A selected bibliography 

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Amstrup, S C; T L McDonald; B F J Manly, editors. 2005. Handbook of capturerecapture analysis. Princeton University Press, Princeton NJ Anderson, D R; K P Burnham; W L Thompson. 2000. Null hypothesis testing: problems, prevalence, and an alternative. J Wildlife Management 64:912923. Arnold, T W. 2010. Uninformative parameters and model selection using Akaike’s Information Criterion. Journal of Wildlife Management 74(6): 11751178 Azevedo FC; F G Lemos, M C
FreitasJunior, D G Rocha, F C C Azevedo. 2018. Puma activity
patterns and temporal overlap with prey in a humanmodified landscape at
Southeastern Brazil. Journal of Zoology, accepted. ● Used the Berger, J O; D A Berry. 1988. Statistical analysis and the illusion of objectivity. American Scientist 76:159165 Berger, W H; F L Parker. 1970. Diversity of planktonic Foramenifera in deep sea sediments. Science 168:13451347.● Origin of BergerParker index of divrsity. Bierregaard, R O, jr; T E Lovejoy; V Kapos; A A dos Santos; R W Hutchings. 1992. The biological dynamics of tropical forest fragments. BioScience, 42, 859866. Bolker, B M 2008. Ecological Models and Data in R. Princeton University Press, Princeton. Bolstad, W M 2004. Introduction to Bayesian statistics. WileyInterscience, Hoboken NJ. Bornand, C N, M Kéry, L Bueche, M Fischer 2014. Hide and seek in vegetation: timetodetection is an efficient design for estimating detectability and occurrence. Methods in Ecology and Evolution 5(5): 433442. Box, George E P 1976. Science and statistics. Journal of the American Statistical Association, 71, 791799. ● First use of the "All models are wrong" aphorism. Buckland, S T; D R Anderson; K P Burnham; J L Laake; D L Borchers; L Thomas 2001. Introduction to distance sampling: estimating abundance of biological populations. Oxford University Press, Oxford, UK. ● Essential reading for anyone doing distance sampling. Buckland, S T; D R Anderson; K P Burnham; J L Laake; D L Borchers; L Thomas, editors. 2004. Advanced distance sampling. Oxford University Press, Oxford, UK Buckland, S T, E A Rexstad; T A Marques; C S Oedekoven 2015. Distance sampling: Methods and applications, Springer. ● Compendium of recent developments in distance sampling, including Bayesian methods. Burnham, K P; D R Anderson 2002. Model selection and multimodel inference. SpringerVerlag ● A highly influential book that introduced AIC to ecologists; still an essential introduction. Butcher, J A; J E Groce; C M Lituma; M C Cocimano; Y SánchezJohnson, et al. 2007. Persistent controversy in statistical approaches in wildlife sciences: a perspective of students. J Wildlife Management 71:21422144. Chamberlin, T C. 1890. The method of multiple working hypotheses: With this method the dangers of parental affection for a favorite theory can be circumvented. Science 15:92. ● Argued for multiple models rather than looking for true/false hypotheses... way back then! Chao, A; TJ Shen. 2003. Nonparametric estimation of Shannon's index of diversity when there are unseen species in sample. Environmental and Ecological Statistics 10:429443. Christensen, R. 2005. Testing Fisher, Neyman, Pearson, and Bayes. American Statistician 59:121126 ● In interesting comparison of the different frequentist approaches and their relationship to Bayes. Cohen, J. 1994. The earth is round (p < .05). American Psychologist 49:9971003. ● An early critique of the mindless application of NHST, still often quoted. Colwell, R K; A Chao; N J Gotelli; SY Lin; C X Mao; R L Chazdon; J T Longino. 