2024/2025 Courses

2024/2025 Course Offerings Related to
Forest Biometrics, Measurements, and Computation

This is an overview of the course offerings from the UBC Faculty of Forestry related to Forest Biometrics, Measurements, and Computation in 2024/2025 taught by Forest Biometrics faculty.

Undergraduate Courses:

FRST 231 Introduction to Biometrics – Basic theories of probability and statistics. Sampling distribution, methods of estimation and hypothesis testing; goodness of fit and tests for independence; analysis of variance, regression and correlation. Instructor: Varhola – 2024/25 W1; Alila – 2024/2025 W2
FRST 232 Computer Applications in Forestry, required for students in BSF, BSc, elective for BSCN and BUF program – This course covers techniques involved in solving forestry data problems, preparing academic report using powerful tools, managing and formatting a wide range of data using R Markdown, Excel, VBA, GIS, Word processing and database management tools. Instructor: Colton – 2024/25, W1, TBD 2024/25 W2
Delivery method: Hybrid
FRST 239 Tree and Stand Measurements, required for BSF students, optional for other programs. Tree and plot measures, basic sampling designs, log scaling, tree volume and biomass measurements and models, and introduction to GIS and Remote sensing data for forest resources management. Instructor: Salmon;
2024/25, W2
Delivery method: In-Person
FRST 339 Forest Level Measurements and Productivity, required for BSF students – This course provides background on the skills required for collecting and analyzing data required for forest resources inventories, including sampling designs, fundamentals of model fitting, growth and yield, and GIS. Instructor: Lam;
2024/25, W2
Delivery method: In-Person
FRST 430 Advanced Biometrics, required for Forest Sciences UG students – This course provides an overview of theory and application of linear models for observational data and experimental designs.

Note: Graduate students, please register for the graduate-level version currently taught as FRST 533C.

 Instructor: Eskelson
2024/25, W1
Delivery method: In-PersonSyllabus

Other relevant, quantitative undergraduate-level courses:

FRST 305 Silviculture, W1 – Silviculture concepts and principles; stand dynamics; artificial and natural regeneration; cultural techniques for forest stand establishment and stand tending; silvicultural systems; decision making and development of prescriptions; connections to forest planning. Instructor: Montwe

FRST 422 Mathematical Modelling in Forest Resource Analysis, W1 – Modelling techniques used in strategic and tactical forest resources analyses. Instructor: Paradis

FRST 436 Growth and Yield, W2 – Techniques of growth and yield projection and discussion of modelling approaches. Exploration of stand dynamics, quantitative implications of management treatments and environmental limitations to tree and stand growth. Instructor: Barbeito

FRE 490 002 Spatial Data Analysis and Remote Sensing, W2 – This course introduces students to spatial data analysis and remote sensing using the R programming language with a focus on social science applications. Instructor: Proctor (UBC Land and Food Systems)

Graduate Courses:

FRST 505C Directed Studies in Forest Science: Application in Data Science in Forest Resources – This course covers the application of Data Science methods in forestry and natural resources using Python. The emphasis is on exploring descriptive data analytic approaches and data wrangling applications for a big dataset to help select appropriate machine learning methodologies for predictive analysis. Instructor: Ahmed
Next offered: 2025/26, W2
Delivery method: Hybrid
FRST 530 Advanced Modelling Methods for Natural Resources Applications – This course covers linear, nonlinear and generalized linear models, with mixed effects versions of each of these. Applications to forests and other natural environments are used as examples.
Note: While not listed as an official pre-requisite, this course requires prior knowledge of linear model theory and applications (e.g., FRST 430/FRST 533C) as well as some experience with R.		 Instructor: Eskelson
2024/25, W2
Delivery method: In-Person
FRST 531 Applied Multivariate Statistics – This course covers the application of a variety of multivariate methods using R for examples. Instructor: Ahmed
Next offered: 2025/26, W2
Delivery method: Hybrid
FRST 533C Problems in Statistical Methods: Advanced Biometrics – This course provides an overview of theory and application of linear models for observational data and experimental designs.
Note: This course is cross-listed with FRST 430. Graduate students enroll in FRST 533C and have additional tasks in assignments and midterm and final exams.		 Instructor: Eskelson
2024/25, W1
Delivery method: In-PersonSyllabus
FRST 533C Problems in Statistical Methods: Applied Spatial Statistics – This course covers an introduction to the theory of spatial statistics with applications to natural resources examples. Instructor: Eskelson
Possibly offered in 2025/26, W2
FRST 556 Land Information Acquisition and Analysis, restricted to MFSM student – This course covers the principles and application of forest data acquisition and use. Instructor: Mulverhill;
2024/25, W1
Delivery method: In-Person
GEM 530 Geospatial Data Analysis, restricted to MGEM students – This course covers the fundamentals of Python programming and scripting as it relates to geospatial data analysis and manipulation. Instructor: Seely
2024/25, W1
Delivery method: In-Person
GEM 540 Linear Regression Models and Introduction to Spatial Statistics, W1&W2, restricted to MGEM students – This course provides an overview of theory and application of linear models for observational data (W1) and an introduction to spatial statistics (W2). Instructor: Barbeito
2024/25, W2
Delivery method: In-Person

