Recent advances in the analysis of behavioural organization and interpretation as indicators of animal welfare

Journal of the Royal Society Interface

Volumn 6, Issue 41, 2009, Pages 1103-1119

  Asher, Lucy ^a   Collins, Lisa M ^a   Ortiz Pelaez, Angel ^a   Drewe, Julian A ^a   Nicol, Christine J ^b   Pfeiffer, Dirk U ^a  

^a ROYAL VETERINARY COLLEGE   (United Kingdom)

^b UNIVERSITY OF BRISTOL   (United Kingdom)

Author keywords

Animal behaviour; Fractal analysis; Markov chains; Modelling; Social networks; Theme

Indexed keywords

ANIMALS; COMPUTER SIMULATION; ELECTRIC NETWORK ANALYSIS; MARKOV PROCESSES;

ANIMAL BEHAVIOUR; FRACTAL ANALYSIS; MARKOV CHAINS; MODELLING; SOCIAL NETWORKS; THEME;

FRACTALS;

ANALYTIC METHOD; ANIMAL BEHAVIOR; ANIMAL WELFARE; BEHAVIORAL SCIENCE; FRACTAL ANALYSIS; MONTE CARLO METHOD; PAIN; PROBABILITY; REVIEW; SIMULATION; SOCIAL NETWORK; STRESS;

ANIMALIA;

EID: 70350495393     PISSN: 17425689     EISSN: 17425662     Source Type: Journal    
DOI: 10.1098/rsif.2009.0221     Document Type: Review

References (163)

