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Related Experiment Video

Updated: Aug 27, 2025

A Method for Quantifying Foliage-Dwelling Arthropods

A Method for Quantifying Foliage-Dwelling Arthropods

Published on: October 20, 2019

Integrating basic and applied research to estimate carnivore abundance.

Sarah N Sells¹, Kevin M Podruzny², J Joshua Nowak³

¹Wildlife Biology Program, University of Montana, Missoula, Montana, USA.

Ecological Applications : a Publication of the Ecological Society of America

|October 2, 2022

Summary

We developed a new multimodel approach to estimate gray wolf (Canis lupus) abundance, integrating basic research with applied management for more efficient and accurate wildlife monitoring. This method improves abundance estimates while reducing costs and effort for wildlife managers.

Keywords:

Canis lupus Montana behavioral models monitoring occupancy model sociality territoriality wolves

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Last Updated: Aug 27, 2025

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Area of Science:

Wildlife ecology and population dynamics.
Conservation biology and applied wildlife management.
Ecological modeling and spatial analysis.

Background:

Estimating gray wolf (Canis lupus) abundance is crucial for effective wildlife management but is often resource-intensive.
Existing field-based monitoring methods are costly and challenging, particularly for large or growing populations.
A gap often exists between fundamental ecological research and practical management applications.

Purpose of the Study:

To develop and validate an integrated, multimodel approach for estimating gray wolf abundance in Montana, USA.
To improve the accuracy and efficiency of wolf population monitoring by leveraging basic research on behavior.
To bridge the gap between ecological theory and applied wildlife management needs.

Main Methods:

A three-part modeling process combining occupancy, mechanistic territory, and empirical group size models.
Utilizing readily available wolf observation data alongside environmental covariates, prey resources, and human impact data.
Developing spatially explicit predictions of wolf distribution, territory size, and pack dynamics.

Main Results:

Estimated Montana wolf population dynamics from 2007 to 2020, noting a peak in 2011 and subsequent stabilization after legal harvest implementation.
Accurate abundance estimates were derived by combining predicted pack numbers and empirically determined pack sizes.
The approach successfully integrated biological mechanisms to predict carnivore abundance at fine spatial scales.

Conclusions:

The integrated multimodel approach provides a more accurate and efficient method for estimating wolf abundance compared to traditional monitoring.
This research demonstrates a successful integration of basic ecological research with applied wildlife management.
The findings offer a valuable tool for informing decision-making and addressing management challenges for wide-ranging carnivores.