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Emergence of the wrapped Cauchy distribution in mixed directional data

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Abstract

Inferring the most appropriate distribution (or distributions) to describe observed directional data is important in many applications of circular statistics. In particular, animal movement paths are typically analysed and modelled by considering the distribution of step lengths and turning (or absolute) angles. Here we demonstrate that a single-wrapped Cauchy distribution can appear to fit directional data mixed from two different underlying wrapped normal distributions. We derive mathematical expressions to calculate the parameter space for which this occurs and illustrate the result by analysing an example data set of the movements of African bull elephants (Loxodonta Africana). We conclude that the presence of a wrapped Cauchy distribution in observed directional data can, in certain cases, be explained by data coming from two distinct underlying distributions. We discuss how this may relate to the presence of multiple movement modes within an observed path when analysing animal movement data.

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References

  • Abe, T., Ley, C.: A tractable, parsimonious and flexible model for cylindrical data, with applications. Econom. Stat. 4, 91–104 (2017)

    MathSciNet  Google Scholar 

  • Abe, T., Shimatani, I.K.: Cylindrical distributions and their applications to biological data. In: Ley, C., Verdebout, T. (eds.) Applied Directional Statistics: Modern Methods and Case Studies, p. 86. CRC Press, Boca Raton (2018)

    Google Scholar 

  • Aradottir, A.L., Robertson, A., Moore, E.: Circular statistical analysis of birch colonization and the directional growth response of birch and black cottonwood in south iceland. Agric. For. Meteorol. 84(1–2), 179–186 (1997)

    Google Scholar 

  • Bartumeus, F., Catalan, J., Viswanathan, G., Raposo, E., Da Luz, M.: The influence of turning angles on the success of non-oriented animal searches. J. Theor. Biol. 252(1), 43–55 (2008)

    MathSciNet  MATH  Google Scholar 

  • Blake, S., Yackulic, C.B., Cabrera, F., Tapia, W., Gibbs, J.P., Kümmeth, F., Wikelski, M.: Vegetation dynamics drive segregation by body size in galapagos tortoises migrating across altitudinal gradients. J. Anim. Ecol. 82(2), 310–321 (2013)

    Google Scholar 

  • Bowlby, H.D., Hanson, J.M., Hutchings, J.A.: Resident and dispersal behavior among individuals within a population of american lobster homarus americanus. Mar. Ecol. Prog. Ser. 331, 207–218 (2007)

    Google Scholar 

  • Breed, G.A., Costa, D.P., Jonsen, I.D., Robinson, P.W., Mills-Flemming, J.: State-space methods for more completely capturing behavioral dynamics from animal tracks. Ecol. Model. 235, 49–58 (2012)

    Google Scholar 

  • Brown, L.M., Crone, E.E.: Individual variation changes dispersal distance and area requirements of a checkerspot butterfly. Ecology 97(1), 106–115 (2016)

    Google Scholar 

  • Cagnacci, F., Focardi, S., Ghisla, A., Van Moorter, B., Merrill, E.H., Gurarie, E., Heurich, M., Mysterud, A., Linnell, J., Panzacchi, M., et al.: How many routes lead to migration? Comparison of methods to assess and characterize migratory movements. J. Anim. Ecol. 85(1), 54–68 (2016)

    Google Scholar 

  • Codling, E.A., Plank, M.J., Benhamou, S.: Random walk models in biology. J. R. Soc. Interface 5(25), 813–834 (2008)

    Google Scholar 

  • Codling, E.A., Bearon, R.N., Thorn, G.J.: Diffusion about the mean drift location in a biased random walk. Ecology 91(10), 3106–3113 (2010)

    Google Scholar 

  • Collett, D., Lewis, T.: Discriminating between the von mises and wrapped normal distributions. Aust. J. Stat. 23(1), 73–79 (1981)

    MATH  Google Scholar 

  • Da Silveira, N.S., Niebuhr, B.B.S., Muylaert, R.D., Ribeiro, M.C., Pizo, M.A.: Effects of land cover on the movement of frugivorous birds in a heterogeneous landscape. PloS ONE 11(6), e0156688 (2016)

    Google Scholar 

  • Dahmen, H., Wahl, V.L., Pfeffer, S.E., Mallot, H.A., Wittlinger, M.: Naturalistic path integration of cataglyphis desert ants on an air-cushioned lightweight spherical treadmill. J. Exp. Biol. 220(4), 634–644 (2017)

    Google Scholar 

  • Drost, Y., Qiu, Y., Posthuma-Doodeman, C., Van Lenteren, J.: Comparison of searching strategies of five parasitoid species of bemisia argentifolii bellows and perring (hom., aleyrodidae). J. Appl. Entomol. 124(2), 105–112 (2000)