1. Abu Maria, K. & Abu Zitar, R. 2007 Emotional agents: a modeling and an application. Inf. Softw. Technol. 49, 695-716. (doi:10.1016/j.infsof.2006.08. 002)
2. Alados, C. L. & Huffman, M. A. 2000 Fractal long-range correlations in behavioural sequences of wild chimpanzees: a non-invasive analytical tool for the evaluation of health. Ethology 106, 105-116. (doi:10.1046/j.1439-0310.2000. 00497.x)
3. Alados, C. L. &Weber, D. N. 1999 Lead effects on the predictability of reproductive behavior in fathead minnows (Pimephales promelas): a mathematical model. Environ. Toxicol. Chem. 18, 2392-2399. (doi:10.1897/1551- 5028(1999)018〈2392:LEOTPO〉2.3.CO;2)
4. Aleman-Meza, B., Nagarajan, M., Ramakrishnan, C., Ding, L., Kolari, P., Sheth, A., Arpinar, I. B., Joshi, A. & Finn, T. 2006 Semantic analysis on social networks: experiences in addressing the problem of conflcit of interest detection. In Proc. Int. Conf. on the World Wide Web, Edinburgh, UK. New York, NY: ACM Press.
5. Anolli, L., Duncan Jr, S., Magnusson, M. S. & Riva, G. 2005 Conversation patterns in Icelandic and Italian people: similarities and differences in rhythm and accommodation. In The hidden structure of interaction: from neurons to culture patterns. Amsterdam, The Netherlands: IOS Press.
6. Asher, L., Davies, G. T. O., Bertenshaw, C. E., Cox, M. A. A. & Bateson, M. 2009 The effects of cage volume and cage shape on the condition and behaviour of captive European starlings (Sturnus vulgaris). Appl. Anim. Behav. Sci. 116, 286-294. (doi:10.1016/j.applanim.2008.10.008)
7. Bakeman, R. & Quera, V. 1995 Analyzing interaction: sequential analysis with SDIS and GSEQ. New York, NY: Cambridge University Press.
8. Barbu, V. S. & Limnios, N. 2008 Semi-Markov chains and hidden semi-Markov models toward applications: their use in reliability and DNA analysis. New York, NY: Birkhäuser.
9. Bassett, L. & Buchanan-Smith, H. M. 2007 Effects of predictability on the welfare of captive animals. Appl. Anim. Behav. Sci. 102, 223-245. (doi:10.1016/j.applanim.2006.05.029)
10. Benhamou, S. 2004 How to reliably estimate the tortuosity of an animal's path: straightness, sinuosity, or fractal dimension? J. Theor. Biol. 229, 209-220. (doi:10.1016/j.jtbi.2004.03.016)
11. Ben-Jacob, E. & Levine, H. 2006 Self-engineering capabilities of bacteria. J. R. Soc. Interface 3, 197-214. (doi:10.1098/rsif.2005.0089)
12. Berkman, L. F. & Syme, S. L. 1979 Social networks, host resistance, and mortality: a nine-year follow-up study of Alameda county residents, vol.109, pp. 186-204. Oxford, UK: Oxford University Press.
13. Bonasera, S., Schenk, A., Luxenberg, E. & Tecott, L. 2008 A novel method for automatic quantification of psychostimulant- evoked route-tracing stereotypy: application to Mus musculus. Psychopharmacology 196, 591-602. (doi:10.1007/s00213-007-0994-996)
14. Borrie, A., Jonsson, G. K. & Magnusson, M. S. 2002 Temporal pattern analysis and its applicability in sport: an explanation and exemplar data. J. Sports Sci. 20, 845-852. (doi:10.1080/026404102320675675)
15. Bowles, S. & Gintis, H. 2004 The evolution of strong reciprocity: cooperation in heterogeneous populations. Theor. Popul. Biol. 65, 17-28. (doi:10.1016/j.tpb.2003.07.001)
16. Brand, M., Oliver, N. & Pentland, A. 1997. Coupled hidden Markov models for complex action recognition. In Proc. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Juan, Puerto Rico, pp. 994-999. New York, NY: IEEE.
17. Broekens, J., Kosters, W. A. & Verbeek, F. J. 2007 Affect, anticipation, and adaptation: affect-controlled selection of anticipatory simulation in artificial adaptive agents. Adapt. Behav. 15, 397-422. (doi:10.1177/1059712307084686)
18. Browne, W. J., McCleery, R.H., Sheldon, B. C. & Pettifor, R.A. 2007 Using cross-classified multivariate mixed response models with application to life history traits in great tits (Parus major). Stat. Modell. 7, 217-238. (doi:10.1177/1471082x0700700301)
19. Bryson, J., Lowe, W. & Stein, L. A. 2001 Hypothesis testing for complex agents. In Workshop on performance metrics for intelligent systems (eds A. M. Meystel & E. R. Messina). Washington, DC: NIST Special Publication.
20. Bryson, J. J., Ando, Y. & Lehman, H. 2007 Agent-based modelling as scientific method: a case study analysing primate social behaviour. Phil. Trans. R. Soc. B 362, 1685-1698. (doi:10.1098/rstb.2007.2061)
21. Burghardt, G. M. 2005 The genesis of animal play: testing the limits. Cambridge, MA: MIT Press.
