Funding for this study was provided by U.S. Department of Energy&#39;s Office of Science, Office of Biological and Environmental Research, Terrestrial Ecosystem Sciences Program Award No. DE-SC0007041, Ameriflux Management program under Flux Core Site Agreement No. 7096915 through Lawrence Berkeley National Laboratory, and the National Science Foundation Hydrological Science grant 1521238. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the funding agencies.

1. Select a Tree for Instrumentation
<ol>
	<li>Select trees for measurement. Ideally, select trees that are healthy with a generally round stem cross-section, and a diameter between 1-2 times the tine length, or a sapwood depth greater than the length of the sensor tines (~5 cm for the specific capacitance sensors demonstrated here). Measure the depth of the sapwood using tree cores, or for many species, calculate sapwood depth through allometric equations relating sapwood area to stem diameter 29,54, as measured by a standard diameter tape. 
	NOTE: However, some types of capacitance sensors may be able to be trimmed to an appropriate length following Step 1.2 without adversely affecting measurement accuracy. Only capacitance sensors with rigid measurement tines that do not contain wiring can be trimmed or cut. Separate calibration is necessary for trimmed sensors. Therefore, select the tree and determine the appropriate tine length prior to the calibration procedure.</li>
	<li>Determine the appropriate length of the sensor tines based on the tree&#39;s diameter and sapwood depth. 
	NOTE: Capacitance sensors integrate moisture information over the length of the sensor tines, L. It is therefore assumed that the integrated observation they provide is representative of the entire stem when the diameter is between L and 2L. The bark and phloem will not affect the measurement as they are removed from the measurement area prior to installation (see section 4.2).
	<ol>
		<li>Trim the sensors for trees where L is greater than the stem diameter, (see Step 1.3) such that the tines do not penetrate through the opposite side of the stem.</li>
		<li>Measure the combined signal from the sapwood and heartwood with the sensor for trees where the diameter is larger than 2L, but sapwood depth is less than L. 
		NOTE: As water content differs in these two tissue types, this may cause a bias if it is assumed that the observation is representative of the whole stem. In such cases, or when the user is only interested in the sapwood water fluctuations, the sensor tines must be trimmed to the sapwood depth such that the observations will represent the water content fluctuations of the sapwood (active xylem) only. When the sapwood depth is larger than L, observations represent only the sapwood, but the sensor does not need to be trimmed.</li>
	</ol>
	</li>
	<li>If necessary (as determined in Steps 1.2.1 and 1.2.2), cut the sensor to fit for the specified application. To cut the sensor tines, clamp the sensor securely to a workbench and, while wearing proper protective equipment, use a power rotary tool equipped with a steel cutting disk to cut each tine to precisely the same length.</li>
</ol>
2. Harvest and Prepare Wood Samples of All Species of Interest to Generate a Species-Specific Calibration
<ol>
	<li>Collect a trunk, juvenile stem, or large branch at least 6 cm in diameter from the species of interest. Larger diameters are preferred in order to maximize the amount of wood encasing the sensor and most closely approximate the trunk density for field measurements. Remove all attached branches or leaves, and any lichen or loose material. 
	NOTE: Refer to the Discussion section for further discussion of uncertainty due to differences in branch and stem density.</li>
	<li>Segment the stem into 25 or more cylindrical sections of ~15 cm length.</li>
	<li>Label each segment and record the average diameter and length of each. Approximate the segments&#39; volume as the volume of a cylinder.</li>
	<li>Separate the segments into two groups for differential rehydration and drying. Place roughly 1/3 of the segments in a water bath to rehydrate, and the other 2/3 of the segments in a drying oven at 60 &#176;C to dehydrate. Keep two segments separate for immediate measurement: preferably one from the middle of the length of the stem, and one from an end. 
	NOTE: Typically, segments drying at 60 &#176;C will be fully desiccated after ~2 weeks, and fully rehydrated after ~3 days. Remove individual segments from the oven/water bath and measure daily or twice-daily intervals (see Step 3.7). In order to produce a gradient of measurements spanning the largest range of possible volumetric water contents.</li>
