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Vélez J, McShea W, Pukazhenthi B, Stevenson P, Fieberg J. Implications of the scale of detection for inferring co-occurrence patterns from paired camera traps and acoustic recorders. CONSERVATION BIOLOGY : THE JOURNAL OF THE SOCIETY FOR CONSERVATION BIOLOGY 2024; 38:e14218. [PMID: 37937478 DOI: 10.1111/cobi.14218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Revised: 08/29/2023] [Accepted: 10/26/2023] [Indexed: 11/09/2023]
Abstract
Multifunctional landscapes that support economic activities and conservation of biological diversity (e.g., cattle ranches with native forest) are becoming increasingly important because small remnants of native forest may comprise the only habitat left for some wildlife species. Understanding the co-occurrence between wildlife and disturbance factors, such as poaching activity and domesticated ungulates, is key to successful management of multifunctional landscapes. Tools to measure co-occurrence between wildlife and disturbance factors include camera traps and autonomous acoustic recording units. We paired 52 camera-trap stations with acoustic recorders to investigate the association between 2 measures of disturbance (poaching and cattle) and wild ungulates present in multifunctional landscapes of the Colombian Orinoquía. We used joint species distribution models to investigate species-habitat associations and species-disturbance correlations. One model was fitted using camera-trap data to detect wild ungulates and disturbance factors, and a second model was fitted after replacing camera-trap detections of disturbance factors with their corresponding acoustic detections. The direction, significance, and precision of the effect of covariates depended on the sampling method used for disturbance factors. Acoustic monitoring typically resulted in more precise estimates of the effects of covariates and of species-disturbance correlations. Association patterns between wildlife and disturbance factors were found only when disturbance was detected by acoustic recorders. Camera traps allowed us to detect nonvocalizing species, whereas audio recording devices increased detection of disturbance factors leading to more precise estimates of co-occurrence patterns. The collared peccary (Pecari tajacu), lowland tapir (Tapirus terrestris), and white-tailed deer (Odocoileus virginianus) co-occurred with disturbance factors and are conservation priorities due to the greater risk of poaching or disease transmission from cattle.
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Affiliation(s)
- Juliana Vélez
- Department of Fisheries, Wildlife and Conservation Biology, University of Minnesota, St. Paul, Minnesota, USA
- Smithsonian's National Zoo and Conservation Biology Institute, Front Royal, Virginia, USA
| | - William McShea
- Smithsonian's National Zoo and Conservation Biology Institute, Front Royal, Virginia, USA
| | - Budhan Pukazhenthi
- Smithsonian's National Zoo and Conservation Biology Institute, Front Royal, Virginia, USA
| | - Pablo Stevenson
- Departamento de Ciencias Biológicas, Universidad de Los Andes, Bogotá, Colombia
| | - John Fieberg
- Department of Fisheries, Wildlife and Conservation Biology, University of Minnesota, St. Paul, Minnesota, USA
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Russo BM, Jones AS, Clement MJ, Fyffe N, Mesler JI, Rubin ES. Camera trapping as a method for estimating abundance of Mexican wolves. WILDLIFE SOC B 2022. [DOI: 10.1002/wsb.1416] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Affiliation(s)
- Brianna M. Russo
- Arizona Game and Fish Department, Research Branch 5000 W. Carefree Highway Phoenix AZ 85086 USA
| | - Andrew S. Jones
- Arizona Game and Fish Department, Research Branch 5000 W. Carefree Highway Phoenix AZ 85086 USA
| | - Matthew J. Clement
- Arizona Game and Fish Department, Research Branch 5000 W. Carefree Highway Phoenix AZ 85086 USA
| | - Nathan Fyffe
- Arizona Game and Fish Department, Research Branch 5000 W. Carefree Highway Phoenix AZ 85086 USA
| | - Jacob I. Mesler
- Arizona Game and Fish Department, Research Branch 5000 W. Carefree Highway Phoenix AZ 85086 USA
| | - Esther S. Rubin
- Arizona Game and Fish Department, Research Branch 5000 W. Carefree Highway Phoenix AZ 85086 USA