22. Cane, V. 1959 Behaviour sequences as semi-Markov chains. J. R. Stat. Soc. Ser. B 21, 36-58.
23. Carrington, P. J., Scott, J. & Wasserman, S. 2005 Models and methods in social network analysis. New York, NY: Cambridge University Press.
24. Cazelles, B., Chavez, M., de Magny, G. C., Guegan, J. F. & Hales, S. 2007 Time-dependent spectral analysis of epidemiological time-series with wavelets. J. R. Soc. Interface 4, 625-636. (doi:10.1098/rsif.2007.0212)
25. Clauset, A., Shalizi, C. R. & Newman, M. E. J. 2007 Powerlaw distributions in empirical data. (http://arxiv.org/ abs/0706.1062v1)
26. Cole, B. J. 1995 Fractal time in animal behavior: the movement activity of Drosophila. Anim. Behav. 50, 1317-1324. (doi:10.1016/0003-3472(95)80047-6)
27. Collins, L. M. & Sumpter, D. J. T. 2007 The feeding dynamics of broiler chickens. J. R. Soc. Interface 4, 65-72. (doi:10.1098/rsif.2006.0157)
28. Collins, L. M., Asher, L., Pfeiffer, D. U. & Nicol, C. J. In preparation. Clustering, synchrony and activity levels in laying hens: the effect of environmental resources on social dynamics.
29. Cook, R. G., Geller, A. I., Zhang, G. R. & Gowda, R. 2004 Touch screen-enhanced visual learning in rats. Behav. Res. Meth. Instrum. 36, 101-106.
30. Coutellier, L., Friedrich, A. C., Failing, K., Marashi, V. & Wurbel, H. 2009 Effects of foraging demand on maternal behaviour and adult offspring anxiety and stress response in C57BL/6 mice. Behav. Brain Res. 196, 192-199. (doi:10.1016/j.bbr.2008.08.042)
31. Croft, D. P., James, R., Ward, A. J. W., Botham, M. S., Mawdsley, D. & Krause, J. 2005 Assortative interactions and social networks in fish. Oecologia 143, 211-219. (doi:10.1007/s00442-004-1796-8) (Pubitemid 40492288)
32. Croft, D. P., James, R. & Krause, J. 2008 Exploring animal social networks. Princeton, NJ: Princeton University Press.
33. Dailey, J.W.&McGlone, J. J. 1997 Oral/nasal/facial and other behaviors of sows kept individually outdoors on pasture, soil or indoors in gestation crates. Appl. Anim. Behav. Sci. 52, 25-43. (doi:10.1016/S0168-1591(96) 01099-4)
34. Dawkins, M. S. 2003 Behaviour as a tool in the assessment of animal welfare. Zoology 106, 383-387. (doi:10.1078/0944-2006-100122)
35. Dicke, M. & Burrough, P. A. 1988 Using fractal dimensions for characterizing tortuosity of animal trails. Physiol. Entomol. 13, 393-398. (doi:10.1111/j.1365-3032.1988.tb01122.x)
36. Donohue, K. D., Medonza, D. C., Crane, E. R. & O'Hara, B. F. 2008 Assessment of a non-invasive high-throughput classifier for behaviours associated with sleep and wake in mice. Biomed. Eng. Online 7, 14. (doi:10.1186/1475-925x-7-14)
37. Drewe, J. A., Madden, J. R. & Pearce, G. P. 2009 The social network structure of a wild meerkat population. 1. Inter-group interactions. Behav. Ecol. Sociobiol. 63, 1295-1306. (doi:10.1007/s00265-009-0782-x)
38. Edwards, A. M. et al. 2007 Revisiting Levy flight search patterns of wandering albatrosses, bumblebees and deer. Nature 449, 1044-1048. (doi:10.1038/nature06199)
39. Eubank, S., Guclu, H., Kumar, V. S. A., Marathe, M. V., Srinivasan, A., Toroczkai, Z. & Wang, N. 2004 Modelling disease outbreaks in realistic urban social networks. Nature 429, 180-184. (doi:10.1038/nature02541) (Pubitemid 38656193)
40. Fowler, S. C., Birkestrand, B. R., Chen, R., Moss, S. J., Vorontsova, E., Wang, G. & Zarcone, T. J. 2001 A force-plate actometer for quantitating rodent behaviors: illustrative data on locomotion, rotation, spatial patterning, stereotypies, and tremor. J. Neurosci. Methods 107, 107-124. (doi:10.1016/S0165-0270(01)00359-4) (Pubitemid 32487615)
41. Fox, C., Merali, Z. & Harrison, C. 2006 Therapeutic and protective effect of environmental enrichment against psychogenic and neurogenic stress. Behav. Brain Res. 175, 1-8. (doi:10.1016/j.bbr.2006.08.016)
42. Fraser, D. 2008 Understanding animal welfare: the science and its cultural context. UFAWAnimal Welfare Series. Oxford, UK: Wiley-Blackwell.
43. Fritz, H., Said, S. & Weimerskirch, H. 2003 Scale-dependent hierarchical adjustments of movement patterns in a longrange foraging seabird. Proc. R. Soc. Lond. B 270, 1143-1148. (doi:10.1098/rspb.2003.2350)
44. Garner, J. P., Mason, G. J. & Smith, R. 2003 Stereotypic route-tracing in experimentally caged songbirds correlates with general behavioural disinhibition. Anim. Behav. 66, 711-727. (doi:10.1006/anbe.2002. 2254)
45. Gatti, D. D., Di Guilmi, C., Gallegati, M., Gaffeo, E., Giulioni, G. & Palestrini, A. 2008 Scaling laws in the macroeconomy. Adv. Complex Syst. 11, 131-138. (doi:10.1142/S0219525908001532)
