1
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Angelakis N, Goldsworthy SD, Connell SD, Durante LM. A novel method for identifying fine-scale bottom-use in a benthic-foraging pinniped. MOVEMENT ECOLOGY 2023; 11:34. [PMID: 37296462 PMCID: PMC10257308 DOI: 10.1186/s40462-023-00386-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 04/16/2023] [Indexed: 06/12/2023]
Abstract
BACKGROUND For diving, marine predators, accelerometer and magnetometer data provides critical information on sub-surface foraging behaviours that cannot be identified from location or time-depth data. By measuring head movement and body orientation, accelerometers and magnetometers can help identify broad shifts in foraging movements, fine-scale habitat use and energy expenditure of terrestrial and marine species. Here, we use accelerometer and magnetometer data from tagged Australian sea lions and provide a new method to identify key benthic foraging areas. As Australian sea lions are listed as endangered by the IUCN and Australian legislation, identifying key areas for the species is vital to support targeted management of populations. METHODS Firstly, tri-axial magnetometer and accelerometer data from adult female Australian sea lions is used in conjunction with GPS and dive data to dead-reckon their three-dimensional foraging paths. We then isolate all benthic phases from their foraging trips and calculate a range of dive metrics to characterise their bottom usage. Finally, k-means cluster analysis is used to identify core benthic areas utilised by sea lions. Backwards stepwise regressions are then iteratively performed to identify the most parsimonious model for describing bottom usage and its included predictor variables. RESULTS Our results show distinct spatial partitioning in benthic habitat-use by Australian sea lions. This method has also identified individual differences in benthic habitat-use. Here, the application of high-resolution magnetometer/accelerometer data has helped reveal the tortuous foraging movements Australian sea lions use to exploit key benthic marine habitats and features. CONCLUSIONS This study has illustrated how magnetometer and accelerometer data can provide a fine-scale description of the underwater movement of diving species, beyond GPS and depth data alone, For endangered species like Australian sea lions, management of populations must be spatially targeted. Here, this method demonstrates a fine-scale analysis of benthic habitat-use which can help identify key areas for both marine and terrestrial species. Future integration of this method with concurrent habitat and prey data would further augment its power as a tool for understanding the foraging behaviours of species.
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Affiliation(s)
- Nathan Angelakis
- University of Adelaide, North Terrace, Adelaide, SA, 5000, Australia.
| | - Simon D Goldsworthy
- University of Adelaide, North Terrace, Adelaide, SA, 5000, Australia
- South Australian Research and Development Institute (SARDI) (Aquatic Sciences), 2 Hamra Avenue, West Beach, SA, 5024, Australia
| | - Sean D Connell
- University of Adelaide, North Terrace, Adelaide, SA, 5000, Australia
| | - Leonardo M Durante
- South Australian Research and Development Institute (SARDI) (Aquatic Sciences), 2 Hamra Avenue, West Beach, SA, 5024, Australia
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2
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Redpath SHA, Marks NJ, Menzies FD, O'Hagan MJH, Wilson RP, Smith S, Magowan EA, McClune DW, Collins SF, McCormick CM, Scantlebury DM. Impact of test, vaccinate or remove protocol on home ranges and nightly movements of badgers a medium density population. Sci Rep 2023; 13:2592. [PMID: 36788237 PMCID: PMC9929337 DOI: 10.1038/s41598-023-28620-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Accepted: 01/20/2023] [Indexed: 02/16/2023] Open
Abstract
In the British Isles, the European badger (Meles meles) is thought to be the primary wildlife reservoir of bovine tuberculosis (bTB), an endemic disease in cattle. Test, vaccinate or remove ('TVR') of bTB test-positive badgers, has been suggested to be a potentially useful protocol to reduce bTB incidence in cattle. However, the practice of removing or culling badgers is controversial both for ethical reasons and because there is no consistent observed effect on bTB levels in cattle. While removing badgers reduces population density, it may also result in disruption of their social behaviour, increase their ranging, and lead to greater intra- and inter-species bTB transmission. This effect has been recorded in high badger density areas, such as in southwest England. However, little is known about how TVR affects the behaviour and movement of badgers within a medium density population, such as those that occur in Northern Ireland (NI), which the current study aimed to examine. During 2014-2017, badger ranging behaviours were examined prior to and during a TVR protocol in NI. Nightly distances travelled by 38 individuals were determined using Global Positioning System (GPS) measurements of animal tracks and GPS-enhanced dead-reckoned tracks. The latter was calculated using GPS, tri-axial accelerometer and tri-axial magnetometer data loggers attached to animals. Home range and core home range size were measured using 95% and 50% autocorrelated kernel density estimates, respectively, based on location fixes. TVR was not associated with measured increases in either distances travelled per night (mean = 3.31 ± 2.64 km) or home range size (95% mean = 1.56 ± 0.62 km2, 50% mean = 0.39 ± 0.62 km2) over the four years of study. However, following trapping, mean distances travelled per night increased by up to 44% eight days post capture. Findings differ from those observed in higher density badger populations in England, in which badger ranging increased following culling. Whilst we did not assess behaviours of individual badgers, possible reasons why no differences in home range size were observed include higher inherent 'social fluidity' in Irish populations whereby movements are less restricted by habitat saturation and/or that the numbers removed did not reach a threshold that might induce increases in ranging behaviour. Nevertheless, short-term behavioural disruption from trapping was observed, which led to significant increases in the movements of individual animals within their home range. Whether or not TVR may alter badger behaviours remains to be seen, but it would be better to utilise solutions such as oral vaccination of badgers and/or cattle as well as increased biosecurity to limit bTB transmission, which may be less likely to cause interference and thereby reduce the likelihood of bTB transmission.
