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Found 11 results

  1. Hello! I am currently using FLightR to analyze geolocator data for migration routes and timing events, but I have been having issues specifically with loading the package geosphere (sometimes the package MASS is an issue too, but geosphere only works less than half the time for the past month I'd say). I am using geosphere to produce final FLightR maps showing migration results and movements represented by a calendar year legend. I am working on two monitors, one computer, where very often I have two different RStudios running and when installing geosphere it continually says geosphere was successfully unpacked in both R sessions, but then only one or none of the maps will load after running the following line, "map.FLightR.ggmap(Result163, seasonal.donut.location=NULL, save=TRUE)" I am currently running version 3.4.1 "Single Candle", and I have also used/run version 3.3.2 "Sincere Pumpkin Patch" where geosphere also used to only work occasionally. Geosphere does not appear to be on the update packages list, therefore any recommendations on how to get geosphere to consistently work? Thank you so much for your time and help in advance! Sabina
  2. AmelieRobertoCharron

    FLightR Error Message.

    Hello! I was trying to run FLightR and when trying to run the 'all.in' function I got the following message: Error in create.proposal(Processed.light, start = start, Grid = Grid) : object 'start_no_polar' not found I ran this function: all.in113 I'm not surprised that the function was unable to find 'start_no_polar' as I haven't defined it. I haven't found 'start_no_polar' defined in any examples of FLightR analysis that I have come across, and I don't know what I should be defining it as. Would anyone have any recommendations on how to proceed? Any help would be appreciated! Thanks, Amélie
  3. Hello! I would like to try FLightR (i.e. template fit) method on some of my Intigeo data. I have previously analyzed these tags with GeoLight. I am following the example posted on GitHub for the Godwits but I run into a problem getting the 'twilight events' file. This actually uses the BAStag package not the FLightR package, but I don't know another way to have my data formatted properly for FLightR. It seems to be an issue with the interactive plots called by the 'twl' function. Here is the code from the Godwit example as well as the error. > twl Error in setGraphicsEventEnv(which, as.environment(list(...))) : this graphics device does not support event handling I am using Mac OS X 10.11.3 El Capitan, R version 3.2.4 Very Secure Dishes I have not had any trouble looking at the transitions with GeoLight but it doesn't seem to produce files in the correct format for FlightR. Thanks for any help! Emily
  4. Analyzing Ecological Data with Hierarchical Models Five-day Workshop: 15-18 Mar 2016 Time: 9 am – 5 pm Location: Rosenstiel School of Marine & Atmospheric Science – University of Miami, Miami, Florida Instructor: Dr. Robert M. Dorazio Wetland and Aquatic Research Center U.S. Geological Survey Gainesville, Florida 32653 Email: bdorazio@usgs.gov Course Description: This workshop is designed to provide wildlife scientists with the training needed to formulate and fit hierarchical models of animal abundance and occurrence to actual data sets. Most of these models can be fitted using either frequentist or Bayesian methods of analysis. However, Bayesian methods will be emphasized in the workshop because scientific interest is often focused on a model’s latent state variables or predictions (such as the abundance or occurrence of animals at sampled or unsampled locations) and computing inferences for these quantities is often difficult with frequentist methods. The workshop begins with a description of hierarchical modeling and its use in the analysis of ecological data. This is followed by a conceptual review of the frequentist system of inference and by an introduction to Bayesian methods of analysis. Next is a description of a generic set of algorithms (Markov chain Monte Carlo) that can be used to fit all of the hierarchical models described in the workshop – and many more! Armed with these tools, participants of the workshop will learn to derive and implement simulation-based algorithms for fitting hierarchical models to different types of data (as opposed to relying on software such as BUGS or JAGS). The workshop is intended to provide substantial hands-on training. Considerable time will be devoted to the technical details of fitting hierarchical models to data and to summarizing and interpreting the results of each analysis. As time permits, data brought to the workshop by participants will be presented and analyzed as class exercises. Prerequisites: (1) working knowledge of the R software program (R Core Team, 2015), (2) laptop computer with R installed, (3) familiarity with the frequentist system of statistical inference (including maximum likelihood estimation), and (4) familiarity with the analytical evaluation of joint, marginal, and conditional probability density functions, particularly as they are used in specifying mixtures of distributions. RSMASworkshopOutline2016.pdf