46. Gillespie, D. T. 1992 Markov processes: an introduction for physical scientists. San Diego, USA: Academic Press.
47. Goldstone, R. L., Roberts, M. E. & Gureckis, T. M. 2008 Emergent processes in group behavior. Curr. Direct. Psychol. Sci. 17, 10-15. (doi:10.1111/j.1467-8721.2008.00539.x)
48. Gonyou, H. W., Zhou, J. Z. & Stricklin, W. R. 1997 Applying animal technology to the design and evaluation of pens for growing-finishing pigs. In Livestock Environment V, Proc. 5th Int. Livest. Environ. Symp., Minneapolis, vol.2, pp. 836-842.
49. Grafen, A. 2002 A state-free optimization model for sequences of behaviour. Anim. Behav. 63, 183-191. (doi:10.1006/anbe.2001.1871)
50. Grammer, K., Kruck, K. B. & Magnusson, M. S. 1998 The courtship dance: patterns of nonverbal synchronization in opposite-sex encounters. J. Nonverbal Behav. 22, 3-29. (doi:10.1023/A:1022986608835) (Pubitemid 128044126)
51. Grimm, V. et al. 2005 Pattern-oriented modeling of agentbased complex systems: lessons from ecology. Science 310, 987-991. (doi:10.1126/science. 1116681) (Pubitemid 41611904)
52. Haccou, P. & Meelis, E. 1992 Statistical analysis of behavioural data: an approach based on time-structured models. Oxford, UK: Oxford University Press.
53. Hanneman, R. A. 2005 Spatial dynamics of human populations: some basic models. See http://faculty.ucr.edu/~ hanneman/spatial/index.html.
54. Hannenhalli, S. S. & Russell, R. B. 2000 Analysis and prediction of functional sub-types from protein sequence alignments. J. Mol. Biol. 303, 61-76. (doi:10.1006/jmbi.2000.4036)
55. Hardy, I. C. W. & Field, S. A. 1998 Logistic analysis of animal contests. Anim. Behav. 56, 787-792. (doi:10.1006/anbe.1998.0833)
56. Hastings, W. K. 1970 Monte-Carlo sampling methods using Markov chains and their applications. Biometrika 57, 97-109. (doi:10.1093/biomet/57.1.97)
57. Hastings, H. M. & Sugihara, G. 1993 Fractals: a user's guide for the natural sciences. Oxford, UK: Oxford Science Publications, Oxford University Press.
58. Hawes, L. C. & Foley, J. M. 1973 Markov analysis of interview communication. Speech Monogr. 40, 208-219.
59. Henderson, J. V., Lines, J. A., Wathes, C. M., White, R. P. & Nicol, C. J. 2001 Behaviour of domestic ducks exposed to mobile predator stimuli. 2. The association of individual duckling attributes with relative position in a flock. Br. Poult. Sci. 42, 439-448. (doi:10.1080/00071660120070659)
60. Hocking, P. M., Rutherford, K. M. D. & Picard, M. 2007 Comparison of time-based frequencies, fractal analysis and T-patterns for assessing behavioural changes in broiler breeders fed on two diets at two levels of feed restriction: a case study. Appl. Anim. Behav. Sci. 104, 37-48. (doi:10. 1016/j.applanim.2006.04.023)
61. House, J. S., Landis, K. R. & Umberson, D. 1988 Social relationships and health. Science 241, 540. (doi:10.1126/science.3399889)
62. Inglis, I. R. & Langton, S. 2006 How an animal's behavioural repertoire changes on response to a changing environment: a stochastic model. Behaviour 143, 1563-1596. (doi:10. 1163/156853906779367044) (Pubitemid 46122092)
63. Jefferies, P., Hart, M. L., Hui, P. M. & Johnson, N. F. 2001 From market games to real-world markets. Eur. Phys. J. B 20, 493-501. (doi:10.1007/s100510170228)
64. Jennings, N. R. 2000 On agent-based software engineering. Artif. Intell. 117, 277-296. (doi:10.1016/S0004-3702(99)00107-1)
65. Jolly, K. G., Ravindran, K. P., Vijayakumar, R. & Kumar, R. S. 2007 Intelligent decision making in multi-agent robot soccer system through compounded artificial neural networks. Robot. Auton. Syst. 55, 589-596. (doi:10.1016/j.robot.2006.12.011)
66. Jonsson, G. K., Anguera, M. T., Blanco-Villasenor, A., Losada, J. L., Hernandez-Mendo, A., Arda, T., Camerino, O. & Castellano, J. 2006 Hidden patterns of play interaction in soccer using SOF-CODER. Behav. Res. Methods 38, 372-381.
67. Kane, A. S., Salierno, J. D., Gipson, G. T., Molteno, T. C. A. & Hunter, C. 2004Avideo-based movement analysis system to quantify behavioral stress responses of fish. Water Res. 38, 3993-4001. (doi:10.1016/j.watres.2004. 06.028)
68. Ke, J., Gong, T. & Wang, W. S. Y. 2008 Language change and social networks. Commun. Comput. Phys. 3, 935-949.
69. Keeling, M. J. & Ross, J. V. 2008 On methods for studying stochastic disease dynamics. J. R. Soc. Interface 5, 171-181. (doi:10.1098/rsif.2007.1106)
