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Local and system-wide adaptation is influenced by population connectivity

  • Patrik NosilEmail author
  • Víctor Soria-Carrasco
  • Jeffrey L. Feder
  • Samuel M. Flaxman
  • Zach Gompert
Research Article

Abstract

Complex systems can be conceptualized and studied as networks of nodes with varying connectivity between nodes. In well-connected systems, local disturbance of individual nodes can be countered by input from neighbouring nodes, buffering the system against local change. Thus, pronounced change in a well-connected system may not occur until the system hits a threshold or ‘tipping point’ that drives a shift to an alternative, system-wide state. In contrast, poorly connected systems are more prone to gradual node-by-node change. We use forward-in-time simulations of multi-locus evolution to test these general predictions concerning complex systems. We do so in the context of local adaptation in patchy environments comprised of many demes (i.e., nodes) of two habitat types. We vary connectivity by manipulating migration rate and the spatial clustering of habitat types. We find gradual and ‘deme-by-deme’ dynamics of local adaptation when connectivity is low. The dynamics transition towards more sudden, system-wide shifts as population connectivity is increased (i.e., many demes adapt more suddenly and simultaneously). Our results support a trade-off between local and system-wide resilience, and we discuss their implications for the conservation of species living in patchy and fragmented habitats.

Keywords

Adaptation Evolution Fragmentation Migration Systems biology Tipping point 

Notes

Acknowledgements

The work was funded by a grant from the H2020 European Research Council (NatHisGen R/129639) to PN, a Royal Society University Research Fellowship to PN, a Leverhulme Trust Early Career Fellowship to VSC, a National Science Foundation grant to JFL, a United States Department of Agriculture NIFA grant to JLF, a National Science Foundation Grant to SMF (DEB 1627483), and a National Science Foundation Grant to ZG (DEB 1638768). The support and resources from the Center for High Performance Computing at the University of Utah are gratefully acknowledged. We thank Rus A. R. Hoelzel and the organizers of the workshop on Conservation of Adaptive Potential and Functional Diversity that took place the 14–15th September in Durham, UK, as well as this special issue.

Supplementary material

10592_2018_1097_MOESM1_ESM.pdf (1.6 mb)
Supplementary material 1 (PDF 1682 KB)

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Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  1. 1.Department of Animal and Plant SciencesUniversity of SheffieldSheffieldUK
  2. 2.Department of BiologyUtah State UniversityLoganUSA
  3. 3.Department of Biological SciencesUniversity of Notre DameNotre DameUSA
  4. 4.Department of Ecology and Evolutionary BiologyUniversity of ColoradoBoulderUSA

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