Mammals show faster recovery from capture and tagging in human-disturbed landscapes
Jazyk angličtina Země Anglie, Velká Británie Médium electronic
Typ dokumentu časopisecké články
Grantová podpora
R01 GM083863
NIGMS NIH HHS - United States
PubMed
39278967
PubMed Central
PMC11402999
DOI
10.1038/s41467-024-52381-8
PII: 10.1038/s41467-024-52381-8
Knihovny.cz E-zdroje
- MeSH
- býložravci fyziologie MeSH
- chování zvířat fyziologie MeSH
- divoká zvířata fyziologie MeSH
- druhová specificita MeSH
- ekosystém * MeSH
- lidé MeSH
- lokomoce fyziologie MeSH
- savci * fyziologie MeSH
- zvířata MeSH
- Check Tag
- lidé MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
Wildlife tagging provides critical insights into animal movement ecology, physiology, and behavior amid global ecosystem changes. However, the stress induced by capture, handling, and tagging can impact post-release locomotion and activity and, consequently, the interpretation of study results. Here, we analyze post-tagging effects on 1585 individuals of 42 terrestrial mammal species using collar-collected GPS and accelerometer data. Species-specific displacements and overall dynamic body acceleration, as a proxy for activity, were assessed over 20 days post-release to quantify disturbance intensity, recovery duration, and speed. Differences were evaluated, considering species-specific traits and the human footprint of the study region. Over 70% of the analyzed species exhibited significant behavioral changes following collaring events. Herbivores traveled farther with variable activity reactions, while omnivores and carnivores were initially less active and mobile. Recovery duration proved brief, with alterations diminishing within 4-7 tracking days for most species. Herbivores, particularly males, showed quicker displacement recovery (4 days) but slower activity recovery (7 days). Individuals in high human footprint areas displayed faster recovery, indicating adaptation to human disturbance. Our findings emphasize the necessity of extending tracking periods beyond 1 week and particular caution in remote study areas or herbivore-focused research, specifically in smaller mammals.
Alaska Department of Fish and Game Wildlife Division 11255 W 8th Street AK USA
Animal Behavior Graduate Group University of California Davis CA 95616 USA
Animal Ecology Institute of Biochemistry and Biology University of Potsdam 14469 Potsdam Germany
Arctic Research Centre Aarhus University Aarhus Denmark
Bionet Natuuronderzoek Stein Netherlands
Büro Renala Gülper Hauptstr 4 14715 Havelaue Germany
Center for Ecological Sciences Indian Institute of Science Bengaluru 560012 India
Copenhagen Zoo Frederiksberg Denmark
Danau Girang Field Centre Sabah Wildlife Department 88100 Kota Kinabalu Sabah Malaysia
Department of Anthropology University of California Davis CA 95616 USA
Department of Behavioural Ecology Bielefeld University Bielefeld Germany
Department of Biological Sciences Chicago State University 9501 S King Drive Chicago IL 60628 USA
Department of Biological Sciences Goethe University 60438 Frankfurt Germany
Department of Biology St Louis University St Louis MO USA
Department of Ecoscience Aarhus University Roskilde Denmark
Department of Fisheries and Wildlife Michigan State University East Lansing MI USA
Department of Genetics Evolution and Environment University College London WC1E 6BT UK
Department of Sociobiology Anthropology University of Göttingen 37077 Göttingen Germany
Department of Veterinary Medicine University of Sassari Via Vienna 2 07100 Sassari Italy
