Shepard ELC, Wilson RP, Quintana F, Laich AG, Liebsch N, Albareda DA, et al. Identification of animal movement patterns using tri-axial accelerometry. Endanger Species Res. 2008;10:47–60.
Snell-Rood EC. An overview of the evolutionary causes and consequences of behavioural plasticity. Anim Behav. 2013;85(5):1004–11.
Moiron M, Laskowski KL, Niemelä PT. Individual differences in behaviour explain variation in survival: a meta-analysis. Ecol Lett. 2020;23(2):399–408.
Sumpter DJT, Broomhead DS. Relating individual behaviour to population dynamics. Proc R Soc Lond B. 2001;268(1470):925–32.
Morales JM, Moorcroft PR, Matthiopoulos J, Frair JL, Kie JG, Powell RA, et al. Building the bridge between animal movement and population dynamics. Philos Trans R Soc B. 2010;365(1550):2289–301.
Wilson MW, Ridlon AD, Gaynor KM, Gaines SD, Stier AC, Halpern BS. Ecological impacts of human-induced animal behaviour change. Ecol Lett. 2020;23(10):1522–36.
Buchholz R. Behavioural biology: an effective and relevant conservation tool. Trends Ecol Evol. 2007;22(8):401–7.
Roever CL, Beyer HL, Chase MJ, van Aarde RJ. The pitfalls of ignoring behaviour when quantifying habitat selection. Divers Distrib. 2014;20(3):322–33.
Matthews SG, Miller AL, Clapp J, Plötz T, Kyriazakis I. Early detection of health and welfare compromises through automated detection of behavioural changes in pigs. Vet J. 2016;217:43–51.
Brown DD, Kays R, Wikelski M, Wilson R, Klimley AP. Observing the unwatchable through acceleration logging of animal behavior. Anim Biotelem. 2013;1(1):1–16.
Hughey LF, Hein AM, Strandburg-Peshkin A, Jensen FH. Challenges and solutions for studying collective animal behaviour in the wild. Philos Trans R Soc B. 2018;373(1746):20170005.
Lush L, Ellwood S, Markham A, Ward AI, Wheeler P. Use of tri-axial accelerometers to assess terrestrial mammal behaviour in the wild. J Zool. 2016;298(4):257–65.
Hays GC. New insights: animal-borne cameras and accelerometers reveal the secret lives of cryptic species. J Anim Ecol. 2015;84(3):587–9.
Desbiez ALJ, Kluyber D, Massocato GF, Attias N. Methods for the characterization of activity patterns in elusive species: the giant armadillo in the Brazilian Pantanal. J Zool. 2021;315(4):301–12.
Canine NG. Unrecognized anti-predator behaviour can bias observational data. Anim Behav. 1990;39(1):195–7.
Wade MR, Zalucki MP, Franzmann BA. Influence of observer presence on pacific damsel bug behavior: who is watching whom? J Insect Behav. 2005;18(5):651–67.
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(7):1741–53.
O’Connell AF, Nichols JD, Karanth KU. Camera traps in animal ecology: methods and analyses, vol. 271. Berlin: Springer; 2011.
Pettorelli N, Laurance WF, O’Brien TG, Wegmann M, Nagendra H, Turner W. Satellite remote sensing for applied ecologists: opportunities and challenges. J Appl Ecol. 2014;51(4):839–48.
Infantes E, Carroll D, Silva WTAF, Härkönen T, Edwards SV, Harding KC. An automated work-flow for pinniped surveys: a new tool for monitoring population dynamics. Front Ecol Evol. 2022;10:905309. https://doi.org/10.3389/fevo.2022.905309.
Carroll D, Infantes E, Pagan EV, Harding KC. Approaching a population‐level assessment of body size in pinnipeds using drones, an early warning of environmental degradation. Remote Sens Ecol Conserv. 2024.
Whitford M, Klimley AP. An overview of behavioral, physiological, and environmental sensors used in animal biotelemetry and biologging studies. Anim Biotelem. 2019;7(1):26.
Nathan R, Spiegel O, Fortmann-Roe S, Harel R, Wikelski M, Getz WM. Using tri-axial acceleration data to identify behavioral modes of free-ranging animals: general concepts and tools illustrated for griffon vultures. J Exp Biol. 2012;215(6):986–96.