</ol>
3. Create a Calibration Relationship between Sensor Output and Volumetric Water Content
<ol>
	<li>Connect a capacitance sensor to a data logging device, following the instructions provided by the manufacturer, and to a computer for real-time sensor readout visualization. Set the time interval for data collection to 30 s.</li>
	<li>Using a premade drilling template held securely in place to maintain alignment, and a drill bit slightly smaller than the diameter of the tines of the capacitance sensor (3.57 mm for the sensor used in this experiment), drill two vertical sets of three holes with the second set located approximately 150 &#176; away around the wood segment with a vertical separation of a few centimeters to ensure that there is no potential overlap between holes. Use the wood segments set aside in Step 2.4 for the first set of measurements.</li>
	<li>Weigh the segment and record the weight to the nearest 0.01 g at the time of measurement. Cap the ends of the segments with plastic wrap to prevent additional drying.</li>
	<li>Immediately after weighing, clean the tines of the capacitance sensor with an alcohol swab and insert it into the stem segment completely, such that no part of the steel tines is visible. Wait for the measurement reading on the output screen to stabilize (2 or 3 min, generally). Record the sensor outputs of temperature, electrical conductivity, and dielectric permittivity (&#949;b) every 30 s for 5 min and compute the average of the 10 measurements.</li>
	<li>Gently remove the sensor from the segment, clean the tines with an alcohol swab, and wait for the output readings to return to zero. Repeat the measurement procedure from step 3.3 onward in the second set of pre-drilled holes.</li>
	<li>Remove plastic from the ends and place the stem segment in the drying oven. Allow it to desiccate completely (generally 2 weeks, or until weight has stabilized for several days).</li>
	<li>Repeat steps 3.3 through 3.7 for all segments. Remove segments from the drying oven and measure more frequently (twice daily) within the first several days of drying, due to the higher rate of initial moisture loss than during the last several days (daily). Dry excess water from the surface of segments removed from the water bath using a paper towel before weighing and measurement. Measure one rehydrated stem segment per day, until all rehydrated segments have been measured.</li>
	<li>After complete desiccation, record the final dry weight of all stem segments.</li>
	<li>Calculate the volumetric water content (VWC, cm3water /cm3wood) of each stem segment at the time of measurement, using the following formula: 
	<img alt="Equation 1" src="/files/ftp_upload/57062/57062eq1.jpg" /> (1) 
	Where Vw is the volume of water (cm3), and Vstem is the volume of the stem segment (cm3) calculated in step 1.2.
	<ol>
		<li>Calculate the volume of water in each segment at the time of measurement as: 
		<img alt="Equation 2" src="/files/ftp_upload/57062/57062eq2.jpg" /> (2) 
		Where mw is the mass water in the stem segment (g) at the time of measurement, and &#961;w is the density of water (1 g cm-3)</li>
		<li>Calculate the mass of water in each segment at the time of measurement as: 
		<img alt="Equation 3" src="/files/ftp_upload/57062/57062eq3.jpg" /> (3) 
		Where Mwet is the mass of the stem segment at the time of measurement (g), and Mdry is the final weight of the segment (g).</li>
	</ol>
	</li>
	<li>Using a statistical analysis software package, create a best-fit linear regression between sensor-observed dielectric permittivity and VWC (Figure 1, Table 1).</li>
</ol>
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/57062/57062fig1.jpg" /> 
Figure 1: Example calibration curves. Calibration curves generated for Quercus rubra, Acer rubrum, Betula papyrifera, Populus grandidentata, and Pinus strobus following Parts 1 and 2 of this protocol. Equations and coefficients of determination are provided for each in Table 1. <a href="//cloudfront-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/57062/57062fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td></td>
			<td>m</td>
			<td>b</td>
			<td>R2</td>
		</tr>
		<tr>
			<td>B. paprifera</td>
			<td>0.048</td>
			<td>-0.098</td>
			<td>0.967</td>
		</tr>
		<tr>
			<td>A. rubrum</td>
			<td>0.067</td>
			<td>-0.158</td>
			<td>0.853</td>
		</tr>
		<tr>
			<td>Q. rubra (shortened)</td>
			<td>0.120</td>
			<td>0.041</td>
			<td>0.636</td>
		</tr>
		<tr>
			<td>Q. rubra</td>
			<td>0.058</td>
			<td>-0.109</td>
