years, 10,000 years or 1,000,000 years) used in each study underlies the conflicting findings about PNC and niche stability, as recently suggested by A. T. Peterson (personal communication, 2009).
Figure 1. Alternative niche shift scenarios and their implications for projecting climatic niches through time. Both panels A and B represent niches in environmental space (CF1, climatic factor 1; CF2, climatic factor 2). Panel A shows the fundamental niche of a hypothetical species X (dotted circle) and the location of the same species (realized niche; plus signs). Parts (a) and (b) show a change in the fundamental and in the realized niche because of an evolutionary change. Parts (c) and (d) show no change in the fundamental niche but a change in the realized niche because of a different set of species competing for the resources (black arrows represent the competition). Panel B duplicates panel A but including a modelled climatic envelope (grey circles). Climatic envelopes are calibrated at current conditions and projected to past conditions. Niche shifts would imply a scarce degree of temporal transferability and therefore a challenge to be resolved in studies predicting the past distribution of species climatic niches.
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The challenges of modelling species climatic niches for past periods of time have been highlighted in recent review papers (Belyea, 2007; Richards et al., 2007; Kozak et al., 2008) and also in many of the case studies reviewed here. However, only 22% of the studies I examined quantitatively assess the assumption of niche stability. Their approaches for testing niche shifts along time are still in their infancy, but they are a promising starting point. For example, Martínez-Meyer et al. (2004) and Martínez-Meyer & Peterson (2006) assessed the ability of ecological niches, as modelled in one time period, to predict the distribution of the climatic niche of species in another period, and vice versa. Peterson and Nyári (2008) proposed a test using information on lineage membership of particular populations of Schiffornis turdina in the Neotropics. They developed genetic algorithm for rule set production (GARP) models based on all seven possible sets of six phylogroups, and tested the ability of each replicate model to anticipate the geographical distribution of the climatic niches of a seventh phylogroup. Pearman et al. (2008a) used multivariate techniques to estimate changes in the niche position of tree species in Europe between the mid-Holocene and the present. Rodríguez-Sánchez & Arroyo (2008) qualitatively assessed the ecological niche conservatism of Laurus, comparing climatic response curves for past and present conditions. Nogués-Bravo et al. (2008a) tested for differences between the climatic conditions occupied by the woolly mammoth using fossil records at three time periods during the late Pleistocene; this test was performed in environmental space, which aids our understanding of changes in the climatic niche of species through time.
A new method for evaluating niche stability is to use metrics that have previously been used to quantify PNC. In a recent paper (Warren et al., 2008), different metrics were proposed to quantify niche overlap between sister species. Taking the metrics in Warren et al. (2008) and changing species X and Y for time periods t1 and t2 would allow one to test the niche stability of a single species X. This approach would require information about the distribution of the analysed species and climate conditions for more than one time period (i.e. the current distribution of a species, and the distribution of dated fossil records of the same species for past periods). Fossil records may be a biased representation of the past distribution of any species, but the approach of Warren and colleagues may overcome this challenge with a randomization procedure that reduces bias in the sampling of each species with respect to environmental tolerances.
CEMs assume equilibrium between species distribution and the climate. Species are said to be at equilibrium with climate if they occur in all climatically suitable areas whilst being absent from all unsuitable ones (sensuAraújo & Pearson, 2005). Failure to colonize suitable areas is related to the dispersal ability of species and to biotic interactions. We currently know, for example, that many European tree species are not in equilibrium with climate (Svenning & Skov, 2004) as a consequence of post-glacial dispersal limitations (Svenning et al., 2008b), and that this dispersal limitation also affects the patterns of species richness of different taxa (Svenning & Skov, 2007; Araújo et al., 2008). Among the possible set of biotic interactions, human impacts play a key role in shaping the distribution of species (Channel & Lomolino, 2000) and in species richness (Nogués-Bravo et al., 2008b); therefore human impacts on biodiversity are one of the key factors affecting equilibrium between species distribution and the climate. We need more research to increase our understanding of the role of humans in competitive displacement. Specifically, it is of the utmost importance to assess human-induced contractions or expansions of species ranges for as many species as possible. A potential framework to deal with this assessment (Channel & Lomolino, 2000) is to reconstruct the historical ranges of species and to relate them to human impacts. Thus, we urgently need to develop detailed spatial data for both humans and other species concerning their past distributions, population densities for different historical moments and the intensity of different waves of colonization.
