CRAN Task View: Analysis of ornithological data

Maintainer: Marc-Olivier Beausoleil
Contact: marc-olivier.beausoleil at
Version: 2021-08-10


The study of ornithology is vast and multidisciplinary in essence. Thus, this “Ornithometrics” ( *ornitho-* ; ‘bird’ and *-metric* ; ‘relating to measurement’) task view contains a collection of packages that can process data taken on or from birds or the environmental variables that are in association with bird activities. To my knowledge, the word Ornithometrics has been used once in a mathematical journal (Underhill 1989).

The headers of the table of content were made to facilitate navigation, but bear in mind that some packages might fall in multiple categories. Other task views could be consulted for broader coverage of topics including ecology and environment (known as the Environmetrics task view) and spatial analysis (which can be found in the Spatial task view). The rest of the CRAN task views can be seen here. There are also independent task views for various topics on GitHub.

Some packages might require specific R versions or RStudio versions.

This task view is made to encourage researchers to work with ornithological data and adopt best practices. Effort was made to cite all the packages as accurately as possible (see reference section and the .bib file here ). In addition, there are resource sections that include Atlases from various countries, states and provinces, but also links to databases that researchers can use to answer questions in ornithology (see the section titled Datasets and atlases ). All references were exported in the style of journal “Ecology”. The references do not include the version of the R packages, but it is highly encouraged to do so when citing packages ( citation(package = "package_name")).

Please contact me to suggest packages or ideas for this task view.

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Communication and acoustic analysis

  • monitoR is a package for bioacoustics detection and monitoring (Hafner and Katz 2018). With the help of viewSpec(), sound files can be viewed as spectrograms. You might want to try setting the player to playback audio to setWavPlayer("afplay") on Mac or setWavPlayer("rhythm-box") on Ubuntu. You might be interested in the AMMonitor package as well.
  • Rraven lets you connect R and the Raven program by The Cornell Lab of Ornithology (Araya-Salas 2020)
  • SongEvo contains functions to simulate (function SongEvo()) cultural evolution in bird song (Danner et al. 2019)
  • soundecology allows the calculation of a wide array of acoustic indices such as the acoustic Complexity Index (ACI), the Normalized Difference Soundscape Index (NDSI), and Acoustic Diversity and Evenness indices (ADI and AEI) (Villanueva-Rivera and Pijanowski 2018)
  • seewave includes a vast library of functions to generate and analyse sound (Sueur, Aubin and Simonis 2008). The book Sound analysis and synthesis with R is a resource that will let you explore multiple of its functionalities (Sueur 2018).
  • tuneR allows the analysis of sound (Ligges et al. 2018)
  • warbleR: Github package to analyse the structure of animal acoustic signals and extract acoustic parameters, visualize spectrograms, apply batch processes and more (Araya-Salas and Smith-Vidaurre 2017). The query_xc() function can search and download sounds from Xeno-canto.


  • acmeR is designed for calculation of Avian and Chiropteran (bat) Mortality Estimators (ACME) by wind turbines (Wolpert and Coleman 2015). You might be interested in the carcass package which implements more functions for estimation of fatalities from collisions with human-made constructions (Korner-Nievergelt et al. 2015). GenEst is another package to estimate bird/bat mortality at wind and solar power facilities (Dalthorp et al. 2018; Dalthorp et al. 2021).
  • windAC similar to acmeR and carcass, but allow an area correction (AC) for carcasses that fall outside the searched area (Studyvin, Rabie and Riser-Espinoza 2020)
  • placer is designed to assess the prevalence of plastic debris in bird nests (Tavares et al. 2020).
  • prioritizr allows the development of models (in particular, mixed integer linear programming (MILP)) to help solve conservation planning (Hanson et al. 2021). Might also require the Gurobi optimization software and the ‘gurobi’ R package
  • rredlist: provided you requested and have an API key, the package allows access to the IUCN red list data (Chamberlain 2020)
  • red can be used to do spatial analyses using observed occurences or estimates ranges (Cardoso 2017)
  • track2kba: a collection of functions used to determine important biodiversity areas using tracking data (Beal et al. 2020).
  • There is no specific package for long-term studies, but you might be interested in looking into the TimeSeries task view.


