No need to switch the modified Arrhenius function back to the old form

Yin, Xinyou

doi:10.1111/nph.17341

Cited by 6 publications

(5 citation statements)

References 14 publications

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“…By using our dendrogram as a guide, researchers no longer need to compare the equations of different models manually, which can often be quite challenging in our experience. For example, our dendrogram shows that the Johnson-Lewin model 30 and a common modification thereof (the simplified Johnson-Lewin model; see Supplementary section S5) yield effectively identical fits, consistent with the conclusions of Yin and co-workers 69 . It is also worth pointing out that the fits of the mechanistic Johnson-Lewin model (and its variants) are typically highly similar to the fits of the phenomenological asymmetric Janisch model (Janisch II; Fig.…”

Section: Recommendations and Conclusionsupporting

confidence: 83%

No model to rule them all: a systematic comparison of 83 thermal performance curve models across traits and taxonomic groups

Kontopoulos,

Sentis,

Daufresne

et al. 2023

Preprint

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In ectotherms, the performance of physiological, ecological, and life-history traits universally increases with temperature to a maximum before decreasing again. Identifying the most appropriate thermal performance model for a specific trait type has broad applications, from metabolic modelling at the cellular level to forecasting the effects of climate change on population, ecosystem, and disease transmission dynamics. To date, numerous mathematical models have been designed, but a thorough comparison among them is lacking. In particular, we do not know if certain models consistently outperform others, and how factors such as sampling resolution and trait or organismal identity influence model performance. These have led researchers to select models semi-arbitrarily, potentially introducing biases that compromise environmental suitability predictions. To fill these gaps, we collect 2,739 thermal performance datasets from diverse traits and taxa, to which we fit 83 models used in previous studies. We detect remarkable variation in model performance which is not primarily driven by sampling resolution, trait type, or taxonomic information. Our results highlight a lack of well-defined scenarios in which certain models are more appropriate than others. Therefore, to avoid likely model-specific biases, future studies should perform model selection to identify the most appropriate model(s) for their data.

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Section: Recommendations and Conclusionsupporting

confidence: 83%

No model to rule them all: a systematic comparison of 83 thermal performance curve models across traits and taxonomic groups

Kontopoulos,

Sentis,

Daufresne

et al. 2023

Preprint

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“…Even with five different temperature measurements, H d is often fixed to avoid overfitting. An in-depth analysis by Medlyn et al (2002) has shown that keeping H d constant does not meaningfully affect the mathematical description of the function, recently supported by Yin (2021). Because the parameters from the peaked Arrhenius curve strongly co-vary, they cannot be evaluated independently, regardless of whether H d is fixed or not.…”

Section: Acclimation Of Photosynthesis To Warmingmentioning

confidence: 99%

Temperature responses of photosynthesis and respiration in evergreen trees from boreal to tropical latitudes

2022

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Evergreen species are widespread across the globe, representing two major plant functional forms in terrestrial models. We reviewed and analysed the responses of photosynthesis and respiration to warming in 101 evergreen species from boreal to tropical biomes. Summertime temperatures affected both latitudinal gas exchange rates and the degree of responsiveness to experimental warming. The decrease in net photosynthesis at 25°C (A net25 ) was larger with warming in tropical climates than cooler ones. Respiration at 25°C (R 25 ) was reduced by 14% in response to warming across species and biomes. Gymnosperms were more sensitive to greater amounts of warming than broadleaved evergreens, with A net25 and R 25 reduced c. 30-40% with > 10°C warming. While standardised rates of carboxylation (V cmax25 ) and electron transport (J max25 ) adjusted to warming, the magnitude of this adjustment was not related to warming amount (range 0.6-16°C). The temperature optimum of photosynthesis (T optA ) increased on average 0.34°C per °C warming. The combination of more constrained acclimation of photosynthesis and increasing respiration rates with warming could possibly result in a reduced carbon sink in future warmer climates. The predictable patterns of thermal acclimation across biomes provide a strong basis to improve modelling predictions of the future terrestrial carbon sink with warming.

