Analysis of capture-recapture data

Analysis of Capture-Recapture Data

Volumn , Issue , 2014, Pages 1-279

  McCrea, Rachel S ^a   Morgan, Byron J T ^a  

^a UNIVERSITY OF KENT   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 85053497784     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1201/b17222     Document Type: Book

References (464)

1. Abadi, F., O. Gimenez, R. Arlettaz and M. Schaub (2012), Estimating the strength of density-dependence in the presence of observation errors using integrated population models. Ecological Modelling 242, 1–9.
2. Aebischer, N. J. (1983), Restoring the legibility of the inscriptions on abraded or corroded bird-rings. Ringing & Migration 4, 275–280.
3. Aebischer, N. J. (1986), Retrospective investigation of an ecological disaster in the shag, Phalacrocorax-aristotellis-a general-method based on long-term marking. Journal of Animal Ecology 55(2), 613–629.
4. Aebischer, N. J. (1999), Multi-way comparisons and generalised linear models of nest success: extensions of the Mayfield method. Bird Study 46 (suppl), 22–31.
5. Alho, J. M. (1990), Logistic regression in capture-recapture models. Biometrics 46, 623–635.
6. Amstrup, S. C., T. L. McDonald and B. F. J. Manly (2005), Handbook of capture-recapture analysis. Princeton University Press, Princeton.
7. Anderson, D. R. and K. P. Burnham (1976), Population ecology of the mallard. VI. The effect of exploitation on survival., vol. 128. US Fisheries Wildlife Services Resource Publication
8. Arnason, A. N. (1972), Parameter estimates from mark-recapture-recovery experiments on two populations subject to migration and death. Researches on Population Ecology 13, 97–113
9. Arnason, A. N. (1973), The estimation of population size, migration rates, and survival in a stratified population. Researches on Population Ecology 15, 1–6
10. Arnason, A. N. and C. J. Schwarz (2002), POPAN-6: exploring convergence and estimate properties with SIMULATE. Journal of Applied Statistics 29, 649–668
11. Arnold, R., Y. Hayakawa and P. Yip (2010), Capture-recapture estimation using finite mixtures of arbitrary dimension. Biometrics 66, 644–655
12. Ashbridge, J. and I. B. J. Goudie (2000), Robust estimators for mark-recapture in heterogeneous populations. Communications in Statistics– Simulation and Computation 29, 1215–1237
13. Asher, J., M. Warren, R. Fox, P. Harding, G. Jeffcoate and S. Jeffcoate (2001), The Millennium Atlas of Butterflies in Britain and Ireland. Oxford University Press
14. Bailey, L. L., S. J. Converse and W. K. Kendall (2010), Bias, precision, and parameter redundancy in complex multistate models with unobservable states. Ecology 91, 1598–1604
15. Bailey, L. L., J. E. Hines, J. D. Nichols and D. I. MacKenzie (2007), Sampling design trade-offs in occupancy studies with imperfect detection: examples and software. Ecological Applications 17, 281–290
16. Bailey, L. L., D. I. MacKenzie and J. D. Nichols (2014), Advances and applications of occupancy models. Methods in Ecology and Evolution, DOI: 10.1111/2041-210X.12100
17. Baillargeon, S. and L.-P. Rivest (2007), Rcapture: Loglinear models for capture-recapture in R. Journal of Statistical Software 19
18. Balmer, D., L. Coiffait, J. Clark and R. Robinson (2008), Bird Ringing. The British Trust for Ornithology, The Nunnery, Thetford, Norfolk, IP24 2PU
19. Barbraud, C. and H. Weimerskirch (2012), Estimating survival and reproduction in a quasi-biennially breeding seabird with uncertain and unobservable states. Journal of Ornithology 152, S605–S615
20. Barker, R. J. (1997), Joint modelling of live recapture, tag-resight and tag-recovery data. Biometrics 53, 666–677
21. Barker, R. J. (1999), Joint analysis of mark-recapture, resighting and ring-recovery data with age-dependence and marking-effect. Bird Study 46 (suppl), 82–91
22. Barker, R. J. and L. Kavalieris (2001), Efficiency gain from auxiliary data requiring additional nuisance parameters. Biometrics 57, 563–566
23. Barker, R. J. and W. A. Link (2013), Bayesian multimodel inference by RJMCMC: a Gibbs sampling approach. The American Statistician 67, 150–156
24. Barnston, A. and R. Livezey (1987), Classification, seasonality and persistence of low-frequency atmospheric circulation patterns. Monthly Weather Review 115, 1083–1126
25. Barry, J., S. Boyd and R. Fryer (2010), Modelling the effects of marine aggregate extraction on benthic assemblages. Journal of the Marine Biological Association of the UK 90, 105–114
26. Barry, S. C., S. P. Brooks, E. A. Catchpole and B. J. T. Morgan (2003), The analysis of ring-recovery data using random effects. Biometrics 59, 54–65
27. Bekker, P., A. Merchens and T. J. Wansbeek (1994), Identification, Equivalent Models and Computer Algebra. Academic Press, Boston
28. Bellman, R. and K. J. Åström (1970), On structural identifiability. Mathematical Biosciences 7, 329–339
29. Bengtsson, T. and J. E. Cavanaugh (2006), An improved Akaike information criterion for state-space model selection. Computational Statistics and Data Analysis 50, 2635–2654
30. Besbeas, P., R. S. Borysiewicz and B. J. T. Morgan (2009), Completing the ecological jigsaw. Environmental and Ecological Statistics 3, 513– 539
31. Besbeas, P., S. N. Freeman and B. J. T. Morgan (2005), The potential of integrated population modelling. Australian and New Zealand Journal of Statistics 47, 35–48
32. Besbeas, P., S. N. Freeman, B. J. T. Morgan and E. A. Catchpole (2002), Integrating mark-recapture-recovery and census data to estimate animal abundance and demographic parameters. Biometrics 58, 540–547
33. Besbeas, P., J.-D. Lebreton and B. J. T. Morgan (2003), The efficient integration of abundance and demographic data. Journal of the Royal Statistical Society, Series C 52, 95–102
34. Besbeas, P. and B. J. T. Morgan (2012a), Kalman filter initialisation for integrated population modelling. Journal of the Royal Statistical Society, Series C 61, 151–162
35. Besbeas, P. and B. J. T. Morgan (2012b), A threshold model for heron productivity. Journal of Agricultural, Biological and Environmental Statistics 17, 128–141
36. Besbeas, P. T. and S. N. Freeman (2006), Methods for joint inference from panel survey and demographic data. Ecology 87, 1138–1145
37. Besbeas, P. T., R. S. McCrea and B. J. T. Morgan (2014), Integrated population model selection in ecology (In prep)
38. Besbeas, P. T. and B. J. T. Morgan (2014), Goodness of fit of integrated population models using calibrated simulation. Methods in Ecology and Evoluton (In Revision)
39. Bishop, Y. M. M., S. E. Fienberg and P. W. Holland (1975), Discrete Multivariate Analysis: Theory and Practice. MIT Press, Cambridge, MA, USA
40. Bled, F., J. A. Royle and E. Cam (2011), Hierarchical modeling of an invasive spread: the Eurasian Collared-Dove Streptopelia decaocto in the United States. Ecological applications 21, 290–302
41. Bloor, M. (2005), Population estimation without censuses or surveys: a discussion of mark-recapture methods illustrated by results from three studies. Sociology 39, 121–138
42. Böhning, D. (2007), A simple variance formula for population size estimators by conditioning. Statistical Methodology 5, 410–423
43. Böhning, D. (2008), Editorial: recent developments in capture-recapture methods and their applications. Biometrical Journal 50, 954–956
44. Böhning, D. (2010), Some general comparative points on Chao’s and Zelterman’s estimators of the population size. Scandinavian Journal of Statistics 37, 221–236
45. Böhning, D., M. Baksh, R. Lerdsuwansri and J. Gallagher (2013), Use of the ratio-plot in capture-recapture estimation. Journal of Computational and Graphical Statistics 22, 133–155
46. Bonnabel, S., P. Martin and E. Salaun (2009), Invariant extended Kalman filter: theory and application to a velocity-aided attitude estimation problem. IEEE Conference on Decision and Control, Shanghai
47. Bonner, S. J. (2012), Implementing the trinomial mark-recapture-recovery model in Program MARK. Methods in Ecology and Evolution 4, 95–98
48. Bonner, S. J., B. J. T. Morgan and R. King (2010), Continuous covariates in mark-recapture-recovery analysis: A comparison of methods. Biometrics 66, 1256–1265
49. Bonner, S. J. and M. R. Schofield (2014), MC(MC)MC: exploring Monte Carlo integration within MCMC for mark-recapture models with individual covariates. Methods in Ecology and Evolution, DOI: 10.1111/2041-210X.12095
50. Bonner, S. J. and C. J. Schwarz (2006), An extension of the Cormack-Jolly-Seber model for continuous covariates with application to Microtus penn-sylvanicus. Biometrics 62, 142–149
51. Bonner, S. J. and C. J. Schwarz (2011), Smoothing population size estimates for time-stratified mark-recapture experiments using Bayesian P-splines. Biometrics 67, 1498–1507
52. Bonner, S. J., D. Thomson and C. J. Schwarz (2009), Time-varying covariates and semi-parametric regression in capture-recapture: an adaptive spline approach. Environmental and Ecological Statistics 3, 657–676
53. Borchers, D. L. (2012), A non-technical overview of spatially explicit capture-recapture models. Journal of Ornithology 152, S435–S444
54. Borchers, D. L., S. T. Buckland and W. Zucchini (2002), Estimating Animal Abundance, Closed Populations. Springer, London
55. Borchers, D. L. and M. G. Efford (2008), Spatially explicit maximum likelihood methods for capture-recapture studies. Biometrics 64, 377–385
56. Borchers, D. L., B. C. Stevenson, D. Kidney, L. J. Thomas and T. A. Marques (2014), A unifying model for capture-recapture and distance sampling. Journal of the American Statistical Association, To appear
57. Bosschieter, L., P. W. Goedhart, R. P. B. Foppen and C. C. Vos (2010), Modelling small-scale dispersal of the Great Reed Warbler, Acrocephalus arundinaceus in a fragmented landscape. Ardea 98, 383–394
