scholarly journals Modeling Canopy Carbon and Water Fluxes Using a Multilayered Model over a Temperate Meadow in Inner Mongolia

2019 ◽  
Vol 14 (1) ◽  
pp. 141-154
Author(s):  
Nina Chen ◽  
Anzhi Wang ◽  
Juan An ◽  
Yushu Zhang ◽  
Ruipeng Ji ◽  
...  
Keyword(s):  
Stomatal Conductance ◽  
Environmental Factors ◽  
Vapor Pressure ◽  
Inner Mongolia ◽  
Saturated Vapor ◽  
Water Flux ◽  
Growing Season ◽  
Leaf Nitrogen ◽  
Leaf Nitrogen Content ◽  
Vegetation Characteristic

Abstract To incorporate canopy vertical structure in a process-based model over a temperate meadow, a multilayered model estimated canopy carbon flux (Fc) and water flux (LE) was applied by comparing with eddy covariance measurements in Inner Mongolia, China. Simulations of diurnal, seasonal CO2 and H2O fluxes and model sensitivity to parameters and variables were analyzed. The results showed that the model underestimated Fc and LE by about 0.6% and 5.0%, respectively. It was able to simulate the diurnal and seasonal variation of Fc and LE and performed well during the day and in the growing season, but poorly at night and early in the growing season. Fc was more sensitive to the leaf nitrogen content distribution coefficient and maximum catalytic activity of Rubisco, whereas LE showed greater sensitivity to the stomatal conductance parameter a1, empirical coefficient of stomatal response to saturated vapor pressure difference Vpds0, and minimum stomatal conductance of CO2gsc0. The response of Fc to environmental factors was ranked as air CO2 concentration (Ca) > air temperature (Ta) > photosynthetically active radiation (PAR) > soil water content (θsm) > vapor pressure deficit (VPD) > wind speed (u0). The response of LE to environmental factors was ranked as Ta > VPD > θsm> PAR> Ca> u0. The response of LE to vegetation characteristic parameters was greater than that of Fc.

scholarly journals Estimating the Leaf Nitrogen Content with a New Feature Extracted from the Ultra-High Spectral and Spatial Resolution Images in Wheat

2021 ◽  
Vol 13 (4) ◽  
pp. 739
Author(s):  
Jiale Jiang ◽  
Jie Zhu ◽  
Xue Wang ◽  
Tao Cheng ◽  
Yongchao Tian ◽  
...  
Keyword(s):  
Nitrogen Content ◽  
Precision Agriculture ◽  
Field Experiments ◽  
Mean Squared Error ◽  
Growing Season ◽  
Leaf Nitrogen ◽  
Textural Analysis ◽  
Hyperspectral Images ◽  
Leaf Nitrogen Content ◽  
New Feature

Real-time and accurate monitoring of nitrogen content in crops is crucial for precision agriculture. Proximal sensing is the most common technique for monitoring crop traits, but it is often influenced by soil background and shadow effects. However, few studies have investigated the classification of different components of crop canopy, and the performance of spectral and textural indices from different components on estimating leaf nitrogen content (LNC) of wheat remains unexplored. This study aims to investigate a new feature extracted from near-ground hyperspectral imaging data to estimate precisely the LNC of wheat. In field experiments conducted over two years, we collected hyperspectral images at different rates of nitrogen and planting densities for several varieties of wheat throughout the growing season. We used traditional methods of classification (one unsupervised and one supervised method), spectral analysis (SA), textural analysis (TA), and integrated spectral and textural analysis (S-TA) to classify the images obtained as those of soil, panicles, sunlit leaves (SL), and shadowed leaves (SHL). The results show that the S-TA can provide a reasonable compromise between accuracy and efficiency (overall accuracy = 97.8%, Kappa coefficient = 0.971, and run time = 14 min), so the comparative results from S-TA were used to generate four target objects: the whole image (WI), all leaves (AL), SL, and SHL. Then, those objects were used to determine the relationships between the LNC and three types of indices: spectral indices (SIs), textural indices (TIs), and spectral and textural indices (STIs). All AL-derived indices achieved more stable relationships with the LNC than the WI-, SL-, and SHL-derived indices, and the AL-derived STI was the best index for estimating the LNC in terms of both calibration (Rc2 = 0.78, relative root mean-squared error (RRMSEc) = 13.5%) and validation (Rv2 = 0.83, RRMSEv = 10.9%). It suggests that extracting the spectral and textural features of all leaves from near-ground hyperspectral images can precisely estimate the LNC of wheat throughout the growing season. The workflow is promising for the LNC estimation of other crops and could be helpful for precision agriculture.