  • Please consult the Genetics Task View about statistical genetics.
  • adegenet contains a diverse set of functions that facilitates the exploration of genetic and genomics data (Jombart 2008; Jombart and Ahmed 2011)
  • If you are interested in building an Animal model, please refer to the MCMCglmm package (Hadfield 2010) and refer to the paper by Wilson et al. (2010).
  • Researchers interested in sample inference from amplicon data (e.g., studies looking at gut microbiome) might look into the dada2 package.

Mark-recapture analysis

  • detect can be used to analyse occupancy and count data using various models (Sólymos, Moreno and Lele 2020).
  • marked is a package for building mark-recapture model including Cormack-Jolly-Seber (CJS) models, Bayesian Markov Chain Monte Carlo (MCMC) methods, and other kinds of structures (Laake, Johnson and Conn 2013)
  • mrds stands for “Mark-Recapture Distance Sampling” and calculates animal abundances (Laake et al. 2020)
  • multimark includes models, accounting for imperfect detection, that can deal with non-invasive marks from different types of sources (images, fluctuating asymetry in colour patterns), to estimate animal abundance and demographic parameters (McClintock 2015)
  • nimbleSCR uses “nimble” to implement Spatial Capture-Recapture (SCR) and Open Population Spatial Capture-Recapture (OPSCR) models (Bischof et al. 2021)
  • openCR: Open population Capture-Recapture package to fit non-spatiatial ans spatial models (Efford 2020)
  • oSCR: open spatial capture-recapture. A the project webpage has details about tutorials and workshops (Sutherland, Royle and Linden 2019)
  • PresenceAbsence (Freeman and Moisen 2008)
  • R2ucare (Gimenez et al. 2018)
  • Rcapture (Rivest and Baillargeon 2019)
  • ringR: includes functions to manipulate ringing data (Harnos, Fehérvári and Csörgő 2015)
  • RMark (Laake 2013)
  • scrbook (Royle et al. 2020).
  • secr (Efford 2020)
  • unmarked (Fiske and Chandler 2011)

Movement ecology, navigation, telemetry, GPS, RFID, habitat use

Relocation of animals: Finding the location of animals can be done via a diversity of methods such as Very High Frequency (VHF) radio waves emitters, Global Positioning System (GPS), semi-automated data collection using MOTUS Wildlefe Tracking System and other techniques. It is recommended to look at the “Space and habitat use characterization” section of the Tracking task view to learn about Home ranges, Habitat use, and Non-conventional approaches for space use. I. Bartomeus has a page in which preference indexes calculations in R are demonstrated.

  • adehabitatHR: Home Range Estimation (Calenge 2006)
  • adehabitatHS: Analysis of Habitat Selection by Animals (Calenge 2006)
  • adehabitatLT: Analysis of Animal Movements (Calenge 2006)
  • bioRad uses radar imagery to infer animals movement (Dokter et al. 2019)
  • cavityuse: Determine cavity use from geolocator light data (LaZerte 2021)
  • crawl random walk models for animal telemetry data (Johnson et al. 2008; Johnson and London 2018)
  • ctmm: (Calabrese, Fleming and Gurarie 2016)
  • dismo (Hijmans et al. 2020) and rmaxent (Baumgartner and Wilson 2017)
  • diveMove processes time-depth recorder (TDR) data (Luque 2007)
  • feedr (LaZerte 2021)
  • FLightR Spatio-temporal relocation of animals using light geolocators (Rakhimberdiev et al. 2015; Rakhimberdiev et al. 2016; Rakhimberdiev et al. 2017; Rakhimberdiev and Saveliev 2020)
  • gaiah lets you find the find the breeding origin of migrant birds (Ruegg et al. 2017; Anderson 2020)
  • GeoLight location of animals using light intensity measurements over time (Lisovski and Hahn 2012)
  • MigConnectivity offers a framework to describe how populations co-occur in a year, i.e., migratory connectivity (Cohen et al. 2018)
  • migrateR : animal movement behavior analysis (Spitz 2019)
  • momentuHMM allows animal movement analysis using hidden Markov models (McClintock and Michelot 2018)
  • Motus. The Motus book can be seen from this link (Brzustowski and Lepage 2021)
  • moveWindSpeed: Estimate wind speeds from bird trajectories (Kranstauber and Weinzierl 2019)
  • probGLS probabilistic algorithm for geolocation data (Merkel 2021)
  • razimuth : (Gerber et al. 2018)
  • rangeBuilder (Cox, et al. 2016)
  • ResourceSelection: (Lele and Keim 2006; Lele 2009; Sólymos and Lele 2016)
  • rhr : reproducible home range analysis with R (Signer and Balkenhol 2015)
  • seabiRds (Patterson 2021)
  • SGAT for animal geolocation data (Sumner, Wotherspoon and Hindell 2009; Lisovski and Hahn 2012)
  • sigloc : The sigloc (Signal Location Estimation; Berg 2015) package is now archived on the CRAN.
  • TwGeos. light-level geolocation (Lisovski, Wotherspoon and Sumner 2016)
  • wildlifeDI (Long et al. 2014)


