Quick Start

This guide will get you started with nuee quickly.

Basic NMDS Analysis

>>> import nuee
>>> import matplotlib.pyplot as plt

>>> # Load sample data
>>> species_data = nuee.datasets.varespec()
>>> env_data = nuee.datasets.varechem()

>>> # Perform NMDS ordination
>>> nmds_result = nuee.metaMDS(species_data, k=2, distance="bray")
>>> print(f"NMDS Stress: {nmds_result.stress:.3f}")
NMDS Stress: 0.133

>>> # Plot the ordination
>>> fig = nuee.plot_ordination(nmds_result, display="sites")
>>> plt.title("NMDS Ordination of Lichen Communities")
>>> plt.show()

Diversity Analysis

>>> import nuee

>>> # Load data
>>> species = nuee.datasets.BCI()

>>> # Calculate Shannon diversity
>>> shannon_div = nuee.shannon(species)
>>> print(f"Mean Shannon diversity: {shannon_div.mean():.3f}")
Mean Shannon diversity: 3.821

>>> # Calculate Gini-Simpson diversity (1 - sum(p^2))
>>> simpson_div = nuee.simpson(species)
>>> print(f"Mean Gini-Simpson diversity: {simpson_div.mean():.3f}")
Mean Gini-Simpson diversity: 0.959

>>> # Calculate species richness
>>> richness = nuee.specnumber(species)
>>> print(f"Mean species richness: {richness.mean():.1f}")
Mean species richness: 90.8

>>> # Plot diversity
>>> fig = nuee.plot_diversity(shannon_div)
>>> plt.show()

Constrained Ordination (RDA)

>>> import nuee
>>> import matplotlib.pyplot as plt

>>> # Load data
>>> species = nuee.datasets.dune()
>>> env = nuee.datasets.dune_env()

>>> # Perform RDA
>>> rda_result = nuee.rda(species, env[["A1", "Moisture", "Manure"]])

>>> # Create biplot
>>> fig = nuee.biplot(rda_result) # TODO broken !
>>> plt.title("RDA Biplot of Dune Meadow Vegetation")
>>> plt.show()

>>> # Fit environmental vectors
>>> envfit_result = nuee.envfit(rda_result, env[["A1", "Moisture", "Manure"]])
>>> print(envfit_result)

Note

envfit replicates vegan’s API but the permutation p-values and vector scaling are still being tuned. Results may differ slightly from vegan::envfit.

PERMANOVA Test

>>> import nuee

>>> # Load data
>>> species = nuee.datasets.mite()
>>> env = nuee.datasets.mite_env()

>>> # Calculate distance matrix
>>> distances = nuee.vegdist(species, method="bray")

>>> # Run PERMANOVA
>>> permanova_result = nuee.adonis2(distances, env[['SubsDens', 'WatrCont']])
>>> print(permanova_result)

Rarefaction Analysis

>>> import nuee
>>> import matplotlib.pyplot as plt

>>> # Load data
>>> species = nuee.datasets.BCI()

>>> # Calculate rarefaction curves
>>> rarefaction = nuee.rarecurve(species, step=10)

>>> # Plot rarefaction curves
>>> fig = nuee.plot_rarecurve(rarefaction)
>>> plt.title("Species Accumulation Curves")
>>> plt.show()

Next Steps

• Check out the User Guide for more detailed information

• Browse the API Reference for complete function documentation

• See Examples for more advanced use cases