Hunting mode and habitat selection mediate the success of human hunters.

Habitat domain Human dimensions Human ecology Hunting mode Movement ecology Predator–prey interactions

Journal

Movement ecology
ISSN: 2051-3933
Titre abrégé: Mov Ecol
Pays: England
ID NLM: 101635009

Informations de publication

Date de publication:
16 Apr 2024
Historique:
received: 14 09 2023
accepted: 08 04 2024
medline: 17 4 2024
pubmed: 17 4 2024
entrez: 16 4 2024
Statut: epublish

Résumé

As a globally widespread apex predator, humans have unprecedented lethal and non-lethal effects on prey populations and ecosystems. Yet compared to non-human predators, little is known about the movement ecology of human hunters, including how hunting behavior interacts with the environment. We characterized the hunting modes, habitat selection, and harvest success of 483 rifle hunters in California using high-resolution GPS data. We used Hidden Markov Models to characterize fine-scale movement behavior, and k-means clustering to group hunters by hunting mode, on the basis of their time spent in each behavioral state. Finally, we used Resource Selection Functions to quantify patterns of habitat selection for successful and unsuccessful hunters of each hunting mode. Hunters exhibited three distinct and successful hunting modes ("coursing", "stalking", and "sit-and-wait"), with coursings as the most successful strategy. Across hunting modes, there was variation in patterns of selection for roads, topography, and habitat cover, with differences in habitat use of successful and unsuccessful hunters across modes. Our study indicates that hunters can successfully employ a diversity of harvest strategies, and that hunting success is mediated by the interacting effects of hunting mode and landscape features. Such results highlight the breadth of human hunting modes, even within a single hunting technique, and lend insight into the varied ways that humans exert predation pressure on wildlife.

Sections du résumé

BACKGROUND BACKGROUND
As a globally widespread apex predator, humans have unprecedented lethal and non-lethal effects on prey populations and ecosystems. Yet compared to non-human predators, little is known about the movement ecology of human hunters, including how hunting behavior interacts with the environment.
METHODS METHODS
We characterized the hunting modes, habitat selection, and harvest success of 483 rifle hunters in California using high-resolution GPS data. We used Hidden Markov Models to characterize fine-scale movement behavior, and k-means clustering to group hunters by hunting mode, on the basis of their time spent in each behavioral state. Finally, we used Resource Selection Functions to quantify patterns of habitat selection for successful and unsuccessful hunters of each hunting mode.
RESULTS RESULTS
Hunters exhibited three distinct and successful hunting modes ("coursing", "stalking", and "sit-and-wait"), with coursings as the most successful strategy. Across hunting modes, there was variation in patterns of selection for roads, topography, and habitat cover, with differences in habitat use of successful and unsuccessful hunters across modes.
CONCLUSIONS CONCLUSIONS
Our study indicates that hunters can successfully employ a diversity of harvest strategies, and that hunting success is mediated by the interacting effects of hunting mode and landscape features. Such results highlight the breadth of human hunting modes, even within a single hunting technique, and lend insight into the varied ways that humans exert predation pressure on wildlife.

Identifiants

pubmed: 38627867
doi: 10.1186/s40462-024-00471-z
pii: 10.1186/s40462-024-00471-z
doi:

Types de publication

Journal Article

Langues

eng

Pagination

29

Subventions

Organisme : Natural Sciences and Engineering Research Council of Canada
ID : RPGIN-2022-03096
Organisme : California Department of Fish and Wildlife
ID : P1680002

Informations de copyright

© 2024. The Author(s).