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Affiliation(s)
- Sophie H A Redpath
- School of Biological Sciences, Queens' University Belfast, 19 Chlorine Gardens, Belfast, BT9 5DL, Northern Ireland
- Veterinary Sciences Division, Agri-Food and Biosciences Institute, Belfast, BT4 3SD, Northern Ireland
| | - Nikki J Marks
- School of Biological Sciences, Queens' University Belfast, 19 Chlorine Gardens, Belfast, BT9 5DL, Northern Ireland
| | - Fraser D Menzies
- Department of Agriculture, Environment and Rural Affairs, Veterinary Epidemiology Unit, Belfast, BT4 3SB, Northern Ireland
| | - Maria J H O'Hagan
- Department of Agriculture, Environment and Rural Affairs, Veterinary Epidemiology Unit, Belfast, BT4 3SB, Northern Ireland
| | - Rory P Wilson
- Department of Biological Sciences, Swansea University, Singleton Park, Swansea, SA2 8PP, Wales
| | - Sinéad Smith
- School of Biological Sciences, Queens' University Belfast, 19 Chlorine Gardens, Belfast, BT9 5DL, Northern Ireland
| | - Elizabeth A Magowan
- School of Biological Sciences, Queens' University Belfast, 19 Chlorine Gardens, Belfast, BT9 5DL, Northern Ireland
| | - David W McClune
- School of Biological Sciences, Queens' University Belfast, 19 Chlorine Gardens, Belfast, BT9 5DL, Northern Ireland
| | - Shane F Collins
- Department of Agriculture, Environment and Rural Affairs, Veterinary Epidemiology Unit, Belfast, BT4 3SB, Northern Ireland
| | - Carl M McCormick
- Veterinary Sciences Division, Agri-Food and Biosciences Institute, Belfast, BT4 3SD, Northern Ireland
| | - D Michael Scantlebury
- School of Biological Sciences, Queens' University Belfast, 19 Chlorine Gardens, Belfast, BT9 5DL, Northern Ireland.
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3
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He P, Klarevas‐Irby JA, Papageorgiou D, Christensen C, Strauss ED, Farine DR. A guide to sampling design for
GPS
‐based studies of animal societies. Methods Ecol Evol 2022. [DOI: 10.1111/2041-210x.13999] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Peng He
- Department of Collective Behaviour Max Planck Institute of Animal Behavior Constance Germany
- Centre for the Advanced Study of Collective Behaviour University of Konstanz Constance Germany
- Department of Biology University of Konstanz Constance Germany
- Department of Evolutionary Biology and Environmental Science University of Zurich Zurich Switzerland
| | - James A. Klarevas‐Irby
- Centre for the Advanced Study of Collective Behaviour University of Konstanz Constance Germany
- Department of Biology University of Konstanz Constance Germany
- Department of Evolutionary Biology and Environmental Science University of Zurich Zurich Switzerland
- Department of Migration Max Planck Institute of Animal Behavior Radolfzell Germany
- Mpala Research Centre Nanyuki Kenya
| | - Danai Papageorgiou
- Department of Collective Behaviour Max Planck Institute of Animal Behavior Constance Germany
- Department of Evolutionary Biology and Environmental Science University of Zurich Zurich Switzerland
| | - Charlotte Christensen
- Department of Collective Behaviour Max Planck Institute of Animal Behavior Constance Germany
- Department of Evolutionary Biology and Environmental Science University of Zurich Zurich Switzerland
- Mpala Research Centre Nanyuki Kenya
| | - Eli D. Strauss
- Department of Collective Behaviour Max Planck Institute of Animal Behavior Constance Germany
- Centre for the Advanced Study of Collective Behaviour University of Konstanz Constance Germany
- Department of Evolutionary Biology and Environmental Science University of Zurich Zurich Switzerland
| | - Damien R. Farine
- Department of Collective Behaviour Max Planck Institute of Animal Behavior Constance Germany
- Department of Evolutionary Biology and Environmental Science University of Zurich Zurich Switzerland
- Division of Ecology and Evolution, Research School of Biology Australian National University Canberra Australia
- Department of Ornithology National Museums of Kenya Nairobi Kenya
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4
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Acácio M, Atkinson PW, Silva JP, Franco AMA. Performance of GPS/GPRS tracking devices improves with increased fix interval and is not affected by animal deployment. PLoS One 2022; 17:e0265541. [PMID: 35353826 PMCID: PMC8966994 DOI: 10.1371/journal.pone.0265541] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2021] [Accepted: 03/03/2022] [Indexed: 11/18/2022] Open
Abstract
The use of GPS tracking technologies has revolutionized the study of animal movement providing unprecedentedly detailed information. The characterization of GPS accuracy and precision under different conditions is essential to correctly identify the spatial and temporal resolution at which studies can be conducted. Here, we examined the influence of fix acquisition interval and device deployment on the performance of a new GPS/GSM solar powered device. Horizontal and vertical accuracy and precision of locations were obtained under different GPS fix acquisition intervals (1min, 20 min and 60 min) in a stationary test. The test devices were deployed on pre-fledgling white storks (Ciconia ciconia) and we quantified accuracy and precision after deployment while controlling for bias caused by variation in habitat, topography, and animal movement. We also assessed the performance of GPS-Error, a metric provided by the device, at identifying inaccurate locations (> 10 m). Average horizontal accuracy varied between 3.4 to 6.5 m, and vertical accuracy varied between 4.9 to 9.7 m, in high (1 min) and low frequency (60 min) GPS fix intervals. These values were similar after the deployment on white storks. Over 84% of GPS horizontal positions and 71% of vertical positions had less than 10m error in accuracy. Removing 3% of data with highest GPS-Error eliminated over 99% of inaccurate positions in high GPS frequency intervals, but this metric was not effective in the low frequency intervals. We confirmed the suitability of these devices for studies requiring horizontal and vertical accuracies of 5-10m. For higher accuracy data, intensive GPS fix intervals should be used, but this requires more sophisticated battery management, or larger batteries and devices.
