Name: leaf area index estimation using three distinct methods in pure deciduous stands
Uploaded: 2019-08-29T13:00:00
Description: Watch this Scientific Journal Video about Leaf Area Index Estimation Using Three Distinct Methods in Pure Deciduous Stands at JoVE.com

We are indebted to the editorial board of the Journal of Forestry Research for encouraging and authorizing us to use the representative results in this protocol from the article published there. We also kindly thank two anonymous reviewers for their valuable comments, which have substantially improved the manuscript. The research was funded by the Ministry of Agriculture of the Czech Republic, institutional support MZE-RO0118 and the National Agency of Agricultural Research (Project No. QK1810126).

1. LAI estimated using litter traps
<ol>
	<li>First, perform a field survey, investigating the site conditions and structure of the studied stands (i.e., inclination and exposition of the slope, forest or vegetation type, forest or vegetation density, homogeneity of the canopy closure, the crown size, and the crown base height).</li>
	<li>Select a suitable litter trap type for positioning below the canopy by choosing the mesh size of the net based on the size of the assimilation apparatus of the studied stands...

Litter traps are deemed as one of the most accurate methods for performing LAI estimation8, but they are more labor-intensive and time-consuming than the indirect methods35,64 which were incorporated into this protocol. Within the entire LAI estimation procedure using litter traps, a precise estimation of the SLA is the most critical point10 because the SLA can vary with plant species65, date...

