Accurate population estimation of Caprinae using camera traps and distance sampling

被引:0
|
作者
Grant M. Harris
Matthew J. Butler
David R. Stewart
Eric M. Rominger
Caitlin Q. Ruhl
机构
[1] United States Fish and Wildlife Service,
[2] New Mexico Department of Game and Fish,undefined
来源
Scientific Reports | / 10卷
关键词
D O I
暂无
中图分类号
学科分类号
摘要
With most of the world’s Caprinae taxa threatened with extinction, the IUCN appeals to the development of simple and affordable sampling methods that will produce credible abundance and distribution data for helping conserve these species inhabiting remote areas. Traditional sampling approaches, like aerial sampling or mark-capture-recapture, can generate bias by failing to meet sampling assumptions, or by incurring too much cost and logistical burden for most projects to address them. Therefore, we met the IUCN’s challenge by testing a sampling technique that leverages imagery from camera traps with conventional distance sampling, validating its operability in mountainous topography by comparing results to known abundances. Our project occurred within a captive facility housing a wild population of desert bighorn sheep (Ovis canadensis) in the Chihuahuan desert of New Mexico, which is censused yearly. True abundance was always within our 90% confidence bounds, and the mean abundance estimates were within 4.9 individuals (average) of the census values. By demonstrating the veracity of this straightforward and inexpensive sampling method, we provide confidence in its operability, urging its use to fill conservation voids for Caprinae and other data-deficient species inhabiting rugged or heavily vegetated terrain.
引用
收藏
相关论文
共 50 条
  • [1] Accurate population estimation of Caprinae using camera traps and distance sampling
    Harris, Grant M.
    Butler, Matthew J.
    Stewart, David R.
    Rominger, Eric M.
    Ruhl, Caitlin Q.
    SCIENTIFIC REPORTS, 2020, 10 (01)
  • [2] Distance sampling with camera traps
    Howe, Eric J.
    Buckland, Stephen T.
    Despres-Einspenner, Marie-Lyne
    Kuehl, Hjalmar S.
    METHODS IN ECOLOGY AND EVOLUTION, 2017, 8 (11): : 1558 - 1565
  • [3] Estimating forest antelope population densities using distance sampling with camera traps
    Amin, Rajan
    Klair, Hannah
    Wacher, Tim
    Ndjassi, Constant
    Fowler, Andrew
    Olson, David
    Bruce, Tom
    ORYX, 2022, 56 (03) : 345 - 351
  • [4] Estimating mesocarnivore abundance on commercial farmland using distance sampling with camera traps
    McKaughan, Jamie E. T.
    Stephens, Philip A.
    Hill, Russell A.
    ECOLOGICAL SOLUTIONS AND EVIDENCE, 2023, 4 (02):
  • [5] Quantifying the sensitivity of camera traps: an adapted distance sampling approach
    Rowcliffe, J. Marcus
    Carbone, Chris
    Jansen, Patrick A.
    Kays, Roland
    Kranstauber, Bart
    METHODS IN ECOLOGY AND EVOLUTION, 2011, 2 (05): : 464 - 476
  • [6] A semi-automated camera trap distance sampling approach for population density estimation
    Henrich, Maik
    Burgueno, Mercedes
    Hoyer, Jacqueline
    Haucke, Timm
    Steinhage, Volker
    Kuehl, Hjalmar S.
    Heurich, Marco
    REMOTE SENSING IN ECOLOGY AND CONSERVATION, 2024, 10 (02) : 156 - 171
  • [7] Using distance sampling with camera traps to estimate the density of group-living and solitary mountain ungulates
    Pal, Ranjana
    Bhattacharya, Tapajit
    Qureshi, Qamar
    Buckland, Stephen T.
    Sathyakumar, Sambandam
    ORYX, 2021, 55 (05) : 668 - 676
  • [8] Overcoming the distance estimation bottleneck in estimating animal abundance with camera traps
    Haucke, Timm
    Kuehl, Hjalmar S.
    Hoyer, Jacqueline
    Steinhage, Volker
    ECOLOGICAL INFORMATICS, 2022, 68
  • [9] Population estimation of Asiatic black bear in the Himalayan Region of India using camera traps
    Bhattacharya, Ankita
    Chatterjee, Nilanjan
    Angrish, Kunal
    Meena, Dharamveer
    Sinha, Bitapi C.
    Habib, Bilal
    URSUS, 2022, 33 (E8)
  • [10] Assessing mammal population densities in response to urbanization using camera trap distance sampling
    Li, Zhilin
    Shi, Xiaoyi
    Lu, Jiayu
    Fu, Xiaohang
    Fu, Yu
    Cui, Yating
    Chen, Lu
    Duo, Li'an
    Wang, Le
    Wang, Tianming
    ECOLOGY AND EVOLUTION, 2023, 13 (10):