58. Box, G. E. P. and G. M. Jenkins (1976), Time Series Analysis: Forecasting and Control. Holden-Day: San Francisco
59. Brooks, S. P., E. A. Catchpole and B. J. T. Morgan (2000a), Bayesian animal survival estimation. Statistical Science, 15, 357–376
60. Brooks, S. P., E. A. Catchpole, B. J. T. Morgan and S. C. Barry (2000b), On the Bayesian analysis of ring-recovery data. Biometrics 56, 951–956
61. Brooks, S. P., N. Friel and R. King (2003), Classical model selection via simulated annealing. Journal of Royal Statistical Society, Series B 65, 503–520
62. Brooks, S. P. and A. Gelman (1998), Alternative methods for monitoring convergence of iterative simulations. Journal of Computational and Graphical Statistics 7, 434–455
63. Brooks, S. P. and P. Giudici (2000), MCMC convergence assessment via two-way ANOVA. Journal of Computational and Graphical Statistics 9, 434–455
64. Brooks, S. P., R. King and B. J. T. Morgan (2004), A Bayesian approach to combining animal abundance and demographic data. Animal Biodiversity and Conservation 27, 515–529
65. Brooks, S. P., B. J. T. Morgan, M. S. Ridout and S. E. Pack (1997), Finite mixture models for proportions. Biometrics 53, 1097–1115
66. Brown, D. I. (2010), Climate modelling for animal survival. Ph.D. thesis, University of Kent
67. Brownie, C., D. R. Anderson, K. P. Burnham and D. S. Robson (1985), Statistical Inference from Band-Recovery Data – A Handbook. United States Department of the Interior, Fish and Wildlife Service
68. Brownie, C., J. E. Hines, J. D. Nichols, K. Pollock and J. B. Hestbeck (1993), Capture-recapture studies for multiple strata including non-Markovian transitions. Biometrics 49, 1173–1187
69. Buckland, S. T., D. R. Anderson, K. P. Burnham, J. L. Laake, D. L. Borchers and L. Thomas (2001), Introduction to Distance Sampling. Oxford University Press, Oxford
70. Buckland, S. T., K. P. Burnham and N. H. Augustin (1997), Model selection: an integral part of inference. Biometrics 53, 603–618
71. Buckland, S. T., K. B. Newman, C. Fernández, L. Thomas and J. Harwood (2007), Embedding population dynamics models in inference. Statistical Science 22, 44–58
72. Buckland, S. T., K. B. Newman, L. Thomas and N. B. Koesters (2004), State-space models for the dynamics of wild animal populations. Ecological Modelling 171, 157–175
73. Buoro, M., E. Prévost and O. Gimenez (2010), Investigating evolutionary trade-offs in wild populations of Atlantic salmon Salmo salar: incorporating detection probabilities and individual heterogeneity. Evolution 64, 2629–2642
74. Burnham, K. P. (1990), Survival analysis of recovery data from birds ringed as young: efficiency of analyses when the numbers ringed are not known. The Ring 13, 115–132
75. Burnham, K. P. (1991), On a unified theory for release-resampling of animal populations. In 1990 Taipei Symposium in Statistics., pp. 11–36, Institute of Statistical Science, Academia Sinica
76. Burnham, K. P. (1993), A theory for combined analysis of ring-recovery and recapture data. In J.-D. Lebreton and P. M. North (eds.), Marked Individuals in the Study of Bird Populations, pp. 199–213, Birkhäuser Verlag, Basel
77. Burnham, K. P. and D. R. Anderson (2002), Model Selection and Multimodel Inference. Springer, second edn.
78. Burnham, K. P., D. R. Anderson, G. C. White, C. Brownie and K. H. Pollock (1987), Design and analysis methods for fish survival experiments based on release-recapture. American Fisheries Society, Monograph 5, Bethesda, Maryland
79. Burnham, K. P. and W. S. Overton (1978), Estimation of the size of a closed population when capture probabilities vary among animals. Biometrika 65, 625–633
80. Burnham, K. P. and E. A. Rexstad (1993), Modeling heterogeneity in survival rates of banded waterfowl. Biometrics 49, 1194–1208
81. Burnham, K. P. and G. C. White (2002), Evaluation of some random effects methodology applicable to bird ringing data. Journal of Applied Statistics, 29, 245–264
82. Cam, E. (2012), Random effects models as means of borrowing strength in survival studies of wild vertebrates. Animal Conservation 15, 129–132
83. Cam, E., W. A. Link, E. G. Cooch, J. Monnat and E. Danchin (2002), Individual covariation in life-history traits: seeing the trees despite the forest. American Naturalist 159, 96–105
84. Carroll, R. J. and F. Lombard (1985), A note on N estimators for the binomial distribution. Journal of the American Statistical Association 80, 423–426
85. Carroll, R. J., L. A. Stefanski, D. Rupert and C. Crainiceanu (2006), Measurement Error in Nonlinear Models. Chapman & Hall/CRC Press, Boca Raton, second edn.
86. Caswell, H. (2001), Matrix Population Models, 2nd edition. Sinauer, Sunderland, Massachusetts
87. Catchpole, E. A. (1995), MATLAB: an environment for analysing ring-recovery and recapture data. Journal of Applied Statistics 22, 801–816
88. Catchpole, E. A., Y. Fan, B. J. T. Morgan, T. Clutton-Brock and T. Coulson (2004a), Sexual dimorphism, survival and dispersal in red deer. Journal of Agricultural, Biological and Environmental Statistics 9, 1–26
89. Catchpole, E. A., S. N. Freeman and B. J. T. Morgan (1993), On boundary estimation in ring recovery models and the effect of adding recapture information. In J.-D. Lebreton and P. M. North (eds.), Marked Individuals in the Study of Bird Populations, pp. 215–228, Birkhäuser Verlag, Basel
90. Catchpole, E. A., S. N. Freeman and B. J. T. Morgan (1996), Steps to parameter redundancy in age-dependent recovery models. Journal of the Royal Statistical Society, Series B 58, 763–774
91. Catchpole, E. A., S. N. Freeman and B. J. T. Morgan (1998a), Estimation in parameter-redundant models. Biometrika 85, 462–468
92. Catchpole, E. A., S. N. Freeman, B. J. T. Morgan and M. P. Harris (1998b), Integrated recovery/recapture data analysis. Biometrics 54, 33– 46
93. Catchpole, E. A., S. N. Freeman, B. J. T. Morgan and W. J. Nash (2001a), Abalone I: Analyzing mark-recapture-recovery data incorporating growth and delayed recovery. Biometrics 57, 469–477
94. Catchpole, E. A., P. M. Kgosi and B. J. T. Morgan (2001b), On the near-singularity of models for animal recovery data. Biometrics 57, 720–726
95. Catchpole, E. A. and B. J. T. Morgan (1991), A note on Seber’s model for ring-recovery data. Biometrika 78, 917–919
96. Catchpole, E. A. and B. J. T. Morgan (1994), Boundary estimation in ring recovery models. Journal of the Royal Statistical Society, Series B 56, 385–391
97. Catchpole, E. A. and B. J. T. Morgan (1996), Model selection in ring recovery models using score tests. Biometrics 52, 664–672
98. Catchpole, E. A. and B. J. T. Morgan (1997), Detecting parameter redundancy. Biometrika 84, 187–196
99. Catchpole, E. A. and B. J. T. Morgan (2001), Deficiency of parameter-redundant models. Biometrika 88, 593–598
100. Catchpole, E. A., B. J. T. Morgan and T. Coulson (2004b), Conditional methodology for individual case history data. Journal of the Royal Statistical Society, Series C 53, 1–9
101. Catchpole, E. A., B. J. T. Morgan, T. N. Coulson, S. N. Freeman and S. D. Albon (2000), Factors influencing Soay sheep survival. Journal of the Royal Statistical Socety, Series C 49, 453–472
102. Catchpole, E. A., B. J. T. Morgan, S. N. Freeman and W. J. Peach (1999), Modelling the survival of British lapwings Vanellus vanellus using weather covariates. Bird Study (suppl) 46, 5–13
103. Catchpole, E. A., B. J. T. Morgan and G. Tavecchia (2008), A new method for analysing discrete life-history data with missing covariate values. Journal of the Royal Statistical Society, Series B 70, 445–460
104. Catchpole, E. A., B. J. T. Morgan and A. Viallefont (2002), Solving problems in parameter redundancy using computer algebra. Journal of Applied Statistics 29, 625–636
105. Chandler, R. and J. Clark (2014), Spatially explicit integrated population models. Methods in Ecology and Evolution, DOI: 10.1111/2041-210X.12153
106. Chao, A. (1987), Estimating the population size for capture-recapture data with unequal catchability. Biometrics 43, 783–791
107. Chao, A. (2001), An overview of closed capture-recapture models. Journal of Agricultural, Biological and Environmental Statistics 6, 158–175
108. Chao, A., H. Y. Pan and S. C. Chiang (2008), The Petersen-Lincoln estimator and its extension to estimate the size of a shared population. Biometrical Journal 50, 957–70
109. Chao, A., P. Tsay, S. Lin, W. Shau and D. Chao (2001), Tutorial in Bio-statistics: The applications of capture-recapture models to epidemiological data. Statistics in Medicine 20, 2123–3157
110. Chao, A., C. W. and C. H. Hsu (2000), Capture-recapture when time and behavioural response affect capture probabilities. Biometrics 56, 427– 433
111. Chapman, D. H. (1951), Some properties of the hypergeometric distribution with applications to zoological surveys. University of California Publications in Statistics 1, 131–160
112. Chappell, M. J. and R. N. Gunn (1998), A procedure for generating locally identifiable reparameterisations of unidentifiable non-linear systems by the similarity transformation approach. Mathematical Biosciences 148, 21–41
113. Chatfield, C. (1995), Model uncertainty, data mining and statistical inference (with discussion). Journal of the Royal Statistical Society, Series A 158, 419–466
114. Choquet, R. and D. J. Cole (2012), A hybrid symbolic-numerical method for determinig model structure. Mathematical Biosciences 236, 117–125
115. Choquet, R. and O. Gimenez (2012), Towards built-in capture-recapture mixed models in program E-SURGE. J. Ornithology 152, 625–639
116. Choquet, R., A.-M. Reboulet, R. Pradel, O. Gimenez and J.-D. Lebreton (2004), M-SURGE — New software for multistate recapture models. Animal Biodiversity and Conservation 27, 207–215
117. Choquet, R., A. M. Reboulet, R. Pradel, O. Gimenez and J.-D. Lebreton (2005), User’s manual for U-Care. Mimeographed document. CEFE/CNRS, Montpellier, France.