			<td>0.718</td>
		</tr>
		<tr>
			<td>P. grandidentata</td>
			<td>0.023</td>
			<td>-0.028</td>
			<td>0.887</td>
		</tr>
		<tr>
			<td>P. strobus</td>
			<td>0.030</td>
			<td>-0.072</td>
			<td>0.900</td>
		</tr>
	</tbody>
</table>
Table 1: Calibration equations for the conversion of &#949;b to VWC for five temperate tree species. Coefficients &#39;m&#39; and &#39;b&#39; are presented for a linear equation in the standard form: VWC = m*&#949;b+b.
4. Installing Capacitance Sensors in Trees for Field Measurements
<ol>
	<li>Prior to sensor installation, record the stem diameter and the height above the ground surface for each sensor location. Typically, to monitor VWC in the trunk, place one sensor ~0.5 m above the ground surface, and place a second one just below the first major branching split (~7.5 m above the ground, Figure 2).</li>
</ol>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/57062/57062fig2.jpg" /> 
Figure 2: Example field experiment setup. A schematic diagram of sensor locations and orientation in a mature tree adjacent to a data logging station. <a href="//cloudfront-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/57062/57062fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<ol start="2">
	<li>Remove the bark to the cambium and create a flat surface where the sensor will be installed using a draw blade. Ensure that this surface is wide and flat enough that the sensor sits flush against the surface of the tree when it is installed such that no part of the tines is exposed. Remove the bark and cambium to ensure that measurements include only water content in the xylem, while excluding water content in the bark or phloem.</li>
	<li>Drill the holes for the tines. Use a drill bit slightly smaller than the diameter of the tines for softer wood, while using a bit closer to the true size of the tines for harder wood (3.57 mm as used in this protocol). For high quality measurements, ensure that the sensor tines make good contact with the wood. Since there will not be a need to remove the sensor regularly, as was the case during the calibration procedure, a slightly smaller drill bit may be used here than the one used for calibration.</li>
	<li>Clean the sensor tines with an alcohol swab to remove any dirt or skin oils, and insert the sensor into the pre-drilled holes. If the sensor meets too much resistance upon insertion, gently back it out and re-drill the holes to widen them slightly. Ensure that all three tines are fully inserted and the body of the sensor sits flush against the tree trunk.</li>
	<li>Use a silicon-based sealant to seal the sensor against the tree trunk to help keep stem flow from entering the holes and to prevent pest infestation.</li>
	<li>Cover the sensor with reflective insulation to avoid external heating.</li>
	<li>Following the manufacturers&#39; specifications, connect all sensors to a 12 V power source and a compatible data logger. Use data collection intervals of 5 min for sensors deployed in the field, but use longer intervals to conserve power in sites where power is limiting, e.g., solar/battery operated sites.</li>
</ol>
5. Process the Raw Data to Stem-Water Storage Using the Calibration Curve
<ol>
	<li>Using the equation of the calibration curve generated in step 2.9, convert the sensor output to VWC for all observations. VWC is generally expressed as cm3 /cm3 or as a percent. The percent VWC will therefore range between 0 and 100%.</li>
	<li>Integrate the total volume of interest (cm3) between the two measurement heights (e.g., in Figure 2: 0.5 m and 7.5 m) by assuming stem diameter changes linearly with height. For trees where the observation represents the whole stem (i.e., trees of diameters between L and 2L, using unmodified sensors, or thinner trees where the sensor was trimmed to the stem diameter, see section 2.2), use equation 4: 
	<img alt="Equation 4" src="/files/ftp_upload/57062/57062eq4.jpg" /> (4) 
	where H is the height difference (vertical distance) between the sensors (e.g., in Figure 2: 700 cm) and r1 and r2 are the radii of the stem (cm) at the bottom and top sensors&#39; locations, respectively. 
	For trees where sensors provide an estimate only of the sapwood water content (see sensor length determination, section 1.2) use eq. 5: 
	<img alt="Equation 5" src="/files/ftp_upload/57062/57062eq5.jpg" /> (5) 
	where s1 and s2 are the sapwood depths (cm) at the bottom and top sensors&#39; locations, respectively.</li>
	<li>Calculate the volume of stem- or sapwood- stored water by multiplying the tree&#39;s average VWC by the total volume of interest.</li>
</ol>

