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Applicability of Dynamic Energy Budget (DEB) models across steep environmental gradients

Robust ecological forecasting requires accurate predictions of physiological responses to environmental drivers. Energy budget models facilitate this by mechanistically linking biology to abiotic drivers, but are usually ground-truthed under relatively stable physical conditions, omitting temporal/s...

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Autores principales: Monaco, Cristián J., McQuaid, Christopher D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6219521/
https://www.ncbi.nlm.nih.gov/pubmed/30401809
http://dx.doi.org/10.1038/s41598-018-34786-w
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author Monaco, Cristián J.
McQuaid, Christopher D.
author_facet Monaco, Cristián J.
McQuaid, Christopher D.
author_sort Monaco, Cristián J.
collection PubMed
description Robust ecological forecasting requires accurate predictions of physiological responses to environmental drivers. Energy budget models facilitate this by mechanistically linking biology to abiotic drivers, but are usually ground-truthed under relatively stable physical conditions, omitting temporal/spatial environmental variability. Dynamic Energy Budget (DEB) theory is a powerful framework capable of linking individual fitness to environmental drivers and we tested its ability to accommodate variability by examining model predictions across the rocky shore, a steep ecotone characterized by wide fluctuations in temperature and food availability. We parameterized DEB models for co-existing mid/high-shore (Mytilus galloprovincialis) and mid/low-shore (Perna perna) mussels on the south coast of South Africa. First, we assumed permanently submerged conditions, and then incorporated metabolic depression under low tide conditions, using detailed data of tidal cycles, body temperature and variability in food over 12 months at three sites. Models provided good estimates of shell length for both species across the shore, but predictions of gonadosomatic index were consistently lower than observed. Model disagreement could reflect the effects of details of biology and/or difficulties in capturing environmental variability, emphasising the need to incorporate both. Our approach provides guidelines for incorporating environmental variability and long-term change into mechanistic models to improve ecological predictions.
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spelling pubmed-62195212018-11-07 Applicability of Dynamic Energy Budget (DEB) models across steep environmental gradients Monaco, Cristián J. McQuaid, Christopher D. Sci Rep Article Robust ecological forecasting requires accurate predictions of physiological responses to environmental drivers. Energy budget models facilitate this by mechanistically linking biology to abiotic drivers, but are usually ground-truthed under relatively stable physical conditions, omitting temporal/spatial environmental variability. Dynamic Energy Budget (DEB) theory is a powerful framework capable of linking individual fitness to environmental drivers and we tested its ability to accommodate variability by examining model predictions across the rocky shore, a steep ecotone characterized by wide fluctuations in temperature and food availability. We parameterized DEB models for co-existing mid/high-shore (Mytilus galloprovincialis) and mid/low-shore (Perna perna) mussels on the south coast of South Africa. First, we assumed permanently submerged conditions, and then incorporated metabolic depression under low tide conditions, using detailed data of tidal cycles, body temperature and variability in food over 12 months at three sites. Models provided good estimates of shell length for both species across the shore, but predictions of gonadosomatic index were consistently lower than observed. Model disagreement could reflect the effects of details of biology and/or difficulties in capturing environmental variability, emphasising the need to incorporate both. Our approach provides guidelines for incorporating environmental variability and long-term change into mechanistic models to improve ecological predictions. Nature Publishing Group UK 2018-11-06 /pmc/articles/PMC6219521/ /pubmed/30401809 http://dx.doi.org/10.1038/s41598-018-34786-w Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Monaco, Cristián J.
McQuaid, Christopher D.
Applicability of Dynamic Energy Budget (DEB) models across steep environmental gradients
title Applicability of Dynamic Energy Budget (DEB) models across steep environmental gradients
title_full Applicability of Dynamic Energy Budget (DEB) models across steep environmental gradients
title_fullStr Applicability of Dynamic Energy Budget (DEB) models across steep environmental gradients
title_full_unstemmed Applicability of Dynamic Energy Budget (DEB) models across steep environmental gradients
title_short Applicability of Dynamic Energy Budget (DEB) models across steep environmental gradients
title_sort applicability of dynamic energy budget (deb) models across steep environmental gradients
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6219521/
https://www.ncbi.nlm.nih.gov/pubmed/30401809
http://dx.doi.org/10.1038/s41598-018-34786-w
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