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12 results for “stomatal conductance”
Light-saturated photosynthetic rate, dark respiration, stomatal conductance and ratio of internal to external carbon dioxide concentration from the 1980-82 Eriophorum vaginatum reciprocal transplant plots from Eagle Creek to Prudhoe Bay, Alaska, 2010
In 1980-1982, six transplant gardens were established along a latitudinal gradient in interior Alaska from Eagle Creek, AK, in the south to Prudhoe Bay, AK, in the north (Shaver et al. 1986) .Three sites, Toolik Lake (TL), Sagwon (SAG), and Prudhoe Bay (PB) are north of the continental divide and the remaining three, Eagle Creek (EC), No Name Creek (NN), and Coldfoot (CF), are south of the continental divide. Each garden consisted of 10 individual tussocks transplanted back to their home-site, as well as 10 individuals from each of the other transplant sites. Data were collected in July 2010 for tussocks transplanted in 1980-82 in a reciprocal transplant experiment and then harvested in 2011. Important variables are garden name, source population, light-saturated photosynthetic rate, dark respiration, stomatal conductance and ratio of internal to external carbon dioxide concentration.
Structural constraints in current stomatal conductance models preclude accurate estimation of evapotranspiration and its partitions
<p>This archive includes the scripts and related input data to produce results for the paper entitled - "Structural constraints in current stomatal conductance models preclude accurate estimation of evapotranspiration and its partitions". Following is the description of files/folders:</p> <p>1. Input_Data: This folder contains all the required input data including FluxNet data, soil properties, quality controlled training-validation data, and metadata & other supporting information of the sites. </p> <p>2. Model_EMP: This folder contains all the scripts for empirical model of stomatal conductance. (Note: Scripts have been written in MATLAB"). No need to change anything except the MATLAB executive path in two files "run_all_tasks_to_optimize_params.sh" and "prediction.sh". Read "ReadMe.txt" file in the folder "Model_EMP" for more instructions on running the model. </p> <p>3. Model_ML: This folder contains all the scripts for pure machine learning model of stomatal conductance. It contains four sub-folders: 1. Model_Config_1 (Model with configuration-1); 2. Model_Config_2_TEA (Model with Configuration-2 & TEA-based T estimates); 3. Model_Config_2_uWUE (Model with Configuration-2 & uWUE-based T estimates); 4. Model_Config_2_Yu22 (Model with Configuration-2 & Yu22-based T estimates). Further instructions have been given in each jupyter notebooks. Briefly, in folder "Model_Config_1", the notebook "train_ML_config_1.ipynb" trains the model parameters and notebook "Predictions_ML_config_1" is used to do predictions. Similar instructions apply for other subfolders. (Note: Scripts have been written in Python Language"). All the scripts are fully functional as long as all the required modules are installed.</p> <p>4. Model_PH_exp: This folder contains all the scripts for plant hydraulics model with explicit representation. All the scripts are self explanatory and further instructions are provided in the scripts as needed. (Note: Scripts have been written in Python Language"). All the scripts are fully functional as long as all the required modules are installed.</p> <p>5. Model_PN_imp: This folder contains all the scripts for plant hydraulics model with implicit representation. Instructions given for "Model_ML" are applicable here. (Note: Scripts have been written in Python Language"). All the scripts are fully functional as long as all the required modules are installed.<br> </p> <p>Versions: Tensorflow 2.11.0, MATLAB_R2022a, Python 3.10.9</p>
Stomatal conductance and tree growth response to multi-year droughts in fire-maintained and fire-excluded forests
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Impact of Helicoverpa zea salivary GOX on stomatal conductance and volatile emission of host plants