Steven R. Garrity is an employee of METER Group Inc. that produces the GS3 Ruggedized Soil Moisture Sensor used in this Article.

Seasonal and diurnal patterns in stem water content observed via capacitance sensors align with trends in concurrent sap flux and environmental forcing measurements (Figure 3, Figure 4, Figure 5). Reservoirs of stem water storage are depleted diurnally when the pace of transpiration surpasses the rate of recharge through woody tissues, and seasonally when soil moisture limits root-water availability...

Water stored in plant material plays an integral role in plants&#39; ability to cope with short- and long-term water stress1,2. Plants store water in roots, stems, and leaves in both intracellular and extracellular (e.g., xylem vessels) spaces 2,3,4. This water has been shown to contribute between 10 and 50% of diurnally transpired water2,5,6,7,8. As such, plant hydraulic capacitance is a key component of the terrestrial water balance, can be used as an indicator of water stress, drought response, and recovery1, and is a critical factor necessary to correct for observed time lags between transpiration and sap flow9,10,11. Real-time monitoring of vegetation water content can also be used in agricultural applications to help constrain orchard and crop irrigation in order to increase watering efficiency12,13. However, measurements of continuous, in-situ stem-water content of woody species7,14,15,16,17,18,19 are rare relative to sap flux measurements20. Here, we outline a procedure for the calibration of capacitance sensors to monitor the volumetric water content within the stems of trees5,21.
Hydrodynamic behaviors and water-use regulation by vegetation are an integral component of the soil-plant-atmosphere continuum22,23 and are therefore important controls for the water and carbon fluxes between the biosphere and atmosphere24,25. The dynamics of stem water content are influenced by both biotic and abiotic factors. Depletion and recharge of stem-stored water are affected by short- and long-term trends in environmental conditions, in particular, vapor pressure deficit and soil water content1,26. The physical properties of the wood27 (e.g., density, vessel structure) and the emergent hydraulic strategy25 (e.g., iso- or anisohydric stomatal regulation) determine a plant&#39;s ability to store and use water19,26,28, and can vary widely by species29,30. Previous studies have demonstrated different roles of capacitance in tropical16,27,31,32,33 and temperate5,7,21 species, and in both angiosperms1,2,34 and gymnosperms6,11,17,19.
Improved knowledge of biomass water content will improve understanding of vegetation strategies for water acquisition and use1,2, along with species&#39; vulnerability to predicted changes in precipitation regimes35,36. Further understanding of plant water use strategies will help predict shifting demographic patterns under future climate scenarios37,38. Through model-data fusion techniques39, stem water content data obtained using this methodology can be used to inform and test scalable, plant-level hydrodynamics models40,41,42,43,44 in order to improve calculations of stomatal conductance and, thereby, simulations of both transpiration and photosynthetic carbon uptake. These advanced hydrodynamic models may provide a significant reduction in uncertainty and error when incorporated into larger land-surface and Earth systems models25,45,46,47,48.
Methods used to monitor or calculate stem water content include tree coring33,49, electronic dendrometers2,15,50, electrical resistance51, gamma radiation attenuation52, deuterium tracers19, networks of sap flux sensors32,33,53, stem psychrometers49, and amplitude11 and time4,12,13 domain reflectometry (TDR). Recent efforts have tested the viability of capacitance sensors that have traditionally been used to measure soil volumetric water content5,18,21,27. Frequency domain reflectometry (FRD)-style capacitance sensors are low cost and use relatively small amounts of energy for continuous measurements, making them an attractive tool for high temporal resolution measurements in field scenarios. The ease of automation of FDR over TDR-style sensors facilitates the collection of continuous sun-hourly data sets, and eliminates many of the challenges inherent in TDR measurements requiring substantial cable lengths13. The use of in-situ capacitance sensors eliminates the need for repetitive coring or branch harvesting, and may provide enhanced accuracy for hardwood species. Woody species that withdraw water principally from extracellular spaces, such as xylem vessels, or have high wood or bark moduli of elasticity, are generally not good candidates for popular dendrometer measurement techniques due to low elastic stem expansion2. Capacitance sensors estimate dielectric permittivity, which can be directly converted to volumetric water content. However, capacitance measurements are sensitive to the density of the media surrounding the sensor. Therefore, we advocate for species-specific calibrations that convert the output of the sensors to volumetric wood-water content5,21.
We present a protocol for a species-specific calibration to convert capacitance sensor output to volumetric water content of wood. Also provided are instructions for field installation of capacitance sensors in mature trees and a discussion of the method&#39;s strengths, weaknesses, and assumptions. These techniques are designed to monitor volumetric water content in the trunk, the largest tree water storage reservoir8, but can be easily expanded to the whole tree with installation of additional sensors along the branches. Measurements of dynamic plant water content will advance the fields of vegetation hydrodynamics, biometeorology, and land-surface modeling.