Near stream groundwater table fluctuations impact transpiration rates of riparian plants: a field study with stomatal conductance and dendrometry measurements

2021 ◽  
Author(s):  
Stefano Martinetti ◽  
Simone Fatichi ◽  
Marius Floriancic ◽  
Paolo Burlando ◽  
Peter Molnar
Keyword(s):  
Stomatal Conductance ◽  
Vapor Pressure ◽  
Water Table ◽  
Vapor Pressure Deficit ◽  
Growing Season ◽  
Groundwater Table ◽  
Short Term ◽  
Riparian Plants ◽  
Gravel Bed ◽  
Riparian Trees

<p>Vegetation establishment, growth, and succession in riparian ecosystems are linked to river and groundwater dynamics. This is especially true in Alpine gravel-bed rivers with wide floodplains and a strong river-aquifer exchange. Here we provide data evidence of riparian plant response to short-term groundwater table fluctuations in a braided gravel-bed river (Maggia). We used indirect physiological variables for photosynthesis and transpiration – stomatal conductance g<sub>s</sub> and daily variation in stem diameter ΔD<sub>d</sub> – which we measured at six mature riparian trees of the Salicaceae family, one Populus nigra and one Alnus incana specimen at two sites during two growing seasons. The site where g<sub>s</sub> measurements were conducted showed a greater depth to groundwater with higher variability compared to the site were dendrometers were placed.</p><p>We analysed the data by means of two different random forest regression algorithms for the two study sites. One with the transpiration-induced daily tree diameter drop during the growing season 2017 as the dependent variable, and one with the raw g<sub>s</sub> measurement sequence, obtained on 10 days throughout the growing season 2019, as the dependent variable. In both algorithms the independent variables consisted of meteorological measures (locally measured and at valley scale) and of groundwater and river stages near the individual plants. We also separated the g<sub>s</sub> measurements into low and high groundwater stage conditions observed during the g<sub>s</sub> field campaign and applied traditional regression analysis of g<sub>s </sub>on vapor pressure deficit VPD and global radiation r<sub>g</sub> for the 2 groundwater stage conditions separately.</p><p>The data analyses demonstrate that:</p><p>(a) short-term variation of the groundwater table affects riparian vegetation: at the site with deeper groundwater, the water table depth was the best predictor of g<sub>s</sub> variability, while at the site with shallower groundwater, temperature and vapor pressure deficit were the best predictors of ΔD<sub>d</sub>  variability;</p><p>(b) instantaneous stomatal conductance is related to vapor pressure deficit (VPD), but conditioned by groundwater levels, with higher stomatal conductance for the same radiative input and VPD when the water table was higher.</p><p>(c) local micro-climate measured at tree locations had a stronger predictive power for g<sub>s</sub> than valley scale climate, suggesting local climate may be an important control on vegetated stands on gravel bars.</p><p>Even though the considered plants are located in close proximity to the river and could be considered to be unaffected by water stress, our analysis provides evidence of riparian trees undertaking physiological adjustments to transpiration in response to groundwater stage, depending on their riparian floodplain settings. In the heavily regulated Maggia river this has implications on the minimum flow release by dams, as prolonged periods of low water stage in the river will lead to a decrease in groundwater stage, and subsequently in reduced growth of phreatophytic riparian plants on the floodplain. We argue such plant-scale measurements should be helpful for the optimisation of flow release levels in regulated riparian systems.</p>

Contribution of overwintering leaves to the growth of three broad-leaved, evergreen shrubs belonging to the Ericaceae family

