Network parameters quantify loss of assemblage structure in human-impacted lake ecosystems

Area of Science:

• Ecology
• Network Theory
• Environmental Science

Background:

• Lake biodiversity alone is insufficient to indicate external pressures, as it overlooks internal community structure changes.
• Network theory suggests unstressed systems exhibit self-organization in species associations, leading to specific frequency distributions.
• Diatom assemblages in lakes provide a valuable model for studying ecological network structures.

Purpose of the Study:

• To identify a proxy for ecological deformation in lake communities using diatom assemblages.
• To test network theory predictions regarding community structure in relation to environmental stress.
• To assess the relationship between human impacts, nutrient loading, and aquatic assemblage structure.

Main Methods:

• Analyzed diatom assemblages from 452 species across 273 lakes in China.
• Applied network theory to examine frequency distributions of species associations (nodal degree).
• Correlated network skewness with environmental variables like total phosphorus, agricultural activity, and urbanization.

Main Results:

• Observed shifts in species association frequency distributions from positive skew (West China, low impact) to negative skew (East China, high impact).
• Found strong correlations between skew values and nutrient loading (total phosphorus) from human activities.
• Demonstrated that positive skew decreases with intensified human impacts and increases during lake recovery.

Conclusions:

• Network parameters, specifically skewness of species associations, can effectively track the loss of aquatic assemblage structure.
• Human pressures significantly alter lake community structure, impacting ecological networks.
• This network-based approach offers a sensitive indicator of ecological deformation in lakes affected by anthropogenic activities.