Department of Zoology and Physiology University of Wyoming Laramie WY 82071 USA
Estación Biológica de Doñana Consejo Superior de Investigaciones Científicas Sevilla Spain
German Primate Center Behavioral Ecology and Sociobiology Unit 37077 Göttingen Germany
Gran Paradiso National Park Turin Italy
Hunting Association of Lower Austria Wickenburggasse 3 1080 Vienna Austria
Institute of Nature Conservation Polish Academy of Sciences 31 120 Kraków Poland
Leibniz Institute for Zoo and Wildlife Research Berlin Germany
Mammal Research Institute Polish Academy of Sciences Stoczek 1 17 230 Białowieża Poland
Mpala Research Centre 555 10400 Nanyuki Kenya
NBFC National Biodiversity Future Centre Palermo 90133 Italy
Norwegian Institute for Nature Research P O Box 5685 Torgarden NO 7485 Trondheim Norway
Office Français de la Biodiversité Montfort 01330 Birieux France
Organisms and Environment Division School of Biosciences Cardiff University Cardiff CF10 3AX UK
Panthera 8 W 40th St 18th Floor New York NY 10018 USA
School of Business Innovation and Sustainability Halmstad University Halmstad Sweden
School of Life Sciences University of KwaZulu Natal Durban South Africa
Smithsonian Conservation Biology Institute National Zoological Park Front Royal VA USA
Tatra National Park Zakopane Poland
Technische Universität München Arcisstraße 21 80333 München Germany
Tragsatec C de Julián Camarillo 6B San Blas Canillejas 28037 Madrid Spain
Université de Toulouse INRAE CEFS Castanet Tolosan France
Wellcome Trust DBT India Alliance Clinical and Public Health Program Bengaluru India
WildCare Institute Saint Louis Zoo 1 Government Drive Saint Louis MO 63110 USA
Wildlife Conservation Society Mongolia Program Ulaanbaatar Mongolia
Wildlife Research Unit Agricultural Centre Baden Wuerttemberg 88326 Aulendorf Germany
Zobrazit více v PubMed
Hebblewhite, M. & Haydon, D. T. Distinguishing technology from biology: a critical review of the use of GPS telemetry data in ecology. Philos. Trans. R. Soc. B Biol. Sci.365, 2303–2312 (2010).10.1098/rstb.2010.0087 PubMed DOI PMC
Nathan, R. et al. A movement ecology paradigm for unifying organismal movement research. Proc. Natl Acad. Sci. USA105, 19052–19059 (2008). 10.1073/pnas.0800375105 PubMed DOI PMC
Jeltsch, F. et al. Integrating movement ecology with biodiversity research—exploring new avenues to address spatiotemporal biodiversity dynamics. Mov. Ecol.1, 6 (2013). 10.1186/2051-3933-1-6 PubMed DOI PMC
Schlägel, U. E. et al. Movement-mediated community assembly and coexistence. Biol. Rev.95, 1073–1096 (2020). 10.1111/brv.12600 PubMed DOI
Allen, A. M. & Singh, N. J. Linking movement ecology with wildlife management and conservation. Front. Ecol. Evol.3, 155 (2016).
Handcock, R. et al. Monitoring animal behaviour and environmental interactions using wireless sensor networks, GPS collars and satellite remote sensing. Sensors9, 3586–3603 (2009). 10.3390/s90503586 PubMed DOI PMC
Kays, R., Crofoot, M. C., Jetz, W. & Wikelski, M. Terrestrial animal tracking as an eye on life and planet. Science348, 6340 (2015). PubMed
Jetz, W., Tertitski, G., Kays, R., Mueller, U. & Wikelski, M. Biological earth observation with animal sensors. Trend. Ecol. Evol.37, 719–724 (2022).10.1016/j.tree.2022.04.012 PubMed DOI
Nathan, R. et al. Big-data approaches lead to an increased understanding of the ecology of animal movement. Science375, eabg1780 (2022). PubMed
Wilmers, C. C. et al. The golden age of bio-logging: how animal-borne sensors are advancing the frontiers of ecology. Ecology96, 1741–1753 (2015). 10.1890/14-1401.1 PubMed DOI