  • Phylogenetics: task view on phylogenetics which includes packages to draw trees, functions to manipulate tress, model and simulate data, calculate divergence times, make inferences, and much more. There are even packages about community and microbial ecology which might be interesting if one wants to study the gut microbiome of birds.
  • adephylo: Exploratory Analyses for the Phylogenetic Comparative Method (Jombart, Balloux and Dray 2010)
  • phylotaR : Retrieval of orthologous DNA from GenBank (Bennett et al. 2018)
  • taxize: (Chamberlain and Szocs 2013; Chamberlain et al. 2020)

Physiology, phenotype, phenology and life histories

  • afpt can be used to estimate, model, predict flight parameters with an aerodynamic model (Klein Heerenbrink, Johansson and Hedenstrom 2015; Klein Heerenbrink 2020)
  • bwimage (Biagolini Jr., C. 2020)
  • flying and FlyingR: (Masinde 2020)
  • geomorph (Collyer and Adams 2018, 2021; Adams et al. 2021; Baken et al. 2021)
  • MixSIAR: Bayesian Mixing Models in R with which stable isotope mixing models can be used to reconstruct avian diet (Stock and Semmens 2016; Stock et al. 2018). Also, check out the package siar to fit Bayesian model to isotopic data on organisms (Gaussian likelihood with mixture dirichlet prior) (Parnell and Jackson 2013) and the package simmr replacing the package “siar” (Parnell 2021). For trophic position, consult the tRophicPosition package (Quezada-Romegialli et al. 2018; Quezada-Romegialli, Jackson and Harrod 2019).
  • moult: Models for analysing moult in birds (Erni et al. 2013)
  • moultmcmc : Bayesian inference for moult phenology models (Boersch-Supan 2021)
  • pavo: color analysis in birds and more (Maia et al. 2019).
  • traits gathers species trait from various data centers including the Birdlife International/IUCN threat and habitat information and more (Chamberlain et al. 2020).

Population dynamics, community ecology, and Evolution

  • Distance (Miller et al. 2019)
  • dsm (Miller et al. 2021)
  • mgcv is useful to get fitness landscapes as smooth surface using generalized additive models (Wood 2003, 2004, 2011, 2017; Wood, Pya and Säfken 2016)
  • nicheROVER: Guide for using nicheROVER (Lysy, Stasko and Swanson 2014)
  • Environmetrics which include the famous community ecology package vegan (Oksanen et al. 2019)

Spatial analysis

  • mapview lets you plot interactive maps and save maps (Appelhans et al. 2020)
  • osmdata is a package importing the OpenStreetMap data which can be used in R (Padgham et al. 2017).
  • raster makes it possible to use raster objects in R (Hijmans 2020). It is useful when using remote sensing data (satellite imagery).
  • sf is a powerful package used to manipulate spatial objects (Pebesma 2018). Check out the requirements to install the package (in particular for GDAL, GEOS, PROJ).
  • sp (Pebesma and Bivand 2005; Bivand, Pebesma and Gómez-Rubio 2013).
  • tmap (Tennekes 2018) uses a syntax similar to ggplot2 (Wickham 2016) to create static or interactive maps.

