Multiple observation processes in spatial capture-recapture models: How much do we gain?

Area of Science:

• Ecology
• Wildlife Biology
• Conservation Science

Background:

• Population monitoring often relies on sparse, incomplete data from various methods.
• Practical and economic constraints limit data collection, leading to information gaps.

Purpose of the Study:

• To develop an integrated spatial capture-recapture (SCR) model for combining multiple data sources.
• To assess the benefits of integrating diverse datasets in SCR models for population monitoring.

Main Methods:

• Developed a multiple observation processes SCR model (MOP).
• Incorporated multiple data sources with imperfect individual identification.
• Validated using extensive simulations and brown bear monitoring data.

Main Results:

• The MOP model provided a more complete understanding of population processes.
• Integrated SCR models reduced parameter bias and increased precision.
• Significant gains observed with low detection probability and high non-identifiable detections.

Conclusions:

• Integrating multiple data sources enhances the reliability of SCR models.
• The MOP approach is beneficial for wildlife monitoring with imperfect data.
• This method is particularly valuable in challenging monitoring scenarios.