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Title: Diversity from genes to ecosystems: A unifying framework to study variation across biological metrics and scales

Author
item GAGGIOTTI, OSCAR - University Of St Andrews
item CHAO, ANN - Tsinghua University
item PERES-NETO, PEDRO - Concordia University
item CHIU, CHUN-HUO - National Taiwan University
item EDWARDS, CHRISTINE - Missouri Botanical Garden
item FORTIN, MARIE-JOSEE - University Of Toronto
item JOST, LOU - Ecominga Foundation, Via A Runtun, Banos, Tungurahua, Ecuador
item Richards, Christopher
item SELKOE, KIMBERLY - University Of Hawaii

Submitted to: Evolutionary Applications
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/1/2018
Publication Date: 1/9/2018
Citation: Gaggiotti, O., Chao, A., Peres-Neto, P., Chiu, C., Edwards, C., Fortin, M., Jost, L., Richards, C.M., Selkoe, K. 2018. Diversity from genes to ecosystems: A unifying framework to study variation across biological metrics and scales. Evolutionary Applications. 11:1176-1193. https://doi.org/10.1111/eva.12593.
DOI: https://doi.org/10.1111/eva.12593

Interpretive Summary: Metrics that measure biological diversity play a fundamental role in research and conservation policy planning. Over the decades, the development of biological diversity indices have been tackled independently by scientists involved in three main disciplines; community ecology, taxonomy & systematics and population genetics. Each approach emphasized a different hierarchy of diversity relevant to that field. For instance ecological diversity measures numbers of species in a given community or ecosystem, phylogenetic diversity measures the diversity of the ancestral relationships between species and population genetics measures the diversity among individuals within a species. While each of these approaches is useful for exploring a particular facet of diversity, we currently lack the ability to integrate these measures across different levels of organization in a coordinated and comparable way. In this paper we develop a unifying mathematical framework based on information from theoretical principles to address this knowledge gap. We expect our framework will have multiple applications covering the fields of conservation biology, community and evolutionary genetics.

Technical Abstract: Biological diversity is a key concept in the life sciences and plays a fundamental role in many ecological and evolutionary processes. Although biodiversity is inherently a hierarchical concept covering different levels of organization (genes, population, species, ecological communities and ecosystems), a diversity index that behaves consistently across these different levels has so far been lacking, hindering the development of truly integrative biodiversity studies. To fill this important knowledge gap, we present a unifying framework for the measurement of biodiversity across hierarchical levels of organization. Our weighted, information-based decomposition framework is based on a Hill number of order q = 1, which weights all elements in proportion to their frequency and leads to diversity measures based on Shannon’s entropy. We investigated the numerical behavior of our approach with simulations and showed that it can accurately describe complex spatial hierarchical structures. To demonstrate the intuitive and straightforward interpretation of our diversity measures in terms of effective number of components (alleles, species, etc.), we applied the framework to a real data set on coral reef biodiversity. We expect our framework will have multiple applications covering the fields of conservation biology, community genetics and eco-evolutionary dynamics.