Hughey, L. F., Hein, A. M., Strandburg-Peshkin, A. & Jensen, F. H. Challenges and solutions for studying collective animal behaviour in the wild. Philos.Trans. R Soc. B Biol. Sci.373, 20170005 (2018).10.1098/rstb.2017.0005 PubMed DOI PMC
Wilson, R. P. et al. Estimates for energy expenditure in free-living animals using acceleration proxies: a reappraisal. J. Animal Ecol.89, 161–172 (2020).10.1111/1365-2656.13040 PubMed DOI PMC
Qasem, L. et al. Tri-axial dynamic acceleration as a proxy for animal energy expenditure; should we be summing values or calculating the vector? PLoS ONE7, e31187 (2012). 10.1371/journal.pone.0031187 PubMed DOI PMC
Martín López, L. M., Miller, P. J. O., Aguilar de Soto, N. & Johnson, M. Gait switches in deep-diving beaked whales: biomechanical strategies for long-duration dives. J. Exp. Biol.218, 1325–1338 (2015). 10.1242/jeb.106013 PubMed DOI
Gunner, R. M. et al. A new direction for differentiating animal activity based on measuring angular velocity about the yaw axis. Ecol. Evol.10, 7872–7886 (2020). 10.1002/ece3.6515 PubMed DOI PMC
Wilson, R. P. et al. Moving towards acceleration for estimates of activity-specific metabolic rate in free-living animals: the case of the cormorant. J. Animal Ecol.75, 1081–1090 (2006).10.1111/j.1365-2656.2006.01127.x PubMed DOI
Gleiss, A. C., Wilson, R. P. & Shepard, E. L. C. Making overall dynamic body acceleration work: on the theory of acceleration as a proxy for energy expenditure. Methods Ecol. Evol.2, 23–33 (2011).10.1111/j.2041-210X.2010.00057.x DOI
Cooke, S. J. et al. Biotelemetry: a mechanistic approach to ecology. Trend Ecol. Evol.19, 334–343 (2004).10.1016/j.tree.2004.04.003 PubMed DOI
McGowan, J. et al. Integrating research using animal-borne telemetry with the needs of conservation management. J. Appl. Ecol.54, 423–429 (2017).10.1111/1365-2664.12755 DOI
Godfrey, J. & Bryant, D. Effects of radio transmitters: review of recent radio-tracking studies. In Conservation Applications of Mmeasuring Energy Expenditure of New Zealand Birds: Assessing Habitat Quality and Costs of Carrying Radio Transmitters. (ed. Williams, M.) 83–95 (Department of Conservation, 2003).
Mech, D. L. & Barber, S. M. A Critique of Wildlife Radio-Tracking and Its Use in National Parks: a Report to the National Park Service, US Geological Survey.https://pubs.usgs.gov/publication/93895 (2002).
Ropert-Coudert, Y. & Wilson, R. Subjectivity in bio-logging science: do logged data mislead? Mem. Nat. Inst. Polar Res.58, 23–33 (2004).
Healy, M., Chiaradia, A., Kirkwood, R. & Dann, P. Balance: a neglected factor when attaching external devices to penguins. Memoirs Nat. Inst. Polar Res.Special Issue, 179–182 (2004).
Powell, R. A. & Proulx, G. Trapping and marking terrestrial mammals for research: integrating ethics, performance criteria, techniques, and common sense. ILAR J.44, 259–276 (2003). 10.1093/ilar.44.4.259 PubMed DOI
Iossa, G., Soulsbury, C. & Harris, S. Mammal trapping: a review of animal welfare standards of killing and restraining traps. Animal Welfare16, 335–352 (2007).10.1017/S0962728600027159 DOI
Morellet, N. et al. The effect of capture on ranging behaviour and activity of the European Roe deer (Capreolus capreolus). Wildlife Biol.15, 278–287 (2009).10.2981/08-084 DOI
Northrup, J. M., Anderson, C. R. & Wittemyer, G. Effects of helicopter capture and handling on movement behavior of mule deer. J. Wildlife Manag.78, 731–738 (2014).10.1002/jwmg.705 DOI
Brogi, R. et al. Capture effects in wild boar: a multifaceted behavioural investigation. Wildlife Biol.2019, 1–10 (2019).