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Affiliation(s)
- Marta Acácio
- School of Environmental Sciences, University of East Anglia, Norwich, United Kingdom
- * E-mail:
| | | | - João Paulo Silva
- CIBIO/InBio, Centro de Investigação em Biodiversidade e Recursos Genéticos, Laboratório Associado, Universidade do Porto, Vairão, Portugal
- CIBIO/InBio, Centro de Investigação em Biodiversidade e Recursos Genéticos, Laboratório Associado, Instituto Superior de Agronomia, Universidade de Lisboa, Lisboa, Portugal
- BIOPOLIS Program in Genomics, Biodiversity and Land Planning, Universidade do Porto, Vairão, Portugal
| | - Aldina M. A. Franco
- School of Environmental Sciences, University of East Anglia, Norwich, United Kingdom
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5
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Magowan EA, Maguire IE, Smith S, Redpath S, Marks NJ, Wilson RP, Menzies F, O’Hagan M, Scantlebury DM. Dead-reckoning elucidates fine-scale habitat use by European badgers Meles meles. ANIMAL BIOTELEMETRY 2022; 10:10. [PMID: 37521810 PMCID: PMC8908954 DOI: 10.1186/s40317-022-00282-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Accepted: 02/23/2022] [Indexed: 05/03/2023]
Abstract
Background Recent developments in both hardware and software of animal-borne data loggers now enable large amounts of data to be collected on both animal movement and behaviour. In particular, the combined use of tri-axial accelerometers, tri-axial magnetometers and GPS loggers enables animal tracks to be elucidated using a procedure of 'dead-reckoning'. Although this approach was first suggested 30 years ago by Wilson et al. (1991), surprisingly few measurements have been made in free-ranging terrestrial animals. The current study examines movements, interactions with habitat features, and home-ranges calculated from just GPS data and also from dead-reckoned data in a model terrestrial mammal, the European badger (Meles meles). Methods Research was undertaken in farmland in Northern Ireland. Two badgers (one male, one female) were live-trapped and fitted with a GPS logger, a tri-axial accelerometer, and a tri-axial magnetometer. Thereafter, the badgers' movement paths over 2 weeks were elucidated using just GPS data and GPS-enabled dead-reckoned data, respectively. Results Badgers travelled further using data from dead-reckoned calculations than using the data from only GPS data. Whilst once-hourly GPS data could only be represented by straight-line movements between sequential points, the sub-second resolution dead-reckoned tracks were more tortuous. Although there were no differences in Minimum Convex Polygon determinations between GPS- and dead-reckoned data, Kernel Utilisation Distribution determinations of home-range size were larger using the former method. This was because dead-reckoned data more accurately described the particular parts of landscape constituting most-visited core areas, effectively narrowing the calculation of habitat use. Finally, the dead-reckoned data showed badgers spent more time near to field margins and hedges than simple GPS data would suggest. Conclusion Significant differences emerge when analyses of habitat use and movements are compared between calculations made using just GPS data or GPS-enabled dead-reckoned data. In particular, use of dead-reckoned data showed that animals moved 2.2 times farther, had better-defined use of the habitat (revealing clear core areas), and made more use of certain habitats (field margins, hedges). Use of dead-reckoning to provide detailed accounts of animal movement and highlight the minutiae of interactions with the environment should be considered an important technique in the ecologist's toolkit.
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Affiliation(s)
- E. A. Magowan
- School of Biological Sciences, Queen’s University Belfast, 19 Chlorine Gardens, Belfast, BT9 5DL Northern Ireland UK
- Randox Laboratories Ltd. Crumlin, Antrim, Northern Ireland UK
| | - I. E. Maguire
- School of Biological Sciences, Queen’s University Belfast, 19 Chlorine Gardens, Belfast, BT9 5DL Northern Ireland UK
- Randox Laboratories Ltd. Crumlin, Antrim, Northern Ireland UK
| | - S. Smith
- School of Biological Sciences, Queen’s University Belfast, 19 Chlorine Gardens, Belfast, BT9 5DL Northern Ireland UK
| | - S. Redpath
- School of Biological Sciences, Queen’s University Belfast, 19 Chlorine Gardens, Belfast, BT9 5DL Northern Ireland UK
| | - N. J. Marks
- School of Biological Sciences, Queen’s University Belfast, 19 Chlorine Gardens, Belfast, BT9 5DL Northern Ireland UK
| | - R. P. Wilson
- Department of Biological Sciences, Institute of Environmental Sustainability, Swansea University, Swansea, UK
| | - F. Menzies
- Department of Agriculture, Environment and Rural Affairs, Veterinary Epidemiology Unit, Belfast, UK
| | - M. O’Hagan
- Department of Agriculture, Environment and Rural Affairs, Veterinary Epidemiology Unit, Belfast, UK
| | - D. M. Scantlebury
- School of Biological Sciences, Queen’s University Belfast, 19 Chlorine Gardens, Belfast, BT9 5DL Northern Ireland UK
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6
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Improving the Accuracy of Estimates of Indoor Distance Moved Using Deep Learning-Based Movement Status Recognition. SENSORS 2022; 22:s22010346. [PMID: 35009888 PMCID: PMC8749573 DOI: 10.3390/s22010346] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/27/2021] [Revised: 12/24/2021] [Accepted: 12/28/2021] [Indexed: 12/04/2022]
Abstract
As a result of the development of wireless indoor positioning techniques such as WiFi, Bluetooth, and Ultra-wideband (UWB), the positioning traces of moving people or objects in indoor environments can be tracked and recorded, and the distances moved can be estimated from these data traces. These estimates are very useful in many applications such as workload statistics and optimized job allocation in the field of logistics. However, due to the uncertainties of the wireless signal and corresponding positioning errors, accurately estimating movement distance still faces challenges. To address this issue, this paper proposes a movement status recognition-based distance estimating method to improve the accuracy. We divide the positioning traces into segments and use an encoder–decoder deep learning-based model to determine the motion status of each segment. Then, the distances of these segments are calculated by different distance estimating methods based on their movement statuses. The experiments on the real positioning traces demonstrate the proposed method can precisely identify the movement status and significantly improve the distance estimating accuracy.
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7
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Gunner RM, Wilson RP, Holton MD, Hopkins P, Bell SH, Marks NJ, Bennett NC, Ferreira S, Govender D, Viljoen P, Bruns A, van Schalkwyk OL, Bertelsen MF, Duarte CM, van Rooyen MC, Tambling CJ, Göppert A, Diesel D, Scantlebury DM. Decision rules for determining terrestrial movement and the consequences for filtering high-resolution global positioning system tracks: a case study using the African lion ( Panthera leo). J R Soc Interface 2022; 19:20210692. [PMID: 35042386 PMCID: PMC8767188 DOI: 10.1098/rsif.2021.0692] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Accepted: 12/08/2021] [Indexed: 01/18/2023] Open
Abstract
The combined use of global positioning system (GPS) technology and motion sensors within the discipline of movement ecology has increased over recent years. This is particularly the case for instrumented wildlife, with many studies now opting to record parameters at high (infra-second) sampling frequencies. However, the detail with which GPS loggers can elucidate fine-scale movement depends on the precision and accuracy of fixes, with accuracy being affected by signal reception. We hypothesized that animal behaviour was the main factor affecting fix inaccuracy, with inherent GPS positional noise (jitter) being most apparent during GPS fixes for non-moving locations, thereby producing disproportionate error during rest periods. A movement-verified filtering (MVF) protocol was constructed to compare GPS-derived speed data with dynamic body acceleration, to provide a computationally quick method for identifying genuine travelling movement. This method was tested on 11 free-ranging lions (Panthera leo) fitted with collar-mounted GPS units and tri-axial motion sensors recording at 1 and 40 Hz, respectively. The findings support the hypothesis and show that distance moved estimates were, on average, overestimated by greater than 80% prior to GPS screening. We present the conceptual and mathematical protocols for screening fix inaccuracy within high-resolution GPS datasets and demonstrate the importance that MVF has for avoiding inaccurate and biased estimates of movement.
