Modelling the influence of light, water and temperature on photosynthesis in young trees of mixed Mediterranean forests

Mayoral, Carolina; Calama, Rafael; Sánchez-González, Mariola; Pardos, Marta

doi:10.1007/s11056-015-9471-y

Cited by 47 publications

(45 citation statements)

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“…However, the LMA in large trees can be extremely high, which may hinder mesophyll conductivity to CO 2 and consequently reduce the A max [34,35]. T leaf has been extensively reported to be parabolically correlated with the A max [20,29,[82][83][84][85], and the optimum temperature (Topt) for the A max was in the range of 15-30 • C for most temperate species [12]. Our results (Figure 1) are also in agreement with the results from the above reports; however, the correlation between T leaf and the A max was weak, and the optimum temperature for A max was approximately 30 • C, which is consistent with the optimum temperature for the A max of Pinus pinea [20].…”

Section: Discussionmentioning

confidence: 99%

“…The A max , AQY and R d are not only important photosynthetic indicators but also core parameters for determining the shape of the PLR curve (Equation (2)). Thus, many studies have linked leaf traits [11,16,32,91] or environmental conditions [20,29] in the PLR models based on their correlations with the A max , AQY and R d to resolve the problem of parameter variation among different species or environments. In this study, we comprehensively considered the influence of spatial position, leaf traits and environmental conditions on leaf photosynthesis and then linked the RDINC, LMA and VPD in the PLR model to extend the PLR model from a single leaf to the whole crown and render the model sufficiently flexible to be applied in different conditions.…”

Section: Discussionmentioning

confidence: 99%

“…Previous studies have suggested that incorrect simulations usually occur when modeling long-term carbon uptake if the spatial and seasonal variations in photosynthesis [46,[92][93][94][95] or leaf traits [96,97] are neglected. Some scientists have successfully incorporated leaf traits [11,16,29,32,91] and environmental conditions [20,29] into the PLR model to extend the model from a single leaf to a larger scale. However, these models are limited in their application because they only describe the response of the A n to PAR in different conditions and do not describe the dynamic simulation of the A n .…”

Section: Discussionmentioning

confidence: 99%

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Dynamic Simulation of the Crown Net Photosynthetic Rate for Young Larix olgensis Henry Trees

Liu

Xie

2019

Forests

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Numerical integration of the instantaneous net photosynthetic rate (An) is a common method for calculating the long-term CO2 uptake of trees, and accurate dynamic simulation of the crown An has been receiving substantial attention. Tree characteristics are challenging to assess given their aerodynamically coarse crown properties, spatiotemporal variation in leaf functional traits and microenvironments. Therefore, the variables associated with the dynamic variations in the crown An must be identified. The relationships of leaf temperature (Tleaf), the vapor pressure deficit (VPD), leaf mass per area (LMA) and the relative depth into the crown (RDINC) with the parameters of the photosynthetic light-response (PLR) model of Larix olgensis Henry were analyzed. The LMA, RDINC and VPD were highly correlated with the maximum net photosynthetic rate (Amax). The VPD was the key variable that mainly determined the variation in the apparent quantum yield (AQY). Tleaf exhibited a significant exponential correlation with the dark respiration rate (Rd). According to the above correlations, the crown PLR model of L. olgensis trees was constructed by linking VPD, LMA and RDINC to the original PLR equation. The model performed well, with a high coefficient of determination (R2) value (0.883) and low root mean square error (RMSE) value (1.440 μmol m−2 s−1). The extinction coefficient (k) of different pseudowhorls within a crown was calculated by the Beer–Lambert equation based on the observed photosynthetically active radiation (PAR) distribution. The results showed that k was not a constant value but varied with the RDINC, solar elevation angle (ψ) and cumulative leaf area of the whole crown (CLA). Thus, we constructed a k model by reparameterizing the power function of RDINC with the ψ and CLA, and the PAR distribution within a crown was therefore well estimated (R2 = 0.698 and RMSE = 174.4 μmol m−2 s−1). Dynamic simulation of the crown An for L. olgensis trees was achieved by combining the crown PLR model and dynamic PAR distribution model. Although the models showed some weakened physiological biochemical processes during photosynthesis, they enabled the estimation of long-term CO2 uptake for an L. olgensis plantation, and the results could be easily fitted to gas-exchange measurements.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Dynamic Simulation of the Crown Net Photosynthetic Rate for Young Larix olgensis Henry Trees