Theil, P. K., Coutant, A. E. & Olesen, C. R. Seasonal changes and activity-dependent variation in heart rate of Roe deer. J. Mammal.85, 245–253 (2004).10.1644/1545-1542(2004)085<0245:SCAAVI>2.0.CO;2 DOI
Grandin, T. & Shivley, C. How farm animals react and perceive stressful situations such as handling, restraint, and transport. Animals5, 1233–1251 (2015). 10.3390/ani5040409 PubMed DOI PMC
Bergvall, U. A. et al. Settle down! ranging behaviour responses of Roe deer to different capture and release methods. Animals11, 3299 (2021). 10.3390/ani11113299 PubMed DOI PMC
Cattet, M., Boulanger, J., Stenhouse, G., Powell, R. A. & Reynolds-Hogland, M. J. An evaluation of long-term capture effects in ursids: implications for wildlife welfare and research. J. Mammal.89, 973–990 (2008).10.1644/08-MAMM-A-095.1 DOI
Alibhai, S. K., Jewell, Z. C. & Towindo, S. S. Effects of immobilization on fertility in female black rhino (Diceros bicornis). J. Zool.253, 333–345 (2001).10.1017/S0952836901000309 DOI
Harcourt, R. G., Turner, E., Hall, A., Waas, J. R. & Hindell, M. Effects of capture stress on free-ranging, reproductively active male Weddell seals. J. Comp. Physiol. A196, 147–154 (2010).10.1007/s00359-009-0501-0 PubMed DOI
Salvo, A. D. Chemical and physical restraint of African wild animals. J. Wildlife Dis.58, 951–953 (2022).
Pelletier, F., Hogg, J. T. & Festa-Bianchet, M. Effect of chemical immobilization on social status of bighorn rams. Animal Behav.67, 1163–1165 (2004).10.1016/j.anbehav.2003.07.009 DOI
Brivio, F., Grignolio, S., Sica, N., Cerise, S. & Bassano, B. Assessing the impact of capture on wild animals: the case study of chemical immobilisation on Alpine ibex. PLoS ONE10, e0130957 (2015). 10.1371/journal.pone.0130957 PubMed DOI PMC
Arnemo, J. M. et al. Risk of capture-related mortality in large free-ranging mammals: experiences from Scandinavia. Wildlife Biol.12, 109–113 (2006).10.2981/0909-6396(2006)12[109:ROCMIL]2.0.CO;2 DOI
Jacques, C. N. et al. Evaluating ungulate mortality associated with helicopter net-gun captures in the Northern great plains. J. Wildlife Manag.73, 1282–1291 (2009).10.2193/2009-039 DOI
Wilson, R. P. et al. Animal lifestyle affects acceptable mass limits for attached tags. Proc. R. Soc. B Biol. Sci.288, 20212005 (2021). PubMed PMC
McIntyre, T. Animal telemetry: tagging effects. Science349, 596–597 (2015). 10.1126/science.349.6248.596-b PubMed DOI
Brooks, C., Bonyongo, C. & Harris, S. Effects of global positioning system collar weight on zebra behavior and location error. J. Wildlife Manag.72, 527–534 (2008).10.2193/2007-061 DOI
Stabach, J. A. et al. Short-term effects of GPS collars on the activity, behavior, and adrenal response of scimitar-horned oryx (Oryx dammah). PLoS ONE15, e0221843 (2020). 10.1371/journal.pone.0221843 PubMed DOI PMC
Wilson, R. P. & McMahon, C. R. Measuring devices on wild animals: what constitutes acceptable practice? Front. Ecol. Environ.4, 147–154 (2006).10.1890/1540-9295(2006)004[0147:MDOWAW]2.0.CO;2 DOI
van de Bunte, W., Weerman, J. & Hof, A. R. Potential effects of GPS collars on the behaviour of two red pandas (Ailurus fulgens) in Rotterdam Zoo. PLoS ONE16, e0252456 (2021). 10.1371/journal.pone.0252456 PubMed DOI PMC
Becciolini, V., Lanini, F. & Ponzetta, M. P. Impact of capture and chemical immobilization on the spatial behaviour of red deer Cervus elaphus hinds. Wildlife Biol.2019, wlb.00499 (2019).
Mortensen, R. M. & Rosell, F. Long-term capture and handling effects on body condition, reproduction and survival in a semi-aquatic mammal. Sci. Rep.10, 17886 (2020). 10.1038/s41598-020-74933-w PubMed DOI PMC
Chi, D., Chester, D., Ranger, W. & Gilbert, B. Effects of capture procedures on black bear activity at an Alaskan Salmon stream. Ursus10, 563–569 (1998).
