Dynamic energy budget theory explained

The dynamic energy budget (DEB) theory is a formal metabolic theory which provides a single quantitative framework to dynamically describe the aspects of metabolism (energy and mass budgets) of all living organisms at the individual level, based on assumptions about energy uptake, storage, and utilization of various substances.[1] [2] [3] [4] [5] [6] [7] [8] [9] The DEB theory adheres to stringent thermodynamic principles, is motivated by universally observed patterns, is non-species specific, and links different levels of biological organization (cells, organisms, and populations) as prescribed by the implications of energetics.[10] [11] Models based on the DEB theory have been successfully applied to over 1000 species with real-life applications ranging from conservation, aquaculture, general ecology, and ecotoxicology[12] [13] (see also the Add-my-pet collection). The theory is contributing to the theoretical underpinning of the emerging field of metabolic ecology.

The explicitness of the assumptions and the resulting predictions enable testing against a wide variety of experimental results at the various levels of biological organization.[14] [15] The theory explains many general observations, such as the body size scaling relationships of certain physiological traits, and provides a theoretical underpinning to the widely used method of indirect calorimetry.[16] Several popular empirical models are special cases of the DEB model, or very close numerical approximations.[17]

Theoretical background

The theory presents simple mechanistic rules that describe the uptake and allocation of energy (and nutrients) and the consequences for physiological organization throughout an organism's life cycle, including the relationships of energetics with aging and effects of toxicants. Assumptions of the DEB theory are delineated in an explicit way, the approach clearly distinguishes mechanisms associated with intra‐ and interspecific variation in metabolic rates, and equations for energy flows are mathematically derived following the principles of physics and simplicity.[18] [19]

Cornerstones of the theory are:

The theory specifies that an organism is made up two main compartments: (energy) reserve and structure. Assimilation of energy is proportional to surface area of the structure, and maintenance is proportional to its volume. Reserve does not require maintenance. Energy mobilization will depend on the relative amount of the energy reserve, and on the interface between reserve and structure. Once mobilized, the energy is split into two branches:

The κ-rule therefore states that the processes of growth and maturation do not directly compete. Maintenance needs to be paid before allocating energy to other processes.

In the context of energy acquisition and allocation, the theory recognizes three main developmental stages: embryo, which does not feed or reproduce, juvenile, which feeds but does not reproduce, and adult, which both feeds and is allocating energy to reproduction. Transitions between these life stages occur at events specified as birth and puberty, which are reached when energy invested into maturation (tracked as 'level of maturity') reaches a certain threshold. Maturity does not increase in the adult stage, and maturity maintenance is proportional to maturity.

Biochemical composition of reserve and structure is considered to be that of generalised compounds, and is constant (the assumption of strong homeostasis) but not necessarily identical. Biochemical transformation from food to reserve (assimilation), and from reserve to structure (growth) include overhead costs. These overheads, together with processes of somatic and maturity maintenance and reproduction overheads (inefficiencies in transformation from reserve to reproductive material), all contribute to the consumption of oxygen and production of carbon dioxide, i.e. metabolism.

DEB models

All dynamic energy budget models follow the energy budget of an individual organism throughout its life cycle; by contrast,"static" energy budget models describe a specific life stage or size of an organism.[20] The main advantage of the DEB-theory based model over most other models is its description of energy assimilation and utilization (reserve dynamics) simultaneously with decoupled processes of growth, development/ maturation, and maintenance.[21] Under constant environmental conditions (constant food and temperature) the standard DEB model can be simplified to the von Bertalanffy (or better, Putter's [22]) growth model, but its mechanistic process-based setup enables incorporating fluctuating environmental conditions, as well as studying reproduction and maturation in parallel to growth.

DEB theory specifies reserves as separate from structure: these are the two state variables that contribute to physical volume, and (in combination with reproduction buffer of adults) fully define the size of an individual. Maturity (also a state variable of the model) tracks how much energy has been invested into maturation, and therefore determines the life stage of the organism relative to maturity levels at which life stage transitions (birth and puberty) occur. Dynamics of the state variables are given by ordinary differential equations which include the major processes of energy uptake and use: assimilation, mobilization, maintenance, growth, maturation, and reproduction.

