A comparison of density estimation methods for monitoring marked and unmarked animal populations

Twining, Joshua P.; McFarlane, Claire; O'Meara, Denise; O’Reilly, Catherine; Reyne, Marina; Montgomery, W. Ian; Helyar, Sarah J.; Tosh, David G.; Augustine, Ben C.

doi:10.1002/ecs2.4165

Cited by 9 publications

(7 citation statements)

References 65 publications

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“…2021), and non‐invasive genetic sampling (Twining et al. 2022). However, much less technical expertise and training is required to employ camera traps, and the cost of supplies and equipment is relatively low after a large initial investment to purchase the cameras.…”

Section: Resultsmentioning

confidence: 99%

“…The cost of using camera traps can be 2-5 times lower than that of live traps (De Bondi et al 2010, White et al 2023. Costs were similar between camera trap surveys and wildlife detection dogs (Glen et al 2016), eDNA surveys (Lyet et al 2021), and non-invasive genetic sampling (Twining et al 2022). However, much less technical expertise and training is required to employ camera traps, and the cost of supplies and equipment is relatively low after a large initial investment to purchase the cameras.…”

Section: Advantages and Strengthsmentioning

confidence: 99%

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Non‐invasive methods for monitoring weasels: emerging technologies and priorities for future research

Jachowski,

Bergeson,

Cotey

et al. 2024

Mammal Review

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Weasels (genus Mustela and Neogale) are of management concern as declining native species in some regions and invasive species in others. Regardless of the need to conserve or remove weasels, there is increasingly a need to use non‐invasive monitoring methods to assess population trends. We conducted a literature review and held the first ever International Weasel Monitoring Symposium to synthesise information on historical and current non‐invasive monitoring techniques for weasels. We also explored current limitations, opportunities, and areas of development to guide future research and long‐term monitoring. Our literature search revealed that in the past 20 years, camera traps were the most commonly used non‐invasive monitoring method (62% of studies), followed by track plates or scent stations designed to collect footprints (23%) and walking transects for tracks in snow or soil (8.7%). Experts agreed that the most promising non‐invasive monitoring techniques available include use of citizen scientist reporting, detection dogs, detecting tracks, non‐invasive genetic surveys, and enclosed or unenclosed camera trap systems. Because each technique has benefits and limitations, using a multi‐method approach is likely required. There is a need for strong commitment to dedicated monitoring that is replicated over space and time such that trend data can be ascertained to better inform future management action. The diversity of non‐invasive monitoring methods now available makes such monitoring possible with relatively minor commitments of funding and effort.

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Section: Resultsmentioning

confidence: 99%

Section: Advantages and Strengthsmentioning

confidence: 99%

Non‐invasive methods for monitoring weasels: emerging technologies and priorities for future research

Jachowski,

Bergeson,

Cotey

et al. 2024

Mammal Review

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“…Due to finite funds, wildlife managers and conservationists are commonly faced with trade‐offs in population monitoring between sampling intensity and spatial extent (Sun et al., 2014; Twining et al., 2022). This is especially problematic where areas of interest are large, with a high degree of landscape variability.…”

Section: Discussionmentioning

confidence: 99%

Integrating presence‐only and detection/non‐detection data to estimate distributions and expected abundance of difficult‐to‐monitor species on a landscape‐scale

Twining,

Fuller,

Sun

et al. 2024

Journal of Applied Ecology

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Estimating species distribution and abundance is foundational to effective management and conservation. Using an integrated species distribution model that combines presence‐only data from various sources with detection/non‐detection data from structured surveys, we estimated the distribution and expected abundance of three difficult‐to‐monitor mammals of management concern across New York State, namely, coyotes (Canis latrans), bobcats (Lynx rufus) and black bears (Ursus americanus). Three distinct landscape‐scale camera trap surveys provided detection/non‐detection data over 9 years between 2013 and 2021, and we augmented those data with incidental records of our focal species from public repositories. We used an inhomogeneous Poisson point process to construct an integrated model that fit both data types simultaneously. We demonstrate a simple application of spatial point density of all species records in the accessed public databases to inform the thinning process to account for unknown spatial sampling in the presence‐only data, often referred to as the ‘magic covariate’. Using this approach, we examine habitat associations and provide spatially explicit estimates in expected abundance across the entirety of New York State for all three focal species. As expected, coyotes were the most widely distributed and abundant species, with a strong positive association with agricultural land uses. Bobcats exhibited low expected abundance throughout the state and showed positive associations with deciduous forest and forest edge, and a negative association with road density. Finally, we observed considerable spatial variation in abundance of black bears with expected abundance increasing in association with various forest cover and composition covariates and decreasing with crop cover. We present insights into habitat associations and spatial variation in abundance, and provide management implications for each of the species of interest. Synthesis and applications. Our integrated modelling method allows for managers to use citizen sightings combined with detection/non‐detection surveys to estimate robust indices of abundance for both high‐ and low‐density, and wide‐spread versus patchily distributed species. Through comparison with previous studies, we highlight how broad‐scale programmes, such as the statewide efforts to estimate species distributions undertaken here, can benefit substantively from integrated models that leverage additional data (here, incidental records) from a larger region of space, and thus capture more landscape heterogeneity than is plausible within formalized surveys alone.

