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Found 36 results

  1. 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.
  2. Modeling Patterns and Dynamics of Species Occurrence The Modeling Patterns and Dynamics of Species Occurrence Workshop will be held at the Swiftel Center in Brookings, SD, 16-20 March 2015. NOTE: The workshop is strictly limited to a set number of registrants. OVERVIEW The presence or absence of a species across a set of landscape units is a fundamental concept widely used in ecology (e.g., species range or distribution, epidemiology, habitat modeling, resource selection probability functions, as a monitoring metric, metapopulation studies, biodiversity, and species co-occurrence). An important sampling issue, however, is that a species may not always be detected when present at a landscape unit. This will result in "false absences" causing parameter estimates to be biased if unaccounted for, possibly leading to misleading results and conclusions, even with moderate levels of imperfect detection. This workshop will cover many of the latest methods for modeling patterns of dynamics of species occurrence in a landscape while accounting for the imperfect detection of the species. Participants will be introduced to available software through worked examples, and there will be special emphasis on aspects of study design. While primarily aimed at the beginner and intermediate level, more experienced researchers will also benefit from attending. Topics to be covered include: single season occupancy models for patterns in species occurrence building predictive models for species occurrence creating maps of species occurrence probabilities, e.g., species distribution maps multiple-season occupancy models for dynamics of species occurrence and changes in distribution important study design considerations sample size determination FORMAT Format for the workshop will be a combination of lectures and exercises. The workshop will start on Monday morning, 8:30 AM, and at 8:00 AM Tuesday-Friday. The workshop will end at noon on Friday. South Dakota State University graduate students wishing to receive credit for the workshop also will need to register for WL792 Tp-Occupancy Modeling (3 credits) for the spring 2015 term. This is a written consent course, so students will need to obtain a signed Registration Authorization form from Dr. Grovenburg. INSTRUCTOR Dr. Darryl MacKenzie, Proteus Consulting Ltd. Darryl is an internationally renowned biometrician, particularly for his work on the development and application of species occurrence models. He has over 15 years experience in applying statistical techniques to ecological and environmental situations, starting at the University of Otago, then progressing to North Carolina State University (based at USGS Patuxent Wildlife Research Center) in 2000, before commencing full-time with Proteus in 2001. Darryl has provided advice on studies for a wide-range of species and enjoys the challenge of combining the statistical theory with the practical realties to develop a pragmatic solution. AGENDA A tentative agenda can be found in the Quick Links box above. Please note that this is a tentative schedule only. COST Registration cost for the 5-day workshop is $850. This fee includes course materials, facilities for the workshop, and morning and afternoon refreshments. All other costs (i.e., travel, lodging, meals, etc.) will be the responsibility of the workshop participant. REGISTRATION Please complete the registration form (available in the Quick Links box above) and forward with payment to: Dr. Troy Grovenburg Department of Natural Resource Management South Dakota State University Box 2140B, NPS 138 Brookings, SD 57007 Completed registration forms paying with credit card can be emailed to Dr. Troy Grovenburg. HOTEL ACCOMMODATIONS We have arranged for a block of rooms at state rates at the Fairfield Inn &Suites under SDSU Dept. of Natural Resources. http://www.sdstate.edu/nrm/organizations/gpnss Fairfield Inn &Suites 3000 LeFevre Drive Brookings, SD 57006 605-692-3500
  3. APPLIED BAYESIAN DATA ANALYSIS USING STAN OCTOBER 24 – 25, 2014 Daniel Lee, Department of Statistics, Columbia University, New York Michael Betancourt, Department of Statistical Sciences, University College London Location: Swiss Ornithological Institute, Sempach, Switzerland Workshop leaders Daniel Lee and Michael Betancourt are members of the core development team of STAN. Both are excellent software engineers. They work with Prof. Andrew Gelman on applied Bayesian statistics, modelling and software development. Daniel is doing research on Monte Carlo Markov chains (MCMC) and Bayesian analyses (http://linkd.in/12xLZYK). Michael studies the mathematical foundations of Bayesian methods in order to motivate efficient practical techniques (http://www.homepages.ucl.ac.uk/~ucakmjb/). Outline Stan is an open-source, general Bayesian inference tool with interfaces in R, Python, Matlab, and the command line. Stan was developed to address the speed and scalability issues of existing Bayesian inference tools, BUGS and JAGS, while maintaining