Potential sources of time lags in calibrating species distribution models

The Anthropocene is characterized by a rapid pace of environmental change and is causing a multitude of biotic responses, including those that affect the spatial distribution of species. Lagged responses are frequent and species distributions and assemblages are consequently pushed into a disequilibrium state. How the characteristics of environmental change-for example, gradual 'press' disturbances such as rising temperatures due to climate change versus infrequent 'pulse' disturbances such as extreme events-affect the magnitude of responses and the relaxation times of biota has been insufficiently explored. It is also not well understood how widely used approaches to assess or project the responses of species to changing environmental conditions can deal with time lags. It, therefore, remains unclear to what extent time lags in species distributions are accounted for in biodiversity assessments, scenarios and models; this has ramifications for policymaking and conservation science alike. This perspective piece reflects on lagged species responses to environmental change and discusses the potential consequences for species distribution models (SDMs), the tools of choice in biodiversity modelling. We suggest ways to better account for time lags in calibrating these models and to reduce their leverage effects in projections for improved biodiversity science and policy.

Automated summary

The rapid environmental changes in the Anthropocene era have caused shifts in species' spatial distributions, with lagged responses leading to disequilibrium states. The effects of different types of environmental change and time lags on species responses have not been adequately explored, which has implications for biodiversity assessments, scenarios, and models, thus impacting policymaking and conservation science. This perspective piece examines lagged species responses to environmental change and discusses ways to improve the calibration of species distribution models (SDMs) to account for time lags and enhance biodiversity science and policy.