Références

Dirzo R, Young HS, Galetti M, Ceballos G, Isaac NJB, Collen B. Defaunation in the anthropocene. Science. 2014;345:401–6.
pubmed: 25061202 doi: 10.1126/science.1251817
Ripple WJ, Abernethy K, Betts MG, Chapron G, Dirzo R, Galetti M, et al. Bushmeat hunting and extinction risk to the world’s mammals. R Soc Open Sci. 2016;3:160498–516.
pubmed: 27853564 pmcid: 5098989 doi: 10.1098/rsos.160498
Darimont CT, Fox CH, Bryan HM, Reimchen TE. The unique ecology of human predators. Science. 2015;349:858–60.
pubmed: 26293961 doi: 10.1126/science.aac4249
Moll RJ, Killion AK, Hayward MW, Montgomery RA. A framework for the Eltonian niche of humans. Bioscience. 2021;71:928–41.
doi: 10.1093/biosci/biab055
Decker DJ, Stedman RC, Larson LR, Siemer WF. Hunting for wildlife management in Africa. The Wildlife Professional. 2015;26–9.
Heffelfinger JR, Geist V, Wishart W. The role of hunting in North American wildlife conservation. Int J Environ Stud. 2013;70:399–413.
doi: 10.1080/00207233.2013.800383
Eichler L, Baumeister D. Hunting for justice. Environ Soc. 2018;9:75–90.
doi: 10.3167/ares.2018.090106
Lebel F, Dussault C, Massé A, Côté SD. Influence of habitat features and hunter behavior on white-tailed deer harvest. J Wildl Manag. 2012;76:1431–40.
doi: 10.1002/jwmg.377
Plante S, Dussault C, Côté SD. Landscape attributes explain migratory caribou vulnerability to sport hunting. J Wildl Manag. 2017;81:238–47.
doi: 10.1002/jwmg.21203
Kuijper DPJ, de Kleine C, Churski M, van Hooft P, Bubnicki J, Jędrzejewska B. Landscape of fear in Europe: wolves affect spatial patterns of ungulate browsing in Białowieża Primeval Forest. Poland Ecography. 2013;36:1263–75.
doi: 10.1111/j.1600-0587.2013.00266.x
Saout SL, Padié S, Chamaillé-Jammes S, Chollet S, Côté S, Morellet N, et al. Short-term effects of hunting on naïve black-tailed deer (Odocoileus hemionus sitkensis): behavioural response and consequences on vegetation growth. Can J Zool. 2014;92:915–25.
doi: 10.1139/cjz-2014-0122
Wilson S, Davies TE, Hazarika N, Zimmermann A. Understanding spatial and temporal patterns of human–elephant conflict in Assam. India Oryx. 2013;49:140–9.
doi: 10.1017/S0030605313000513
Smith JA, Wang Y, Wilmers CC. Top carnivores increase their kill rates on prey as a response to human-induced fear. Proc R Soc B Biol Sci. 2015;282:20142711–20142711.
doi: 10.1098/rspb.2014.2711
Wilmers CC, Nickel B, Bryce CM, Smith JA, Wheat RE, Yovovich V. The golden age of bio-logging: how animal-borne sensors are advancing the frontiers of ecology. Ecology. 2015;96:1741–53.
pubmed: 26378296 doi: 10.1890/14-1401.1
Wang Y, Nickel B, Rutishauser M, Bryce CM, Williams TM, Elkaim G, et al. Movement, resting, and attack behaviors of wild pumas are revealed by tri-axial accelerometer measurements. Mov Ecol. 2015;3:2.
pubmed: 25709837 pmcid: 4337468 doi: 10.1186/s40462-015-0030-0
Preisser EL, Orrock JL, Schmitz OJ. Predator hunting mode and habitat domain alter nonconsumptive effects in predator-prey interactions. Ecology. 2007;88:2744–51.
pubmed: 18051642 doi: 10.1890/07-0260.1
Schmitz OJ. Behavior of predators and prey and links with population-level processes. Oxford: Oxford University Press; 2005.
doi: 10.1093/oso/9780195171204.003.0012
MacNulty DR, Mech LD, Smith DW. A proposed ethogram of large-carnivore predatory behavior, exemplified by the wolf. J Mammal. 2007;88:595–605.
doi: 10.1644/06-MAMM-A-119R1.1
Scharf I. The interaction between ambush predators, search patterns of herbivores, and aggregations of plants. Behav Ecol. 2021;32:1246–55.
doi: 10.1093/beheco/arab091
Smith JA, Donadio E, Bidder OR, Pauli JN, Sheriff MJ, Perrig PL, et al. Where and when to hunt? Decomposing predation success of an ambush carnivore. Ecology. 2020;e03172.
Heurich M, Zeis K, Küchenhoff H, Müller J, Belotti E, Bufka L, et al. Selective predation of a stalking predator on ungulate prey. PLoS ONE. 2016;11:e0158449.
