Integrating dynamic energy budget (DEB) theory with traditional bioenergetic models

Nisbet, Roger M.; Jusup, Marko; Klanjšček, Tin; Pecquerie, Laure

doi:10.1242/jeb.059675

Cited by 129 publications

(97 citation statements)

References 82 publications

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“…Similar scaling is possible using the DEB theory for metabolic organization developed by Kooijman (2001). This mechanistic model attempts to explain biological dynamics from cells to populations across a wide range of organismal biodiversity via a mass balance energy approach of individuals (Nisbet et al 2012;Kooijman 2001;Martin et al 2012). The DEB model has several advantages including: relying on simple physiological principles common to all species, a limited number of parameters that integrate genetic and environmental effects on the animal, and a structure that allows for the integration of different time scales (including ontogeny and evolutionary time) (Alunno-Bruscia et al 2009;Martin et al 2012).…”

Section: Rev Fish Biol Fisheriesmentioning

confidence: 99%

“…A problem in its application, however, is that many of the underlying processes are intimately interlinked, complicating the study of individual processes or their contributions (Kooijman 2010). Recent DEB extensions link to bioenergetics (Nisbet et al 2012) and individual based models (IBM; Martin et al 2012). Finally, SDMs use spatial ecological data to predict species range and habitat suitability, and can be parameterized with physiological data to offer a mechanistic view of the fundamental niche that can be mapped in a landscape context for robust mechanistic insights (Kearney and Porter 2009).…”

Section: Rev Fish Biol Fisheriesmentioning

confidence: 99%

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Physiology in the service of fisheries science: Why thinking mechanistically matters

Horodysky

Cooke

Brill

2015

Rev Fish Biol Fisheries

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Behavioral responses of fishes to variability in environmental conditions and habitat quality are central to population-level demographic processes. Although field surveys can correlate abundance to habitat variables (physiochemical, biotic, and structural), they cannot provide mechanistic explanations. Moreover, field surveys are often stratified by time or geographic criteria relevant to humans, whereas fishes stratify by habitat variables relevant to them. If mechanisms underlying behavior are not explicitly understood, conclusions based on survey data can lead to biased inferences as to species-specific habitat requirements and preferences, as well as changes in stock size occurring over time. Because physiology is the transfer function that links specific environmental conditions to behavior and fitness, we argue great gains can be made through the integration of physiology and fisheries science. These are complementary disciplines, albeit ones that generally function at very different temporal and spatial scales, as well as different levels of biological organization. We argue more specifically that integrating physiological approaches with behavioral studies and traditional fisheries survey data (where each approach develops hypotheses to be tested in the other) can mechanistically link processes from cells through populations to place fisheries management in an appropriate ecosystem context. We further contend that population-and species-specific mechanistic understanding of physiological abilities and tolerances can significantly help to: improve stock assessments, describe essential fish habitat, predict rates of post-release mortality, develop effective bycatch reduction strategies, and forecast the population effects of increases in global temperatures and ocean acidification.

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Section: Rev Fish Biol Fisheriesmentioning

confidence: 99%

Section: Rev Fish Biol Fisheriesmentioning

confidence: 99%

Physiology in the service of fisheries science: Why thinking mechanistically matters

Horodysky

Cooke

Brill

2015

Rev Fish Biol Fisheries

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“…Energetic and materials budgets are widely used in ecology to predict how environmental variables alter an organism's performance (e.g., Sousa et al 2008;Nisbet et al 2012). They offer a common framework for handling the diverse traits, life-history characteristics, and metabolic capabilities of different organisms.…”

Section: Introductionmentioning

confidence: 99%

Interactive effects of light, nitrogen source, and carbon dioxide on energy metabolism in the diatom Thalassiosira pseudonana

Shi

Hopkinson

et al. 2015

Limnology & Oceanography

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Due to the ongoing effects of climate change, phytoplankton are likely to experience enhanced irradiance, more reduced nitrogen, and increased water acidity in the future ocean. Here, we used Thalassiosira pseudonana as a model organism to examine how phytoplankton adjust energy production and expenditure to cope with these multiple, interrelated environmental factors. Following acclimation to a matrix of irradiance, nitrogen source, and CO 2 levels, the diatom's energy production and expenditures were quantified and incorporated into an energetic budget to predict how photosynthesis was affected by growth conditions. Increased light intensity and a shift from NO 2 3 to NH 1 4 led to increased energy generation, through higher rates of light capture at high light and greater investment in photosynthetic proteins when grown on NH 1 4 . Secondary energetic expenditures were adjusted modestly at different culture conditions, except that NO 2 3 utilization was systematically reduced by increasing pCO 2 . The subsequent changes in element stoichiometry, biochemical composition, and release of dissolved organic compounds may have important implications for marine biogeochemical cycles. The predicted effects of changing environmental conditions on photosynthesis, made using an energetic budget, were in good agreement with observations at low light, when energy is clearly limiting, but the energetic budget over-predicts the response to NH 1 4 at high light, which might be due to relief of energetic limitations and/or increased percentage of inactive photosystem II at high light. Taken together, our study demonstrates that energetic budgets offered significant insight into the response of phytoplankton energy metabolism to the changing environment and did a reasonable job predicting them.

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“…Such channeling of resources between functional responses is in tune with the dynamic energy budget theory (DEB) (based on works by Nisbet et al, 2012;Pecquerie et al;Sousa et al, 2010), albeit at the level of a unicellular system.…”

Section: Effects Of Resource Limitations On Functional Responsesmentioning

confidence: 97%

A Gauge model-based analysis of: Reduction(s) in osmolyte infusion interval and its effects on the aggregate measure of systemic failure for a unicellular system

Jeff-Eke

2015

Preprint

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This is a companion to A Gauge model for analysis of Biological systems.Here we reconcile the gauge model with a "real" system, which in this case is a unicellular system. We address effects of infusion of free osmolytes into an intracellular space of interest, and how changes to the frequency of infusion affects the aggregate measure of systemic failure. We also describe limitations to the functionality of the system that may stem from a limited availability of resources. We end by introducing a theoretical problem related to how well the system can tolerate random and extreme changes to the frequency of osmolytes presented via infusion.

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Integrating dynamic energy budget (DEB) theory with traditional bioenergetic models

Cited by 129 publications

References 82 publications

Physiology in the service of fisheries science: Why thinking mechanistically matters

Physiology in the service of fisheries science: Why thinking mechanistically matters

Interactive effects of light, nitrogen source, and carbon dioxide on energy metabolism in the diatom Thalassiosira pseudonana

A Gauge model-based analysis of: Reduction(s) in osmolyte infusion interval and its effects on the aggregate measure of systemic failure for a unicellular system

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