4.4 Article

Life-history traits moderate the susceptibility of native mammals to an invasive predator

期刊

BIOLOGICAL INVASIONS
卷 22, 期 9, 页码 2671-2684

出版社

SPRINGER
DOI: 10.1007/s10530-020-02278-6

关键词

Bayesian hierarchical occupancy model; Burmese python; Greater everglades ecosystem; Invasive species; Life-history traits; Mammals

资金

  1. U.S. Geological Survey
  2. University of Florida Institute of Food and Agricultural Sciences
  3. USDA National Institute of Food and Agriculture [FLA-WEC-005125]

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The invasive Burmese python (Python molurus bivittatus) is causing declines in the numbers and diversity of native mammals in the Greater Everglades Ecosystem (GEE). However, limited evidence suggests that some species may be less susceptible to pythons than others. This difference in susceptibility may be a function of different life-history traits. We analysed incidence data with a multi-species hierarchical occupancy model to evaluate the influence of pythons on native mammals and examine the association between python's influence on species occurrence and life-history traits. We also used our traits-based model to predict the effects of pythons on occupancy probabilities of five mammalian species of conservation or management concern known to occur in the GEE but not detected in our study. Ten of 18 observed mammals showed significant negative effects from pythons, while one responded positively. We found that three of the six species traits evaluated (mass, fecundity, and habitat breadth) moderated the negative effects of pythons on mammal occurrence and were, thus, useful for predicting species responses. Our results suggest larger, fecund and/or species with wide habitat breadths were less susceptible to increasing relative densities of pythons. Our results also suggest a positive and neutral associations between rodents and relative python density, likely due to wide habitat breadths, high fecundity rates, and the reduction of mammalian predators in areas with higher relative python densities. These trait relationships predicted a negative response of all five unobserved species of management concern included in our analysis. Our study provides a broader understanding of wildlife community vulnerability to invasive predators and demonstrates how trait-based models can be used to elucidate generalizable patterns and generate predictions for rare and/or undetected species.

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