@Article{Fronhofer2023,
  author       = {Emanuel A. Fronhofer and Dov Corenblit and Jhelam N. Deshpande and Lynn Govaert and Philippe Huneman and Frédérique Viard and Philippe Jarne and Sara Puijalon},
  journal      = {Ecol. Lett.},
  title        = {Eco-evolution from deep time to contemporary dynamics: the role of timescales and rate modulators},
  year         = {2023},
  number       = {S1},
  pages        = {S91--S108},
  volume       = {26},
  abstract     = {Eco-evolutionary dynamics, or eco-evolution for short, are often thought to involve rapid demography (ecology) and equally rapid heritable phenotypic changes (evolution) leading to novel, emergent system behaviours. We argue that this focus on contemporary dynamics is too narrow: Eco-evolution should be extended, first, beyond pure demography to include all environmental dimensions and, second, to include slow eco-evolution which unfolds over thousands or millions of years. This extension allows us to conceptualise biological systems as occupying a two-dimensional time space along axes that capture the speed of ecology and evolution. Using Hutchinson's analogy: Time is the ‘theatre’ in which ecology and evolution are two interacting ‘players’. Eco-evolutionary systems are therefore dynamic: We identify modulators of ecological and evolutionary rates, like temperature or sensitivity to mutation, which can change the speed of ecology and evolution, and hence impact eco-evolution. Environmental change may synchronise the speed of ecology and evolution via these rate modulators, increasing the occurrence of eco-evolution and emergent system behaviours. This represents substantial challenges for prediction, especially in the context of global change. Our perspective attempts to integrate ecology and evolution across disciplines, from gene-regulatory networks to geomorphology and across timescales, from today to deep time.},
  doi          = {10.1111/ele.14222},
  funding      = {ANR JCJC E-SIASH ANR-19-CE02-529-0015},
  hal_id       = {hal-04243257},
  isem_pub_no  = {ISEM-2023-069},
  preprint_doi = {https://doi.org/10.48550/arXiv.2210.12041},
}