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Ornithology Exchange

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This group is dedicated to sharing knowledge and helping others in using R for Ornithology Research. We are an inclusive community built to help Ornithologists learn, teach, build, and troubleshoot in R across a broad range of experience levels. Please read our code of conduct (under General Topics) before posting.
  1. What's new in this group
  2. Thanks! This is still a work in progress, and I included all of the packages suggested here. This is an example of the reference that I'm building (see Cran task views for comparison) https://beausoleilmo.github.io/Ornithometrics-ctv/Ornithometrics.html
  3. For acoustic data I use Seewave warbleR tuneR I also recommend Sound Analysis and Synthesis With R by Jerome Sueur
  4. Thanks! Well, if you are interested, I'm actually building a Cran task View (or maybe just a Task view) for ornithologists. If anyone wants to join, we can discuss on how to move forward :D
  5. For regression models I regularly use emmeans/emtrends: https://aosmith.rbind.io/2019/03/25/getting-started-with-emmeans/ visreg: https://pbreheny.github.io/visreg/ rr2 to plot partial residual plots, calculate model coefficients and effect sizes, and extract pseudo R-squared values for anything that is not least squares. This is especially useful for regression models with lots of variables, especially multiple categorical variables and/or interactions.
  6. Some population related packages: Distance dsm marked mrds nimbleSCR oSCR PresenceAbsence Rcapture RMark scrbook secr unmarked Some packages for accessing bird observation citizen science data: auk (and ebirdst) rinat rgbif Lots of general modeling packages: MuMIn AICcmodavg You might also check out some of the CRAN task views such as, Analysis of Ecological and Environmental Data Analysis of Spatial Data Multivariate Statistics Phylogenetics, Especially Comparative Methods Cluster Analysis & Finite Mixture Models Handling and Analyzing Spatio-Temporal Data
  7. I'm compiling a list of relevant R packages in ornithology. I was wondering if you can provide one or more packages that you find relevant in these categories. Communication and acoustic analysis Conservation Genetics Mark-recapture analysis Movement ecology, navigation, telemetry, GPS, habitat use Phylogeny Physiology, phenology and life histories Population dynamics I welcome packages not only on CRAN. Thanks!
  8. I would suggest deciding what kind of model you want to use before deciding which software to implement it with. You have distance data, so you could use distance sampling. But you also have repeated surveys within a season, so you might consider an N-mixture model. With your time intervals you could use a removal model. And there are ways to combine those data, for example by using a time-removal plus distance sampling model. Part of your choice should be based on your main question. If you need a density estimate for an area, you probably want a distance sampling model of some sort. If you are content to know N, the number of birds observed (or expected to be observed) on a given point, then an N-mixture model of some sort may suffice. To learn more about the various types of models (many of which are implemented in unmarked), I suggest you get a copy of this book: Kéry, Marc, J. Andrew Royle. 2015. Applied hierarchical modeling in ecology: analysis of distribution, abundance and species richness in R and BUGS: volume 1: prelude and static models. Academic Press. London, UK. I do not consider myself an expert on any of these types of models, and given that nobody else has answered in the last couple of days, I suggest you re-post your question on the unmarked Google group: https://groups.google.com/forum/#!forum/unmarked. Or if you're interested in going Bayesian, the hmecology: Hierarchical Modeling in Ecology group https://groups.google.com/forum/#!forum/hmecology Let us know what you find out.
  9. I am looking for some guidance on producing density and population estimates from a point count dataset for about a dozen grassland bird species while linking relationships to a suite of habitat data. I had intended to use package 'detect', adapting previously used code, but in light of a recent paper by Solymos et al. 2018, it does not seem appropriate for these data, as all species have fewer than the 1000 detection sample size suggested by Solymos. So I have been struggling to determine whether using a function in the package 'unmarked' is appropriate or if I should be looking to program Distance. The purpose of my project is practical grassland bird habitat management and conservation. With unmarked, I am unsure which functions should be utilized and how to get the process going. I have reviewed various literature on the package, but would greatly appreciate any help here. Here is the structure for my data: 37 sites, 521 points, 2 survey visits in one year, 3 distance bands (0-50m, 50-100m, >100m), 5 - 1min time intervals-singing & non-singing detections recorded separately survey covariates: site_name, survey_yr, time since local sunrise, sky, wind, temp, surveyor habitat covariates: 29 variables: 12 different grassland community types (proportion), 10 disturbance types (proportion), cover: herb, shrub, bare (integer), height: herb, bare, shrub (integer) Thank you in advance for any help you can provide! David
  10. Just FYI you can now also render PowerPoint presentations using rmarkdown in RStudio: https://support.rstudio.com/hc/en-us/articles/360004672913-Rendering-PowerPoint-Presentations-with-RStudio I haven't tried it yet but it looks like some of my gripes about other types of presentations are solved here, e.g. you can use columns, and templates.
