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Henk M, Hilson C, Bean WT, Barton DC, Gunther MS. Noninvasive genetic sampling with a spatial capture‐recapture analysis to estimate abundance of Roosevelt elk. J Wildl Manage 2022. [DOI: 10.1002/jwmg.22294] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
- Makenzie Henk
- Department of Wildlife California State Polytechnic University, Humboldt, 1 Harpst Street Arcata CA 95521 USA
| | - Carrington Hilson
- California Department of Fish and Wildlife, 619 2nd Street Eureka CA 95501 USA
| | - William T. Bean
- Department of Wildlife California State Polytechnic University, Humboldt, 1 Harpst Street Arcata CA 95521 USA
| | - Daniel C. Barton
- Department of Wildlife California State Polytechnic University, Humboldt, 1 Harpst Street Arcata CA 95521 USA
| | - Micaela Szykman Gunther
- Department of Wildlife California State Polytechnic University, Humboldt, 1 Harpst Street Arcata CA 95521 USA
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2
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Hennig JD, Schoenecker KA, Cain JW, Roemer GW, Laake JL. Accounting for residual heterogeneity in double‐observer sightability models decreases bias in burro abundance estimates. J Wildl Manage 2022. [DOI: 10.1002/jwmg.22239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
- Jacob D. Hennig
- Contractor with the U.S. Geological Survey, Fort Collins Science Center 2150 Centre Ave Fort Collins CO 80526 USA
| | - Kathryn A. Schoenecker
- U.S. Geological Survey, Fort Collins Science Center 2150 Centre Ave Fort Collins CO 80526 USA
| | - James W. Cain
- U.S. Geological Survey, New Mexico Cooperative Fish and Wildlife Research Unit, Department of Fish, Wildlife, and Conservation Ecology New Mexico State University Las Cruces NM 88003 USA
| | - Gary W. Roemer
- Department of Fish, Wildlife, and Conservation Ecology New Mexico State University Las Cruces NM 88003 USA
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3
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Gedir JV, Cain JW, Lubow BC, Karish T, Delaney DK, Roemer GW. Estimating Abundance and Simulating Fertility Control in a Feral Burro Population. J Wildl Manage 2021. [DOI: 10.1002/jwmg.22058] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Affiliation(s)
- Jay V. Gedir
- Department of Fish, Wildlife and Conservation Ecology, New Mexico State University, Las Cruces NM 88003 USA
| | - James W. Cain
- U.S. Geological Survey, New Mexico Cooperative Fish and Wildlife Research Unit, Department of Fish, Wildlife and Conservation Ecology, New Mexico State University, Las Cruces NM 88003 USA
| | | | - Talesha Karish
- Department of Fish, Wildlife and Conservation Ecology, New Mexico State University, Las Cruces NM 88003 USA
| | - David K. Delaney
- U.S. Army Construction Engineering Research Laboratory Champaign IL 61826 USA
| | - Gary W. Roemer
- Department of Fish, Wildlife and Conservation Ecology, New Mexico State University, Las Cruces NM 88003 USA
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4
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Hennig JD, Schoenecker KA, Terwilliger ML, Holm GW, Laake JL. Comparison of Aerial Thermal Infrared Imagery and Helicopter Surveys of Bison ( Bison bison) in Grand Canyon National Park, USA. SENSORS 2021; 21:s21155087. [PMID: 34372324 PMCID: PMC8348576 DOI: 10.3390/s21155087] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Revised: 07/03/2021] [Accepted: 07/08/2021] [Indexed: 11/16/2022]
Abstract
Aerial thermal infrared (TIR) surveys are an attractive option for estimating abundances of large mammals inhabiting extensive and heterogeneous terrain. Compared to standard helicopter or fixed-wing aerial surveys, TIR flights can be conducted at higher altitudes translating into greater spatial coverage and increased observer safety; however, monetary costs are much greater. Further, there is no consensus on whether TIR surveys offer improved detection. Consequently, we performed a study to compare results of a TIR and helicopter survey of bison (Bison bison) on the Powell Plateau in Grand Canyon National Park, USA. We also compared results of both surveys to estimates obtained using a larger dataset of bison helicopter detections along the entire North Rim of the Grand Canyon. Observers in the TIR survey counted fewer individual bison than helicopter observers (101 to 127) and the TIR survey cost was 367% higher. Additionally, the TIR estimate was 18.8% lower than the estimate obtained using a larger dataset, while the comparative helicopter survey was 9.3% lower. Despite our small sample size, we found that helicopter surveys are currently the best method for estimating bison abundances in dense canopy cover sites due to ostensibly more accurate estimates and lower cost compared to TIR surveys. Additional research will be needed to evaluate the efficacy of these methods, as well as very high resolution satellite imagery, for bison populations in more open landscapes.
