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Inferring functional traits in a deep-sea wood-boring bivalve using dynamic energy budget theory
Gaudron, S.M.; Lefebvre, S.; Marques, G.M. (2021). Inferring functional traits in a deep-sea wood-boring bivalve using dynamic energy budget theory. NPG Scientific Reports 11(1): 22720. https://dx.doi.org/10.1038/s41598-021-02243-w
In: Scientific Reports (Nature Publishing Group). Nature Publishing Group: London. ISSN 2045-2322; e-ISSN 2045-2322
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| Auteurs | | Top |
- Gaudron, S.M.
- Lefebvre, S.
- Marques, G.M.
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| Abstract |
For species in the deep sea, there is a knowledge gap related to their functional traits at all stages of their life cycles. Dynamic energy budget (DEB) theory has been proven to be an efficient framework for estimating functional traits throughout a life cycle using simulation modelling. An abj-DEB model, which compared with the standard DEB model includes an extra juvenile stage between the embryo and the usual juvenile stages, has been successfully implemented for the deep-sea Atlantic woodeater Xylonora atlantica. Most of the core and primary parameter values of the model were in the range of those found for shallow marine bivalve species; however, in comparison to shallow marine bivalves, X. atlantica required less energy conductance and energy to reach the puberty stage for the same range of body sizes, and its maximum reserve capacity was higher. Consequently, its size at first reproduction was small, and better survival under starvation conditions was expected. A series of functional traits were simulated according to different scenarios of food density and temperature. The results showed a weak cumulative number of oocytes, a low growth rate and a small maximum body size but an extended pelagic larval duration under deep-sea environmental conditions. Moreover, DEB modelling helped explain that some male X. atlantica individuals remain dwarfs while still reproducing by changing their energy allocation during their ontogenetic development in favour of reproduction. The estimation of functional traits using DEB modelling will be useful in further deep-sea studies on the connectivity and resilience of populations. |
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