Statistical Modeling of Bobcat Population Dynamics
Summary
Statistical modelling of bobcat population dynamics integrates diverse data sources—harvest records, telemetry, camera‐trap detections and environmental variables—within unified frameworks to infer key demographic parameters and spatial behaviours. Age‐at‐harvest models and statistical population reconstruction employ cohort data to estimate survival, recruitment and abundance over time. Hierarchical Bayesian and integrated population models synthesise telemetry and survey data while explicitly quantifying uncertainty and allowing for temporal and spatial heterogeneity. Occupancy and dynamic occupancy models reveal patterns of presence and colonisation across landscapes, whereas resource selection functions and connectivity analyses link habitat features with movement and dispersal corridors. Together these approaches provide robust estimates of population trends, inform sustainable harvest quotas and guide habitat management, ensuring bobcat conservation in human‐altered and protected ecosystems globally.
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Statistical Modeling of Bobcat Population Dynamics publication trend
The graph below shows the total number of articles in statistical modeling of bobcat population dynamics across all publications each year (not limited to Nature Index journals).
Technical terms
Bayesian hierarchical model: A statistical framework that integrates multiple data sources and hierarchical levels (e.g. individual, population) using probability distributions to estimate parameters and their uncertainty.
Age‐at‐harvest data: Records of the age classes of harvested individuals, used to reconstruct population demographics and infer survival and recruitment rates.
Statistical population reconstruction: Techniques that use age‐structured harvest or survey data to estimate past and present population abundance and demographic rates.
Resource Selection Function (RSF): A model that quantifies the probability of an animal using a resource unit (e.g. habitat type) based on environmental covariates.
Habitat connectivity: The degree to which landscapes facilitate or impede movement among habitat patches, often modelled using resistance surfaces and circuit theory.
References
- A flexible Bayesian approach for estimating survival probabilities from age‐at‐harvest data. Methods in Ecology and Evolution (2023).
- Habitat connectivity and resource selection in an expanding bobcat (Lynx rufus) population. PeerJ (2021).
- Habitat selection in a recovering bobcat (Lynx rufus) population. PLOS ONE (2022).
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