Leos-Barajas V, Photopoulou T, Langrock R, Patterson TA, Watanabe YY, Murgatroyd M, et al. Analysis of animal accelerometer data using hidden Markov models. Methods Ecol Evol. 2017;8(2):161–73.
Williams HJ, Taylor LA, Benhamou S, Bijleveld AI, Clay TA, de Grissac S, et al. Optimizing the use of biologgers for movement ecology research. J Anim Ecol. 2020;89(1):186–206.
Collins PM, Green JA, Warwick-Evans V, Dodd S, Shaw PJA, Arnould JPY, et al. Interpreting behaviors from accelerometry: a method combining simplicity and objectivity. Ecol Evol. 2015;5(20):4642–54.
Soulsbury CD, Gray HE, Smith LM, Braithwaite V, Cotter SC, Elwood RW, et al. The welfare and ethics of research involving wild animals: a primer. Methods Ecol Evol. 2020;11(10):1164–81.
Hounslow JL, Brewster LR, Lear KO, Guttridge TL, Daly R, Whitney NM, et al. Assessing the effects of sampling frequency on behavioural classification of accelerometer data. J Exp Mar Biol Ecol. 2019;512:22–30.
Yan RC, Wilson RP. Subjectivity in bio-logging science: do logged data mislead? Mem Natl Inst Polar Res Spec Issue. 2004;58:23–33.
Kölzsch A, Neefjes M, Barkway J, Müskens GJDM, Van Langevelde F, De Boer WF, et al. Neckband or backpack? Differences in tag design and their effects on GPS/accelerometer tracking results in large waterbirds. Anim Biotelem. 2016;4(1):13.
Garde B, Wilson RP, Fell A, Cole N, Tatayah V, Holton MD, et al. Ecological inference using data from accelerometers needs careful protocols. Methods Ecol Evol. 2022;13(4):813–25.
IUCN. The IUCN red list of threatened species. 2023. Version 2023-1.
Heinrich S, Wittmann TA, Prowse TAA, Ross JV, Delean S, Shepherd CR, et al. Where did all the pangolins go? International CITES trade in pangolin species. Glob Ecol Conserv. 2016;8:241–53.
Ingram DJ, Coad L, Abernethy KA, Maisels F, Stokes EJ, Bobo KS, et al. Assessing Africa-Wide Pangolin exploitation by scaling local data. Conserv Lett. 2018;11(2):1–9.
Ingram DJ, Cronin DT, Challender DWS, Venditti DM, Gonder MK. Characterising trafficking and trade of pangolins in the Gulf of Guinea. Glob Ecol Conserv. 2019;17:e00576.
Wright, N., Jimerson, J. The rescue, rehabilitation and release of pangolins in Pangolins: Science, Society and Conservation. Challender, D. W. S., Nash, H. C., Waterman, C., Nyhus, P. J, editors. Academic Press; 2020. p. 495–504.
Nash H, Lee PB, Low MR. Rescue, rehabilitation and release of Sunda pangolins in Singapore. In: Global reintroduction perspectives: 2018 case studies from around the globe. Soorae, P. S, editor. IUCN/SSC Reintroduction Specialist Group, Gland, Switzerland and Environment Agency. Abu Dhabi, UAE; 2018. p. 221-225.
Carroll D, Harvey-Carroll J, Trivella CM, Connelly E. Non-fatal removal of ground pangolin (Smutsia temminckii Smuts, 1832) tracking devices by predators. Afr J Ecol. 2023;62:e13225.
Pavese S, Centeno C, Von Fersen L, Eguizábal GV, Donet L, Asencio CJ, et al. Video validation of tri-axial accelerometer for monitoring zoo-housed Tamandua tetradactyla activity patterns in response to changes in husbandry conditions. Animals. 2022;12(19):2516.
Auge AC, Blouin-Demers G, Murray DL. Developing a classification system to assign activity states to two species of freshwater turtles. PLoS ONE. 2022;17(11):e0277491.
Clark BL. Northern gannet Morus bassanus foraging ecology: a multidimensional approach. Exeter: University of Exeter; 2019.
