4.6 Article

Identifying robust strategies for assisted migration in a competitive stochastic metacommunity

期刊

CONSERVATION BIOLOGY
卷 35, 期 6, 页码 1809-1820

出版社

WILEY
DOI: 10.1111/cobi.13736

关键词

climate change; community ecology; dispersal; managed relocation; stochastic model; translocation; cambio climatico; dispersion; ecologia comunitaria; modelo estocastico; reubicacion gestionada; translocacion

资金

  1. National Science Foundation [1655475]
  2. Direct For Biological Sciences [1655475] Funding Source: National Science Foundation
  3. Division Of Environmental Biology [1655475] Funding Source: National Science Foundation

向作者/读者索取更多资源

The study suggests that when deciding to conduct assisted migration, choosing species with certain traits for relocation and leaving behind a portion of the population for potential repeat translocation can increase the long-term persistence of the species. Additionally, assisted migration benefits species with low dispersal ability, but may increase extinction risk for species with narrow thermal tolerances.
Assisted migration (AM) is the translocation of species beyond their historical range to locations that are expected to be more suitable under future climate change. However, a relocated population may fail to establish in its donor community if there is high uncertainty in decision-making, climate, and interactions with the recipient ecological community. To quantify the benefit to persistence and risk of establishment failure of AM under different management scenarios (e.g., choosing target species, proportion of population to relocate, and optimal location to relocate), we built a stochastic metacommunity model to simulate several species reproducing, dispersing, and competing on a temperature gradient as temperature increases over time. Without AM, the species were vulnerable to climate change when they had low population sizes, short dispersal, and strong poleward competition. When relocating species that exemplified these traits, AM increased the long-term persistence of the species most when relocating a fraction of the donor population, even if the remaining population was very small or rapidly declining. This suggests that leaving behind a fraction of the population could be a robust approach, allowing managers to repeat AM in case they move the species to the wrong place and at the wrong time, especially when it is difficult to identify a species' optimal climate. We found that AM most benefitted species with low dispersal ability and least benefited species with narrow thermal tolerances, for which AM increased extinction risk on average. Although relocation did not affect the persistence of nontarget species in our simple competitive model, researchers will need to consider a more complete set of community interactions to comprehensively understand invasion potential.

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