In summary, climate predictions through time may well be seriously misleading because of the possible lack of equilibrium between species distributions and climate in many different taxa. Therefore we should establish approaches to assess the degree of this equilibrium. However, new evidence indicates that even when model results suggest a climatic equilibrium for a species' distribution, the time transferability of niche models does not necessarily provide realistic results (Varela et al., 2009). I suggest two potential ways to deal with the challenge of equilibrium between species distributions and climate for hindcasting or forecasting CEMs. The first one is to hindcast only those species that are in equilibrium or near to equilibrium with climate. A proxy metric to measure equilibrium between species distributions and climate is range filling (Svenning & Skov, 2004), the realized/potential range size ratio (R/F). Because different model classes may well produce completely different potential range sizes (Pearson et al., 2006), a consensus approach (Araújo et al., 2005) may be a robust option for measuring R/F. The second way is to implement key population processes, such as dispersal and/or local extinction (see De Marco et al., 2008), which affect the degree of equilibrium between species distributions and climate. Implementing these processes for hindcasting species climatic niches will allow us, on the one hand, to simulate colonization and local extinctions, and therefore to increase the reliability of the projections through time. On the other hand, hindcasting species climatic niches including colonization and local extinctions for species with a good record of fossil remains will allow us to validate the accuracy of these novel methods to improve projections through time. In this sense, hindcasting species climatic niches for those species with a good fossil record would be an apt arena for validating and improving CEMs. Some meritorious advances in niche modelling have incorporated dispersal. Iverson et al. (2004) combined a habitat model with a model of habitat colonization for predicting the future distribution of tree species in North America using cellular automata (but see Thuiller et al., 2008, for a list of some limitations of this kind of approach). Also using cellular automata, range expansion and contractions (De Marco et al., 2008) may be simulated based on local colonization and extinction constrained by local climatic suitability.
There is solid evidence of the occurrence of non-analogous fossil assemblages in Quaternary palaeoecological records (Jackson & Williams, 2004; Williams & Jackson, 2007). These non-analogous communities might be related to the occurrence of non-analogous climate conditions in the past, and to the idiosyncratic responses of each species to climate change because of their unique genetic heritage, their own physiological traits and the different pool of competing species (Graham & Grimm, 1990); but see (Lyons, 2003). Calibrating the climatic niche of species under current conditions and projecting them to non-analogous conditions in the past would lead to spurious response curves and therefore to naïve projections (Thuiller et al., 2004). However, only one of the studies reviewed herein assessed the occurrence of non-analogous climate conditions for the time periods used to project the climatic niches (Fløjgaard et al., 2009). One way to deal with this problem is to calibrate the niche of species using fossil records and palaeoclimatic reconstruction across different time periods, a multi-temporal calibration approach, and then to project this multi-temporal climatic niche to the same periods used to calibrate the model (Nogués-Bravo et al., 2008a). Another way is to assess the geographical distribution of non-analogous climates, as has been done to assess the potential occurrence of non-analogous climates in the future (Ohlemüller et al., 2004; Williams et al., 2007). Delimiting the geographical distribution of non-analogous climate conditions may well clarify the credibility of the projections across the study region.
Finally, projecting the climatic niche of species to past or future periods is not projecting the distribution of species. The realized niche of species and the geographical area occupied by this realized niche are the result of the interaction of mechanisms operating at large scales (Grinnellian niche) and small scales such as, for example, biotic interactions (Eltonian niche). The studies I have reviewed tend to confound the climatic niche with the distribution of the species and this confusion has profound implications for interpreting their results.
One of the most striking challenges of CEMs is to validate the projections of the climatic niches using independent data (Araújo et al., 2005). The standard approach to validate a model in the research field of CEMs is to split the current distribution of the species into two sets: one for calibrating the model and one for validating it. Unfortunately, this approach is also the favourite of the reviewed studies. Only 30% of the studies use independent data to quantitatively validate the projections (Table 1). One potential way to independently validate a model is to use the location of refugia that have been identified based on phylogeographical analyses, and using CEM tools to make parallel predictions (Waltari et al., 2007). A second method is to quantitatively assess the proportion of fossil occurrences of modelled species within the projected climatic niche of modelled species (Martínez-Meyer et al., 2004; Waltari & Guralnick, 2009). A third method, for animal species with well-studied habitat conditions, would be to use dated pollen records as an independent source of information. For example, the use of the treeline in Eurasia, based on pollen records (MacDonald et al., 2000), was recently used to validate the climatic niche of the woolly mammoth (Nogués-Bravo et al., 2008a).