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Hedley RW, Joubert B, Bains HK, Bayne EM. Acoustic detection of gunshots to improve measurement and mapping of hunting activity. WILDLIFE SOC B 2022. [DOI: 10.1002/wsb.1370] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Affiliation(s)
- Richard W. Hedley
- University of Alberta 11335 Saskatchewan Drive NW Edmonton AB T6G 2M9 Canada
| | - Brian Joubert
- Alberta Environment and Parks 9915 108 Street NW Edmonton AB T5K 2G6 Canada
| | - Harsimran K. Bains
- University of Alberta 11335 Saskatchewan Drive NW Edmonton AB T6G 2M9 Canada
| | - Erin M. Bayne
- University of Alberta 11335 Saskatchewan Drive NW Edmonton AB T6G 2M9 Canada
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Larsen HL, Pertoldi C, Madsen N, Randi E, Stronen AV, Root-Gutteridge H, Pagh S. Bioacoustic Detection of Wolves: Identifying Subspecies and Individuals by Howls. Animals (Basel) 2022; 12:ani12050631. [PMID: 35268200 PMCID: PMC8909475 DOI: 10.3390/ani12050631] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Revised: 02/25/2022] [Accepted: 02/28/2022] [Indexed: 11/16/2022] Open
Abstract
Simple Summary This study evaluates the use of acoustic devices as a method to monitor wolves by analyzing different variables extracted from wolf howls. By analyzing the wolf howls, we focused on identifying individual wolves, subspecies. We analyzed 170 howls from 16 individuals from the three subspecies: Arctic wolves (Canis lupus arctos), Eurasian wolves (C.l. lupus), and Northwestern wolves (C.l. occidentalis). We assessed the potential for individual recognition and recognition of three subspecies: Arctic, Eurasian, and Northwestern wolves. Abstract Wolves (Canis lupus) are generally monitored by visual observations, camera traps, and DNA traces. In this study, we evaluated acoustic monitoring of wolf howls as a method for monitoring wolves, which may permit detection of wolves across longer distances than that permitted by camera traps. We analyzed acoustic data of wolves’ howls collected from both wild and captive ones. The analysis focused on individual and subspecies recognition. Furthermore, we aimed to determine the usefulness of acoustic monitoring in the field given the limited data for Eurasian wolves. We analyzed 170 howls from 16 individual wolves from 3 subspecies: Arctic (Canis lupus arctos), Eurasian (C. l. lupus), and Northwestern wolves (C. l. occidentalis). Variables from the fundamental frequency (f0) (lowest frequency band of a sound signal) were extracted and used in discriminant analysis, classification matrix, and pairwise post-hoc Hotelling test. The results indicated that Arctic and Eurasian wolves had subspecies identifiable calls, while Northwestern wolves did not, though this sample size was small. Identification on an individual level was successful for all subspecies. Individuals were correctly classified with 80%–100% accuracy, using discriminant function analysis. Our findings suggest acoustic monitoring could be a valuable and cost-effective tool that complements camera traps, by improving long-distance detection of wolves.
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Affiliation(s)
- Hanne Lyngholm Larsen
- Department of Chemistry and Bioscience, Aalborg University, 9220 Aalborg, Denmark; (C.P.); (N.M.); (E.R.); (A.V.S.); (S.P.)
- Correspondence:
| | - Cino Pertoldi
- Department of Chemistry and Bioscience, Aalborg University, 9220 Aalborg, Denmark; (C.P.); (N.M.); (E.R.); (A.V.S.); (S.P.)
| | - Niels Madsen
- Department of Chemistry and Bioscience, Aalborg University, 9220 Aalborg, Denmark; (C.P.); (N.M.); (E.R.); (A.V.S.); (S.P.)
| | - Ettore Randi
- Department of Chemistry and Bioscience, Aalborg University, 9220 Aalborg, Denmark; (C.P.); (N.M.); (E.R.); (A.V.S.); (S.P.)
| | - Astrid Vik Stronen
- Department of Chemistry and Bioscience, Aalborg University, 9220 Aalborg, Denmark; (C.P.); (N.M.); (E.R.); (A.V.S.); (S.P.)
- Department of Biology, Biotechnical Faculty, University of Ljubljana, 1000 Ljubljana, Slovenia
| | - Holly Root-Gutteridge
- Animal Behaviour, Cognition and Welfare Group, University of Lincoln, Lincoln LN6 7TS, UK;
- School of Animal Rural and Environmental Sciences, Nottingham Trent University, Southwell NG25 0QF, UK
| | - Sussie Pagh
- Department of Chemistry and Bioscience, Aalborg University, 9220 Aalborg, Denmark; (C.P.); (N.M.); (E.R.); (A.V.S.); (S.P.)