118. Choquet, R., L. Rouan and R. Pradel (2009), Program E-SURGE: a software application for fitting Multievent models. Environmental and Ecological Statistics 3, 845–865
119. Clark, J. S., G. Ferraz, N. Oguge, H. Hays and J. Dicostanzo (2005), Hierarchical Bayes for structured, variable populations: from recapture data to life-history prediction. Ecology 86, 2232–2244
120. Clobert, J. and J.-D. Lebreton (1985), Dépendance de facteurs de milieu dans les estimations de taux de survie par capture-recapture. Biometrics 41, 1031–1037
121. Clutton-Brock, T. and B. C. Sheldon (2010), Individuals and populations: the role of long-term, individual-based studies of animals in ecology and evolutionary biology. Trends in Ecology and Evolution 25, 573–582
122. Clutton-Brock, T. H. (1988), Reproductive Success: studies of individual variation in contrasting breeding systems. Chicago University Press, Chicago
123. Clutton-Brock, T. H. and S. D. Albon (1989), Red Deer in the Highlands. BSP Professional Books, Oxford
124. Clutton-Brock, T. H., F. E. Guinness and S. D. Albon (1982), Red Deer: Behaviour and Ecology of Two Sexes. Chicago University Press, Chicago
125. Colchero, F. and J. Clark (2012), Bayesian inference on age-specific survival for censored and truncated data. Journal of Animal Ecology 81, 139–149
126. Cole, D. J. (2012), Determining parameter redundancy of multi-state mark-recapture models for sea birds. Journal of Ornithology 152, 305–315
127. Cole, D. J., R. Choquet, O. Gimenez, R. S. McCrea, B. J. T. Morgan and R. Pradel (2014), Does your (study) species have memory? Analysing capture-recapture data with memory models. Ecology and Evolution, DOI: 10.1002/ece3.1037
128. Cole, D. J. and R. S. McCrea (2014), Parameter redundancy in discrete state-space and integrated models. University of Kent Technical Report: UKC/SMSAS/12/012
129. Cole, D. J. and B. J. T. Morgan (2010a), A note on determining parameter redundancy in age-dependent tag return models for estimating fishing mortality, natural mortality and selectivity. Journal of Agricultural Biological and Environmental Statistics 15, 431–434
130. Cole, D. J. and B. J. T. Morgan (2010b), Parameter redundancy with covariates. Biometrika 97, 1002–1005
131. Cole, D. J., B. J. T. Morgan, E. A. Catchpole and B. A. Hubbard (2012), Parameter redundancy in mark-reovery models. Biometrical Journal 54, 507–523
132. Cole, D. J., B. J. T. Morgan and D. M. Titterington (2010), The parametric structure of models. Mathematical Biosciences 228, 16–30
133. Conn, P. and E. Cooch (2009), Multistate capture-recapture analysis under imperfect state observation: an application to disease models. Journal of Applied Ecology 46, 486–492
134. Cooch, E. and G. C. White (2010), Program Mark: A gentle introduction. www.phidot.org
135. Cooch, E. G., P. B. Conn, S. P. Ellner, A. P. Dobson and K. H. Pollock (2012), Disease dynamics in wild populations: modelling and estimation: a review. Journal of Ornithology 152, S485–S509
136. Corless, R. M. and D. J. Jeffrey (1997), The Turing factorization of a rectangular matrix. SIGSAM Bulletin 31, 20–28
137. Cormack, R. M. (1964), Estimates of survival from sightings of marked animals. Biometrika 51, 429–438
138. Cormack, R. M. (1970), Statistical appendix to Fordham’s paper. Journal of Animal Ecology 39, 24–27
139. Cormack, R. M. (1979), Sampling Biological Populations: Models for capture-recapture, pp. 217–55. Fairland: International Co-operative Publishing House
140. Cormack, R. M. (1989), Log-linear models for capture-recapture. Biometrics 45, 395–413
141. Cormack, R. M. (1992), Interval estimation for mark-recapture studies of closed populations. Biometrics 48, 567–576
142. Cormack, R. M. (2000), George Jolly–Obituary. Biometrics 56, 128
143. Cormack, R. M. and P. E. Jupp (1991), Inference for Poisson and multinomial models for capture-recapture experiments. Biometrika 78, 911–916
144. Coull, B. and A. Agresti (1999), The use of mixed logit models to reflect heterogeneity in capture-recapture studies. Biometrics 55, 294–301
145. Cowen, L. L., P. T. Besbeas, B. J. T. Morgan and C. J. Schwarz (2013), A comparison of abundance estimates from extended batch-marking and Jolly-Seber type experiments. Ecology and Evolution (DOI-10.1002/ece3.899)
146. Cox, D. R. and H. D. Miller (1965), The Theory of Stochastic Processes. Chapman & Hall, London
147. Cox, D. R. and D. Oakes (1984), Analysis of Survival Data. Chapman & Hall, London
148. Craig, C. C. (1953), On the utilization of marked specimens in estimating populations of flying insects. Biometrika 40, 170–176
149. Crosbie, S. F. and B. F. J. Manly (1985), Parsimonious modelling of capture-mark-recapture studies. Biometrics 41, 385–398
150. Cruyff, M. J. L. F. and P. G. M. van der Heijden (2008), Point and interval estimation of the population size using a zero-truncated negative binomial regression model. Biometrical Journal 50, 1035–1050
151. Cubaynes, S., R. Pradel, R. Choquet, C. Duchamp, J. M. Gaillard, E. Marboutin, C. Miquel, A. M. Reboulet, C. Poillot, P. Taberlet and O. Gimenez (2010), Importance of accounting for detection heterogeneity when estimating abundance: the case of the French wolves. Conservation Biology 24, 621–626
152. Dail, D. and L. Madsen (2011), Models for estimating abundance from repeated counts of an open meta population. Biometrics 67, 577–587
153. Darroch, J. N. (1958), The multiple-recapture census. I Estimation of a closed population. Biometrika 45, 343–359
154. Davison, A. C. (2003), Statistical Models. Cambridge University Press, Cambridge
155. Dawson, D. and M. Efford (2009), Bird population density estimated from acoustic signals. Journal of Applied Ecology 46, 1201–1209
156. de Valpine, P. (2004), Monte Carlo state-space liklelihoods by weighted posterior kernel density estimation. Journal of the American Statistical Association 99, 523–536
157. de Valpine, P. (2008), Improved estimation of normalizing constants from Markov chain Monte Carlo output. Journal of Computational and Graphical Statistics 17, 335–351
158. de Valpine, P. (2012), Frequentist analysis of hierarchical models for population dynamics and demographic data. Journal of Ornithology 152(Supplement 2), S393–S408
159. de Valpine, P. and R. Hilbourn (2005), State-space likelihoods for nonlinear fisheries time-series. Canadian Journal of Fisheries and Aquatic Science 62, 1937–1952
160. Dennis, B., J. M. Ponciano, S. R. Lele, M. L. Taper and D. F. Staples (2006), Estimating density dependence, process noise and observation error. Ecological Monographs 76, 323–341
161. Dennis, B., J. M. Ponciano and M. L. Taper (2010), Replicated sampling increases efficiency in monitoring biological populations. Ecology 91(2), 610–620
162. Dennis, E. B., B. J. T. Morgan and M. S. Ridout (2014), Computational aspects of N-mixture models. Biometrics (In Revision)
163. Desprez, M., R. Pradel, E. Cam, J.-Y. Monnat and O. Gimenez (2011), Now you see him, now you don’t: experience, not age, is related to reproduction in kittiwakes. Proceedings of the Royal Society B 278, 3060–3066
164. Dorazio, R. M., H. L. Jelks and F. Jordan (2005), Improving removal-based estimates of abundance by sampling a population of spatially distinct subpopulations. Biometrics 61, 1093–1101
165. Dorazio, R. M. and J. A. Royle (2003), Mixture models for estimating the size of a closed population when capture rates vary among individuals. Biometrics 59, 351–364
166. Dorazio, R. M. and J. A. Royle (2005), Rejoinder to “The performance of mixture models in heterogeneous closed populations”. Biometrics 61, 874–876
167. Dupuis, J. and C. Schwarz (2007), A Bayesian approach to the multistate Jolly-Seber capture-recapture model. Biometrics 63, 1015–1022
168. Dupuis, J. A. (1995), Bayesian estimation of movement and survival probabilities from capture-recapture data. Biometrika 82, 761–772
169. Durbin, J. and S. Koopman (2001), Time Series Analysis by State Space Methods. Oxford University Press, Oxford
170. Efford, M. G. and D. K. Dawson (2012), Occupancy in continuous habitats. Ecosphere 3(4), 32
