Assessing the importance of demographic parameters for population dynamics using Bayesian integrated population...

Area of Science:

• Ecology
• Conservation Biology
• Wildlife Management

Background:

• Effective management of declining or game species requires understanding vital rates influencing population growth.
• Matrix population models and life-stage simulation analysis (LSA) have been used to assess vital rate sensitivity and variability.
• Existing LSA methods face challenges in data integration, variance disentanglement, and flexibility.

Purpose of the Study:

• To develop and apply a Bayesian integrated population model (IPM) for elk (Cervus canadensis) populations.
• To extend the IPM to evaluate vital rate sensitivity within a Bayesian framework.
• To test the prevailing paradigm that juvenile survival is the primary driver of population growth rate (λ) in large herbivores.

Main Methods:

• Developed a hierarchical Bayesian IPM integrating known-fate survival, fecundity, and population count data.
• Accounted for both process and sampling variance within the model.
• Applied a Bayesian LSA approach to assess the sensitivity of λ to different vital rates.

Main Results:

• Adult female survival explained more variation in λ than elk calf survival.
• Summer and winter elk calf survival were of nearly equivalent importance to λ.
• The Bayesian IPM improved the precision of vital rate estimates.

Conclusions:

• Adult female survival is a more critical driver of elk population dynamics than previously assumed.
• Bayesian integrated population modeling and sensitivity analysis offer advantages for conservation and management.
• This framework can refine population monitoring and inform conservation strategies for diverse species.