70. Keller-McNulty, S., McNulty, M. S. & Gustafson, D. A. 1991 Stochastic-models for software science. J. Syst. Softw. 16, 59-68. (doi:10.1016/0164-1212(91)90032-2)
71. Kembro, J. M., Satterlee, D.G., Schmidt, J. B., Perillo, M.A. & Marin, R. H. 2008 Open-field temporal pattern in ambulation in Japanese quail selected for contrasting adrenocortical responsiveness to brief manual restraint. Poult. Sci. 87, 2186-2195. (doi:10.3382/ps.2008-00108)
72. Kerepesi, A., Jonsson, G. K., Miklosi, A., Topal, J., Csanyi, V. & Magnusson, M. S. 2005 Detection of temporal patterns in dog-human interaction. Behav. Processes 70, 69-79. (doi:10.1016/j.beproc.2005.04.006) (Pubitemid 40828305)
73. Kerepesi, A., Kubinyi, E., Jonsson, G. K., Magnusson, M. S. & Miklosi, A. 2006 Behavioural comparison of human-animal (dog) and human-robot (AIBO) interactions. Behav. Processes 73, 92-99. (doi:10.1016/j.beproc.2006.04. 001) (Pubitemid 43766282)
74. Kim, S. 2006 Player's positional dependence of fractal behaviors in a soccer game. Fractals-Complex Geom. Patterns Scaling Nat. Soc. 14, 71-76. (doi:10.1142/S0218348X06003003)
75. Kirkden, R. D. & Pajor, E. A. 2006 Using preference, motivation and aversion tests to ask scientific questions about animals' feelings. Appl. Anim. Behav. Sci. 100, 29-47. (doi:10.1016/j.applanim.2006.04.009)
76. Korte, S. M., Olivier, B. & Koolhaas, J. M. 2007 A new animal welfare concept based on allostasis. Physiol. Behav. 92, 422-428. (doi:10.1016/j. physbeh.2006.10.018)
77. Kramer, K. & Kinter, L. B. 2003 Evaluation and applications of radiotelemetry in small laboratory animals. Physiol. Genom. 13, 197-205. (doi:10.1152/physiolgenomics.00164.2002)
78. Krause, J., Croft, D. P. & James, R. 2007 Social network theory in the behavioural sciences: potential applications. Behav. Ecol. Sociobiol. 62, 15-27. (doi:10.1007/s00265-007-0445-8)
79. Kristensen, H. H., Aerts, J. M., Leroy, T., Wathes, C. M. & Berckmans, D. 2006 Modelling the dynamic activity of broiler chickens in response to step-wise changes in light intensity. Appl. Anim. Behav. Sci. 101, 125-143. (doi:10.1016/j.applanim.2006.01.007)
80. Krogh, A., Larsson, B., von Heijne, G. & Sonnhammer, E. L. L. 2001 Predicting transmembrane protein topology with a hidden Markov model: application to complete genomes. J. Mol. Biol. 305, 567-580. (doi:10.1006/jmbi.2000.4315)
81. Larget, B. & Simon, D. L. 1999 Markov chain Monte Carlo algorithms for the Bayesian analysis of phylogenetic trees. Mol. Biol. Evol. 16, 750-759.
82. Leonardi, R., Migliorati, P. & Prandini, M. 2004 Semantic indexing of soccer audio-visual sequences: a multimodal approach based on controlled Markov chains. IEEE Trans. Circuit. Syst. Video Technol. 14, 634-643. (doi:10.1109/TCSVT.2004.826751)
83. Lewis, M. H. 2004 Environmental complexity and central nervous system development and function. Mental Retard. Dev. Disabil. Res. Rev. 10, 91-95. (doi:10.1002/mrdd.20017)
84. Lo, C. C., Chou, T., Penzel, T., Scammell, T. E., Strecker, R. E., Stanley, H. E. & Ivanov, P. C. 2004 Common scale-invariant patterns of sleep-wake transitions across mammalian species. Proc. Natl Acad. Sci. USA 101, 17545-17548. (doi:10.1073/pnas.0408242101)
85. Lusseau, D. 2003 The emergent properties of a dolphin social network. Proc. R. Soc. Lond. B 270, S186-S188. (doi:10.1098/rsbl.2003.0057)
86. Lusseau, D. & Newman, M. E. J. 2004 Identifying the role that animals play in their social networks. Proc. R. Soc. Lond. B 271, 477-481. (doi:10.1098/rsbl.2004.0225)
87. Lyon,M. & Kemp, A. S. 2004 Increasedtemporalpatterns inchoice responding and altered cognitive processes in schizophrenia and mania. Psychopharmacology 172, 211-219.
88. Macy, M. W. & Willer, R. 2002 From factors to actors: computational sociology and agent-based modeling. Ann. Rev. Sociol. 28, 143-166. (doi:10.1146/annurev.soc.28.110601.141117)
89. Magnusson, M. S. 2000 Discovering hidden time patterns in behavior: T-patterns and their detection. Behav. Res. Methods Instrum. 32, 93-110.
90. Magnusson, M. S. 2004 Theme: powerful tool for the detection and analysis of hidden patterns in behavior. Reference Manual Version 5.0. Wageningen, The Netherlands: Noldus Information Technology.
91. Magnusson, M. S. 2005 Understanding social interaction: discovering hidden structure with model and algorithms. The hidden structure of interaction: from neurons to culture patterns (eds L. Anolli, S. J. Duncen, M. S. Magnusson & G. Riva). Amsterdam, The Netherlands: IOS Press.
