Understanding movement data and movement processes: Current and emerging directions

Ecology Letters

Volumn 11, Issue 12, 2008, Pages 1338-1350

  Schick, Robert S ^a   Loarie, Scott R ^a   Colchero, Fernando ^a   Best, Benjamin D ^a   Boustany, Andre ^a   Conde, Dalia A ^a   Halpin, Patrick N ^a   Joppa, Lucas N ^a   McClellan, Catherine M ^a   Clark, James S ^a,b  

^a DUKE UNIVERSITY   (United States)

^b Duke University   (United States)

Author keywords

Animal movement; First passage time; Fractal analysis; Hierarchical Bayes; L vy flights; Resource selection functions; Spatial ecology; State space models; Telemetry

Indexed keywords

ANIMAL; CLIMATE CHANGE; ECOLOGY; HABITAT LOSS; MOVEMENT; POPULATION DISTRIBUTION; POPULATION DYNAMICS;

ANIMAL; BIOLOGICAL MODEL; ECOLOGY; ENVIRONMENT; MOVEMENT (PHYSIOLOGY); PHYSIOLOGY; POPULATION DYNAMICS; POPULATION MIGRATION; REVIEW;

ANIMAL MIGRATION; ANIMALS; ECOLOGY; ENVIRONMENT; MODELS, BIOLOGICAL; MOVEMENT; POPULATION DYNAMICS;

ANIMALIA;

EID: 55649098388     PISSN: 1461023X     EISSN: 14610248     Source Type: Journal    
DOI: 10.1111/j.1461-0248.2008.01249.x     Document Type: Review

References (84)