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Zwerts JA, Stephenson PJ, Maisels F, Rowcliffe M, Astaras C, Jansen PA, Waarde J, Sterck LEHM, Verweij PA, Bruce T, Brittain S, Kuijk M. Methods for wildlife monitoring in tropical forests: Comparing human observations, camera traps, and passive acoustic sensors. CONSERVATION SCIENCE AND PRACTICE 2021. [DOI: 10.1111/csp2.568] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022] Open
Affiliation(s)
- Joeri A. Zwerts
- Ecology and Biodiversity Utrecht University Utrecht The Netherlands
- Animal Behaviour & Cognition Utrecht University Utrecht The Netherlands
| | - P. J. Stephenson
- IUCN SSC Species Monitoring Specialist Group, Laboratory for Conservation Biology, Department of Ecology & Evolution University of Lausanne Lausanne Switzerland
| | - Fiona Maisels
- Faculty of Natural Sciences University of Stirling FK9 4LA UK
- Global Conservation Program Wildlife Conservation Society 2300 Southern Boulevard Bronx New York USA
| | | | | | - Patrick A. Jansen
- Department of Environmental Sciences Wageningen University Wageningen The Netherlands
- Smithsonian Tropical Research Institute Panama Republic of Panama
| | | | | | - Pita A. Verweij
- Copernicus Institute of Sustainable Development Utrecht University Utrecht The Netherlands
| | - Tom Bruce
- Zoological Society of London Cameroon Yaoundé Cameroon
- James Cook University Townsville Queensland Australia
| | - Stephanie Brittain
- Interdisciplinary Centre for Conservation Science (ICCS), Department of Zoology University of Oxford Oxford UK
| | - Marijke Kuijk
- Ecology and Biodiversity Utrecht University Utrecht The Netherlands
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Cozzi G, Hollerbach L, Suter SM, Reiners TE, Kunz F, Tettamanti F, Ozgul A. Eyes, ears, or nose? Comparison of three non-invasive methods to survey wolf recolonisation. Mamm Biol 2021. [DOI: 10.1007/s42991-021-00167-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
AbstractThe development and use of cost-effective and appropriate survey methods to assess species distribution and to monitor range expansion and contraction of wild populations is crucial due to the limited financial resources for conservation. Of particular importance, yet little studied, is the ability to collect information before a wild population is well established, i.e. at the early stages of recolonisation. During 2018 and 2019, we used camera traps, audio recorders, and scat detection dogs simultaneously to investigate composition, detection probability, and territorial extent of a pack of wolves in the Swiss Alps. We compared the efficacy of these survey methods by assessing sampling effort, data obtained, and costs. We show that, under the presented setup, camera traps and scat detection dogs substantially outperformed audio recorders in detecting wolves, representing the packs’ territorial extent, and revealing the number of adult wolves. The detection dogs did not detect pups but, unlike the other methods, allowed the identification of single individuals. The use of four camera traps during 13 weeks, a 24-km-long transect walked with the detection dog, or the use of one audio recorder during 148 weeks were necessary to obtain a comparable wolf detection probability. Our results show that no single method was able to return all information that we hoped to collect. Comprehensive and cost-effective information was best obtained by combining data from camera traps and detection dogs. We suggest both methods to be simultaneously used to successfully investigate wolf recolonisation into historical range.
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Sadhukhan S, Root-Gutteridge H, Habib B. Identifying unknown Indian wolves by their distinctive howls: its potential as a non-invasive survey method. Sci Rep 2021; 11:7309. [PMID: 33790346 PMCID: PMC8012383 DOI: 10.1038/s41598-021-86718-w] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2020] [Accepted: 03/19/2021] [Indexed: 02/01/2023] Open
Abstract
Previous studies have posited the use of acoustics-based surveys to monitor population size and estimate their density. However, decreasing the bias in population estimations, such as by using Capture-Mark-Recapture, requires the identification of individuals using supervised classification methods, especially for sparsely populated species like the wolf which may otherwise be counted repeatedly. The cryptic behaviour of Indian wolf (Canis lupus pallipes) poses serious challenges to survey efforts, and thus, there is no reliable estimate of their population despite a prominent role in the ecosystem. Like other wolves, Indian wolves produce howls that can be detected over distances of more than 6 km, making them ideal candidates for acoustic surveys. Here, we explore the use of a supervised classifier to identify unknown individuals. We trained a supervised Agglomerative Nesting hierarchical clustering (AGNES) model using 49 howls from five Indian wolves and achieved 98% individual identification accuracy. We tested our model's predictive power using 20 novel howls from a further four individuals (test dataset) and resulted in 75% accuracy in classifying howls to individuals. The model can reduce bias in population estimations using Capture-Mark-Recapture and track individual wolves non-invasively by their howls. This has potential for studies of wolves' territory use, pack composition, and reproductive behaviour. Our method can potentially be adapted for other species with individually distinctive vocalisations, representing an advanced tool for individual-level monitoring.
