PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
June 1, 2026Trends in Ecology & Evolution0 citationsOpen Access

Revisiting evolutionary rescue in the wild

View Full Paper
LBLaurinne J. BalstadMBMarissa L. BaskettSCStephanie M. Carlson

Key Points

  • This research aims to explore how evolution can help populations survive in changing environments through evolutionary rescue methods.
  • Examined various lines of evidence for evolutionary rescue in natural populations.
  • Analyzed the relationship between environmental stress, genetic diversity, and adaptive traits.
  • Identified traits and pathways that facilitate evolutionary rescue across different ecosystems.
  • Found that reducing environmental stress significantly enhances the chances of evolutionary rescue.
  • Maintaining genetic diversity and protecting adaptive alleles were crucial for successful outcomes.
  • Demonstrated that evolution can play a significant role in mitigating extinction risks under environmental change.

Abstract

Environmental change is rapidly occurring. Theoretical and experimental work predicts that evolution can facilitate population persistence in novel and changing environments evolutionary rescue (ER). Recent examples now allow for testing foundational ER hypotheses in wild systems. We propose a more nuanced view for identifying ER by emphasizing the probabilistic role of evolution in reducing extinction risk through the examination of multiple lines of evidence. Using this approach, we identify a range of evolving traits, evolutionary pathways, and population outcomes from ER. Across systems, reducing environmental stress, maintaining genetic diversity, and protecting adaptive alleles can facilitate ER when relevant and desirable. The ways population-level ER might affect higher levels of biological organization and ecosystem resilience likely constitute the next chapter in understanding ER.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Balstad et al. (2026) studied this question.

synapsesocial.com/papers/6a1d230d02fbce9130638c59https://doi.org/10.1016/j.tree.2026.04.015
Ask AI
Helpful
Bookmark
Share
View Full Paper