    Google Scholar 

  • Drucker, E., Lauder, G.: Wake dynamics and fluid forces of turning maneuvers in sunfish. J. Exp. Biol. 204(3), 431–442 (2001)

    Google Scholar 

  • Fryxell, J.M., Hazell, M., Börger, L., Dalziel, B.D., Haydon, D.T., Morales, J.M., McIntosh, T., Rosatte, R.C.: Multiple movement modes by large herbivores at multiple spatiotemporal scales. Proc. Natl. Acad. Sci. 105(49), 19,114–19,119 (2008)

    Google Scholar 

  • Gibbs, A.L., Su, F.E.: On choosing and bounding probability metrics. Int. Stat. Rev. 70(3), 419–435 (2002)

    MATH  Google Scholar 

  • Gurarie, E., Bracis, C., Delgado, M., Meckley, T.D., Kojola, I., Wagner, C.M.: What is the animal doing? Tools for exploring behavioural structure in animal movements. J. Anim. Ecol. 85(1), 69–84 (2016)

    Google Scholar 

  • Hurford, A.: Gps measurement error gives rise to spurious 180 turning angles and strong directional biases in animal movement data. PLoS ONE 4(5), e5632 (2009)

    Google Scholar 

  • Imoto, T., Shimizu, K., Abe, T.: A cylindrical distribution with heavy-tailed linear part. Jpn J Stat Data Sci 2(1), 129–154 (2019)

    MathSciNet  MATH  Google Scholar 

  • Jammalamadaka, S.R., Kozubowski, T.J.: A general approach for obtaining wrapped circular distributions via mixtures. Sankhya A 79(1), 133–157 (2017)

    MathSciNet  MATH  Google Scholar 

  • Jammalamadaka, S.R., SenGupta, A.: Topics in Circular Statistics, vol. 5. World Scientific, Singapore (2001)

    Google Scholar 

  • Jerde, C.L., Visscher, D.R.: Gps measurement error influences on movement model parameterization. Ecol. Appl. 15(3), 806–810 (2005)

    Google Scholar 

  • Johnson, D.S., London, J.M., Lea, M.A., Durban, J.W.: Continuous-time correlated random walk model for animal telemetry data. Ecology 89(5), 1208–1215 (2008)

    Google Scholar 

  • Jones, M., Pewsey, A.: A family of symmetric distributions on the circle. J. Am. Stat. Assoc. 100(472), 1422–1428 (2005)

    MathSciNet  MATH  Google Scholar 

  • Jonsen, I.: Joint estimation over multiple individuals improves behavioural state inference from animal movement data. Sci. Rep. 6(20), 625 (2016)

    Google Scholar 

  • Jonsen, I., Basson, M., Bestley, S., Bravington, M., Patterson, T., Pedersen, M.W., Thomson, R., Thygesen, U.H., Wotherspoon, S.: State-space models for bio-loggers: a methodological road map. Deep Sea Res. II 88, 34–46 (2013)

    Google Scholar 

  • Kareiva, P., Shigesada, N.: Analyzing insect movement as a correlated random walk. Oecologia 56(2–3), 234–238 (1983)

    Google Scholar 

  • Kato, S., Jones, M., et al.: An extended family of circular distributions related to wrapped cauchy distributions via brownian motion. Bernoulli 19(1), 154–171 (2013)

    MathSciNet  MATH  Google Scholar 

  • Knell, A.S., Codling, E.A.: Classifying area-restricted search (ars) using a partial sum approach. Theor. Ecol. 5(3), 325–339 (2012)

    Google Scholar 

  • Landler, L., Ruxton, G.D., Malkemper, E.P.: Circular data in biology: advice for effectively implementing statistical procedures. Behav. Ecol. Sociobiol. 72(8), 128 (2018)

    Google Scholar 

  • Langrock, R., King, R., Matthiopoulos, J., Thomas, L., Fortin, D., Morales, J.M.: Flexible and practical modeling of animal telemetry data: hidden markov models and extensions. Ecology 93(11), 2336–2342 (2012)

    Google Scholar 

  • Langrock, R., Hopcraft, J.G.C., Blackwell, P.G., Goodall, V., King, R., Niu, M., Patterson, T.A., Pedersen, M.W., Skarin, A., Schick, R.S.: Modelling group dynamic animal movement. Methods Ecol. Evol. 5(2), 190–199 (2014)

    Google Scholar 

  • Li, M., Bolker, B.M.: Incorporating periodic variability in hidden markov models for animal movement. Mov. Ecol. 5(1), 1 (2017)

    Google Scholar 

  • Mardia, K., Sutton, T.: On the modes of a mixture of two von mises distributions. Biometrika 62, 699–701 (1975)

    MathSciNet  MATH  Google Scholar 

  • Mardia, K.V., Jupp, P.E.: Directional Statistics, vol. 494. Wiley, New York (2000)

