Effectiveness of a distance sampling from roads program for white-tailed deer in the National Capital Region parks

Green, Nicholas S.; Wildhaber, Mark L.; Albers, Janice L.

doi:10.36967/nrr-2284469

Cited by 2 publications

(6 citation statements)

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“…We fit 14 CDS models (i.e., combinations of key function and series adjustment terms) to each of the 630 simulated datasets (Supplemental Information Table S1). Full details of the analysis are presented in the Supplemental Information and followed the procedure used by Green et al (2021). We calculated the variance of each population size estimate using the R 2 estimator of Fewster et al (2009).…”

Section: Discussionmentioning

confidence: 99%

“…Simulated distance surveys were constructed by applying a detection function to determine each simulated cluster's probability of detection based on minimum perpendicular distance from the transect. The detection function used was the one most frequently selected as the best fitting in a previous analysis of park surveys (Green et al 2021). The probability of a cluster of deer being detected was modeled using a uniform key function with one cosine series adjustment (Buckland et al 2001):

g(x)=\frac{1+{{\rm{\alpha }}}_{1}\cos (\pi {x}_{s})}{1+{{\rm{\alpha }}}_{1}}

where g ( x ) is the detection probability,

{{\rm{\alpha }}}_{1}

is a coefficient estimated from survey data, π is the ratio of a circle's circumference to its diameter, and x s is the standardized distance (observed distance divided by the maximum observed distance).…”

Section: Methodsmentioning

confidence: 99%

“…For each simulated analysis, the observed distances were pooled by transect across the 3 sampling nights (Buckland et al 2001). Distances were then grouped into intervals, with the cut points for intervals determined based on guidelines suggested by Buckland et al (2001) and a procedure previously used by Green et al (2021). Thus, cut points for the distances in each of the 630 simulated surveys were determined independently of the other simulations.…”

Section: Methodsmentioning

confidence: 99%

“…The size of the simulated deer population was set to the mean estimated deer population size of 920 deer for the focal park (CATO) for the years 2001−2011 (Green et al 2021). Mean cluster size for those 11 years (1.70 deer) was maintained in the simulated data by drawing sizes of simulated clusters from a Poisson distribution.…”

Section: Deer Population Simulationsmentioning

confidence: 99%

Section: Deer Population Simulationsmentioning

confidence: 99%

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Interaction between transect design and animal distribution in distance sampling of deer

Green

Wildhaber

Albers

2022

Wildlife Society Bulletin

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We conducted a simulation study to evaluate the consequences of violating statistical assumptions of distance sampling (DS) on the bias and precision of population estimates of white‐tailed deer (Odocoileus virginianus). Distance sampling is a method for estimating the density of organisms using a distribution of observed distances to individuals. A key assumption of DS is that sampling transects are randomly located with respect to the population being sampled. Most DS transects used in National Parks follow roads and trails, which are not positioned randomly. We constructed spatially explicit simulations of surveys using 7 different types of deer spatial distributions and 3 survey designs. A significant interaction between survey type and deer distribution type explained most of the variation in population estimates across simulations and this interaction was also a significant predictor of the coefficient of variation (CV) of population estimates. Simulation results suggested that 1) non‐road surveys were more robust to bias than were road surveys, 2) effectiveness of each of 3 survey types was dependent on the way deer were distributed across the landscape, and 3) non‐road surveys produced unbiased estimates of populations affected by roads, whereas road surveys did not. The results of our study suggest that DS surveys using pre‐existing roads and trails have potential biases resulting from study design, something that could be considered by land managers when constructing surveys.

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Section: Discussionmentioning

confidence: 99%

g(x)=\frac{1+{{\rm{\alpha }}}_{1}\cos (\pi {x}_{s})}{1+{{\rm{\alpha }}}_{1}}

where g ( x ) is the detection probability,

{{\rm{\alpha }}}_{1}

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Deer Population Simulationsmentioning

confidence: 99%

Section: Deer Population Simulationsmentioning

confidence: 99%

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Interaction between transect design and animal distribution in distance sampling of deer

Green

Wildhaber

Albers

2022

Wildlife Society Bulletin

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Enumerating White‐Tailed Deer Using Unmanned Aerial Vehicles

Preston

Wildhaber

Green

et al. 2021

Wildlife Society Bulletin

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The white‐tailed deer (Odocoileus virginianus) is an ecologically important species in forests of North America. Effective management of forests requires accurate, precise estimates of deer population abundance to plan and justify management actions. Spotlight surveys in combination with distance sampling are a common method of estimating deer population abundance; however, spotlight surveys are known to have serious drawbacks such as high costs and sampling biases. Therefore, we tested the effectiveness of enumerating deer from unmanned aerial vehicle (UAV) flights, conducted 1 and 6 March 2018, to develop population and density estimates in 2 United States National Parks: Harpers Ferry National Historic Park (HAFE) and Monocacy National Battlefield (MONO). Concurrent spotlight surveys at MONO enabled us to compare estimates obtained by the 2 methods. Deer density estimates by 4 observers of UAV‐obtained thermal imagery from HAFE were 94.5 ± 3.9 deer/km2. Concurrent UAV and spotlight surveys at MONO found 19.7 ± 0.5 deer/km2 and 6.4 ± 4.9 deer/km2, respectively; suggesting that spotlight surveys may significantly underestimate deer densities. Despite the logistical challenges to UAV operation, our findings demonstrate that UAVs will become an invaluable tool for wildlife management as technology improves. © 2021 The Wildlife Society. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

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Effectiveness of a distance sampling from roads program for white-tailed deer in the National Capital Region parks

Cited by 2 publications

References 0 publications

Interaction between transect design and animal distribution in distance sampling of deer

Interaction between transect design and animal distribution in distance sampling of deer

Enumerating White‐Tailed Deer Using Unmanned Aerial Vehicles

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