Ecology and Evolution (Jul 2020)

Large‐scale patterns of seed removal by small mammals differ between areas of low‐ versus high‐wolf occupancy

  • Jennifer L. Chandler,
  • Timothy R. Van Deelen,
  • Nathan P. Nibbelink,
  • John L. Orrock

DOI
https://doi.org/10.1002/ece3.6415
Journal volume & issue
Vol. 10, no. 14
pp. 7145 – 7156

Abstract

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Abstract Because most tree species recruit from seeds, seed predation by small‐mammal granivores may be important for determining plant distribution and regeneration in forests. Despite the importance of seed predation, large‐scale patterns of small‐mammal granivory are often highly variable and thus difficult to predict. We hypothesize distributions of apex predators can create large‐scale variation in the distribution and abundance of mesopredators that consume small mammals, creating predictable areas of high and low granivory. For example, because gray wolf (Canis lupus) territories are characterized by relatively less use by coyotes (C. latrans) and greater use by foxes (Vulpes vulpes, Urocyon cinereoargentus) that consume a greater proportion of small mammals, wolf territories may be areas of reduced small‐mammal granivory. Using large‐scale, multiyear field trials at 22 sites with high‐ and low‐wolf occupancy in northern Wisconsin, we evaluated whether removal of seeds of four tree species was lower in wolf territories. Consistent with the hypothesized consequences of wolf occupancy, seed removal of three species was more than 25% lower in high‐wolf‐occupancy areas across 2 years and small‐mammal abundance was more than 40% lower in high‐wolf areas during one of two study years. These significant results, in conjunction with evidence of seed consumption in situ and the absence of significant habitat differences between high‐ and low‐wolf areas, suggest that top‐down effects of wolves on small‐mammal granivory and seed survival may occur. Understanding how interactions among carnivores create spatial patterns in interactions among lower trophic levels may allow for more accurate predictions of large‐scale patterns in seed survival and forest composition.

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