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Affiliation(s)
- Jacob D. Hennig
- Contractor with the U.S. Geological Survey, Fort Collins Science Center, Fort Collins, CO 80526, USA
- Correspondence:
| | | | - Miranda L.N. Terwilliger
- National Park Service, Grand Canyon National Park, Grand Canyon, AZ 86023, USA; (M.L.N.T.); (G.W.H.)
| | - Gregory W. Holm
- National Park Service, Grand Canyon National Park, Grand Canyon, AZ 86023, USA; (M.L.N.T.); (G.W.H.)
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5
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DYAL JORDANR, Miller KV, Cherry MJ, D'Angelo GJ. Estimating Sightability for Helicopter Surveys Using Surrogates of White‐Tailed Deer. J Wildl Manage 2021. [DOI: 10.1002/jwmg.22040] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
- JORDAN R. DYAL
- Daniel B. Warnell School of Forestry and Natural Resources University of Georgia 180 E Green Street Athens GA 30602 USA
| | - Karl V. Miller
- Daniel B. Warnell School of Forestry and Natural Resources University of Georgia 180 E Green Street Athens GA 30602 USA
| | - Michael J. Cherry
- Caesar Kleberg Wildlife Research Institute Texas A&M University‐Kingsville 700 University Boulevard Kingsville TX 78363 USA
| | - Gino J. D'Angelo
- Daniel B. Warnell School of Forestry and Natural Resources University of Georgia 180 E Green Street Athens GA 30602 USA
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6
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Bristow KD, Clement MJ, Crabb ML, Harding LE, Rubin ES. Comparison of aerial survey methods for elk in Arizona. WILDLIFE SOC B 2019. [DOI: 10.1002/wsb.940] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Kirby D. Bristow
- Arizona Game and Fish Department5000 W Carefree HighwayPhoenixAZ85086USA
| | - Matthew J. Clement
- Arizona Game and Fish Department5000 W Carefree HighwayPhoenixAZ85086USA
| | - Michelle L. Crabb
- Arizona Game and Fish Department5000 W Carefree HighwayPhoenixAZ85086USA
| | - Larisa E. Harding
- Arizona Game and Fish Department5000 W Carefree HighwayPhoenixAZ85086USA
| | - Esther S. Rubin
- Arizona Game and Fish Department5000 W Carefree HighwayPhoenixAZ85086USA
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7
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Conroy MJ, Harris G, Stewart DR, Butler MJ. Evaluation of desert bighorn sheep abundance surveys, southwestern Arizona, USA. J Wildl Manage 2018. [DOI: 10.1002/jwmg.21463] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Michael J. Conroy
- Warnell School of Forestry and Natural Resources; University of Georgia; Athens GA 30602 USA
| | - Grant Harris
- U.S. Fish and Wildlife Service; P.O. Box 1306 Albuquerque NM 87103 USA
| | - David R. Stewart
- U.S. Fish and Wildlife Service; P.O. Box 1306 Albuquerque NM 87103 USA
| | - Matthew J. Butler
- U.S. Fish and Wildlife Service; P.O. Box 1306 Albuquerque NM 87103 USA
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Barnas AF, Felege CJ, Rockwell RF, Ellis-Felege SN. A pilot(less) study on the use of an unmanned aircraft system for studying polar bears (Ursus maritimus). Polar Biol 2018. [DOI: 10.1007/s00300-018-2270-0] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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Baumgardt JA, Reese KP, Connelly JW, Garton EO. Visibility bias for sage-grouse lek counts. WILDLIFE SOC B 2017. [DOI: 10.1002/wsb.800] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Affiliation(s)
- Jeremy A. Baumgardt
- Fish and Wildlife Sciences; University of Idaho; P.O. Box 441136 Moscow ID 83844 USA
| | - Kerry P. Reese
- Fish and Wildlife Sciences; University of Idaho; P.O. Box 441136 Moscow ID 83844 USA
| | - John W. Connelly
- Fish and Wildlife Sciences; University of Idaho; P.O. Box 441136 Moscow ID 83844 USA
| | - Edward O. Garton
- Fish and Wildlife Sciences; University of Idaho; P.O. Box 441136 Moscow ID 83844 USA
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Clement MJ, Converse SJ, Royle JA. Accounting for imperfect detection of groups and individuals when estimating abundance. Ecol Evol 2017; 7:7304-7310. [PMID: 28944018 PMCID: PMC5606903 DOI: 10.1002/ece3.3284] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2017] [Revised: 06/16/2017] [Accepted: 06/28/2017] [Indexed: 11/29/2022] Open
Abstract