the ability to write models easily through a statistical language. The default algorithm is an auto-tuned variant of Hamiltonian Monte Carlo, which is a more efficient MCMC algorithm for general problems than Gibbs sampling or random-walk Metropolis Hastings. This exciting new tool is now open to everybody and has the potential to be very useful in the daily life of a data analyst that use comparably complex models in a Bayesian framework. The course will start with a short introduction to Bayesian inference and how Stan works. However, the main goal of the course is the practical application of Stan to different models starting with ordinary linear regression and ending with more complex models such as generalized linear mixed and hierarchical models. Download the attached course announcement for full details and information on how to registration. course_announcement_STAN 2014.pdf
  4. Intermediate-level workshop Bayesian population analysis using BUGS and JAGS Instructors: Marc Kéry & Michael Schaub, Swiss Ornithological Institute Date: 22–26 September 2014 Venue: College of Forestry and Conservation, University of Montana, Missoula Computers: Bring your own laptop with latest R and WinBUGS, JAGS or OpenBUGS Costs: 603 USD This course introduces many key models used in the analysis of distribution, abundance and survival, as well as their spatial and temporal patterns, in a Bayesian analysis framework. It closely follows our book “Bayesian population analysis using WinBUGS” (Academic Press, 2012). We use programs R and WinBUGS and JAGS to fit and understand some of the most widely used models for the analysis of animal and plant populations. These include: Poisson generalized linear mixed model (e.g., Link and Sauer 2002) Closed-population models for population size Cormack-Jolly-Seber models for estimating survival probabilities Multistate capture-recapture models for estimating survival and transition rates Integrated population models (Besbeas et al. 2002; Schaub et al. 2007) Site-occupancy models (MacKenzie et al. 2002, 2003) for the analysis of species distributions Binomial mixture models (Royle 2004) for the analysis of distribution and abundance with full accounting for observation error In this intermediate-level workshop 3/4 of the time are spent on lecturing and 1/4 on solving exercises. No previous experience with program WinBUGS, or Bayesian statistics, is assumed. However, a good working knowledge of modern regression methods (ANOVA, ANCOVA, generalised linear models) and of program R is required. Please bring your own laptops and install a recent version of R plus WinBUGS 1.4., with the upgrade patch and the immortality key decoded (in this order). Alternatively, JAGS and OpenBUGS work fine for 99% of what we do. Please apply here (www.umt.edu/sell/extended/courses/populationanalysis), describing your background and knowledge in statistical modeling, R and WinBUGS/OpenBUGS/JAGS, by 8 August 2014 at the latest. Workshop invitations will be sent out before 31 August 2014.
  5. Several workshops will be held at the 21st annual conference of The Wildlife Society to be held October 25-30, 2014 in Pittsburgh, Pennsylvania, USA. Many of these may be of interest to people working with birds. This is a preliminary list. They will be adding more sessions through July as each one is confirmed. All workshops will be full day sessions held on Saturday, Oct. 25, unless noted otherwise. Human-Carnivore Interactions and Management in the Eastern USA Estimating Resource Selection Using R Feedback for Student Reviewers of TWS Journals (Workshop scheduled for Tuesday, Oct. 28, half day session) Conservation Affairs and Subunit Leadership Workshop Animal Trapping Techniques for Researchers and Managers Flipped Learning in Natural Resources: How to Get Started (Half Day Workshop) Wildlife Data Management Fundamentals Urban Conservation in a Revitalized ‘Steel City’ Analyses of Wildlife Spatial Behaviors with T-LoCoH (Half Day Workshop) Model-based Inference for Rare, Clustered Populations: Dealing with Excess Zeroes Behind the Scenes of Scientific Publication and Critical Review 3.0 Research and Management of Novel Infectious Diseases in Reptiles and Amphibians The current list of workshops can be found here: http://wildlifesociety.org/workshops/ The meeting website is here: http://wildlifesociety.org/
