Wildlife density estimation by distance sampling: A novel technique with movement compensation

Area of Science:

• Wildlife ecology
• Ecological modeling
• Conservation science

Background:

• Population density estimation is crucial for wildlife conservation.
• Traditional distance sampling methods struggle with mobile populations, leading to overestimates.
• Existing software like Distance has limitations for dynamic animal groups.

Purpose of the Study:

• Introduce WildlifeDensity, a novel distance sampling method and software.
• Address limitations of current methods for mobile wildlife populations.
• Improve accuracy in estimating population density for conservation.

Main Methods:

• Developed mechanistic models for visual detections based on radial or perpendicular distances.
• Incorporated movement compensation models to correct for population-observer relative motion.
• Tested WildlifeDensity on benchmark populations, mobile songbirds, and forest birds.

Main Results:

• WildlifeDensity provided estimates comparable to Distance for immobile populations.
• Radial distance analysis in WildlifeDensity showed slight improvement for low-mobility populations (kangaroos).
• The movement compensation model effectively removed observer speed bias in detection rates.
• WildlifeDensity yielded acceptable density estimates for mobile birds where Distance overestimated.

Conclusions:

• WildlifeDensity extends distance sampling capabilities by compensating for animal movement.
• The method does not require complete detectability on the transect line.
• Supports radial distances, simplifying fieldwork and enhancing measurement accuracy for wildlife density estimation.