Quantifying Coyote (Canis latrans) Abundance and Habitat Use in the Long Point National Wildlife Area Using Camera Traps

Coyotes (Canis latrans) are a widespread predator within North America, acting as a keystone species in a variety of ecosystems. Within protected areas, understanding the role of coyotes as a top predator is important for effective management. However, studying coyotes is challenging as the species is elusive and highly plastic in their abundance, spatial temporal distribution, habitat selection, and choice of prey. Within the Long Point National Wildlife Area (LPNWA) coyotes have been identified as a top predator but management lacks up-to-date information about the coyote population. In the summer of 2022, we initiated a two-year camera trapping study using 30 cameras rotated across 90 sites in a 500 m2 hexagonal grid arranged across the LPNWA Long Point Unit. Using the observations at each site, the Random Encounter Model (REM) was applied to estimate the density of adults and pups across the breeding and pup-rearing seasons from 2022 to 2024. Generalized linear models (GLMs) were created to inform how different characteristics of the landscape (e.g., habitat type, distance to shore, topography) influence the activity of coyotes across climactic seasons. The results of this study will inform on the density and habitat use of the coyotes to provide baseline information for Canadian Wildlife Service management.

Publication Details

Journal
Scholarship@Western (Western University)
Published
2024-08-20
Primary Topic
Indian and Buddhist Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Quantifying Coyote (Canis latrans) Abundance and Habitat Use in the Long Point National Wildlife Area Using Camera Traps

Scholarship@Western (Western University)
Indian and Buddhist Studies
article

Quantifying Coyote (Canis latrans) Abundance and Habitat Use in the Long Point National Wildlife Area Using Camera Traps

article en

Abstract

Coyotes (Canis latrans) are a widespread predator within North America, acting as a keystone species in a variety of ecosystems. Within protected areas, understanding the role of coyotes as a top predator is important for effective management. However, studying coyotes is challenging as the species is elusive and highly plastic in their abundance, spatial temporal distribution, habitat selection, and choice of prey. Within the Long Point National Wildlife Area (LPNWA) coyotes have been identified as a top predator but management lacks up-to-date information about the coyote population. In the summer of 2022, we initiated a two-year camera trapping study using 30 cameras rotated across 90 sites in a 500 m2 hexagonal grid arranged across the LPNWA Long Point Unit. Using the observations at each site, the Random Encounter Model (REM) was applied to estimate the density of adults and pups across the breeding and pup-rearing seasons from 2022 to 2024. Generalized linear models (GLMs) were created to inform how different characteristics of the landscape (e.g., habitat type, distance to shore, topography) influence the activity of coyotes across climactic seasons. The results of this study will inform on the density and habitat use of the coyotes to provide baseline information for Canadian Wildlife Service management.

Scholarship@Western (Western University)
Life in Land
Openalex Percentile: Top 16%
Indian and Buddhist Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Quantifying Coyote (Canis latrans) Abundance and Habitat Use in the Long Point National Wildlife Area Using Camera Traps · Scholarship@Western (Western University) (2024) | TGRS Research Map | TGRS