Teaching in Yellowstone
David W. Roberts
Department of Ecology
Montana State University
I am a vegetation ecologist interested in:
- vegetation theory
- simulation modeling
- multivariate analysis of
As I currently serve as Department Head, my teaching assignment is somewhat reduced.
My primary teaching assignment is one undergraduate-level course and
two alternating graduate-level courses:
- Rocky Mountain Vegetation (BIOE408) is a senior-level course in
place-based vegetation ecology. We cover species identification in the field,
plant ecophysiology, and community ecology, all while emphasizing the vegetation
of the Rocky Mountains. The course involves several all-day field trips into
the Gallatin Mountains, and extensive lab work in map and biodiversity analysis.
- Analysis of
Ecological Communities (BIOE 540) is a hands-on multivariate analysis
course taught in the R environment. The course includes sections on individual
species mapping with GLM, GAM, and TREE/Random Forests models, ordination with PCA, PCO,
NMDA, CCA, and FSO, and classification by hierarchical and non-hierarchical methods
including optpart and optsil.
The syllabus is available
here and the lab manual
is available here
- Vegetation Ecology (BIOE 534) is a primary literature review of benchmark
papers in the vegetation theory and analysis, and stresses the development of
modern thought in vegetation ecology.
I am the author of several R packages for ecological analysis.
- labdsv — the Lab for Dynamic Synthetic Vegephenomenology basic package. Data visualization,
ordination, indicator species analysis
- optpart — optimal partitioning algorithms, goodness-of-clustering statistics
- fso — fuzzy set and multivariate fuzzy set ordination
- coenoflex — gradient-based ecological community simulation
These packages are available at the Comprehensive R Archive Network here.
Recent and Current Research Projects
Grand Teton National Park Vegetation Data Management System
As part of an effort to develop a simulation model of the future vegetation of
Grand Teton National Park (see just below) I have undertaken
a systematic revision of the basic data on vegetation of the Park (and nearby
National Forests) using a combination of the GRASS GIS system, the PostgreSQL
database system, and R statistical software. The base data consists of 745
detailed vegetation sample plots, and 1122
accuracy assessment plots with reduced detail on vegetation composition. The
vegetation map itself consists of more than 49000 polygons of 52 specific map
PostgreSQL is an extraordinary open-source relational database that links
directly to GRASS and R, so that data are held in a single location, with
spatial operations managed by GRASS, statistical calculations managed by R, and
full database query capability in PostgreSQL. The current SQL schema for the
project is available here
The integration of the three software components allows me to use the best tool
for each task while managing the data as a single entity. GRASS provides an
effective integration of raster and vector data, and is connected directly to the
PostgreSQL database for point and polygon attributes. While R is capable of
working with spatial data I find the GRASS data storage superior for large raster
data sets, and the GRASS geographic and imaging routines simpler for routine
use. While PostgreSQL can be spatiallly enabled into PostGIS, by storing the
polygon spatial data in GRASS rather than PostgreSQL the database tables are
directly readable and writable in R, which I use for all aspects of
The GRASS GIS system allows comprehensive script-based management of spatial
data and imagery.
Simulating the Future of Grand Teton National Park
I am developing a GIS-based simulation model of the future
vegetation of Grand Teton National Park. The project grows out of a previous
Park-directed effort map the vegetation of the Park (see here).
The base data are described just above
The model is a state-and-transition model written in FORTRAN interfaced
to the GIS for both ARC and GRASS. Each polygon follows a type-specific successional
trajectory subject to type- and time-specific disturbance regimes. Climate
change is implemented as a change in base environment, which in turn can change
the underlying vegetation type.
Solid lines (with numbers greater than one) represent successional development
dotted lines (with numbers less than one) represent disturbance events in
probability of occurrence in a given year.
Work is still in progress and interim reports will be posted here.
Terrestrial Ecosystem Unit Inventory of the Beartooth Mountains
The Beartooth project is what the US Forest Service calls a
"Terrestrial Ecosystem Unit Inventory." This is an integrated potential
vegetation/soil classification that employs sample plots with full vascular
plant species abundances and full soil pits. Our work is on the Custer National
Forest section of the Beartooth Mountains, and includes 511 sample plots
collected through a collaboration of the Custer National Forest and the LabDSV
at Montana State University. We have recently completed the final ecological type
classification and mapping. The final report is available