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Affiliation(s)
- Richard M. Gunner
- Department for the Ecology of Animal Societies Radolfzell, Max Planck Institute of Animal Behavior, Baden-Württemberg, Germany
- Department for the Ecology of Animal Societies, Max Planck Institute of Animal Behavior, 78315 Radolfzell, Germany
| | - Rory P. Wilson
- Department for the Ecology of Animal Societies Radolfzell, Max Planck Institute of Animal Behavior, Baden-Württemberg, Germany
| | - Mark D. Holton
- Department for the Ecology of Animal Societies Radolfzell, Max Planck Institute of Animal Behavior, Baden-Württemberg, Germany
| | - Phil Hopkins
- Department for the Ecology of Animal Societies Radolfzell, Max Planck Institute of Animal Behavior, Baden-Württemberg, Germany
| | - Stephen H. Bell
- School of Biological Sciences, Queen's University Belfast, 19 Chlorine Gardens, Belfast BT9 5DL, UK
| | - Nikki J. Marks
- School of Biological Sciences, Queen's University Belfast, 19 Chlorine Gardens, Belfast BT9 5DL, UK
| | - Nigel C. Bennett
- Mammal Research Institute, Department of Zoology and Entomology, University of Pretoria, Pretoria 002, South Africa
| | - Sam Ferreira
- Savanna and Grassland Research Unit, South African National Parks, Scientific Services Skukuza, Kruger National Park, Skukuza 1350, South Africa
| | - Danny Govender
- Savanna and Grassland Research Unit, South African National Parks, Scientific Services Skukuza, Kruger National Park, Skukuza 1350, South Africa
| | - Pauli Viljoen
- Savanna and Grassland Research Unit, South African National Parks, Scientific Services Skukuza, Kruger National Park, Skukuza 1350, South Africa
| | - Angela Bruns
- Veterinary Wildlife Services, South African National Parks, 97 Memorial Road, Old Testing Grounds, 8301 Kimberley, South Africa
| | - O. Louis van Schalkwyk
- Department of Agriculture, Forestry and Fisheries, Government of South Africa, Skukuza, South Africa
- Department of Migration, Max Planck Institute of Animal Behavior, 78315 Radolfzell, Germany
| | - Mads F. Bertelsen
- Center for Zoo and Wild Animal Health, Copenhagen Zoo, Roskildevej 38, 2000 Frederiksberg, Denmark
| | - Carlos M. Duarte
- Red Sea Research Centre, King Abdullah University of Science and Technology, Thuwal 23955, Saudi Arabia
| | - Martin C. van Rooyen
- Mammal Research Institute, Department of Zoology and Entomology, University of Pretoria, Pretoria 002, South Africa
| | - Craig J. Tambling
- Department of Zoology and Entomology, University of Fort Hare Alice Campus, Ring Road, Alice 5700, South Africa
| | - Aoife Göppert
- School of Biological Sciences, Queen's University Belfast, 19 Chlorine Gardens, Belfast BT9 5DL, UK
| | - Delmar Diesel
- School of Biological Sciences, Queen's University Belfast, 19 Chlorine Gardens, Belfast BT9 5DL, UK
| | - D. Michael Scantlebury
- School of Biological Sciences, Queen's University Belfast, 19 Chlorine Gardens, Belfast BT9 5DL, UK
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8
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Wilson RP, Rose KA, Gunner R, Holton MD, Marks NJ, Bennett NC, Bell SH, Twining JP, Hesketh J, Duarte CM, Bezodis N, Jezek M, Painter M, Silovsky V, Crofoot MC, Harel R, Arnould JPY, Allan BM, Whisson DA, Alagaili A, Scantlebury DM. Animal lifestyle affects acceptable mass limits for attached tags. Proc Biol Sci 2021; 288:20212005. [PMID: 34702077 PMCID: PMC8548787 DOI: 10.1098/rspb.2021.2005] [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] [Indexed: 11/21/2022] Open
Abstract
Animal-attached devices have transformed our understanding of vertebrate ecology. To minimize any associated harm, researchers have long advocated that tag masses should not exceed 3% of carrier body mass. However, this ignores tag forces resulting from animal movement. Using data from collar-attached accelerometers on 10 diverse free-ranging terrestrial species from koalas to cheetahs, we detail a tag-based acceleration method to clarify acceptable tag mass limits. We quantify animal athleticism in terms of fractions of animal movement time devoted to different collar-recorded accelerations and convert those accelerations to forces (acceleration × tag mass) to allow derivation of any defined force limits for specified fractions of any animal's active time. Specifying that tags should exert forces that are less than 3% of the gravitational force exerted on the animal's body for 95% of the time led to corrected tag masses that should constitute between 1.6% and 2.98% of carrier mass, depending on athleticism. Strikingly, in four carnivore species encompassing two orders of magnitude in mass (ca 2–200 kg), forces exerted by ‘3%' tags were equivalent to 4–19% of carrier body mass during moving, with a maximum of 54% in a hunting cheetah. This fundamentally changes how acceptable tag mass limits should be determined by ethics bodies, irrespective of the force and time limits specified.