  6. Instructors: Marc Kéry & Andy Royle, Swiss Ornithological Institute & USGS Patuxent Wildlife Research Center Date: 13–15 August 2014 Venue: Cornell University, Ithaca New York Computers: Bring your own laptop with latest R/unmarked and WinBUGS/OpenBUGS/JAGS 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. Metapopulation 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 package WinBUGS have opened up entirely new possibilities for ecologists to conduct complex population analyses. On the other hand, the R package unmarked contains a wealth of functions to analyse hierarchical models of abundance in a frequentist mode of inference. This course introduces key hierarchical models used in the analysis of abundance and its spatial and temporal patterns, and provides both Bayesian and the frequentist methods for their analysis. We use package unmarked in R as well as WinBUGS 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 (e.g., removal, double-observer) for the analysis of distribution and abundance, CAR modeling of spatial autocorrelation in abundance hierarchical distance sampling models (e.g., Royle et al. 2004, Conn et al. 2012), dynamic models of abundance (Royle & Dorazio 2008; Dail & Madsen 2011) 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 preferentially of program R or another programming language is required. No previous experience with program WinBUGS is assumed (but, of course, it 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., with the upgrade patch and the immortality key decoded (in this order, only for the latter). OpenBUGS should work for most of what we do. Please apply here by 1 July 2014: https://docs.google.com/forms/d/1rabj8gKVm37TVnFyKqsi4lR0CMfxL9DDMh3o--GRpKA/viewform
  7. Applied hierarchical modeling in ecology using BUGS and R: site-structured models for abundance (Workshop) Instructors: Marc Kéry & Andy Royle, Swiss Ornithological Institute & USGS Patuxent Wildlife Research Center Date: 16–18 June 2014 Venue: USGS Patuxent Wildlife Research Center, Laurel, Maryland Computers: Bring your own laptop with latest R/unmarked and WinBUGS/OpenBUGS/JAGS Course fee: USD$450 (normal rate), USD$300 (student rate), 2 wild cards available. 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. Metapopulation 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 package WinBUGS have opened up entirely new possibilities for ecologists to conduct complex population analyses. On the other hand, the R package unmarked contains a wealth of functions to analyse hierarchical models of abundance in a frequentist mode of inference. This course introduces key hierarchical models used in the analysis of abundance and its spatial and temporal patterns, and provides both Bayesian and the frequentist methods for their analysis. We use package unmarked in R as well as WinBUGS 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 (e.g., removal, double-observer) for the analysis of distribution and abundance, CAR modeling of spatial autocorrelation in abundance hierarchical distance sampling models (e.g., Royle et al. 2004, Conn et al. 2012), dynamic models of abundance (Royle & Dorazio 2008; Dail & Madsen 2011) 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 preferentially of program R or another programming language is required. No previous experience with program WinBUGS is assumed (but, of course, it 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., with the upgrade patch and the immortality key decoded (in this order, only for the latter). OpenBUGS should work for most of what we do. Please apply here by 1 May 2014: https://docs.google.com/forms/d/1Rn9kHWNTa_SwxW_0nGP2qzA6id4aQSo5Cl7AupnfnmY/viewform
  8. 1st Annual Graduate Workshop on Environmental Data Analytics July 28 – August 1, 2014 National Center for Atmospheric Research, Boulder CO. Applications due *March 17, 2014*. Travel and lodging fellowships are available. Workshop website: www2.image.ucar.edu/event/env-analytics This workshop series is designed to help prepare the next generation of researchers and practitioners to work within, and contribute to, the data-rich era. Each workshop will bring together graduate students and senior scientists in environmental statistics and related fields to explore contemporary topics in applied environmental data modeling. The workshop will consist of computing and modeling tutorials, presentations from graduate student participants, and several invited talks from established leaders in environmental data modeling. Tutorials and invited talks will address useful ideas and tools directly applicable to student participants' current and future research. To facilitate the exchange of information and shared learning, student talks should focus on modeling or computing challenges faced in their research. Workshop participants will: Develop new modeling and computing skills through hands-on analyses and lectures lead by quantitative scientists Share research findings and explore open questions within and at the interface of environmental, ecological, climatic, and statistical sciences Learn about the National Center for Atmospheric Research (NCAR) and National Ecological Observatory Network (NEON) data resources that can facilitate scientific discovery Workshop tutorials: Climate data analytics -- Doug Nychka, Institute for Mathematics Applied to Geosciences, NCAR. Bayesian statistics and Monte Carlo integration strategies -- Jennifer Hoeting, Department of Statistics, Colorado State University. Hierarchical models for massive spatio-temporal data analysis -- Sudipto Banerjee, Division of Biostatistics, University of Minnesota. Andrew Finley, Department of Forestry, Michigan State University. Please visit the workshop website for additional information. Funded by the National Science Foundation, Division of Emerging Frontiers and the National Center for Atmospheric Research.