LAI, defined as half of the total leaf surface area per unit of horizontal ground surface area1, is a key variable used in many bio-geophysical and chemical exchange models focused on carbon and water fluxes2,3,4. LAI is directly proportional to the active surface of leaves where it drives primary production (photosynthesis), transpiration, energy exchange, and other physiological attributes connected with a range of ecosystem processes in plant communities5.
Numerous approaches and instruments for performing LAI estimation have been developed, and they are currently available on the market6,7,8,9. Ground-based methods for performing LAI estimation can be grouped into two main categories: (i) direct, and (ii) indirect methods10,11,12. The first group includes methods measuring leaf area directly, while the indirect methods infer LAI from measurements of more readily measurable parameters, using radiative transfer theory (in terms of time, labour-intensiveness, and technology)13,14.
This protocol deals with the practical use of litter traps and the needle technique, as non-destructive semi-direct methods10; and the optical device plant canopy analyzer as an indirect method6,7 for performing LAI estimation on a chosen sample from temperate deciduous forest stands in Central Europe (see its structural and dendrometric characteristics in Appendix A and Appendix B).
In deciduous forests and crops, it is possible to perform non-destructive semi-direct LAI estimation using litter traps11 distributed below the canopy layer15. Litter traps provide precise LAI values for deciduous species in which LAI reaches a plateau within the growing season. However, for species that can replace leaves during the growing season, such as poplar, the method overestimates LAI11. This method assumes that the content of the traps represents the average amount of leaves that fall during a leaf-fall period in the stand16, especially during the autumn months. Traps are opened boxes or nets (Figure 1) with a predetermined sufficient size (minimum 0.18 m2, but preferably over 0.25 m2)10,17, lateral sides preventing the wind from blowing leaves into/out of the traps, and with a perforated bottom avoiding decomposition of the leaves; which are located below the canopy layer of the studied stand, however, above the ground surface11. The distribution of the traps can be either random18 or systematic in transects19 or a regular spacing grid20. The number and distribution of traps are a crucial methodological step for performing an accurate LAI estimation reflecting the unique stand structure, spatial homogeneity, expected wind speed and direction, especially in the case of sparse stands (or alleys and orchards), and the work capacity for evaluating data. The precision of LAI estimation increases with the rising frequency of traps within studied stands11,21 (see Figure 2).
The recommended frequency of collecting samples of the litter-fall from each trap is at least monthly10 and even twice per week in periods of heavy fall, which may coincide with heavy rainfall. It is necessary to prevent decomposition of the litter in the traps and the leaching of nutrients from the material during rain episodes in the case of chemical analysis. After collecting leaves in a field, a mixed sub-sample is used for estimating the specific leaf area (SLA, cm2 g-1)22, defined as the fresh projected area of leaves to its dry mass weight ratio. The rest of the collected litter is dried to a constant weight and used for calculating the dry mass of the litter as g cm-2 in the lab. Leaf dry mass on each collection date is converted into the leaf area by multiplying the collected biomass by SLA or leaf dry mass per area (LMA, g cm-2) as the inverse parameter to SLA23,24. A fresh projected area of particular leaves can be determined using a planimetric approach. The planimetric method is based on the dependency between the area of a specific leaf and the area covered by the leaf in the horizontal surface. The leaf is horizontally fixed to the scan screen, and its average is measured using a leaf area meter. Then, its area is calculated. Many leaf area meters based on different measurement principles are available on the market. Some of them include, for instance, the LI-3000C Portable Leaf Area Meter, which uses the orthogonal projection method, and the LI-3100C Area Meter, which measures leaf average using a fluorescent light source and a semi-conducted scanning camera. The next device, the CI-202 portable laser leaf area meter, codes a leaf length using a code reader. Besides them, the AM350 and BSLM101 Portable Leaf Area Meters are also commonly used for performing accurate leaf area estimation.
Furthermore, leaf area meters based on systems that analyze video exist. These leaf area meters consist of a video camera, a digitalisation frame, a screen, and a PC, including suitable software for making the data analysis such as WD3 WinDIAS Leaf Image Analysis System11. Currently, conventional scanners connected to a PC can be used for an estimating leaf area. Afterwards, the leaf area is calculated as a multiple of the number of black pixels and its size depends on the selected resolution (dots per inch &#8211; dpi), or the leaf area is measured through specific software, for instance, WinFOLIA. Finally, the total dry mass of leaves collected within a known ground surface area is converted into the LAI by multiplying by SLA and a shrinkage coefficient25 which reflects the changes in the area of fresh and dried leaves. Shrinkage depends on the tree species, water content and leaf softness. The shrinkage of leaves in length and width (what affect the projected area) is usually up to 10%26, for instance, it ranges from 2.6 to 6.8% for oak27. Sorting leaves by species for weighing and establishing the specific leaf area ratio is necessary to determine the contribution of each species to the total LAI28.
LAI determination by the needle technique is an inexpensive method derived from the inclined point quadrat method29,30,31,32. In deciduous stands, it is an alternative for performing LAI estimation without using traps10 based on the assumption that the total leaf number and their area in a tree are equal to what is collected on the soil surface after a complete leaf-fall20. A thin sharp needle is pierced vertically into the litter lying on the ground immediately after the leaf-fall10. After the complete leaf-fall, the leaves are collected from the ground onto a needle of a vertical probe, are related to the contact number and equal the actual LAI value. An intensive sampling (100-300 sampling points per studied stand per field probe) by the needle technique is required to quantify a mean contact number and to derive the LAI value correctly10,20,33.
The plant canopy analyzer (e.g., LAI-2000 or LAI-2200 PCA) is a commonly used portable instrument for performing an indirect LAI estimation by taking a measurement of the light transmission throughout the canopy7 within the filtered blue portion of the light spectrum (320-490 nm)34,35 to minimize the contribution of the light which has passed through the leaves, was scattered by the canopy and is passing through the foliage7,34. In the blue part of the light spectrum, the maximum contrast between the leaf and sky is achieved, and the foliage appears black against the sky34. Therefore, it is based on the canopy gap fraction analysis7. The instrument has been widely used for making eco-physiological studies in plant communities such as crops36, grasslands37, coniferous stands8, and deciduous stands38. The plant canopy analyzer uses a fisheye optical sensor with a FOV of 148&#176; 35 to project a hemispherical image of the canopy onto silicon detectors to arrange them into five concentric rings39 with central zenith angles of 7&#176;, 23&#176;, 38&#176;, 53&#176;, and 68&#176; 9,40,41. Five view caps (i.e., 270&#176;, 180&#176;, 90&#176;, 45&#176;, and 10&#176;) can be used to restrict the azimuth view of the optical sensor27 to avoid shading by obstacles in an open area (for the above-referenced reading) or the operator in the sensor&#8217;s FOV during LAI estimation can adjust the FOV sensor to an open area for above-canopy readings. Measurements using the plant canopy analyzer are taken above (or in a sufficiently extended open area) and below the studied canopy7. The same view caps must be used for both above and below readings to avoid biases of gap fraction estimation34. The LAI-2000 PCA produces an effective leaf area index (LAIe) as introduced by Chen et al.42, or rather an effective plant area index (PAIe) as woody elements are included in the sensor reading value. In deciduous stands with flat leaves, the LAIe is the same as the hemi-surface LAI. In the case of evergreen forest stands, the LAIe is necessary to correct for the clumping effect at the shoot level (SPAR, STAR)43, the clumping index at scales larger than the shoot (&#937;E)44, and the contribution of woody elements including stems and branches (i.e., woody-to-total area ratio),45 which cause a systematic LAI underestimation20. The clumping index on a higher spatial scale than the shoot or leaf could be quantified as an apparent clumping index (ACF), which can be estimated using the plant canopy analyzer when more restrictive view caps are used27. As these authors state that this ACF is deduced from a ratio of LAI values calculated from transmittance by different procedures for homogeneous and non-homogeneous canopies according to Lang46, we presume that this clumping index describes rather canopy homogeneity. Besides the ACF calculation, new diffuser caps that enable a more extensive application of LAI-2200 PCA in respect of weather conditions, a user menu instead of Fct codes, and the possibility to take many more measurements per file session are among the main technological upgrades compared to the former LAI-2000 PCA34,47. Measurements and subsequent internal software calculations are based on four assumptions: (1) light blocking plant elements including leaves, branches, and stems, are randomly distributed in the canopy, (2) foliage is an optically black body that absorbs all the light it receives, (3) all plant elements are the same projection to the horizontal ground surface as a simple geometric convex shape, (4) plant elements are small compared to the area covered by each ring11.