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Affiliation(s)
- Rory P Wilson
- Swansea Laboratory for Animal Movement, Biosciences, College of Science, Swansea University, Singleton Park, Swansea SA2 8PP, UK
| | - Kayleigh A Rose
- Swansea Laboratory for Animal Movement, Biosciences, College of Science, Swansea University, Singleton Park, Swansea SA2 8PP, UK
| | - Richard Gunner
- Swansea Laboratory for Animal Movement, Biosciences, College of Science, Swansea University, Singleton Park, Swansea SA2 8PP, UK
| | - Mark D Holton
- College of Science, Swansea University, Fabian Way, Swansea SA1 8EN, UK
| | - Nikki J Marks
- School of Biological Sciences, Queen's University Belfast, Belfast BT9 5DL, UK
| | - Nigel C Bennett
- Mammal Research Institute, Department of Zoology and Entomology, University of Pretoria, Pretoria 0002, South Africa
| | - Stephen H Bell
- School of Biological Sciences, Queen's University Belfast, Belfast BT9 5DL, UK
| | - Joshua P Twining
- School of Biological Sciences, Queen's University Belfast, Belfast BT9 5DL, UK
| | - Jamie Hesketh
- Swansea Laboratory for Animal Movement, Biosciences, College of Science, Swansea University, Singleton Park, Swansea SA2 8PP, UK
| | - Carlos M Duarte
- Red Sea Research Centre, King Abdullah University of Science and Technology, Thuwal 23955, Saudi Arabia
| | - Neil Bezodis
- Applied Sports, Technology, Exercise and Medicine (A-STEM) Research Centre, College of Engineering, Swansea University, Bay Campus, Swansea SA1 8EN, UK
| | - Milos Jezek
- Department of Game Management and Wildlife Biology, Faculty of Forestry and Wood Sciences, Czech University of Life Sciences, Prague 165 00, Czech Republic
| | - Michael Painter
- Department of Game Management and Wildlife Biology, Faculty of Forestry and Wood Sciences, Czech University of Life Sciences, Prague 165 00, Czech Republic
| | - Vaclav Silovsky
- Department of Game Management and Wildlife Biology, Faculty of Forestry and Wood Sciences, Czech University of Life Sciences, Prague 165 00, Czech Republic
| | - Margaret C Crofoot
- Department for the Ecology of Animal Societies, Max Planck Institute of Animal Behavior, Bücklestraβe 5, Konstanz D-78467, Germany
| | - Roi Harel
- Department for the Ecology of Animal Societies, Max Planck Institute of Animal Behavior, Bücklestraβe 5, Konstanz D-78467, Germany.,Germany and Department of Biology, University of Konstanz, Konstanz 78457, Germany
| | - John P Y Arnould
- School of Life and Environmental Sciences, Deakin University, Melbourne Burwood Campus, 221 Burwood Highway, Burwood, VC 3125, Victoria, Australia
| | - Blake M Allan
- School of Life and Environmental Sciences, Deakin University, Melbourne Burwood Campus, 221 Burwood Highway, Burwood, VC 3125, Victoria, Australia
| | - Desley A Whisson
- School of Life and Environmental Sciences, Deakin University, Melbourne Burwood Campus, 221 Burwood Highway, Burwood, VC 3125, Victoria, Australia
| | - Abdulaziz Alagaili
- KSU Mammals Research Chair, Zoology Department, King Saud University, Riyadh, Saudi Arabia
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9
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Gunner RM, Holton MD, Scantlebury DM, Hopkins P, Shepard ELC, Fell AJ, Garde B, Quintana F, Gómez-Laich A, Yoda K, Yamamoto T, English H, Ferreira S, Govender D, Viljoen P, Bruns A, van Schalkwyk OL, Cole NC, Tatayah V, Börger L, Redcliffe J, Bell SH, Marks NJ, Bennett NC, Tonini MH, Williams HJ, Duarte CM, van Rooyen MC, Bertelsen MF, Tambling CJ, Wilson RP. How often should dead-reckoned animal movement paths be corrected for drift? ANIMAL BIOTELEMETRY 2021; 9:43. [PMID: 34900262 PMCID: PMC7612089 DOI: 10.1186/s40317-021-00265-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Accepted: 09/25/2021] [Indexed: 05/19/2023]
Abstract
BACKGROUND Understanding what animals do in time and space is important for a range of ecological questions, however accurate estimates of how animals use space is challenging. Within the use of animal-attached tags, radio telemetry (including the Global Positioning System, 'GPS') is typically used to verify an animal's location periodically. Straight lines are typically drawn between these 'Verified Positions' ('VPs') so the interpolation of space-use is limited by the temporal and spatial resolution of the system's measurement. As such, parameters such as route-taken and distance travelled can be poorly represented when using VP systems alone. Dead-reckoning has been suggested as a technique to improve the accuracy and resolution of reconstructed movement paths, whilst maximising battery life of VP systems. This typically involves deriving travel vectors from motion sensor systems and periodically correcting path dimensions for drift with simultaneously deployed VP systems. How often paths should be corrected for drift, however, has remained unclear. METHODS AND RESULTS Here, we review the utility of dead-reckoning across four contrasting model species using different forms of locomotion (the African lion Panthera leo, the red-tailed tropicbird Phaethon rubricauda, the Magellanic penguin Spheniscus magellanicus, and the imperial cormorant Leucocarbo atriceps). Simulations were performed to examine the extent of dead-reckoning error, relative to VPs, as a function of Verified Position correction (VP correction) rate and the effect of this on estimates of distance moved. Dead-reckoning error was greatest for animals travelling within air and water. We demonstrate how sources of measurement error can arise within VP-corrected dead-reckoned tracks and propose advancements to this procedure to maximise dead-reckoning accuracy. CONCLUSIONS We review the utility of VP-corrected dead-reckoning according to movement type and consider a range of ecological questions that would benefit from dead-reckoning, primarily concerning animal-barrier interactions and foraging strategies.
