AI Article Synopsis
- Developed a flexible model for estimating upper limit populations of long-tailed macaques using camera trap images and habitat preference mapping.
- The model combines environmental data, GPS data, and direct sightings to produce estimated population numbers, optimized through a parameter representing inquisitiveness.
- Results indicate that long-tailed macaque populations are up to 80% smaller than expected, highlighting the model's accuracy and potential as a noninvasive tool for wildlife conservation across species.
Article Abstract
Accurately estimating population sizes for free-ranging animals through noninvasive methods, such as camera trap images, remains particularly limited by small datasets. To overcome this, we developed a flexible model for estimating upper limit populations and exemplified it by studying a group-living synanthrope, the long-tailed macaque (). Habitat preference maps, based on environmental and GPS data, were generated with a maximum entropy model and combined with data obtained from camera traps, line transect distance sampling, and direct sightings to produce an expected number of individuals. The mapping between habitat preference and number of individuals was optimized through a tunable parameter ρ (inquisitiveness) that accounts for repeated observations of individuals. Benchmarking against published data highlights the high accuracy of the model. Overall, this approach combines citizen science with scientific observations and reveals the long-tailed macaque populations to be (up to 80%) smaller than expected. The model's flexibility makes it suitable for many species, providing a scalable, noninvasive tool for wildlife conservation.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11122667 | PMC |
| http://dx.doi.org/10.1126/sciadv.adn5390 | DOI Listing |
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