ArticlePloS one2017
Does landscape connectivity shape local and global social network structure in white-tailed deer?
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
6 citing papers in PubMed.
- Intraspecific Contact Among White-Tailed Deer: A Literature Review and Chronic Wasting Disease Case Study.Ecology and evolution · 2026Review
- An Updated Framework for Modeling White-Tailed Deer (Ecology and evolution · 2024Article
- Individual-level patterns of resource selection do not predict hotspots of contact.Movement ecology · 2023Article
- Agricultural land use shapes dispersal in white-tailed deer (Odocoileus virginianus).Movement ecology · 2022Article
- Variability in the estimation of ungulate group sizes complicates ecological inference.Ecology and evolution · 2020Review
- Transmission on empirical dynamic contact networks is influenced by data processing decisions.Epidemics · 2019Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Intraspecific social behavior can be influenced by both intrinsic and extrinsic factors. While much research has focused on how characteristics of individuals influence their roles in social networks, we were interested in the role that landscape structure plays in animal sociality at both individual (local) and population (global) levels. We used female white-tailed deer (Odocoileus virginianus) in Illinois, USA, to investigate the potential effect of landscape on social network structure by weighting the edges of seasonal social networks with association rate (based on proximity inferred from GPS collar data). At the local level, we found that sociality among female deer in neighboring social groups (n = 36) was mainly explained by their home range overlap, with two exceptions: 1) during fawning in an area of mixed forest and grassland, deer whose home ranges had low forest connectivity were more social than expected; and 2) during the rut in an area of intensive agriculture, deer inhabiting home ranges with high amount and connectedness of agriculture were more social than expected. At the global scale, we found that deer populations (n = 7) in areas with highly connected forest-agriculture edge, a high proportion of agriculture, and a low proportion of forest tended to have higher weighted network closeness, although low sample size precluded statistical significance. This result implies that infectious disease could spread faster in deer populations inhabiting such landscapes. Our work advances the general understanding of animal social networks, demonstrating how landscape features can underlie differences in social behavior both within and among wildlife social networks.
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