Integrating human mobility and animal movement data reveals complex space-use between humans and white-tailed deer in urban environments

Abstract Human expansion into wildlife habitats has increased the need to understand human–wildlife interactions, necessitating interdisciplinary approaches to assess zoonotic disease transmission risks and public health impacts. This study integrated fine-grained human foot traffic data with hourly...

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Main Authors: Szandra A. Péter, Travis Gallo, Jennifer Mullinax, Amira Roess, Gabriela Palomo-Munoz, Taylor Anderson
Format: Article
Language:English
Published: Nature Portfolio 2025-05-01
Series:Scientific Reports
Subjects:
Online Access:https://doi.org/10.1038/s41598-025-03577-5
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author Szandra A. Péter
Travis Gallo
Jennifer Mullinax
Amira Roess
Gabriela Palomo-Munoz
Taylor Anderson
author_facet Szandra A. Péter
Travis Gallo
Jennifer Mullinax
Amira Roess
Gabriela Palomo-Munoz
Taylor Anderson
author_sort Szandra A. Péter
collection DOAJ
description Abstract Human expansion into wildlife habitats has increased the need to understand human–wildlife interactions, necessitating interdisciplinary approaches to assess zoonotic disease transmission risks and public health impacts. This study integrated fine-grained human foot traffic data with hourly GPS data from 38 white-tailed deer (Odocoileus virginianus), a species linked to SARS-CoV-2, brucella, and chronic wasting disease, in Howard County, Maryland. We explored spatial and temporal overlap between human and deer activity over 24 months (2018–2019) across a hexagonal tessellation with metrics like hourly popularity and visit counts. Negative binomial models were fitted to the visit counts of each deer and humans per tessellation area, using landscape features as predictors. A separate deer-only model included commercial human activity as another predictor. Spatial analysis showed deer and humans sharing spaces in the study area, with results indicating deer using more populated residential areas and areas with commercial activity. Temporal analysis showed deer avoiding commercial spaces during daytime but using them in late evening and early morning. These findings highlight the complex space use between species and the importance of integrating detailed human mobility and animal movement data when managing wildlife–human conflict and zoonotic disease transmission, particularly in urban areas with a high probability of deer–human interactions.
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spelling doaj-art-35a6dc4a20064f0d886dbdf8bb7c5a582025-08-20T02:03:35ZengNature PortfolioScientific Reports2045-23222025-05-0115111210.1038/s41598-025-03577-5Integrating human mobility and animal movement data reveals complex space-use between humans and white-tailed deer in urban environmentsSzandra A. Péter0Travis Gallo1Jennifer Mullinax2Amira Roess3Gabriela Palomo-Munoz4Taylor Anderson5Department of Geography and Geoinformation Science, George Mason UniversityDepartment of Environmental Science and Technology, University of MarylandDepartment of Environmental Science and Technology, University of MarylandDepartment of Global and Community Health, George Mason UniversityDepartment of Environmental Science and Technology, University of MarylandDepartment of Geography and Geoinformation Science, George Mason UniversityAbstract Human expansion into wildlife habitats has increased the need to understand human–wildlife interactions, necessitating interdisciplinary approaches to assess zoonotic disease transmission risks and public health impacts. This study integrated fine-grained human foot traffic data with hourly GPS data from 38 white-tailed deer (Odocoileus virginianus), a species linked to SARS-CoV-2, brucella, and chronic wasting disease, in Howard County, Maryland. We explored spatial and temporal overlap between human and deer activity over 24 months (2018–2019) across a hexagonal tessellation with metrics like hourly popularity and visit counts. Negative binomial models were fitted to the visit counts of each deer and humans per tessellation area, using landscape features as predictors. A separate deer-only model included commercial human activity as another predictor. Spatial analysis showed deer and humans sharing spaces in the study area, with results indicating deer using more populated residential areas and areas with commercial activity. Temporal analysis showed deer avoiding commercial spaces during daytime but using them in late evening and early morning. These findings highlight the complex space use between species and the importance of integrating detailed human mobility and animal movement data when managing wildlife–human conflict and zoonotic disease transmission, particularly in urban areas with a high probability of deer–human interactions.https://doi.org/10.1038/s41598-025-03577-5Human mobilityMovement ecologyHuman–wildlife interactionsData integration
spellingShingle Szandra A. Péter
Travis Gallo
Jennifer Mullinax
Amira Roess
Gabriela Palomo-Munoz
Taylor Anderson
Integrating human mobility and animal movement data reveals complex space-use between humans and white-tailed deer in urban environments
Scientific Reports
Human mobility
Movement ecology
Human–wildlife interactions
Data integration
title Integrating human mobility and animal movement data reveals complex space-use between humans and white-tailed deer in urban environments
title_full Integrating human mobility and animal movement data reveals complex space-use between humans and white-tailed deer in urban environments
title_fullStr Integrating human mobility and animal movement data reveals complex space-use between humans and white-tailed deer in urban environments
title_full_unstemmed Integrating human mobility and animal movement data reveals complex space-use between humans and white-tailed deer in urban environments
title_short Integrating human mobility and animal movement data reveals complex space-use between humans and white-tailed deer in urban environments
title_sort integrating human mobility and animal movement data reveals complex space use between humans and white tailed deer in urban environments
topic Human mobility
Movement ecology
Human–wildlife interactions
Data integration
url https://doi.org/10.1038/s41598-025-03577-5
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