Resources – Integrated Fisheries Ecology Lab

Teaching

I teach across three levels of the REM curriculum, built around the idea that environmental management is decision-making under uncertainty, and I have taught field courses at Bamfield.

REM 100: Global ChangeFirst-year. How the global environment is changing, why environmental decisions are hard, and how solutions get enacted at global and local scales.
REM 325: Uncertainty, Risk, and Decision AnalysisThird and fourth year. A formal framework for making defensible decisions when our understanding of social-ecological systems is incomplete.
REM 423: Research Methods in Fisheries AssessmentFourth year. Building and applying fish population dynamics models, analysing data, and quantifying uncertainty. Assignments replicate real British Columbia fisheries assessments.
REM 613: Methods in Fisheries AssessmentThe graduate section of REM 423, taught simultaneously with different expectations and assessment.
REM 625: Risk Assessment and Decision AnalysisGraduate. Quantitative methods for handling uncertainty in natural resource management, and for communicating risk to managers, scientists, and the public.
Bamfield Marine Sciences CentreVisiting teaching faculty. Ecological Models & Data, taught twice at Bamfield.
Ecological Models & Data: course materialsLectures, code, and assignments from the Bamfield course, openly available.

Code and tools

Analyses from our papers, and modelling tools we help build or use.

My GitHub repositoriesPublished analyses, simulation models, and R tools from the lab.
CEMPRAAn open-source R package and Shiny app linking environmental pressures to the capacity and productivity of a target species, built for prioritising recovery actions where data are limited.
Joe Model: cumulative effects appThe cumulative-effects component of CEMPRA, usable in the browser without installing anything.

Learning to model

The resources we most often hand to new students. All free.

Statistical RethinkingRichard McElreath's course and R package. The best available introduction to Bayesian inference for ecologists, and the one we start people on.
Statistical Rethinking with brms and the tidyverseA. Solomon Kurz's companion translating the book's models into brms, ggplot2, and tidyverse code.
Applied Time Series Analysis (FISH 550)Holmes, Ward, and Scheuerell's University of Washington course on time series in fisheries and environmental science. Syllabus, lectures, and datasets.
ATSA computer labsThe accompanying lab book, worked through in R.
Bayes BAESA friendly introduction to Bayesian methods from Hannah Watkins, a postdoctoral fellow in our lab, and Helen Yan.

Data

Open data we use and recommend.

Pacific Salmon ExplorerPopulation status, habitat, and biological data for salmon across British Columbia, from the Pacific Salmon Foundation.

Funding and graduate study

Where our students and postdocs find support. We help with these applications.

SFU REM graduate programsProgram structure, requirements, and application deadlines for the MRM and PhD.
NSERC CGS Master'sThe main national scholarship for incoming master's students.
NSERC CGS DoctoralThe doctoral equivalent, for students entering or already in a PhD.
NSERC Postdoctoral FellowshipsNational postdoctoral support. We are glad to co-develop an application.
Liber Ero FellowshipPostdoctoral fellowships for applied conservation research in Canada, with a strong emphasis on partnership and policy impact.

Partners

The organisations we work alongside.

Central Coast Indigenous Resource AllianceIndigenous-led marine stewardship serving the Central Coast Nations.
Kitasoo Xai'xais First NationOur partners in Klemtu on Pacific herring, Dungeness crab, and marine stewardship.
Ha'oom Fisheries SocietySupporting the Nuu-chah-nulth Nations in revitalising their fisheries on the West Coast of Vancouver Island.
Musgamagw Dzawada'enuxw Fisheries GroupFisheries management and stewardship in Musgamagw Dzawada'enuxw territory.
Pacific Salmon FoundationSalmon conservation, research funding, and the data behind the Pacific Salmon Explorer.