Benchmarking successional progress in a quantitative food web

Area of Science:

• Ecology and Ecosystem Management
• Theoretical Ecology
• Aquatic Ecology

Background:

• Succession theory explains community assembly but rarely links species-level processes to system-level changes.
• Plankton succession in lakes is a model for autogenic secondary succession, observable over a growing season.
• Understanding ecosystem-level drivers of change comparable across systems remains a challenge.

Purpose of the Study:

• To mechanistically link species and functional group processes to system-level changes in a pelagic food web.
• To test ecological theories (ecosystem, metabolic, food web, thermodynamics, information) using long-term plankton data.
• To develop and validate indices for quantifying successional progress.

Main Methods:

• Utilized a long-term dataset from Lake Constance including biomass, production, food quality, functional diversity, and mass-balanced food webs.
• Extracted population- and system-level indices to analyze successional trajectories.
• Introduced and applied weighted connectance as an index for energy flow interconnectedness.

Main Results:

• Successional progress in Lake Constance was quantifiable and followed predictable stages.
• Mean body mass, functional diversity, predator-prey weight ratios, trophic positions, and energy flow complexity increased during succession.
• Mass-specific metabolic activity and system export decreased; ascendency and eco-exergy did not increase as predicted.

Conclusions:

• Successional progress in pelagic ecosystems is quantifiable and predictable, integrating functional diversity and metabolic theory.
• Weighted connectance is a suitable index for assessing energy flow evenness and interconnectedness during succession.
• This study provides a benchmark for quantifying successional progress across diverse ecosystems.