Data and atlases

Citizen science have much success when it comes to birding. Bird observation through citizen science data is amazingly rich and available to download either by requesting the data or an application programming interface or API access.






Research miscellaneous

  • bSims: Bird Point Count Simulator (Sólymos 2019)
  • climwin: Climate window analysis (van de Pol et al. 2016)
  • emmeans (Lenth 2021)
  • Modeling and model comparison with packages like lme4 (Bates et al. 2015), MuMIn (Bartoń 2020) and AICcmodavg (Mazerolle 2020), INLA (integrated nested Laplace approximation) with inlabru allows you to build a wide variety of spatiotemporal models in a Bayesian framework that are computationally efficient (Bachl et al. 2019)
  • ggThemeAssist (Gross and Ottolinger 2016)
  • litsearchr (Grames et al. 2019, 2020)
  • patchwork (Pedersen 2020)
  • rjags is the R interface to Just Another Gibbs Sampler (JAGS) which allows flexible hierarchical Bayesian model construction (Plummer 2003)
  • rr2 (Ives 2018; Ives and Li 2018)
  • rstan can create advanced Bayesian models and has also wrappers (rstanarm) to implement common statistical methods (Brilleman et al. 2018; Stan Development Team 2020; Goodrich 2020)
  • tidyverse (Wickham et al. 2019)
  • visreg (Breheny and Burchett 2017)


