Spatial occupancy models for data collected on stream networks

TL;DR

This paper introduces specialized spatial occupancy models tailored for stream and river network data, enhancing biodiversity monitoring accuracy in freshwater ecosystems.

Contribution

The paper develops novel spatial occupancy models that incorporate the unique network structure of streams and rivers, addressing limitations of traditional models.

Findings

Models successfully applied to semi-aquatic mammal data

Enhanced accuracy in species distribution estimation

Robust framework for freshwater biodiversity assessment

Abstract

To effectively monitor biodiversity in streams and rivers, we need to quantify species distribution accurately. Occupancy models are useful for distinguishing between the non-detection of a species and its actual absence. While these models can account for spatial autocorrelation, they are not suited for streams and rivers due to their unique network spatial structure. Here, I propose spatial occupancy models specifically designed for data collected on stream and river networks. I present the statistical developments and illustrate their application using data on a semi-aquatic mammal. Overall, spatial stream network occupancy models offer a robust method for assessing biodiversity in freshwater ecosystems.