<table>
	<tbody>
		<tr>
			<td>Area Meter</td>
			<td>LI-COR Biosciences Inc., NE, USA</td>
			<td>LI-3100C</td>
			<td>https://www.licor.com/env/products/leaf_area/LI-3100C/</td>
		</tr>
		<tr>
			<td>Computer Image Analysis System</td>
			<td>Regent Instruments Inc., CA</td>
			<td>WinFOLIA</td>
			<td>http://www.regentinstruments.com/assets/images_winfolia2/WinFOLIA2018-s.pdf</td>
		</tr>
		<tr>
			<td>File Viewer</td>
			<td>LI-COR Biosciences Inc., NE, USA</td>
			<td>FV2200C Software</td>
			<td>https://www.licor.com/env/products/leaf_area/LAI-2200C/software.html</td>
		</tr>
		<tr>
			<td>Laboratory oven</td>
			<td>Amerex Instruments Inc., CA, USA</td>
			<td>CV150</td>
			<td>https://www.labcompare.com/4-Drying-Ovens/2887-IncuMax-Convection-Oven-250L/?pda=4|2887_2_0|||</td>
		</tr>
		<tr>
			<td>Leaf Image Analysis System</td>
			<td>Delta-T Devices, UK</td>
			<td>WD3 WinDIAS</td>
			<td>https://www.delta-t.co.uk/product/wd3/</td>
		</tr>
		<tr>
			<td>Litter traps</td>
			<td>Any</td>
			<td>NA</td>
			<td>See Fig. 2</td>
		</tr>
		<tr>
			<td>Needle</td>
			<td>Any</td>
			<td>NA</td>
			<td>Maximum diameter of 2 mm</td>
		</tr>
		<tr>
			<td>Plant Canopy Analyser</td>
			<td>LI-COR Biosciences Inc., NE, USA</td>
			<td>LAI-2000 PCA</td>
			<td>LAI-2200 PCA or LAI-2200C as improved versions of LAI-2000 PCA can be used, see: https://www.licor.com/env/products/leaf_area/LAI-2200C/</td>
		</tr>
		<tr>
			<td>Portable Laser Leaf Area Meter</td>
			<td>CID Bio-Science, WA, USA</td>
			<td>CI-202</td>
			<td>https://cid-inc.com/plant-science-tools/leaf-area-measurement/ci-202-portable-laser-leaf-area-meter/</td>
		</tr>
		<tr>
			<td>Portable Leaf Area Meter</td>
			<td>ADC, BioScientic Ltd., UK</td>
			<td>AM350</td>
			<td>https://www.adc.co.uk/products/am350-portable-leaf-area-meter/</td>
		</tr>
		<tr>
			<td>Portable Leaf Area Meter</td>
			<td>Bionics Scientific Technogies (P). Ltd., India</td>
			<td>BSLM101</td>
			<td>http://www.bionicsscientific.com/measuring-meters/leaf-area-index-meter.html</td>
		</tr>
		<tr>
			<td>Portable Leaf Area Meter</td>
			<td>LI-COR Biosciences Inc., NE, USA</td>
			<td>LI-3000C</td>
			<td>https://www.licor.com/env/products/leaf_area/LI-3000C/</td>
		</tr>
	</tbody>
</table>

