Resource Selection Function Workshop

The Oregon Chapter of The Wildlife Society is hosting a two and a half day RSF workshop, taught by Dr. Ryan Long from the University of Idaho. The workshop will be held May 23rd -25th, in Adair Village (Near Corvallis), at the ODFW Office conference room.

Topics will include:

workshop.PNG

  1. Attendees will need to provide their own laptop computers for completing workshop exercises.
  2. Computers will need to have the most recent versions of ArcGIS and R (64-bit) installed prior to the workshop:
    1. 21-day trial versions of ArcGIS are available for download: http://www.esri.com/arcgis/trial
    2. R: The following required packages should be installed in advance: lme4, MASS, and ruffit. The first two packages can be installed from CRAN. The ruffit package must be installed by running the following code in R:install.packages(“ruf”,repos=”http://www.stat.ucla.edu/~handcock”).

REGISTER NOW!

May 23-25, 2018
Address: 7118 NE Vandenberg Ave, Adair Village, OR 97330.
REGISTRATION: $200; Boxed lunches available for $20.
Any questions, please contact ORTWS President Elect John Goodell jfiskegoodell@gmail.com

Full Course Description

Space-use decisions made by animals in heterogeneous environments can reflect a variety of important processes, including the acquisition and investment of energy, avoidance of mortality from predation or other sources, intra- and interspecific competition, and interactions with both natural and anthropogenic features of the landscape. Consequently, quantifying patterns of resource selection by animals can provide key insights into relationships among the environment, individual fitness, and population dynamics that are critical for making effective management and conservation decisions. Although powerful model-based approaches to quantifying resource selection have been developed in recent years, many managers and researchers continue to use outdated techniques that provide limited insight into complex wildlife-habitat relationships. The objective of this course is to provide participants with the skills and confidence necessary to proceed from a raw dataset of animal locations and habitat characteristics to a final resource selection function using modern modeling techniques. Course structure will consist of lecture modules in the mornings (roughly 30% of the course) focused on key elements of the background and theory of resource selection analysis, and hands-on computer labs in the afternoons (roughly 70% of the course). Some previous experience with ArcGIS and/or R statistical software will be helpful.

Course Topics

  • Lecture: Introduction to resource selection analysis
    • Central definitions and concepts (use, availability, selection, preference, etc.)
    • Spatial and temporal scale (1st through 4th order selection and the importance of daily and seasonal patterns of selection)
    • Sampling and study design (the various sampling schemes and units typically associated with resource selection studies)
    • Categorical data and selection ratios (2D vs. 3D selection ratios, selection ratios as the response variable in a modeling framework)
    • Modeling resource selection (advantages, disadvantages, goals, and steps)
  • Lecture: Logistic regression
    • The logistic model and classic logistic design
    • Difficulties of the classic approach
    • Mixed-effects logistic regression (with a discussion of conditional logistic regression)
  • Hands-on computer lab: Modeling resource selection using mixed-effects logistic regression
  • Lecture: Modeling use as a continuous variable
    • Resource utilization functions (RUFs; Marzluff et al. 2004, Millspaugh et al. 2006)
    • Negative binomial regression (Sawyer et al. 2006, 2007, 2009)
  • Hands-on computer lab: Modeling resource selection using the RUF approach
  • Hands-on computer lab: Modeling resource selection using negative binomial regression
  • Interactive presentation: Mapping predicted probability of use from an RSF across a landscape
  • Interactive presentation: K-fold cross validation

Instructor Contact Information

Ryan Long
Department of Fish and Wildlife Sciences
University of Idaho
Moscow, ID 83844
E-mail: ralong@uidaho.edu
Phone (office): 208-885-7225

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