2012. Models and estimators linking individualbased and samplebased rarefaction, extrapolation and comparison of assemblages. Journal of Plant Ecology 5:321. link Cooch, E; G White 2010 (9th edition, but constantly updated). Program MARK: a gentle introduction. Available online in PDF format here Crome, F H J; M R Thomas; L A Moore. 1996. A novel Bayesian approach to assessing impacts of rain forest logging. Ecological Applications 6:11041123 ● One of the earliest applications of Bayesian methods to management. Faced with the need for "plain English" interpretations, they explored "Bayesian procedures, which allow straightforward probability statements to be made about specific cases." (p. 1104). Dalgaard, P 2002. Introductory Statistics with R. SpringerVerlag, New York. ● This was my introduction to doing statistical analysis in R. Efford, M. 2004. Density estimation in livetrapping studies. Oikos, 106, 598610 ● The first approach to SECR, now superseded by MLE methods in the 2009 paper. Efford, M G; D K Dawson; D L Borchers 2009. Population density estimated from locations of individuals on a passive detector array. Ecology 90(10): 26762682. Efford, M G; G Mowat 2014. Compensatory heterogeneity in spatially explicit capturerecapture data. Ecology 95(5): 13411348. ● Explanation of the "a0" parameterisation in SECR. Efron, B; R J Tibshirani 1993. An introduction to the bootstrap. Chapman and Hall/CRC, London. Ergon, Torbjřrn & Beth Gardner 2014. Separating mortality and emigration: modelling space use, dispersal and survival with robustdesign spatialcapturerecapture data. Methods in Ecology and Evolution, 5, 13271336. ● An application of SCR to a CJS survival model; some good ideas on SCR fit diagnostics and useful code. Fidler, F; M A Burgman; G Cumming; R Buttrose; N Thomason. 2006. Impact of criticism of nullhypothesis significance testing on statistical reporting practices in conservation biology. Conservation Biology 20:15391544. Fisher, R A 1925, 1946. Statistical methods for research workers. Oliver and Boyd, Edinburgh. (Page numbers refer to the 10 edition, 1946). Fisher, R A; A S Corbet; C B Williams. 1943. The relation between the number of species and the number of individuals in a random sample of an animal population. J Animal Ecology 12:4258. ● The origin of "Fisher's alpha" index of diversity. Fox, J. 2002. An R and SPLUS Companion to Applied Regression, Sage Publications Inc, Thousand Oaks CA. Galipaud, M; M A F Gillingham; FX DechaumeMoncharmont. 2017. A farewell to the sum of Akaike weights: the benefits of alternative metrics for variable importance estimations in model selection. Methods in Ecology and Evolution, 8, 15581678. ● Much of the paper is concerned with deficiencies in sum of weights as a measure of importance; section 5.2 deals with standardised parameter estimates, which they recommend. Gardner, B; J Reppucci, M Lucherini, J A Royle. 2010. Spatially explicit inference for open populations: estimating demographic parameters from cameratrap studies. Ecology, 91, 33763383. Gelman, A 2006. Prior distributions for variance parameters in hierarchical models. Bayesian Analysis 1(3): 515534. Gelman, A; J B Carlin; H S Stern; D B Dunson; A Vehtari; D B Rubin. 2014. Bayesian data analysis, 3 edn. Chapman and Hall/CRC, Boca Raton Gelman, A; J Hill 2007. Data analysis using regression and multilevel/hierarchical models. Cambridge University Press. ● A nice introduction to hierarchical modelling with BUGS code; most of the examples come from the social sciences. Gelman, A; H Stern. 2006. The difference between “significant” and “not significant” is not itself statistically significant. American Statistician 60(4):328331. Gotelli, N J; A M Ellison. 