Lee, Laura, Atkinson, David ORCID: 0000-0002-9956-2454, Hirst, Andrew G and Cornell, Stephen J ORCID: 0000-0001-6026-5236
(2020)
A new framework for growth curve fitting based on the von Bertalanffy Growth Function.
SCIENTIFIC REPORTS, 10 (1).
7953-.
Text
LL_Growth_modelling_methodology_27-1-20 DA5_SC_AGH2_AGH.docx - Author Accepted Manuscript Download (109kB) |
Abstract
All organisms grow. Numerous growth functions have been applied to a wide taxonomic range of organisms, yet some of these models have poor fits to empirical data and lack of flexibility in capturing variation in growth rate. We propose a new VBGF framework that broadens the applicability and increases flexibility of fitting growth curves. This framework offers a curve-fitting procedure for five parameterisations of the VBGF: these allow for different body-size scaling exponents for anabolism (biosynthesis potential), besides the commonly assumed 2/3 power scaling, and allow for supra-exponential growth, which is at times observed. This procedure is applied to twelve species of diverse aquatic invertebrates, including both pelagic and benthic organisms. We reveal widespread variation in the body-size scaling of biosynthesis potential and consequently growth rate, ranging from isomorphic to supra-exponential growth. This curve-fitting methodology offers improved growth predictions and applies the VBGF to a wider range of taxa that exhibit variation in the scaling of biosynthesis potential. Applying this framework results in reliable growth predictions that are important for assessing individual growth, population production and ecosystem functioning, including in the assessment of sustainability of fisheries and aquaculture.
Item Type: | Article |
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Uncontrolled Keywords: | Animals, Body Size, Species Specificity, Models, Biological |
Depositing User: | Symplectic Admin |
Date Deposited: | 01 Jun 2020 08:53 |
Last Modified: | 18 Jan 2023 23:50 |
DOI: | 10.1038/s41598-020-64839-y |
Open Access URL: | https://www.nature.com/articles/s41598-020-64839-y |
Related URLs: | |
URI: | https://livrepository.liverpool.ac.uk/id/eprint/3089224 |