Building integral projection models with nonindependent vital rates

Area of Science:

• Ecology
• Population Biology
• Mathematical Biology

Background:

• Population dynamics are shaped by interconnected demographic processes like survival, reproduction, growth, and maturation.
• These vital rates can fluctuate over time, across locations, and among individuals, often exhibiting dependencies.
• Conventional integral projection models (IPMs) often simplify these relationships by assuming independence between demographic processes.

Purpose of the Study:

• To investigate methods for incorporating dependencies between demographic processes within IPMs.
• To explore how temporal variation and individual heterogeneity influence these dependencies.
• To compare the performance of models accounting for dependencies against conventional IPMs.

Main Methods:

• Developed and applied approaches to model between-process dependence in IPMs.
• Incorporated temporal variation, individual heterogeneity, and combined effects.
• Utilized simulations and a case study of Soay sheep (Ovis aries) for validation.

Main Results:

• Correlations between vital rates can moderately influence the variability of population-level statistics.
• Models incorporating dependencies provided a more nuanced understanding of population dynamics compared to independent-rate models.
• The study identified specific scenarios where between-process dependencies significantly impact model outcomes.

Conclusions:

• Including dependencies between demographic processes in IPMs is advisable for accurate population dynamics estimation.
• Ignoring these correlations may lead to biased parameter estimates and population predictions.
• Understanding vital rate dependencies is crucial for effective population management and evolutionary studies.