Equity, diversity, and inclusion commitment
This book is open in two senses: openly licensed (anyone can reuse and adapt it), and open to its audience (no learner should feel that this book is not for them).
What “open” means in practice
| Dimension | Our commitment |
|---|---|
| Cost | The book and every tool it teaches (R, RStudio, Quarto, Posit Cloud) are free of charge. No paywalls, no required textbook purchase. |
| Hardware | Posit Cloud (free tier) lets a learner complete every chapter from a smartphone, tablet, or library computer. No need for a personal high-end laptop. |
| Prior experience | The book assumes no prior coding background. Chapters 1–3 use Excel — a tool most learners already have access to — as the bridge into computational thinking. |
| Language background | A glossary is provided. Technical terms are defined on first use. Where English-language conventions diverge from common usage, we say so. |
| Learning differences | Each chapter offers multiple ways through: read, watch the screencast (where available), do the exercises, work the group lab, or take the quiz. There is no single required path. |
| Career direction | Chapters reference careers in research, government forestry agencies, First Nations forestry councils, consulting, NGOs, and field crews — not just academic paths. |
Whose voices are in this book
Forestry analytics has historically been a field dominated by certain demographics. This book is committed to:
- Citing and referencing the work of women, BIPOC, and Indigenous forestry researchers and practitioners. Where classic R / tidyverse documentation is cited, we additionally cite ecological and forestry researchers from diverse backgrounds whose substantive work informs our examples.
- Featuring diverse data sources. The course uses Environmental Reporting BC, the Government of Ontario, and references the BC First Nations Forestry Council.
- Avoiding default examples that exclude. We do not centre Christian-calendar holidays, sports-team affiliation examples, or career arcs that assume a specific cultural background.
Inclusive language
This book follows the following conventions:
- “Learner” rather than “student” — inclusive of returning adults, mature learners, career-changers, and informal learners.
- “Chapter” rather than “week” — does not assume a fixed pacing.
- “Course site” rather than a specific LMS name — portable across institutional contexts.
- Avoidance of ableist language — we work to remove phrases like “easy”, “obvious”, “just”, “see”, or “simply” when they imply that a concept should be effortless. Learning takes work; that is normal.
- Gender-neutral defaults — we use “everyone”, “the learner”, or “they” instead of “guys” or default-masculine language.
- Plain language alongside technical terms — “the tibble (a kind of data frame)” rather than introducing jargon without translation.
Multiple ways of knowing
The quantitative methods in this book — descriptive statistics, group summaries, regression smoothers, spatial overlays — are one way of understanding forests. They are powerful, and they are necessary for many of the questions a working forester or researcher will ask. They are not sufficient on their own.
Traditional Ecological Knowledge (TEK), oral history, participatory observation, place-based experience, and First Nations forestry practices offer complementary forms of knowledge that are equally rigorous, equally evidence-based, and in many cases more deeply informed about the specific forest systems being analysed. A complete forestry analysis brings these forms of knowledge into partnership, not into hierarchy.
For deeper engagement with this idea, see:
- Atleo, C. (2011). Tsawalk: A Nuu-chah-nulth Worldview. UBC Press.
- Kimmerer, R. W. (2013). Braiding Sweetgrass: Indigenous Wisdom, Scientific Knowledge, and the Teachings of Plants. Milkweed Editions.
- BC First Nations Forestry Council resources at https://www.bcfnfc.ca/.
- Mills, A. & McGregor, D. (2022). Indigenous Data Sovereignty in Canada. (Various publications.)