# Run Reproducible BioGeoBEARS Analyses

Phylogenetic biogeography workflows often fail because tree labels, distribution files, and model settings do not align. This skill validates inputs and prepares a reproducible BioGeoBEARS analysis with comparisons and visualizations.

## Install

```bash
npx skillstore add brunoasm/biogeobears
```

## Metadata

- Status: approved
- Slug: brunoasm-biogeobears
- Skillstore revision: r2
- Version status: missing
- Tree hash: 4c6ef9fd6e4dadf930187ffcf2c7c607620de9e6188e194f8484dd4a5d509f75
- Author: brunoasm
- GitHub username: brunoasm
- License: MIT
- Repository: https://github.com/brunoasm/my\_claude\_skills/tree/main/biogeobears
- Ref: a39a91716eadede5f4cdefd78178fed4e837a128
- Supported tools: Claude, Codex, Claude Code
- Audit status: complete
- Agent install advisory: allowed
- Manual install advisory: allowed
- Artifact signature: available
- Audit attestation: unavailable
- Human verification: not\_verified
- Risk factors: filesystem, external\_commands, network
- Quality score: 83
- Quality tier: gold
- Public page: https://skillstore.pages.dev/skills/brunoasm-biogeobears
- Manifest: https://skillstore.pages.dev/api/skills/brunoasm-biogeobears/manifest

## Capabilities

- Validates PHYLIP-like geography files, binary range codes, area counts, and species counts.
- Checks geography species names against tip labels parsed from a Newick tree.
- Reformats CSV or TSV presence data into the format required by BioGeoBEARS.
- Prepares an RMarkdown workflow for DEC, DIVALIKE, BAYAREALIKE, and selected \+J variants.
- Compares fitted models using likelihoods, AIC, AICc, AIC weights, and paired likelihood-ratio summaries.
- Produces saved model objects, ancestral-range PDF plots, an HTML report, and session information.

## Use Cases

- Prepare an island clade study: Validate a tree and island-presence table before reconstructing ancestral ranges.
- Standardize collaborative inputs: Convert mixed CSV or TSV distribution data into a consistent BioGeoBEARS geography file.
- Compare biogeographic models: Prepare a documented workflow that compares model fit and produces plots for a thesis.

## Prompt Templates

### Validate analysis inputs

```
Validate [tree path] and [geography path]. Report rooting, branch-length, label, delimiter, and binary-code problems before changing files.
```

### Reformat distribution data

```
Convert [distribution path] into BioGeoBEARS geography format. Preserve the source, list normalized species names, and validate against [tree path].
```

### Configure model comparison

```
Prepare an analysis for [tree path] and [geography path] using maximum range size [number]. Compare [models] and generate both plot types.
```

### Diagnose and interpret results

```
Review [report path] and [results directory]. Identify convergence concerns, compare supported models, explain parameter uncertainty, and state interpretation limits.
```

## Limitations

- Requires R 4.0 or later, BioGeoBEARS dependencies, RMarkdown packages, and Python 3.
- Input trees must be rooted, include branch lengths, and use labels matching the geography file.
- Runtime grows quickly as area count, maximum range size, and tree size increase.
- Model selection and \+J interpretation require biological justification and current statistical guidance.

## Best Practices

- Keep original inputs unchanged and write normalized copies into a dedicated analysis directory.
- Choose maximum range size from biological evidence because state space and runtime grow quickly.
- Review convergence, parameter estimates, and model assumptions before interpreting AIC rankings.

## Anti Patterns

- Do not continue when tree tips and geography species names differ.
- Do not set maximum range size only to reduce runtime without biological justification.
- Do not interpret \+J support as definitive evidence without checking assumptions and current methodological guidance.

## Security Audit

- Audited at: 2026-07-23T11:31:00.931\+00:00
- Summary: All 110 static findings were adjudicated as false positives. Most detections are Markdown or RMarkdown backticks and intentional relative paths within the generated analysis directory. The explicit file write uses a user-selected output path, with no hidden network access, reconnaissance, or untrusted command evaluation.

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