171. Efford, M. G., D. K. Dawson and D. L. Borchers (2009), Population density estimated from locations of individuals on a passive detector array. Ecology 90, 2676–2682
172. Efford, M. G., D. K. Dawson and C. S. Robbins (2004), DENSITY: software for analysing capture-recapture data from passive detector arrays. Animal Biodiversity and Conservation 27, 217–228
173. Efford, M. G., B. Warburton, M. C. Coleman and R. J. Barker (2005), A field test of two methods for density estimation. Wildlife Society Bulletin 33, 731–738
174. Eubank, R. L. and S. Wang (2002), The equivalence between the Cholesky decomposition and the Kalman filter. The American Statistician 56, 39– 43
175. Evans, M. A., D. G. Bonett and L. L. McDonald (1994), A general-theory for modelling capture-recapture data from a closed population. Biometrics 50, 396–405
176. Evans, N. D. and M. J. Chappell (2000), Extensions to a procedure for generating locally identifiable reparametrisations of unidentifiable systems. Mathematical Biosciences 168, 137–159
177. Fewster, R. M. and P. E. Jupp (2009), Inference on population size in bino mial detectability models. Biometrika 96, 805–820
178. Fewster, R. M. and P. E. Jupp (2013), Information on parameters of interest decreases under transformations. Journal of Multivariate Analysis 120, 34–39
179. k contingency tables. Biometrika 59, 591–603
180. Fisher, R. A., A. S. Corbet and C. B. Williams (1943), The relation between the number of species and the number of individuals in a random sample of an animal population. Journal of Animal Ecology 12, 42–58
181. Fiske, I. and R. B. Chandler (2011), unmarked: An R package for fitting hierarchical models of wildlife occurrence and abundance. Journal of Statistical Software 43, 1–23
182. Foster, S. D., H. Shimadzu and R. Darnell (2012), Uncertainty in spatially predicted covariates: is it ignorable? Journal of the Royal Statistical Society, Series C 61, 637–652
183. Fournier, D. and C. P. Archibald (1982), A general theory for analyzing catch at age data. Canadian Journal of Fisheries and Aquatic Sciences 39, 1195–1207
184. Fournier, D. A., H. J. Skaug, J. Ancheta, J. Ianelli, A. Magnusson, M. N. Maunder, A. Nielsen and J. Sibert (2012), AD Model Builder: using automatic differentiation for statistical inference of highly parameterized complex nonlinear models. Optimization Methods and Software 27, 233– 249
185. Freckleton, R. P., A. R. Watkinson, R. E. Green and W. J. Sutherland (2006), Census error and the detection of density dependence. Journal of Animal Ecology 75, 837–851
186. Frederiksen, M., J.-D. Lebreton and T. Bregnballe (2001), The interplay between culling and density-dependence in the great cormorant: a modelling approach. Journal of Applied Ecology 38, 617–627
187. Frederiksen, M., J.-D. Lebreton, R. Pradel, R. Choquet and O. Gimenez (2013), Review: Identifying links between vital rates and environment: a toolbox for the applied ecologist. Journal of Applied Ecology 51, 71–81
188. Freeman, S. N. and P. T. Besbeas (2012), Quantifying changes in abundance without counting animals: extensions to a method of fitting integrated population models. Journal of Ornithology 152, 409–418
189. Freeman, S. N. and B. J. T. Morgan (1990), Studies in the analysis of ring-recovery data. The Ring 13, 271–288
190. Freeman, S. N. and B. J. T. Morgan (1992), A modelling strategy for recovery data from birds ringed as nestlings. Biometrics 48, 217–236
191. Freeman, S. N., D. Pomeroy and H. Tushabe (2003), On the use of timed species counts to estimate avian abundance indices in species-rich communities. African Journal of Ecology 41, 337–348
192. Furness, R. W. and J. J. D. Greenwood (1993), Birds as Monitors of Environmental Change. Chapman & Hall, London
193. Gaillard, J.-M., D. Allaine, D. Pontier, N. Yoccoz and D. Promislow (1994), Senescence in natural populations of mammals: a reanalysis. Evolution 48(2), 509–516
194. Gardner, B., J. A. Royle and M. T. Wegan (2009), Hierarchical models for estimating density from DNA mark-recapture studies. Ecology 90, 1106– 1115
195. Garrett, E. S. and S. L. Zeger (2000), Latent class model diagnosis. Biometrics 56, 1055–1067
196. Gauthier, G., P. T. Besbeas, J.-D. Lebreton and B. J. T. Morgan (2007), Population growth in snow geese: A modeling approach integrating demographic and survey information. Ecology 88, 1420–1429
197. Gelfand, A. E. and S. K. Sahu (1999), Identifiability, improper priors, and Gibbs sampling for generalized linear models. Journal of the American Statistical Association 94, 247–253
198. Gelman, A., X. Meng and H. Stern (1996), Posterior predictive assessment of model fitness via realized discrepancies – with discussion. Statistica Sinica 6, 733–807
199. Gelman, A. J., J. B. Carlin, H. S. Stern and D. B. Rubin (2004), Bayesian Data Analysis. Chapman & Hall, London, second edn.
200. Genovart, M., A. Sanz-Aguilar, A. Fernandez-Chacon, J. M. Igual, R. Pradel, M. G. Forero and D. Oro (2013), Contrasting effects of climatic variability on the demography of a trans-equatorial migratory seabird. Journal of Animal Ecology 82, 121–130
201. George, E. I. and C. P. Robert (1992), Capture-recapture estimation via Gibbs sampling. Biometrika 79, 677–683
202. Ghahramani, Z. (2001), An introduction to hidden Markov models and Bayesian networks. Journal of Pattern Recognition and Artificial Intelligence 15, 9–42
203. Gimenez, O., S. J. Bonner, R. King, R. A. Parker, S. P. Brooks, L. E. Jamieson, V. Grosbois, B. J. T. Morgan and L. Thomas (2008), Win BUGS for population ecologists: Bayesian modeling using Markov chain Monte Carlo. Environmental and Ecological Statistics 3, 885–918
204. Gimenez, O. and R. Choquet (2010), Individual heterogeneity in studies on marked animals using numerical integration: capture-recapture mixed models. Ecology 91, 148–154
205. Gimenez, O., R. Choquet and J.-D. Lebreton (2003), Parameter redundancy in multistate capture-recapture models. Biometrical Journal 45, 704–722
206. Gimenez, O., R. Covas, C. R. Brown, M. D. Anderson, M. B. Brown and T. Lenormand (2006a), Nonparametric estimation of natural selection on a quantitative trait using mark-recapture data. Evolution 60, 460– 466
207. Gimenez, O., C. Crainiceanu, C. Barbraud, S. Jenouvrier and B. J. T. Morgan (2006b), Semiparametric regression in capture-recapture modelling. Biometrics 62, 691–698
208. Gimenez, O., B. J. T. Morgan and S. P. Brooks (2009), Weak identifiability in models for mark-recapture-recovery data. Environmental and Ecological Statistics 3, 1057–1070
209. Gimenez, O., V. Rossi, R. Choquet, C. Dehais, B. Doris, H. Varella, J.-P. Vila and R. Pradel (2007), State-space modelling of data on marked individuals. Ecological Modelling 206, 431–438
210. Gitzen, R. A., J. J. Millspaugh, A. B. Cooper and D. S. Licht (2012), Design and Analysis of Long-term Ecological Monitoring Studies. Cambridge University Press, Cambridge
211. Givens, G. H. and J. A. Hoeting (2005), Computational Statistics. Wiley, New York
212. Good, I. J. (1953), The population frequencies of species and the estimation of population parameters. Biometrika 40, 237–264
213. Goodman, L. A. (1974), Exploratory latent structure analysis using both identifiable and unidentifiable models. Biometrika 61, 215–31
214. Gormley, A. M., E. Slooten, S. Dawson, R. J. Barker, W. Rayment, S. du Fresne and S. Brager (2012), First evidence that marine protected areas can work for marine mammals. Journal of Applied Ecology 49, 474–480
215. Goudie, I. B. J. and M. Goudie (2007), Who captures the marks for the Petersen estimator? Journal of the Royal Statistical Society, Series A 170, 825–839
216. Graham, R. L., D. E. Knuth and O. Patashnik (1988), Concrete Mathematics. Addison-Wesley
217. Green, P. J. (1995), Reversible Jump Markov Chain Monte Carlo Computation and Bayesian Model Determination. Biometrika 82, 711–732
218. Green, P. J. and B. W. Silverman (1994), Nonparametric regression and Generalized Linear Models. Chapman and Hall, New York. USA.