<table><tbody><tr><td>Ruggedized Soil Moisture Sensor</td><td>METER Group Inc.</td><td>GS-3</td><td>Capacitance sensors</td></tr><tr><td>1/8&quot; drill bit</td><td>Any</td><td>N/A</td><td></td></tr><tr><td>9/64&quot; drill bit</td><td>Any</td><td>N/A</td><td></td></tr><tr><td>Drying oven</td><td>Any</td><td>N/A</td><td></td></tr><tr><td>Chainsaw</td><td>Any</td><td>N/A</td><td></td></tr><tr><td>Electric drill</td><td>Any</td><td>N/A</td><td></td></tr><tr><td>Bucket for water bath</td><td>Any</td><td>N/A</td><td></td></tr><tr><td>Alcohol swabs</td><td>Any</td><td>N/A</td><td></td></tr><tr><td>Draw knife</td><td>Any</td><td>N/A</td><td></td></tr><tr><td>Data logger</td><td>Any</td><td>N/A</td><td></td></tr><tr><td>Silicon sealant</td><td>Any</td><td>N/A</td><td></td></tr></tbody></table>

the calibration and use of capacitance sensors to monitor stem water content in trees

Water transport and storage through the soil-plant-atmosphere continuum is critical to the terrestrial water cycle, and has become a major research focus area. Biomass capacitance plays an integral role in the avoidance of hydraulic impairment to transpiration. However, high temporal resolution measurements of dynamic changes in the hydraulic capacitance of large trees are rare. Here, we present procedures for the calibration and use of capacitance sensors, typically used to monitor soil water content, to measure the volumetric water content in trees in the field. Frequency domain reflectometry-style observations are sensitive to the density of the media being studied. Therefore, it is necessary to perform species-specific calibrations to convert from the sensor-reported values of dielectric permittivity to volumetric water content. Calibration is performed on a harvested branch or stem cut into segments that are dried or re-hydrated to produce a full range of water contents used to generate a best-fit regression with sensor observations. Sensors are inserted into calibration segments or installed in trees after pre-drilling holes to a tolerance fit using a fabricated template to ensure proper drill alignment. Special care is taken to ensure that sensor tines make good contact with the surrounding media, while allowing them to be inserted without excessive force. Volumetric water content dynamics observed via the presented methodology align with sap flow measurements recorded using thermal dissipation techniques and environmental forcing data. Biomass water content data can be used to observe the onset of water stress, drought response and recovery, and has the potential to be applied to the calibration and evaluation of new plant-level hydrodynamics models, as well as to the partitioning of remotely sensed moisture products into above- and belowground components.