1978 ◽  
Vol 56 (10) ◽  
pp. 1248-1261 ◽  
Author(s):  
R. J. Reader
Keyword(s):  
Growing Season ◽  
Leaf Nitrogen ◽  
Leaf Nitrogen Content ◽  
Nitrogen And Phosphorus ◽  
Southern Ontario ◽  
Plant Parts ◽  
Mature Leaves ◽  
Growing Seasons ◽  
Labrador Tea ◽  
Ledum Groenlandicum

Individual leaves of three bog ericads, leatherleaf (Chamaedaphne calyculata), bog laurel (Kalmia polifolia), and Labrador tea (Ledum groenlandicum), were retained for a maximum of two growing seasons in a peat bog in southern Ontario. The premature loss of mature leaves, resulting from artificial defoliation, significantly reduced the growth of new shoots of L. groenlandicum and K. polifolia but not of C. calyculata. Defoliation effects were directly proportional to the normal retention time for overwintering leaves. Mature leaves probably translocate photosynthate, nitrogen, and phosphorus to other plant parts. This would explain why leaf dry weights were greatest at the start, rather than at the end, of the leaves' second growing season. Net photosynthetic rates decreased with leafage, but in terms of leaf nitrogen content, new and old leaves fixed equal amounts of carbon.

Photosynthesis - stomatal conductance model LEAFC3-N: specification for barley, generalised nitrogen relations, and aspects of model application

2008 ◽  
Vol 35 (10) ◽  
pp. 797 ◽  
Author(s):  
Johannes Müller ◽  
Henning Braune ◽  
Wulf Diepenbrock
Keyword(s):  
Stomatal Conductance ◽  
Growth Models ◽  
Leaf Nitrogen ◽  
Carbon Gain ◽  
Model Parameters ◽  
Leaf Nitrogen Content ◽  
Time Step ◽  
Close Range ◽  
Crop Growth Models ◽  
Parameter Values

We discuss a generalised formulation of the nitrogen-sensitive photosynthesis−stomatal conductance model LEAFC3-N to be used as a submodel of functional–structural plant models (FSPMs) or traditional crop growth models for C3-crops. Based on a parameterisation study for barley, we demonstrate that the large variation of characteristics related to potential leaf photosynthesis and stomatal conductance, along with different factors, can be accounted for by introducing functions that relate parameter values to nitrogen contents. These relationships follow the same pattern for different C3 crops, and their parameters are in close range. The accuracy of the parameters and the minimum simulation time step required for reliable predictions of the integrated diurnal carbon gain (IDC) is assessed. For IDC predictions with an accuracy of about ±5%, the accuracy of the slope of the relationship between maximum carboxylation rate and leaf nitrogen content should be of similar order. For other key model parameters, an error of ±20% or even greater may be tolerated. A time step of 1–2 h will be sufficient to predict IDC with an accuracy of about ±5%.

scholarly journals Sensitivity of Functional Traits to Environmental factors in a Karst Plant Community

2022 ◽  
Author(s):  
Yang Wang ◽  
Limin Zhang ◽  
Jin Chen ◽  
Ling Feng ◽  
Fangbing Li ◽  
...  
Keyword(s):  
Environmental Factors ◽  
Nitrogen Content ◽  
Bulk Density ◽  
Leaf Area ◽  
Plant Community ◽  
Functional Traits ◽  
Specific Leaf Area ◽  
Soil Bulk Density ◽  
Leaf Nitrogen ◽  
Leaf Nitrogen Content

In this study, the plant communities at five succession stages (herbage, herbage-shrub, shrub, tree-shrub, and tree) in the Zhenning Karst Plateau area of Guizhou were examined. The changes of plant functional characteristics in different succession stages were analyzed, as was the relationship between functional traits and environmental factors. The main results include the following. (1) During the succes-sion process, plant height, leaf dry matter mass, leaf area, leaf nitrogen content, and leaf phosphorus content gradually increased, whereas leaf thickness and specific leaf area decreased, and leaf C:P ratio and leaf N:P ratios did not change significantly. (2) Soil organic matter, soil total nitrogen, soil total phosphorus, soil C:N, soil C:P, and soil C:K increased at first and then decreased, reaching a peak at the tree-shrub stage. Soil total potassium fluctuated and soil bulk density gradually decreased and reached the lowest value at the tree-shrub stage. (3) Redundancy analysis (RDA) showed that the plant community shifted from a nutri-ent-poor soil environment to a nutrient-rich environment. Soil total phosphorus, soil C:K, soil organic mat-ter, soil C:N, and soil bulk density were the key environmental factors affecting the change of functional traits. (4) Structural equation modeling suggests that that specific leaf area and leaf nitrogen content had more sensitive responses to soil nutrient resources and environmental factors, respectively.

