Improving population analysis using indirect count data: A case study of chimpanzees and elephants
Abstract Estimating spatiotemporal patterns of population density is a primary objective of wildlife monitoring programs. However, estimating density is challenging for species that are elusive and/or occur in habitats with limited visibility. In such situations, indirect measures (e.g., nests, dung...
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| Format: | Article |
| Language: | English |
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Wiley
2025-02-01
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| Series: | Ecosphere |
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| Online Access: | https://doi.org/10.1002/ecs2.70150 |
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| author | Samuel Ayebare Neil A. Gilbert Andrew J. Plumptre Simon Nampindo Elise F. Zipkin |
| author_facet | Samuel Ayebare Neil A. Gilbert Andrew J. Plumptre Simon Nampindo Elise F. Zipkin |
| author_sort | Samuel Ayebare |
| collection | DOAJ |
| description | Abstract Estimating spatiotemporal patterns of population density is a primary objective of wildlife monitoring programs. However, estimating density is challenging for species that are elusive and/or occur in habitats with limited visibility. In such situations, indirect measures (e.g., nests, dung) can serve as proxies for counts of individuals. Scientists have developed approaches to estimate population density using these “indirect count” data, although current methods do not adequately account for variation in sign production and spatial patterns of animal density. In this study, we describe a modified hierarchical distance sampling model that maximizes the information content of indirect count data using Bayesian inference. We apply our model to assess the status of chimpanzee and elephant populations using counts of nests and dung, respectively, which were collected along transects in 2007 and 2021 in western Uganda. Compared with conventional methods, our modeling framework produced more precise estimates of covariate effects on expected animal density by accounting for both long‐term and recent variations in animal abundance and enabled the estimation of the number of days that animal signs remained visible. We estimated a 0.98 probability that chimpanzee density in the region had declined by at least 10% and a 0.99 probability that elephant density had increased by 50% from 2007 to 2021. We recommend applying our modified hierarchical distance sampling model in the analysis of indirect count data to account for spatial variation in animal density, assess population change between survey periods, estimate the decay rate of animal signs, and obtain more precise density estimates than achievable with traditional methods. |
| format | Article |
| id | doaj-art-441387c488b049c0b1fe2474fd8f281c |
| institution | DOAJ |
| issn | 2150-8925 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Wiley |
| record_format | Article |
| series | Ecosphere |
| spelling | doaj-art-441387c488b049c0b1fe2474fd8f281c2025-08-20T02:45:24ZengWileyEcosphere2150-89252025-02-01162n/an/a10.1002/ecs2.70150Improving population analysis using indirect count data: A case study of chimpanzees and elephantsSamuel Ayebare0Neil A. Gilbert1Andrew J. Plumptre2Simon Nampindo3Elise F. Zipkin4Department of Integrative Biology Michigan State University East Lansing Michigan USADepartment of Integrative Biology Michigan State University East Lansing Michigan USAKBA Secretariat, c/o BirdLife International Cambridge UKWildlife Conservation Society (WCS), Uganda Program Kampala UgandaDepartment of Integrative Biology Michigan State University East Lansing Michigan USAAbstract Estimating spatiotemporal patterns of population density is a primary objective of wildlife monitoring programs. However, estimating density is challenging for species that are elusive and/or occur in habitats with limited visibility. In such situations, indirect measures (e.g., nests, dung) can serve as proxies for counts of individuals. Scientists have developed approaches to estimate population density using these “indirect count” data, although current methods do not adequately account for variation in sign production and spatial patterns of animal density. In this study, we describe a modified hierarchical distance sampling model that maximizes the information content of indirect count data using Bayesian inference. We apply our model to assess the status of chimpanzee and elephant populations using counts of nests and dung, respectively, which were collected along transects in 2007 and 2021 in western Uganda. Compared with conventional methods, our modeling framework produced more precise estimates of covariate effects on expected animal density by accounting for both long‐term and recent variations in animal abundance and enabled the estimation of the number of days that animal signs remained visible. We estimated a 0.98 probability that chimpanzee density in the region had declined by at least 10% and a 0.99 probability that elephant density had increased by 50% from 2007 to 2021. We recommend applying our modified hierarchical distance sampling model in the analysis of indirect count data to account for spatial variation in animal density, assess population change between survey periods, estimate the decay rate of animal signs, and obtain more precise density estimates than achievable with traditional methods.https://doi.org/10.1002/ecs2.70150chimpanzeeselephantsindirect countsmarked sign countpopulation changespatial abundance patterns |
| spellingShingle | Samuel Ayebare Neil A. Gilbert Andrew J. Plumptre Simon Nampindo Elise F. Zipkin Improving population analysis using indirect count data: A case study of chimpanzees and elephants Ecosphere chimpanzees elephants indirect counts marked sign count population change spatial abundance patterns |
| title | Improving population analysis using indirect count data: A case study of chimpanzees and elephants |
| title_full | Improving population analysis using indirect count data: A case study of chimpanzees and elephants |
| title_fullStr | Improving population analysis using indirect count data: A case study of chimpanzees and elephants |
| title_full_unstemmed | Improving population analysis using indirect count data: A case study of chimpanzees and elephants |
| title_short | Improving population analysis using indirect count data: A case study of chimpanzees and elephants |
| title_sort | improving population analysis using indirect count data a case study of chimpanzees and elephants |
| topic | chimpanzees elephants indirect counts marked sign count population change spatial abundance patterns |
| url | https://doi.org/10.1002/ecs2.70150 |
| work_keys_str_mv | AT samuelayebare improvingpopulationanalysisusingindirectcountdataacasestudyofchimpanzeesandelephants AT neilagilbert improvingpopulationanalysisusingindirectcountdataacasestudyofchimpanzeesandelephants AT andrewjplumptre improvingpopulationanalysisusingindirectcountdataacasestudyofchimpanzeesandelephants AT simonnampindo improvingpopulationanalysisusingindirectcountdataacasestudyofchimpanzeesandelephants AT elisefzipkin improvingpopulationanalysisusingindirectcountdataacasestudyofchimpanzeesandelephants |