pubmed: 27548478 pmcid: 4993363 doi: 10.1371/journal.pone.0158449
Miller JRB, Ament JM, Schmitz OJ. Fear on the move: predator hunting mode predicts variation in prey mortality and plasticity in prey spatial response. J Anim Ecol. 2013;83:214–22.
pubmed: 24028410 doi: 10.1111/1365-2656.12111
Schmitz OJ, Miller JRB, Trainor AM, Abrahms B. Toward a community ecology of landscapes: predicting multiple predator–prey interactions across geographic space. Ecology. 2017;98:2281–92.
pubmed: 28585719 doi: 10.1002/ecy.1916
Smith JA, Donadio E, Pauli JN, Sheriff MJ, Bidder OR, Middleton AD. Habitat complexity mediates the predator–prey space race. Ecology. 2019;100:599–609.
doi: 10.1002/ecy.2724
Montgomery RA, Raupp J, Miller SA, Wijers M, Lisowsky R, Comar A, et al. The hunting modes of human predation and potential nonconsumptive effects on animal populations. Biol Cons. 2022;265:109398.
doi: 10.1016/j.biocon.2021.109398
Rowland MM, Nielson RM, Wisdom MJ, Johnson BK, Findholt S, Clark D, et al. Influence of landscape characteristics on hunter space use and success. J Wildl Manag. 2021;85:1394–409.
doi: 10.1002/jwmg.22107
Brown CL, Smith JB, Wisdom MJ, Rowland MM, Spitz DB, Clark DA. Evaluating indirect effects of hunting on mule deer spatial behavior. J Wildl Manag. 2020;834:1246–55.
doi: 10.1002/jwmg.21916
Visscher DR, Macleod I, Vujnovic K, Vujnovic D, Dewitt PD. Human risk induced behavioral shifts in refuge use by elk in an agricultural matrix. Wildl Soc Bull. 2017;41:162–9.
doi: 10.1002/wsb.741
Stedman R, Diefenbach DR, Swope CB. Integrating wildlife and human-dimensions research methods to study hunters. J Wildl Manag. 2004;68:762–73.
doi: 10.2193/0022-541X(2004)068[0762:IWAHRM]2.0.CO;2
Gaynor KM, McInturff A, Brashares JS. Contrasting patterns of risk from human and non-human predators shape temporal activity of prey. J Anim Ecol. 2021;91:46–60.
pubmed: 34689337 doi: 10.1111/1365-2656.13621
Papworth SK, Bunnefeld N, Slocombe K, Milner-Gulland EJ. Movement ecology of human resource users: using net squared displacement, biased random bridges and resource utilization functions to quantify hunter and gatherer behaviour. Methods Ecol Evol. 2012;3:584–94.
doi: 10.1111/j.2041-210X.2012.00189.x
Jones MD, Berl JL, Tri AN, Edwards JW, Spiker HA. Fine-Scale movements and spatial behaviors of bear hunters: combining GPS with survey methods. Hum Dimens Wildl. 2017;22:362–73.
doi: 10.1080/10871209.2017.1324070
Brøseth H, Pedersen HChR. Hunting effort and game vulnerability studies on a small scale: a new technique combining radio-telemetry, GPS and GIS. J Appl Ecol. 2000;37:182–90.
doi: 10.1046/j.1365-2664.2000.00477.x
Brashares J, Connor T, Dorcy J, Gaynor KM, McInturff A, Bach B, et al. Hopland Columbian Black-Tailed Deer Estimation Project Final Report (CDFW contract #P1680002). Report to the California Department of Fish and Wildlife.
Thieurmel B, Elmarhraoui A. suncalc: Compute sun position, sunlight phases, moon position and lunar phase. 2022. R Package.
Michelot T, Langrock R, Patterson TA. moveHMM: an R package for the statistical modelling of animal movement data using hidden Markov models. Methods Ecol Evol. 2016;7:1308–15.
doi: 10.1111/2041-210X.12578
Scholz F, Zhu A. kSamples: K-Sample Rank Tests and their Combinations. 2019. R Package.
Manly B, McDonald LL, Thomas DL, McDonald TL, Erickson WP. Resource selection by animals: statistical design and analysis for field studies. Berlin: Springer; 2002.
Fieberg J, Signer J, Smith B, Avgar T. A ‘How to’ guide for interpreting parameters in habitat-selection analyses. J Anim Ecol. 2021;90:1027–43.
pubmed: 33583036 pmcid: 8251592 doi: 10.1111/1365-2656.13441
Norum JK, Lone K, Linnell JDC, Odden J, Loe LE, Mysterud A. Landscape of risk to roe deer imposed by lynx and different human hunting tactics. Eur J Wildl Res. 2015;61:831–40.
doi: 10.1007/s10344-015-0959-8
