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A century of wild bee sampling: historical data and neural network analysis reveal ecological traits associated with species loss.
Graham, Kelsey K; Glaum, Paul; Hartert, Joseph; Gibbs, Jason; Tucker, Erika; Isaacs, Rufus; Valdovinos, Fernanda S.
Afiliação
  • Graham KK; USDA-ARS-PWA Pollinating Insect Research Unit , Logan, UT 84341, USA.
  • Glaum P; Department of Entomology, Michigan State University , East Lansing, MI 48824, USA.
  • Hartert J; Department of Ecology and Evolutionary Biology, University of Michigan , Ann Arbor, MI 48109, USA.
  • Gibbs J; Department of Environmental Science and Policy, University of California , Davis, CA 95616, USA.
  • Tucker E; Waterborne Environmental , Leesburg, VA 20175, USA.
  • Isaacs R; Department of Ecology and Evolutionary Biology, University of Michigan , Ann Arbor, MI 48109, USA.
  • Valdovinos FS; Department of Entomology, University of Manitoba , Winnipeg, Manitoba, Canada R3T 2N2.
Proc Biol Sci ; 291(2028): 20232837, 2024 Aug.
Article em En | MEDLINE | ID: mdl-39137885
ABSTRACT
We analysed the wild bee community sampled from 1921 to 2018 at a nature preserve in southern Michigan, USA, to study long-term community shifts in a protected area. During an intensive survey in 1972 and 1973, Francis C. Evans detected 135 bee species. In the most recent intensive surveys conducted in 2017 and 2018, we recorded 90 species. Only 58 species were recorded in both sampling periods, indicating a significant shift in the bee community. We found that the bee community diversity, species richness and evenness were all lower in recent samples. Additionally, 64% of the more common species exhibited a more than 30% decline in relative abundance. Neural network analysis of species traits revealed that extirpation from the reserve was most likely for oligolectic ground-nesting bees and kleptoparasitic bees, whereas polylectic cavity-nesting bees were more likely to persist. Having longer phenological ranges also increased the chance of persistence in polylectic species. Further analysis suggests a climate response as bees in the contemporary sampling period had a more southerly overall distribution compared to the historic community. Results exhibit the utility of both long-term data and machine learning in disentangling complex indicators of bee population trajectories.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Biodiversidade Limite: Animals País/Região como assunto: America do norte Idioma: En Revista: Proc Biol Sci Assunto da revista: BIOLOGIA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Biodiversidade Limite: Animals País/Região como assunto: America do norte Idioma: En Revista: Proc Biol Sci Assunto da revista: BIOLOGIA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Reino Unido