Clark B, Irigoin-Lovera C, Gonzales-DelCarpio D, Diaz-Santibañez I, Votier S, Zavalaga C. Interactions between anchovy fisheries and Peruvian boobies revealed by bird-borne cameras and movement loggers. Mar Ecol Prog Ser. 2022;701:145–57.
Reisinger RR, Corney S, Raymond B, Lombard AT, Bester MN, Crawford RJM, et al. Habitat model forecasts suggest potential redistribution of marine predators in the southern Indian Ocean. Divers Distrib. 2022;28(1):142–59.
Reisinger RR, Raymond B, Hindell MA, Bester MN, Crawford RJM, Davies D, et al. Habitat modelling of tracking data from multiple marine predators identifies important areas in the Southern Indian Ocean. Divers Distrib. 2018;24(4):535–50.
Kuhn M. A Short Introduction to the caret package. R Found Stat Comput. 2015;1:1–10.
Wright MN, Ziegler A. ranger: a fast implementation of random forests for high dimensional data in C++ and R. J Stat Softw. 2017;77:1–17.
Friard O, Gamba M. BORIS: a free, versatile open-source event-logging software for video/audio coding and live observations. Methods Ecol Evol. 2016;7(11):1325–30.
R Core Team. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria; 2024.
Zeileis A, Grothendieck G. zoo: S3 infrastructure for regular and irregular time series. J Stat Softw. 2005;14(6):1–27.
Grolemund G, Wickham H. Dates and times made easy with lubridate. J Stat Softw. 2011;40(3):1–25.
Wickham H. ggplot2: elegant graphics for data analysis. New York: Springer; 2016.
Wickham H, Averick M, Bryan J, Chang W, McGowan LD, François R, et al. Welcome to the tidyverse. J Open Source Softw. 2019;4(43):1686.
Wickham H, François R, Henry L, Müller K, Vaughan D. dplyr: a grammar of data manipulation. R package version 1.1.4. 2023.
Barrett T, Dowle M, Srinivasan A, Gorecki J, Chirico M, Hocking T. data.table: Extension of ‘data.frame’. R package version 1.15.0. 2024.
Kuhn, M. Building Predictive Models in R Using the caret Package. Journal of Statistical Software, 2008;28(5), 1–26.
Jeantet L, Dell’Amico F, Forin-Wiart MA, Coutant M, Bonola M, Etienne D, et al. Combined use of two supervised learning algorithms to model sea turtle behaviours from tri-axial acceleration data. J Exp Biol. 2018;221(10): jeb177378.
Kirchner TM, Devineau O, Chimienti M, Thompson DP, Crouse J, Evans AL, et al. Predicting moose behaviors from tri-axial accelerometer data using a supervised classification algorithm. Anim Biotelem. 2023;11(1):32.
Tatler J, Cassey P, Prowse TAA. High accuracy at low frequency: detailed behavioural classification from accelerometer data. J Exp Biol. 2018;221 (23): jeb184085.
Price E, Langford J, Fawcett TW, Wilson AJ, Croft DP. Classifying the posture and activity of ewes and lambs using accelerometers and machine learning on a commercial flock. Appl Anim Behav Sci. 2022;251:105630.
Rautiainen H, Alam M, Blackwell PG, Skarin A. Identification of reindeer fine-scale foraging behaviour using tri-axial accelerometer data. Mov Ecol. 2022;10(1):40.
Walton E, Casey C, Mitsch J, Vázquez-Diosdado JA, Yan J, Dottorini T, et al. Evaluation of sampling frequency, window size and sensor position for classification of sheep behaviour. R Soc Open Sci. 2018;5(2):171442.
Broell F, Noda T, Wright S, Domenici P, Steffensen JF, Auclair JP, et al. Accelerometer tags: detecting and identifying activities in fish and the effect of sampling frequency. J Exp Biol. 2013;216(Pt 7):1255–64.
Yu H, Muijres FT, te Lindert JS, Hedenström A, Henningsson P. Accelerometer sampling requirements for animal behaviour classification and estimation of energy expenditure. Anim Biotelem. 2023;11(1):28.
Graf PM, Wilson RP, Qasem L, Hackländer K, Rosell F. The use of acceleration to code for animal behaviours; a case study in free-ranging Eurasian beavers castor fiber. PLoS ONE. 2015;10(8):e0136751.
