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Ecology Visualization

Visualization functions for ecological data including species abundance distributions, community composition, ordination plots, diversity comparisons, distance heatmaps, and ecological networks.

Key Concepts

All plot functions return a matplotlib Axes object that can be further customized. Figures can be saved to disk via the output_path parameter. Interactive dashboards require Plotly.

Function Reference

plot_species_abundance_distribution(abundance_data, species_names=None, ax=None, output_path=None, figsize=(10,6), **kwargs) -> Axes

Rank-abundance curve (Whittaker plot). Pass log_scale=True in kwargs for log y-axis. Top 5 species are labeled when names are provided.

plot_diversity_accumulation_curve(diversity_data, ax=None, output_path=None, figsize=(10,6)) -> Axes

Species accumulation / rarefaction curve with optional 95% confidence intervals. Input is a list of dicts with sample_size, species_count, and optional confidence_lower/confidence_upper.

plot_community_composition(community_matrix, species_names=None, sample_names=None, ax=None, output_path=None, figsize=(12,8)) -> Axes

Stacked bar chart of relative abundances across samples.

plot_beta_diversity_ordination(ordination_coords, sample_groups=None, ax=None, output_path=None, figsize=(8,6)) -> Axes

Scatter plot of PCoA/NMDS coordinates. Points colored by sample_groups if provided, otherwise by sample index with a colorbar.

plot_diversity_indices_comparison(diversity_indices, index_names=None, ax=None, output_path=None, figsize=(10,6)) -> Axes

Grouped bar chart comparing multiple diversity indices across samples. Input is a dict mapping index names to arrays.

plot_rank_abundance_curve_comparison(abundance_datasets, ax=None, output_path=None, figsize=(10,6)) -> Axes

Overlay multiple rank-abundance curves for cross-community comparison.

plot_biodiversity_rarefaction(rarefaction_data, ax=None, output_path=None, figsize=(10,6)) -> Axes

Rarefaction curves for multiple communities. Input is a dict mapping community names to lists of {sample_size, species_count} dicts.

plot_ecological_distance_heatmap(distance_matrix, sample_names=None, ax=None, output_path=None, figsize=(10,8)) -> Axes

Heatmap of pairwise ecological distances. Labels shown for 20 or fewer samples.

plot_ecological_network(interaction_matrix, species_names=None, ax=None, output_path=None, figsize=(10,8), **kwargs) -> Axes

Spring-layout network of species interactions. Requires networkx. Pass threshold in kwargs to control minimum edge weight.

create_interactive_ecology_dashboard(ecology_data, output_path=None, **kwargs) -> plotly.Figure

Interactive Plotly dashboard. Requires plotly. Pass diversity_indices key in the data dict. Saves as HTML when output_path is given.

Usage Examples

import numpy as np
from metainformant.ecology.visualization.visualization import (
    plot_species_abundance_distribution,
    plot_beta_diversity_ordination,
    plot_ecological_distance_heatmap,
)

# Rank-abundance curve
abundances = np.array([45, 23, 12, 8, 5, 3, 2, 1, 1])
ax = plot_species_abundance_distribution(abundances, log_scale=True)

# Ordination plot with groups
coords = np.array([[0.1, 0.2], [-0.3, 0.1], [0.2, -0.4], [-0.1, 0.3]])
groups = np.array(["forest", "forest", "grassland", "grassland"])
ax = plot_beta_diversity_ordination(coords, groups, output_path="output/ordination.png")

# Distance heatmap
dm = np.array([[0, 0.3, 0.7], [0.3, 0, 0.5], [0.7, 0.5, 0]])
ax = plot_ecological_distance_heatmap(dm, sample_names=["A", "B", "C"])

Optional Dependencies

  • seaborn -- enhanced styling (optional)
  • plotly -- interactive dashboard (required for create_interactive_ecology_dashboard)
  • networkx -- ecological network plots (required for plot_ecological_network)

Configuration

Environment variable prefix: ECO_

Related Modules

  • metainformant.ecology.community -- data sources for diversity plots
  • metainformant.ecology.ordination -- coordinates for ordination plots
  • metainformant.visualization -- general-purpose plot library