Parameters of the model are individual specific, but similarities between individuals of the same species yield species-specific parameter estimations.[23] DEB parameters are estimated from several types of data simultaneously.[24] [25] Routines for data entry and parameter estimation are available as free software package DEBtool implemented in the MATLAB environment, with the process of model construction explained in a Wiki-style manual . Estimated parameters are collected in the online library called the Add-my-pet project.

The standard DEB model

The standard model quantifies the metabolism of an isomorph (organism that does not change in shape during ontogeny) that feeds on one type of food with a constant composition (therefore the weak homeostasis applies, i.e. the chemical composition of the body is constant). The state variables of the individual are 1 reserve, 1 structure, maturity, and (in the adult stage) the reproduction buffer. Parameter values are constant throughout life. The reserve density at birth equals that of the mother at egg formation. Foetuses develop similarly, but receive unrestricted amount of reserve from the mother during development.

Extensions of the standard model

DEB theory has been extended into many directions, such as

A list and description of most common typified models can be found here .

Criticism

The main criticism is directed to the formal presentation of the theory (heavy mathematical jargon), number of listed parameters, the symbol heavy notation, and the fact that modeled (state) variables and parameters are abstract quantities which cannot be directly measured, all making it less likely to reach its intended audience (ecologists) and be an "efficient" theory.[29]

However, more recent publications aim to present the DEB theory in an "easier to digest" content to "bridge the ecology-mathematics gap". List of parameters is a direct result of list of processes which are of interest—if only growth under constant food and temperature is of interest, the standard DEB model can be simplified to the von Bertalanffy growth curve. Adding more processes into focus (such as reproduction and/or maturation), and forcing the model with fluctuating (dynamic) environmental conditions, needless to say, will result in more parameters.

The general methodology of estimation of DEB parameters from data is described in van der Meer 2006; Kooijman et al 2008 shows which particular compound parameters can be estimated from a few simple observations at a single food density and how an increasing number of parameters can be estimated if more quantities are observed at several food densities. A natural sequence exists in which parameters can be known in principle. In addition, routines for data entry and scripts for parameter estimation are available as a free and documented software package DEBtool, aiming to provide a ready-to-use tool for users with less mathematical and programing background. Number of parameters, also pointed as relatively sparse for a bioenergetic model, vary depending on the main application and, because the whole life cycle of an organism is defined, the overall number of parameters per data-set ratio is relatively low.[30] Linking the DEB (abstract) and measured properties is done by simple mathematical operations which include auxiliary parameters (also defined by the DEB theory and included in the DEBtool routines), and include also switching between energy-time and mass-time contexts. Add my pet (AmP) project explores parameter pattern values across taxa. The DEB notation is a result of combining the symbols from the main fields of science (biology, chemistry, physics, mathematics) used in the theory, while trying to keep the symbols consistent. As the symbols themselves contain a fair bit of information (see DEB notation document), they are kept in most of the DEB literature.

Compatibility (and applicability) of DEB theory/models with other approaches

Dynamic energy budget theory presents a quantitative framework of metabolic organization common to all life forms, which could help to understand evolution of metabolic organization since the origin of life. As such, it has a common aim with the other widely used metabolic theory: the West-Brown-Enquist (WBE) metabolic theory of ecology, which prompted side-by-side analysis of the two approaches.[31] Though the two theories can be regarded as complementary to an extent,[32] they were built on different assumptions and have different scope of applicability. In addition to a more general applicability, the DEB theory does not suffer from consistency issues pointed out for the WBE theory.

Applications

Many more examples of applications have been published in scientific literature.