1. Anderson-Sprecher, R. Ledolter, J. (1991). State-space analysis of wildlife telemetry data. J. Am. Stat. Assoc., 86, 596 602.
2. Armsworth, P. Roughgarden, J. (2005). The impact of directed versus random movement on population dynamics and biodiversity patterns. Am. Nat., 165, 449 465.
3. Bartumeus, F., da Luz, M., Viswanathan, G. Catalan, J. (2005). Animal search strategies: a quantitative random-walk analysis. Ecology, 86, 3078 3087.
4. Berliner, M. (1996). Hierarchical bayesian time series models. In : Maximum Entropy and Bayesian Methods (eds Hanson, K. Silver, R.). Kluwer, Dordrecht, pp. 15 22.
5. Blackwell, P.G. (1997). Random diffusion models for animal movement. Ecol. Model., 100, 87 102.
6. Blackwell, P.G. (2003). Bayesian inference for markov processes with diffusion and discrete components. Biometrika, 90, 613 627.
7. Bowler, D. Benton, T. (2005). Causes and consequences of animal dispersal strategies: relating individual behaviour to spatial dynamics. Biol. Rev., 80, 205 225.
8. Carlin, B.P. Louis, T.A. (2000). Bayes and Empirical Bayes Methods for Data Analysis. Chapman & Hall, New York.
9. Christ, A., Ver Hoef, J. Zimmerman, D.L. (2008). An animal movement model incorporating home range and habitat selection. Environ. Ecol. Stat., 15, 27 38.
10. Clark, J.S. (2005). Why environmental scientists are becoming bayesians. Ecol. Lett., 8, 2 14.
11. Clark, J.S. (2007). Models for Ecological Data: An Introduction. Princeton University Press, Princeton.
12. Clark, J.S. Bjørnstad, O. (2004). Population inference from messy data: errors, missing and hidden states, and lagged responses. Ecology, 85, 3140 3150.
13. Clark, J.S., Silman, M., Kern, R., Macklin, E. HilleRisLambers, J. (1999). Seed dispersal near and far: patterns across temperate and tropical forests. Ecology, 80, 1475 1494.
14. Clark, J.S., Lewis, M. Horvath, L. (2001). Invasion by extremes: population spread with variation in dispersal and reproduction. Am. Nat., 157, 537 554.
15. Clark, J.S., Lewis, M.A., McLachlan, J. HilleRisLambers, J. (2003). Estimating population spread based on dispersal data: what can we forecast and how well. Ecology, 84, 1979 1988.
16. Cooke, S.J., Hinch, S.G., Wikelski, M., Andrews, R.D., Kuchel, L.J., Wolcott, T.G. et al. (2004). Biotelemetry: a mechanistic approach to ecology. Trends Ecol. Evol., 19, 334 343.
17. Dall, S.R.X., Giraldeau, L.-A., Olsson, O., McNamara, J.M. Stephens, D.W. (2005). Information and its use by animals in evolutionary ecology. Trends Ecol. Evol., 20, 187 193.
18. Dalziel, B.D., Morales, J.M. Fryxell, J.M. (2008). Fitting probability distributions to animal movement trajectories: using artifical neural networks to link distance, resources, and memory. Am. Nat., 172, 248 258.
19. Dicke, M. Burrough, P.A. (1988). Using fractal dimensions for characterizing tortuosity of animal trails. Physiol. Entomol., 13, 393 398.
20. Eckert, S.A., Moore, J.E., Dunn, D.C., van Buiten, R.S., Eckert, K.L. Halpin, P. (2008). Modeling loggerhead turtle movement in the Mediterranean: importance of body size and oceanography. Ecol. Appl., 18, 290 308.
21. Edwards, A., Phillips, R., Watkins, N., Freeman, M., Murphy, E., Afanasyev, V. et al. (2007). Revisiting Lévy flight search patterns of wandering albatrosses, bumblebees and deer. Nature, 449, 1044 1048.
22. Fauchald, P. Tveraa, T. (2003). Using first-passage time in the analysis of area-restricted search and habitat selection. Ecology, 84, 282 288.
23. Forester, J.D., Ives, A.R., Turner, M.G., Anderson, D.P., Fortin, D., Beyer, H.L. et al. (2007). State-space models link elk movement patterns to landscape characteristics in Yellowstone National Park. Ecol. Monogr., 77, 285 299.
24. Fritz, H., Said, S. Weimerskirch, H. (2003). Scale-dependent hierarchical adjustments of movement patterns in a long-range foraging seabird. P Roy. Soc. Lond. B Bio., 270, 1143 1148.
25. Gautestad, A. Mysterud, I. (2005). Intrinsic scaling complexity in animal dispersion and abundance. Am. Nat., 165, 44 55.
26. Gelfand, A. Smith, A. (1990). Sampling-based approaches to calculating marginal densities. J. Am. Stat. Assoc., 85, 398 409.
27. Godley, B.J., Blumenthal, J.M., Broderick, A.C., Coyne, M.S., Godfrey, M.H., Hawkes, L.A. et al. (2008). Satellite tracking of sea turtles: where have we been and where do we go next? Endangered Species Research, 4, 3 22.