leaf area index estimation using three distinct methods in pure deciduous stands

Accurate estimations of leaf area index (LAI), defined as half of the total leaf surface area per unit of horizontal ground surface area, are crucial for describing the vegetation structure in the fields of ecology, forestry, and agriculture. Therefore, procedures of three commercially used methods (litter traps, needle technique, and a plant canopy analyzer) for performing LAI estimation were presented step-by-step. Specific methodological approaches were compared, and their current advantages, controversies, challenges, and future perspectives were discussed in this protocol. Litter traps are usually deemed as the reference level. Both the needle technique and the plant canopy analyzer (e.g., LAI-2000) frequently underestimate LAI values in comparison with the reference. The needle technique is easy to use in deciduous stands where the litter completely decomposes each year (e.g., oak and beech stands). However, calibration based on litter traps or direct destructive methods is necessary. The plant canopy analyzer is a commonly used device for performing LAI estimation in ecology, forestry, and agriculture, but is subject to potential error due to foliage clumping and the contribution of woody elements in the field of view (FOV) of the sensor. Eliminating these potential error sources was discussed. The plant canopy analyzer is a very suitable device for performing LAI estimations at the high spatial level, observing a seasonal LAI dynamic, and for long-term monitoring of LAI.

Average LAI values at the stand level of all studied stands in the 2013 growing season are presented in Figure 8. On all plots except A, the highest values were measured by litter traps, which serve as the reference level. Contrarily, the highest mean LAI value was estimated through the needle technique on plot A. All differences between LAI values estimated using litter traps and a plant canopy analyzer were not significant (p &#62; 0.05; Figure 8, left). On pl...

Watch this Scientific Journal Video about Leaf Area Index Estimation Using Three Distinct Methods in Pure Deciduous Stands at JoVE.com

Leaf Area Index Estimation Using Three Distinct Methods in Pure Deciduous Stands

An accurate estimation of leaf area index (LAI) is crucial for many models of material and energy fluxes within plant ecosystems and between an ecosystem and the atmospheric boundary layer. Therefore, three methods (litter traps, needle technique, and PCA) for taking precise LAI measurements were in the presented protocol.

Accurate estimations of leaf area index (LAI), defined as half of the total leaf surface area per unit of horizontal ground surface area, are crucial for ...

