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Breeding return times and abundance in capture-recapture models
Shirley Pledger1, Edward Baker, Kim Scribner
1School of Mathematics, Statistics and Operations Research, Victoria University of Wellington, Wellington 6140, New Zealand.
This study introduces a new model for estimating animal population size and survival, accounting for temporary absences. Ignoring temporary emigration can lead to inaccurate abundance estimates in long-lived species.
Area of Science:
- Ecology
- Wildlife population dynamics
- Conservation biology
Background:
- Long-lived species often exhibit temporary emigration, complicating population estimation.
- Traditional capture-recapture models may not accurately account for animals not breeding annually.
- Accurate abundance and survival estimates are crucial for effective wildlife management.
Purpose of the Study:
- To develop a novel statistical model for estimating abundance, survival, and return probabilities in long-lived species.
- To address limitations of existing temporary emigration models with simple sampling designs.
- To apply the model to lake sturgeon (Acipenser fulvescens) data.
Main Methods:
- Developed a likelihood-based model by incorporating return time parameters into the Schwarz-Arnason Jolly-Seber model.
- Utilized lake sturgeon data from a closed population with a simple, one-sample-per-year scheme.
- Estimated sex-specific survival, transition probabilities, and breeding return times.
Main Results:
- The new model provided plausible estimates for abundance, survival, transition, and return time parameters.
- Demonstrated that standard Jolly-Seber models can overestimate abundance when temporary emigration is present.
- Successfully estimated sex-specific parameters for lake sturgeon.
Conclusions:
- The developed model offers a more accurate approach to estimating population parameters in species with temporary emigration.
- Accounting for temporary emigration is essential to avoid biased abundance estimates in long-lived animals.
- This method enhances the reliability of demographic data for conservation efforts.
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