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Unifying concepts of biological function from molecules to ecosystems
Author(s) -
Farnsworth Keith D.,
Albantakis Larissa,
Caruso Tancredi
Publication year - 2017
Publication title -
oikos
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.672
H-Index - 179
eISSN - 1600-0706
pISSN - 0030-1299
DOI - 10.1111/oik.04171
Subject(s) - ecology , function (biology) , ambiguity , ecological network , mutualism (biology) , hierarchy , construct (python library) , clarity , ecosystem , systems ecology , organism , ecosystem ecology , computer science , biology , biodiversity , applied ecology , evolutionary biology , paleontology , biochemistry , economics , market economy , programming language
The concept of function arises at all levels of biological study and is often loosely and variously defined, especially within ecology. This has led to ambiguity, obscuring the common structure that unites levels of biological organisation, from molecules to ecosystems. Here we build on already successful ideas from molecular biology and complexity theory to create a precise definition of biological function which spans levels of biological organisation and can be quantified in the unifying currency of biomass, enabling comparisons of functional effectiveness (irrespective of the specific function) across the field of ecology. We give precise definitions of ecological and ecosystem function that bring clarity and precision to studies of biodiversity– ecosystem function relationships and questions of ecological redundancy. To illustrate the new concepts and their unifying power, we construct a simple community‐level model with nutrient cycling and animal‐plant mutualism, emphasising the importance of its network structure in determining overall functioning. This type of network structure is that of an autocatalytic set of functional relationships, which also appears at biochemical, cellular and organism levels of organisation, creating a nested hierarchy. This enables a common and unifying concept of function to apply from molecular interaction networks up to the global ecosystem.

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