  5. Instructors: Marc Kéry & Andy Royle, Swiss Ornithological Institute & USGS Patuxent Wildlife Research Center Date: 9–13 November 2015 Venue: Patuxent Wildlife Research Center, Laurel/MD Course fee: USD$550 (normal rate), USD$350 (student rate) The analysis of abundance and of the dynamic rates governing their change lies at the core of ecology and its applications such as conservation and wildlife management. Meta-population designs, where repeated measurements of some quantity such as counts or distance measurements are made at a collection of sites, underlie a vast number of studies in ecology and management. Inference about such data is conveniently based on hierarchical models, where one submodel describes the underlying true state of the process (e.g., abundance at a site) and another submodel describes the observation process that connects the true state to the observations. In recent years, much progress has been made in the development of methods and computer algorithms to fit hierarchical models. In particular, Bayesian statistical analysis and the general-purpose Bayesian software packages BUGS and JAGS have revolutionized the ways in which ecologists can conduct complex population analyses. On the other hand, the R package unmarked contains a wealth of functions for a frequentist analysis of hierarchical models of abundance. This course introduces key hierarchical models used in the analysis of abundance and survival and their spatial and temporal patterns, and provides both Bayesian and frequentist methods for their analysis. We use packages unmarked and wiqid and especially WinBUGS, OpenBUGS and JAGS to fit and understand some of the most widely used models for the analysis of animal and plant populations. These include: Binomial (Royle 2004) and multinomial N-mixture models (Dorazio et al. 2005, Royle et al. 2007) Conventional distance sampling and Hierarchical distance sampling (e.g., Royle et al. 2004, Sillett et al. 2012) Dynamic models of abundance for replicated counts (Dail & Madsen 2011) or distance sampling data (Sollmann et al. 2015) Cormack-Jolly-Seber (CJS) models, especially hierarchical CJS models for variation in survival over space (Saracco et al. 2010) or in a community of species This is an intermediate-level workshop with about 80% spent lecturing and 20% on solving exercises. A working knowledge of modern regression methods (GLMs, mixed models) and of program R is required. Previous experience with the BUGS language is beneficial. Please bring your own laptops and install a recent version of R, with the latest version of package unmarked, plus JAGS and/or WinBUGS 1.4. OpenBUGS works for most of what we do. Please apply here by 1 October 2015: https://docs.google.com/forms/d/1qqjfnIqk7TX8MTaYX2UzPl9OtdCtjodKQ206Qd8zSKY/viewform?usp=send_form
  6. “Master” R in Washington DC this September! Join RStudio Chief Data Scientist Hadley Wickham at the AMA – Executive Conference Center in Arlington, VA on September 14 and 15, 2015 for this rare opportunity to learn from one of the R community’s most popular and innovative authors and package developers. It will be at least another year before Hadley returns to teach his class on the East Coast, so don't miss this opportunity to learn from him in person. The venue is conveniently located next to Ronald Reagan Washington National Airport and a short distance from the Metro. Attendance is limited. Past events have sold out. Register today! Cross-posted from the RStudio Blog, http://blog.rstudio.org/2015/06/12/hadley-wickhams-master-r-developer-workshop-washington-dc-registration-is-open/
  7. Join RStudio Chief Data Scientist Hadley Wickham at the University of Illinois at Chicago, on Wednesday May 27th & 28th for this rare opportunity to learn from one of the R community’s most popular and innovative authors and package developers. As of this post, the workshop is two-thirds sold out. If you’re in or near Chicago and want to boost your R programming skills, this is Hadley’s only Central US public workshop planned for 2015. Register here: https://rstudio-chicago.eventbrite.com
  8. Instructors: Marc Kéry & Jérôme Guélat, Swiss Ornithological Institute Date: 9–11 February 2015 Venue: Universidade Federal de Viçosa, Minas Gerais, Brazil Computers: Bring your own laptop with latest R, JAGS and WinBUGS or OpenBUGS Costs: 1000 Reais (400 US$) This course gives an introduction to Bayesian statistical modeling using BUGS software and then introduces a key class of models for the analysis of species distribution, habitat selection, occurrence and abundance: site‐occupancy models (MacKenzie et al. 2002, 2003; Tyre et al. 2003). Model fitting is shown using the Bayesian BUGS software and the R package unmarked. The course follows the book “Bayesian population analysis using WinBUGS” (Academic Press, 2012) by Kéry & Schaub and the upcoming book “Applied hierarchical models in ecology” (Academic Press, 2015) by Marc Kéry & Andy Royle. See the attached flier for more details. Occupancy Workshop Announcement, Vicosa, 9-11 Feb 2015.pdf
  9. Melanie Colón

