TY - JOUR
T1 - Diversity from genes to ecosystems
T2 - A unifying framework to study variation across biological metrics and scales
AU - Gaggiotti, Oscar E.
AU - Chao, Anne
AU - Peres-Neto, Pedro
AU - Chiu, Chun Huo
AU - Edwards, Christine
AU - Fortin, Marie Josée
AU - Jost, Lou
AU - Richards, Christopher M.
AU - Selkoe, Kimberly A.
N1 - Publisher Copyright:
© 2018 The Authors. Evolutionary Applications published by John Wiley & Sons Ltd
PY - 2018/8
Y1 - 2018/8
N2 - 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 behaviour 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.
AB - 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 behaviour 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.
KW - Hill numbers
KW - biodiversity indices
KW - genetic diversity
KW - hierarchical spatial structure
KW - species diversity
UR - http://www.scopus.com/inward/record.url?scp=85042157403&partnerID=8YFLogxK
U2 - 10.1111/eva.12593
DO - 10.1111/eva.12593
M3 - Article
AN - SCOPUS:85042157403
SN - 1752-4563
VL - 11
SP - 1176
EP - 1193
JO - Evolutionary Applications
JF - Evolutionary Applications
IS - 7
ER -