  11. Note- 'officer' is replacing 'ReporteRs': http://davidgohel.github.io/ReporteRs/index.html so switch over if you have been using ReporteRs
  12. I've recently came across an R package called 'officer' that makes it really easy to export editable figures/graphs (base or ggplot) to an Office application. This makes it really easy to modify figures for presentations or in my case a poster. Every element will be generated as a text/shape etc so you can change colors, text sizes, move them around etc. Also looks as though you could generate an entire presentation or document if you wanted. Figured I would share the knowledge. Here is a link to the vignette for exporting to powerpoint. I was able to follow it exactly and achieve the desired result but if you have issue feel free to reply. There are also other vignettes for the package on CRAN if you are interested in other applications. https://cran.r-project.org/web/packages/officer/vignettes/powerpoint.html -Alli
  13. Hi All, I'm currently in the process of running ZIP models in rjags to test some hypotheses about duck pair abundance. The zero-inflated models include only an intercept parameter and then 3 different dummy parameters to represent the wetland cover class variables 2, 3, and 4. In theory, one would expect the non-transformed value of the parameter estimates to decrease in value from cover class 1 to 4 sequentially. I'm seeing this trend in the MLE models we ran first actually: (Intercept) WCCone WCCthree WCCtwo -6.4537 6.0062 0.8016 3.5753 Unfortunately, I'm running up against a bit of a snag in rjags. The parameter estimates for the wetland cover classes in the zero-inflated portion of the model all end up being relatively the same (~-7 - -8) and are truncated at -10 (see the not-so-nice looking trace plots in attached word file: a2,a3,a4). I've checked for correlations among the covariates, mistakes in the data, and at this point, I am concerned that this might be a coding problem. I realize this is somewhat of an inane question to ask, however, I'm unfortunately not in an academic lab where I can easily find a fellow JAGS coder, so usually end up having to turn to sources like these if I want a second set of eyes. So, I'm hoping there's someone out there who is willing to look through the attached code and let me know if they see an error that might be causing these weird results. I've literally spent the last 6 months digging through these data and this code so I think my eyes cross every time I look at it. Any help would be great. Thanks, KC Example.docx KCScript.R
  14. Any of you who have talked with me about teaching R for any length of time have heard me talk about how 'life changing' the instructor training I received through Data Carpentry and Software Carpentry as been. A big part of that is because Software Carpentry was founded by Greg Wilson, and he has spent a LOT of time thinking about teaching, and learning from the best pedagogical research on how to teach coding. Greg just released a new book all about teaching technology, and while not all of will apply to teaching R, this is 100% what I recommend folks read if they want to learn how to teach coding based on the best science of how people learn. Greg is also fantastic at building practices into his classrooms that are welcoming to new comers and make sure that some of the barriers that those with great experience sometimes put up without thinking are broken down. The book is available open source online, more info here. http://third-bit.com/2018/07/15/teaching-tech-together.html
  15. Hi All, This is likely to become the largest tab within R Onithology. Here is where you can post on most any topic, but we request you use tags to help other users sort through the posts and find things of interest. Possible tags could include bioacoustics, power analysis, distance sampling, radar, modeling, and many many others. Feel free to start new tags of your own!
  16. Sorry, wrong link. This should be the right one: http://vinr.ir/sites/default/files/Winston%20Chang-R%20Graphics%20Cookbook-O%27Reilly%20Media%20%282013%29.pdf
  17. The R Graphics Cookbook has both ggplot and base R recipes: http://www.bagualu.net/wordpress/wp-content/uploads/2015/10/R_Cookbook.pdf.
  18. There is a R package to help build hex stickers! https://cran.r-project.org/web/packages/hexSticker/index.html I wonder if we could graph the outline of a bird or something and use that?
  19. Hi Everyone, I almost exclusively use ggplot for my graphing, but sometimes I have folks ask me questions about how to do something graphing related in base R. Anyone know of good resources I can point them to?