In this section, we present calibration data for five common eastern forest tree species, followed by a detailed analysis of field measurements of stem-water storage in three Acer rubrum individuals during the 2016 growing season. Calibration curves were generated for Acer rubrum, Betula papyrifera, Pinus strobus, Populus grandidentata, and Quercus rubra (Figure 1). Slopes of the curves differed by as much as 97.7% for P. grandi...

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The Calibration and Use of Capacitance Sensors to Monitor Stem Water Content in Trees

The hydraulic capacitance of biomass is a key component of the vegetation water budget, which serves as a buffer against short and long-term drought stresses. Here, we present a protocol for the calibration and use of soil moisture capacitance sensors to monitor water content in the stems of large trees.

Water transport and storage through the soil-plant-atmosphere continuum is critical to the terrestrial water cycle, and has become a major research focus ...

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12.4K Views.  University of Texas at Austin. The hydraulic capacitance of biomass is a key component of the vegetation water budget, which serves as a buffer against short and long-term drought stresses. Here, we present a protocol for the calibration and use of soil moisture capacitance sensors to monitor water content in the stems of large trees.

Video: The Calibration and Use of Capacitance Sensors to Monitor Stem Water Content in Trees

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A Telemetric, Gravimetric Platform for Real-Time Physiological Phenotyping of Plant&ndash;Environment Interactions

Food security for the growing global population is a major concern. The data provided by genomic tools far exceeds the supply of phenotypic data, creating a knowledge gap. To meet the challenge of improving crops to feed the growing global population, this gap must be bridged.
Physiological traits are considered key functional traits in the context of responsiveness or sensitivity to environmental conditions. Many recently introduced high-throughput (HTP) phenotyping techniques are based on remote sensing or imaging and are capable of directly measuring morphological traits, but measure physiological parameters mainly indirectly.
This paper describes a method for direct physiological phenotyping that has several advantages for the functional phenotyping of plant&#8211;environment interactions. It helps users overcome the many challenges encountered in the use of load-cell gravimetric systems and pot experiments. The suggested techniques will enable users to distinguish between soil weight, plant weight and soil water content, providing a method for the continuous and simultaneous measurement of dynamic soil, plant and atmosphere conditions, alongside the measurement of key physiological traits. This method allows researchers to closely mimic field stress scenarios while taking into consideration the environment&#8217;s effects on the plants&#8217; physiology. This method also minimizes pot effects, which are one of the major problems in pre-field phenotyping. It includes a feed-back fertigation system that enables a truly randomized experimental design at a field-like plant density. This system detects the soil-water-content limiting threshold (&#952;) and allows for the translation of data into knowledge through the use of a real-time analytic tool and an online statistical resource. This method for the rapid and direct measurement of the physiological responses of multiple plants to a dynamic environment has great potential for use in screening for beneficial traits associated with responses to abiotic stress, in the context of pre-field breeding and crop improvement.

A Telemetric, Gravimetric Platform for Real-Time Physiological Phenotyping of Plant&#8211;Environment Interactions

This high-throughput, telemetric, whole-plant water relations gravimetric phenotyping method enables direct and simultaneous real-time measurements, as well as the analysis of multiple yield-related physiological traits involved in dynamic plant&#8211;environment interactions.

Food security for the growing global population is a major concern. The data provided by genomic tools far exceeds the supply of phenotypic data, creating ...