Gerrits AP, Wightman PH, Cantrell JR, Ruth C, Chamberlain MJ, Collier BA. Movement ecology of spring wild turkey hunters on public lands in South Carolina, USA. Wildl Soc Bull. 2020;44:260–70.
doi: 10.1002/wsb.1094
Wirsing AJ, Heithaus MR, Brown JS, Kotler BP, Schmitz OJ. The context dependence of non-consumptive predator effects. Ecol Lett. 2021;24:113–29.
pubmed: 32990363 doi: 10.1111/ele.13614
Bonnot N, Morellet N, Verheyden H, Cargnelutti B, Lourtet B, Klein F, et al. Habitat use under predation risk: hunting, roads and human dwellings influence the spatial behaviour of roe deer. Eur J Wildl Res. 2013;59:185–93.
doi: 10.1007/s10344-012-0665-8
Espinosa S, Branch LC, Cueva R. Road development and the geography of hunting by an Amazonian Indigenous group: consequences for wildlife conservation. PLoS ONE. 2014;9:e114916.
pubmed: 25489954 pmcid: 4260950 doi: 10.1371/journal.pone.0114916
Laurance WF, Croes BM, Tchignoumba L, Lahm SA, Alonso A, Lee ME, et al. Impacts of roads and hunting on Central African rainforest mammals. Conserv Biol. 2006;20:1251–61.
pubmed: 16922241 doi: 10.1111/j.1523-1739.2006.00420.x
Say-Sallaz E, Chamaillé-Jammes S, Fritz H, Valeix M. Non-consumptive effects of predation in large terrestrial mammals: Mapping our knowledge and revealing the tip of the iceberg. Biol Cons. 2019;235:36–52.
doi: 10.1016/j.biocon.2019.03.044
Handegard NO, Boswell KM, Ioannou CC, Leblanc SP, Tjøstheim DB, Couzin ID. The dynamics of coordinated group hunting and collective information transfer among schooling prey. Curr Biol. 2012;22:1213–7.
pubmed: 22683262 doi: 10.1016/j.cub.2012.04.050
Muro C, Escobedo R, Spector L, Coppinger RP. Wolf-pack (Canis lupus) hunting strategies emerge from simple rules in computational simulations. Behav Process. 2011;88:192–7.
doi: 10.1016/j.beproc.2011.09.006
Mitchell WA, Lima SL. Predator-prey shell games: large-scale movement and its implications for decision-making by prey. Oikos. 2002;99:249–59.
doi: 10.1034/j.1600-0706.2002.990205.x
Laundré JW. Behavioral response races, predator-prey shell games, ecology of fear, and patch use of pumas and their ungulate prey. Ecology. 2010;91:2995–3007.
pubmed: 21058559 doi: 10.1890/08-2345.1
Liu OR, Fisher M, Feist BE, Abrahms B, Richerson K, Samhouri JF. Mobility and flexibility enable resilience of human harvesters to environmental perturbation. Glob Environ Chang. 2023;78:102629.
doi: 10.1016/j.gloenvcha.2022.102629
O’Farrell S, Chollett I, Sanchirico JN, Perruso L. Classifying fishing behavioral diversity using high-frequency movement data. Proc Natl Acad Sci. 2019;116:16811–6.
pubmed: 31399551 pmcid: 6708367 doi: 10.1073/pnas.1906766116
Bolnick DI, Svanbäck R, Fordyce JA, Yang LH, Davis JM, Hulsey CD, et al. The Ecology of Individuals: Incidence and Implications of Individual Specialization. Am Nat. 2003;161:1–28.
pubmed: 12650459 doi: 10.1086/343878
Dall SRX, Bell AM, Bolnick DI, Ratnieks FLW. An evolutionary ecology of individual differences. Ecol Lett. 2012;15:1189–98.
pubmed: 22897772 pmcid: 3962499 doi: 10.1111/j.1461-0248.2012.01846.x

Auteurs

Kaitlyn M Gaynor (KM)

Departments of Zoology and Botany, University of British Columbia, Vancouver, BC, Canada. kaitlyn.gaynor@ubc.ca.

Alex McInturff (A)

U.S. Geological Survey Washington Cooperative Fish and Wildlife Research Unit, School of Environmental and Forest Sciences, University of Washington, Seattle, WA, USA. amcintur@uw.edu.

Briana L Abrahms (BL)

Center for Ecosystem Sentinels, Department of Biology, University of Washington, Seattle, WA, USA.

Alison M Smith (AM)

Hopland Research and Extension Center, University of California, Division of Agriculture and Natural Resources, Hopland, CA, USA.

Justin S Brashares (JS)

Department of Environmental Science, Policy, and Management, University of California - Berkeley, Berkeley, CA, USA.

Classifications MeSH