Evolutionary genomics can improve prediction of species' responses to climate change

Abstract

Global climate change (GCC) increasingly threatens biodiversity through the loss of species, and the transformation of entire ecosystems. Many species are challenged by the pace of GCC because they might not be able to respond fast enough to changing biotic and abiotic conditions. Species can respond either by shifting their range, or by persisting in their local habitat. If populations persist, they can tolerate climatic changes through phenotypic plasticity, or genetically adapt to changing conditions depending on their genetic variability and census population size to allow for de novo mutations. Otherwise, populations will experience demographic collapses and species may go extinct. Current approaches to predicting species responses to GCC begin to combine ecological and evolutionary information for species distribution modelling. Including an evolutionary dimension will substantially improve species distribution projections which have not accounted for key processes such as dispersal, adaptive genetic change, demography, or species interactions. However, eco-evolutionary models require new data and methods for the estimation of a species' adaptive potential, which have so far only been available for a small number of model species. To represent global biodiversity, we need to devise large-scale data collection strategies to define the ecology and evolutionary potential of a broad range of species, especially of keystone species of ecosystems. We also need standardized and replicable modelling approaches that integrate these new data to account for eco-evolutionary processes when predicting the impact of GCC on species' survival. Here, we discuss different genomic approaches that can be used to investigate and predict species responses to GCC. This can serve as guidance for researchers looking for the appropriate experimental setup for their particular system. We furthermore highlight future directions for moving forward in the field and allocating available resources more effectively, to implement mitigation measures before species go extinct and ecosystems lose important functions.

Keywords: Biodiversity loss; eco‐evolutionary dynamics; genomic quantitative genetics; models.

Figure 1

Graphical outline of how biodiversity can respond to changing environmental conditions under GCC, how to investigate these mechanisms, and how different types of empirical data can be used for predicting biodiversity responses to climate change (read from centre to top, then from centre to bottom). Sections in red highlight the connection of genomic and ecological data as basis for eco‐evolutionary modelling as most promising strategy to generate predictions for a relevant proportion of biodiversity fast enough to meet the accelerating pace of GCC. For a final implementation of this strategy, there is further demand for the development of tools to reliably estimate fitness from cohort/time‐series data. Predictions of how biodiversity responds to GCC are fundamental to urgently needed strategies for ecosystem management and conservation in order to counter‐act the imminent loss of biodiversity, ecosystem functioning, and ecosystem services.

Figure 2

Outline of our proposed mode of action to collect, store, and analyse eco‐evolutionary data as a joint venture of citizens and scientists. A comprehensive database can then support eco‐evolutionary modelling to predict biodiversity responses to GCC. These predictions will provide government and society with educated recommendations in order to take significant actions for conservation.