bio-ecological-genomics-community-ecology
Analyzes community composition using constrained ordination (CCA, RDA, db-RDA), variance partitioning (varpart), indicator species analysis (indicspecies multipatt), and distance-based environmental gradient methods with vegan. Links species composition to environmental explanatory variables. Use when testing how environmental gradients structure species communities, identifying habitat indicator taxa, or partitioning explained variation among predictors. Not for basic unconstrained ordination and PERMANOVA (see microbiome/diversity-analysis).
npx skills add BioTender-max/awesome-bio-agent-skills --skill community-ecology --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
## Version Compatibility Reference examples tested with: ggplot2 3.5+, vegan 2.6+ Before using code patterns, verify installed versions match. If versions differ: - R: `packageVersion('<pkg>')` then `?function_name` to verify parameters If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying. # Community Ecology **"Test how environmental variables structure my species communities"** → Link species composition to environmental gradients using constrained ordination (CCA, RDA, db-RDA), partition explained variation among predictor groups with varpart, and identify habitat indicator taxa with multipatt. - R: `vegan::cca()`, `vegan::rda()`, `vegan::dbrda()` for constrained ordination - R: `indicspecies::multipatt()` for indicator species analysis Analyzes species-environment relationships using constrained ordination, variance partitioning, and indicator species analysis. ## Canonical Correspondence Analysis (CCA) CCA models unimodal species responses along environmental gradients. Appropriate when species have optima along gradients (bell-shaped response curves): ```r library(vegan) #
- Version Compatibility
- Canonical Correspondence Analysis (CCA)
- Redundancy Analysis (RDA)
- Forward Selection with ordiR2step
- Distance-Based RDA (db-RDA)
- Variance Partitioning
- Three-Way Partition
- Indicator Species Analysis
- Point-Biserial Correlation
- CCA vs RDA Decision
- Publication-Quality Triplot
- Related Skills
What does the bio-ecological-genomics-community-ecology skill do?
Analyzes community composition using constrained ordination (CCA, RDA, db-RDA), variance partitioning (varpart), indicator species analysis (indicspecies multipatt), and distance-based environmental gradient methods with vegan. Links species composition to environmental explanatory variables. Use when testing how environmental gradients structure species communities, identifying habitat indicator taxa, or partitioning explained variation among predictors. Not for basic unconstrained ordination and PERMANOVA (see microbiome/diversity-analysis).
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill community-ecology --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From BioTender-max/awesome-bio-agent-skills, a repository with 135 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.