A macroecological theory of microbial biodiversity

Area of Science:

• Microbial Ecology
• Biodiversity Science
• Ecological Theory

Background:

• Microorganisms are Earth's most abundant, diverse, and functionally vital organisms.
• Vast microbial community datasets exist but are underutilized for uncovering fundamental ecological patterns.
• Existing data lack unifying explanations for microbial community structure and biodiversity-abundance relationships.

Purpose of the Study:

• To test competing ecological theories against large-scale microbial datasets.
• To identify the best predictors of microbial abundance and diversity-abundance scaling laws.
• To explore unifying explanations for microbial community structure.

Main Methods:

• Analysis of a global dataset comprising over 20,000 samples from diverse ecosystems (environmental, engineered, host-related).
• Evaluation of various ecological theories' power to predict microbial abundance distributions.
• Assessment of diversity-abundance scaling laws within microbial communities.

Main Results:

• Lognormal dynamics, reflecting synergistic stochastic processes, best explain observed microbial abundance and diversity patterns.
• These lognormal dynamics demonstrate predictive power across a wide range of microbial abundances.
• The findings provide a unifying explanation for microbial community structure.

Conclusions:

• Ecological processes governing microbial communities are multiplicative and stochastic, best described by lognormal dynamics.
• Understanding these dynamics is crucial for comprehending the structure and function of microbial ecosystems.
• This research advances biodiversity theory by providing a scalable explanation for commonness and rarity.