Modeling activity patterns of wildlife using time-series analysis

Abstract

The study of wildlife activity patterns is an effective approach to understanding fundamental ecological and evolutionary processes. However, traditional statistical approaches used to conduct quantitative analysis have thus far had limited success in revealing underlying mechanisms driving activity patterns. Here, we combine wavelet analysis, a type of frequency-based time-series analysis, with high-resolution activity data from accelerometers embedded in GPS collars to explore the effects of internal states (e.g., pregnancy) and external factors (e.g., seasonal dynamics of resources and weather) on activity patterns of the endangered giant panda (Ailuropoda melanoleuca). Giant pandas exhibited higher frequency cycles during the winter when resources (e.g., water and forage) were relatively poor, as well as during spring, which includes the giant panda's mating season. During the summer and autumn when resources were abundant, pandas exhibited a regular activity pattern with activity peaks every 24 hr. A pregnant individual showed distinct differences in her activity pattern from other giant pandas for several months following parturition. These results indicate that animals adjust activity cycles to adapt to seasonal variation of the resources and unique physiological periods. Wavelet coherency analysis also verified the synchronization of giant panda activity level with air temperature and solar radiation at the 24-hr band. Our study also shows that wavelet analysis is an effective tool for analyzing high-resolution activity pattern data and its relationship to internal and external states, an approach that has the potential to inform wildlife conservation and management across species.

References Alados, C. L., Escos, J. M., & Emlen, J. (1996). Fractal structure of sequential behaviour patterns: An indicator of stress. Animal Behaviour, 51, 437–443. Alados, C. L., & Weber, D. N. (1999). Lead effects on the predictability of reproductive behavior in fathead minnows (Pimephales promelas): A mathematical model. Environmental Toxicology and Chemistry, 18, 2392–2399. Aschoff, J. (1966). Circadian activity pattern with two peaks. Ecology, 657–662. Bjørnstad, O. N., & Grenfell, B. T. (2001). Noisy clockwork: Time series analysis of population fluctuations in animals. Science, 293, 638–643. Broell, F., Taylor, A. D., Litvak, M. K., Bezanson, A., & Taggart, C. T. (2016). Post-tagging behaviour and habitat use in shortnose sturgeon measured with high-frequency accelerometer and PSATs. Animal Biotelemetry, 4, 1. Carter, N. H., Shrestha, B. K., Karki, J. B., Pradhan, N. M. B., & Liu, J. (2012). Coexistence between wildlife and humans at fine spatial scales. Proceedings of the National Academy of Sciences, 109, 15360–15365. Cazelles, B., Chavez, M., Berteaux, D., Ménard, F., Vik, J. O., Jenouvrier, S., & Stenseth, N. C. (2008). Wavelet analysis of ecological time series. Oecologia, 156, 287–304. Coulombe, M.-L., Massé, A., & Côté, S. D. (2006). Quantification and accuracy of activity data measured with VHF and GPS telemetry. Wildlife Society Bulletin, 34, 81–92. Escos, J., Alados, C. L., & Emlen, J. (1995). Fractal structures and fractal functions as disease indicators. Oikos, 310–314. Getz, W. M., & Saltz, D. (2008). A framework for generating and analyzing movement paths on ecological landscapes. Proceedings of the National Academy of Sciences, 105, 19066–19071. Grinsted, A., Moore, J. C., & Jevrejeva, S. (2004). Application of the cross wavelet transform and wavelet coherence to geophysical time series. Nonlinear Processes in Geophysics, 11, 561–566. Huang, J., Li, Y.-Z., Du, L.-M., Yang, B., Shen, F.-J., Zhang, H.-M., … Yue, B.