28. Hays, G.C., Åkesson, S., Godley, B.J., Luschi, P. Santidrian, P. (2001). The implications of location accuracy for the interpretation of satellite-tracking data. Anim. Behav., 61, 1035 1040.
29. Hinrichsen, D. Pritchard, A. (2005). Mathematical Systems Theory I: Modelling, State Space Analysis, Stability and Robustness. Springer, Heidelberg.
30. Johnson, A.R., Milne, B.T. Wiens, J.A. (1992). Diffusion in fractal landscapes: simulations and experimental studies of Tenebrionid beetle movements. Ecology, 73, 1968 1983.
31. Johnson, C.J., Parker, K.L., Heard, D.C. Gillingham, M.P. (2002a). A multiscale behavioral approach to understanding the movements of woodland caribou. Ecol. Appl., 12, 1840 1860.
32. Johnson, C.J., Parker, K.L., Heard, D.C. Gillingham, M.P. (2002b). Movement parameters of ungulates and scale-specific responses to the environment. J. Anim. Ecol., 71, 225 235.
33. Johnson, C.J., Seip, D.R. Boyce, M.S. (2004). A quantitative approach to conservation planning: using resource selection functions to map the distribution of mountain caribou at multiple spatial scales. J. Appl. Ecol., 41, 238 251.
34. Johnson, C.J., Parker, K.L., Heard, D.C. Gillingham, M.P. (2006). Unrealistic animal movement rates as behavioural bouts: a reply. J. Anim. Ecol., 75, 303 308.
35. Johnson, D.S., London, J.M., Lea, M.-A. Durban, J. (2008). Continuous-time correlated random walk model for animal telemetry data. Ecology, 89, 1208 1215.
36. Jonsen, I., Myers, R. Flemming, J.M. (2003). Meta-analysis of animal movement using state-space models. Ecology, 84, 3055 3063.
37. Jonsen, I., Flemming, J.M. Myers, R. (2005). Robust state-space modeling of animal movement data. Ecology, 86, 2874 2880.
38. Jonsen, I., Myers, R. James, M. (2006). Robust hierarchical state-space models reveal diel variation in travel rates of migrating leatherback turtles. J. Anim. Ecol., 75, 1046 1057.
39. Jonsen, I., Myers, R. James, M. (2007). Identifying leatherback turtle foraging behaviour from satellite telemetry using a switching state-space model. Mar. Ecol. Prog. Ser., 337, 255 264.
40. Kalman, R. (1960). A new approach to linear filtering and prediction problems. J. Basic Eng-T ASME, 82, 35 45.
41. Kareiva, P. (1990). Population dynamics in spatially complex environments: theory and data. Philos. T. Roy. Soc. B, 330, 175 190.
42. Kareiva, P.M. Shigesada, N. (1983). Analyzing insect movement as a correlated random walk. Oecologia, 56, 234 238.
43. Kareiva, P. Wennergren, U. (1995). Connecting landscape patterns to ecosystem and population processes. Nature, 373, 299 302.
44. Kot, M., Lewis, M. van den Driessche, P. (1996). Dispersal data and the spread of invading organisms. Ecology, 77, 2027 2042.
45. Levin, S.A. (1992). The problem of pattern and scale in ecology. Ecology, 73, 1943 1967.
46. Lima, S.L. Zollner, P.A. (1996). Towards a behavioral ecology of ecological landscapes. Trends Ecol. Evol., 11, 131 135.
47. Lunn, D., Thomas, A., Best, N. Spiegelhalter, D. (2000). WinBUGS-A Bayesian modelling framework: concepts, structure, and extensibility. Stat. Comput., 10, 325 337.
48. Manly, B. McDonald, T. (2002). Resource Selection by Animals: Statistical Design and Analysis for Field Studies. Springer, Dordrecht.
49. Marsh, L. Jones, R. (1988). The form and consequences of random walk movement models. J. Theor. Biol., 133, 113 131.
50. Milne, B. (1991). Lessons from applying fractal models to landscape patterns. In : Quantitative Methods in Landscape Ecology (eds Turner, M. Gardner, R.). Springer, New York, pp. 199 235.
51. Moorcroft, P. Barnett, A. (2008). Mechanistic home range models and resource selection analysis: a reconciliation and unification. Ecology, 89, 1112 1119.
52. Moorcroft, P., Lewis, M. Crabtree, R. (1999). Home range analysis using a mechanistic home range model. Ecology, 80, 1656 1665.
53. Moorcroft, P., Lewis, M. Crabtree, R. (2006). Mechanistic home range models capture spatial patterns and dynamics of coyote territories in Yellowstone. P Roy. Soc. Lond. B Bio., 273, 1651 1659.
54. Morales, J. (2002). Behavior at habitat boundaries can produce leptokurtic movement distributions. Am. Nat., 160, 531 538.