If animals are independently detected during surveys, many methods exist for estimating animal abundance despite detection probabilities <1. Common estimators include double‐observer models, distance sampling models and combined double‐observer and distance sampling models (known as mark‐recapture‐distance‐sampling models; MRDS). When animals reside in groups, however, the assumption of independent detection is violated. In this case, the standard approach is to account for imperfect detection of groups, while assuming that individuals within groups are detected perfectly. However, this assumption is often unsupported. We introduce an abundance estimator for grouped animals when detection of groups is imperfect and group size may be under‐counted, but not over‐counted. The estimator combines an MRDS model with an N‐mixture model to account for imperfect detection of individuals. The new MRDS‐Nmix model requires the same data as an MRDS model (independent detection histories, an estimate of distance to transect, and an estimate of group size), plus a second estimate of group size provided by the second observer. We extend the model to situations in which detection of individuals within groups declines with distance. We simulated 12 data sets and used Bayesian methods to compare the performance of the new MRDS‐Nmix model to an MRDS model. Abundance estimates generated by the MRDS‐Nmix model exhibited minimal bias and nominal coverage levels. In contrast, MRDS abundance estimates were biased low and exhibited poor coverage. Many species of conservation interest reside in groups and could benefit from an estimator that better accounts for imperfect detection. Furthermore, the ability to relax the assumption of perfect detection of individuals within detected groups may allow surveyors to re‐allocate resources toward detection of new groups instead of extensive surveys of known groups. We believe the proposed estimator is feasible because the only additional field data required are a second estimate of group size.
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Affiliation(s)
- Matthew J Clement
- U.S. Geological Survey Patuxent Wildlife Research Center Laurel MD USA.,Arizona Game and Fish Department Phoenix AZ USA
| | - Sarah J Converse
- U.S. Geological Survey Patuxent Wildlife Research Center Laurel MD USA.,U.S. Geological Survey Washington Cooperative Fish and Wildlife Research Unit School of Environmental and Forest Sciences (SEFS) and School of Aquatic and Fishery Sciences (SAFS) University of Washington Seattle WA USA
| | - J Andrew Royle
- U.S. Geological Survey Patuxent Wildlife Research Center Laurel MD USA
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Golding JD, Nowak JJ, Dreitz VJ. A multispecies dependent double-observer model: A new method for estimating multispecies abundance. Ecol Evol 2017; 7:3425-3435. [PMID: 28515878 PMCID: PMC5433993 DOI: 10.1002/ece3.2946] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2016] [Revised: 02/25/2017] [Accepted: 03/03/2017] [Indexed: 11/23/2022] Open
Abstract
Conservation of biological communities requires accurate estimates of abundance for multiple species. Recent advances in estimating abundance of multiple species, such as Bayesian multispecies N‐mixture models, account for multiple sources of variation, including detection error. However, false‐positive errors (misidentification or double counts), which are prevalent in multispecies data sets, remain largely unaddressed. The dependent‐double observer (DDO) method is an emerging method that both accounts for detection error and is suggested to reduce the occurrence of false positives because it relies on two observers working collaboratively to identify individuals. To date, the DDO method has not been combined with advantages of multispecies N‐mixture models. Here, we derive an extension of a multispecies N‐mixture model using the DDO survey method to create a multispecies dependent double‐observer abundance model (MDAM). The MDAM uses a hierarchical framework to account for biological and observational processes in a statistically consistent framework while using the accurate observation data from the DDO survey method. We demonstrate that the MDAM accurately estimates abundance of multiple species with simulated and real multispecies data sets. Simulations showed that the model provides both precise and accurate abundance estimates, with average credible interval coverage across 100 repeated simulations of 94.5% for abundance estimates and 92.5% for detection estimates. In addition, 92.2% of abundance estimates had a mean absolute percent error between 0% and 20%, with a mean of 7.7%. We present the MDAM as an important step forward in expanding the applicability of the DDO method to a multispecies setting. Previous implementation of the DDO method suggests the MDAM can be applied to a broad array of biological communities. We suggest that researchers interested in assessing biological communities consider the MDAM as a tool for deriving accurate, multispecies abundance estimates.