2004. A primer of ecological statistics. Sinauer Associates, Sunderland MA. GuilleraArroita, G, B J T Morgan, M S Ridout, M Linkie 2011. Species occupancy modeling for detection data collected along a transect." Journal of Agricultural, Biological, and Environmental Statistics 16(3): 301317. Hedges, S; D Lawson. 2006. Dung survey standards for the MIKE programme. CITES MIKE Central Coordinating Unit, Nairobi, Kenya. Hedges, S; M J Tyson; A F Sitompul; M F Kinnaird; D Gunaryadi; Aslan. 2005. Distribution, status, and conservation needs of Asian elephants (Elephas maximus) in Lampung Province, Sumatra, Indonesia. Biological Conservation 124:3548. ● Application of dung surveys to estimate populations. Hilborn, R; M Mangel 1997. The ecological detective: confronting models with data. Princeton University Press, Princeton NJ. ● An early call to use models n ecology. use likelihood ratio, AIC and Bayesian methods of model selection. Hill, M O. 1973. Diversity and evenness: a unifying notation and its consequences. Ecology 54:427431. ● Introduction of "Hill's numbers" for quantifying diversity. Hines, Nichols, Royle, MacKenzie, Gopalaswamy, Kumar, Karanth 2010. Tigers on trails: occupancy modeling for cluster sampling. Ecological Applications 20(5): 14561466. ● Describe analysis of spatiallyreplicated occupancy data when observations on adjacent replicates (eg, segments of a transect) are correlated. Hobbs, N T; M B Hooten. 2015. Bayesian models: a statistical primer for ecologists. Princeton and Oxford, Princeton University Press. ● A theoretical introduction to the topic with no computer code (!); intimidating at first glance, but the authors take us through progressively and clearly. Hooten, M B; N T Hobbs 2015. A guide to Bayesian model selection for ecologists. Ecological Monographs 85(1): 328. ● An excellent review using the Swiss willow tit data set, including WAIC. There are corrections to the code here. Johnson, D H. 1999. The insignificance of statistical hypothesis testing. J Wildlife Management 63:763772. Johnson, D S; P B Conn, M B Hooten, J C
Ray, B A Pond 2013. Spatial occupancy models for large data sets. Ecology
94(4): 801808.
● Bayesian analysis of spatiallyautocorrelated
occupancy data, implemented in the Jost, L. 2006. Entropy and diversity. Oikos 113:363375. ● Caustic comments on the use of entropy for diversity indexing; The only sensible indices are in units of species. Karanth, K U; J D Nichols; N S Kumar; W A Link; J E Hines. 2004. Tigers and their prey: Predicting carnivore densities from prey abundance. Proceedings of the National Academy of Sciences 101:48544858. (Available on line at http://www.ncbi.nlm.nih.gov/pmc/articles/PMC387338/) ● Background to the Kanha closed captures data set. Kéry, M 2010. Introduction to WinBUGS for ecologists: A Bayesian approach to regression, ANOVA, mixed models and related analyses. Academic Press.
Kéry, M; J A Royle 2016
AHM book.
Applied hierarchical modeling in ecology: Analysis of distribution,
abundance and species richness in R and BUGS Vol 1. Amsterdam etc,
Elsevier.
● An indepth treatment of a range of wildlife models, with
full R and BUGS/JAGS code to run the examples. MLE analyses use the
Kéry, M; M Schaub 2012. Bayesian population analysis using WinBUGS  a hierarchical perspective. Academic Press. ● A wide range of wildlife models with full R and WinBUGS code, and JAGS code is available online. King, R; B J T Morgan, O Gimenez, S P Brooks 2010. Bayesian analysis for population ecology. Boca Raton, Chapman & Hall/CRC. Kruschke, J K 2011. Doing Bayesian data analysis: a tutorial with R and BUGS. Elsevier, Amsterdam Kruschke, J K 2013. Bayesian estimation supersedes the t test.
Journal of Experimental Psychology: General, 142, 573603.
