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# 🏜️ Desert EcoStats Toolkit

A collection of reproducible R scripts for analyzing desert ecological communities. Designed to process community matrix data (species × plots) and explore biodiversity patterns, species associations, and community structure.

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## 🔁 Workflow Overview

```plaintext
Raw Community Matrix
        │
        ▼
[1] Diversity Indices
    - Richness, Shannon, Simpson
    - Evenness, rarefaction

        ▼
[2] Ordination (NMDS)
    - Visualize community structure
    - Identify compositional patterns

        ▼
[3] Co-occurrence Analysis
    - Detect species-level associations
    - Reveal positive/negative pairings

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📜 Scripts & What They Do

diversity_summary.R

🧮 Calculates basic biodiversity metrics per plot. - Richness: # of species - Shannon & Simpson: Diversity indices - Evenness: How evenly species are distributed - Rarefaction Curve: Sampling effort vs. richness

📤 Outputs: - diversity_summary.csv - rarefaction_curve.pdf

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ordination_nmds.R

📊 Performs Non-metric Multidimensional Scaling (NMDS) using Bray-Curtis dissimilarity. - Reduces high-dimensional data into 2D - Useful for identifying patterns in species composition

📤 Outputs: - nmds_plot.pdf (base R) - nmds_plot_ggplot.pdf (optional: cleaner ggplot version)

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cooccurrence_analysis.R

🔗 Uses the cooccur package to analyze non-random species co-occurrences. - Converts data to presence/absence - Identifies significant positive or negative pairings

📤 Outputs: - cooccurrence_summary.txt (summary of interactions) - all_species_pairs.csv (all pairwise results) - cooccurrence_plot.pdf (heatmap visualization)

map_california_counties.R

🗺️ Generates a simple map of California counties with county labels using the maps package.

📤 Outputs: - california_counties_map.pdf

permanova_nmds.R

🔄 Simulates desert community data, runs a PERMANOVA test across habitat types, and visualizes results with an NMDS plot colored by habitat.

📤 Outputs: - permanova_results.csv - nmds_habitat.png

desert_constrained_ordination_app.R

🖥️ Interactive Shiny app to perform constrained ordination (RDA or CCA) on simulated desert data. Choose the method, run the analysis, and view the ordination plot plus printed summary.

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📂 Directory Structure

desert-ecostats/
├── data/
│   ├── example_community_matrix.csv
│   ├── desert_community_matrix.csv
│   └── desert_environmental_data.csv
├── plots/
│   ├── diversity_summary.csv
│   ├── rarefaction_curve.pdf
│   ├── nmds_plot.pdf
│   ├── cooccurrence_plot.pdf
│   └── ...
├── scripts/
│   ├── diversity_summary.R
│   ├── ordination_nmds.R
│   ├── cooccurrence_analysis.R
│   ├── map_california_counties.R
│   ├── permanova_nmds.R
│   └── desert_constrained_ordination_app.R
└── README.md  ← You are here

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🔧 Requirements

• R ≥ 4.2
• Packages: vegan, cooccur, ggplot2, shiny, maps, here

install.packages(c("vegan", "cooccur", "ggplot2", "shiny", "maps", "here"))

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🚧 Coming Soon

• Constrained ordination (CCA/RDA)
• Indicator species analysis
• Integration of habitat metadata ```