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“…Despite working in rugged and undeveloped terrain, we were successful in estimating cougar abundance and density, and our findings corroborate previous research highlighting the efficacy of noninvasive detection dog teams in elucidating the demography and ecology of cryptic species (Davidson et al, 2014; Long et al, 2007; Petroelje et al, 2021). Though we did not conduct a formal comparison between traditional and integrated SCR models, our quantitative approach joins a rich body of literature demonstrating the utility of integrated approaches in estimating animal abundance and density (e.g., Morin et al, 2022; Ruprecht et al, 2021, 2022; Tourani et al, 2020; Twining et al, 2022) while also collecting ancillary data on locally rare species of interest (Appendix S1: Table S1, Figure S3). Through this work, we demonstrated the utility of noninvasive sampling approaches to elucidate important population parameters and provide foundational information about the population of a species of conservation interest.…”

Section: Discussionmentioning

confidence: 99%

An integrated spatial capture–recapture approach reveals the distribution of a cryptic carnivore in a protected area

Martin

Green

Garrison³

et al. 2023

Ecosphere

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Quantifying animal abundance, density, and distributions affords the opportunity to understand the effects of landscape structure and change on species of conservation interest, but estimating these parameters can be difficult for rare and cryptic species. Noninvasive sampling methods, such as remote cameras or scat DNA, can mitigate the challenges of studying rare and cryptic species while also minimizing effects on species of conservation interest or concern. Data derived from these methods can be integrated into robust, contemporary quantitative methods, including spatial capture–recapture (SCR) models, which provide a hierarchical framework for jointly estimating animal abundance, distribution, and, consequently, density. Herein, we developed an integrated SCR model to estimate the abundance, density, and distribution of a large carnivore of conservation interest, the cougar (Puma concolor), in a rugged and remote protected area, Yosemite National Park, California, USA. We combined spatial encounter data from DNA‐based individual identification of scats with detection count data derived from remote cameras to estimate cougar density and detection probability in Yosemite. We further estimated how cougar density and detection probability varied as a result of vegetation, topography, anthropogenic and natural linear features, and survey effort. Using data collected in 2019 and 2020, we estimated a median of 31 (SD = 3.96, 95% credible intervals = 24–39) cougars in Yosemite across the two years, with higher densities associated with productive, vegetated areas. We found detection probability by scent detection teams was higher for females than males and positively correlated with survey effort, proximity to trails, and distance farther from roads and streams. Our study illustrates the utility of noninvasive survey methods that yield individual identities in rugged and remote environments, where capture and handling of cryptic, low‐density animals is logistically challenging and cost prohibitive. Integrated modeling approaches, as used here, allow ecologists to leverage empirical data using a robust quantitative framework that can effectively address conservation objectives. Through this work, we demonstrate the importance of large, contiguous, and heterogeneous ecosystems to the ecology of wide‐ranging species that occur in dynamic landscapes.

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A comparison of density estimation methods for monitoring marked and unmarked animal populations

Cited by 9 publications

References 65 publications

Non‐invasive methods for monitoring weasels: emerging technologies and priorities for future research

Non‐invasive methods for monitoring weasels: emerging technologies and priorities for future research

Integrating presence‐only and detection/non‐detection data to estimate distributions and expected abundance of difficult‐to‐monitor species on a landscape‐scale

An integrated spatial capture–recapture approach reveals the distribution of a cryptic carnivore in a protected area

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