  • Adams, D. C., M. L. Collyer, A. Kaliontzopoulou, and E. K. Baken. 2021. Geomorph: Software for geometric morphometric analyses.
  • Anderson, E. C. 2020. gaiah: Genetic and isotopic assignment accounting for habitat suitability.
  • Appelhans, T., F. Detsch, C. Reudenbach, and S. Woellauer. 2020. mapview: Interactive Viewing of Spatial Data in R.
  • Araya-Salas, M., and G. Smith-Vidaurre. 2017. warbleR: an r package to streamline analysis of animal acoustic signals. Methods in Ecology and Evolution 8:184–191.
  • Araya-Salas, M. 2020. Rraven: connecting R and Raven bioacoustic software.
  • Bachl, F. E., F. Lindgren, D. L. Borchers, and J. B. Illian. 2019. inlabru: an R package for Bayesian spatial modelling from ecological survey data. Methods in Ecology and Evolution 10:760–766.
  • Baken, E. K., M. L. Collyer, A. Kaliontzopoulou, and D. C. Adams. 2021. gmShiny and geomorph v4.0: new graphical interface and enhanced analytics for a comprehensive morphometric experience. Methods in Ecology and Evolution.
  • Bartoń, K. 2020. MuMIn: Multi-Model Inference.
  • Barve, V., and E. Hart. 2021. rinat: Access “iNaturalist” Data Through APIs.
  • Bates, D., M. Mächler, B. Bolker, and S. Walker. 2015. Fitting Linear Mixed-Effects Models Using lme4. Journal of Statistical Software 67:1–48.
  • Baumgartner, J., and P. Wilson. 2017. rmaxent: Tools for working with Maxent in R.
  • Beal, M., S. Oppel, J. Handley, L. Pearmain, V. Morera-Pujol, M. Miller, P. Taylor, Ben Lascelles, and M. Dias. 2020. BirdLifeInternational/track2kba.
  • Bennett, D. J., H. Hettling, D. Silvestro, A. Zizka, C. D. Bacon, S. Faurby, R. A. Vos, and A. Antonelli. 2018. phylotaR: An Automated Pipeline for Retrieving Orthologous DNA Sequences from GenBank in R. Life 8:20.
  • Berg, S. S. 2015. The package “sigloc” for the R software: a tool for triangulating transmitter locations in ground-based telemetry studies of wildlife populations. Bulletin of the Ecological Society of America 96:500–507.
  • Biagolini Jr, C. 2020. bwimage: Describe image patterns in natural structures.
  • Birds Canada. 2019. Motus Wildlife Tracking System. Port Rowan, Ontario. Available:
  • Birds Studies Canada. 2018. NatureCounts web application. Port Rowan, Ontario. Available:
  • Bischof, R., D. Turek, C. Milleret, T. Ergon, P. Dupont, and P. de Valpine. 2021. nimbleSCR: Spatial Capture-Recapture (SCR) Methods Using “nimble”.
  • Bivand, R., E. J. Pebesma, and V. Gómez-Rubio. 2013. Applied Spatial Data Analysis with R - Second Edition. Springer, New York, NY.
  • Boersch-Supan, P. 2021. moultmcmc: Bayesian Inference For Avian Moult Pheology Models.
  • Breheny, P., and W. Burchett. 2017. Visualization of regression models using visreg. The R Journal 9:56–71.
  • Brilleman, S. L., M. J. Crowther, M. Moreno-Betancur, J. B. Novik, and R. Wolfe. 2018. Joint longitudinal and time-to-event models via Stan.
  • Brzustowski, J., and D. Lepage. 2021. motus: Fetch and use data from the Motus Wildlife Tracking System.
  • Burnett, J. L., L. S. Wszola, and G. Palomo-Muñoz. 2019. bbsAssistant: An R package for downloading and handling data and information from the North American Breeding Bird Survey. The Journal of Open Source Software 4:1768.
  • Calabrese, J. M., C. H. Fleming, and E. Gurarie. 2016. ctmm: an R package for analyzing animal relocation data as a continuous-time stochastic process. Methods in Ecology and Evolution 7:1124–1132.
  • Calenge, C. 2006. The package “adehabitat” for the R software: A tool for the analysis of space and habitat use by animals. Ecological Modelling 197:516–519.
  • Cardoso, P. 2017. red - an R package to facilitate species red list assessments according to the IUCN criteria. Biodiversity Data Journal 5:e20530.
  • Chamberlain, S. 2020. rredlist: “IUCN” Red List Client.
  • Chamberlain, S. 2021. spocc: Interface to species occurrence data sources.
  • Chamberlain, S., and C. Boettiger. 2017. R Python, and Ruby clients for GBIF species occurrence data. PeerJ PrePrints:1–32.
  • Chamberlain, S., and E. Szöcs. 2013. taxize - taxonomic search and retrieval in R. F1000Research 2:191.
