Community Ecology Notes

What is a Community?

• In principle: all organisms living in a particular place
• Spatially explicit & different spatial scales
• More generally: restricted to a subset of organisms such as taxonomy or trophic level.

Main Aims of Community Ecology

• Explaining and predicting the distribution and abundance of species in time and space.
• Considering abiotic and biotic factors and underlying mechanisms
• Quantifying patterns and looking for general results (e.g., species-area relationships).
• Studying dynamics of communities and response to disturbance.

Why is it Important?

• Common approach in ecological research from $m^2$ to $km^2$. Species interactions are key, so studying multiple species is important.
• Much ecological theory has been developed at this scale.
• Important for conservation and habitat management, classification, biomonitoring, and diagnostics (e.g., National Vegetation Classification (NVC), River Invertebrate Prediction and Classification System (RIVPACS)).

Criticism of the Community Concept

• Most research is at a single scale: ‘local community’.
• Implicit assumption that the community is closed with arbitrary boundaries.
• Reflects differences expressed by Clements (community is discrete) and Gleason (individualistic view).
• In reality, different processes act at different scales, and local communities are affected by processes at larger scales.

The Meta-Community

• A set of communities linked by dispersal, with multiple interacting species.
• Recognizes that processes occur at different scales.
• Analogous to population vs. meta-population.
• The community is viewed in the regional context, considering neighboring communities and a regional species pool from which species can immigrate.
• Local dynamics are affected by dispersal among communities.

Describing Communities

• Ecological networks
• Temporal change
• Diversity, composition…
• Environmental change, community response, resilience & stability
• Assembly rules

Describing Communities: Four Basic Properties

1. Abundance distributions
2. Evenness and dominance
3. Richness
4. Composition

Evenness and Dominance

• Describe how total abundance is distributed among species.
• More even = ‘more diverse’.
• Many diversity indices (e.g., Shannon-Weiner) combine evenness with species richness.
• Simpson’s evenness ranges from 0 to 1, where 0 indicates low evenness (one/few species dominate) and 1 indicates high evenness (species equally abundant).

Richness

• Number of species in a community.
• Simplest concept but most challenging to measure. Most species in a community are rare (low abundance) = low detection probability.
• More individuals in a sample (or more samples) → more species likely to be found.
• Difficult to separate the role of sampling effort and greater abundance.

Richness – Three Strategies

1. Use 'species density'
2. Estimators of total richness (e.g. Chao indices)
3. Rarefy the data

Comparing Communities

1. Compare richness, evenness, etc.
2. Summarise overall differences in composition using Ordination methods (e.g., NMDS - 'Non-metric multidimensional scaling').

Comparing Communities: Process

• Start with a species x site matrix.
• Calculate a distance matrix to summarise differences in the abundance of all taxa between each site pair.
• Use Bray-Curtis or Jaccard dissimilarity metrics (0 = identical, 1 = no species in common).