A General, Synthetic Model for Predicting Biodiversity Gradients from Environmental Geometry

Area of Science:

• Ecology
• Biodiversity Science
• Theoretical Ecology

Background:

• Biodiversity gradients, observed across latitudes and elevations, are a central topic in ecology with numerous proposed explanations.
• The role of abiotic environmental geometry in shaping these gradients is often hypothesized but lacks comprehensive theoretical evaluation due to fragmented understanding of predicted diversity patterns.

Purpose of the Study:

• To develop a mathematical model synthesizing multiple mechanisms through which environmental geometry can drive biodiversity gradients.
• To predict nuanced and realistic species-richness patterns across geographical and environmental gradients.

Main Methods:

• A mathematical model was constructed to characterize species ranges based on their environmental niches and range size limitations.
• These species ranges were mapped onto simplified geometric environments, specifically a sphere and a cone.
• The model's predictions were compared against empirical biodiversity data and existing geometric models.

Main Results:

• The model successfully predicts realistic species-richness gradients, including latitudinal diversity gradients with tropical plateaus and mid-latitude inflection points.
• It also predicts elevational diversity gradients with maxima at low elevations and highlights a 'mid-environment effect' that enhances species richness in intermediate environments.
• Model predictions align with observed empirical biodiversity gradients and depend on ecological traits in a testable manner.

Conclusions:

• Environmental geometry plays a more significant role in driving biodiversity gradients than previously appreciated.
• The developed model offers a unified framework for several geometric hypotheses and suggests a re-evaluation of their importance.
• The findings emphasize the need to consider geometric constraints and mid-environment effects in ecological studies of biodiversity patterns.