A selected bibliography
Azevedo FC; F G Lemos, M C
Freitas-Junior, D G Rocha, F C C Azevedo. 2018. Puma activity
patterns and temporal overlap with prey in a human-modified landscape at
Southeastern Brazil. Journal of Zoology, accepted. ● Used the
Bornand, C N, M Kéry, L Bueche, M Fischer 2014. Hide and seek in vegetation: time-to-detection is an efficient design for estimating detectability and occurrence. Methods in Ecology and Evolution 5(5): 433-442.
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, 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.
Butcher, J A; J E Groce; C M Lituma; M C Cocimano; Y Sánchez-Johnson, et al. 2007. Persistent controversy in statistical approaches in wildlife sciences: a perspective of students. J Wildlife Management 71:2142-2144.
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!
Colwell, R K; A Chao; N J Gotelli; S-Y Lin; C X Mao; R L Chazdon; J T Longino. 2012. Models and estimators linking individual-based and sample-based rarefaction, extrapolation and comparison of assemblages. Journal of Plant Ecology 5:3-21. 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 6:1104-1123 ● 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).
Ergon, Torbjřrn & Beth Gardner 2014. Separating mortality and emigration: modelling space use, dispersal and survival with robust-design spatial-capture-recapture data. Methods in Ecology and Evolution, 5, 1327-1336. ● 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 null-hypothesis significance testing on statistical reporting practices in conservation biology. Conservation Biology 20:1539-1544.
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 12:42-58. ● The origin of "Fisher's alpha" index of diversity.
Galipaud, M; M A F Gillingham; F-X Dechaume-Moncharmont. 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, 1558-1678. ● 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.
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.
Guillera-Arroita, 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): 301-317.
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 124:35-48. ● 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.
Hines, Nichols, Royle, MacKenzie, Gopalaswamy, Kumar, Karanth 2010. Tigers on trails: occupancy modeling for cluster sampling. Ecological Applications 20(5): 1456-1466. ● Describe analysis of spatially-replicated 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): 3-28. ● An excellent review using the Swiss willow tit data set, including WAIC. There are corrections to the code here.
Johnson, D S; P B Conn, M B Hooten, J C
Ray, B A Pond 2013. Spatial occupancy models for large data sets. Ecology
● Bayesian analysis of spatially-autocorrelated
occupancy data, implemented in the
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 101:4854-4858. (Available on line at http://www.ncbi.nlm.nih.gov/pmc/articles/PMC387338/) ● Background to the Kanha closed captures data set.
Kéry, M; J A Royle 2016
Applied hierarchical modeling in ecology: Analysis of distribution,
abundance and species richness in R and BUGS Vol 1. Amsterdam etc,
● An in-depth 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 on-line.
Kruschke, J K 2013. Bayesian estimation supersedes the t test.
Journal of Experimental Psychology: General, 142, 573-603.
● 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 40:1102-1111. ● ...or more to the point, dung and nest persistence times.
Lebreton, J-D; 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, 67-118.
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 41:454-462
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 83:2248-2255 ● 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.
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 38:349-363.
Maurer, B A; B J McGill. 2011. Measurement of species diversity. 55-64 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".
Morrogh-Bernard, H; S Husson; S E Page; J O Rieley. 2003. Population status of the Bornean orang-utan (Pongo pygmaeus) in the Sebangau peat swamp forest, Central Kalimantan, Indonesia. Biological Conservation 110:141-152.
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.
Rényi, A. 1961. On measures of entropy and information. Pages p 547-561 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, 2:565-580, 1976.
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 capture-recapture 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, 53-62.
Russon, A E; A Erman; R Dennis. 2001. The population and distribution of Orang-utans (Pongo pygmaeus pygmaeus) in and around Danau Sentarum Wildlife Reserve, West Kalimantan, Indonesia. Biological Conservation 97:21-28.
Shannon, C E. 1948. A mathematical theory of communication. Bell System Technical Journal 27:379-423 (link) ● The original paper on diversity; read this if you want to use the Shannon-Wiener index!
Tobler, M W, A Zúńiga Hartley, S E Carrillo-Percastegui, G V N Powell 2015. Spatiotemporal hierarchical modelling of species richness and occupancy using camera trap data. Journal of Applied Ecology 52(2): 413-421.
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: 109-118. ● 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 129-147 in Nadler, R D, B F M Galdikas, L K Sheeran, and N Rosen, editors. The neglected ape. Plenum, New York.
Vehtari, A; Gelman A; Gabry J. 2016. Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC. Statistics and Computing. doi: 10.1007/s11222-016-9696-4 (link).
Vucetich, J A; R O Peterson; C L Schaefer. 2002. The effect of prey and predator densities on wolf predation. Ecology 83:3003-3013 ● 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. 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 15:1342-1350 ● 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, 606-613. ● They used unpaired cameras and analysed the data for left flanks and right flanks separately.