Liu

Xie

2019

Forests

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“…速率, 使RuBP浓度不足而限制光合速率, 即RuBP 再生速率限制阶段 (Farquhar et al, 1980;von Caemmerer & Farquhar, 1981;Harley & Sharkey, 1991;von Caemmerer, 2000) (Miao et al, 2009)可以由以下公式计算得到, 即: Miao et al, 2009;Yin et al, 2009; 唐星林等, 2017a)。模型II较全面地考虑了光合作用的原初反应过程 (Ye et al, 2013a(Ye et al, , 2013b, 可定量研究与植物光合作用原初反应过程中的激子传递效率和捕光色素分子的参数变化情况以及这些参数对光的响应问题, 并且用其中的参数可以讨论植物的PSII动力学下调 (Ralph & Gademann, 2005;Kirchhoff et al, 2007;Brading et al, 2011) (Ježilová et al, 2015;Mayoral et al, 2015;Park et al, 2016;Bellucco et al, 2017;Quiroz et al,…”

Section: 表3 分配到碳同化和光呼吸途径的光合电子流unclassified

“…Chinese Journal of Plant Ecology, 42, 498-507. DOI: 10.17521/cjpe.2017.0320 植物的光合作用受光强、CO 2 浓度和温度等环境因子的影响。Farquhar等(1980)以及其他学者 (von Caemmerer & Farquhar, 1981;Harley & Sharkey, 1991;von Caemmerer, 2000von Caemmerer, , 2013根据核酮糖-1,5-二磷酸羧化酶/加氧酶(Rubisco)酶动力学反应和核酮糖-1,5-二磷酸(RuBP)再生反应化学计量学, 提出 C 3 植物光合生化模型(简称FvCB模型)。现在, FvCB 模型因能描述稳态的碳同化过程且具有明确的生物学意义而被广泛应用于光合作用研究 (Dubois et al, 2007;Farquhar & Busch, 2017)。生化模型由描述Rubisco酶活性限制、RuBP再生限制和磷酸丙糖利用率(TPU)限制等3个过程的子模型构成。其中非直角双曲线模型(简称模型I)是生化模型的主要子模型 (Long & Bernacchi, 2003;Dubois et al, 2007;Farquhar & Busch, 2017; 梁星云和刘世荣, 2017; 唐星林等, 2017a, 2017b)。在植物光合作用对光响应曲线(A n -I曲线, I为光合有效辐射) 的拟合中, 模型I得到广泛的应用和验证, 但由此模型拟合光响应曲线得到的最大净光合速率(A nmax )显著高于实测值 (Calama et al, 2013;王荣荣等, 2013;冷寒冰等, 2014;Ježilová et al, 2015;Mayoral et al, 2015;Park et al, 2016;Bellucco et al, 2017;Quiroz et al, 2017), 这将高估植物的光合能力; 并且该模型不能拟合植物发生光抑制时的光响应曲线 (Ye, 2007;dos Santos et al, 2013;王海珍等, 2017) (Cheng et al, 2001;Long & Bernacchi, 2003 (Serôdio et al, 2013;Li et al, 2015Li et al, , 2018Sun et al, 2015;Gao et al, 2017aGao et al, , 2017bShimada et al, 2017)…”

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Determination of maximum electron transport rate and its impact on allocation of electron flow

Ye¹,

Shi-Hua²,

An³

et al. 2018

Chinese Journal of Plant Ecology

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Aims The non-rectangular hyperbolic model (termed as model I) is the main submodel of the FvCB biochemical model, which is used to estimate the maximum electron transport rate (J max) of plant leaves. The submodel is widely applied to fit the light-response curves of electron transport rate (J-I curves), and obtain J max. However, it has not been strictly verified whether J max calculated by model I is consistent with the measured values. Methods Light-response curves of electron transport rate and of photosynthesis rate of soybean (Glycine max) (under shading and full sunlight) were simultaneously measured by LI-6400-40, then these data were simulated by model I and the mechanistic model of light-response of electron transport rate (termed as model II). Important findings The results showed that there was the significant differences between J max estimated by model I and the observation data irrespective of shading and full sunny leaves of soybean. However, there was no significant difference between J max calculated by model II and the measured value. Because J max was overestimated by model I, it must lead to overestimate the amount of photosynthetic electron flow to allocate to photorespiration pathway, and magnify the photoprotection of photorespiration on plants. On the contrary, the J max and saturation light intensity (PAR sat) obtained by the model II were in very close agreement with the observations. It can be concluded that the model II was superior to the model I in estimates of J max and PAR sat. Therefore, we recommend model II to be used as an operational model for fitting J-I curves and accurately assess the role of photorespiration on plant photo-protection.

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Dynamics of frost tolerance during regeneration in a mixed (pine–oak–juniper) Mediterranean forest

Mayoral

Strimbeck

Sánchez-González

et al. 2015

Trees

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Modelling the influence of light, water and temperature on photosynthesis in young trees of mixed Mediterranean forests

Cited by 47 publications

References 46 publications

Dynamic Simulation of the Crown Net Photosynthetic Rate for Young Larix olgensis Henry Trees

Dynamic Simulation of the Crown Net Photosynthetic Rate for Young Larix olgensis Henry Trees

Determination of maximum electron transport rate and its impact on allocation of electron flow

Dynamics of frost tolerance during regeneration in a mixed (pine–oak–juniper) Mediterranean forest

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