-S. (2015). Genome-wide survey and analysis of microsatellites in giant panda (Ailuropoda melanoleuca), with a focus on the applications of a novel microsatellite marker system. BMC Genomics, 16, 61. Hull, V., Zhang, J., Zhou, S., Huang, J., Li, R., Liu, D., … Zhang, H. (2015). Space use by endangered giant pandas. Journal of Mammalogy, 96, 230–236. Kembro, J., Perillo, M., Pury, P., Satterlee, D., & Marin, R. (2009). Fractal analysis of the ambulation pattern of Japanese quail. British Poultry Science, 50, 161–170. Lau, K., & Weng, H. (1995). Climate signal detection using wavelet transform: How to make a time series sing. Bulletin of the American Meteorological Society, 76, 2391–2402. Lee, J. E., Larsen, R. T., Flinders, J. T., & Eggett, D. L. (2010). Daily and seasonal patterns of activity at pygmy rabbit burrows in Utah. Western North American Naturalist, 70, 189–197. Li, C., Zhou, S., Xiao, D., Chen, Z., & Tian, Z. (1992). A general description of Wolong Nature Reserve. In Wolong Nature Reserve SNC (Ed.), The animal and plant resources and protection of Wolong Nature Reserve (pp. 313–325). Chengdu: Sichuan Publishing House of Science and Technology. Loe, L. E., Bonenfant, C., Mysterud, A., Severinsen, T., Øritsland, N. A., Langvatn, R., … Stenseth, N. C. (2007). Activity pattern of arctic reindeer in a predator-free environment: No need to keep a daily rhythm. Oecologia, 152, 617–624. MacIntosh, A. J., Alados, C. L., & Huffman, M. A. (2011). Fractal analysis of behaviour in a wild primate: Behavioural complexity in health and disease. Journal of the Royal Society Interface, 8, 1497–1509. MacIntosh, A. J., Pelletier, L., Chiaradia, A., Kato, A., & Ropert-Coudert, Y. (2013). Temporal fractals in seabird foraging behaviour: Diving through the scales of time. Scientific Reports, 3, 1884. Maier, J. A. K., Maier, H. A., & White, R. G. (1996). Effects of ambient temperature on activity monitors of radiocollars. The Journal of Wildlife Management, 393–398. Mandel, J., Bildstein, K., Bohrer, G., & Winkler, D. (2008). Movement ecology of migration in turkey vultures. Proceedings of the National Academy of Sciences, 105, 19102–19107. Motohashi, Y., Miyazaki, Y., & Takano, T. (1993). Assessment of behavioral effects of tetrachloroethylene using a set of time-series analyses. Neurotoxicology and Teratology, 15, 3–10. Nakamura, I., Watanabe, Y. Y., Papastamatiou, Y. P., Sato, K., & Meyer, C. G. (2011). Yo-yo vertical movements suggest a foraging strategy for tiger sharks Galeocerdo cuvier. Marine Ecology Progress Series, 424, 237–246. Nathan, R., Getz, W. M., Revilla, E., Holyoak, M., Kadmon, R., Saltz, D., & Smouse, P. E. (2008). A movement ecology paradigm for unifying organismal movement research. Proceedings of the National Academy of Sciences, 105, 19052–19059. Nelson, R. J. (1991). Maternal diet influences reproductive development in male prairie vole offspring. Physiology & Behavior, 50, 1063–1066. Nie, Y., Speakman, J. R., Wu, Q., Zhang, C., Hu, Y., Xia, M., … Wei, W. (2015). Exceptionally low daily energy expenditure in the bamboo-eating giant panda. Science, 349, 171–174. Nie, Y., Zhang, Z., Raubenheimer, D., Elser, J. J., Wei, W., & Wei, F. (2015). Obligate herbivory in an ancestrally carnivorous lineage: The giant panda and bamboo from the perspective of nutritional geometry. Functional Ecology, 29, 26–34. Pan, W., Lu, Z., Zhu, X., Wang, D., Wang, H., Long, Y., … Zhou, X. (2014). A chance for lasting survival: Ecology and behavior of wild giant pandas. Washington, D.C.: Smithsonian Institution Scholarly Press. Pianka, E. R. (1973). The structure of lizard communities. Annual Review of Ecology and Systematics, 53–74. Polansky, L., Wittemyer, G., Cross, P. C., Tambling, C. J., & Getz, W. M. (2010). From moonlight to movement and synchronized randomness: Fourier and wavelet analyses of animal location time series data. Ecology, 91, 1506–1518. Prendergast, B. J., Nelson, R. J., & Zucker, I. (2002). Mammalian seasonal rhythms: Behavior and neuroendocrine