Estimating population size of fishers (<i>Pekania pennanti</i>) using camera stations and auxiliary data on home range size

Furnas, Brett J.; Landers, Russ H.; Callas, Richard; Matthews, Sean M.

doi:10.1002/ecs2.1747

Cited by 27 publications

(25 citation statements)

References 55 publications

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“…Ecological research is experiencing an explosion in the use of wildlife imagery. Camera trapping has become a common noninvasive survey technique (Burton et al, ; O'Connell, Nichols, & Karanth, ; Rowcliffe & Carbone, ), especially for rare and elusive forest‐dwelling species (Furnas, Landers, Callas, & Matthews, ; Stewart et al, ), and has been used to obtain crucial ecological information (Caravaggi et al, ). Landscape‐scale camera grids or transects are increasing across the globe (McShea, Forrester, Costello, He, & Kays, ), and such sampling may be used to monitor global biodiversity in the future (Rich et al, ; Steenweg et al, ).…”

Section: Introductionmentioning

confidence: 99%

Measuring agreement among experts in classifying camera images of similar species

Gooliaff

Hodges

2018

Ecology and Evolution

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Camera trapping and solicitation of wildlife images through citizen science have become common tools in ecological research. Such studies collect many wildlife images for which correct species classification is crucial; even low misclassification rates can result in erroneous estimation of the geographic range or habitat use of a species, potentially hindering conservation or management efforts. However, some species are difficult to tell apart, making species classification challenging—but the literature on classification agreement rates among experts remains sparse. Here, we measure agreement among experts in distinguishing between images of two similar congeneric species, bobcats (Lynx rufus) and Canada lynx (Lynx canadensis). We asked experts to classify the species in selected images to test whether the season, background habitat, time of day, and the visible features of each animal (e.g., face, legs, tail) affected agreement among experts about the species in each image. Overall, experts had moderate agreement (Fleiss’ kappa = 0.64), but experts had varying levels of agreement depending on these image characteristics. Most images (71%) had ≥1 expert classification of “unknown,” and many images (39%) had some experts classify the image as “bobcat” while others classified it as “lynx.” Further, experts were inconsistent even with themselves, changing their classifications of numerous images when they were asked to reclassify the same images months later. These results suggest that classification of images by a single expert is unreliable for similar‐looking species. Most of the images did obtain a clear majority classification from the experts, although we emphasize that even majority classifications may be incorrect. We recommend that researchers using wildlife images consult multiple species experts to increase confidence in their image classifications of similar sympatric species. Still, when the presence of a species with similar sympatrics must be conclusive, physical or genetic evidence should be required.

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Section: Introductionmentioning

confidence: 99%

Measuring agreement among experts in classifying camera images of similar species

Gooliaff

Hodges

2018

Ecology and Evolution

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“…We note that our analyses were also restricted to linear covariate relationships, apart from Julian day, and that we did not directly evaluate potential spatial autocorrelation among our sampling sites. The spatial covariates we used in our occupancy models likely mitigated the potential issue of spatial autocorrelation, but future studies may consider using spatial occupancy models and assessing covariate relationships in greater detail by including polynomial and interaction terms (Furnas, Landers, Callas, & Matthews, ; Johnson, Conn, Hooten, Ray, & Pond, ).…”

Section: Discussionmentioning

confidence: 99%

Acoustic and camera surveys inform models of current and future vertebrate distributions in a changing desert ecosystem

Rich

Furnas

Newton

et al. 2019

Diversity and Distributions

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Aim: Maintaining biodiversity in the face of land use and climate change is a paramount challenge, particularly when distributions of many species remain incompletely known. Emerging technologies help address this data deficiency by facilitating the collection of spatially explicit data for multiple species from multiple taxa. In this study, we combine acoustic and visual sensor surveys to inform conservation and land use planning in an area experiencing rapid climate and land use change.Location: Mojave Desert, California, United States. Methods: We deployed camera traps and acoustic detectors at 210 sites betweenMarch and July 2016. We identified photographic detections of mammals and acoustic recordings of songbirds to the species level and used multispecies occupancy models to estimate and evaluate species' occupancy probabilities. We then extrapolated model results to the region and forecasted how projected climate and land use changes might affect species' occupancy probabilities in 50 years. Lastly, we identified areas with high conservation value (i.e., high relative species richness) now and in 50 years, and related the distributions of these areas to land use designations. Results:We detected 15 mammal and 68 songbird species. At the community level, occupancy decreased with increasing temperatures and distances to woodlands. We forecasted that occupancy probabilities and areas with high conservation value would decline in 50 years due to projected increases in maximum temperatures and identified that up to 43%, 24% and 27% of land designated for renewable energy development, recreation and military activities, respectively, encompassed these high value areas. Main conclusions:Cooler areas close to woodlands and water are of high conservation value to mammals and songbirds in the Mojave. These areas will become increasingly limited with changing climate, however, making their protection from human disturbance imperative. We encourage continued use of visual and acoustic sensors across large spatial, temporal and taxonomic scales as tools to inform land use and wildlife conservation. K E Y W O R D Sacoustic recorder, camera trap, climate change, land use planning, Mojave Desert, multispecies occupancy model, species richness

