Animal movement tools (amt): R package for managing tracking data and conducting habitat selection analyses

Abstract

Advances in tracking technology have led to an exponential increase in animal location data, greatly enhancing our ability to address interesting questions in movement ecology, but also presenting new challenges related to data management and analysis. Step‐selection functions (SSFs) are commonly used to link environmental covariates to animal location data collected at fine temporal resolution. SSFs are estimated by comparing observed steps connecting successive animal locations to random steps, using a likelihood equivalent of a Cox proportional hazards model. By using common statistical distributions to model step length and turn angle distributions, and including habitat‐ and movement‐related covariates (functions of distances between points, angular deviations), it is possible to make inference regarding habitat selection and movement processes or to control one process while investigating the other. The fitted model can also be used to estimate utilization distributions and mechanistic home ranges. Here, we present the R package amt (animal movement tools) that allows users to fit SSFs to data and to simulate space use of animals from fitted models. The amt package also provides tools for managing telemetry data. Using fisher ( Pekania pennanti ) data as a case study, we illustrate a four‐step approach to the analysis of animal movement data, consisting of data management, exploratory data analysis, fitting of models, and simulating from fitted models.

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References 51

1. 1.

   Agostinelli, C., & Lund, U. (2017 ). R package circular: Circular Statistics (version 0.4‐93). CA: Department of Environmental Sciences, Informatics and Statistics, Ca’ Foscari University, Venice, Italy. UL: Department of Statistics, California Polytechnic State University, San Luis Obispo, California, USA.

   Not in our library

2. 2.

   Akaike, H. (1974 ). A new look at the statistical model identification. IEEE transactions on automatic control, 19, 716–723.

   Not in our library10.1109/tac.1974.1100705

3. 3.
   Relative Selection Strength: Quantifying effect size in habitat‐ and step‐selection inference · 2017

   No notice
4. 4.

   Avgar, T., Potts, J. R., Lewis, M. A., & Boyce, M. S. (2016 ). Integrated step selection analysis: Bridging the gap between resource selection and animal movement. Methods in Ecology and Evolution., 7, 619–630.

   Not in our library10.1111/2041-210x.12528

5. 5.

   Barnett, A. H., & Moorcroft, P. R. (2008 ). Analytic steady‐state space use patterns and rapid computations in mechanistic home range analysis. Journal of Mathematical Biology, 57, 139–159.

   Not in our library10.1007/s00285-007-0149-8

6. 6.

   Beyer, H. L., Haydon, D. T., Morales, J. M., Frair, J. L., Hebblewhite, M., Mitchell, M., & Matthiopoulos, J. (2010 ). The interpretation of habitat preference metrics under use‐availability designs. Philosophical Transactions of the Royal Society B: Biological Sciences, 365, 2245–2254.

   Not in our library10.1098/rstb.2010.0083

7. 7.

   Bivand, R., & Lewin‐Koh, N. (2017 ). maptools: Tools for Reading and Handling Spatial Objects. R package version 0.9‐2.

   Not in our library

8. 8.

   Boyce, M. S., & McDonald, L. L. (1999 ). Relating populations to habitats using resource selection functions. Trends in Ecology & Evolution, 14, 268–272.

   Not in our library10.1016/s0169-5347(99)01593-1

9. 9.

   Brost, B. M., Hooten, M. B., Hanks, E. M., & Small, R. J. (2015 ). Animal movement constraints improve resource selection inference in the presence of telemetry error. Ecology, 96, 2590–2597.

   Not in our library10.1890/15-0472.1

10. 10.

    Brown, D. D., LaPoint, S., Kays, R., Heidrich, W., Kümmeth, F., & Wikelski, M. (2012 ). Accelerometer‐informed gps telemetry: Reducing the trade‐off between resolution and longevity. Wildlife Society Bulletin, 36, 139–146.

    Not in our library10.1002/wsb.111

11. 11.

