4.5 Article

Is evolution faster at ecotones? A test using rates and tempo of diet transitions in Neotropical Sigmodontinae (Rodentia, Cricetidae)

期刊

ECOLOGY AND EVOLUTION
卷 11, 期 24, 页码 18676-18690

出版社

WILEY
DOI: 10.1002/ece3.8476

关键词

ancestral character mapping; ancestral character reconstruction; macroecology; macroevolution; Neotropics; niche evolution

资金

  1. Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior
  2. Conselho Nacional de Desenvolvimento Cientifico e Tecnologico [304820/2014-8, 307527/2018-2]

向作者/读者索取更多资源

The study evaluated the speed of diet evolution at ecotones, finding that species at ecotones have fewer changes in diet compared to core areas. Despite the greater environmental complexity at ecotones, species there evolve slowly, requiring generalist habits for foraging in ephemeral environments.
We evaluated whether evolution is faster at ecotones as niche shifts may be needed to persist under unstable environment. We mapped diet evolution along the evolutionary history of 350 sigmodontine species. Mapping was used in three new tip-based metrics of trait evolution - Transition Rates, Stasis Time, and Last Transition Time - which were spatialized at the assemblage level (aTR, aST, aTL). Assemblages were obtained by superimposing range maps on points located at core and ecotone of the 93 South American ecoregions. Using Linear Mixed Models, we tested whether ecotones have species with more changes from the ancestral diet (higher aTR), have maintained the current diet for a shorter time (lower aST), and have more recent transitions to the current diet (lower aLT) than cores. We found lower aTR, and higher aST and aLT at ecotones than at cores. Although ecotones are more heterogeneous, both environmentally and in relation to selection pressures they exert on organisms, ecotone species change little from the ancestral diet as generalist habits are necessary toward feeding in ephemeral environments. The need to incorporate phylogenetic uncertainty in tip-based metrics was evident from large uncertainty detected. Our study integrates ecology and evolution by analyzing how fast trait evolution is across space.

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