219. Greenwood, J. J. D. (2009), 100 years of ringing in Britain and Ireland. Ringing & Migration 24, 147–153
220. Grosbois, V., M. P. Harris, T. Anker-Nilssen, R. H. McCleery, D. N. Shaw, B. J. T. Morgan and O. Gimenez (2009), Modeling survival at multi-population scales using mark-recapture data. Ecology 90, 2922–2932
221. Guillera-Arroita, G. (2011), Impact of sampling with replacement in occupancy studies with spatial replication. Methods in Ecology and Evolution 2, 401–406
222. Guillera-Arroita, G., B. J. T. Morgan, M. S. Ridout and M. Linkie (2011), Species occupancy modeling for detection data collected along a transect. Journal of Agricultural, Biological, and Environmental Statistics 16, 301–317
223. Guillera-Arroita, G., M. S. Ridout and B. J. T. Morgan (2010), Design of occupancy studies with imperfect detection. Methods in Ecology and Evolution 1, 131–139
224. Guillera-Arroita, G., M. S. Ridout and B. J. T. Morgan (2014), Two-stage Bayesian study design for species occupancy estimation. Journal of Agricultural Biological and Environmental Statistics 19, 278–291
225. Guillera-Arroita, G., M. S. Ridout, B. J. T. Morgan and M. Linkie (2012), Models for species-detection data collected along transects in the presence of abundance-induced heterogeneity and clustering in the detection process. Methods in Ecology and Evolution 3, 358–367
226. Harvey, A. C. (1989), Forecasting, structural time series and the Kalman filter. Cambridge University Press, Cambridge
227. Hastie, T. and W. Fithian (2013), Inference from presence-only data; the ongoing controversy. Ecography 36, 864–867
228. Heisey, D. M. and E. V. Nordheim (1990), Biases in the Pollock and Cornelius method of estimating nest survival. Biometrics 46, 855–862
229. Heisey, D. M. and E. V. Nordheim (1995), Modelling age-specific survival in nesting studies, using a general approach for doubly-censored and truncated data. Biometrics 51, 51–60
230. Hénaux, V., T. Bregnballe and J.-D. Lebreton (2007), Dispersal and recruitment during population growth in a colonial bird, the great cormorant Phalacrocorax carbo sinensis. Avian Biology 38, 44–57
231. Hestbeck, J. B., J. D. Nichols and R. Malecki (1991), Estimates of movement and site fidelity using mark-resight data of wintering Canada geese. Ecology 72, 523–533
232. Heyde, C. C. and H.-J. Schuh (1978), Uniform bounding of probability generating functions and the evolution of reproduction rates in birds. Journal of Applied Probability 15, 243–250
233. Hill, M. O. (2011), Local frequency as a key to interpreting species occurrence data when recording effort is not known. Methods in Ecology and Evolution 3, 195–205
234. Hinde, A. (1998), Demographic Methods. Arnold, London
235. Hines, J. E. (1994), MSSURVIV Users Manual. National Biological Service, Patuxent Wildlife Research Center, Laurel, MD 20708
236. Hines, J. E. (2006), PRESENCE2-Software to estimate patch occupancy and related parameters. USGS-PWRC, http://www.mbr-pwrc.gov/software/presence.html
237. Hines, J. E., J. D. Nichols, J. A. Royle, D. I. MacKenzie, A. M. Gopalswamy, N. Samba Kumar and K. U. Karanth (2010), Tigers on trails: occupancy modeling for cluster sampling. Ecological Applications 20, 1456–1466
238. Hirst, D. (1994), An improved removal method for estimating animal abundance. Biometrics 50, 501–505
239. Hoeting, J. A., M. Leecaster and D. Bowden (2000), An improved model for spatially correlated binary responses. Journal of Agricultural, Biological, and Environmental Statistics 5, 102–114
240. Hook, E. B. and R. R. Regal (1995), Capture-recapture methods in epidemiology: methods and limitations. Epidemiologic Reviews 17, 243–264
241. Horvitz, D. G. and D. J. Thompson (1952), A generalization of sampling without replacement from a finite universe. Journal of the American Statistical Association 47, 663–685
242. Hubbard, B. A., D. J. Cole and B. J. T. Morgan (2014), Parameter redundancy in capture-recapture-recovery models. Statistical Methodology 17, 17–29
243. Huggins, R. (1989), On the statistical analysis of capture experiments. Biometrika 76, 113–140
244. Huggins, R. (1991), Some practical aspects of a conditional likelihood approach to capture experiments. Biometrics 47, 725–732
245. Huggins, R. and W. H. Hwang (2010), A measurement error model for heterogeneous capture probabilities in mark-recapture experiments: An estimating equation approach. Journal of Agricultural, Biological, and Environmental Statistics 15, 198–208
246. Huggins, R. and W. H. Hwang (2011), A review of the use of conditional likelihood in capture-recapture experiments. International Statistical Review 79, 385–400
247. Huggins, R., Y. Wang and J. Kearns (2010), Analysis of an extended batch marking experiment using estimating equations. Journal of Agricultural, Biological and Environmental Statistics 15, 279–289
248. Hunter, C. M. and H. Caswell (2008), Rank and redundancy of multistate mark-recapture models for seabird populations with unobservable states. Ecological and Environmental Statistics Series 3, 797–826
249. Hwang, W.-H. and S. Y. H. Huang (2003), Estimation in capture-recapture models when covariates are subject to measurement errors. Biometrics 59, 1113–1122
250. Hwang, W. H., S. Y. H. Huang and C. Y. Wang (2007), Effects of measurement error and conditional score estimation in capture-recapture models. Statistica Sinica 17, 301–316
251. Illian, J., P. Penttinen, H. Stoyan and D. Stoyan (2008), Statistical Analysis and Modelling of Spatial Point Patterns. Statistics in Practice, Wiley, New York
252. Jiang, H., K. H. Pollock, C. Brownie, J. E. Hightower, J. M. Hoenig and W. S. Hearn (2007), Age-dependent tag return models for estimating fishing mortality, natural mortality and selectivity. Journal of Agricultural, Biological and Environmental Statistics 12, 177–194
253. Johnson, D. S., P. B. Conn, M. B. Hooten, J. Ray and B. A. Pond (2013), Spatial occupancy models for large data sets. Ecology 94, 801–808
254. Johnson, N. L., A. W. Kemp and S. Kotz (2005), Univariate Discrete Distributions. Wiley, New York, third edn.
255. Jolly, G. M. (1965), Explicit estimates from capture-recapture data with both death and immigration-stochastic model. Biometrika 52, 225–247
256. Julier, S. J. and J. K. Uhlmann (1997), New extension of the Kalman filter to nonlinear systems. SPIE Proceedings, Signal processing, Sensor Fusion and Target Recognition VI 3068
257. Kendall, W. L. and R. Bjorkland (2001), Using open robust design models to estimate temporary emigration from capture-recapture data. Biometrics 57, 1113–1122
258. Kendall, W. L., J. E. Hines and J. D. Nichols (2003), Adjusting multistate capture-recapture models for misclassification bias: manatee breeding proportions. Ecology 84, 1058–1066
259. Kendall, W. L. and J. D. Nichols (2002), Estimating state-transition probabilities for unobservable states using capture-recapture/resighting data. Ecology 83, 3276–3284
260. Kendall, W. L., J. D. Nichols and J. E. Hines (1997), Estimating temporary emigration using capture-recapture data with Pollock’s robust design. Ecology 78, 563–578
261. Kendall, W. L., K. H. Pollock and C. Brownie (1995), A likelihood-based approach to capture-recapture estimation of demographic parameters under the robust design. Biometrics 51, 293–308
262. Kéry, M. (2010), Introduction to WinBUGS for Ecologists. Academic Press, Amsterdam
263. Kéry, M., G. Guillera-Arroita and J. J. Lahoz-Monfort (2013), Analysing and mapping species range dynamics using occupancy models. Journal of Biogeography 40, 1463–1474
264. Kéry, M., J. A. Royle, H. Schmid, M. Schaub, B. Volet, G. Häfliger and N. Zbinden (2010), Site-occupancy distribution modeling to correct population-trend estimates derived from opportunistic observations. Conservation Biology 24, 1388–1397
265. Kéry, M. and M. Schaub (2012), Bayesian Population Analysis using Win-BUGS. Academic Press, Amsterdam
266. King, R. (2012), A review of Bayesian state-space modelling of capture-recapture-recovery data. Interface Focus 2, 190–204
267. King, R. and S. P. Brooks (2001), Model selection for integrated recovery/recapture data. Biometrics 58, 841–851
268. King, R. and S. P. Brooks (2003a), Closed-form likelihoods for Arnason-Schwarz models. Biometrika 89, 435–444
269. King, R. and S. P. Brooks (2003b), Survival and spatial fidelity of mouflons: The effect of location, age, and sex. Journal of Agricultural Biological and Environmental Statistics 8, 486–513
270. King, R. and S. P. Brooks (2004a), Bayesian analysis of Hector’s dolphins. Animal Biodiversity and Conservation 27, 343–354
271. King, R. and S. P. Brooks (2004b), A classical study of catch-effort models for Hector’s dolphins. Journal of the American Statistical Association 99, 325–333
272. King, R., S. P. Brooks, C. Mazzetta, S. N. Freeman and B. J. T. Morgan (2008), Identifying and diagnosing population declines: A Bayesian assessment of lapwings in the UK. Journal of the Royal Statistical Society, Series C 57, 607–632
273. King, R., S. P. Brooks, B. J. T. Morgan and T. Coulson (2006), Factors influencing Soay sheep survival: a Bayesian analysis. Biometrics 62, 211– 220
274. King, R., B. J. T. Morgan, O. Gimenez and S. P. Brooks (2010), Bayesian Analysis for Population Ecology. Chapman & Hall/CRC, Boca Raton, Florida
275. Knape, J., P. Besbeas and P. de Valpine (2013), Using uncertainty estimates in analyses of population time series. Ecology 94, 2097–2107
276. Kolbert, E. (2014), The Sixth Extinction: An Unnatural History. Bloomsbury Publishing, London
277. Korner-Nievergelt, F., A. Sauter, P. W. Atkinson, J. Guelat, W. Kania, M. Kéry, U. Koppen, R. A. Robinson, M. Schaub, K. Thorup, H. van der Jeugd and A. J. van Noordwijk (2010), Improving the analysis of movement data from marked individuals through explicit estimation of observer heterogeneity. Journal of Avian Biology 41, 8–17
278. Kuhnert, R., V. J. D. R. Vilas, J. Gallagher and D. Böhning (2008), A bagging-based correction for the mixture model estimator of population size. Biometrical Journal 50, 993–1005
279. Laake, J. L., D. S. Johnson and P. B. Conn (2013), marked: an R package for maximum likelihood and Markov chain Monte Carlo analysis of capture-recapture data. Methods in Ecology and Evolution 4, 885–890
280. Laake, J. L. and E. Rexstad (2008), RMark: R code for MARK analyis. R Package version 1
281. Lahoz-Monfort, J. J. (2012), Bayesian Analysis of Multi-species Demography: Synchrony and Integrated Population Models for a Breeding Community of Seabirds. Ph.D. thesis, University of Kent
282. Lahoz-Monfort, J. J., M. P. Harris, B. J. T. Morgan, S. N. Freeman and S. Wanless (2014), Exploring the consequences of reducing survey effort for detecting individual and temporal variability in survival. Journal of Applied Ecology 51, 534–543
283. Lahoz-Monfort, J. J., B. J. T. Morgan, M. P. Harris, F. Daunt, S. Wanless and S. N. Freeman (2013), Breeding together: modeling productivity synchrony at a multi-species community. Ecology 94, 3–10
284. Lahoz-Monfort, J. J., B. J. T. Morgan, M. P. Harris, S. Wanless and S. N. Freeman (2010), A capture-recapture model for exploring multi-species synchrony in survival. Methods in Ecology and Evolution 2, 116–124
285. Langrock, R. (2011), Some applications of nonlinear and non-Gaussian state-space modelling by means of hidden Markov models. Journal of Applied Statistics 38, 2955–2970
286. Langrock, R. and R. King (2013), Maximum likelihood estimation of mark-recapture-recovery models in the presence of continuous covariates. Annals of Applied Statistics 7, 1249–1835
287. Lanumteang, K. and D. Böhning (2011), An extension of Chao’s estimator of population size based on the first three capture frequency counts. Computational Statistics and Data Analysis 55, 2302–2311
288. Lebreton, J.-D. (2001), The use of bird rings in the study of survival. Ardea 89 (special issue), 85–100
