open access publication

Article, 2020

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

Evolution Letters, ISSN 2056-3744, Volume 4, 1, Pages 4-18, 10.1002/evl3.154

Contributors

Waldvogel, Ann-Marie 0000-0003-2637-0766 [1] Feldmeyer, Barbara 0000-0002-0413-7245 [1] Rolshausen, Gregor 0000-0003-1398-7396 [1] Exposito-Alonso, Moises 0000-0001-5711-0700 [2] Rellstab, Christian 0000-0002-0221-5975 [3] Kofler, Robert 0000-0001-9960-7248 [4] Mock, Thomas 0000-0001-9604-0362 [5] Schmid, Karl J 0000-0001-5129-895X [6] Schmitt, Imke 0000-0002-7381-0296 [1] [7] [8] Bataillon, Thomas Martin Jean 0000-0002-4730-2538 [9] Savolainen, Outi A 0000-0001-9851-7945 [10] Bergland, Alan Olav [11] Flatt, Thomas 0000-0002-5990-1503 [12] Guillaume, Frédéric 0000-0003-0874-0081 [13] Pfenninger, Markus Markus 0000-0002-1547-7245 [1] [8] [14]

Affiliations

  1. [1] Senckenberg Biodiversity and Climate Research Centre
  2. [NORA names: Germany; Europe, EU; OECD];
  3. [2] Department of Plant Biology Carnegie Institution for Science Stanford California
  4. [3] Swiss Federal Institute for Forest, Snow and Landscape Research
  5. [NORA names: Switzerland; Europe, Non-EU; OECD];
  6. [4] University of Veterinary Medicine Vienna
  7. [NORA names: Austria; Europe, EU; OECD];
  8. [5] University of East Anglia
  9. [NORA names: United Kingdom; Europe, Non-EU; OECD];

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

abiotic conditions, adaptive genetic changes, adaptive potential, approach, biodiversity, census, census population size, changes, changing conditions, climate, climate change, collapse, collection strategies, conditions, data, data collection strategies, de novo mutations, demographic collapse, demography, dimensions, direction, dispersion, distributed projects, distribution model, eco-evolutionary model, eco-evolutionary processes, ecology, ecosystem, estimation, evolutionary dimension, evolutionary genomics, evolutionary information, evolutionary potential, experimental setup, field, function, genetic changes, genetic variability, genome, genomic approaches, global biodiversity, global climate change, guidance, habitat, impact, impacts of global climate change, implement mitigation measures, information, interaction, keystone species, local habitat, loss, loss of species, measurements, method, mitigation measures, model, model species, modeling approach, mutations, pacing, phenotypic plasticity, plasticity, population, population size, potential, prediction, predictions of species’ responses , process, project, range, research, resources, response, setup, size, species, species distribution models, species interactions, species of ecosystems, species responses, species survival, species' adaptive potential., strategies, survival, system, transformation, variables

Funders

  • Deutsche Forschungsgemeinschaft
  • Swiss National Science Foundation

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