The leaf area index serves as the interface between leaves and the atmosphere in which many physiological processes are implemented, especially photosynthetic uptake. The main advantages of this method for leaf area index estimation are the straightforward applicability, short measurement time requirements, and the precision of the acquired data. Given that these methods have already been used for ecophysiological studies in crops, grasslands, conifers, and hardwood forest stands, they should be widely applicable to most other plant ecosystems.All of the described methods for leaf area index estimation are straightforward and simple to use. Researchers new to the methods should not encounter difficulties with implementing the measurements. Visual demonstration of these leaf area index estimation methods is essential for their comprehension, design, and implementation.Demonstrating the procedure will be Pavel Haninec, a PhD student from the Department of Forest Botany, Dendrology, and Geobiocoenology. For leaf area index estimation using litter traps, place 15 to 25 traps per investigated stand with a capturing area ranging from 0.18 meters squared up to 0.5 meters squared or more at the beginning of the growing season. Place the traps at regular spacing throughout the studied stand within one or two mutually perpendicular transects or a regular grid, a minimum of 0.1 meter above the ground surface to enable air to blow beneath the collecting part of the traps.Firmly fix each of the traps above the ground surface and below the stand canopy so that there are no changes in the capturing area. At each measurement time point, place the collected litter from each of the traps into appropriately labeled paper bags for transport to the lab. Back at the lab, separate the assimilation apparatus from the other litter components.To perform a specific leaf area estimation, thoroughly mix the sample from each trap before separating a subsample of at least 100 to 200 leaves from all of the used traps. After briefly soaking any dried leaves in 60 to 70 degrees Celsius water to keep the leaves from folding or curling, place the leaves from the subsample in a flat, straight manner onto a scan board without overlapping. Dry the subsample for 48 hours at 80 or 105 degrees Celsius to attain a constant weight in a ventilated oven with a thermostat to homogenize and maintain the internal temperature.At the end of the drying period, weigh the dry mass of the subsample on a lab scale with a minimum degree of accuracy of one gram and calculate the specific leaf area as the fresh projected area of leaves from the subsample designated for the specific leaf area estimation divided by the dry mass weight. Then, oven dry the rest of the sample from each trap for 48 hours at the same temperature that was used for the specific leaf area estimation and multiply the dry mass weight of the rest of the sample for each particular litter trap by the correct specific leaf area value to reach the total projected leaf area index per trap. To estimate the leaf area index using the needle technique, immediately after a complete leaf fall use a sufficiently long, sharp, metallic needle with no more than a two-millimeter diameter to puncture leaves at a more or less similar angle through the layer of freshly fallen leaves lying on the ground surface at each of at least 100 probed sampling points.Check to make sure that only freshly fallen leaves are present on the needle, removing any partially decomposed leaves from the previous year as necessary. Then, count the number of leaves pierced by the needle from each stab at each sampling point before repeating the needle technique leaf collection at subsequent sampling points. For leaf area index estimation using a plant canopy analyzer optical device, locate a suitable open clearing with identical sky conditions as above the observed plot, a maximum distance of one kilometer.Apply the same cap and orientation for both above-and below-canopy readings and slowly move with the sensor below the canopy in transect, watching the variability of the most upper ring readings. Using the same view cap for the both above-and below-canopy readings is necessary for correct leaf area index estimation using a plant canopy analyzer. The number and spacing of the transects depends upon the particular canopy structure of the stand.Perform the above-canopy readings as the first measurement of each stand transect or grid in a sufficient open area and perform the below-canopy readings in one to three transects and between five to 36 sampling points from 0.5 to two meters above the ground. Use the restriction view caps if the sensor is held below two meters to exclude the operator from the field of view and use a minimum distance between the sensor and the nearest element of the aboveground parts of the plant of at least four times the diameter or width of the component. Estimate the woody area index during the leaf-off period, both before bud breaking in early spring and after complete leaf fall in late autumn.To calculate the woody area index values from the field-measured raw data, use the the leaf area index 2200 File Viewer freeware and estimate the plant area index using the same procedure as for making the woody area index estimation. Then calculate the actual leaf area index value at the stand level as the difference between the mean plant area index and woody area index values. In this representative experiment, on Plots B, C, and D, the needle technique significantly underestimated the leaf area index obtained from the litter traps.Conversely, on Plot A, this technique overestimated the leaf area index measured using the litter traps at a not-significant level. Further, significant differences among the leaf area index values estimated by the plant canopy analyzer and the needle technique were found in all cases. The woody area index can be readily measured using a plant canopy analyzer after the complete leaf fall and before bud break.In this representative experiment, the most rapid leaf area index development was noted during the period from bud break occurring in April until the beginning of May. From May until the end of June, a continuation of the fast leaf area index development of leaves was observed, although with a lower intensity compared to the previous period. From the second half of June until the end of July, the leaf area index value declined in Plot B and the stagnation of the leaf area index was more evident during this period on Plot A.In all of the studied forest stands, the leaves started to fall at the end of September, as illustrated by the decrease in the leaf area index curve.The most critical part of the litter trap method is the accurate estimation of the specific leaf area from a sufficiently large subsample of leaves. For the plant canopy analyzer, it is essential to perform the measurements under standard overcast and windless conditions. Digital hemispherical photographs and laser scanning technology can also be used to determine the leaf area index and the spatial distribution of the leaves within the canopy.Currently, the most significant challenge in leaf area index estimation is using remote sensing to determine the foliage quality.

