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Related Experiment Video

Updated: Jul 7, 2026

Spotting Cheetahs: Identifying Individuals by Their Footprints

Spotting Cheetahs: Identifying Individuals by Their Footprints

Published on: May 1, 2016

Conflicts and Collisions With an Endangered Carnivore: Landscape Drivers and Spatial Risk Pattern.

Marta Prat-Guitart¹, David P Onorato², James E Hines³

¹Department of Wildlife Ecology and Conservation University of Florida Gainesville Florida USA.

Ecology and Evolution

|July 6, 2026

Summary

This summary is machine-generated.

Human-wildlife conflicts and vehicle collisions involving Florida panthers (Puma concolor coryi) are increasing. Landscape fragmentation and road proximity drive these risks, necessitating targeted conservation strategies for coexistence.

Keywords:

carnivore conservation depredation human–wildlife conflict landscape ecology occupancy modeling vehicular collision

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Last Updated: Jul 7, 2026

Spotting Cheetahs: Identifying Individuals by Their Footprints

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Published on: May 1, 2016

An R-Based Landscape Validation of a Competing Risk Model

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

Linking Predation Risk, Herbivore Physiological Stress and Microbial Decomposition of Plant Litter

Linking Predation Risk, Herbivore Physiological Stress and Microbial Decomposition of Plant Litter

Published on: March 12, 2013

Area of Science:

Ecology
Conservation Biology
Wildlife Management

Background:

Human encroachment on natural habitats escalates human-wildlife conflicts and mortality.
Understanding the drivers of Florida panther (Puma concolor coryi) conflicts and vehicle collisions is crucial for conservation.

Purpose of the Study:

To investigate the spatiotemporal dynamics and drivers of human-panther conflicts and vehicle collisions.
To develop a predictive map of high-risk areas for targeted mitigation strategies.

Main Methods:

Utilized long-term data (2006-2022) from Southwest Florida, USA.
Applied dynamic occupancy models to estimate occurrence, colonization, and extinction probabilities.
Analyzed landscape configuration and proximity to roads as key drivers.

Main Results:

Recorded 277 conflicts and 239 collisions.
Occurrence probabilities for both increased initially and then stabilized.
Conflicts linked to fragmented habitats; collisions associated with connected landscapes and roads.
Habitat fragmentation and road proximity were significant drivers.

Conclusions:

Landscape configuration significantly influences human-panther conflicts and vehicle collisions.
Predictive mapping can guide mitigation efforts like habitat management and wildlife crossings.
Informed strategies support long-term coexistence between humans and Florida panthers.