Integrating metabolic scaling variation into the maximum entropy theory of ecology explains Taylor's law for individual metabolic rate in tropical forests

Meng, Xu; Jiang, Mengke; Wang, Huafeng

doi:10.1016/j.ecolmodel.2021.109655

Cited by 4 publications

(4 citation statements)

References 81 publications

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“…B 289: 20221605 rates of metabolizing drugs based on age and drug type [13,153,154]. The predictions of many theoretical models in ecology, forestry and conservation biology may also be improved by recognizing the diversity of metabolic scaling [13,23,25,102,127,155].…”

Section: Conclusion and Prospectsmentioning

confidence: 99%

“…In addition, the demise of the 3/4-power law is revolutionizing medical protocols for administering drug dosages to humans, who exhibit significantly different b values for rates of metabolizing drugs based on age and drug type [13,153,154]. The predictions of many theoretical models in ecology, forestry and conservation biology may also be improved by recognizing the diversity of metabolic scaling [13,23,25,102,127,155].…”

Section: Conclusion and Prospectsmentioning

confidence: 99%

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Variable metabolic scaling breaks the law: from ‘Newtonian’ to ‘Darwinian’ approaches

Glazier

2022

Proc. R. Soc. B.

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Life's size and tempo are intimately linked. The rate of metabolism varies with body mass in remarkably regular ways that can often be described by a simple power function, where the scaling exponent ( b , slope in a log-linear plot) is typically less than 1. Traditional theory based on physical constraints has assumed that b is 2/3 or 3/4, following natural law, but hundreds of studies have documented extensive, systematic variation in b . This overwhelming, law-breaking, empirical evidence is causing a paradigm shift in metabolic scaling theory and methodology from ‘Newtonian’ to ‘Darwinian’ approaches. A new wave of studies focuses on the adaptable regulation and evolution of metabolic scaling, as influenced by diverse intrinsic and extrinsic factors, according to multiple context-dependent mechanisms, and within boundary limits set by physical constraints.

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Section: Conclusion and Prospectsmentioning

confidence: 99%

Section: Conclusion and Prospectsmentioning

confidence: 99%

Variable metabolic scaling breaks the law: from ‘Newtonian’ to ‘Darwinian’ approaches

Glazier

2022

Proc. R. Soc. B.

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“…Across crops as diverse as maize, wheat, tomato and soybean, crop yield variance increased with mean crop yield according to Taylor's power law, and this relationship persisted across scales (across species, environments and globally; Döring et al, 2015). Additionally, the variance–mean relationship of metabolic rates across tropical tree communities followed Taylor's power law (Xu et al, 2021), as did measures of leaf asymmetry (Wang et al, 2018). In another example, trait means and variances were well described by Taylor's power law for wood density, plant height, fruit size, leaf thickness, foliar C/P ratio and foliar C/N ratio, but not for seed size, specific leaf area or leaf tannin and phenol content (Ulrich et al, 2021).…”

Section: Power Laws For Quantifying Variance Scalingmentioning

confidence: 99%

Power laws and plant trait variation in spatio‐temporally heterogeneous environments

Hulshof

Umaña

2022

Global Ecol Biogeogr

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A challenge: Variation is ubiquitous in nature across all spatial and temporal scales and underlies prominent ecological and evolutionary theories. Although understanding the causes and consequences of trait variation is a central goal of trait-based ecology, the scaling of trait variance across space and time (variance scaling) is unresolved. A solution:We argue that characterizing trait variance across spatio-temporal scales using a combination of prominent power laws can elucidate the role of environmental variability in trait variation and potential mechanisms driving trait patterns. In particular, the species-time-area relationship and Taylor's power law help to establish a generalizable framework for developing and testing variance scaling theory. Finally, we outline priority research questions and tractable systems for answering them.Successional forests, long-term forest monitoring networks and censuses of shortlived taxa are ideal for coupling high-resolution environmental data with measurements of trait variance across scales to test the models proposed here. Main conclusions:Characterizing the behaviour of variance across spatio-temporal scales is feasible and a prerequisite for developing a predictive theory of trait-based ecology.

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“…Instead of assuming a constant metabolic scaling exponent, as in the testing of the original METE, we estimate the exponent from the PP-METE and FP-METE models by fitting the corresponding model predictions to the observed ISD. Xu (2020) showed that the PP-METE models described the ISD of trees within communities in two separate forests reasonably accurately; and Xu et al (2021) used the PP-METE models to successfully predict the form and parameters of the scaling relationship between the mean and the variance of the individual metabolic rate across tree communities in a tropical forest.…”

Section: Introductionmentioning

confidence: 99%

Earthquake disturbance shifts metabolic energy use and partitioning in a monodominant forest

Meng

Allen

Newman

2023

Global Ecol Biogeogr

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AimBoth macroecology and disturbance ecology have long been used to characterize population‐ and community‐level patterns across scales, but the integration of both approaches in characterizing disturbed ecosystems is rare. Here, we use the maximum entropy theory of ecology (METE) to model the individual size distribution (ISD) of trees in pre‐ and post‐disturbance tree populations and estimate the corresponding metabolic scaling exponents.LocationNew Zealand.Time Period1987–1999.Major Taxa StudiedMountain beech (Fuscospora cliffortioides Nothofagaceae).MethodsMETE uses information entropy and empirical macro‐state variables to constrain predictions of ecological distributions related to biodiversity. METE has successfully predicted a range of biodiversity metrics in static or relatively undisturbed conditions. However, METE can fail to accurately model ecological patterns in disturbed ecosystems. We extend existing theoretical predictions to a highly disturbed ecosystem by treating the metabolic scaling exponent and Lagrange multipliers as free parameters in METE.ResultsWe showed that the fully parameterized METE (FP‐METE) model reasonably predicted the ISD of mountain beech populations in a monodominant forest after a strong earthquake, which restructured the forest. Furthermore, the FP‐METE model revealed that decreasing metabolic scaling exponent drove the substantial decline of total metabolic rate energy and the redistribution of energy towards smaller trees after the earthquake. Increased number of small trees was not sufficient to capture the full impact of disturbance on forest energy use.Main ConclusionsOur FP‐METE model applies an informatics approach to estimate the metabolic scaling relationship. We find that instead of maintaining a fixed value, the metabolic scaling exponent is variable among populations, and declines significantly after an earthquake disturbance. This leads to major shifts in the total population metabolic energy and energy distribution. With this approach, we now have the opportunity to advance beyond categorizing forms of mathematical distributions that describe biodiversity patterns and move into a predictive framework where the true constraints on ecosystems and their dynamics emerge.

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Integrating metabolic scaling variation into the maximum entropy theory of ecology explains Taylor's law for individual metabolic rate in tropical forests

Cited by 4 publications

References 81 publications

Variable metabolic scaling breaks the law: from ‘Newtonian’ to ‘Darwinian’ approaches

Variable metabolic scaling breaks the law: from ‘Newtonian’ to ‘Darwinian’ approaches

Power laws and plant trait variation in spatio‐temporally heterogeneous environments

Earthquake disturbance shifts metabolic energy use and partitioning in a monodominant forest

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