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Understanding the source of pollution in a stream is vital to preserving, restoring, and maintaining the stream&#8217;s function and habitat it provides. Sediments from highly eroding streambanks are a major source of pollution in a stream system and have the potential to jeopardize habitat, infrastructure, and stream function. Watershed management practices throughout the Cleveland Metroparks attempt to locate and inventory the source and rate the risk of potential streambank erosion to assist in formulating effect stream, riparian, and habitat management recommendations. The Bank Erosion Hazard Index (BEHI), developed by David Rosgen of Wildland Hydrology is a fluvial geomorphic assessment procedure used to evaluate the susceptibility of potential streambank erosion based on a combination of several variables that are sensitive to various processes of erosion. This protocol can be time consuming, difficult for non-professionals, and confined to specific geomorphic regions. To address these constraints and assist in maintaining consistency and reducing user bias, modifications to this protocol include a &#8220;Pre-Screening Questionnaire&#8221;, elimination of the Study Bank-Height Ratio metric including the bankfull determination, and an adjusted scoring system. This modified protocol was used to assess several high priority streams within the Cleveland Metroparks. The original BEHI protocol was also used to confirm the results of the modified BEHI protocol. After using the modified assessment in the field, and comparing it to the original BEHI method, the two were found to produce comparable BEHI ratings of the streambanks, while significantly reducing the amount of time and resources needed to complete the modified protocol.

Modifying the Bank Erosion Hazard Index BEHI Protocol for Rapid Assessment of Streambank Erosion in Northeastern Ohio

Streambank erosion potential can be evaluated and ranked using David Rosgen&#8217;s Bank Erosion Hazard Index (BEHI), however this protocol has significant limitations. Here we present protocol modifications to address time constraints, allow nonprofessionals to complete accurate assessments, and account for non-alluvial stream conditions in Northeast Ohio.

Understanding the source of pollution in a stream is vital to preserving, restoring, and maintaining the stream&#8217;s function and habitat it provides. ...