92. Manno, T. G. 2008 Social networking in the Columbian ground squirrel, Spermophilus columbianus. Anim. Behav. 75, 1221-1228. (doi:10.1016/j.anbehav. 2007.09.025)
93. María, G. A., Escós, J. & Alados, C. L. 2004 Complexity of behavioural sequences and their relation to stress conditions in chickens (Gallus gallus domesticus): a non-invasive technique to evaluate animal welfare. Appl. Anim. Behav. Sci. 86, 93-104. (doi:10.1016/j.applanim.2003.11.012)
94. Martaresche, M., Le Fur, C., Magnusson, M. S., Faure, J. M. & Picard, M. 2000 Time structure of behaviour patterns realted to feed pecking in chicks. Physiol. Behav. 70, 443-451. (doi:10.1016/S0031-9384(00)00283-3)
95. Martin, P. & Bateson, P. 1993 Measuring behaviour: an introductory guide. New York, NY: Cambridge University Press.
96. Maynard-Smith, J. 1972 On evolution. Edinburgh, UK: Edinburgh University Press.
97. McBryde, E. S., Pettitt, A. N., Cooper, B. S. & McElwain, D. L. S. 2007 Characterizing an outbreak of vancomycinresistant Enterococci using hidden Markov models. J. R. Soc. Interface 4, 745-754. (doi:10.1098/rsif.2007.0224)
98. McCowan, B., Anderson, K., Heagarty, A. & Cameron, A. 2008 Utility of social network analysis for primate behavioral management and well-being. Appl. Anim. Behav. Sci. 109, 396-405. (doi:10.1016/j.applanim.2007.02.009)
99. McDonnell, S. M. & Poulin, A. 2002 Equid play ethogram. Appl. Anim. Behav. Sci. 78, 263-290. (doi:10.1016/S0168-1591(02)00112-0)
100. Merlet, F., Puterflam, J., Faure, J. M., Hocking, P. M., Magnusson, M. S. & Picard, M. 2005 Detection and comparison of time patterns of behaviours of two broiler breeder genotypes fed ad libitum and two levels of feed restriction. Appl. Anim. Behav. Sci. 94, 255-271. (doi:10.1016/j.applanim.2005. 02.014)
101. Miall, A. D. 1973 Markov chain analysis applied to an ancient alluvial plain succession. Sedimentology 20, 347-364. (doi:10.1111/j.1365-3091.1973. tb01615.x)
102. Miller, G. E., Chen, E. & Zhou, E. S. 2007 If it goes up, must it come down? Chronic stress and the hypothalamic- pituitary-adrenocortical axis in humans. Psychol. Bull. 133, 25-45. (doi:10.1037/0033-2909.133.1.25)
103. Minsky, M. L. 2006 The emotion machine: commonsense thinking, artificial intelligence, and the future of the human mind. New York, NY: Simon & Schuster.
104. Minta, S. C. 1992 Tests of spatial and temporal interaction among animals. Ecol. Appl. 2, 178-188. (doi:10.2307/1941774)
105. Moreno, J. L. 1934 Who shall survive? Foundations of sociometry, group psychotherapy and sociodrama. Washington, DC: Nervous and Mental Disease Publishing Co.
106. Mundry, R. & Sommer, C. 2007 Discriminant function analysis with non-independent data: consequences and an alternative. Anim. Behav. 74, 965-976. (doi:10.1016/j.anbehav.2006.12.028)
107. Nerkar, A. & Paruchuri, S. 2005 Evolution of R&D capabilities: the role of knowledge networks within a firm. Manage. Sci. 51, 771-785. (doi:10.1287/mnsc.1040.0354)
108. Onody, R. N. & de Castro, P. A. 2004 Complex network study of Brazilian soccer players. Phys. Rev. E 70, (doi:10.1103/PhysRevE.70.037103)
109. Pack, A. I. et al. 2007 Novel method for high-throughput phenotyping of sleep in mice. Physiol. Genom. 28, 232-238. (doi:10.1152/physiogenomics.00139. 2006)
110. Patin, G., Sighireanu, M. & Touili, T. 2007 Spade: verification of multithreaded dynamic and recursive programs. Lect. Notes Comput. Sci. 4590, 254. (doi:10.1007/978-3-540-73368-3-28)
111. Paulus, M. P. & Geyer, M. A. 1993 Quantitative assessment of microstructure of rat behavior. 1. F(D), the extension of the scaling hypothesis. Psychopharmacology 113, 177-186. (doi:10.1007/BF02245695)
112. Paulus, M. P., Bakshi, V. P. & Geyer, M. A. 1998 Isolation rearing affects sequential organization of motor behavior in post-pubertal but not pre-pubertal Lister and Sprague-Dawley rats. Behav. Brain Res. 94, 271-280. (doi:10.1016/S0166-4328(97)00158-7)
113. Pei, J., Han, J., Mortazavi-Asl, B., Pinto, H., Chen, Q., Dayal, U. & Hsu, M. C. 2001 PrefixSpan: mining sequential patterns efficiently by prefix-projected pattern. Data Eng. 17, 215-224. (Pubitemid 32457120)
114. Peng, C. K., Buldyrev, S. V., Havlin, S., Simons, M., Stanley, H. E. & Goldberger, A. L. 1994 Mosaic organization of DNA nucleotides. Phys. Rev. E 49, 1685-1689. (doi:10.1103/PhysRevE.49.1685)
115. Peng, C. K., Havlin, S., Hausdorff, J. M., Mietus, J. E., Stanley, H. E. & Goldberger, A. L. 1995a Fractal mechanisms and heart rate dynamics: long-range correlations and their breakdown with disease. J. Electrocardiol. 28, 59-65. (doi:10.1016/S0022-0736(95)80017-4) (Pubitemid 26044100)