● Background to the Kruschke, J K 2014 DBDA2. Doing Bayesian data analysis: a tutorial with R, JAGS and Stan 2nd Edition. Elsevier, Amsterdam Laing, S E; S T Buckland; R W Burn; D Lambie; A Amphlett. 2003. Dung and nest surveys: estimating decay rates. J Applied Ecology 40:11021111. ● ...or more to the point, dung and nest persistence times. Lebreton, JD; K P Burnham; J Clobert; D R Anderson. 1992. Modeling survival and testing biological hypotheses using marked animals: a unified approach with case studies. Ecological Monographs, 62, 67118. Link, W A; R J Barker 2010. Bayesian Inference with ecological applications. Academic Press, San Diego CA. Longino, J T; J Coddington; R K Colwell. 2002. The ant fauna of a tropical rain forest: estimating species richness three different ways. Ecology 83:689702 Lynam, A J; R Laidlaw; Wan Shaharuddin Wan Noordin; S Elagupillay; E L Bennett. 2007. Assessing the conservation status of the tiger Panthera tigris at priority sites in Peninsular Malaysia. Oryx 41:454462 Magurran, A E 2004. Measuring biological diversity. Blackwell. MacKenzie, D I; J D Nichols; G B Lachman; S Droege; J A Royle; C A Langtimm. 2002. Estimating site occupancy rates when detection probabilities are less than one. Ecology 83:22482255 ● The first paper to estimate occupancy by jointly estimating probability of occupancy and probability of detection. MacKenzie, D I; J D Nichols; A J Royle; K H Pollock; L L Bailey; J E Hines 2006. Occupancy estimation and modeling : inferring patterns and dynamics of species occurrence. Elsevier Publishing. ● A good book on occupancy; does not cover many of the more recent developments and doesn't include Bayesian analysis. McElreath, R. 2016. Statistical rethinking: a Bayesian course with examples in R and Stan. Boca Raton etc, CRC Press. ● An excellent introduction to modelling from a Bayesian perspective. It gets into quite deep water with AIC and other information criteria, maximum entropy priors, etc, but clearly explained and well paced. McGarvey, D J. 2007. Merging precaution with sound science under the Endangered Species Act. BioScience 57:6570. Marques, F F C; S T Buckland; D Goffin; C E Dixon; D L Borchers; B A Mayle; A J Peace. 2001. Estimating deer abundance from line transect surveys of dung: sika deer in southern Scotland. J Applied Ecology 38:349363. Maurer, B A; B J McGill. 2011. Measurement of species diversity. 5564 in Magurran, A E, and B J McGill, editors. Biological diversity: frontiers in measurement and assessment. Oxford University Press, Oxford, New York NY Matthiopoulos, J. 2011. How to be a quantitative ecologist: The 'A to R' of green mathematics and statistics, John Wiley & Sons. ● A nice, general introduction to quantitative methods intended for "refugees from high school math". Morrison, M L; W M Block; M D Strickland; W L Kendall. 2001. Wildlife study design Springer, New York. MorroghBernard, H; S Husson; S E Page; J O Rieley. 2003. Population status of the Bornean orangutan (Pongo pygmaeus) in the Sebangau peat swamp forest, Central Kalimantan, Indonesia. Biological Conservation 110:141152. Nouvellet, P; G S A Rasmussen, D W Macdonald, F Courchamp. 2012. Noisy clocks and silent sunrises: measurement methods of daily activity pattern. Journal of Zoology 286:179184. Ntzoufras, I 2009. Bayesian modeling using WinBUGS. Wiley, Hoboken NJ. Otis, D.L.; K P Burnham; G C White; D R Anderson. 1978. Statistical inference from capture data on closed animal populations. Wildlife Monographs, 62, 1135. Payne, J; C M Francis; K Phillipps. 1985. A field guide to the mammals of Borneo. The Sabah Society and WWF Malaysia. Pollock, K H. 1982. A capturerecapture design robust to unequal probability of capture. Journal of Wildlife Management, 46, 752757. Popper, K. 1959. The logic of scientific discovery. Bantam Books Quinn, G P; M J Keough. 2002. Experimental design and data analysis for biologists. Cambridge University Press, Cambridge UK. Ramsey, F L; D W Schafer 2002. The statistical sleuth: a course in methods of data analysis. Duxbury Press, Belmont CA. ● If you need an introduction to NHST, this is a good modern treatment with many biological examples. Rennolls, K; Y Laumonier. 2006. A new local estimator of regional species diversity, in terms of ‘shadow species’, with a case study from Sumatra. J Tropical Ecology 22:321329. Rényi, A. 1961. On measures of entropy and information. Pages p 547561 in Neyman, J, editor. 4th Berkeley symposium on mathematical statistics and probability. University of California Press, Berkeley CA, Berkeley. Reprinted in Pal Turan (Hrsg), Selected papers of Alfred Rényi. Akademiai Kiado, Budapest, 2:565580, 1976. Robinson, D H; H Wainer. 2002. On the past and future of null hypothesis significance testing. J Wildlife Management 66:263271 Royall, R M 1997. Statistical evidence: a likelihood paradigm. Chapman and Hall/CRC, New York NY ● Argues for keeping separate the questions: What do the data tell me? What do I believe? What should I do?