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“…The temperature responses of A sat , g m , J max and V cmax , wherever possible, were described by a modified Arrhenius equation (Medlyn et al, 2002):

X goodbreak= X_{25} \exp (][, \frac{E_{X}}{R} ()(, \frac{1}{298} goodbreak- \frac{1}{T_{leaf}})) \frac{1 + \exp (][, \frac{D_{X}}{R} ()(, \frac{S_{X}}{D_{X}} goodbreak- \frac{1}{298}))}{1 + \exp (][, \frac{D_{X}}{R} ()(, \frac{S_{X}}{D_{X}} goodbreak- \frac{1}{T_{leaf}}))}

where R is the universal gas constant (0.008314 kJ K −1 mol −1 ), X 25 is the value of parameters estimated at T leaf = 25°C, E X , D X and S X are the activation energy, deactivation energy and the entropy factor of relevant parameters respectively. To estimate T opt and the value of relevant parameter at T opt ( X opt ), the same data were fitted to the modified Arrhenius equation written in the form containing T opt (Medlyn et al, 2002; Yin, 2021):

X goodbreak= X_{opt} \frac{D_{X} \exp (][, \frac{E_{X}}{R} ()(, \frac{1}{T_{opt}} goodbreak- \frac{1}{T_{leaf}}))}{D_{X} - E_{X} (}{, 1 goodbreak- \exp (][, \frac{D_{X}}{R} ()(, \frac{1}{T_{opt}} goodbreak- \frac{1}{T_{leaf}})))}

Note that (i) E X and D X are common to Equations (1) and (2), and the estimates of E X or D X from the two equations are identical (Yin, 2021), and (ii) T leaf in both equations should be in K.…”

Section: Methodsmentioning

confidence: 99%

“…where R is the universal gas constant (0.008314 kJ K −1 mol −1 ), X 25 is the value of parameters estimated at T leaf = 25°C, E X , D X and S X are the activation energy, deactivation energy and the entropy factor of relevant parameters respectively. To estimate T opt and the value of relevant parameter at T opt (X opt ), the same data were fitted to the modified Arrhenius equation written in the form containing T opt (Medlyn et al, 2002;Yin, 2021):…”

Section: Temperature Responses Of Photosynthetic Parametersmentioning

confidence: 99%

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Neglecting acclimation of photosynthesis under drought can cause significant errors in predicting leaf photosynthesis in wheat

Fang

Martre

Jin

et al. 2022

Global Change Biology

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Extreme climatic events, such as heat waves, cold snaps and drought spells, related to global climate change, have become more frequent and intense in recent years. Acclimation of plant physiological processes to changes in environmental conditions is a key component of plant adaptation to climate change. We assessed the temperature response of leaf photosynthetic parameters in wheat grown under contrasting water regimes and growth temperatures (Tgrowth). Two independent experiments were conducted under controlled conditions. In Experiment 1, two wheat genotypes were subjected to well‐watered or drought‐stressed treatments; in Experiment 2, the two water regimes combined with high, medium and low Tgrowth were imposed on one genotype. Parameters of a biochemical C3‐photosynthesis model were estimated at six leaf temperatures for each factor combination. Photosynthesis acclimated more to drought than to Tgrowth. Drought affected photosynthesis by lowering its optimum temperature (Topt) and the values at Topt of light‐saturated net photosynthesis, stomatal conductance, mesophyll conductance, the maximum rate of electron transport (Jmax) and the maximum rate of carboxylation by Rubisco (Vcmax). Topt for Vcmax was up to 40°C under well‐watered conditions but 24–34°C under drought. The decrease in photosynthesis under drought varied among Tgrowth but was similar between genotypes. The temperature response of photosynthetic quantum yield under drought was partly attributed to photorespiration but more to alternative electron transport. All these changes in biochemical parameters could not be fully explained by the changed leaf nitrogen content. Further model analysis showed that both diffusional and biochemical parameters of photosynthesis and their thermal sensitivity acclimate little to Tgrowth, but acclimate considerably to drought and the combination of drought and Tgrowth. The commonly used modelling approaches, which typically consider the response of diffusional parameters, but ignore acclimation responses of biochemical parameters to drought and Tgrowth, strongly overestimate leaf photosynthesis under variable temperature and drought.

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No need to switch the modified Arrhenius function back to the old form

Abstract: A comment on Murphy & Stinziano (2020) 'A derivation error that affects carbon balance models exists in the current implementation of the modified Arrhenius function'

Cited by 6 publications

References 14 publications

No model to rule them all: a systematic comparison of 83 thermal performance curve models across traits and taxonomic groups

No model to rule them all: a systematic comparison of 83 thermal performance curve models across traits and taxonomic groups

Temperature responses of photosynthesis and respiration in evergreen trees from boreal to tropical latitudes

Neglecting acclimation of photosynthesis under drought can cause significant errors in predicting leaf photosynthesis in wheat

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