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Affiliation(s)
- Richard M. Gunner
- Swansea Lab for Animal Movement, Department of Biosciences, Swansea University, Singleton Park, Swansea SA2 8PP, Wales, UK
| | - Mark D. Holton
- Swansea Lab for Animal Movement, Department of Biosciences, Swansea University, Singleton Park, Swansea SA2 8PP, Wales, UK
| | - David M. Scantlebury
- School of Biological Sciences, Queen’s University Belfast, Belfast, 19 Chlorine Gardens, Belfast BT9 5DL, Northern Ireland, UK
| | - Phil Hopkins
- Swansea Lab for Animal Movement, Department of Biosciences, Swansea University, Singleton Park, Swansea SA2 8PP, Wales, UK
| | - Emily L. C. Shepard
- Swansea Lab for Animal Movement, Department of Biosciences, Swansea University, Singleton Park, Swansea SA2 8PP, Wales, UK
| | - Adam J. Fell
- Biological and Environmental Sciences, University of Stirling, Stirling FK9 4LA, Scotland, UK
| | - Baptiste Garde
- Swansea Lab for Animal Movement, Department of Biosciences, Swansea University, Singleton Park, Swansea SA2 8PP, Wales, UK
| | - Flavio Quintana
- Instituto de Biología de Organismos Marinos (IBIOMAR), CONICET. Boulevard Brown, 2915, U9120ACD Puerto Madryn, Chubut, Argentina
| | - Agustina Gómez-Laich
- Departamento de Ecología, Genética y Evolución & Instituto de Ecología, Genética Y Evolución de Buenos Aires (IEGEBA), CONICET, Pabellón II Ciudad Universitaria, C1428EGA Buenos Aires, Argentina
| | - Ken Yoda
- Graduate School of Environmental Studies, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, Japan
| | - Takashi Yamamoto
- Organization for the Strategic Coordination of Research and Intellectual Properties, Meiji University, Nakano, Tokyo, Japan
| | - Holly English
- School of Biology and Environmental Science, University College Dublin, Belfield, Dublin, Ireland
| | - Sam Ferreira
- Savanna and Grassland Research Unit, Scientific Services Skukuza, South African National Parks, Kruger National Park, Skukuza 1350, South Africa
| | - Danny Govender
- Savanna and Grassland Research Unit, Scientific Services Skukuza, South African National Parks, Kruger National Park, Skukuza 1350, South Africa
| | - Pauli Viljoen
- Savanna and Grassland Research Unit, Scientific Services Skukuza, South African National Parks, Kruger National Park, Skukuza 1350, South Africa
| | - Angela Bruns
- Veterinary Wildlife Services, South African National Parks, 97 Memorial Road, Old Testing Grounds, Kimberley 8301, South Africa
| | - O. Louis van Schalkwyk
- Department of Agriculture, Government of South Africa, Land Reform and Rural Development, Pretoria 001, South Africa
- Department of Migration, Max Planck Institute of Animal Behavior, 78315 Radolfzell, Germany
- Department of Veterinary Tropical Diseases, Faculty of Veterinary Science, University of Pretoria, Onderstepoort 0110, South Africa
| | - Nik C. Cole
- Durrell Wildlife Conservation Trust, Les Augrès Manor, Channel Islands, Trinity JE3 5BP, Jersey, UK
- Mauritian Wildlife Foundation, Grannum Road, Indian Ocean, Vacoas, Mauritius
| | - Vikash Tatayah
- Mauritian Wildlife Foundation, Grannum Road, Indian Ocean, Vacoas, Mauritius
| | - Luca Börger
- Swansea Lab for Animal Movement, Department of Biosciences, Swansea University, Singleton Park, Swansea SA2 8PP, Wales, UK
- Centre for Biomathematics, Swansea University, Swansea SA2 8PP, UK
| | - James Redcliffe
- Swansea Lab for Animal Movement, Department of Biosciences, Swansea University, Singleton Park, Swansea SA2 8PP, Wales, UK
| | - Stephen H. Bell
- School of Biological Sciences, Queen’s University Belfast, Belfast, 19 Chlorine Gardens, Belfast BT9 5DL, Northern Ireland, UK
| | - Nikki J. Marks
- School of Biological Sciences, Queen’s University Belfast, Belfast, 19 Chlorine Gardens, Belfast BT9 5DL, Northern Ireland, UK
| | - Nigel C. Bennett
- Mammal Research Institute. Department of Zoology and Entomology, University of Pretoria, Pretoria 002., South Africa
| | - Mariano H. Tonini
- Instituto Andino Patagónico de Tecnologías Biológicas y Geoambientales, Grupo GEA, IPATEC-UNCO-CONICET, San Carlos de Bariloche, Río Negro, Argentina
| | - Hannah J. Williams
- Department of Migration, Max Planck Institute of Animal Behavior, 78315 Radolfzell, Germany
| | - Carlos M. Duarte
- Red Sea Research Centre, King Abdullah University of Science and Technology, Thuwal 23955, Saudi Arabia
| | - Martin C. van Rooyen
- Mammal Research Institute. Department of Zoology and Entomology, University of Pretoria, Pretoria 002., South Africa
| | - Mads F. Bertelsen
- Center for Zoo and Wild Animal Health, Copenhagen Zoo, Roskildevej 38, DK-2000 Frederiksberg, Denmark
| | - Craig J. Tambling
- Department of Zoology and Entomology, University of Fort Hare, Alice Campus, Ring Road, Alice 5700, South Africa
| | - Rory P. Wilson
- Swansea Lab for Animal Movement, Department of Biosciences, Swansea University, Singleton Park, Swansea SA2 8PP, Wales, UK
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10
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Carnahan AM, van Manen FT, Haroldson MA, Stenhouse GB, Robbins CT. Quantifying energetic costs and defining energy landscapes experienced by grizzly bears. J Exp Biol 2021; 224:224/6/jeb241083. [DOI: 10.1242/jeb.241083] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2020] [Accepted: 02/17/2021] [Indexed: 11/20/2022]
Abstract
ABSTRACT
Animal movements are major determinants of energy expenditure and ultimately the cost–benefit of landscape use. Thus, we sought to understand those costs and how grizzly bears (Ursus arctos) move in mountainous landscapes. We trained captive grizzly bears to walk on a horizontal treadmill and up and down 10% and 20% slopes. The cost of moving upslope increased linearly with speed and slope angle, and this was more costly than moving horizontally. The cost of downslope travel at slower speeds was greater than the cost of traveling horizontally but appeared to decrease at higher speeds. The most efficient walking speed that minimized cost per unit distance was 1.19±0.11 m s−1. However, grizzly bears fitted with GPS collars in the Greater Yellowstone Ecosystem moved at an average velocity of 0.61±0.28 m s−1 and preferred to travel on near-horizontal slopes at twice their occurrence. When traveling uphill or downhill, grizzly bears chose paths across all slopes that were ∼54% less steep and costly than the maximum available slope. The net costs (J kg−1 m−1) of moving horizontally and uphill were the same for grizzly bears, humans and digitigrade carnivores, but those costs were 46% higher than movement costs for ungulates. These movement costs and characteristics of landscape use determined using captive and wild grizzly bears were used to understand the strategies that grizzly bears use for preying on large ungulates and the similarities in travel between people and grizzly bears that might affect the risk of encountering each other on shared landscapes.
