Abstract
Methods for estimating population densities of unmarked species using camera traps are still under development. One such method is called ‘random encounter model (REM)’ and, to our knowledge, has never been used to estimate densities of mountain-dwelling ungulates. In this study, we tested the REM method to estimate the density of Balkan chamois (Rupicapra r. balcanica) in a Mediterranean habitat, Mt. Biokovo. To meet the assumptions of REM, we systematically placed 25 camera traps throughout the known range of the population (approximately 65 km2) at the intersections of 2-km grid cells. Prior to data collection, population density was estimated by visual counts on sample plots in August 2020. Cameras were operational between July 2020 and September 2020 and active throughout the 24-h period. All parameters for REM (i.e. average movement speed, angle and radius) were estimated using exclusively camera trap data. We obtained 279 independent events of chamois from 2503 camera trap days. The density estimate obtained by REM resulted to be 20.65 ± 5.27 ind. km−2, slightly higher than the reference value obtained by visual counts: 17.33 ± 0.98 ind. km−2. Other parameters required to calculate density were speed (1.62 km·day−1 ± 0.21), detection radius (5.56 m ± 0.21) and detection angle (1.16 + 0.05 radians). Therefore, REM has shown comparable results to visual counts and may have potential for estimating density of mountain ungulates, especially in rugged and inaccessible mountainous areas with low detectability where other approaches are inadequate or impossible.
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Availability of data and material
All the data supporting the results in the manuscript is still processing for additional analysis. Therefore, data are under embargo for 1 year after submission. After that period, scripts and other artefacts used to generate the analyses presented in the paper will be archived in an appropriate public repository.
References
Anonymous (2019a) Central hunting records. www.mps.hr/hr/sume/lovstvo/sredisnja–lovna–evidencija. Accessed 15 Feb 2019 (In Croatian)
Anonymous (2019b) Hunting act. Official gazette of Republic Croatia: 99/18, 32/19. (In Croatian)
Apollonio M, Scandura M, Šprem N (2014) Reintroduction as a management tool for ungulates: fifty years since the successful reintroduction of the Balkan chamois to Mt Biokovo, Croatia. In Putman R, Apollonio M (eds) Behaviour and management of European ungulates. Whittles Publishing, Scotland, UK, pp 57–58
Apps P, McNutt JW (2018) Are camera traps fit for purpose? A rigorous, reproducible and realistic test of camera trap performance. Afr J Ecol 56:710–720
Buckland ST, Anderson DR, Burnham KP, Laake JL, Borchers DL, Thomas L (2001) Introduction to distance sampling. Oxford University Press, Oxford
Corlatti L, Fattorini L, Nelli L (2015) The use of block counts, mark-resight and distance sampling to estimate population size of a mountain-dwelling ungulate. Popul Ecol 57:409–419
Corlatti L, Lorenzini R, Lovari S (2011) The conservation of the chamois Rupicapra spp. Mamm Rev 41:163–174
Cusack JJ, Swanson A, Coulson T, Packer C, Carbone C, Dickman AJ, Kosmala M, Lintott C, Rowcliffe JM (2015) Applying a random encounter model to estimate lion density from camera traps in Serengeti National Park, Tanzania. J Wildl Manag 79:1014–1021
ENETWILD consortium, Grignolio S, Apollonio M, Brivio F, Vicente J, Acevedo P, Palencia P, Petrovic K, Keuling O (2020) Guidance on estimation of abundance and density data of wild ruminant population: methods, challenges, possibilities. EFSA Support Publ 2020:EN–1876
Escos J, Alados CL (1988) Estimating mountain ungulate density in Sierras de Cazorla y Segura. Mammalia 52:425–428
Gamelon M, Filli F, Saether BE, Herfindal I (2020) Multi-event capture-recapture analysis in Alpine chamois reveals contrasting responses to interspecific competition, within and between populations. J Anim Ecol 89:2279–2289. https://doi.org/10.1111/1365-2656.13299
Gilbert NA, Clare JDJ, Stenglein JL, Zuckerberg B (2021) Abundance estimation of unmarked animals based on camera-trap data. Conserv Biol 35:88–100. https://doi.org/10.1111/cobi.13517
Gray TNE (2018) Monitoring tropical forest ungulates using camera-trap data. J Zool 305:173–179. https://doi.org/10.1111/jzo.12547