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Affiliation(s)
- Sougata Sadhukhan
- grid.452923.b0000 0004 1767 4167Animal Ecology and Conservation Biology, Wildlife Institute of India, Dehradun, 248001 India
| | - Holly Root-Gutteridge
- grid.36511.300000 0004 0420 4262Animal Behaviour, Cognition and Welfare Group, University of Lincoln, Lincoln, UK ,grid.12082.390000 0004 1936 7590Reby Lab, School of Psychology, University of Sussex, Brighton, UK
| | - Bilal Habib
- grid.452923.b0000 0004 1767 4167Animal Ecology and Conservation Biology, Wildlife Institute of India, Dehradun, 248001 India
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Cameron J, Crosby A, Paszkowski C, Bayne E. Visual spectrogram scanning paired with an observation–confirmation occupancy model improves the efficiency and accuracy of bioacoustic anuran data. CAN J ZOOL 2020. [DOI: 10.1139/cjz-2020-0103] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Passive acoustic monitoring using autonomous recording units has improved anuran amphibian call survey data collection. A challenge associated with this approach is the time required for audio data processing. Our objective was to develop a more efficient method of processing and analyzing acoustic data through visual spectrogram scanning and the application of an observation–confirmation occupancy model. We compared detection rates between methods of standard recording listening and visually scanning spectrogram images using different spectrogram parameters. Relative to listening, we found that 1 min spectrograms in two 30 s frames yield the best time efficiency–accuracy trade-off. A standard occupancy model applied to visual scanning data underestimated occupancy estimates relative to listening data for three species and overestimated occupancy for one species. The observation–confirmation model used a subset of listening data to improve the estimates of detection probability from visual scanning and therefore reduced bias in occupancy estimates when compared with using visual scanning data alone. Overall, the combination of the visual scanning method and the observation–confirmation model allowed us to maintain the accuracy of occupancy estimates while greatly increasing the efficiency of anuran data processing. These methods are widely applicable and can increase sample size and precision for acoustic monitoring programs using autonomous recording units.
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Affiliation(s)
- J. Cameron
- Department of Biological Sciences, University of Alberta, CW405, Biological Science Building, Edmonton, AB T6G 2R3, Canada
| | - A. Crosby
- Department of Biological Sciences, University of Alberta, CW405, Biological Science Building, Edmonton, AB T6G 2R3, Canada
- Department of Biological Sciences, University of Alberta, CW405, Biological Science Building, Edmonton, AB T6G 2R3, Canada
| | - C. Paszkowski
- Department of Biological Sciences, University of Alberta, CW405, Biological Science Building, Edmonton, AB T6G 2R3, Canada
- Department of Biological Sciences, University of Alberta, CW405, Biological Science Building, Edmonton, AB T6G 2R3, Canada
| | - E. Bayne
- Department of Biological Sciences, University of Alberta, CW405, Biological Science Building, Edmonton, AB T6G 2R3, Canada
- Department of Biological Sciences, University of Alberta, CW405, Biological Science Building, Edmonton, AB T6G 2R3, Canada
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Barber‐Meyer SM, Palacios V, Marti‐Domken B, Schmidt LJ. Testing a New Passive Acoustic Recording Unit to Monitor Wolves. WILDLIFE SOC B 2020. [DOI: 10.1002/wsb.1117] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Shannon M. Barber‐Meyer
- United States Geological Survey Northern Prairie Wildlife Research Center 8711 37th Street, SE Jamestown ND 58401‐7317 USA
| | - Vicente Palacios
- ARCA, People and Nature, S.L. Spain
- Association for the Conservation of Nature in Human Environments C/Fontana, 2 49337 Villanueva de Valrojo Spain
| | - Barbara Marti‐Domken
- Association for the Conservation of Nature in Human Environments C/Fontana, 2 49337 Villanueva de Valrojo Spain
| | - Lori J. Schmidt
- The International Wolf Center 1393 Highway 169 Ely MN 55731 USA
- Vermilion Community College 1900 E Camp Street Ely MN 55731 USA
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