116. Peng, C. K., Havlin, S., Stanley, H. E. & Goldberger, A. L. 1995b Quantification of scaling exponents and crossover phenomena in nonstationary heartbeat time-series. Chaos 5, 82-87. (doi:10.1063/1.166141)
117. Pickover, C. A. & Khorasani, A. 1986 Fractal characterization of speech wave-form graphs. Comput. Graph. 10, 51-61. (doi:10.1016/0097-8493(86) 90068-3)
118. Poisbleau, M., Jenouvrier, S. & Fritz, H. 2006 Assessing the reliability of dominance scores for assigning individual ranks in a hierarchy. Anim. Behav. 72, 835-842. (doi:10.1016/j.anbehav.2006.01.024)
119. Rands, S. A., Cowlishaw, G., Pettifor, R. A., Rowcliffe, J. M. & Johnstone, R. A. 2003 Spontaneous emergence of leaders and followers in foraging pairs. Nature 423, 432-434. (doi:10.1038/nature01630) (Pubitemid 36626993)
120. Reynolds, C. W. 1987 Flocks, herds and schools: a distributed behavioural model. Comput. Graph. 21, 25-34. (doi:10.1145/37402.37406)
121. Riley, M. A. & Turvey, M. T. 2002 Variability and determinism in motor behavior. J. Motor Behav. 34, 99-125.
122. Ruis, M. A.W., te Brake, J. H. A., Buwalda, B., De Boer, S. F., Meerlo, P., Korte, S. M., Blokhuis, H. J. & Koolhaas, J. M. 1999 Housing familiar male wildtype rats together reduces the long-term adverse behavioural and physiological effects of social defeat. Psychoneuroendocrinology 3, 285-300.
123. Ruis, M. A. W., te Brake, J. H. A., Engel, B., Buist, W. G., Blokhuis, H. J. & Koolhaas, J. M. 2001 Adaptation to social isolation: acute and long-term stress responses of growing gilts with different coping characteristics. Physiol. Behav. 73, 541-551. (doi:10.1016/S0031-9384(01)00548- 0)
124. Rutherford, K. M. D., Haskell, M. J.,Glasbey, C., Jones, R. B.& Lawrence, A. B. 2003 Detrended fluctuation analysis of behavioural responses to mild acute stressors in domestic hens. Appl. Anim. Behav. Sci. 83, 125-139. (doi:0.1016/s0168-1591(03)00115-1)
125. Rutherford, K. M. D., Haskell, M. J., Glasbey, C., Jones, R. B.& Lawrence, A. B. 2004 Fractal analysis of animal behaviour as an indicator of animal welfare. Anim.Welf. 13, S99-S103.
126. Rutherford, K. M. D., Haskell, M. J., Glasbey, C. & Lawrence, A. B. 2006 The responses of growing pigs to a chronicintermittent stress treatment. Physiol. Behav. 89, 670-680. (doi:10.1016/j.physbeh.2006.08.006)
127. Sade, D. S. 1972 Sociometrics of Macaca-mulatta: linkages and cliques in grooming matrices. Folia Primatol. 18, 196-223. (doi:10.1159/000155480)
128. Scheibe, K. M., Berger, A., Langbein, J., Streich, W. J. & Eichhorn, K. 1999 Comparative analysis of ultradian and circadian behavioural rhythms for diagnosis of biorhythmic state of animals. Biol. Rhythm Res. 30, 216-233. (doi:10.1076/brhm.30.2.216.1420)
129. Scott, J. 2000 Social network analysis: a handbook. London, UK: Sage.
130. Shibuichi, S., Onda, T., Satoh, N. &Tsujii, K. 1996 Super waterrepellent surfaces resulting from fractal structure. J. Phys. Chem. 100, 19512-19517. (doi:10.1021/jp9616728)
131. Slater, P. J. B. 1993 Describing sequences of behavior. In Perspectives in ethology: behavior and evolution, vol.10 (eds P. P. G. Bateson, P. H. Klopfer & N. S. Thompson), pp. 131-153. New York, NY: Springer.
132. Smith, T. G., Marks, W. B., Lange, G. D., Sheriff, W. H. & Neale, E. A. 1989 A fractal analysis of cell images. J. Neurosci. Methods 27, 173-180.
133. Spink, A. J., Tegelenbosch, R. A. J., Buma, M. O. S. & Noldus, L. 2001 The ethovision video tracking system: a tool for behavioral phenotyping of transgenic mice. Physiol. Behav. 73, 731-744. (doi:10.1016/S0031-9384(01)00530- 3)
134. Spinka, M., Newberry, R. C. & Bekoff, M. 2001 Mammalian play: training for the unexpected. Q. Rev. Biol. 76, 141-168. (doi:10.1086/393866)
135. Stricklin, W. R., Zhou, J. Z. & Gonyou, H. W. 1995 Selfish animats and robot ethology: using artificial animals to investigate social and spatial-behavior. Appl. Anim. Behav. Sci. 44, 187-203. (doi:10.1016/0168- 1591(95)00613-W)
136. Stricklin, W. R., de Bourcier, P., Zhou, J. Z. & Gonyou, H.W. 1998 Artificial pigs in space: using artificial intelligence and artificial life techniques to design animal housing. J. Anim. Sci. 76, 2609-2613.
137. Sugihara, G. & May, R. M. 1990 Applications of fractals in ecology. Trends Ecol. Evol. 5, 79-86. (doi:10.1016/0169-5347(90)90235-6)
138. Sumpter, D. J. T. 2006 The principles of collective animal behaviour. Phil. Trans. R. Soc. B 361, 5-22. (doi:10.1098/rstb.2005.1733)