scholarly journals Leaf Nitrogen Content, Photosynthesis and Radiation Use Efficiency in Peanut1

1993 ◽  
Vol 20 (1) ◽  
pp. 40-43 ◽  
Author(s):  
T. R. Sinclair ◽  
J. M. Bennett ◽  
K. J. Boote
Keyword(s):  
Nitrogen Content ◽  
Field Tests ◽  
Positive Association ◽  
Growing Season ◽  
Leaf Nitrogen ◽  
Radiation Use Efficiency ◽  
Leaf Nitrogen Content ◽  
Wide Range ◽  
Use Efficiency ◽  
Radiation Use

Abstract It has been hypothesized that a close correlation exists between specific leaf nitrogen content (SLN, g N m-2 leaf area) and leaf carbon exchange rate (CER), and crop radiation use efficiency (RUE). This association has not been investigated previously in peanut (Arachis hypogaea L.) so the objective of this research was to obtain such data under greenhouse and field conditions. In the greenhouse study differing nitrogen fertilizer treatments for a non-nodulated cultivar resulted in leaves with a wide range of SLN and CER. A strong, positive association between SLN and CER was found. In the field little variation in either SLN or CER was observed through much of the growing season in four commercial cultivars. Consistent with the observation of stability in SLN and CER, RUE based on total, intercepted solar radiation was found to be constant at 1.00 g MJ-1 through the growing season. However, the observed RUE was 29% greater than a theoretical RUE calculated assuming a uniform distribution of SLN in the canopy. One possibility is that RUE of peanuts may be enhanced by a nonuniform SLN distribution within its leaf canopy. In any event, the results of both the greenhouse and field tests showed that peanut CO2 assimilation is closely linked to leaf SLN.

Effect of Mycorrhizal Fungi on Gas Exchange of Micropropagated Guava Plantlets (Psidium guajava L.) during Acclimatization and Plant Establishment

HortScience ◽  
1998 ◽  
Vol 33 (3) ◽  
pp. 501c-501
Author(s):  
Andrés A. Estrada-Luna ◽  
Jonathan N. Egilla ◽  
Fred T. Davies
Keyword(s):  
Tissue Culture ◽  
Stomatal Conductance ◽  
Gas Exchange ◽  
Vapor Pressure ◽  
Mycorrhizal Fungi ◽  
Vapor Pressure Deficit ◽  
Psidium Guajava ◽  
Glomus Etunicatum ◽  
Plant Establishment ◽  
Use Efficiency

The effect of mycorrhizal fungi on gas exchange of micropropagated guava plantlets (Psidium guajava L.) during acclimatization and plant establishment was determined. Guava plantlets (Psidium guajava L. cv. `Media China') were asexually propagated through tissue culture and acclimatized in a glasshouse for eighteen weeks. Half of the plantlets were inoculated with ZAC-19, which is a mixed isolate containing Glomus etunicatum and an unknown Glomus spp. Plantlets were fertilized with modified Long Ashton nutrient solution containing 11 (g P/ml. Gas exchange measurements included photosynthetic rate (A), stomatal conductance (gs), internal CO2 concentration (Ci), transpiration rate (E), water use efficiency (WUE), and vapor pressure deficit (VPD). Measurements were taken at 2, 4, 8 and 18 weeks after inoculation using a LI-6200 portable photosynthesis system (LI-COR Inc. Lincoln, Neb., USA). Two weeks after inoculation, noninoculated plantlets had greater A compared to mycorrhizal plantlets. However, 4 and 8 weeks after inoculation, mycorrhizal plantlets had greater A, gs, Ci and WUE. At the end of the experiment gas exchange was comparable between noninoculated and mycorrhizal plantlets.

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