Herrero J, Serrano A, Prada C, Arberas OF (2011) Using block counts and distance sampling to estimate populations of chamois. Pirineos 166:123–133. https://doi.org/10.3989/pirineos.2011.166006
Hofmeester TR, Rowcliffe JM, Jansen PA (2017) A simple method forestimating the effective detection distance of camera traps. Remote Sens Ecol Conserv 3(2):81–89. https://doi.org/10.1002/rse2.25
Koster SH, Hart JA (1988) Methods of estimating ungulate populations in tropical forests. Afr J Ecol 26:117–126. https://doi.org/10.1111/j.1365-2028.1988.tb00962.x
Lancia RA, Nichols JD, Pollock KH (1994) Estimating the number of animals in wildlife populations. In Bookhout TA (ed) Research and management techniques for wildlife and habitats, 5th edn. The Wildlife Society, Bethesda, USA, pp 215–253
Loison A, Appolinaire J, Jullien JM, Dubray D (2006) How reliable are total counts to detect trends in population size of chamois Rupicapra rupicapra and R. pyrenaica? Wild Biol 12:77–88. https://doi.org/10.2981/0909-6396(2006)12[77:HRATCT]2.0.CO;2
López-Martín J, Xifra J, Emmanuel S (2013) Estimating the population density of Pyrenean chamois using distance sampling method. Proceeding of the II International Rupicapra Symposium. Bellver de Cerdanya, Catalonia, Spain, pp 99
Luo G, Wei W, Dai Q, Ran J (2020) Density estimation of unmarked populations using camera traps in heterogeneous space. Wildl Soc Bull 44:173–181. https://doi.org/10.1002/wsb.1060
Manzo E, Bartolommei P, Rowcliffe JM, Cozzolino R (2012) Estimation of population density of European pine marten in central Italy using camera trapping. Acta Therio 57:165–172. https://doi.org/10.1007/s13364-011-0055-8
Marcon A, Battocchio D, Apollonio M, Grignolio S (2019) Assessing precision and requirements of three methods to estimate roe deer density. PLoS One 14:e0222349. https://doi.org/10.1371/journal.pone.0222349
Marcon A, Bongi P, Battocchio D, Apollonio M (2020) REM: performance on a high-density fallow deer (Dama dama) population. Mammal Res 65:835–841. https://doi.org/10.1007/s13364-020-00522-x
Massei G, Coats J, Lambert MS, Pietravalle S, Gill R, Cowan D (2017) Camera traps and activity signs to estimate wild boar density and derive abundance indices: camera traps to estimate wild boar density. Pest Manag Sci 74:853–860. https://doi.org/10.1002/ps.4763
Mattioli L, Canu A, Passilongo D, Scandura M, Apollonio M (2018) Estimation of pack density in grey wolf (Canis lupus) by applying spatially explicit capture-recapture models to camera trap data supported by genetic monitoring. Front Zool 15:38. https://doi.org/10.1186/s12983-018-0281-x
Miller DR (2020) Distance sampling detection function and abundance estimation. http://github.com/DistanceDevelopment/Distance/. Accessed 5 Mar 2021
Moeller AK, Lukacs PM, Horne JS (2018) Three novel methods to estimate abundance of unmarked animals using remote cameras. Ecosphere 9:e02331. https://doi.org/10.1002/ecs2.2331
Morrison ML, Marcot B, Mannan W (2006) Wildlife-habitat relationships: concepts and applications. Island Press, Washington, DC
Nakashima Y, Fukasawa K, Samejima H (2018) Estimating animal density without individual recognition using information derivable exclusively from camera traps. J Appl Ecol 55:735–744. https://doi.org/10.1111/1365-2664.13059
Nesti I, Posillico M, Lovari S (2010) Ranging behaviour and habitat selection of Alpine chamois. Ethol Ecol Evol 22:215–231. https://doi.org/10.1080/03949370.2010.502316
Octenjak D, Pađen L, Šilić V, Reljić S, Vukičević TT, Kusak J (2020) Wolf diet and prey selection in Croatia. Mammal Res 65:647‒654. https://doi.org/10.1007/s13364-020-00517-8
Ozimec R (2008) Fauna Biokova. Biokovo Graphis, Zagreb, Croatia, pp 109–136 (In Croatian)
Palencia P, Fernández-López J, Vicente J, Acevedo P (2021) Innovations in movement and behavioural ecology from camera traps: day range as model parameter. Methods Ecol Evol. https://doi.org/10.1111/2041-210X.13609
Pérez JM, Sarasa M, Moço G et al (2015) The effect of data analysis strategies in density estimation of mountain ungulates using distance sampling. Ital J Zool 82:262–270. https://doi.org/10.1080/11250003.2014.974695
Pfeffer SE, Spitzer R, Allen AM et al (2018) Pictures or pellets? Comparing camera trapping and dung counts as methods for estimating population densities of ungulates. Remote Sens Ecol Conserv 4:173–183. https://doi.org/10.1002/rse2.67