  9. A Workshop will be held in the Centre for Research into Ecological and Environmental Modelling (CREEM), University of St Andrews, from 2nd - 4th June 2014. Integrated nested Laplacian approximation (INLA) facilitates the fitting of a large range of complex statistical models by dramatically reducing computation time. This three day workshop discusses how spatial models may be fitted with INLA using the package R-INLA. We discuss a wide range of different types of spatial models, in particular complex spatial models, spatial point process models and hierarchical models. We will also introduce the participants to flexible spatial modelling methods using the SPDE approach to spatial modelling and provide an outlook to recent developments. Data examples will mainly be related to ecological studies but the course is equally relevant to researchers from other fields and in-depth knowledge of ecology is not expected. Teaching will be a combination of lectures, computer sessions and discussions. Participants are encouraged to bring their own data set but this is not a requirement. The programme (lectures and practicals) will include: a general introduction to integrated nested Laplacian approximation ( INLA) how to fit simple (non-spatial models) in R- INLA an overview of types of spatial models and examples examples of simple spatial models in R-INLA more complex spatial models, joint models, marked point patterns, models with multivariate RFs examples of complex spatial models in R-INLA There will be ample opportunity for: hands-on practical exercises feedback/ questions and answers time for discussion of participants' data sets in groups Participants are encouraged to bring their own data set but this is not a requirement. For more information about the workshop content please contact Janine Illian, email:janine@mcs.st-and.ac.uk Instructors Janine Illian, (University of St. Andrews) Sigrunn Sørbye, (University of Tromsø, Norway) Daniel Simpson, (Norwegian University of Science and Technology) Places will be filled on a first-come, first served basis on the receipt of a completed registration form and payment in full. A registration form is available here: http://creem2.st-andrews.ac.uk/registration-and-fees/ Please contact: Rhona Rodger Centre for Research into Ecological and Environmental Modelling University of St Andrews The Observatory, Buchanan Gardens St. Andrews Scotland KY16 9LZ Tel:+44 1334 461842 Fax: +44 1334 461800 Email: rmr5@st-andrews.ac.uk
  10. Training Announcement Data Analysis IIIB: Environmental Sampling and Monitoring using R (CSP4230) Course Dates: December 10-14, 2012 Location: Shepherdstown, WV Course Description/Course Overview: This course will develop the participant’s skills needed to monitor species trends and distributions, and assess changes due to management actions or impacts in the environment. The design aspects used in class will address the ecological and predictive capacity of prospective approaches, with the overall aim of increasing the predictive power of the analyses and reducing the error associated with modeling the environment. The overall goal of the course is to familiarize the participants with the statistical sampling concepts and definitions, and the “where”, “when”, and “how” of sampling. The six primary objectives of the course will include: site selection designs, stratification, panel rotation designs, field methods and their influences on detectability, status estimation, and trend estimation. Data Analysis IIIB course will explore the principles and application of analytical approaches and design techniques important to the management of threatened and endangered plant and animal populations. Emphasis will also be placed on the development of design and analytical skills, and the estimation of status and trends. The course is designed for the students to learn the concepts and techniques through lectures, exercises, and working with data sets. The aim of these exercises is to familiarize students with the mathematical notation, statistical approaches, and modeling techniques frequently used in designing and implementing field studies. Concepts and techniques covered in class will include: (1) haphazard and convenience sampling; (2) terminology; (3) site selection and variable probability sampling; (4) stratification and “soft” stratification using GRTS: (5) panel rotation designs and concept of connectedness; (6) field methods and using repeat visits for presence; (7) bootstrapping and computer simulation; (8) status estimation using quadrat and distance methods; and (9) trend estimation for both abrupt and long-term trends. Instructors: Dr. Timothy J. Robinson (University of Wyoming, Laramie Campus) Dr. Dave R. Smith (USGS Leetown Science Center, WV) Who Should Attend: The course is designed for individuals who are competent in basic statistics and are familiar with linear and logistic regression, and how to use an ANOVA table. Students should be interested in developing and/or strengthening their ability to perform reliable and unbiased analyses. We are targeting FWS biologists and others whose job responsibilities include the assessment and analysis of population or habitat data or trends in populations for a variety of activities or responsibilities. Course Length: 4 ½ days/36 hours Course Objectives: The objective of this course is to develop critical monitoring and design skills, based upon reliable analytical techniques that are consistent with statistical sampling theory and field implementation; whereby, participants will be able to assess and monitor the distribution of plant and animal species based upon both abiotic and biotic attributes of the species and its environment. Cost: There is no tuition fee for FWS, NPS, and BLM personnel. Tuition is $1195 for non-FWS participants. How to Apply: Register on-line at https://doilearn.doi.gov/. Non-DOI employees should contact Barbara Evans at 304-876-7451 or (barbara_evans@fws.gov). The course code is CSP4230. Questions: Please contact Joe W. Witt (joe_witt@fws.gov) or So Lan Ching (so_lan_ching@fws.gov), Division of Conservation Science and Policy, at 304/876-7447 or 304/876-7771.
  11. The Bioacoustics Research Program at the Cornell Lab of Ornithology in Ithaca, NY will be running a Sound Analysis Workshop from August 6-10, 2012. There are 4 places available (maximum class size is 10). Please see here for more details http://www.birds.cor...lysis-workshops . The curriculum focuses on sound spectrographic analysis techniques and how they can be applied to biological research. We mainly use Raven, which is a sound analysis and visualization software tool developed at BRP, for instruction and analysis in this course. The standard fee is $1,300, but there is a discounted rate of $1,040 for registered students (Bachelors, Master or Ph.D.). The fee covers tuition, lunches, and a complimentary 1-yr license for Raven. Please contact Liz Rowland, edr6@cornell.edu if you're interested or have questions.
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