Comparing spatial capture–recapture modeling and nest count methods to estimate orangutan densities in the Wehea Forest, East Kalimantan, Indonesia

Spehar, Stephanie; Loken, Brent; Rayadin, Yaya; Royle, J. Andrew

doi:10.1016/j.biocon.2015.06.013

Cited by 16 publications

(12 citation statements)

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“…; Spehar et al. ). The data consisted of 43 sets of data in several formats (collectively referred to here as datasets), including raw camera trap images, pdf tables, GIS shapefiles, and (in most cases) single and multi‐tab Excel spreadsheets.…”

Section: Combining Camera Trap Data From Multiple Sources: a Case Studymentioning

confidence: 98%

Best practices and software for the management and sharing of camera trap data for small and large scales studies

Scotson

Johnston

Iannarilli

et al. 2017

Remote Sens Ecol Conserv

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Camera traps typically generate large amounts of bycatch data of non-target species that are secondary to the study's objectives. Bycatch data pooled from multiple studies can answer secondary research questions; however, variation in field and data management techniques creates problems when pooling data from multiple sources. Multi-collaborator projects that use standardized methods to answer broad-scale research questions are rare and limited in geographical scope. Many small, fixed-term independent camera trap studies operate in poorly represented regions, often using field and data management methods tailored to their own objectives. Inconsistent data management practices lead to loss of bycatch data, or an inability to share it easily. As a case study to illustrate common problems that limit use of bycatch data, we discuss our experiences processing bycatch data obtained by multiple research groups during a range-wide assessment of sun bears Helarctos malayanus in Southeast Asia. We found that the most significant barrier to using bycatch data for secondary research was the time required, by the owners of the data and by the secondary researchers (us), to retrieve, interpret and process data into a form suitable for secondary analyses. Furthermore, large quantities of data were lost due to incompleteness and ambiguities in data entry. From our experiences, and from a review of the published literature and online resources, we generated nine recommendations on data management best practices for field site metadata, camera trap deployment metadata, image classification data and derived data products. We cover simple techniques that can be employed without training, special software and Internet access, as well as options for more advanced users, including a review of data management software and platforms. From the range of solutions provided here, researchers can employ those that best suit their needs and capacity. Doing so will enhance the usefulness of their camera trap bycatch data by improving the ease of data sharing, enabling collaborations and expanding the scope of research.

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Section: Combining Camera Trap Data From Multiple Sources: a Case Studymentioning

confidence: 98%

Best practices and software for the management and sharing of camera trap data for small and large scales studies

Scotson

Johnston

Iannarilli

et al. 2017

Remote Sens Ecol Conserv

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“…Remote heat‐ and motion‐sensitive photography (camera trapping) and capture‐recapture (CR) analytical methods are increasingly used to estimate abundances of rare and elusive animals such as large carnivores and great apes (Head et al, ; Karanth, ; O'Connell, Nichols, & Karanth, ; Spehar, Loken, Rayadin, & Royle, ). CR models for closed populations estimate the size of the population at risk of detection from binary encounter histories describing whether each individual was detected during each of two or more discrete sampling occasions (Otis, Burnham, White, & Anderson, ).…”

Section: Introductionmentioning

confidence: 99%

“…Detection probability is thereby a function of distance and other covariates, which allows for flexible trap designs in which sampling is not continuous across space (Efford & Fewster, ). The combination of camera trapping and SECR modeling shows promise for improving estimates of great ape abundance (Head et al, ; Spehar et al, ). Still, small sample sizes (e.g., small number of captures and recaptures), and the inability to model individual heterogeneity in detection probability from small samples, may affect the accuracy and precision of SECR estimates (Spehar et al, ).…”

Section: Introductionmentioning

confidence: 99%

“…The combination of camera trapping and SECR modeling shows promise for improving estimates of great ape abundance (Head et al, ; Spehar et al, ). Still, small sample sizes (e.g., small number of captures and recaptures), and the inability to model individual heterogeneity in detection probability from small samples, may affect the accuracy and precision of SECR estimates (Spehar et al, ). As such, the reliability and efficiency of camera trapping and SECR modeling requires further investigation and validation.…”

Section: Introductionmentioning

confidence: 99%

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An empirical evaluation of camera trapping and spatially explicit capture‐recapture models for estimating chimpanzee density