Royle, J A; R B Chandler; R Sollmann; B
Gardner 2014 SCR book. Spatial capturerecapture Elsevier.
● The standard book on SECR, going into
lots of detail of Bayesian analysis in JAGS but also covering MLE
methods and the Royle, J A; R M Dorazio 2008. Hierarchical modeling and inference in ecology: the analysis of data from populations, metapopulations and communities. Academic Press. ● The seminal book that introduced hierarchical modelling concepts and Bayesian analysis to ecologists. Royle, J A; A K Fuller, C Sutherland 2016. Spatial capture–recapture models allowing Markovian transience or dispersal. Population Ecology, 58, 5362. Royle, J A; J D Nichols. 2003. Estimating abundance from repeated presenceabsence data or point counts. Ecology 84:777790 Russon, A E; A Erman; R Dennis. 2001. The population and distribution of Orangutans (Pongo pygmaeus pygmaeus) in and around Danau Sentarum Wildlife Reserve, West Kalimantan, Indonesia. Biological Conservation 97:2128. Shannon, C E. 1948. A mathematical theory of communication. Bell System Technical Journal 27:379423 (link) ● The original paper on diversity; read this if you want to use the ShannonWiener index! Simpson, E H. 1949. Measurement of diversity. Nature 163:688 ● And read this if you want to use Simpson's index! Snedecor, G W. 1937. Statistical Methods Applied to Experiments in Agriculture and Biology Stephens, P A; S W Buskirk; C Martínez del Rio. 2007. Inference in ecology and evolution. Trends in Ecology and Evolution 22:192197 Tobler, M W, A Zúńiga Hartley, S E CarrilloPercastegui, G V N Powell 2015. Spatiotemporal hierarchical modelling of species richness and occupancy using camera trap data. Journal of Applied Ecology 52(2): 413421. Tobler, M W; G V N Powell 2013. Estimating jaguar densities with camera traps: Problems with current designs and recommendations for future studies. Biological Conservation 159: 109118. ● Main recommendation was that researchers use simulations to experiment with different designs. van Schaik, C P; A Priatna; D Priatna. 1995. Population estimates and habitat preferences of orangutans based on line transects of nests. pp 129147 in Nadler, R D, B F M Galdikas, L K Sheeran, and N Rosen, editors. The neglected ape. Plenum, New York. Venables, W N; B D Ripley 2002. Modern applied statistics with S. SpringerVerlag, New York. Vehtari, A; Gelman A; Gabry J. 2016. Practical Bayesian model evaluation using leaveoneout crossvalidation and WAIC. Statistics and Computing. doi: 10.1007/s1122201696964 (link). Vucetich, J A; R O Peterson; C L Schaefer. 2002. The effect of prey and predator densities on wolf predation. Ecology 83:30033013 ● Nice examples of the use of AIC to choose between models which are not variations on the regression theme  and are not nested. Wade, P R. 2000. "Bayesian methods in conservation biology." Conservation Biology 14(5): 13081316. Wade, P R. 2001. The conservation of exploited species in an uncertain world: novel methods and the failure of traditional techniques. Ch 6 in Reynolds, J, G M Mace, K H Redford, and J G Robinson, editors. Conservation of exploited species. Cambridge University Press, Cambridge UK. ● Compares NHST with Bayesian analysis as a basis for decision making, showing how Bayes is more useful for management. This convinced me back in 2003 that we needed to use Bayes for wildlife data analysis. Walsh, P D; L J T White. 2005. Evaluating the steady state assumption: simulations of gorilla nest decay. Ecological Applications 15:13421350 ● Debunk the idea of a simple relationship between nest counts and primate numbers. Changes in nest counts tell you more about the weather than the animals. Wang, S W; D W Macdonald. 2009. The use of camera traps for estimating tiger and leopard populations in the high altitude mountains of Bhutan. Biological Conservation, 142, 606613. ● They used unpaired cameras and analysed the data for left flanks and right flanks separately. Yates, F. 1935. Complex experiments. J Royal Statistical Society Supplement 2:181247 