In Situ Soil Moisture Sensors in Undisturbed Soils

Soil moisture directly affects operational hydrology, food security, ecosystem services, and the climate system. However, the adoption of soil moisture data has been slow due to inconsistent data collection, poor standardization, and typically short record duration. Soil moisture, or quantitatively volumetric soil water content (SWC), is measured using buried, in situ sensors that infer SWC from an electromagnetic response. This signal can vary considerably with local site conditions such as clay content and mineralogy, soil salinity or bulk electrical conductivity, and soil temperature; each of these can have varying impacts depending on the sensor technology.
Furthermore, poor soil contact and sensor degradation can affect the quality of these readings over time. Unlike more traditional environmental sensors, there are no accepted standards, maintenance practices, or quality controls for SWC data. As such, SWC is a challenging measurement for many environmental monitoring networks to implement. Here, we attempt to establish a community-based standard of practice for in situ SWC sensors so that future research and applications have consistent guidance on site selection, sensor installation, data interpretation, and long-term maintenance of monitoring stations.
The videography focuses on a multi-agency consensus of best-practices and recommendations for the installation of in situ SWC sensors. This paper presents an overview of this protocol along with the various steps essential for high-quality and long-term SWC data collection. This protocol will be of use to scientists and engineers hoping to deploy a single station or an entire network.

In Situ Soil Moisture Sensors in Undisturbed Soils

The determination of soil water content is a critical mission requirement for many state and federal agencies. This protocol synthesizes multi-agency efforts to measure soil water content using buried in situ sensors.

Soil moisture directly affects operational hydrology, food security, ecosystem services, and the climate system. However, the adoption of soil moisture ...

Protocol for Soil Hydraulic Property Measurement via Evaporation

Measurements of Soil Water Potential and Conductivity based on a Simple Evaporation Experiment using a Hydraulic Property Analyzer

The measurement of soil hydraulic properties is critical in understanding the physical components of soil health as well as integrated knowledge of soil systems under various management practices. Collecting reliable data is imperative for informing decisions that affect agriculture and the environment. The simple evaporation experiment described here uses instrumentation in a laboratory setting to analyze soil samples collected in the field. The soil water tension of the sample is measured by the instrument, and tension data is modeled by software to return soil hydraulic properties. This method can be utilized to measure soil water retention and hydraulic conductivity and give insight into differences in treatments or environmental dynamics over time. Initial establishment requires a user, but data acquisition is automated with the instrument. Soil hydraulic properties are not easily measured with traditional experiments, and this protocol offers a simple and optimal alternative. Interpretation of results and options for extending the data range are discussed.

Author Spotlight: Advancing Agricultural Land Ecosystem Research with a Hydraulic Property Analyzer to Assess Soil Health

This article features a simple evaporation experiment using a hydraulic property instrument for a soil sample. Through efficient means, measurements can be taken over a series of days to generate high-quality data.

The measurement of soil hydraulic properties is critical in understanding the physical components of soil health as well as integrated knowledge of soil ...

Use of Atomic Force Microscopy to Measure Mechanical Properties and Turgor Pressure of Plant Cells and Plant Tissues

We present here the use of atomic force microscopy to indent plant tissues and recover its mechanical properties. Using two different microscopes in indentation mode, we show how to measure an elastic modulus and use it to evaluate cell wall mechanical properties. In addition, we also explain how to evaluate turgor pressure. The main advantages of atomic force microscopy are that it is non-invasive, relatively rapid (5~20 min), and that virtually any type of living plant tissue that is superficially flat can be analyzed without the need for treatment. The resolution can be very good, depending on the tip size and on the number of measurements per unit area. One limitation of this method is that it only gives direct access to the superficial cell layer.

Here, we present atomic force microscopy (AFM), operated as a nano- and micro-indentation tool on cells and tissues. The instrument allows the simultaneous acquisition of 3D surface topography of the sample and its mechanical properties, including cell wall Young's modulus as well as turgor pressure.