289. Lebreton, J.-D., T. Almeras and R. Pradel (1999), Competing events, mixtures of information and multistratum recapture models. Bird Study 46, S39–S46
290. Lebreton, J.-D., K. P. Burnham, J. Clobert and D. R. Anderson (1992), Modeling survival and testing biological hypotheses using marked animals: A unified approach with case studies. Ecological Monographs 62, 67–118
291. Lebreton, J.-D., B. J. T. Morgan, R. Pradel and S. N. Freeman (1995), A simultaneous survival rate analysis of dead recovery and live recapture data. Biometrics 51, 1418–1428
292. Lebreton, J.-D., J. D. Nichols, R. J. Barker, R. Pradel and J. A. Spendelow (2009), Modeling individual animal histories with multistate capture-recapture models. Advances in Ecological Research 41, 87–173
293. Lee, S. M. and A. Chao (1994), Estimating population size via sample coverage for closed capture-recapture models. Biometrics 50, 88–97
294. Lincoln, F. C. (1930), The waterfowl flyways of North America. US Department of Agriculture Circular 118, 1–4
295. Lindberg, M. S. (2012), A review of designs for capture-mark-recapture studies in discrete time. Journal of Ornithology 152, S355–S370
296. Link, W. A. (2003), Nonidentifiability of population size from capture-recapture data with heterogeneous detection probabilities. Biometrics 59, 1123–1130
297. Link, W. A. and R. J. Barker (2005), Modeling association among demographic parameters in analysis of open population capture-recapture data. Biometrics 61, 46–54
298. Link, W. A. and R. J. Barker (2009), Bayesian Inference: With Ecological Applications. Academic Press, Amsterdam
299. Link, W. A., J. Yoshizaki, L. L. Bailey and K. Pollock (2010), Uncovering a latent multinomial: analysis of mark-recapture data. Biometrics 66, 178–185
300. Linkie, M., R. S. Borysiewicz, Y. Dinata, A. Nugroho, I. Achmad Haidir, M. S. Ridout, N. Leader-Williams and B. J. T. Morgan (2008), Predicting the spatio-temporal patterns of tiger and their prey across a primary-disturbed forest landscape in Sumatra. University of Kent Technical Report: UKC/IMS/08/021
301. Little, M. P., W. Heidenreich and G. Li (2010), Parameter identifiability and redundancy: theoretical considerations. PLoS ONE 5, e8915
302. Lloyd, C. J. (1999), Statistical Analysis of Categorical Data. Wiley, New York
303. Loison, A., M. Festa-Bianchet, J.-M. Gaillard, J. T. Jorgenson and J.-M. Jullien (1999), Age-specific survival in five populations of ungulates: evidence of senescence. Ecology 80, 2539–2554
304. Lukacs, P. M. and K. P. Burnham (2005), Estimating population size from DNA-based closed capture-recapture data incorporating genotyping error. Journal of Wildlife Management 69, 396–403
305. Lunn, D., C. Jackson, N. Best, A. Thomas and D. Spiegelhalter (2013), The BUGS Book: A Practical Introduction to Bayesian Analysis. Chapman & Hall, CRC Press, Boca Raton
306. MacDonald, I. L. and W. Zucchini (1997), Hidden Markov and Other Models for Discrete-valued Time Series. Chapman & Hall, CRC Press, Boca Raton
307. MacKenzie, D. I., J. D. Nichols, G. B. Lachman, S. Droege, J. A. Royle and C. A. Langtimm (2002), Estimating site occupancy rates when detection probabilities are less than one. Ecology 83, 2248–2255
308. MacKenzie, D. I., J. D. Nichols, J. A. Royle, K. H. Pollock, L. L. Bailey and J. E. Hines (2006), Occupancy Estimation and Modeling: Inferring Patterns and Dynamics of Species Occurrence. Academic Press, Amsterdam
309. Marques, T., L. Thomas, S. Martin, D. Mellinger, S. Jarvis, R. Morrissey, C.-A. Ciminello and N. DiMarzio (2012), Spatially explicit capture-recapture methods to estimate Minke whale density from data collected at bottom-mounted hydrophones. Journal of Ornithology 152, S445– S455
310. Matechou, E. (2010), Applications and Extensions of Capture-recapture Stopover Models. Ph.D. thesis, University of Kent
311. Matechou, E., B. J. T. Morgan, S. Pledger, J. A. Collazo and J. E. Lyons (2013), Integrated analysis of capture-recapture-resighting data and counts of unmarked birds at stop-over sites. Journal of Agricultural, Biological, and Environmental Statistics 18, 120–135
312. Maunder, M. N. and A. E. Punt (2013), A review of integrated analysis in fisheries stock assessment. Fisheries Research 142, 61–74
313. Mazzetta, C., B. J. T. Morgan and T. Coulson (2010), A state-space modelling approach to population size estimation. Technical report, University of Kent Technical Report: UKC/SMSAS/10/025
314. McCrea, R. S. (2012), Sufficient statistic likelihood construction for age-and time-dependent multi-state joint recapture and recovery data. Statistics and Probability Letters 82, 357–359
315. McCrea, R. S. and B. J. T. Morgan (2011), Multistate mark-recapture model selection using score tests. Biometrics 67, 234–241
316. McCrea, R. S., B. J. T. Morgan and T. Bregnballe (2011), Model comparison and assessment for multistate capture-recapture-recovery models. Journal of Ornithology 152, 293–303
317. McCrea, R. S., B. J. T. Morgan, D. I. Brown and R. A. Robinson (2012), Conditional modelling of ring-recovery data. Methods in Ecology and Evolution 3, 823–831
318. McCrea, R. S., B. J. T. Morgan and D. J. Cole (2013), Age-dependent models for recovery data on animals marked at unknown age. Journal of the Royal Statistical Society, Series C 62, 101–113
319. McCrea, R. S., B. J. T. Morgan and O. Gimenez (2014a), Certain capture-recapture diagnostic goodness-of-fit tests are score tests. University of Kent Technical Report: UKC/SMSAS/14/001
320. McCrea, R. S., B. J. T. Morgan, O. Gimenez, P. Besbeas, J.-D. Lebreton and T. Bregnballe (2010), Multi-site integrated population modelling. Journal of Agricultural, Biological and Environmental Statistics 15, 539– 561
321. McCrea, R. S., B. J. T. Morgan and R. Pradel (2014b), Diagnostic tests for joint recapture and recovery data. Journal of Agricultural, Biological and Environmental Statistics (To appear)
322. McLachlan, G. J. and T. Krishnan (1997), The EM Algorithm and Extensions. Wiley, New York
323. Metropolis, N., A. W. Rosenbluth, M. N. Rosenbluth, A. H. Teller and E. Teller (1953), Equations of state calculations by fast computing machines. Journal of Chemical Physics 21, 1087–1091
324. Meyer, R. and R. B. Millar (1999), BUGS in Bayesian stock assessments. Canadian Journal of Fisheries and Aquatic Science 56, 1078–1086
325. Michelot, T., R. Langrock, T. Kneib and R. King (2013), Maximum penalized likelihood estimation in semiparametric capture-recapture models. arXiv:1311.1039
326. Millar, R. B. (2004), Sensitivity of Bayes estimators to hyper-parameters with an application to maximum yield from fisheries. Biometrics 60, 536–542
327. Millar, R. B. and R. Meyer (2000a), Bayesian state space modelling of age-structured data: fitting a model is just the beginning. Canadian Journal of Fisheries and Aquatic Science 57, 43–50
328. Millar, R. B. and R. Meyer (2000b), Non-linear state space modelling of fisheries biomass dynamics by using Metropolis-Hastings within-Gibbs sampling. Journal of the Royal Statistical Society, Series C 49, 327–342
329. Miller, D., B. J. T. Morgan, M. S. Ridout, P. Carey and P. Rothery (2011a), Methods for exact perturbation analysis. Methods in Ecology and Evolution 2, 283–288
330. Miller, D. A., J. D. Nichols, B. T. McClintock, E. H. Campbell Grant, L. Bailey and L. A. Weir (2011b), Improving occupancy estimation when two types of observational error occur: non-detection and species misidentification. Ecology 92, 1422–1428
331. Moran, P. A. P. (1951), A mathematical theory of animal trapping. Biometrika 38, 307–311
332. Moreno, M. and S. R. Lele (2010), Improved estimation of site occupancy using penalised likelihood. Ecology 91, 341–346
333. Morgan, B. J. T. (2008), Applied Stochastic Modelling. Chapman & Hall, CRC Press, London, second edn.
334. Morgan, B. J. T. and S. N. Freeman (1989), A model with first-year variation for ring-recovery data. Biometrics 45, 1087–1102
335. Morgan, B. J. T., J.-D. Lebreton and S. N. Freeman (1997), Ornithology, Statistics in Encyclopedia of Statistical Sciences 1, 438–447
336. Morgan, B. J. T., D. J. Revell and S. N. Freeman (2007), A note on simplifying likelihoods for site occupancy models. Biometrics 63, 618–621
337. Morgan, B. J. T. and M. S. Ridout (2008), A new mixture model for capture heterogeneity. Journal of the Royal Statistical Society, Series C 57, 433– 446
338. Morgan, B. J. T. and D. E. Thomson (2002), Statistical Analysis of Data from Marked Bird Populations: special issue of Journal of Applied Statistics, vol 29, Nos 1-4 . Taylor & Francis
339. Morgan, B. J. T. and A. Viallefont (2012), Ornithological data. Encyclopedia of Environmetrics 3, 1495–1499
340. Moyes, K., T. Coulson, B. J. T. Morgan, A. Donald, S. J. Morris and T. H. Clutton-Brock (2006), Cumulative reproduction and survival costs in female red deer. Oikos 115, 241–252
341. Moyes, K., B. J. T. Morgan, A. Morris, S. Morris, T. H. Clutton-Brock and T. Coulson (2011), Individual differences in reproductive costs examined using multi-state methods. Journal of Animal Ecology 80, 456–465
342. Mysterud, A., G. Steinheim, N. Yoccoz, O. Holand and N. C. Stenseth (2002), Early onset of reproductive senescence in domestic sheep, Ovis aries. Oikos 97, 177–183
343. Nasution, M. D., C. Brownie, K. H. Pollock and R. A. Powell (2004), The effect on model identifiability of allowing different relocation rates for live and dead animals in the combined analysis of telemetry and recapture data. Journal of Agricultural, Biological and Environmental Statistics 9, 27–41
344. Newman, K. B. (1998), State-space modelling of animal movement and mortality with application to salmon. Biometrics 54, 1290–1314
345. Newman, K. B., S. T. Buckland, B. J. T. Morgan, R. King, D. L. Borchers, D. J. Cole, P. T. Besbeas, O. Gimenez and L. Thomas (2014), Modelling Population Dynamics: Model Formulation, Fitting and Assessment using State-space Methods. Springer, New York
346. Newman, K. B., C. Fernández, L. Thomas and S. T. Buckland (2008), Monte Carlo inference for state-space models of wild animal populations. Biometrics 65, 572–583
347. Nichols, J. D., J. R. Sauer, K. H. Pollock and J. B. Hestbeck (1992), Estimating transition probabilities for stage-based population projection matrices using capture-recapture data. Ecology 73, 306–312
348. Norris, B. (2012), Statistical Analysis and Modelling of Benthic Data. Ph.D. thesis, University of Kent
349. Norris, J. L. and K. H. Pollock (1997), Nonparametric MLE under two closed capture-recapture models with heterogeneity. Biometrics 52, 639–649
350. North, P. M. and B. J. T. Morgan (1979), Modelling heron survival using weather data. Biometrics 35, 667–681
351. O’Brien, T. and M. Kinnaird (2011), Density estimation of sympatric carnivores using spatially explicit capture-recapture methods and standard trapping grid. Ecological Applications 21, 2908–2916
352. Okland, J.-M., O. A. Haaland and H. J. Skaug (2010), A method for defining management units based on genetically determined close relatives. ICES Journal of Marine Science 67, 551–558
353. Oliver, L. (2012), Modelling Individual Heterogeneity in Mark-recapture Studies. Ph.D. thesis, University of Kent
354. Oliver, L. J., B. J. T. Morgan, S. M. Durant and N. Pettorelli (2011), Individual heterogeneity in recapture probability and survival estimates in cheetah. Ecological modelling 222, 776–784
355. Otis, D. L., K. P. Burnham, G. C. White and D. R. Anderson (1978), Statistical inference from capture data on closed animal populations. Wildlife Monographs 62, 1–135
356. Overstall, A. M. and R. King (2014), conting: An R package for Bayesian analysis of complete and incomplete contingency tables. Journal of Statistical Software p. To appear
357. Overton, W. S. (1969), Wildlife Management Techniques: Estimating the number of animals in wildlife populations, pp. 403–455. Wildlife Society, Washington DC, third edn.