    MATH  Google Scholar 

  • Masseran, N., Razali, A.M., Ibrahim, K., Latif, M.T.: Fitting a mixture of von mises distributions in order to model data on wind direction in peninsular Malaysia. Energy Convers. Manag. 72, 94–102 (2013)

    Google Scholar 

  • Mastrantonio, G., Grazian, C., Mancinelli, S., Bibbona, E., et al.: New formulation of the logistic-gaussian process to analyze trajectory tracking data. Ann. Appl. Stat. 13(4), 2483–2508 (2019)

    MathSciNet  MATH  Google Scholar 

  • McClintock, B.T., Michelot, T.: momentuhmm: R package for generalized hidden markov models of animal movement. Methods Ecol. Evol. 9(6), 1518–1530 (2018)

    Google Scholar 

  • McClintock, B.T., King, R., Thomas, L., Matthiopoulos, J., McConnell, B.J., Morales, J.M.: A general discrete-time modeling framework for animal movement using multistate random walks. Ecol. Monogr. 82(3), 335–349 (2012)

    Google Scholar 

  • McClintock, B.T., London, J.M., Cameron, M.F., Boveng, P.L.: Modelling animal movement using the argos satellite telemetry location error ellipse. Methods Ecol. Evol. 6(3), 266–277 (2015)

    Google Scholar 

  • McKellar, A.E., Langrock, R., Walters, J.R., Kesler, D.C.: Using mixed hidden markov models to examine behavioral states in a cooperatively breeding bird. Behav. Ecol. 26(1), 148–157 (2014)

    Google Scholar 

  • Michelot, T., Langrock, R., Patterson, T.A.: movehmm: an R package for the statistical modelling of animal movement data using hidden markov models. Methods Ecol. Evol. 7(11), 1308–1315 (2016)

    Google Scholar 

  • Michelot, T., Langrock, R., Bestley, S., Jonsen, I.D., Photopoulou, T., Patterson, T.A.: Estimation and simulation of foraging trips in land-based marine predators. Ecology 98(7), 1932–1944 (2017)

    Google Scholar 

  • Morales, J.M., Haydon, D.T., Frair, J., Holsinger, K.E., Fryxell, J.M.: Extracting more out of relocation data: building movement models as mixtures of random walks. Ecology 85(9), 2436–2445 (2004)

    Google Scholar 

  • Morellato, L.P.C., Alberti, L., Hudson, I.L.: Applications of Circular Statistics in Plant Phenology: A Case Studies Approach, pp. 339–359. Springer, Netherlands (2010)

    Google Scholar 

  • Nams, V.O.: Combining animal movements and behavioural data to detect behavioural states. Ecol. Lett. 17(10), 1228–1237 (2014)

    Google Scholar 

  • Nelder, J.A., Mead, R.: A simplex method for function minimization. Comput. J. 7(4), 308–313 (1965). https://doi.org/10.1093/comjnl/7.4.308

    Article  MathSciNet  MATH  Google Scholar 

  • Nicosia, A., Duchesne, T., Rivest, L.P., Fortin, D.: A general hidden state random walk model for animal movement. Comput. Stat. Data Anal. 105, 76–95 (2017)

    MathSciNet  MATH  Google Scholar 

  • Nilsen, C., Paige, J., Warner, O., Mayhew, B., Sutley, R., Lam, M., Bernoff, A.J., Topaz, C.M.: Social aggregation in pea aphids: experiment and random walk modeling. PLoS ONE 8(12), 1–11 (2013)

    Google Scholar 

  • Parton, A., Blackwell, P.G.: Bayesian inference for multistate ‘step and turn’ animal movement in continuous time. J. Agric. Biol. Environ. Stat. 22(3), 373–392 (2017)

    MathSciNet  MATH  Google Scholar 

  • Patterson, T.A., Basson, M., Bravington, M.V., Gunn, J.S.: Classifying movement behaviour in relation to environmental conditions using hidden markov models. J. Anim. Ecol. 78(6), 1113–1123 (2009)

    Google Scholar 

  • Patterson, T.A., McConnell, B.J., Fedak, M.A., Bravington, M.V., Hindell, M.A.: Using gps data to evaluate the accuracy of state-space methods for correction of argos satellite telemetry error. Ecology 91(1), 273–285 (2010)

    Google Scholar 

  • Patterson, T.A., Parton, A., Langrock, R., Blackwell, P.G., Thomas, L., King, R.: Statistical modelling of animal movement: a myopic review and a discussion of good practice. arXiv preprint arXiv:160307511 (2016)

  • Pérez-Barbería, F.J., Small, M., Hooper, R.J., Aldezabal, A., Soriguer-Escofet, R., Bakken, G.S., Gordon, I.J.: State-space modelling of the drivers of movement behaviour in sympatric species. PLoS ONE 10(11), 1–21 (2015)