Hawkins, P. Bio-logging and animal welfare: practical refinements. Mem. Natl Inst. Polar Res. Spec. Issue58, 58–68 (2004).
Gehrt, S. D., Anchor, C. & White, L. A. Home range and landscape use of coyotes in a metropolitan landscape: conflict or coexistence? J. Mammal.90, 1045–1057 (2009).10.1644/08-MAMM-A-277.1 DOI
Prange, S., Gehrt, S. D. & Wiggers, E. P. Influences of anthropogenic resources on Raccoon (Procyon lotor) movements and spatial distribution. J. Mammal.85, 483–490 (2004).10.1644/BOS-121 DOI
Samia, D. S. M., Nakagawa, S., Nomura, F., Rangel, T. F. & Blumstein, D. T. Increased tolerance to humans among disturbed wildlife. Nat. Commun.6, 8877 (2015). 10.1038/ncomms9877 PubMed DOI PMC
Tucker, M. A. et al. Moving in the anthropocene: global reductions in terrestrial mammalian movements. Science359, 466–469 (2018). 10.1126/science.aam9712 PubMed DOI
Ciuti, S. et al. Effects of humans on behaviour of wildlife exceed those of natural predators in a landscape of fear. PLoS ONE7, e50611 (2012). 10.1371/journal.pone.0050611 PubMed DOI PMC
Gaynor, K. M., Hojnowski, C. E., Carter, N. H. & Brashares, J. S. The influence of human disturbance on wildlife nocturnality. Science360, 1232–1235 (2018). 10.1126/science.aar7121 PubMed DOI
Chinnadurai, S. K., Strahl-Heldreth, D., Fiorello, C. V. & Harms, C. A. Best-practice guidelines for field-based surgery and anesthesia of free-ranging wildlife. I. Anesthesia and analgesia. J. Wildlife Dis.52, S14–S27 (2016).10.7589/52.2S.S14 PubMed DOI
Neumann, W., Ericsson, G., Dettki, H. & Arnemo, J. M. Effect of immobilizations on the activity and space use of female moose (Alces alces). Can. J. Zool.89, 1013–1018 (2011).10.1139/z11-076 DOI
Woodroffe, R. & Vincent, A. Mother’s little helpers: patterns of male care in mammals. Trend. Ecol. Evol.9, 294–297 (1994).10.1016/0169-5347(94)90033-7 PubMed DOI
Roche, D. G., Careau, V. & Binning, S. A. Demystifying animal ‘personality’ (or not): why individual variation matters to experimental biologists. J. Exp. Biol.219, 3832–3843 (2016). PubMed
Sloan Wilson, D., Clark, A. B., Coleman, K. & Dearstyne, T. Shyness and boldness in humans and other animals. Trend. Ecol. Evol.9, 442–446 (1994).10.1016/0169-5347(94)90134-1 PubMed DOI
Schirmer, A., Herde, A., Eccard, J. A. & Dammhahn, M. Individuals in space: personality-dependent space use, movement and microhabitat use facilitate individual spatial niche specialization. Oecologia189, 647–660 (2019). 10.1007/s00442-019-04365-5 PubMed DOI PMC
Lingle, S. & Pellis, S. Fight or flight? antipredator behavior and the escalation of coyote encounters with deer. Oecologia131, 154–164 (2002). 10.1007/s00442-001-0858-4 PubMed DOI
Quick, J. C. & Spielberger, C. D. Walter Bradford Cannon: pioneer of stress research. Int. J. Stress Manag.1, 141–143 (1994).10.1007/BF01857607 DOI
Bracha, S. H. Freeze, flight, fight, fright, faint: adaptationist perspectives on the acute stress response spectrum. CNS Spectr.9, 679–685 (2004). 10.1017/S1092852900001954 PubMed DOI
Tablado, Z. & Jenni, L. Determinants of uncertainty in wildlife responses to human disturbance. Biol. Rev.92, 216–233 (2017). 10.1111/brv.12224 PubMed DOI
Santini, L. et al. One strategy does not fit all: determinants of urban adaptation in mammals. Ecol. Lett.22, 365–376 (2019). 10.1111/ele.13199 PubMed DOI PMC