We present here the use of atomic force microscopy to indent plant tissues and recover its mechanical properties. Using two different microscopes in ...

Developmental Biology

Measurement of Leaf Hydraulic Conductance and Stomatal Conductance and Their Responses to Irradiance and Dehydration Using the Evaporative Flux Method (EFM)

Water is a key resource, and the plant water transport system sets limits on maximum growth and drought tolerance. When plants open their stomata to achieve a high stomatal conductance (gs) to capture CO2 for photosynthesis, water is lost by transpiration1,2. Water evaporating from the airspaces is replaced from cell walls, in turn drawing water from the xylem of leaf veins, in turn drawing from xylem in the stems and roots. As water is pulled through the system, it experiences hydraulic resistance, creating tension throughout the system and a low leaf water potential (&Psi;leaf). The leaf itself is a critical bottleneck in the whole plant system, accounting for on average 30% of the plant hydraulic resistance3. Leaf hydraulic conductance (Kleaf = 1/ leaf hydraulic resistance) is the ratio of the water flow rate to the water potential gradient across the leaf, and summarizes the behavior of a complex system: water moves through the petiole and through several orders of veins, exits into the bundle sheath and passes through or around mesophyll cells before evaporating into the airspace and being transpired from the stomata. Kleaf is of strong interest as an important physiological trait to compare species, quantifying the effectiveness of the leaf structure and physiology for water transport, and a key variable to investigate for its relationship to variation in structure (e.g., in leaf venation architecture) and its impacts on photosynthetic gas exchange. Further, Kleaf responds strongly to the internal and external leaf environment3. Kleaf can increase dramatically with irradiance apparently due to changes in the expression and activation of aquaporins, the proteins involved in water transport through membranes4, and Kleaf declines strongly during drought, due to cavitation and/or collapse of xylem conduits, and/or loss of permeability in the extra-xylem tissues due to mesophyll and bundle sheath cell shrinkage or aquaporin deactivation5-10. Because Kleaf can constrain gs and photosynthetic rate across species in well watered conditions and during drought, and thus limit whole-plant performance they may possibly determine species distributions especially as droughts increase in frequency and severity11-14.
We present a simple method for simultaneous determination of Kleaf and gs on excised leaves. A transpiring leaf is connected by its petiole to tubing running to a water source on a balance. The loss of water from the balance is recorded to calculate the flow rate through the leaf. When steady state transpiration (E, mmol &bull; m-2 &bull; s-1) is reached, gs is determined by dividing by vapor pressure deficit, and Kleaf by dividing by the water potential driving force determined using a pressure chamber (Kleaf= E /- &Delta;&psi;leaf, MPa)15.
This method can be used to assess Kleaf responses to different irradiances and the vulnerability of Kleaf to dehydration14,16,17.

Measurement of Leaf Hydraulic Conductance and Stomatal Conductance and Their Responses to Irradiance and Dehydration Using the Evaporative Flux Method EFM

We describe a relatively rapid (30 min) and realistic method for simultaneously measurement of leaf hydraulic conductance (Kleaf) and stomatal conductance (gs) for transpiring excised leaves. The method can be modified to measure the light and dehydration responses of Kleaf and gs.

Water is a key resource, and the plant water transport system sets limits on maximum growth and drought tolerance. When plants open their stomata to ...

The Calibration and Use of Capacitance Sensors to Monitor Stem Water Content in Trees

Summary

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A Telemetric, Gravimetric Platform for Real-Time Physiological Phenotyping of Plant–Environment Interactions

In Situ Soil Moisture Sensors in Undisturbed Soils

Measurements of Soil Water Potential and Conductivity based on a Simple Evaporation Experiment using a Hydraulic Property Analyzer

Use of Atomic Force Microscopy to Measure Mechanical Properties and Turgor Pressure of Plant Cells and Plant Tissues

Measurement of Leaf Hydraulic Conductance and Stomatal Conductance and Their Responses to Irradiance and Dehydration Using the Evaporative Flux Method (EFM)