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Affiliation(s)
- Anthony M. Carnahan
- School of Biological Sciences, Washington State University, Pullman, WA 99164-4236, USA
| | - Frank T. van Manen
- US Geological Survey, Northern Rocky Mountain Science Center, Interagency Grizzly Bear Study Team, Bozeman, MT 59715, USA
| | - Mark A. Haroldson
- US Geological Survey, Northern Rocky Mountain Science Center, Interagency Grizzly Bear Study Team, Bozeman, MT 59715, USA
| | | | - Charles T. Robbins
- School of the Environment and School of Biological Sciences, Washington State University, Pullman, WA 99164-4236, USA
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11
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Developing a Simulated Online Model That Integrates GNSS, Accelerometer and Weather Data to Detect Parturition Events in Grazing Sheep: A Machine Learning Approach. Animals (Basel) 2021; 11:ani11020303. [PMID: 33503953 PMCID: PMC7911250 DOI: 10.3390/ani11020303] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Revised: 01/11/2021] [Accepted: 01/13/2021] [Indexed: 12/26/2022] Open
Abstract
Simple Summary Near-real-time monitoring of livestock using on-animal sensor technology has the potential to improve animal welfare and productivity through increased surveillance and improved decision-making capabilities. One potentially valuable application is for monitoring of lambing events in sheep. This research reports on the development of a machine learning classification algorithm for autonomous detection of lambing events. The algorithm uses data from Global Navigation Satellite System (GNSS) tracking collars, accelerometer ear tags and local weather data. Overall, four features of sheep behaviour were identified as having the greatest importance for lambing detection, including various measures of social distancing and frequency of posture change. Using these four features, the final algorithm was able to detect up to 91% of lambing events. This knowledge is intended to contribute to the development of commercially feasible lambing detection systems for improved surveillance of animals, ultimately improving methods of monitoring during critical welfare periods. Abstract In the current study, a simulated online parturition detection model is developed and reported. Using a machine learning (ML)-based approach, the model incorporates data from Global Navigation Satellite System (GNSS) tracking collars, accelerometer ear tags and local weather data, with the aim of detecting parturition events in pasture-based sheep. The specific objectives were two-fold: (i) determine which sensor systems and features provide the most useful information for lambing detection; (ii) evaluate how these data might be integrated using ML classification to alert to a parturition event as it occurs. Two independent field trials were conducted during the 2017 and 2018 lambing seasons in New Zealand, with the data from each used for ML training and independent validation, respectively. Based on objective (i), four features were identified as exerting the greatest importance for lambing detection: mean distance to peers (MDP), MDP compared to the flock mean (MDP.Mean), closest peer (CP) and posture change (PC). Using these four features, the final ML was able to detect 27% and 55% of lambing events within ±3 h of birth with no prior false positives. If the model sensitivity was manipulated such that earlier false positives were permissible, this detection increased to 91% and 82% depending on the requirement for a single alert, or two consecutive alerts occurring. To identify the potential causes of model failure, the data of three animals were investigated further. Lambing detection appeared to rely on increased social isolation behaviour in addition to increased PC behaviour. The results of the study support the use of integrated sensor data for ML-based detection of parturition events in grazing sheep. This is the first known application of ML classification for the detection of lambing in pasture-based sheep. Application of this knowledge could have significant impacts on the ability to remotely monitor animals in commercial situations, with a logical extension of the information for remote monitoring of animal welfare.
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12
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Palencia P, Vicente J, Barroso P, Barasona J, Soriguer RC, Acevedo P. Estimating day range from camera‐trap data: the animals’ behaviour as a key parameter. J Zool (1987) 2019. [DOI: 10.1111/jzo.12710] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Affiliation(s)
- P. Palencia
- Instituto de Investigación en Recursos Cinegéticos IREC (UCLM‐CSIC‐JCCM) Ciudad Real Spain
| | - J. Vicente
- Instituto de Investigación en Recursos Cinegéticos IREC (UCLM‐CSIC‐JCCM) Ciudad Real Spain
| | - P. Barroso
- Instituto de Investigación en Recursos Cinegéticos IREC (UCLM‐CSIC‐JCCM) Ciudad Real Spain
| | - J.Á. Barasona
- Animal Health Department VISAVET Centre Facultad de Veterinaria Universidad Complutense de Madrid Madrid Spain
| | | | - P. Acevedo
- Instituto de Investigación en Recursos Cinegéticos IREC (UCLM‐CSIC‐JCCM) Ciudad Real Spain
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13
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Curtin NA, Bartlam-Brooks HLA, Hubel TY, Lowe JC, Gardner-Medwin AR, Bennitt E, Amos SJ, Lorenc M, West TG, Wilson AM. Remarkable muscles, remarkable locomotion in desert-dwelling wildebeest. Nature 2018; 563:393-396. [PMID: 30356212 DOI: 10.1038/s41586-018-0602-4] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2018] [Accepted: 08/24/2018] [Indexed: 11/09/2022]
Abstract
Large mammals that live in arid and/or desert environments can cope with seasonal and local variations in rainfall, food and climate1 by moving long distances, often without reliable water or food en route. The capacity of an animal for this long-distance travel is substantially dependent on the rate of energy utilization and thus heat production during locomotion-the cost of transport2-4. The terrestrial cost of transport is much higher than for flying (7.5 times) and swimming (20 times)4. Terrestrial migrants are usually large1-3 with anatomical specializations for economical locomotion5-9, because the cost of transport reduces with increasing size and limb length5-7. Here we used GPS-tracking collars10 with movement and environmental sensors to show that blue wildebeest (Connochaetes taurinus, 220 kg) that live in a hot arid environment in Northern Botswana walked up to 80 km over five days without drinking. They predominantly travelled during the day and locomotion appeared to be unaffected by temperature and humidity, although some behavioural thermoregulation was apparent. We measured power and efficiency of work production (mechanical work and heat production) during cyclic contractions of intact muscle biopsies from the forelimb flexor carpi ulnaris of wildebeest and domestic cows (Bos taurus, 760 kg), a comparable but relatively sedentary ruminant. The energetic costs of isometric contraction (activation and force generation) in wildebeest and cows were similar to published values for smaller mammals. Wildebeest muscle was substantially more efficient (62.6%) than the same muscle from much larger cows (41.8%) and comparable measurements that were obtained from smaller mammals (mouse (34%)11 and rabbit (27%)). We used the direct energetic measurements on intact muscle fibres to model the contribution of high working efficiency of wildebeest muscle to minimizing thermoregulatory challenges during their long migrations under hot arid conditions.
