Diversity in Biology: definitions, quantification, and models

TL;DR

This paper reviews the concept of diversity across various scientific fields, discussing mathematical principles, definitions, applications, and how diversity is quantified in samples versus entire populations.

Contribution

It provides a comprehensive overview of diversity indices, their mathematical foundations, and their application across multiple disciplines, highlighting commonalities and differences.

Findings

Diversity indices are crucial for characterizing complex populations.

Sampling affects the measurement of diversity in populations.

Diversity concepts are widely applicable across scientific fields.

Abstract

Diversity indices are useful single-number metrics for characterizing a complex distribution of a set of attributes across a population of interest. The utility of these different metrics or sets of metrics depend on the context and application, and whether a predictive mechanistic model exists. In this topical review, we first summarize the relevant mathematical principles underlying heterogeneity in a large population before outlining the various definitions of `diversity' and providing examples of scientific topics in which its quantification plays an important role. We then review how diversity has been a ubiquitous concept across multiple fields including ecology, immunology, cellular barcoding experiments, and socioeconomic studies. Since many of these applications involve sampling of populations, we also review how diversity in small samples is related to the diversity in the entire population. Features that arise in each of these applications are highlighted.