Thinned Point Process Models for Telemetry Data
February 6, 2025
This project aimed to develop methods to estimate spatially explicit survival of wildlife from telemetry data.
Citation Information
| Publication Year | 2025 |
|---|---|
| Title | Thinned Point Process Models for Telemetry Data |
| DOI | 10.5066/P9HSN8PV |
| Authors | Joseph M Eisaguirre |
| Product Type | Data Release |
| Record Source | USGS Asset Identifier Service (AIS) |
| USGS Organization | Alaska Science Center |
| Rights | This work is marked with CC0 1.0 Universal |
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Estimating spatially explicit survival and mortality risk from telemetry data with thinned point process models Estimating spatially explicit survival and mortality risk from telemetry data with thinned point process models
Mortality risk for animals often varies spatially and can be linked to how animals use landscapes. While numerous studies collect telemetry data on animals, the focus is typically on the period when animals are alive, even though there is important information that could be gleaned about mortality risk. We introduce a thinned spatial point process (SPP) modelling framework that couples...
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Estimating spatially explicit survival and mortality risk from telemetry data with thinned point process models Estimating spatially explicit survival and mortality risk from telemetry data with thinned point process models
Mortality risk for animals often varies spatially and can be linked to how animals use landscapes. While numerous studies collect telemetry data on animals, the focus is typically on the period when animals are alive, even though there is important information that could be gleaned about mortality risk. We introduce a thinned spatial point process (SPP) modelling framework that couples...
Authors
Joseph Michael Eisaguirre, Medeleine G. Lohman, Graham G. Frye, Heather E. Johnson, Thomas V. Riecke, Perry J. Williams