Blum, M. E., Buderman, F. E., Bennett, J. R., Stewart, K. M., Cox, M., & Williams, P. J. 2024, Comparing contemporary models to traditional indices to estimate abundance of desert bighorn sheep, The Journal of Wildlife Management, 88(2), e22517

Abstract

Aerial surveys for large ungulates produce count data that often underrepresent the number of animals. Errors in count data can lead to erroneous estimates of abundance if they are not addressed. Our objective was to address imperfect detection probability by developing a framework that produces realistic and defensible estimates of bighorn sheep (Ovis canadensis) abundance. We applied our framework to a population of desert bighorn sheep (O. c. nelsoni) in the Great Basin, Nevada, USA. We captured and marked 24 desert bighorn sheep with global positioning system (GPS)-collars and then conducted helicopter surveys naïve to the locations of collared animals. We developed a Bayesian integrated data model to leverage information from telemetry data, helicopter survey counts, and habitat characteristics to estimate abundance while accounting for availability and perception probability (i.e., detection given availability). Distance to ridgeline, terrain ruggedness, tree cover, and slope influenced perception probability of sheep given they were viewable from the helicopter. There was also annual variation in perception probability (2018: median = 0.64, credible interval [CrI] = 0.37–0.87; 2019: median = 0.81, CrI = 0.49–0.97). The abundance estimates from the integrated data model decreased from 2018 (594; 95% CrI = 537–656) to 2019 (487; 95% CrI = 436–551). In addition, accounting for availability and imperfect perception resulted in greater estimates of abundance compared to traditional directed search methods, which were 340 for 2018 and 320 for 2019. Our modeling framework can be used to generate more defensible population estimates of bighorn sheep and other large mammals that have been surveyed in a similar manner.

Learn more about the author(s)

 

Also of Interest:

 
Scorching sun and a thermometer reading over 100 degrees
Heat Illness and Hydration
Summer heat is no surprise to southern Nevada, but northern Nevada has its fair share of excessive heat warning days. It is a ruthless and even deadly problem. According to the Centers for Disease Control, nearly 1,200 Americans die from extreme heat each year, many who do not re...
Mazzullo, N. 2024, Extension | University of Nevada, Reno
Effects of isoenergetic supplementation as water use mitigation strategy on water footprint and health of nursing bull calves Franco, A. M., da Silva, A. E. M., de Moura, F. H., Norris, A. B., Roloson, S. B., Gerrard, D. E.; De Mello, A. S.; Fonseca, M. A. 2023, Transl Anim Sci. 2023 Nov 16;7(1):txad127
Climate data and information needs of indigenous communities on reservation lands: insights from stakeholders in the Southwestern United States.
This study provides empirical evidence specific to the climate adaptation needs of Indigenous community in the arid southwestern USA. Study respondents prioritize climate information and data that serve to assess local climate change impacts, enhance food security, and integrate ...
Fillmore, H. and Singletary, L. 2021, Climatic Change, 169(37)
tomatoes on the vine
Combatting Salinity: Evaluation of Tomato Rootstocks Under Mild and Severe Salt Stress
This Extension publication reports the results of University of Nevada, Reno Experiment Station research that tested six different commercial tomato rootstocks and one commercial tomato cultivar for salt tolerance under low, moderate and severe salinity levels.
Bonarota, M.S., Barrios-Masias, F.H., & Singletary, L. 2021, Extension, University of Nevada, Reno FS-21-08
yarrow
Groundcover Plants for Southern Nevada: Viable Alternatives to Turfgrass
Groundcover plants are essential for keeping southern Nevada cool. While many desert residents are removing turfgrass to reduce water use, they should consider replacing it with the attractive, drought tolerant alternatives discussed in this publication.
McGue, L., Robinson, M.L., O'Callaghan, A.O. and Leas, L. 2021, Extension, University of Nevada, Reno, FS-21-93