  20. Packages are a useful way to bundle the codes you made and load them quickly. It may seem that this is an advanced user kind of task, but I feel moderate experience users can grasp the concept of creating their own package quite quickly. You dont even need to publish anything on CRAN, just load it locally! To get people started I'd suggest looking at Hillary Parkers quick and relatively easy guide to creating your first package: https://hilaryparker.com/2014/04/29/writing-an-r-package-from-scratch/ After you get started playing around with that, you'll learn that function writing has its own set of quirks, especially as your codes get more complex. At that point I'd send people to start reading Hadley Wickhams Advanced R online book. Just read all through the 'Foundations' section atleast, to get a good grasp on why certain things do and don't work for you: http://adv-r.had.co.nz/ There's a lot to learn and gain from learning about packages, and users can certainly take it as far as they want. Feel free to share any tips or tricks of package building!
  21. Currently this is an open forum to discuss what other points we might need to address and add to our code of conduct. Feel free to discuss any changes.
  22. So with this group launching and even having had our first meeting, we should create a logo. Any one have any great ideas or want to post a design for everyone to see, please share! Examples of current hex stickers and R logos: https://www.redbubble.com/shop/rstudio+stickers
  23. Please read. Youre continued use of this forum is an implicit agreement to adhere to the Code of Conduct. Rnithology is dedicated to providing a harassment-free experience for everyone. We do not tolerate harassment of participants in any form. This code of conduct applies to all Rnithology spaces, including meetups, Twitter, mailing lists, both online and offline. Anyone who violates this code of conduct may be sanctioned or expelled from these spaces at the discretion of the Leadership Team. Some Rnithology spaces may have additional rules in place, which will be made clearly available to participants. Participants are responsible for knowing and abiding by these rules. Harassment includes: Offensive comments related to gender, gender identity and expression, sexual orientation, disability, mental illness, neuro(a)typicality, physical appearance, body size, age, race, or religion. Unwelcome comments regarding a person's lifestyle choices and practices, including those related to food, health, parenting, drugs, and employment. Deliberate misgendering or use of 'dead' or rejected names. Gratuitous or off-topic sexual images or behaviour in spaces where they're not appropriate. Threats of violence. Incitement of violence towards any individual, including encouraging a person to commit suicide or to engage in self-harm. Deliberate intimidation. Stalking or following. Harassing photography or recording, including logging online activity for harassment purposes. Sustained disruption of discussion. Unwelcome sexual attention. Continued one-on-one communication after requests to cease. Deliberate "outing" of any aspect of a person's identity without their consent except as necessary to protect vulnerable people from intentional abuse. Publication of non-harassing private communication. Rnithology prioritizes marginalized people's safety over privileged people's comfort. The Leadership Team will not act on complaints regarding: 'Reverse' -isms, including 'reverse racism,' 'reverse sexism,' and 'cisphobia'. Reasonable communication of boundaries, such as "leave me alone," "go away," or "I'm not discussing this with you." Communicating in a 'tone' you don't find congenial. Criticizing racist, sexist, cissexist, or otherwise oppressive behavior or assumptions. Reporting If you are being harassed by a member/guest/participant of/at Rnithology, notice that someone else is being harassed, or have any other concerns, please contact the Leadership Team via EMAIL ADDRESS. Local incidences will be handled together with the local organisers. If the person who is harassing you is on the team, they will recuse themselves from handling your incident. We will respond as promptly as we can. We will take all good-faith reports of harassment by Rnithology members seriously. This includes harassment outside our spaces and harassment that took place at any point in time. In order to protect volunteers from abuse and burnout, we reserve the right to reject any report we believe to have been made in bad faith. Reports intended to silence legitimate criticism may be deleted without response. We will respect confidentiality requests for the purpose of protecting victims of abuse. At our discretion, we may publicly name a person about whom we've received harassment complaints, or privately warn third parties about them, if we believe that doing so will increase the safety of Rnithology members or the general public. We will not name harassment victims without their affirmative consent. Consequences Participants asked to stop any harassing behavior are expected to comply immediately. If a participant engages in harassing behavior, the Leadership Team may take any action they deem appropriate, up to and including expulsion from all Rnithology spaces and identification of the participant as a harasser to other Rrnithology members or the general public.
  24. We are working on putting together a blog post for the ROpenSci blog that will better outline the community we want to create, I'll be sure to post a link here when it goes live [might be a few weeks]. Glad to hear about github classroom, I've not used it myself but it sounds really powerful. Certainly a great skillset to give to students.
  25. Sounds great! I want to get involved but don't know how... I didn't see any links to a discussion forum or email list and no issues on that repo. As a side note, I used GitHub Classroom last semester for my R class Quantitative Biology. Students generally liked learning Git and using GitHub, and appreciated the many advantages that method of collaboration had to offer.

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