 

Other graduate-level, applied statistics courses across UBC campus:

BIOL 501.101 Quantitative Methods in Ecology and Evolution, W1 – This course covers quantitative methods for data analysis in ecology and evolution. The format is a mixture of lectures/discussions on methodological topics and practical workshops using the R package. Instructor: Schluter (UBC Zoology)

FISH 506H Statistics in Ecology and Marine Sciences, W1 – Data in ecology and marine sciences are frequently associated with large challenges. Controlled experiments are often difficult and observational studies are often associated with missing data and measurement error. This class will introduce some of the challenges of using statistics to answer questions in ecology and marine sciences and the statistical tools developed to handle them. Topics covered in this class are: missing data, multiple imputation, censored and truncated data, GLMs, overdispersion, hidden Markov models, and state-space models. This course is a statistics class for graduate students in the Department of Statistics (STAT) and the Ocean and Fisheries Graduate program (OCF). This class is intended for students with good statistics background and some familiarity with R. The class is not recommended for students will little experience analysing data and those with limited R programming skills. Instructor: Auger-Methe (UBC Statistics)

507C 202 Experimental Design and Hierarchical Model Building with Bayesian Inference, W2. Instructor: Wolkovich (UBC Forestry)

FRST 532C-301 Quantitative Methods in Wildlife Ecology, W1 –  How can we understand and manage wildlife in rapidly-changing environments? Rigorous, quantitative methods are often required to evaluate the status of wildlife populations and test hypotheses about what is causing them to change. This course will provide an overview and hands-on practice with analytical methods commonly used in animal ecology and conservation. Students should have completed undergraduate (and/or graduate) courses in animal ecology and statistics, and have familiarity with R statistical software. Instructor: Burton (UBC Forestry)

 GEOS 506 201 Population Dynamics in Time and Space: Models, Data and Applications, W2 – Mathematical models are fundamental for describing and predicting population dynamics in time and space. Emphasis on implementation of theoretical and applied population models of plants and animals. Recommended: Undergraduate coursework in ecology and experience using statistical software (contact instructor for more information). Instructor: Williams (UBC Geography)

STAT 545A/B Exploratory Data Analysis, W1 – Empowering students to write a clean and modern data analysis. https://stat545.stat.ubc.ca/ Instructor: (UBC Statistics)

 

There are probably many more relevant courses available that I do not know about! If you know about courses that you think should be listed here, please e-mail bianca.eskelson@ubc.ca with that information. Thank you!

 

Statistics help available on UBC campus:

1) Free Statistical Consultation Options: https://www.stat.ubc.ca/free-statistical-consultation-202324-0 –> need to submit requests to align with term schedules of stats consulting courses

2)   Applied Statistics and Data Science Group (ubc.ca)

  • Provide workshops and short courses
  • The Statistical Opportunity for Students (SOS) program (ubc.ca)
    • Hourly Rates for ASDA statistical consultant:
      • UBC affiliated faculty or students: $120
      • Non-UBC client: $210
    • Hourly Rates for statistical faculty consultant:
      • UBC affiliated faculty or students: $240
      • Non-UBC client: $420

NOTE: BUDGET for this service in your grant proposals!