Spatial Occupancy Models for Data Collected on Stream Networks

2024/11/01 by Olivier Giménez · 2 voices · 3 citations
Computer Science · Environmental Science · #Data Management and Algorithms #Data Mining Algorithms and Applications #Species Distribution and Climate Change

paper · pdf · doi:10.1002/aqc.70013

Abstract

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.

Cited by

• NeMO: a flexible R package for nested multi-species occupancy modeling and eDNA study optimization
• Estimating invasive rodent abundance using removal data and hierarchical models
• Improving Species Distribution Models for Stream Networks by Incorporating Spatial Autocorrelation in Multi‐Sourced Datasets: A Range‐Wide Assessment of Idaho Giant Salamander Status and Future Risk

Discussions

• I have a new paper 😇 in which I show how to analyse data collected on stream networks using occupancy models, check it out here onlinelibrary.wiley.com/doi/10.1002/... 😉 I also have a few slides the [bsky, 44 points, 1 comments]
• New spatial occupancy models for data collected on stream networks Check out the last publication by @oaggimenez.bsky.social from the #CESAB DISCAR group: 👉 doi.org/10.1002/aqc.... 🔑 It offers [bsky, 34 points, 0 comments]

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