Després‐Einspenner

Howe

Drapeau

et al. 2017

American J Primatol

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Empirical validations of survey methods for estimating animal densities are rare, despite the fact that only an application to a population of known density can demonstrate their reliability under field conditions and constraints. Here, we present a field validation of camera trapping in combination with spatially explicit capture-recapture (SECR) methods for enumerating chimpanzee populations. We used 83 camera traps to sample a habituated community of western chimpanzees (Pan troglodytes verus) of known community and territory size in Taï National Park, Ivory Coast, and estimated community size and density using spatially explicit capture-recapture models. We aimed to: (1) validate camera trapping as a means to collect capture-recapture data for chimpanzees; (2) validate SECR methods to estimate chimpanzee density from camera trap data; (3) compare the efficacy of targeting locations frequently visited by chimpanzees versus deploying cameras according to a systematic design; (4) evaluate the performance of SECR estimators with reduced sampling effort; and (5) identify sources of heterogeneity in detection probabilities. Ten months of camera trapping provided abundant capture-recapture data. All weaned individuals were detected, most of them multiple times, at both an array of targeted locations, and a systematic grid of cameras positioned randomly within the study area, though detection probabilities were higher at targeted locations. SECR abundance estimates were accurate and precise, and analyses of subsets of the data indicated that the majority of individuals in a community could be detected with as few as five traps deployed within their territory. Our results highlight the potential of camera trapping for cost-effective monitoring of chimpanzee populations.

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“…In general, orangutan census techniques are subject to interpretation since they are most commonly based on the density of orangutan nests due to the fact that direct counts of animals are hindered by low encounter rates [ 7 ]. Nevertheless, the indisputable rapid decline in Sumatran and Bornean orangutan populations (suggested average annual losses of 230–400 Sumatran and 2050–4850 Bornean orangutans over the last 25 years) has heightened awareness that rapid action is needed for conversation efforts to be effective [ 5 , 8 – 10 ].…”

Section: Introductionmentioning

confidence: 99%

Derivation of induced pluripotent stem cells from orangutan skin fibroblasts

et al. 2015

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BackgroundOrangutans are an endangered species whose natural habitats are restricted to the Southeast Asian islands of Borneo and Sumatra. Along with the African great apes, orangutans are among the closest living relatives to humans. For potential species conservation and functional genomics studies, we derived induced pluripotent stem cells (iPSCs) from cryopreserved somatic cells obtained from captive orangutans.ResultsPrimary skin fibroblasts from two Sumatran orangutans were transduced with retroviral vectors expressing the human OCT4, SOX2, KLF4, and c-MYC factors. Candidate orangutan iPSCs were characterized by global gene expression and DNA copy number analysis. All were consistent with pluripotency and provided no evidence of large genomic insertions or deletions. In addition, orangutan iPSCs were capable of producing cells derived from all three germ layers in vitro through embryoid body differentiation assays and in vivo through teratoma formation in immune-compromised mice.ConclusionsWe demonstrate that orangutan skin fibroblasts are capable of being reprogrammed into iPSCs with hallmark molecular signatures and differentiation potential. We suggest that reprogramming orangutan somatic cells in genome resource banks could provide new opportunities for advancing assisted reproductive technologies relevant for species conservation efforts. Furthermore, orangutan iPSCs could have applications for investigating the phenotypic relevance of genomic changes that occurred in the human, African great ape, and/or orangutan lineages. This provides opportunities for orangutan cell culture models that would otherwise be impossible to develop from living donors due to the invasive nature of the procedures required for obtaining primary cells.Electronic supplementary materialThe online version of this article (doi:10.1186/s13104-015-1567-0) contains supplementary material, which is available to authorized users.

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Comparing spatial capture–recapture modeling and nest count methods to estimate orangutan densities in the Wehea Forest, East Kalimantan, Indonesia

Cited by 16 publications

References 53 publications

Best practices and software for the management and sharing of camera trap data for small and large scales studies

Best practices and software for the management and sharing of camera trap data for small and large scales studies

An empirical evaluation of camera trapping and spatially explicit capture‐recapture models for estimating chimpanzee density

Derivation of induced pluripotent stem cells from orangutan skin fibroblasts

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