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

TLDR

Bioclimate envelope models have been used to predict species distribution changes under climate change, but critics argue that non‑climatic factors such as biotic interactions, evolution, and dispersal also shape distributions. The authors review criticisms of bioclimate envelope models and argue that, while limited, they can still provide a useful first approximation of climate change impacts, and they propose a hierarchical modelling framework to mitigate these limitations. They evaluate criticisms and propose a hierarchical, scale‑dependent modelling framework that incorporates additional factors to address the limitations of bioclimate envelope models. The authors emphasize that model results must be interpreted with caution, noting that spatial scale is crucial and that limitations must be considered.

Abstract

ABSTRACT 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.