358. Papaix, J., S. Cubaybes, M. Buoro, A. Charmantier, P. Perret and O. Gimenez (2010), Combining capture-recapture data and pedigree information to assess heritability of demographic parameters in the wild. Journal of Evolutionary Biology 23, 2176–2184
359. Parent, E. and E. E. Rivot (2013), Introduction to Hierarchical Bayesian Modeling. Chapman & Hall, CRC Press, Boca Raton
360. Perrins, C. (1974), Birds. Collins, London
361. Petersen, C. G. J. (1894), On the biology of our flat-fishes and on the decrease of our flat-fish fisheries. Report of the Danish Biological Station IV, 1893–1894
362. Pledger, S. (2000), Unified maximum likelihood estimates for closed capture-recapture models using mixtures. Biometrics 56, 434–442
363. Pledger, S. (2005), The performance of mixture models in heterogeneous closed population capture-recapture. Biometrics 61, 868–873
364. Pledger, S., M. Efford, K. H. Pollock, J. Collazo and J. Lyons (2009), Stopover duration analysis with departure probability dependent on unknown time since arrival. Environmental and Ecological Statistics 3, 1071–1082
365. Pledger, S. and P. Phillpot (2008), Using mixtures to model heterogeneity in ecological capture-recapture studies. Biometrical Journal 50, 1022–1034
366. Pledger, S., K. H. Pollock and J. L. Norris (2003), Open capture-recapture models with heterogeneity. I Cormack-Jolly-Seber model. Biometrics 56, 786–794
367. Pledger, S. and C. J. Schwarz (2002), Modelling heterogeneity of survival in band-recovery data using mixtures. Journal of Applied Statistics 29, 315–327
368. Polacheck, T., R. Hilborn and A. E. Punt (1993), Fitting surplus production models: comparing methods and measuring uncertainty. Canadian Journal of Fisheries and Aquatic Science 50, 2597–2607
369. Pollock, K. H. (1982), A capture-recapture design robust to unequal probability of capture. Journal of Wildlife Management 46, 752–757
370. Pollock, K. H. (1991), Modelling capture, recapture and removal statistics for estimation of demographic parameters for fish and wildlife populations: past present and future. Journal of the American Statistical Association 86, 225–238
371. Pollock, K. H. (2000), Capture-recapture models. Journal of the American Statistical Association 95, 293–296
372. Pollock, K. H. (2002), The use of auxiliary variables in capture-recapture modelling: an overview. Journal of Applied Statistics 29, 85–102
373. Pollock, K. H. and W. L. Cornelius (1988), A distribution-free nest survival model. Biometrics 44, 397–404
374. Pollock, K. H., J. E. Hines, and J. D. Nichols (1985), Goodness-of-fit tests for open capture-recapture models. Biometrics 41, 399–410
375. Pollock, K. H., J. E. Hines and J. D. Nichols (1984), The use of auxiliary variables in capture-recapture and removal experiments. Biometrics 40, 329–340
376. Pollock, K. H., D. L. Solomon and D. S. Robson (1974), Test for mortality recruitment in a K sample tag recapture experiment. Biometrics 30, 77–87
377. Poole, D. and J. E. Zeh (2002), Estimation of adult bowhead whale survival rates using Markov chain Monte Carlo methods. Journal of Agricultural, Biological and Environmental Statistics 7, 1–13
378. Pradel, R. (1993), Flexibility in survival analysis from recapture data: Handling trap-dependence. In J.-D. Lebreton and P. North (eds.), Marked Individuals in the Study of Bird Population, pp. 11–36, Basel: Birkhauser.
379. Pradel, R. (1996), Utilization of capture-mark-recapture for the study of recruitment and population growth rate. Biometrics 52, 703–709
380. Pradel, R. (2005), Multievent: an extension of multistate capture-recapture models to uncertain states. Biometrics 61, 442–447
381. Pradel, R. (2009), The stakes of capture-recapture models with state uncertainty. Environmental and Ecological Statistics 3, 781–795
382. Pradel, R., O. Gimenez and J.-D. Lebreton (2005), Principles and interest of GOF tests for multistate capture-recapture models. Animal Biodiversity and Conservation 28, 189–204
383. Pradel, R., J. E. Hines, J.-D. Lebreton and J. D. Nichols (1997), Capture-recapture survival models taking account of transients. Biometrics 53, 60–72
384. Pradel, R., L. Maurin-Bernier, O. Gimenez, M. Genovart, R. Choquet and D. Oro (2009), Estimation of sex-specific survival with uncertainty in sex assessment. Canadian Journal of Statistics 36, 29–42
385. Pradel, R., C. Wintrebert and O. Gimenez (2003), A proposal for a goodnessof-fit test to the Arnason-Schwarz multisite capture-recapture model. Biometrics 59, 43–53
386. Revell, D. J. (2007), Efficient Modelling Methods for Mark-recapture-recovery Data. Ph.D. thesis, University of Kent
387. Reynolds, T. J., R. King, J. Harwood, M. Frederiksen, M. P. Harris and S. Wanless (2009), Integrated data analyses in the presence of emigration and tag loss. Journal of Agricultural, Biological and Environmental Statistics 14, 411–431
388. Ridout, M. S. and P. T. Besbeas (2004), An empirical model for underdis-persed count data. Statistical Modelling 4, 77–89
389. Rivalan, P., A. C. Prevot-Julliard, R. Choquet, R. Pradel, B. Jacquemin and M. Girondot (2005), Trade-off between current reproductive investment and delay to next reproduction in leatherback sea turtle. Oecologia 145, 564–574
390. Rivot, E. and E. Prévost (2002), Hierarchical Bayesian analysis of capture-mark-recapture data. Canadian Journal of Fisheries and Aquatic Science 59, 1768–1784
391. Rivot, E., E. Prévost and E. Parent (2001), How robust are Bayesian pos terior inferences based on a Ricker model with regards to measurement errors and prior assumptions about parameters? Canadian Journal of Fisheries and Aquatic Science 58, 2284–2297
392. Rivot, E., E. Prévost, E. Parent and J.-L. Bagliniére (2004), A Bayesian state-space modelling framework for fitting a salmon stage-structured population dynamic model to multiple time series of field data. Ecological Modelling 179, 463–485
393. Roberts, J. M. and D. D. Brewer (2003), Estimating the prevalence of male clients of prostitute women in Vancouver with a simple capture-recapture method. Journal of the Royal Statistical Sociey Series A 169, 745–756
394. Rocchetti, I., J. Bunge and D. Böhning (2011), Population size estimation based upon ratios of recapture probabilities. Annals of Applied Statistics 5, 1512–1533
395. Rothenberg, T. J. (1971), Identification in parametric models. Econometrica 39, 577–591
396. Rouan, L., R. Choquet and P. Pradel (2009), A general framework for modeling memory in capture-recapture data. Journal of Agricultural, Biological and Environmental Statistics 14, 338–355
397. Royle, J. A. (2004), N-mixture models for estimating population size from spatially replicated counts. Biometrics 60, 108–115
398. Royle, J. A. (2008), Modeling individual effects in the Cormack–Jolly–Seber model: a state–space formulation. Biometrics 64, 364–370
399. Royle, J. A. (2009), Analysis of capture-recapture models with individual covariates using data augmentation. Biometrics 65, 267–274
400. Royle, J. A., R. Chandler, R. Sollmann and B. Gardner (2013), Spatial Capture-Recapture. Academic Press, Amsterdam
401. Royle, J. A., R. B. Chandler, C. Yackulic and J. D. Nichols (2012), Likelihood analysis of species occurrence probability from presence-only data for modelling species distributions. Methods in Ecology and Evolution 3, 545–554
402. Royle, J. A. and R. M. Dorazio (2008), Hierarchical Modeling and Inference in Ecology. Academic Press, London
403. Royle, J. A., R. M. Dorazio and W. A. Link (2007), Analysis of multinomial models with unknown index using data augmentation. Journal of Computational and Graphical Statistics 16, 67–85
404. Royle, J. A., K. Karanth, A. Gopalaswamy and N. Kumar (2009), Bayesian inference in camera trapping studies for a class of spatial capture-recapture models. Ecology 90, 3233–3244
405. Royle, J. A. and M. Kéry (2007), A Bayesian state-space formulation of dynamic occupancy models. Ecology 88, 1813–1823
406. Royle, J. A. and W. A. Link (2002), Random effects and shrinkage estimation in capture-recapture models. Journal of Applied Statistics, 29, 329–351
407. Royle, J. A. and W. A. Link (2006), Generalized site occupancy models allowing for false positive and false negative errors. Ecology 87, 835–841
408. Royle, J. A. and J. D. Nichols (2003), Estimating abundance from repeated presence-absence data or point counts. Ecology 84, 777–790
409. Royle, J. A. and K. Young (2008), A hierarchical model for spatially explicit capture-recapture data. Ecology 89, 2281–2289
410. Runge, J. P., J. E. Hines and J. D. Nichols (2007), Estimating species-specific survival and movement when species identification is uncertain. Ecology 88, 282–288
411. Sanathanan, L. (1977), Estimating the size of a truncated sample. Journal of the American Statistical Association 72, 669–672
412. Sandland, R. L. and R. M. Cormack (1984), Statistical inference for Poisson and multinomial models for capture-recapture experiments. Biometrika 71, 27–33
413. Saraux, C., C. Le Bohec, J. M. Durant, V. Viblanc, M. Gauthier-Clerk, D. Beaune, Y.-H. Parl, N. Yoccoz, N. Stenseth and Y. Le Mayo (2010), Reliability of flipper-banded penguins as indicators of climate change. Nature 469, 203–206
414. Schaub, M. and F. Abadi (2011), Integrated population models: a novel analysis framework for deeper insights into population dynamics. Journal of Ornithology 152(Suppl 1), S227–S237
415. Schaub, M. and W. L. Kendall (2012), Estimation, modelling and conservation of vertebrate populations using marked individuals. Journal of Ornithology 152, S291–S292
416. Schnabel, Z. E. (1938), The estimation of the total fish population of a lake. The American Mathematical Monthly 45, 348–352
417. Schofield, M. R. and R. J. Barker (2008), A unified capture-recapture framework. Journal of Agricultural, Biological and Environmental Statistics 13, 458–477
418. Schofield, M. R. and R. J. Barker (2010), Data augmentation and reversible jump MCMC for multinomial index problems. arXiv:1009.3507
419. Schwarz, C., J. F. Schweigert and A. N. Arnason (1993), Estimating migration rates using tag-recovery data. Biometrics 59, 291–318
420. Schwarz, C. G. and A. N. Arnason (1996), A general methodology for the analysis of capture-recapture experiments in open populations. Biometrics 52, 860–873
421. Schwarz, C. J. and G. A. F. Seber (1999), A review of estimating animal abundance III. Statistical Science 14, 427–456
422. Schwarz, C. J. and W. T. Stobo (1999), Estimation and effects of tag-misread rates in capture-recapture studies. Canadian Journal of Fisheries and Wildlife Management 56, 551–559
423. Seber, G. A. F. (1965), A note on the multiple-recapture census. Biometrika 52, 249–259
424. Seber, G. A. F. (1971), Estimating age-specific survival rates from bird-band returns when the reporting rate is constant. Biometrika 58, 491–497