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“…Using telemetry data specific to our 1‐month survey windows, gathered in the same general study area, we determined a biologically meaningful range of effective sampling area sizes (quantity often unknown in many wildlife studies) and used it to calculate densities based on track signs of unmarked individuals gathered on transects. As space use data becomes more readily available for many species, this general approach for estimating population density can be applied to other types of wildlife data, such as camera trap data (e.g., Furnas et al., ).…”

Section: Discussionmentioning

confidence: 99%

“…A combination of the two approaches—repeated track counts and noninvasive genetic sampling—could be developed into a hybrid long‐term monitoring protocol (e.g., track‐based monitoring in between the years with genetic monitoring), as combining data types into single analysis frameworks provides improved inference on wildlife populations (Sollmann et al., ). Lastly, as most of the uncertainty affecting the precision of density estimates is due to uncertainties in the effective sampling area, it is recommended to increase resources for GPS collars and provide better coordination of GPS tracking efforts with field surveys (Furnas et al., ). An additional benefit of GPS collar data is that they could be combined with DNA data to improve the precision of spatial capture–recapture designs (Royle, Chandler, Sollmann, & Gardner, ), although implementing such designs at regional scale may exceed the financial possibilities of management agencies in developing countries.…”

Section: Discussionmentioning

confidence: 99%

“…Specifically, the goal of this study was to build on current monitoring methods for game species implemented by the Romanian wildlife authorities and evaluate an alternative approach to estimate brown bear density at the level of game management unit, which integrates repeated track surveys and home range methods. Integrating different data types is an increasingly common practice in wildlife studies, as it leads to improved inferences on animal populations (e.g., Besbeas, Freeman, Morgan, & Catchpole, ; Furnas, Landers, Callas, & Matthews, ; Gopalaswamy et al., ; Ivan, White, & Shenk, ; Sollmann et al., ). In this study, we used repeated track counts to estimate abundances (at transect level) and independent home range information based on GPS telemetry data to calculate brown bear densities.…”

Section: Introductionmentioning

confidence: 99%

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Integrating sign surveys and telemetry data for estimating brown bear (Ursus arctos) density in the Romanian Carpathians

Popescu

Iosif

Pop

et al. 2017

Ecology and Evolution

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Accurate population size estimates are important information for sustainable wildlife management. The Romanian Carpathians harbor the largest brown bear (Ursus arctos) population in Europe, yet current management relies on estimates of density that lack statistical oversight and ignore uncertainty deriving from track surveys. In this study, we investigate an alternative approach to estimate brown bear density using sign surveys along transects within a novel integration of occupancy models and home range methods. We performed repeated surveys along 2‐km segments of forest roads during three distinct seasons: spring 2011, fall‐winter 2011, and spring 2012, within three game management units and a Natura 2000 site. We estimated bears abundances along transects using the number of unique tracks observed per survey occasion via N‐mixture hierarchical models, which account for imperfect detection. To obtain brown bear densities, we combined these abundances with the effective sampling area of the transects, that is, estimated as a function of the median (± bootstrapped SE) of the core home range (5.58 ± 1.08 km2) based on telemetry data from 17 bears tracked for 1‐month periods overlapping our surveys windows. Our analyses yielded average brown bear densities (and 95% confidence intervals) for the three seasons of: 11.5 (7.8–15.3), 11.3 (7.4–15.2), and 12.4 (8.6–16.3) individuals/100 km2. Across game management units, mean densities ranged between 7.5 and 14.8 individuals/100 km2. Our method incorporates multiple sources of uncertainty (e.g., effective sampling area, imperfect detection) to estimate brown bear density, but the inference fundamentally relies on unmarked individuals only. While useful as a temporary approach to monitor brown bears, we urge implementing DNA capture–recapture methods regionally to inform brown bear management and recommend increasing resources for GPS collars to improve estimates of effective sampling area.

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Estimating population size of fishers (Pekania pennanti) using camera stations and auxiliary data on home range size

Cited by 27 publications

References 55 publications

Measuring agreement among experts in classifying camera images of similar species

Measuring agreement among experts in classifying camera images of similar species

Acoustic and camera surveys inform models of current and future vertebrate distributions in a changing desert ecosystem

Integrating sign surveys and telemetry data for estimating brown bear (Ursus arctos) density in the Romanian Carpathians

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