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Bridging Ecological Stoichiometry and Nutritional Geometry with homeostasis concepts and integrative models of organism nutrition
Author(s) -
Sperfeld Erik,
Wagner Nicole D.,
Halvorson Halvor M.,
Malishev Matthew,
Raubenheimer David
Publication year - 2017
Publication title -
functional ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.272
H-Index - 154
eISSN - 1365-2435
pISSN - 0269-8463
DOI - 10.1111/1365-2435.12707
Subject(s) - biology , ecology , trophic level , ecological stoichiometry , organism , bridging (networking) , conceptual framework , ecosystem , computer science , sociology , paleontology , computer network , social science
Summary The role of nutrition in linking animals with their environment is increasingly seen as fundamental to explain ecological interactions. The two currently predominant frameworks for exploring questions in nutritional ecology – Nutritional Geometry (NG) and Ecological Stoichiometry (ES) – share common features, but also differ in their goals and origins. NG originates from behavioural ecology using terrestrial insects as model organisms in tightly controlled feeding experiments, while ES originates from biogeochemistry focusing on the transfer of key elements across trophic levels, mainly in aquatic environments. Here, we review the history of these two complementary frameworks, emphasizing the key concepts defining their respective aims, methodologies and focal taxa to answer questions at different ecological scales. We identify and explore homeostasis as a shared conceptual cornerstone of each framework that can be used to bridge knowledge gaps and for developing new hypotheses within nutritional ecology. Expanding on the concept of homeostasis, we introduce dynamic energy budget (DEB) models as a general way to address homeostatic regulation at its fundamental level. Specifically, we describe how a two‐reserve DEB model can be used to track metabolic pathways of nutrients as well as elements and suggest that multi‐reserve DEB models, when integrated and parameterized with NG and ES concepts, can form powerful components of agent‐based models to predict how animal nutrition influences individual and trophic interactions in food webs.

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