Milner, J. M., Van Beest, F. M., Schmidt, K. T., Brook, R. K. & Storaas, T. To feed or not to feed? evidence of the intended and unintended effects of feeding wild ungulates. J. Wildlife Manag.78, 1322–1334 (2014).10.1002/jwmg.798 DOI
Alberti, M. et al. Global urban signatures of phenotypic change in animal and plant populations. Proc. Natl Acad. Sci.114, 8951–8956 (2017). 10.1073/pnas.1606034114 PubMed DOI PMC
Tucker, M. A. et al. Behavioral responses of terrestrial mammals to COVID-19 lockdowns. Science380, 1059–1064 (2023). 10.1126/science.abo6499 PubMed DOI
Erb, P. L., McShea, W. J. & Guralnick, R. P. Anthropogenic influences on macro-level mammal occupancy in the Appalachian trail corridor. PLoS ONE7, e42574 (2012). 10.1371/journal.pone.0042574 PubMed DOI PMC
Tuomainen, U. & Candolin, U. Behavioural responses to human-induced environmental change. Biol. Rev.86, 640–657 (2011). 10.1111/j.1469-185X.2010.00164.x PubMed DOI
Gaynor, K. M. et al. An applied ecology of fear framework: linking theory to conservation practice. Animal Conserv.24, 308–321 (2021).10.1111/acv.12629 DOI
Martínez-Abraín, A., Quevedo, M. & Serrano, D. Translocation in relict shy-selected animal populations: program success versus prevention of wildlife-human conflict. Biol. Conserv.268, 109519 (2022).10.1016/j.biocon.2022.109519 DOI
Gallagher, C. A., Grimm, V., Kyhn, L. A., Kinze, C. C. & Nabe-Nielsen, J. Movement and seasonal energetics mediate vulnerability to disturbance in marine mammal populations. Am. Nat.197, 296–311 (2021). 10.1086/712798 PubMed DOI
Nabe-Nielsen, J. et al. Predicting the impacts of anthropogenic disturbances on marine populations. Conserv. Lett.11, e12563 (2018).
Pirotta, E. et al. Understanding the population consequences of disturbance. Ecol. Evol.8, 9934–9946 (2018). PubMed PMC
Wikelski, M., Davidson, S. C. & Kays, R. The Movebank Data Repository.www.movebank.org (2020).
Kranstauber, B., Smolla, M. & Scharf, A. Move: Visualizing and Analyzing Animal Track Data. https://cran.r-project.org/package=move (2020).
Scharf, A. moveACC: Visualitation and Analysis of Acceleration Data (Mainly for eObs Tags).https://gitlab.com/anneks/moveACC/ (2018).
Calenge, C. The package “adehabitat” for the R software: A tool for the analysis of space and habitat use by animals. Ecol. Model.197, 516–519 (2006).10.1016/j.ecolmodel.2006.03.017 DOI
McGowan, P. J. K. Mapping the terrestrial human footprint. Nature537, 172–173 (2016). 10.1038/537172a PubMed DOI
Venter, O. et al. Sixteen years of change in the global terrestrial human footprint and implications for biodiversity conservation. Nat. Commun.7, 12558 (2016). 10.1038/ncomms12558 PubMed DOI PMC
Wood, S. N. Generalized Additive Models 2nd edn, Vol. 496 (Chapman and Hall/CRC, 2017).
Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw.67, 1–48 (2015).
Faurby, S. et al. PHYLACINE 1.2: the phylogenetic Atlas of mammal macroecology. Ecology99, 2626–2626 (2018). 10.1002/ecy.2443 PubMed DOI
Barton, K. MuMIn: Multi-Model Inference. R Package Version 1.15.6.https://cran.r-project.org/web/packages/MuMIn/MuMIn.pdf (2016).
Urbano, F. & Cagnacci, F. Data management and sharing for collaborative science: lessons learnt from the euromammals iInitiative. Front. Ecol. Evol.9, 727023 (2021).
Gorelick, N. et al. Google earth engine: planetary-scale geospatial analysis for everyone. Remote Sens. Environ. 202, 18–27 (2017).