substrates. Hormones, Brain and Behavior, 2, 93–156. Presley, S. J., Willig, M. R., Castro-Arellano, I., & Weaver, S. C. (2009). Effects of habitat conversion on temporal activity patterns of phyllostomid bats in lowland Amazonian rain forest. Journal of Mammalogy, 90, 210–221. Roll, U., Dayan, T., & Kronfeld-Schor, N. (2006). On the role of phylogeny in determining activity patterns of rodents. Evolutionary Ecology, 20, 479–490. Rosenfeld, M., & Shelby, N. (2004). Methods for augmenting immune defenses contemplating the administration of phenolic and indoleamine-like compounds for use in animals ans humans. Google Patents. Rouyer, T., Fromentin, J.-M., Ménard, F., Cazelles, B., Briand, K., Pianet, R., … Stenseth, N. C. (2008). Complex interplays among population dynamics, environmental forcing, and exploitation in fisheries. Proceedings of the National Academy of Sciences, 105, 5420–5425. Rutherford, K. M., Haskell, M. J., Glasbey, C., & Lawrence, A. B. (2006). The responses of growing pigs to a chronic-intermittent stress treatment. Physiology & Behavior, 89, 670–680. Ryan, M. A., Whisson, D. A., Holland, G. J., & Arnould, J. P. (2013). Activity patterns of free-ranging koalas (Phascolarctos cinereus) revealed by accelerometry. PLoS One, 8, e80366. Sakamoto, K. Q., Sato, K., Ishizuka, M., Watanuki, Y., Takahashi, A., Daunt, F., & Wanless, S. (2009). Can ethograms be automatically generated using body acceleration data from free-ranging birds? PLoS One, 4, e5379. Schaller, G. B., Hu, J., Pan, W., & Zhu, J. (1985). The giant pandas of Wolong. Illinois, USA: University of Chicago Press Chicago. Schwartz, C. C., Podruzny, S., Cain, S. L., & Cherry, S. (2009). Performance of spread spectrum global positioning system collars on grizzly and black bears. The Journal of Wildlife Management, 73, 1174–1183. Seuront, L., & Cribb, N. (2011). Fractal analysis reveals pernicious stress levels related to boat presence and type in the Indo-Pacific bottlenose dolphin, Tursiops aduncus. Physica A: Statistical Mechanics and its Applications, 390, 2333–2339. Shimada, I., Minesaki, Y., & Hara, H. (1995). Temporal fractal in the feeding behavior of Drosophila melanogaster. Journal of Ethology, 13, 153–158. Sichuan Provincial Forestry Department (2015). The giant panda of Sichuan—The fourth giant panda survey of Sichuan province (in Chinese). Chengdu, China: Sichuan Science & Technology Press. Swets, J. A. (1988). Measuring the accuracy of diagnostic systems. Science, 240, 1285–1293. Torrence, C., & Compo, G. P. (1998). A practical guide to wavelet analysis. Bulletin of the American Meteorological Society, 79, 61–78. Whitney, N. M., Pratt, H. L. Jr, Pratt, T. C., & Carrier, J. C. (2010). Identifying shark mating behaviour using three-dimensional acceleration loggers. Endangered Species Research, 10, 71–82. Wittemyer, G., Elsen, P., Bean, W. T., Burton, A. C. O., & Brashares, J. S. (2008). Accelerated human population growth at protected area edges. Science, 321, 123–126. Wittemyer, G., Polansky, L., Douglas-Hamilton, I., & Getz, W. M. (2008). Disentangling the effects of forage, social rank, and risk on movement autocorrelation of elephants using Fourier and wavelet analyses. Proceedings of the National Academy of Sciences, 105, 19108–19113. Woodroffe, R., Thirgood, S., & Rabinowitz, A. (2005). People and wildlife, conflict or co-existence?. Cambridge University Press. Zhang, J., Hull, V., Huang, J., Zhou, S., Xu, W., Yang, H., … Huang, Y. (2015). Activity patterns of the giant panda (Ailuropoda melanoleuca). Journal of Mammalogy, 96, 1–12. Zhang, Z., Sheppard, J. K., Swaisgood, R. R., Wang, G., Nie, Y., Wei, W., … Wei, F. (2014). Ecological scale and seasonal heterogeneity in the spatial behaviors of giant pandas. Integrative Zoology, 9, 46–60. Zollner, P. A., & Lima, S. L. (1999). Search strategies for landscape-level interpatch movements. Ecology, 80, 1019–1030.