Workshops


I maintain two lists of workshop topics. Ready-to-go workshops are ones I’ve taught relatively recently; their outlines are stable and they’re relatively inexpensive to host. Available workshops aren’t quite “ready-to-go” because their content needs updating before I teach them again. Available workshops usually cost more than ready-to-go ones. Email me at trent at mcdonalddatasciences . com (no spaces) for more information.

Ready-to-Go Workshops

Beginner Distance Sampling

Conventional line and point transect distance sampling, with covariates, in R.

Description

Estimating population abundance is a fundamental task in wildlife biology. Distance-sampling, implemented as line-transects or point-transects, is one of two primary abundance methods, the other being capture-recapture. Distance-sampling estimates abundance by correcting for detection that declines with increasing distance between observer and target. Conventional distance-sampling approaches, which can include detection covariates (e.g., Buckland et al. 2001, and basic models in Program Distance), have a rich history.

In this workshop, I introduce participants to conventional and hierarchical line- and point-transect methods for distance-sampling analysis in Program R. Participants leave able to identify and implement appropriate methods for a given study design, after working through multiple case studies of conventional and hierarchical distance-sampling analyses in R.

Target Audience

I designed this workshop for managers, researchers, and students with a basic understanding of statistics and working familiarity with Program R. If you know how to subset a data.frame and fit and work with lm and/or glm model objects in R, you’ll be able to follow along and use the workshop scripts. Everyone, including R newcomers, should benefit from the foundational “why,” “when,” and “what” discussions.

General Outline of Topics

Session 1: Half day

  1. Welcome
  2. Conventional distance sampling (no covariates)
    1. Line transect methods and example
    2. Point transect methods and example
  3. Conventional distance analysis with detection covariates
    1. Methods and case study
  4. Case study 2
    1. Combined species detection functions, separate species abundance

Session 2: Half day

  1. Introduction to hierarchical distance sampling
  2. Case study 3
    1. Real-world aerial surveys
  3. Case study 4
    1. Real-world aerial surveys
  4. Question and answer

Software

I distribute example datasets, scripts, and other materials via download. The workshop uses the following free software:

I provide software installation instructions ahead of time.

Instructors

My co-instructors and I have conducted and consulted on distance-sampling studies of diverse taxa across the globe, including surveys from the ground, air, and sea. This workshop is a new distillation of beginner content, built from what we’ve learned teaching past workshops for The Wildlife Society, the Society for Marine Mammalogy, the Wyoming Game and Fish Department, and the University of Wyoming.

Trent McDonald, Ph.D., President and Chief Analyst, McDonald Data Sciences

Jason Carlisle, Ph.D., Quantitative Biologist, Wyoming Game and Fish Department

Embere Hall, Ph.D., Science Unit Supervisor, Wyoming Game and Fish Department

Costs

Negotiable. Costs depend on format, length, expenses, and more.

Available Workshops

I’m always open to developing custom statistical and quantitative ecology workshops tailored to your needs. Here’s a list and brief description of workshops I’ve taught in the past:

  • Habitat Modeling: Habitat modeling in ecology is similar in nature to consumer modeling in marketing studies. It uses animal locations to estimate habitat selection functions that identify attractive and unattractive habitat characteristics relative to random selection. Once I’ve identified the important characteristics of resources or habitats, I can map high and low relative selection probability and identify critical habitats. Geographic Information Systems (GIS) are an integral part of modern habitat modeling.

  • Capture-Recapture Analyses: Capture-recapture studies in ecology seek to estimate demographic parameters (survival, emigration, immigration, births, etc.), abundance (the total number of organisms in a group), or both. These studies generally involve capturing organisms, marking them with unique identifiers (tags), and attempting to recapture them later. Under various assumptions, the proportion of unmarked organisms among all organisms, together with the total number of marked organisms, lets me estimate abundance in a population. Capture-recapture studies apply to both changing (“open”) and unchanging (“closed”) populations. Modern capture-recapture studies use capture location and the geographic distance between activity centers and capture effort to improve abundance estimates.

  • Computer-Intensive Statistics: Computer-intensive statistics applies permutation, bootstrap, and simulation methods to determine significance for hypothesis tests, confidence intervals, ANOVA, regression, and more, instead of relying on parametric distributions like the normal, t, or F. The simplicity behind these methods helps practitioners build better intuition for their problems and equips them with results that depend on fewer assumptions.