See also

Further reading

External links

Notes and References

  1. Sousa. Tânia. Domingos. Tiago. Kooijman. S. A. L. M.. 2008. From empirical patterns to theory: a formal metabolic theory of life. Philosophical Transactions of the Royal Society of London B: Biological Sciences. en. 363. 1502. 2453–2464. 10.1098/rstb.2007.2230. 0962-8436. 18331988. 2606805.
  2. Jusup. Marko. Sousa. Tânia. Domingos. Tiago. Labinac. Velimir. Marn. Nina. Wang. Zhen. Klanjšček. Tin. Physics of metabolic organization. Physics of Life Reviews. 20. 1–39. 10.1016/j.plrev.2016.09.001. 27720138. 2017. 2017PhLRv..20....1J. free.
  3. van der Meer. Jaap. 2006. Metabolic theories in ecology. Trends in Ecology & Evolution. en. 21. 3. 136–140. 10.1016/j.tree.2005.11.004. 16701489. 0169-5347.
  4. Kooijman. S. A. L. M.. 2001. Quantitative aspects of metabolic organization: a discussion of concepts. Philosophical Transactions of the Royal Society of London B: Biological Sciences. en. 356. 1407. 331–349. 10.1098/rstb.2000.0771. 0962-8436. 11316483. 1088431.
  5. Kooijman. S. A. L. M.. Troost. T. A.. 2007-02-01. Quantitative steps in the evolution of metabolic organisation as specified by the Dynamic Energy Budget theory. Biological Reviews. en. 82. 1. 113–142. 10.1111/j.1469-185x.2006.00006.x. 17313526. 801451. 1469-185X. free.
  6. Book: M., Kooijman, S. A. L.. Dynamic energy budgets in biological systems : theory and applications in ecotoxicology. 1993. Cambridge University Press. 978-0521452236. Cambridge. 29596070.
  7. Book: M., Kooijman, S. A. L.. Dynamic energy and mass budgets in biological systems. 2000. Cambridge University Press. Kooijman, S. A. L. M.. 978-0521786089. 2nd. Cambridge, UK. 42912283.
  8. Book: Kooijman, S. A. L. M.. Dynamic Energy Budget Theory for Metabolic Organisation. 2010. Cambridge University Press. 9780521131919. en.
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  10. Nisbet. R. M.. Muller. E. B.. Lika. K.. Kooijman. S. A. L. M.. From molecules to ecosystems through dynamic energy budget models. Journal of Animal Ecology. 69. 6. 913–926. 10.1111/j.1365-2656.2000.00448.x. 2008. free.
  11. Maino. James L.. Kearney. Michael R.. Nisbet. Roger M.. Kooijman. Sebastiaan A. L. M.. 2014-01-01. Reconciling theories for metabolic scaling. Journal of Animal Ecology. en. 83. 1. 20–29. 10.1111/1365-2656.12085. 23668377. 1365-2656. free.
  12. Web site: Zotero DEB library of scientific literature.
  13. van der Meer. Jaap. Klok. Chris. Kearney. Michael R.. Wijsman. Jeroen W.M.. Kooijman. Sebastiaan A.L.M.. 35years of DEB research. Journal of Sea Research. 94. 1–4. 10.1016/j.seares.2014.09.004. 2014. 2014JSR....94....1V.
  14. van der Meer. Jaap. 2006. An introduction to Dynamic Energy Budget (DEB) models with special emphasis on parameter estimation. Journal of Sea Research. en. 56. 2. 85–102. 10.1016/j.seares.2006.03.001. 2006JSR....56...85V. 7361555 . 1385-1101.
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  16. Book: Kooijman, S.A.L.M.. https://books.google.com/books?id=aIgvDwAAQBAJ&q=The+von+Bertalanffy+growth+rate+as+a+function+of+physiological+parameters:+a+comparative+analysis. Mathematical Ecology - Proceedings Of The Autumn Course Research Seminars International Ctr For Theoretical Physics.
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  21. Mueller. Casey A.. Augustine. Starrlight. Kooijman. Sebastiaan A.L.M.. Kearney. Michael R.. Seymour. Roger S.. The trade-off between maturation and growth during accelerated development in frogs. Comparative Biochemistry and Physiology Part A: Molecular & Integrative Physiology. 163. 1. 95–102. 10.1016/j.cbpa.2012.05.190. 22613786. 2012.
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  23. The AmP project: Comparing Species on the Basis of Dynamic Energy Budget Parameters. Marques, G. M., Lika, K., Augustine, S., Pecquerie, L., Domingos, T. and Kooijman, S. A. L. M. PLOS Computational Biology. 2018. 14. 5. e1006100. 10.1371/journal.pcbi.1006100. 29742099. 5962104. 2018PLSCB..14E6100M. 2018-04-05 . free .
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