Deriving observation distances for camera trap distance sampling

Zuleger, Annika; Holland, Ruben; Kühl, Hjalmar S.

doi:10.1111/aje.12959

Cited by 6 publications

(6 citation statements)

References 42 publications

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“…Validation for OCTDE beyond this paper is derived from previous tests of its photogrammetry (Leorna et al., 2022; Zuleger et al., 2022) and population density estimation approaches (Howe et al., 2017). Here, it was tested on a model population of known size and compared to an alternative method that also has associated uncertainty.…”

Section: Discussionmentioning

confidence: 99%

“…Optics theory can be used to estimate the distance of an object to the camera in a given image, if the following information is available: focal length; the object's real‐life size (i.e. any linear dimension); and the object's size on the sensor (Leorna et al., 2022; Zuleger et al., 2022). The latter value can be calculated from the object's size on the image in pixels and the size of the sensor in both pixels and millimetres (Greivenkamp, 2004; Hecht, 2012).…”

Section: Methodsmentioning

confidence: 99%

“…Validation for OCTDE beyond this paper is derived from previous tests of its photogrammetry (Leorna et al, 2022;Zuleger et al, 2022) and population density estimation approaches (Howe et al, 2017).…”

Section: The Future Of Octdementioning

confidence: 99%

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Efficient data collection for camera trap‐based density estimation: A preliminary assessment

Ternyik,

McKaughan,

Hill

et al. 2024

Ecol Sol and Evidence

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Camera traps have great potential for generating wildlife insights by providing high resolution site‐specific data. Methods of data collection and analysis reliant on these tools for population density estimation can be relatively resource intensive, hindering their mainstream adoption. Here, we explore the potential of population density estimates derived from a distance sampling method based on optics theory, which greatly simplifies the process of setting up camera sites and analysing data. Specifically, we (1) tested the method on human subjects in an artificial environment, (2) compared it to another method relying on virtual grids on images using wild populations of black‐backed jackal (Canis mesomelas) and African civet (Civettictis civetta) in South Africa and (3) deployed it to estimate wild boar (Sus scrofa) population densities in Hungary. The initial human trials resulted in an estimate that was extremely close to true population density. When compared to the virtual grid method, results suggest that our distance sampling method can deliver accurate estimates with increased convenience and robustness against disruptions of the camera sites. The wild boar study resulted in a realistic density estimate, which can be used as a baseline when assessing future fluctuations in population density. As this new approach does not have special requirements for setting up camera sites, it is efficient and widely applicable across other density estimation methods requiring an estimate for effective detection distance. Additionally, the method can be applied in the retrospective analysis of existing datasets.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Efficient data collection for camera trap‐based density estimation: A preliminary assessment

Ternyik,

McKaughan,

Hill

et al. 2024

Ecol Sol and Evidence

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“…Such discrepancies might discourage future researchers from using camera traps to estimate trends in density across large spatiotemporal expanses, but this finding reflects the current technology available for accurately processing data. Models for automated species tagging (Willi et al 2019, Norouzzadeh et al 2021) and distance estimation (Haucke et al 2021, Zuleger et al 2022) appear promising and, if easy‐to‐use forms are readily available in the future, could substantially decrease the cost of processing data from camera traps. To predict future cost effectiveness, we simulated a reduction in the data‐processing cost of camera‐trap sampling to $200; however, the weighted and unweighted cost‐effectiveness ratios showed the same preference rankings across methods.…”

Section: Discussionmentioning

confidence: 99%

Using cost‐effectiveness analysis to compare density‐estimation methods for large‐scale wildlife management

Delisle

McGovern

Dillman

et al. 2023

Wildlife Society Bulletin

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Density estimates for animal populations often inform conservation and management decisions. Many methods to estimate animal density exist but deciding between competing alternatives traditionally has depended upon assessing multiple factors (e.g., precision, total cost, area sampled) independently and often in an ad hoc manner. Cost‐effectiveness analysis is a tool that economists use to decide objectively between competing alternatives. We extend cost‐effectiveness analysis to simultaneously integrate precision and per‐area cost of sampling when selecting between competing techniques used to estimate animal density both after a single application of a method and across several applications of capital equipment. Our extension allows for weighting of factors that may vary with the objectives and constraints of decision makers. We apply our extension of cost‐effectiveness analysis to a case study in which population density of white‐tailed deer (Odocoileus virginianus) was estimated in 3 large management units in Indiana, USA, using 3 competing distance‐sampling methods: fecal‐pellet, camera‐trap, and aerial sampling. The unweighted cost effectiveness of aerial sampling with color and infrared sensors was usually superior after a single application of each method and was always superior across several applications in differing landscapes. Pellet sampling was the most cost effective after a single application of each method in an agriculturally‐dominated management unit. Although camera sampling has increased in popularity, the cost effectiveness of camera sampling was poorer than the other 2 methods, even when allowing for potential future innovations to streamline data processing. Cost‐effectiveness analysis can be useful when selecting among competing methods for monitoring animal populations of conservation and management importance. The same principles used in our cost‐effectiveness analysis can be used to decide between competing alternatives related to any ecological monitoring in addition to density estimation.

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“…While camera traps are useful tools (e.g. Orban et al, 2023; Zuleger et al, 2022), they are often costly for routine use by local communities. Therefore, it is valuable to consider groups that can serve as proxies for mammals in such monitoring efforts.…”

Section: What To Monitor?mentioning

confidence: 99%

Community forests as beacons of conservation: Enabling local populations monitor their biodiversity

Luiselli

2023

Afr J Ecol

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Habitat fragmentation is one of the main threats to biodiversity in Africa. In this article, we highlight the importance of conserving the Guinean forests of West Africa, which are rich in biodiversity and endemism but threatened by habitat loss, degradation and fragmentation. The size of forest patches is critical, with larger fragments containing more species than smaller ones. The protection of intact, dense forest patches is vital for any conservation strategy in West Africa, but improving the management of forests that are already used for logging and hunting is also essential. Community forests (CFs) can play a crucial role in conservation, especially if there is a substantial network that can promote ecological connectivity. However, biomonitoring in CFs remains a challenge due to inadequate resources. By developing standardised, easy‐to‐apply and inexpensive methods for biomonitoring, communities can be involved in biomonitoring instead of relying solely on scientists and expensive equipment. We present a monitoring framework here where we suggest local communities should become the main agents for biomonitoring in their own forests; we highlight a five‐step scheme. The importance of the various CFs in terms of conservation should be made through a combination of accurate, standardised face‐to‐face interviews with selected persons in the target communities and biomonitoring be based on the RAPELD scheme. The latter will be implemented after specifically training local ‘wise’ persons. We are proposing a kind of ‘citizen science’ scheme, applied to enhance the ability of local communities to monitor their own biodiversity.

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Deriving observation distances for camera trap distance sampling

Abstract: This is an open access article under the terms of the Creat ive Commo ns Attri bution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Cited by 6 publications

References 42 publications

Efficient data collection for camera trap‐based density estimation: A preliminary assessment

Efficient data collection for camera trap‐based density estimation: A preliminary assessment

Using cost‐effectiveness analysis to compare density‐estimation methods for large‐scale wildlife management

Community forests as beacons of conservation: Enabling local populations monitor their biodiversity

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