  • Chamberlain, S., E. Szöecs, Z. Foster, Z. Arendsee, C. Boettiger, K. Ram, I. Bartomeus, J. Baumgartner, J. ODonnell, J. Oksanen, B. G. Tzovaras, P. Marchand, V. Tran, M. Salmon, G. Li, and M. Grenié. 2020. taxize: Taxonomic information from around the web.
  • Chamberlain, S., V. Barve, D. McGlinn, D. Oldoni, P. Desmet, L. Geffert, and K. Ram. 2021. rgbif: Interface to the Global Biodiversity Information Facility API.
  • Chamberlain, S., Z. Foster, I. Bartomeus, D. LeBauer, C. Black, and D. Harris. 2020. traits: Species Trait Data from Around the Web.
  • Cohen, E. B., J. A. Hostetler, M. T. Hallworth, C. S. Rushing, T. S. Sillett, and P. P. Marra. 2018. Quantifying the strength of migratory connectivity. Methods in Ecology and Evolution 9:513–524.
  • Collyer, M. L., and D. C. Adams. 2018. RRPP: An R package for fitting linear models to high‐dimensional data using residual randomization. Methods in Ecology and Evolution 9:1772–1779.
  • Collyer, M. L., and D. C. Adams. 2021. RRPP: Linear Model Evaluation with Randomized Residuals in a Permutation Procedure.
  • Cox, C. L., D. L. Rabosky, P. O. Title, I. A. Holmes, A. Feldman, J. A. McGuire, and A. R. D. Rabosky. 2016. Coral snakes predict the evolution of mimicry across New World snakes. Nature Communications 7:11484.
  • Dalthorp, D., J. Simonis, L. Madsen, M. Huso, P. Rabie, J. Mintz, R. Wolpert, J. Studyvin, and F. Korner-Nievergelt. 2021. GenEst: Generalized Mortality Estimator.
  • Dalthorp, D., L. Madsen, M. M. Huso, P. A. Rabie, R. Wolpert, J. Studyvin, J. Simonis, and J. Mintz. 2018. GenEst Statistical Models—A Generalized Estimator of Mortality. Page 13 in U.S. Geological Survey Techniques and Methods, Book 7. Bureau of Land Management and the National Renewable Energy Laboratory, Reston, Virginia.
  • Danner, R., E. Derryberry, G. Derryberry, J. Danner, and D. Luther. 2019. SongEvo: An Individual-Based Model of Bird Song Evolution.
  • Dokter, A. M., P. Desmet, J. H. Spaaks, S. Van Hoey, L. Veen, L. Verlinden, C. Nilsson, G. Haase, H. Leijnse, A. Farnsworth, W. Bouten, and J. Shamoun-Baranes. 2019. bioRad: biological analysis and visualization of weather radar data. Ecography 42:852–860.
  • eBird. 2021. eBird: An online database of bird distribution and abundance “web application”. eBird, Cornell Lab of Ornithology, Ithaca, New York.
  • Edwards, B. P. M., and A. C. Smith. 2020. bbsBayes: An R Package for Hierarchical Bayesian Analysis of North American Breeding Bird Survey Data. bioRxiv:1–25.
  • Efford, M. 2020. secr: Spatially explicit capture-recapture models.
  • Efford, M. 2020. openCR: Open population capture-recapture models.
  • Erni, B., B. T. Bonnevie, H.-D. Oschadleus, R. Altwegg, and Les G Underhill. 2013. moult: An R Package to Analyze Moult in Birds. Journal of Statistical Software 52:1–23.
  • Fick, S. E., and R. J. Hijmans. 2017. Worldclim 2: New 1-km spatial resolution climate surfaces for global land areas.
  • Fiske, I. J., 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.
  • Freeman, E. A., and G. Moisen. 2008. PresenceAbsence: An R package for presence-absence model analysis. Journal of Statistical Software 23:1–31.
  • Gerber, B. D., M. B. Hooten, C. P. Peck, M. B. Rice, J. H. Gammonley, A. D. Apa, and A. J. Davis. 2018. Accounting for location uncertainty in azimuthal telemetry data improves ecological inference. Movement Ecology 6:1–14.
  • Gimenez, O., J.-D. Lebreton, R. Choquet, and R. Pradel. 2018. R2ucare: An R package to perform goodness-of-fit tests for capture-recapture models. Methods in Ecology and Evolution 9:1749–1754.
  • Goodrich, B., J. Gabry, I. Ali, and S. Brilleman. 2020. rstanarm: Bayesian applied regression modeling via Stan.
  • Grames, E. M., A. N. Stillman, M. W. Tingley, and C. S. Elphick. 2019. An automated approach to identifying search terms for systematic reviews using keyword co-occurrence networks. Methods in Ecology and Evolution 10:1645–1654.
  • Grames, E. M., A. N. Stillman, M. W. Tingley, and C. S. Elphick. 2020. litsearchr: Automated search term selection and search strategy for systematic reviews.
  • Gross, C., and P. Ottolinger. 2016. ggThemeAssist: Add-in to Customize “ggplot2” Themes.
  • Hadfield, J. D. 2010. MCMC methods for multi-response generalized linear mixed models: The MCMCglmm R package. Journal of Statistical Software 33:1–22.