    Program R Workshop

    Program R Workshop 9-13 March 2015 The Great Plains Natural Science Society and the Department of Natural Resource Management at South Dakota State University will host a Program R Workshop in Brookings, SD. The 4.5-day workshop will be presented by Dr. Darryl MacKenzie at the Swiftel Center. The workshop will cover many beginning and intermediate level topics and participants will be introduced to various statistical procedures through worked examples. Topics to be covered include: Basic Operators Plotting Functions Arrays and Matrices Descriptive Analysis Basic Statistical Tests Linear Models Generalized Linear Models Simulation Complex plots Registration fee is $650. Please contact Dr. Troy Grovenburg (troy.grovenburg@sdstate.edu) or visit http://www.sdstate.edu/nrm/organizations/gpnss for additional information and registration details.
  10. The newly renamed Smithsonian-Mason School of Conservation, a partnership between George Mason University and the Smithsonian Conservation Biology Institute (SCBI), is proud to announce their Spring/Summer 2013 course schedule. The School is now offering more courses than ever before, in a wide range of topics, all focused on training in different aspects of biodiversity conservation, from effective conservation leadership, to technical tools in statistics and field sampling. All courses are currently either 1 or 2-week intensive residential courses and they will now be held in a brand-new, sustainably-built Academic Center on the grounds of SCBI in Front Royal Virginia. Most courses can be taken either for graduate credit or continuing education units. See our upcoming offerings below and check out our website for more course details and pricing. Smithsonian-Mason School of Conservation Graduate/Professional Training Courses SPRING/SUMMER 2013 Front Royal, Virginia, USA Visit our website (http://SMConservation.gmu.edu) or email us at SCBItraining@si.edu for more details about each course, course costs, and credits earned. Statistics for Ecology and Conservation Biology March 4-15, 2013 Gain in-depth knowledge of analysis techniques for cutting-edge ecological research, employing R: classical regression models; mixed models; generalized linear models; generalized additive models; how to deal with the limitations of real datasets; and conservation-specific approaches. Estimating Animal Abundance and Occupancy (new course!) April 1-12, 2013 The course is designed to provide a strong theoretical and analytical background to both graduate students and professionals in distance sampling, mark-recapture, and occupancy modeling techniques, with a strong focus on the practical use of field data in the programs DISTANCE, MARK and PRESENCE. Species Monitoring & Conservation: Terrestrial Mammals April 29-May 10, 2013 This course teaches current techniques in assessment and monitoring of wild mammal populations, including bats. Participants learn principles of study design; current field assessment methods; data analysis techniques including MARK and DISTANCE software; application of monitoring data to decision-making and population management; and collection and preparation of museum voucher specimens. Species Monitoring & Conservation: Reptiles (new course!) May 13-24, 2013 This course will provide technical training in the essential aspects of reptile conservation. In addition to providing hands-on experience with current field monitoring techniques, participants will also learn to analyze mark-recapture, distance sampling and occupancy field data. The course will also include a review of reptile taxonomy and phylogeny, and the role of captive propagation in reptile conservation. Non-Invasive Genetic Techniques in Wildlife Conservation June 1-7, 2013 Learn how new developments in non-invasive genetics allow biologists and managers to answer questions in animal behavior, population biology and population management. Course participants will work through a directed research project, from study design through field data collection, sampling protocols, and DNA extraction and amplification, to analysis of microsatellite and sequence data. Adaptive Management for Conservation Success June 10-21, 2013 This course is taught in partnership with Foundations of Success (FOS). Working in teams on a real conservation project, participants practice conceptualizing projects, formulating objectives and providing evidence of conservation results. The course builds skills in designing and planning effective projects that provide clear evidence of conservation impact, and in use of Miradi adaptive management software.
  11. Introduction to linear mixed effects modelling course with R. 11 - 15 February 2013. Lisbon, Portugal. For details, see: http://www.highstat....statscourse.htm Course flyer: http://www.highstat....bSIM_Lisbon.pdf
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