A Flexible Framework for N-Mixture Occupancy Models: Advancing Abundance Estimation in Breeding Bird

Music City Center 

Estimating species abundance under imperfect detection remains a critical challenge in biodiversity research. The widely-used N-mixture model effectively separates abundance from individual detection probabilities without requiring marked individuals. However, its strict closure assumption often leads to biased results in dynamic ecological contexts. To overcome this limitation, we propose an extended framework that incorporates a community parameter, representing the proportion of individuals consistently present throughout the survey period. This innovation unifies and generalizes the standard occupancy and N-mixture models as special cases, offering enhanced flexibility and robustness.

Using simulations and applications to real-world datasets-including five species from the North American Breeding Bird Survey and 46 species from the Swiss Breeding Bird Survey-our framework demonstrates improved accuracy and adaptability in scenarios where closure assumptions do not hold. This work advances statistical methodologies for biodiversity monitoring, bridging critical gaps in tools for studying dynamic ecosystems and informing conservation efforts.

Abundance Estimation

Imperfect Detection


Occupancy Models

N-mixture Models 

Section on Statistics and the Environment