Modeling net CO 2 assimilation ( A N ) within the crown of young planted Larix olgensis trees

Xie

2019

Forests

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.

Section: Model Descriptionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Xie

2019

Forests

“…The spatial distribution of foliage influences the sapwood cross-sectional area (or area increment) [5][6][7][8][9], light transmittance [2,10,11], microenvironment [1,12,13], radial pattern of sap flux density [3] and photosynthetic productivity [14][15][16]. The vertical foliage distribution generally plays an important role in determining an effective crown [17], consisting of branches that can produce excess photosynthate to contribute to the growth of the main tree stem [18], which provides a reference for an artificial pruning height in young forests [19].…”

Section: Introductionmentioning

confidence: 99%

The Spatial Distribution of the Needle Area of Planted Larix olgensis Trees

Xie

2019

Forests

The spatial distribution of leaf area largely governs both the structure and function of a tree crown. Three sample trees were selected from a 16-year-old Larix olgensis plantation in the Maoershan Forest Farm, Heilongjiang Province, based on the average diameter at breast height in each plot. All needles from the branches in the nodal and internodal pseudowhorls within the crown were destructively sampled. The crown was divided into several segments in the vertical and horizontal directions, resulting in different sub-regions. The needle area (NA) in each sub-region was computed based on the needle mass per area (NMA). The vertical and horizontal distributions and their cumulative NA distributions were characterized using the Weibull distribution function and its cumulative form. A two-dimensional NA model was created by combining the two Weibull distribution functions of the vertical and horizontal distributions. The variation in the spatial distribution of the NA among the different crown directions is discussed, and the influence of competition from competitors on the spatial distribution of NA was analyzed. The results showed that the Weibull distribution function and its cumulative form performed well in describing the vertical and horizontal distributions and the cumulative distributions of the NA, which was generally concentrated upward within the crown. This phenomenon was most apparent in dense stands with strong competition. The center of the NA exhibited an inward shift in the horizontal direction within the crown but shifted outwards with an increase in competition. The cumulative vertical and horizontal distributions of the NA obviously varied with different crown directions, which was associated mainly with the light conditions. The two-dimensional NA patterns showed that the center of the NA generally shifted outward with an increase in the relative depth into the crown (RDINC), and that more concentrated and more skewed patterns usually occurred under increased competition. Different crown directions exhibited different two-dimensional NA patterns, but the core driver was the variable light condition caused by the competitors, particularly in closed stands.

“…per area (LMA), nitrogen (N) content [8][9][10] , leaf temperature (T leaf ) and global site factor (GSF) [11][12][13] . Our previous study successfully established a dynamic crown PLR model for Larix olgensis trees by linking the LMA, T leaf , vapour pressure deficit (VPD) and relative depth into the crown (RDINC) in the original PLR equation 13 . These results laid the foundation for estimating the net primary production (NPP) and further exploring its allocation mechanisms in individual L. olgensis trees.…”

mentioning

confidence: 99%

“…The PLR curves for trees generally exhibit spatial variations, even within an individual crown [14][15][16] . Thus, it is inappropriate to measure only one position to represent the photosynthetic characteristics of the whole crown 13 . Our previous study 13,17,18 suggested that the PLR curves significantly differed in the vertical direction in the crown of a L. olgensis tree.…”

mentioning

confidence: 99%

Determination of the most effective design for the measurement of photosynthetic light-response curves for planted Larix olgensis trees

Jia

2020

Sci Rep

A photosynthetic light-response (PLR) curve is a mathematical description of a single biochemical process and has been widely applied in many eco-physiological models. To date, many PLR measurement designs have been suggested, although their differences have rarely been explored, and the most effective design has not been determined. In this study, we measured three types of PLR curves (High, Middle and Low) from planted Larix olgensis trees by setting 31 photosynthetically active radiation (PAR) gradients. More than 530 million designs with different combinations of PAR gradients from 5 to 30 measured points were conducted to fit each of the three types of PLR curves. The influence of different PLR measurement designs on the goodness of fit of the PLR curves and the accuracy of the estimated photosynthetic indicators were analysed, and the optimal design was determined. The results showed that the measurement designs with fewer PAR gradients generally resulted in worse predicted accuracy for the photosynthetic indicators. However, the accuracy increased and remained stable when more than ten measurement points were used for the PAR gradients. The mean percent error (M%E) of the estimated maximum net photosynthetic rate (P max) and dark respiratory rate (R d) for the designs with less than ten measurement points were, on average, 16.4 times and 20.1 times greater than those for the designs with more than ten measurement points. For a single tree, a unique PLR curve design generally reduced the accuracy of the predicted photosynthetic indicators. Thus, three optimal measurement designs were provided for the three PLR curve types, in which the root mean square error (RMSE) values reduced by an average of 8.3% and the coefficient of determination (R 2) values increased by 0.3%. The optimal design for the High PLR curve type should shift more towards high-intensity PAR values, which is in contrast to the optimal design for the Low PLR curve type, which should shift more towards low-intensity PAR values. The photosynthetic light-response (PLR) curve reflects the instantaneous response of the net photosynthetic rate (P n) to different gradients of photosynthetically active radiation (PAR). It can provide measures of many photosynthetic indicators, such as the maximum P n (P max), dark respiration rate (R d), apparent quantum yield (AQY), light compensation point (LCP) and light saturated point (LSP), for analysing plant photosynthetic activity 1. In addition, it is also a basic element for modelling the photosynthesis 2-4 and primary productivity 5-7 of vegetation and forests. In recent studies, the application of the PLR model has been expanded from a single leaf to larger scales by linking some leaf functional traits and environmental conditions, such as the leaf mass