    Cagnacci, F., Boitani, L., Powell, R. A., & Boyce, M. S. (2010 ). Animal ecology meets gps‐based radiotelemetry: A perfect storm of opportunities and challenges. Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 365, 2157–2162.

    Not in our library10.1098/rstb.2010.0107

12. 12.

    Calabrese, J. M., Fleming, C. H., & Gurarie, E. (2016 ). ctmm: An R package for analyzing animal relocation data as a continuous‐time stochastic process. Methods in Ecology and Evolution, 7, 1124–1132.

    Not in our library10.1111/2041-210x.12559

13. 13.

    Cooper, N., & Hsing, P. Y. (2017 ). A guide to reproducible code in ecology and evolution. Technical report, British Ecological Society. Available at https://www.britishecologicalsociety.org/wp-content/uploads/2017/12/guide-to-reproducible-code.pdf.

    Not in our library

14. 14.

    Delignette‐Muller, M. L., & Dutang, C. (2015 ). fitdistrplus: An R package for fitting distributions. Journal of Statistical Software, 64, 1–34.

    Not in our library

15. 15.

    Duchesne, T., Fortin, D., & Rivest, L. P. (2015 ). Equivalence between step selection functions and biased correlated random walks for statistical inference on animal movement. PLoS ONE, 10, e0122947

    Not in our library10.1371/journal.pone.0122947

16. 16.

    Fieberg, J. R., Forester, J. D., Street, G. M., Johnson, D. H., ArchMiller, A. A., & Matthiopoulos, J. (2018 ). Used‐habitat calibration plots: A new procedure for validating species distribution, resource selection, and step‐selection models. Ecography, 41, 737–752.

    Not in our library10.1111/ecog.03123

17. 17.

    Fieberg, J., Matthiopoulos, J., Hebblewhite, M., Boyce, M. S., & Frair, J. L. (2010 ). Correlation and studies of habitat selection: Problem, red herring or opportunity? Philosophical Transactions of the Royal Society of London B: Biological Sciences, 365, 2233–2244.

    Not in our library10.1098/rstb.2010.0079

18. 18.

    Forester, J. D., Im, H. K., & Rathouz, P. J. (2009 ). Accounting for animal movement in estimation of resource selection functions: Sampling and data analysis. Ecology, 90, 3554–3565.

    Not in our library10.1890/08-0874.1

19. 19.

    Fortin, D., Beyer, H. L., Boyce, M. S., Smith, D. W., Duchesne, T., & Mao, J. S. (2005 ). Wolves influence elk movements: Behavior shapes a trophic cascade in yellowstone national park. Ecology, 86, 1320–1330.

    Not in our library10.1890/04-0953

20. 20.

    Gail, M. H., Lubin, J. H., & Rubinstein, L. V. (1981 ). Likelihood calculations for matched case‐control studies and survival studies with tied death times. Biometrika, 68, 703–707.

    Not in our library10.1093/biomet/68.3.703

21. 21.

    Grolemund, G., & Wickham, H. (2011 ). Dates and times made easy with lubridate. Journal of Statistical Software, 40, 1–25.

    Not in our library

22. 22.

    Gurarie, E., Andrews, R. D., & Laidre, K. L. (2009 ). A novel method for identifying behavioural changes in animal movement data. Ecology Letters, 12, 395–408.

    Not in our library10.1111/j.1461-0248.2009.01293.x

23. 23.

    Hanks, E. M., Hooten, M. B., Alldredge, M. W. (2015 ). Continuous‐time discrete space models for animal movement. The Annals of Applied Statistics, 9, 145–165.

    Not in our library10.1214/14-aoas803

24. 24.

    Henry, L., & Wickham, H. (2017 ). purrr: Functional Programming Tools. R package version 0.2.2.2.

    Not in our library

25. 25.

    Hijmans, R. J. (2017 ). raster: Geographic Data Analysis and Modeling. R package version 2.6‐7.