425. Seber, G. A. F. (1982), The Estimation of Animal Abundance and Related Parameters. Griffin, London, second edn.
426. Self, S. G. and K.-Y. Liang (1987), Asymptotic properties of maximum likelihood estimators and likelihood ratio tests under non-standard conditions. Journal of the American Statistical Association 82, 605–610
427. Senar, J. C., A. A. Dhondt and M. J. Conroy (2004), The quantitative study of marked individuals in ecology, evolution and conservation biology. Animal Biodiversity and Conservation 27, 1–2
428. Servanty, S.R., Choquet, E. Baubet, S. Brandt, G. J.-M.M. Schaub, C. Togo, J.-D. Lebreton, M. Buoro and O. Gimenez (2010), Assessing compensatory vs. additive mortality using marked animals: a Bayesian state-space modeling approach. Ecology 91, 1916–1923
429. Shapiro, A. and M. Browne (1983), On the investigation of local identifiability: a counter example. Psychometrika 48, 303–304
430. Singh, P., A. Gopalaswamy, J. A. Royle, N. Kumar and K. Karanth (2010), SPACECAP: A program to estimate animal abundance and density using Bayesian spatially explicit capture-recapture models. Version 1.0. Wildlife Conservation Society-India Program, Centre for Wildlife Studies, Bangalore, India
431. Sisson, S. A. and Y. Fan (2009), Towards automating model selection for a mark-recapture-recovery analysis. Journal of the Royal Statistical Society C 58, 247–266
432. Smith, E. P. and G. van Belle (1984), Nonparametric estimation of species richness. Biometrics 40, 119–129
433. Stanley, T. R. and K. P. Burnham (1999), A closure test for time-specific capture-recapture data. Environmental and Ecological Statistics 6, 197– 209
434. Stanley, T. R. and J. D. Richards (2005), Software review: A program for testing capture-recapture data for closure. Wildlife Society Bulletin 33, 782–785
435. Stoklosa, J. and R. Huggins (2012), A robust P-spline approach to closed population capture-recapture models with time-dependence and heterogeneity. Computational Statistics and Data Analysis 56, 408–417
436. Sullivan, P. J. (1992), A Kalman filter approach to catch-at-length analysis. Biometrics 48, 237–258
437. Tavecchia, G., P. T. Besbeas, T. Coulson, B. J. T. Morgan and T. H. Clutton-Brock (2009), Estimating population size and hidden demographic parameters with state-space modelling. The American Naturalist 173, 722– 733
438. Thomson, D. L., M. J. Conroy, D. R. Anderson, K. P. Burnham, E. G. Cooch, C. M. Francis, J.-D. Lebreton, M. Lindberg, B. J. T. Morgan, D. L. Otis and G. C. White (2009), Standardising terminology and notation for the analysis of demographic processes in marked populations. Environmental and Ecological Statistics 3, 1099–1106
439. Tibshirani, R. (1996), Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society Series B 58, 267–288
440. Tierney, L. (1994), Markov chains for exploring posterior distributions. Annals of Statistics 22, 1701–1762
441. Tyre, A. J., B. Tenhumberg, S. A. Field, D. Niejalke, K. Parris and H. P. Possingham (2003), Improving precision and reducing bias in biological surveys: estimating false-negative error rates. Ecological Applications 13, 1790–1801
442. van der Heijden, P. G. M., R. Bustami, M. J. Cruyff, G. Engbersen and H. C. van Houwelingen (2003a), Point and interval estimation of the population size using the truncated Poisson regression model. Statistical Modelling 3, 305–322
443. van der Heijden, P. G. M., M. Cruyff and D. Böhning (2014), Capture-recapture to estimate crime populations. In G. Bruisma and D. Weisburd (eds.), Encyclopedia of Criminology and Criminal Justice, pp. 267–278, Springer, New York
444. van der Heijden, P. G. M., M. Cruyff and H. C. van Houwelingen (2003b), Estimating the size of a criminal population from police records using the truncated Poisson regression model. Statistica Neerlandica 57, 289–304
445. van Deusen, P. C. (2002), An EM algorithm for capture-recapture estimation. Environmental and Ecological Statistics 9, 151–165
446. Veran, S., O. Gimenez, E. Flint, W. Kendall, P. Doherty and J.-D. Lebreton (2007), Quantifying the impact of longline fisheries on adult survival in the black-footed albatross. Journal of Applied Ecology 44, 942–952
447. Véran, S. and J.-D. Lebreton (2008), The potential of integrated modelling in conservation biology: a case study of the black-footed albatross (Phoebastria nigripes). The Canadian Journal of Statistics 36, 85–98
448. Vounatsou, P. and A. F. M. Smith (1995), Bayesian analysis of ring-recovery data via Markov chain Monte Carlo. Biometrics 51, 687–708
449. Wang, J.-P. (2010), Estimating the species richness by a Poisson-compound Gamma model. Biometrika 97, 727–740
450. Wang, J.-P. and B. G. Lindsay (2005), A penalized nonparametric maximum likelihood approach to species richness estimation. Journal of the American Statistical Association 100, 942–959
451. Welsh, A. H., D. B. Lidenmayer and C. F. Donnelly (2013), Fitting and interpreting occupancy models. PLOSOne 8, e52015
452. White, G. C. and K. P. Burnham (1999), Program Mark: survival estimation from populations of marked animals. Bird study 46, S120–S139
453. Williams, B. K., J. D. Nichols and M. J. Conroy (2002), Analysis and Management of Animal Populations. Academic Press, San Diego, California
454. Winiarski, K. J., D. L. Miller, P. W. C. Paton and S. R. McWilliams (2014), A spatial conservation prioritization approach for protecting marine brids given proposed off-shore wind energy development. Biological Conservation 169, 79–88
455. Wintrebert, C., A. H. Zwinderman, E. Cam, R. Pradel and J. C. Van Houwelingen (2005), Joint modeling of breeding and survival of Rissa tridactyla using frailty models. Ecological Modelling 181, 203–213
456. Wright, J. A., R. J. Barker, M. R. Schofield, A. C. Frantz, A. E. Byrom and D. M. Gleeson (2009), Incorporating genotype uncertainty into mark-recapture–type models for estimating abundance using DNA samples. Biometrics 65, 833–840
457. Yang, H.-C. and A. Chao (2005), Modeling animals’ behavioural response by Markov chain models for capture-recapture experiments. Biometrics 61, 1010–1017
458. Yang, Y. and K. C. Land (2013), Age-Period-Cohort analysis. Chapman & Hall, CRC Press, Boca Raton
459. Yip, P., L. Xi, A. Chao and W. H. Hwang (2000), Estimating the population size with a behavioural response in capture-recapture experiments. Environmental and Ecological Statistics 7, 405–414
460. Young, E. D. V. (2002), Statistical Methods for Timed Species Counts. Master’s thesis, University of Kent
461. Zelterman, D. (1988), Robust estimation in truncated discrete distributions with applications to capture-recapture experiments. Journal of Statistical Planning and Inference 18, 225–237
462. Zheng, C., O. Ovaskainen, M. Saastamoinen and I. Hanski (2007), Age-dependent survival analyzed with Bayesian models of mark-recapture data. Ecology 88, 1970–1976
463. Zippin, C. (1956), An evaluation of the removal method of estimating animal populations. Biometrics 12, 163–189
464. Zucchini, W. and I. L. MacDonald (1999), Hidden Markov Models for Time Series: An introduction using R. Chapman & Hall, CRC Press, Boca Raton