Predicting current and future biological invasions: both native and invaded ranges matter

The classical approach to predicting the geographical extent of species invasions consists of training models in the native range and projecting them in distinct, potentially invasible areas. However, recent studies have demonstrated that this approach could be hampered by a change of the realized climatic niche, allowing invasive species to spread into habitats in the invaded ranges that are climatically distinct from those occupied in the native range. We propose an alternative approach that involves fitting models with pooled data from all ranges. We show that this pooled approach improves prediction of the extent of invasion of spotted knapweed (Centaurea maculosa) in North America on models based solely on the European native range. Furthermore, it performs equally well on models based on the invaded range, while ensuring the inclusion of areas with similar climate to the European niche, where the species is likely to spread further. We then compare projections from these models for 2080 under a severe climate warming scenario. Projections from the pooled models show fewer areas of intermediate climatic suitability than projections from the native or invaded range models, suggesting a better consensus among modelling techniques and reduced uncertainty.     

Biotic attrition from tropical forests correcting for truncated temperature niches

Species migration in response to warming temperatures is expected to lead to ‘biotic attrition,’ or loss of local diversity, in areas where the number of species emigrating or going locally extinct exceeds the number immigrating. Biotic attrition is predicted be especially severe in the low‐lying hot tropics since elevated temperatures may surpass the observed tolerances of most extant species. It is possible, however, that the estimated temperature niches of many species are inaccurate and truncated with respect to their true tolerances due to the absence of hotter areas under current global climate. If so, these species will be capable of persisting in some areas where future temperatures exceed current temperatures, reducing rates of biotic attrition. Here, we use natural history collections data to estimate the realized thermal niches of > 2000 plant species from the tropical forests of South America. In accord with the truncation hypothesis, we find that the thermal niches of species from hot lowland areas are several degrees narrower than the thermal niches of species from cooler areas. We estimate rates of biotic attrition for South American tropical forests due to temperature increases ranging from 1 to 5 °C, and under two niche assumptions. The first is that the observed thermal niches truly reflect the plant's tolerances and that the reduction in niche breadth is due to increased specialization. The second is that lowland species have the same mean thermal niche breadth as nonlowland and nonequatorial species. The differences between these two models are dramatic. For example, using observed thermal niches we predict an almost complete loss of plant diversity in most South American tropical forests due to a 5 °C temperature increase, but correcting for possible niche truncation we estimate that most forests will retain > 50–70% of their current species richness. The different predictions highlight the importance of using fundamental vs. realized niches in predicting the responses of species to global climate change.     

Modelled spatial distribution of marine fish and projected modifications in the North Atlantic Ocean

The objectives of this work were to examine the past, current and potential influence of global climate change on the spatial distribution of some commercially exploited fish and to evaluate a recently proposed new ecological niche model (ENM) called nonparametric probabilistic ecological niche model (NPPEN). This new technique is based on a modified version of the test called Multiple Response Permutation Procedure (MRPP) using the generalized Mahalanobis distance. The technique was applied in the extratropical regions of the North Atlantic Ocean on eight commercially exploited fish species using three environmental parameters (sea surface temperature, bathymetry and sea surface salinity). The numerical procedure and the model allowed a better characterization of the niche (sensu Hutchinson) and an improved modelling of the spatial distribution of the species. Furthermore, the technique appeared to be robust to incomplete or bimodal training sets. Despite some potential limitations related to the choice of the climatic scenarios (A2 and B2), the type of physical model (ECHAM 4) and the absence of consideration of biotic interactions, modelled changes in species distribution explained some current observed shifts in dominance that occurred in the North Atlantic sector, and particularly in the North Sea. Although projected changes suggest a poleward movement of species, our results indicate that some species may not be able to track their climatic envelope and that climate change may have a prominent influence on fish distribution during this century. The phenomenon is likely to trigger locally major changes in the dominance of species with likely implications for socio‐economical systems. In this way, ENMs might provide a new management tool against which changes in the resource might be better anticipated.     

Phylogeography and species biogeography of montane Great Basin stoneflies

Sky islands are ideal systems for determining the effects of climatic oscillations on species distributions and genetic structure. Our study focused on montane stonefly populations in the Great Basin of western North America. We used niche-based distribution modelling, phylogeography and traditional species-based biogeography to test several hypotheses as follows: (i) genetic differentiation among Doroneuria baumanni populations will be independent of hydrologic connectivity (headwater model); (ii) Sky islands were colonized when habitat was more continuous and populations likely experienced multiple expansions and contractions; (iii) Colonization events were coincident with the late Pleistocene and Holocene; and (iv) Shared topography and climate history will result in concordant patterns of genetic differentiation in D. baumanni and occurrences of 32 stonefly species across the region. Overall, Φ(ST) 's and coalescent-based estimates of migration were consistent with the headwater model. Maximum likelihood and Bayesian gene trees identified three major nonoverlapping east-west clades. Distribution modelling indicated more suitable habitat in the Great Basin during the Last Glacial Maximum than at present, but none during the last interglacial period. Demographic analyses showed evidence of population expansion in one of the three major east-west clades. Intra-clade divergence times (60,000-183,000ybp) were well within the late Pleistocene while among-clade divergence times (499.000-719,000ybp) were deeper. Genetic differentiation in D. baumanni and distributions of stonefly species were significantly concordant. These results imply that climatic oscillations have played major roles in shaping the genetic structure and distributions of Great Basin stoneflies, but that divergence among clades occurred much earlier than our late Pleistocence/early Holocene predictions.     

Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful?

Modelling strategies for predicting the potential impacts of climate change on the natural distribution of species have often focused on the characterization of a species’ bioclimate envelope. A number of recent critiques have questioned the validity of this approach by pointing to the many factors other than climate that play an important part in determining species distributions and the dynamics of distribution changes. Such factors include biotic interactions, evolutionary change and dispersal ability. This paper reviews and evaluates criticisms of bioclimate envelope models and discusses the implications of these criticisms for the different modelling strategies employed. It is proposed that, although the complexity of the natural system presents fundamental limits to predictive modelling, the bioclimate envelope approach can provide a useful first approximation as to the potentially dramatic impact of climate change on biodiversity. However, it is stressed that the spatial scale at which these models are applied is of fundamental importance, and that model results should not be interpreted without due consideration of the limitations involved. A hierarchical modelling framework is proposed through which some of these limitations can be addressed within a broader, scale‐dependent context.