    Google Scholar 

  • Pewsey, A., Lewis, T., Jones, M.C.: The wrapped t family of circular distributions. Aust. N. Z. J. Stat. 49(1), 79–91 (2007)

    MathSciNet  MATH  Google Scholar 

  • Pistorius, P., Hindell, M., Crawford, R., Makhado, A., Dyer, B., Reisinger, R.: At-sea distribution and habitat use in king penguins at sub-antarctic marion Island. Ecol. Evolut. 7(11), 3894–3903 (2017)

    Google Scholar 

  • Pohle, J., Langrock, R., van Beest, F.M., Schmidt, N.M.: Selecting the number of states in hidden markov models: pragmatic solutions illustrated using animal movement. J. Agric. Biol. Environ. Stat. 22(3), 270–293 (2017)

    MathSciNet  MATH  Google Scholar 

  • Polansky, L., Wittemyer, G., Cross, P.C., Tambling, C.J., Getz, W.M.: From moonlight to movement and synchronized randomness: Fourier and wavelet analyses of animal location time series data. Ecology 91(5), 1506–1518 (2010)

    Google Scholar 

  • Postlethwaite, C.M., Dennis, T.E.: Effects of temporal resolution on an inferential model of animal movement. PLoS ONE 8(5), 1–11 (2013)

    Google Scholar 

  • R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2018). http://www.R-project.org/

  • Ravindran, P., Ghosh, S.K.: Bayesian analysis of circular data using wrapped distributions. J. Stat. Theory Pract. 5(4), 547–561 (2011)

    MathSciNet  MATH  Google Scholar 

  • Rivest, L.P., Duchesne, T., Nicosia, A., Fortin, D.: A general angular regression model for the analysis of data on animal movement in ecology. J. Roy. Stat. Soc. Ser. C (Appl. Stat.) 65(3), 445–463 (2016)

    MathSciNet  Google Scholar 

  • Roy, S., Adnan, M.A.S.: Wrapped generalized gompertz distribution: an application to ornithology. J. Biomet. Biostat. 3(6), 153–156 (2012)

    Google Scholar 

  • Schtickzelle, N., Joiris, A., Dyck, H.V., Baguette, M.: Quantitative analysis of changes in movement behaviour within and outside habitat in a specialist butterfly. BMC Evolut. Biol. 7(1), 4 (2007)

    Google Scholar 

  • Schultz, C.B., Crone, E.E.: Edge-mediated dispersal behavior in a prairie butterfly. Ecology 82(7), 1879–1892 (2001)

    Google Scholar 

  • Seoane, N.: Modelling free-range cattle movements in forests using multistate random walks. J. Biol. Syst. 23(supp01), S43–S54 (2015)

    Google Scholar 

  • Stephens, M.A.: Random walk on a circle. Biometrika 50(3/4), 385–390 (1963)

    MathSciNet  MATH  Google Scholar 

  • Taylor-King, J.P., van Loon, E.E., Rosser, G., Chapman, S.J.: From birds to bacteria: generalised velocity jump processes with resting states. Bull. Math. Biol. 77(7), 1213–1236 (2015)

    MathSciNet  MATH  Google Scholar 

  • Torres, L.G., Orben, R.A., Tolkova, I., Thompson, D.R.: Classification of animal movement behavior through residence in space and time. PLoS ONE 12(1), 1–18 (2017)

    Google Scholar 

  • van de Kerk, M., Onorato, D.P., Criffield, M.A., Bolker, B.M., Augustine, B.C., McKinley, S.A., Oli, M.K.: Hidden semi-markov models reveal multiphasic movement of the endangered florida panther. J. Anim. Ecol. 84(2), 576–585 (2015)

    Google Scholar 

  • Wall, J., Wittemyer, G., LeMay, V., Douglas-Hamilton, I., Klinkenberg, B.: Data from: elliptical time-density model to estimate wildlife utilization distributions. Movebank Data Repository (2014a). https://doi.org/10.5441/001/1.f321pf80/1

    Article  Google Scholar 

  • Wall, J., Wittemyer, G., LeMay, V., Douglas-Hamilton, I., Klinkenberg, B.: Elliptical time-density model to estimate wildlife utilization distributions. Methods Ecol. Evol. 5(8), 780–790 (2014b)

    Google Scholar 

  • Young, H.C., Reid, T.G., Randall, L.A., Lachowsky, L.E., Foster, D.J., Pengelly, C.J., Latty, T., Reid, M.L.: Influences of movement behavior on animal distributions at edges of homogeneous patches. Int. J. Zool. 2013:602845 (2013)

    Google Scholar 

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Bailey, J.D., Codling, E.A. Emergence of the wrapped Cauchy distribution in mixed directional data. AStA Adv Stat Anal 105, 229–246 (2021). https://doi.org/10.1007/s10182-020-00380-7

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