Rovero F, Marshall AR (2009) Camera trapping photographic rate as an index of density in forest ungulates. J Appl Ecol 46:1011–1017. https://doi.org/10.1111/j.1365-2664.2009.01705.x
Rovero F, Zimmermann F (2016) Camera trapping for wildlife research. Pelagic Publishing Ltd, UK
Rovero F, Zimmermann F, Berzi D, Meek P (2013) “Which camera trap type and how many do I need?” A review of camera features and study designs for a range of wildlife research applications. Hystrix 24:148–156. https://doi.org/10.4404/hystrix-24.2-8789
Rowcliffe JM (2019) Activity: animal activity statistics. R package version 1.3. https://CRAN.R-project.org/package=activity. Accessed 5 Mar 2021
Rowcliffe JM, Carbone C, Jansen PA, Roland K, Kranstauber B (2011) Quantifying the sensitivity of camera traps: an adapted distance sampling approach. Methods Ecol Evol 2:464–476. https://doi.org/10.1111/j.2041-210X.2011.00094.x
Rowcliffe JM, Field J, Turvey ST, Carbone C (2008) Estimating animal density using camera traps without the need for individual recognition. J Appl Ecol 45:1228–1236. https://doi.org/10.1111/j.1365-2664.2008.01473.x
Rowcliffe JM, Jansen PA, Kays R, Kranstauber B, Carbone C (2016) Wildlife speed cameras: measuring animal travel speed and day range using camera traps. Remote Sens Ecol Conserv 2:84–94. https://doi.org/10.1002/rse2.17
Rowcliffe JM, Kays R, Carbone C, Jansen PA (2013) Clarifying assumptions behind the estimation of animal density from camera trap rates. J Wildl Manag 77:876–876. https://doi.org/10.1002/jwmg.533
Schwarz CJ, Seber GAF (1999) Estimating animal abundance: review III. Statist Sci 14:427–456. https://doi.org/10.1214/ss/1009212521
Seber GAF (1982) The estimation of animal abundance: and related parameters, 2nd edn. Macmillan Pub Co, New York
Silver S, Ostro L, Marsh L et al (2004) The use of camera traps for estimating jaguar Panthera onca abundance and density using capture/recapture analysis. Oryx 38:148–154. https://doi.org/10.1017/S0030605304000286
Singh NJ, Milner-Gulland EJ (2011) Monitoring ungulates in Central Asia: current constraints and future potential. Oryx 45:38–49. https://doi.org/10.1017/S0030605310000839
Šprem N, Zanella D, Ugarković D, Prebanić I, Gančević P, Corlatti L (2015) Unimodal activity pattern in forest-dwelling chamois: typical behaviour or interspecific avoidance? Eur J Wildl Res 61:789–794. https://doi.org/10.1007/s10344-015-0939-z
Trinajstić I (2002) Vegetation overview of Biokovo area. Ekološke monografije, Biokovo 2:13–37 (In Croatian)
Unterthiner S, Ferretti F, Rossi L, Lovari S (2012) Sexual and seasonal differences of space use in Alpine chamois. Ethol Ecol Evol 24:257–274. https://doi.org/10.1080/03949370.2012.658872
Zero VH, Sundaresan SR, O’Brien TG, Kinnaird MF (2013) Monitoring an endangered savannah ungulate, Grevy’s zebra Equus grevyi: choosing a method for estimating population densities. Oryx 47:410–419. https://doi.org/10.1017/S0030605312000324
Acknowledgements
We want to express our appreciation to the park staff members of Nature park ‘Biokovo’ and ‘Hrvatske Šume Ltd’ for support and organization of the research.
Funding
This study was supported by (i) the RESBIOS European Union’s Horizon 2020 Research and Innovation Program (No. 872146) and (ii) ENETWILD project (No. OC/EFSA/ALPHA/2016/01 – 01). PP received support from the Spanish government (MINECO-UCLM) through an FPU grant (FPU16/00039).
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KK and PP wrote all drafts of the manuscript. JV and NŠ conceptualized the framework and revised all drafts of the manuscript. PP did the statistical analyses. KK obtained and arranged raw data. NS and MA supervised all stages of this work, from data collection to data analysis, and participated in revising the manuscript. All authors have read and agreed to the published version of the manuscript.
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Kavčić, K., Palencia, P., Apollonio, M. et al. Random encounter model to estimate density of mountain-dwelling ungulate. Eur J Wildl Res 67, 87 (2021). https://doi.org/10.1007/s10344-021-01530-1
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DOI: https://doi.org/10.1007/s10344-021-01530-1