Individual-based dynamic energy budget modelling of earthworm life-histories in the context of competition
Kim J. Rakel,
Thomas G. Preuss and
André Gergs
Ecological Modelling, 2020, vol. 432, issue C
Abstract:
In the environmental risk assessment of chemicals, ecological modelling can facilitate the quantification of specific protection goals, for instance by the extrapolation of untested situations from toxicity test results. In particular, individual-based models (IBMs) are gaining resonance in the regulatory community as a mean to predict how populations perform under environmental perturbation. In this regard, the hope is that standardised or general designs will increase the applicability and acceptance of model based risk assessments. Strong moves in the direction of generalised IBM designs have been made based on metabolic theories such as the dynamic energy budget (DEB) theory. Here, we parameterise the standard DEB model for the earthworm Eisenia fetida and test the individual-based DEB model by comparing predictions with published data on life-histories measured for individual worms and populations. Overall, the comparison showed good agreement between the simulations and the data, suggesting that the standard DEB model, more precisely DEBs ‘kappa-rule’, characterizing the energy partitioning between somatic and reproductive processes, is applicable to earthworms. The parametrized model is able to predict growth and reproduction for different food quality and availability.
Keywords: Individual-based model; Dynamic energy budget theory; Earthworm; Eisenia fetida; Growth; Reproduction; Population (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304380020302921
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:432:y:2020:i:c:s0304380020302921
DOI: 10.1016/j.ecolmodel.2020.109222
Access Statistics for this article
Ecological Modelling is currently edited by Brian D. Fath
More articles in Ecological Modelling from Elsevier
Bibliographic data for series maintained by Catherine Liu ().