[Paper Review] Linking evolutionary and ecological theory illuminates non-equilibrium biodiversity

Andrew J. Rominger, Isaac Overcast+4 more|arXiv (Cornell University)|May 12, 2017

Genetic diversity and population structure16 references3 citations

TL;DR

This paper proposes a synthesis of ecological and evolutionary theory to understand non-equilibrium biodiversity dynamics by integrating macroecological patterns with population genetic inference from next-generation sequencing data. By using likelihood-based tests and joint genetic-assembly modeling, the framework identifies non-equilibrium states through negative correlations between lineage age and abundance, revealing that both ecological and evolutionary processes drive biodiversity change in ways equilibrium models miss.

ABSTRACT

Whether or not biodiversity dynamics tend toward stable equilibria remains an unsolved question in ecology and evolution with important implications for our understanding of diversity and its conservation. Phylo/population genetic models and macroecological theory represent two primary lenses through which we view biodiversity. While phylo/population genetics provide an averaged view of changes in demography and diversity over timescales of generations to geological epochs, macroecology provides an ahistorical description of commonness and rarity across contemporary co-occurring species. Our goal is to combine these two approaches to gain novel insights into the non-equilibrium nature of biodiversity. We help guide near future research with a call for bioinformatic advances and an outline of quantitative predictions made possible by our approach.

Motivation & Objective

• To address the lack of understanding in how non-equilibrium dynamics shape biodiversity, especially under anthropogenic pressures.
• To overcome the limitations of equilibrium-based ecological and evolutionary theories that obscure historical dynamics and mechanistic causes.
• To develop a framework that combines macroecological patterns with population genetic inference to test for non-equilibrium processes.
• To enable detection of non-equilibrium states through genetic signatures such as population expansion and lineage-age-abundance relationships.
• To guide future research through bioinformatic advances and theory-driven predictions grounded in next-generation sequencing data.

Proposed method

• Uses likelihood-based test statistics, particularly an extended z-score from the exact test of Etienne, to assess goodness of fit between theoretical models and observed species abundance distributions.
• Applies neutral and statistical theories of biodiversity as null models, assuming demographic drift or statistical equilibrium, to compare with empirical data.
• Integrates population genetic models with community assembly theory to detect non-equilibrium dynamics via joint genetic-assembly modeling frameworks.
• Employs next-generation sequencing (NGS) data to extract genome-wide signals of population expansion, selection, and divergence rates.
• Tests for non-equilibrium by examining correlations between lineage age and abundance, expecting negative relationships under non-equilibrium conditions.
• Proposes that model selection favoring population expansion over stationary models indicates non-equilibrium ecological and evolutionary dynamics.

Experimental results

Research questions

• RQ1 How can ecological and evolutionary theories be synthesized to detect non-equilibrium dynamics in biodiversity?
• RQ2 What genetic and demographic signatures indicate that a community is not in ecological or evolutionary equilibrium?
• RQ3 How do non-equilibrium processes such as rapid speciation or sweepstakes immigration leave detectable signals in population genetic data?
• RQ4 Can joint genetic-assembly models improve the detection of non-equilibrium community dynamics compared to traditional equilibrium-based models?
• RQ5 What role do evolutionary relaxation and historical processes play in obscuring non-equilibrium signals in contemporary biodiversity patterns?

Key findings

• Non-equilibrium ecological communities foster non-equilibrium evolution, resulting in a negative correlation between lineage age and abundance, which can be detected through genetic data.
• Population expansion models are favored over demographically stationary models in non-equilibrium communities, indicating dynamic assembly processes.
• Speciation and sweepstakes immigration produce similar population genetic signals—such as rapid population expansion—under non-equilibrium conditions, complicating inference without joint modeling.
• Evolutionary processes that rapidly generate new ecological strategies can force ecological systems out of equilibrium, leading to detectable signals of strong selection and rapid divergence in genomic data.
• Evolutionary demographic equilibrium, where systems forget past non-equilibrium phases, can only be detected using fossil record data, highlighting a key limitation in current molecular approaches.
• The integration of high-throughput sequencing, advanced bioinformatics, and theoretical modeling enables robust detection of non-equilibrium dynamics, offering a path forward for conservation and biodiversity science.