<p>This data set contain raw data associated with the manuscript titled "Silencing the alarm: An insect salivary enzyme closes plant stomata and inhibits volatile release". </p> <p>Herbivore-induced plant volatiles (HIPVs) are widely recognized as ecologically important to plant. While the majority of studies focused on the induction of this "cry for help", little is known about whether insect herbivores have evolved mechanisms to reduce the release of HIPVs. Here we show that a caterpillar (<em>Helicoverpa zea</em>) salivary enzyme, glucose oxidase (GOX), commonly secreted on plant leaves causes stomatal closure and reductions in emissions of several HIPVs involved in plant defenses. We found that application of GOX to wounded regions of leaves led to reductions in stomatal conductance on tomato (<em>Solanum lycopersicum</em>) and soybean (<em>Glycine max</em>) for at least two days. The role of GOX in reducing stomatal aperture was confirmed using GOX knockout lines of <em>H. zea</em> (CRISPR-Cas9 mutagenesis), and microscopic observations of stomata. In addition, GOX reduced the emission of several HIPVs during feeding by <em>H. zea</em>, including (Z)-3-hexenol, (Z)-jasmone, and (Z)-3-hexenyl acetate, which are important air borne signals in plant defenses. Our findings highlight a novel mechanism where insect herbivore reduces the release of HIPVs during feeding by targeting fundamental plant structure (i.e. stomata), and the link between of stomatal dynamics and releases of HIPVs. We demonstrate the existence of HIPVs-interfering mechanisms as a potential evolutionary strategy for insect herbivores to interfere with plant air borne signals.</p>
Sapflow and stomatal conductance data in 3 savanna tree species
<p>This dataset includes both sap flow and stomatal conductance data for 3 woody savanna species (11 individuals of <em>Colophospermum mopane</em>, and each 9 of both <em>Senegalia mellifera</em> and <em>Catophractes alexandri</em>). Each data point contains information on a browsing level that has been manually applied to an individual plant plus information on environmental conditions.</p>
Sapflow and stomatal conductance data in 3 savanna tree species
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Impact of Helicoverpa zea salivary GOX on stomatal conductance and volatile emission of host plants
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Datasets used in "Stomatal conductances influences interannual variability and long-term changes in regional cumulative plant uptake of ozone"
Model archived fields for surface ozone, effective stomatal conductance, and leaf area index corresponding to Clifton, O. E., Lombardozzi, D. L., Fiore, A. M., Paulot, F., & Horowitz, L. W., (2020). Stomatal conductance influences interannual variability and long-term changes in regional cumulative plant uptake, Environmental Research Letters.
Grass veins are leaky pipes: Vessel widening in grass leaves explain variation in stomatal conductance and vessel diameter among species
<p>The widening of xylem vessels from tip-to-base of trees is an adaptation to minimize the hydraulic resistance of a long pathway. Given that parallel veins of monocot leaves do not branch hierarchically, vessels should also widen basipetally but, in addition to minimizing resistance, should also account for water volume lost to transpiration since they supply water to the lamina along their lengths, i.e. "leakiness".</p> <p>We measured photosynthesis, stomatal conductance, and vessel diameter at 5 locations along each leaf of 5 perennial grass species.</p> <p>We found that the rate of conduit widening in grass leaves was larger than the widening exponent required to minimize pathlength resistance (0.35 vs. ~0.22). Furthermore, variation in the widening exponent among species was positively correlated with maximal stomatal conductance (r<sup>2 </sup>= 0.20) and net CO<sub>2</sub> assimilation (r<sup>2</sup> = 0.45).</p> <p>These results suggest that faster rates of conduit widening (>0.22) were associated with higher rates of water loss. Taken together, our results show that the widening exponent is linked to plant function in grass leaves and that natural selection has favored parallel vein networks that are constructed to meet transpiration requirements while minimizing hydraulic resistance within grass blades.</p>
Software code for simulations and analyses concerning the calculation of canopy stomatal conductance at eddy covariance sites
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Grass veins are leaky pipes: Vessel widening in grass leaves explain variation in stomatal conductance and vessel diameter among species
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Novel Role of JAC1 in Influencing Photosynthesis, Stomatal Conductance, and Photooxidative Stress Signalling Pathway in Arabidopsis thaliana
GEO Series GSE143762. Arabidopsis thaliana. 12 samples. Type: Expression profiling by high throughput sequencing.
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