139. Sundaresan, S. R., Fischhoff, I. R., Dushoff, J. & Rubenstein, D. I. 2007 Network metrics reveal differences in social organization between two fission-fusion species, Grevy's zebra and onager. Oecologia 151, 140-149. (doi:10.1007/s00442-006-0553-556)
140. Tavazoei, M. S. & Haeri, M. 2007 An optimization algorithm based on chaotic behavior and fractal nature. J. Comput. Appl. Math. 206, 1070-1081. (doi:10.1016/j.cam.2006.09.008)
141. Tong, A. H. Y. et al. 2004 Global mapping of the yeast genetic interaction network. Science 303, 808-813. (doi:10.1126/science.1091317)
142. Troscianko, T., Holmes, A., Stillman, J., Mirmehdi, M., Wright, D. & Wilson, A. 2004 What happens next? The predictability of natural behaviour viewed through CCTV cameras. Perception 33, 87-101. (doi:10.1068/p3402) (Pubitemid 38389683)
143. Uchino, B. N., Cacioppo, J. T. & Kiecolt-Glaser, J. K. 1996 The relationship between social support and physiological processes: a review with emphasis on underlying mechanisms and implications for health. Psychol. Bull. 119, 488-531. (doi:10.1037/0033-2909.119.3.488)
144. Valdez, M. P. & Young, K. C. 1985 Number fluxes in equilibrium raindrop populations: a Markov-chain analysis. J. Atmos. Sci. 42, 1024-1036. (doi:10.1175/1520-0469(1985)042,1024:NFIERP.2.0.CO;2)
145. Vernon, M. C. & Keeling, M. J. 2009 Representing the UK's cattle herd as static and dynamic networks. Proc. R. Soc. B 276, 469-476. (doi:10.1098/rspb.2008.1009)
146. Vicsek, T. 2000 Complexity: the bigger picture. Nature 418, 131. (doi:10.1038/418131a)
147. Visser, E. K., van Reenen, C. G., van derWerf, J. T., Schilder, M. B., Knaap, J. H., Barneveld, A. & Blokhuis, H. J. 2002 Heart rate and heart rate variability during a novel object test and a handling test in young horses. Physiol. Behav. 76, 289-296. (doi:10.1016/S0031-9384(02)00698-4)
148. Wasserman, S. & Faust, K. 1994 Structural analysis in the social sciences. In Social network analysis. Cambridge, UK: Cambridge University Press.
149. Watts, D. J. & Strogatz, S. H. 1998 Collective dynamics of 'small-world' networks. Nature 393, 440-442. (doi:10.1038/30918)
150. Watts, J. M. 1998 Animats: computer-simulated animals in behavioral research. J. Anim. Sci. 76, 2596-2604.
151. Wechsler, B. & Bachmann, I. 1998 A sequential analysis of eliminative behaviour in domestic pigs. Appl. Anim. Behav. Sci. 56, 29-36. (doi:10.1016/S0168-1591(97)00075-0)
152. Wey, T., Blumstein, D. T., Shen, W. & Jordan, F. 2008 Social network analysis of animal behaviour: a promising tool for the study of sociality. Anim. Behav. 75, 333-344. (doi:10.1016/j.anbehav.2007.06.020)
153. White, D. J. & Smith, V. A. 2007 Testing measures of animal social association by computer simulation. Behaviour 144, 1447-1468. (doi:10.1163/156853907782418259)
154. Wiepkema, P. R. & Koolhaas, J. M. 1993 Stress animal welfare. Anim. Welf. 2, 195-218.
155. Williams, R. & Lusseau, D. 2006 A killer whale social network is vulnerable to targeted removals. Biol. Lett. 2, 497-500. (doi:10.1098/rsbl.2006. 0510)
156. Wingfield, J. C. 2005 The concept of allostasis: coping with a capricious environment. J. Mammal. 86, 248-254. (doi:10.1644/BHE-004.1)
157. Wolf, J. B. W., Mawdsley, D., Trillmich, F. & James, R. 2007 Social structure in a colonial mammal: unravelling hidden structural layers and their foundations by network analysis. Anim. Behav. 74, 1293-1302. (doi:10.1016/j.anbehav.2007.02.024)
158. Yamamoto, Y. & Hughson, R. L. 1991 Coarse-graining spectral-analysis: new method for studying heart-rate-variability. J. Appl. Physiol. 71, 1143-1150.
159. Yang, Y., Atkinson, P. & Ettema, D. 2008 Individual spacetime activity-based modelling of infectious disease transmission within a city. J. R. Soc. Interface 5, 759-772. (doi:10.1098/rsif.2007.1218)
160. Yeates, J. W. & Main, D. C. J. 2008 Assessment of positive welfare: a review. Vet. J. 175, 293-300. (doi:10.1016/j.tvjl.2007.05.009)
161. Yin, G. & Zhang, Q. 2005 Discrete-time Markov chains: two-time-scale methods and applications. New York, NY: Springer.
162. Young, K. C. 1994 A multivariate chain model for simulating climatic parameters from daily data. J. Appl. Meteorol. 33, 661-671. (doi:10.1175/1520- 0450(1994)033,0661:AMCMFS.2.0.CO;2)
163. Zhang, B., Park, B. H., Karpinets, T. & Samatova, N. F. 2008 From pull-down data to protein interaction networks and complexes with biological relevance. Bioinformatics 24, 979-986. (doi:10.1093/bioinformatics/btn036)