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Affiliation(s)
- Jessie D Golding
- Avian Science Center Wildlife Biology Program University of Montana Missoula MT USA
| | - J Joshua Nowak
- Wildlife Biology Program University of Montana Missoula MT USA
| | - Victoria J Dreitz
- Avian Science Center Wildlife Biology Program University of Montana Missoula MT USA
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Reilly BK, van Hensbergen HJ, Eiselen RJ, Fleming PJS. Statistical power of replicated helicopter surveys in southern African conservation areas. Afr J Ecol 2016. [DOI: 10.1111/aje.12341] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Affiliation(s)
- Brian K. Reilly
- Department of Nature Conservation; Tshwane University of Technology; Private Bag X680 Pretoria 0001 South Africa
| | | | - Riette J. Eiselen
- Department of Finance and Investment Management; University of Johannesburg; PO Box 524 Auckland Park 2006 South Africa
| | - Peter J. S. Fleming
- Vertebrate Pest Research Unit; Biosecurity NSW; Orange Agricultural Institute; 1447 Forest Road Orange NSW 2800 Australia
- School of Environmental and Rural Sciences; University of New England; Armidale NSW 2351 Australia
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Lubow BC, Ransom JI. Practical Bias Correction in Aerial Surveys of Large Mammals: Validation of Hybrid Double-Observer with Sightability Method against Known Abundance of Feral Horse (Equus caballus) Populations. PLoS One 2016; 11:e0154902. [PMID: 27139732 PMCID: PMC4854450 DOI: 10.1371/journal.pone.0154902] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2016] [Accepted: 04/20/2016] [Indexed: 11/21/2022] Open
Abstract
Reliably estimating wildlife abundance is fundamental to effective management. Aerial surveys are one of the only spatially robust tools for estimating large mammal populations, but statistical sampling methods are required to address detection biases that affect accuracy and precision of the estimates. Although various methods for correcting aerial survey bias are employed on large mammal species around the world, these have rarely been rigorously validated. Several populations of feral horses (Equus caballus) in the western United States have been intensively studied, resulting in identification of all unique individuals. This provided a rare opportunity to test aerial survey bias correction on populations of known abundance. We hypothesized that a hybrid method combining simultaneous double-observer and sightability bias correction techniques would accurately estimate abundance. We validated this integrated technique on populations of known size and also on a pair of surveys before and after a known number was removed. Our analysis identified several covariates across the surveys that explained and corrected biases in the estimates. All six tests on known populations produced estimates with deviations from the known value ranging from -8.5% to +13.7% and <0.7 standard errors. Precision varied widely, from 6.1% CV to 25.0% CV. In contrast, the pair of surveys conducted around a known management removal produced an estimated change in population between the surveys that was significantly larger than the known reduction. Although the deviation between was only 9.1%, the precision estimate (CV = 1.6%) may have been artificially low. It was apparent that use of a helicopter in those surveys perturbed the horses, introducing detection error and heterogeneity in a manner that could not be corrected by our statistical models. Our results validate the hybrid method, highlight its potentially broad applicability, identify some limitations, and provide insight and guidance for improving survey designs.
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Affiliation(s)
- Bruce C. Lubow
- Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, Colorado, 80523, United States of America
| | - Jason I. Ransom
- U.S. Geological Survey, Fort Collins Science Center, Fort Collins, Colorado, 80526, United States of America
- * E-mail:
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Forsyth DM, MacKenzie DI, Wright EF. Monitoring ungulates in steep non-forest habitat: a comparison of faecal pellet and helicopter counts. NEW ZEALAND JOURNAL OF ZOOLOGY 2014. [DOI: 10.1080/03014223.2014.936881] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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