Dentinger JE, Börger L, Holton MD, Jafari-Marandi R, Norman DA, Smith BK, et al. A probabilistic framework for behavioral identification from animal-borne accelerometers. Ecol Model. 2022;464:109818.
Pietersen DW, McKechnie AE, Jansen R. Home range, habitat selection and activity patterns of an arid-zone population of Temminck’s ground pangolins, Smutsia temminckii. Afr Zool. 2014;49(2):265–76.
Richer R, Coulson I, Heath M. Foraging behaviour and ecology of the Cape pangolin (Manis temminckii) in north-western Zimbabwe. Afr J Ecol. 1997;35(4):361–9.
Gaubert P, Wilson D, Mittermeier R. Family manidae. In: Handbook of the Mammals of the World, vol.2. Wilson DE, Mittermeier RA, editors. Lynx Edicions; 2011. p. 82–103.
Swart J. Smutsia temminckii Ground pangolin. In: Mammals of Africa, vol. V, carnivores, pangolins, equids, rhinoceroses. Kingdon J, Hoffmann M, editors. London: Bloomsbury Publishing; 2013. p. 400–405.
Panaino W, Parrini F, Kamerman PR, Hetem RS, Meyer LCR, Smith D, et al. Temminck’s pangolins relax the precision of body temperature regulation when resources are scarce in a semi-arid environment. Conserv Physiol. 2023;11(1):coad068.
Champagnon J, Elmberg J, Guillemain M, Gauthier-Clerc M, Lebreton JD. Conspecifics can be aliens too: a review of effects of restocking practices in vertebrates. J Nat Conserv. 2012;20(4):231–41.
Harrington LA, Moehrenschlager A, Gelling M, Atkinson RPD, Hughes J, Macdonald DW. Conflicting and complementary ethics of animal welfare considerations in reintroductions. Conserv Biol. 2013;27(3):486–500.
Molony SE, Dowding CV, Baker PJ, Cuthill IC, Harris S. The effect of translocation and temporary captivity on wildlife rehabilitation success: an experimental study using European hedgehogs (Erinaceus europaeus). Biol Conserv. 2006;130(4):530–7.
Ewen JG, Armstrong DP, Parker KA, Seddon PJ, editors. Reintroduction biology: integrating science and management. 1st ed. Hoboken: Wiley; 2012.
Mihoub J, Le Gouar P, Sarrazin F. Breeding habitat selection behaviors in heterogeneous environments: implications for modeling reintroduction. Oikos. 2009;118(5):663–74.
Scillitani L, Darmon G, Monaco A, Cocca G, Sturaro E, Rossi L, et al. Habitat selection in translocated gregarious ungulate species: an interplay between sociality and ecological requirements. J Wildl Manag. 2013;77(4):761–9.
Richardson KM, Ewen JG. Habitat selection in a reintroduced population: social effects differ between natal and post-release dispersal. Anim Conserv. 2016;19(5):413–21.
Picardi S, Coates P, Kolar J, O’Neil S, Mathews S, Dahlgren D. Behavioural state-dependent habitat selection and implications for animal translocations. J Appl Ecol. 2022;59(2):624–35.
Silva WT, Harding KC, Marques GM, Bäcklin BM, Sonne C, Dietz R, et al. Life cycle bioenergetics of the gray seal (Halichoerus grypus) in the Baltic Sea: population response to environmental stress. Environ Int. 2020;145:106145.
Heighton SP, Gaubert P. A timely systematic review on pangolin research, commercialization, and popularization to identify knowledge gaps and produce conservation guidelines. Biol Conserv. 2021;256:109042.
Zanvo S, Djagoun CAMS, Gaubert P, Azihou AF, Jézéquel C, Djossa B, et al. Modeling population extirpation rates of white-bellied and giant pangolins in Benin using validated local ecological knowledge. Conserv Sci Pract. 2023;5(8):e12986.
Carroll D, Ahola MP, Carlsson AM, Sköld M, Harding KC. 120-years of ecological monitoring data shows that the risk of overhunting is increased by environmental degradation for an isolated marine mammal population: the Baltic grey seal. J Anim Ecol. 2024;93:525–39.
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