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Toward reliable population density estimates of partially marked populations using spatially explicit mark-resight methods.

ABSTRACT: Camera traps are used increasingly to estimate population density for elusive and difficult to observe species. A standard practice for mammalian surveys is to place cameras on roads, trails, and paths to maximize detections and/or increase efficiency in the field. However, for many species it is unclear whether track-based camera surveys provide reliable estimates of population density.Understanding how the spatial arrangement of camera traps affects population density estimates is of key interest to contemporary conservationists and managers given the rapid increase in camera-based wildlife surveys.We evaluated the effect of camera-trap placement, using several survey designs, on density estimates of a widespread mesopredator, the red fox Vulpes vulpes, over a two-year period in a semi-arid conservation reserve in south-eastern Australia. Further, we used the certainty in the identity and whereabouts of individuals (via GPS collars) to assess how resighting rates of marked foxes affect density estimates using maximum likelihood spatially explicit mark-resight methods.Fox detection rates were much higher at cameras placed on tracks compared with off-track cameras, yet in the majority of sessions, camera placement had relatively little effect on point estimates of density. However, for each survey design, the precision of density estimates varied considerably across sessions, influenced heavily by the absolute number of marked foxes detected, the number of times marked foxes was resighted, and the number of detection events of unmarked foxes.Our research demonstrates that the precision of population density estimates using spatially explicit mark-resight models is sensitive to resighting rates of identifiable individuals. Nonetheless, camera surveys based either on- or off-track can provide reliable estimates of population density using spatially explicit mark-resight models. This underscores the importance of incorporating information on the spatial behavior of the subject species when planning camera-trap surveys.

SUBMITTER: Carter A

PROVIDER: S-EPMC6392348 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

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Toward reliable population density estimates of partially marked populations using spatially explicit mark-resight methods.

Carter Andrew A Potts Joanne M JM Roshier David A DA

Ecology and evolution 20190124 4

Camera traps are used increasingly to estimate population density for elusive and difficult to observe species. A standard practice for mammalian surveys is to place cameras on roads, trails, and paths to maximize detections and/or increase efficiency in the field. However, for many species it is unclear whether track-based camera surveys provide reliable estimates of population density.Understanding how the spatial arrangement of camera traps affects population density estimates is of key inter ...[more]

PMID: 30847098

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Project description:Camera trapping is the standard field method of monitoring cryptic, low-density mammal populations. Typically, researchers run camera surveys for 60 to 90 days and estimate density using closed population spatially explicit capture-recapture (SCR) models. The SCR models estimate density, capture probability (g0), and a scale parameter (?) that reflects ranging behaviour. We used a year of camera data from 20 camera stations to estimate the density of male jaguars (Panthera onca) in the Cockscomb Basin Wildlife Sanctuary in Belize, using closed population SCR models. We subsampled the dataset into 276 90-day sessions and 186 180-day sessions. Estimated density fluctuated from 0.51 to 5.30 male jaguars / 100 km2 between the 90-day sessions, with comparatively robust and precise estimates for the 180-day sessions (0.73 to 3.75 male jaguars / 100 km2). We explain the variation in density estimates from the 90-day sessions in terms of temporal variation in social behaviour, specifically male competition and mating events during the three-month wet season. Density estimates from the 90-day sessions varied with ?, but not with the number of individuals detected, suggesting that variation in density was almost fully attributable to changes in estimated ranging behaviour. We found that the models overestimated ? when compared to the mean ranging distance derived from GPS tracking data from two collared individuals in the camera grid. Overestimation of ? when compared to GPS collar data was more pronounced for the 180-day sessions than the 90-day sessions. We conclude that one-off ('snap-shot') short-term, small-scale camera trap surveys do not sufficiently sample wide-ranging large carnivores. When using SCR models to estimate the density from these data, we caution against the use of poor sampling designs and/or misinterpretation of scope of inference. Although the density estimates from one-off, short-term, small-scale camera trap surveys may be statistically accurate within each short-term sampling period, the variation between density estimates from multiple sessions throughout the year illustrate that the estimates obtained should be carefully interpreted and extrapolated, because different factors, such as temporal stochasticity in behaviour of a few individuals, may have strong repercussions on density estimates. Because of temporal variation in behaviour, reliable density estimates will require larger samples of individuals and spatial recaptures than those presented in this study (mean +/- SD = 14.2 +/- 1.2 individuals, 37.7 +/- 4.7 spatial recaptures, N = 276 sessions), which are representative of, or higher than published sample sizes. To satisfy the need for larger samples, camera surveys will need to be more expansive with a higher density of stations. In the absence of this, we advocate longer sampling periods and subsampling through time as a means of understanding and describing stability or variation between density estimates.

Project description:Abundance estimation of carnivore populations is difficult and has prompted the use of non-invasive detection methods, such as remotely-triggered cameras, to collect data. To analyze photo data, studies focusing on carnivores with unique pelage patterns have utilized a mark-recapture framework and studies of carnivores without unique pelage patterns have used a mark-resight framework. We compared mark-resight and mark-recapture estimation methods to estimate bobcat (Lynx rufus) population sizes, which motivated the development of a new "hybrid" mark-resight model as an alternative to traditional methods. We deployed a sampling grid of 30 cameras throughout the urban southern California study area. Additionally, we physically captured and marked a subset of the bobcat population with GPS telemetry collars. Since we could identify individual bobcats with photos of unique pelage patterns and a subset of the population was physically marked, we were able to use traditional mark-recapture and mark-resight methods, as well as the new "hybrid" mark-resight model we developed to estimate bobcat abundance. We recorded 109 bobcat photos during 4,669 camera nights and physically marked 27 bobcats with GPS telemetry collars. Abundance estimates produced by the traditional mark-recapture, traditional mark-resight, and "hybrid" mark-resight methods were similar, however precision differed depending on the models used. Traditional mark-recapture and mark-resight estimates were relatively imprecise with percent confidence interval lengths exceeding 100% of point estimates. Hybrid mark-resight models produced better precision with percent confidence intervals not exceeding 57%. The increased precision of the hybrid mark-resight method stems from utilizing the complete encounter histories of physically marked individuals (including those never detected by a camera trap) and the encounter histories of naturally marked individuals detected at camera traps. This new estimator may be particularly useful for estimating abundance of uniquely identifiable species that are difficult to sample using camera traps alone.

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Dataset Information

Toward reliable population density estimates of partially marked populations using spatially explicit mark-resight methods.

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Toward reliable population density estimates of partially marked populations using spatially explicit mark-resight methods.

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