  • Hafner, S. D., and J. Katz. 2018. monitoR: Acoustic template detection in R.
  • Hatch, J., E. Josephson, and D. Sigourney. 2021. seebirdr: Formats and summarizes seabird shipboard survey data for database upload and cruise reports.
  • Hanson, J. O., R. Schuster, N. Morrell, M. Strimas-Mackey, M. E. Watts, P. Arcese, J. Bennett, and H. P. Possingham. 2021. prioritizr: Systematic conservation prioritization in R.
  • Harnos, A., P. Fehérvári, and T. Csörgő. 2015. Hitchhikers’ guide to analysing bird ringing data Part 1: data cleaning, preparation and exploratory analyses. Ornis Hungarica 23:163–188.
  • Hernández, J. G., and S. Varela. 2015. rAvis: Interface to the Bird-Watching Dataset Proyecto AVIS.
  • Hijmans, R. J. 2020. raster: Geographic Data Analysis and Modeling.
  • Hijmans, R. J., S. Phillips, J. Leathwick, and J. Elith. 2020. dismo: Species Distribution Modeling.
  • Ives, A. R. 2018. R2s for Correlated Data: Phylogenetic Models, LMMs, and GLMMs. Systematic biology 68:234–251.
  • Ives, A. R., and D. Li. 2018. rr2: An R package to calculate R2s for regression models. The Journal of Open Source Software 3:1028.
  • Johnson, D. S., J. M. London, M.-A. Lea, and J. W. Durban. 2008. Continuous‐time correlated random walk model for animal telemetry data. Ecology 89:1208–1215.
  • Johnson, D., J. M. London, Kenady. 2017. crawl: an R package for fitting continuous-cime correlated random walk models to animal movement data.
  • Jombart, T. 2008. adegenet: a R package for the multivariate analysis of genetic markers. Bioinformatics 24:1403–1405.
  • Jombart, T., F. Balloux, and S. Dray. 2010. adephylo: exploratory analyses for the phylogenetic comparative method. Bioinformatics:1907–1909.
  • Jombart, T., and I. Ahmed. 2011. adegenet 1.3-1: new tools for the analysis of genome-wide SNP data 27:3070–3071.
  • Kalnay, E., M. Kanamitsu, R. Kistler, W. Collins, D. Deaven, L. Gandin, M. Iredell, S. Saha, G. White, J. Woollen, Y. Zhu, M. Chelliah, W. Ebisuzaki, W. Higgins, J. Janowiak, K. C. Mo, C. Ropelewski, J. Wang, A. Leetmaa, R. Reynolds, R. Jenne, and D. Joseph. 1996. The NCEP/NCAR 40-Year reanalysis project. Bulletin of the American Meteorological Society 77:437–472.
  • Kanamitsu, M., W. Ebisuzaki, J. Woollen, S.-K. Yang, J. J. Hnilo, M. Fiorino, and G. L. Potter. 2002. NCEP-DOE AMIP-II reanalysis (R-2). Bulletin of the American Meteorological Society:1–14.
  • Kemp, M. U., E. E. van Loon, J. Shamoun-Baranes, and W. Bouten. 2012a. RNCEP: global weather and climate data at your fingertips. Methods in Ecology and Evolution 3:65–70.
  • Kemp, M. U., J. Shamoun-Baranes, E. E. van Loon, J. D. McLaren, A. M. Dokter, and W. Bouten. 2012b. Quantifying flow-assistance and implications for movement research. Journal of Theoretical Biology 308:56–67.
  • Klein Heerenbrink, M. 2020. afpt: Tools for modelling of animal flight performance.
  • Klein Heerenbrink, M., L. C. Johansson, and A. Hedenstrom. 2015. Power of the wingbeat: modelling the effects of flapping wings in vertebrate flight. Proceedings of the Royal Society A 471:20140952.
  • Korner-Nievergelt, F., and R. A. Robinson. 2014. Introducing the R-package “birdring.” Ringing and Migration 29:51–61.
  • Korner-Nievergelt, F., O. Behr, R. Brinkmann, M. A. Etterson, M. M. P. Huso, D. Dalthorp, P. Korner-Nievergelt, T. Roth, and I. Niermann. 2015. Mortality estimation from carcass searches using the R-package carcass—a tutorial. Wildlife Biology 21:30–43.
  • Laake, J. L. 2013. RMark: An R Interface for analysis of capture-recapture data with MARK. Page 25 Alaska Fisheries Science Center AFSC processed report 2013-01. Alaska Fish. Sci. Cent., NOAA, Natl. Mar. Fish. Serv. Seattle, WA.
  • Laake, J., D. Borchers, L. Thomas, D. Miller, and J. Bishop. 2020. mrds: Mark-Recapture Distance Sampling.
  • 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.
  • LaZerte, S. E. 2021. cavityuse: Detecting Cavity Use From Geolocator Data.
  • LaZerte, S. E. 2021. feedr: Transforming raw RFID data.
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Marc-Olivier Beausoleil

Beausoleil, Marc-Olivier. 2021. Ornithometrics: a collection of R packages to analyse ornithological data. 10.6084/m9.figshare.14453757