Regulation of reproductive processes with dynamic energy budgets. (27th February 2019)

• Record Type: Journal Article
• Authors: Muller, Erik B.; Lika, Konstadia; Nisbet, Roger M.; Schultz, Irvin R.; Casas, Jérôme; Gergs, André; Murphy, Cheryl A.; Nacci, Diane; Watanabe, Karen H.
• Editors: Smallegange, Isabel
• Is Part Of: Functional ecology. Volume 33:Number 5(2019)
• Page Start: 819
• Page End: 832
• Publication Date: 2019-02-27
• Subjects: bioenergetics -- DEB theory -- dynamic energy budget -- rainbow trout; Ecology -- Periodicals; 574.505
• DOI: 10.1111/1365-2435.13298
• Languages: English
• ISSNs: 0269-8463

Abstract

Abstract: Linking organismal‐level processes to underlying suborganismal mechanisms at the molecular, cellular and organ level constitutes a major challenge for predictive ecological risk assessments. This challenge can be addressed with the simple bioenergetic models in the family of dynamic energy budget (DEB), which consist of a small number of state equations quantifying universal processes, such as feeding, maintenance, development, reproduction and growth. Motivated by the need for process‐based models to evaluate the impact of endocrine disruptors on ecologically relevant endpoints, this paper develops and evaluates two general modelling modules describing demand‐driven feedback mechanisms within the DEB modelling framework exerted by gonads on the allocation of resources to production of reproductive matter. These modules describe iteroparous, semelparous and batch‐mode reproductive strategies. The modules have a generic form with both positive and negative feedback components; species‐ and sex‐specific attributes of endocrine regulation can be added without changing the core of the modules. We demonstrate that these modules successfully describe time‐resolved measurements of wet weight of body, ovaries and liver, egg diameter and plasma content of vitellogenin and oestradiol in rainbow trout ( Oncorynchus mykiss ) by fitting these models to published and new data, which require the estimation of less than two parameters per data type. We illustrate the general applicability of the concept of demand‐driven allocation of resources to reproduction by evaluating one of the modules with data on growth and seed production of an annual plant, the common bean ( Phaseolis vulgaris ). Aplain language summary is available for this article. Abstract : Plain Language Summary