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Affiliation(s)
- Nancy A Curtin
- Structure & Motion Laboratory, Royal Veterinary College, University of London, Hatfield, UK.
| | | | - Tatjana Y Hubel
- Structure & Motion Laboratory, Royal Veterinary College, University of London, Hatfield, UK
| | - John C Lowe
- Structure & Motion Laboratory, Royal Veterinary College, University of London, Hatfield, UK
| | | | - Emily Bennitt
- Okavango Research Institute, University of Botswana, Maun, Botswana
| | - Stephen J Amos
- Structure & Motion Laboratory, Royal Veterinary College, University of London, Hatfield, UK
| | - Maja Lorenc
- Structure & Motion Laboratory, Royal Veterinary College, University of London, Hatfield, UK
| | - Timothy G West
- Structure & Motion Laboratory, Royal Veterinary College, University of London, Hatfield, UK
| | - Alan M Wilson
- Structure & Motion Laboratory, Royal Veterinary College, University of London, Hatfield, UK.
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14
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Hirakawa T, Yamashita T, Tamaki T, Fujiyoshi H, Umezu Y, Takeuchi I, Matsumoto S, Yoda K. Can AI predict animal movements? Filling gaps in animal trajectories using inverse reinforcement learning. Ecosphere 2018. [DOI: 10.1002/ecs2.2447] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Affiliation(s)
- Tsubasa Hirakawa
- Department of Computer Science; Chubu University; 1200 Matsumoto Kasugai Aichi 487-0027 Japan
| | - Takayoshi Yamashita
- Department of Computer Science; Chubu University; 1200 Matsumoto Kasugai Aichi 487-0027 Japan
| | - Toru Tamaki
- Graduate School of Engineering; Hiroshima University; 1-4-1 Kagamiyama Higashi Hiroshima Hiroshima 739-8527 Japan
| | - Hironobu Fujiyoshi
- Department of Computer Science; Chubu University; 1200 Matsumoto Kasugai Aichi 487-0027 Japan
| | - Yuta Umezu
- Department of Computer Science; Nagoya Institute of Technology; Gokiso-cho Showa-ku Nagoya 466-8555 Japan
| | - Ichiro Takeuchi
- Department of Computer Science; Nagoya Institute of Technology; Gokiso-cho Showa-ku Nagoya 466-8555 Japan
- RIKEN Center for Advanced Intelligence Project; 1-4-1 Nihonbashi Chuo-ku Tokyo 103-0027 Japan
- Center for Materials Research by Information Integration; National Institute for Materials Science; 1-2-1 Sengen Tsukuba 305-0047 Japan
| | - Sakiko Matsumoto
- Graduate School of Environmental Studies; Nagoya University; Furo Chikusa Nagoya 464-8601 Japan
| | - Ken Yoda
- Graduate School of Environmental Studies; Nagoya University; Furo Chikusa Nagoya 464-8601 Japan
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15
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Schlaich AE, Bouten W, Bretagnolle V, Heldbjerg H, Klaassen RHG, Sørensen IH, Villers A, Both C. A circannual perspective on daily and total flight distances in a long-distance migratory raptor, the Montagu's harrier, Circus pygargus. Biol Lett 2017; 13:rsbl.2017.0073. [PMID: 28615350 DOI: 10.1098/rsbl.2017.0073] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2017] [Accepted: 05/23/2017] [Indexed: 11/12/2022] Open
Abstract
Long-distance migrants are particularly recognized for the distances covered on migration, yet little is known about the distances they cover during the rest of the year. GPS-tracks of 29 Montagu's harriers from breeding areas in France, The Netherlands and Denmark showed that harriers fly between 35 653 and 88 049 km yr-1, of which on average only 28.5% is on migration. Mean daily distances during migration were 296 km d-1 in autumn and 252 km d-1 in spring. Surprisingly, males' daily distances during breeding (217 km d-1) were close to those during migration, whereas breeding females moved significantly less (101 km d-1) than males. In terms of flight distance, the breeding season seemed nearly as demanding as migration periods for males. During the six winter months, both sexes moved less (114 and 128 km d-1 for females and males, respectively) than during migration. Harriers therefore covered shorter daily distances during winter which might allow birds to compensate for the more demanding phases of migration and breeding.
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Affiliation(s)
- Almut E Schlaich
- Dutch Montagu's Harrier Foundation, PO Box 46, 9679ZG Scheemda, The Netherlands .,Conservation Ecology Group, GELIFES, University of Groningen, PO Box 11103, 9700CC Groningen, The Netherlands.,Centre d'Etudes Biologiques de Chizé, UMR 7372, CNRS & Université de la Rochelle, 79360 Villiers-en-Bois, France
| | - Willem Bouten
- Computational Geo-Ecology, IBED, University of Amsterdam, PO Box 94248, 1090GE Amsterdam, The Netherlands
| | - Vincent Bretagnolle
- Centre d'Etudes Biologiques de Chizé, UMR 7372, CNRS & Université de la Rochelle, 79360 Villiers-en-Bois, France.,LTER 'Zone Atelier Plaine & Val de Sèvre', Centre d'Etudes Biologiques de Chizé, CNRS, 79360 Villiers-en-Bois, France
| | - Henning Heldbjerg
- DOF-BirdLife Denmark, Vesterbrogade 140, 1620 Copenhagen V, Denmark.,Department of Bioscience-Wildlife Ecology, Aarhus University, Grenåvej 14, 8410 Rønde, Denmark
| | - Raymond H G Klaassen
- Dutch Montagu's Harrier Foundation, PO Box 46, 9679ZG Scheemda, The Netherlands.,Conservation Ecology Group, GELIFES, University of Groningen, PO Box 11103, 9700CC Groningen, The Netherlands
| | - Iben H Sørensen
- DOF-BirdLife Denmark, Vesterbrogade 140, 1620 Copenhagen V, Denmark.,Danish Hunters' Association, Molsvej 34, 8410 Rønde, Denmark
| | - Alexandre Villers
- Centre d'Etudes Biologiques de Chizé, UMR 7372, CNRS & Université de la Rochelle, 79360 Villiers-en-Bois, France.,Unité Biostatistiques et Processus Spatiaux, INRA, Domaine Saint-Paul, Site Agroparc, 84914 Avignon Cedex 9, France
| | - Christiaan Both
- Conservation Ecology Group, GELIFES, University of Groningen, PO Box 11103, 9700CC Groningen, The Netherlands
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16
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SMART collars help track and conserve wildlife. Proc Natl Acad Sci U S A 2017; 114:3266-3268. [DOI: 10.1073/pnas.1701956114] [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] Open
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