TY - JOUR
AU - André L. Koch Liston
AU - Xueying Zhu
AU - Tran V. Bang
AU - Phaivanh Phiapalath
AU - Tanvir Ahmed
AU - Sabit Hasan
AU - Sajib Biswas
AU - Shimul Nath
AU - Toufique Ahmed
AU - Kurnia Ilham
AU - Ngwe Lwin
AU - Cain Agger
AU - Suzuki Ai
AU - Emeline Auda
AU - Eva Gazagne
AU - Jan F. Kamler
AU - Milou Groenenberg
AU - Sarah Banet-Eugene
AU - Neil Challis
AU - Nicole Leroux
AU - Pablo Sinovas
AU - Vanessa H. Muñoz
AU - Susan Lappan
AU - Zaki Zainol
AU - Valeria Albanese
AU - Athanasia Alexiadou
AU - Daniel R. K. Nielsen
AU - Anna Holzner
AU - Nadine Ruppert
AU - Elodie F. Briefer
AU - Agustin Fuentes
AU - Malene F. Hansen
AB - 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 (Macaca fascicularis). 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.
BT - Science Advances
DA - 2024-05-24
DO - 10.1126/sciadv.adn5390
IS - 21
N2 - 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 (Macaca fascicularis). 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.
PY - 2024
EP - eadn5390
T2 - Science Advances
TI - A model for the noninvasive, habitat-inclusive estimation of upper limit abundance for synanthropes, exemplified by M. fascicularis
UR - https://www.science.org/doi/10.1126/sciadv.adn5390
VL - 10
Y2 - 2025-10-10
ER -