55. Morales, J. Ellner, S. (2002). Scaling up animal movements in heterogeneous landscapes: the importance of behavior. Ecology, 83, 2240 2247.
56. Morales, J.M., Haydon, D.T., Frair, J., Holsinger, K.E. Fryxell, J.M. (2004). Extracting more out of relocation data: building movement models as mixtures of random walks. Ecology, 85, 2436 2445.
57. Morales, J., Fortin, D., Frair, J. Merrill, E. (2005). Adaptive models for large herbivore movements in heterogeneous landscapes. Landscape Ecol., 20, 301 316.
58. Mueller, T. Fagan, W.F. (2008). Search and navigation in dynamic environments - from individual behaviors to population distributions. Oikos, 117, 654 664.
59. Nams, V. (2005). Using animal movement paths to measure response to spatial scale. Oecologia, 143, 179 188.
60. Nams, V. (2006). Improving accuracy and precision in estimating fractal dimension of animal movement paths. Acta Biotheor., 54, 1 11.
61. Newman, K. (1998). State-space modeling of animal movement and mortality with application to salmon. Biometrics, 54, 1290 1314.
62. Okubo, A. (1980). Diffusion and Ecological Problems: Mathematical models. Springer-Verlag, Berlin.
63. Okubo, A. Levin, S. (1989). A theoretical framework for data analysis of wind dispersal of seeds and pollen. Ecology, 70, 329 338.
64. Okubo, A. Levin, S. eds 2002). Diffusion and Ecological Problems, 2nd edn. Springer, New York.
65. Ovaskainen, O. (2004). Habitat-specific movement parameters estimated using mark-recapture data and a diffusion model. Ecology, 85, 242 257.
66. Ovaskainen, O., Rekola, H., Meyke, E. Arjas, E. (2008). Bayesian methods for analyzing movements in heterogeneous landscapes from mark-recapture data. Ecology, 89, 542 554.
67. Patterson, T., Thomas, L., Wilcox, C., Ovaskainen, O. Matthiopoulos, J. (2008). State-space models of individual animal movement. Trends Ecol. Evol., 23, 87 94.
68. Royer, F., Fromentin, J.M. Gaspar, P. (2005). A state-space model to derive bluefin tuna movement and habitat from archival tags. Oikos, 109, 473 484.
69. Shlesinger, M., Zaslavsky, G. Klafter, J. (1993). Strange kinetics. Nature, 31, 37.
70. Sibert, J. Fournier, D. (2001). Possible models for combining tracking data with conventional tagging data. In : Electronic Tagging and Tracking in Marine Fisheries (eds Sibert, J. Nielsen, J.). Kluwer Academic Publishers, The Netherlands, pp. 443 456.
71. Sibly, R., Nott, H. Fletcher, D. (1990). Splitting behaviour into bouts. Anim. Behav., 39, 63 69.
72. Sims, D., Southall, E., Humphries, N., Hays, G., Bradshaw, C., Pitchford, J. et al. (2008). Scaling laws of marine predator search behaviour. Nature, 451, 1098 1102.
73. Skellam, J.G. (1951). Random dispersal in theoretical populations. Biometrika, 38, 196 218.
74. Tremblay, Y., Roberts, A. Costa, D. (2007). Fractal landscape method: an alternative approach to measuring area-restricted searching behavior. J. Exp. Biol., 210, 935.
75. Turchin, P. (1991). Translating foraging movements in heterogeneous environments into the spatial distribution of foragers. Ecology, 72, 1253 1266.
76. Turchin, P. (1996). Fractal analyses of animal movement: a critique. Ecology, 77, 2086 2090.
77. Turchin, P. (1998). Quantitative Analysis of Movement: Measuring and Modeling Population Redistribution in Animals and Plants. Sinauer Associates, Sunderland.
78. Viswanathan, G., Afanasyev, V., Buldyrev, S., Murphy, E., Prince, P. Stanley, H. (1996). Levy flight search patterns of wandering albatrosses. Nature, 381, 413 415.
79. Viswanathan, G., Buldyrev, S., Havlin, S., da Luz, M., Raposo, E. Stanley, H. (1999). Optimizing the success of random searches. Nature, 401, 911 914.
80. West, M. Harrison, J. (1997). Bayesian Forecasting and Dynamic Models. Springer Verlag, New York, NY.
81. Wiens, J. Milne, B. (1989). Scaling of "landscapes" in landscape ecology, or, landscape ecology from a beetle's perspective. Landscape Ecol., 3, 87 96.
82. Wikle, C.K. (2003). Hierarchical bayesian models for predicting the spread of ecological processes. Ecology, 84, 1382 1394.
83. Wikle, C., Berliner, L. Cressie, N. (1998). Hierarchical Bayesian space-time models. Environ. Ecol. Stat., 5, 117 154.
84. With, K. (1994). Using fractal analysis to assess how species perceive landscape structure. Landscape Ecol., 9, 25 36.