    Not in our library

26. 26.

    Hooten, M. B., Buderman, F. E., Brost, B. M., Hanks, E. M., & Ivan, J. S. (2016 ). Hierarchical animal movement models for population‐level inference. Environmetrics, 27, 322–333.

    Not in our library10.1002/env.2402

27. 27.

    Hooten, M. B., Johnson, D. S., Hanks, E. M., & Lowry, J. H. (2010 ). Agent‐based inference for animal movement and selection. Journal of Agricultural, Biological and Environmental Statistics, 15, 523–538.

    Not in our library10.1007/s13253-010-0038-2

28. 28.

    Hooten, M. B., Johnson, D. S., McClintock, B. T., & Morales, J. M. (2017 ). Animal movement: Statistical models for telemetry data. Boca Raton, FL: CRC Press.

    Not in our library

29. 29.

    Johnson, D. S., Hooten, M. B., & Kuhn, C. E. (2013 ). Estimating animal resource selection from telemetry data using point process models. Journal of Animal Ecology, 82, 1155–1164.

    Not in our library10.1111/1365-2656.12087

30. 30.

    Johnson, D. S., Thomas, D. L., Ver Hoef, J. M., & Christ, A. (2008 ). A general framework for the analysis of animal resource selection from telemetry data. Biometrics, 64, 968–976.

    Not in our library10.1111/j.1541-0420.2007.00943.x

31. 31.

    Kays, R., Crofoot, M. C., Jetz, W., & Wikelski, M. (2015 ). Terrestrial animal tracking as an eye on life and planet. Science, 348, aaa2478

    Not in our library10.1126/science.aaa2478

32. 32.

    LaPoint, S., Gallery, P., Wikelski, M., & Kays, R. (2013a ). Animal behavior, cost‐based corridor models, and real corridors. Landscape Ecology, 28, 1615–1630.

    Not in our library10.1007/s10980-013-9910-0

33. 33.

    LaPoint, S., Gallery, P., Wikelski, M., & Kays, R. (2013b ). Data from: Animal behavior, cost‐based corridor models, and real corridors. Landscape Ecology, 28, 1615–1630.

    Not in our library10.1007/s10980-013-9910-0

34. 34.

    Lewis, K. P., Vander Wal, E., & Fifield, D. A. (2018 ). Wildlife biology, big data, and reproducible research. Wildlife Society Bulletin., 42, 172–179.

    Not in our library10.1002/wsb.847

35. 35.

    Manly, B., McDonald, L., Thomas, D. L., McDonald, T. L., & Erickson, W. P. (2007 ). Resource selection by animals: Statistical design and analysis for field studies. Dordrecht, The Netherlands: Kluwer Academic Publishers.

    Not in our library

36. 36.

    McClintock, B. T. (2017 ). Incorporating telemetry error into hidden markov models of animal movement using multiple imputation. Journal of Agricultural, Biological and Environmental Statistics, 22, 249–269.

    Not in our library10.1007/s13253-017-0285-6

37. 37.

    McClintock, B. T., & Michelot, T. (2018 ). momentuhmm: R package for generalized hidden markov models of animal movement. Methods in Ecology and Evolution, 9, 1518–1530.

    Not in our library10.1111/2041-210x.12995

38. 38.

    Michelot, T., Langrock, R., & Patterson, T. A. (2016 ). movehmm: An R package for the statistical modelling of animal movement data using hidden Markov models. Methods in Ecology and Evolution, 7, 1308–1315.

    Not in our library10.1111/2041-210x.12578

39. 39.

    Moorcroft, P. R., & Lewis, M. A. (2013 ). Mechanistic home range analysis.(MPB‐43). Princeton, NJ: Princeton University Press

    Not in our library10.1515/9781400849734

40. 40.

    Müller, K., & Wickham, H. (2018 ). tibble: Simple Data Frames. R package version 1.4.2.

    Not in our library

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