Integrating macroecological metrics and community taxonomic structure

Area of Science:

• Ecology
• Macroecology
• Theoretical Ecology

Background:

• Macroecological theory often focuses on species-level distributions.
• Understanding ecological patterns across higher taxonomic levels is crucial.
• The maximum entropy principle offers a powerful framework for ecological predictions.

Purpose of the Study:

• To extend macroecological theory based on the maximum entropy principle to higher taxonomic categories (genera, families).
• To predict species richness distributions and the dependence of abundance and metabolic rate distributions on taxonomic tree structure.
• To integrate macroecology with taxonomic tree structure for a unified understanding of phylogenetic community structure.

Main Methods:

• Applied the maximum entropy principle to macroecological theory beyond the species level.
• Predicted species richness distributions across genera and families.
• Analyzed the relationship between abundance, metabolic rate, and taxonomic tree structure.

Main Results:

• Predictions for species richness across genera/families for birds, arthropods, plants, and microorganisms showed excellent agreement with data.
• The theory successfully predicted patterns of hyper-dominance and rarity.
• A new relationship between body size and abundance was supported by intertidal invertebrate data.

Conclusions:

• The extended maximum entropy theory accurately predicts ecological patterns across multiple taxonomic levels.
• Integrating macroecology with taxonomic structure provides a unified framework for understanding biodiversity.
• The maximum entropy principle is a robust tool for advancing macroecological theory and phylogenetic community structure research.