Measuring Rates of Herbicide Metabolism in Dicot Weeds with an Excised Leaf Assay

In order to isolate and accurately determine rates of herbicide metabolism in an obligate-outcrossing dicot weed, waterhemp (Amaranthus tuberculatus), we developed an excised leaf assay combined with a vegetative cloning strategy to normalize herbicide uptake and remove translocation as contributing factors in herbicide-resistant (R) and &#8211;sensitive (S) waterhemp populations. Biokinetic analyses of organic pesticides in plants typically include the determination of uptake, translocation (delivery to the target site), metabolic fate, and interactions with the target site. Herbicide metabolism is an important parameter to measure in herbicide-resistant weeds and herbicide-tolerant crops, and is typically accomplished with whole-plant tests using radiolabeled herbicides. However, one difficulty with interpreting biokinetic parameters derived from whole-plant methods is that translocation is often affected by rates of herbicide metabolism, since polar metabolites are usually not mobile within the plant following herbicide detoxification reactions. Advantages of the protocol described in this manuscript include reproducible, accurate, and rapid determination of herbicide degradation rates in R and S populations, a substantial decrease in the amount of radiolabeled herbicide consumed, a large reduction in radiolabeled plant materials requiring further handling and disposal, and the ability to perform radiolabeled herbicide experiments in the lab or growth chamber instead of a greenhouse. As herbicide resistance continues to develop and spread in dicot weed populations worldwide, the excised leaf assay method developed and described herein will provide an invaluable technique for investigating non-target site-based resistance due to enhanced rates of herbicide metabolism and detoxification.

This manuscript describes how herbicide metabolism rates can be effectively quantified with excised leaves from a dicot weed, thereby reducing variability and removing any possible confounding effects of herbicide uptake or translocation typically observed in whole-plant assays.

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The use of video camera systems in ecological studies of fish continues to gain traction as a viable, non-extractive method of measuring fish lengths and estimating fish abundance. We developed and implemented a rotating stereo-video camera tool that covers a full 360 degrees of sampling, which maximizes sampling effort compared to stationary camera tools. A variety of studies have detailed the ability of static, stereo-camera systems to obtain highly accurate and precise measurements of fish; the focus here was on the development of methodological approaches to quantify fish density using rotating camera systems. The first approach was to develop a modification of the metric MaxN, which typically is a conservative count of the minimum number of fish observed on a given camera survey. We redefine MaxN to be the maximum number of fish observed in any given rotation of the camera system. When precautions are taken to avoid double counting, this method for MaxN may more accurately reflect true abundance than that obtained from a fixed camera. Secondly, because stereo-video allows fish to be mapped in three-dimensional space, precise estimates of the distance-from-camera can be obtained for each fish. By using the 95% percentile of the observed distance from camera to establish species-specific areas surveyed, we account for differences in detectability among species while avoiding diluting density estimates by using the maximum distance a species was observed. Accounting for this range of detectability is critical to accurately estimate fish abundances. This methodology will facilitate the integration of rotating stereo-video tools in both applied science and management contexts.

We describe a new method for counting fishes, and estimating relative abundance (MaxN) and fish density using rotating stereo-video camera systems. We also demonstrate how to use distance from camera (Z distance) to estimate species-specific detectability.

The use of video camera systems in ecological studies of fish continues to gain traction as a viable, non-extractive method of measuring fish lengths and ...

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Specific and Accurate Detection of the Citrus Greening Pathogen Candidatus liberibacter  spp. Using Conventional PCR on Citrus Leaf Tissue Samples

Citrus Greening is a particularly destructive disease affecting citrus crops globally. Presented here is a simple method using PCR and genomic DNA extraction of citrus leaf tissue for the accurate and precise identification of the citrus greening pathogen, Candidatus liberibacter spp.

Citrus greening, also known as huanglongbing, is a destructive citrus disease ravaging citrus farms globally. This disease causes asymmetrical yellow leaf ...

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Bioindication Testing of Stream Environment Suitability for Young Freshwater Pearl Mussels Using In Situ Exposure Methods

In situ bioindications enable determination of the suitability of an environment for endangered mussel species. We describe two methods based on the juvenile exposure of freshwater pearl mussels in cages to oligotrophic river habitats. Both methods are implemented in variants for open water and hyporheic water environments.

Knowledge of habitat suitability for freshwater mussels is an important step in the conservation of this endangered species group. We describe a protocol ...

Protocol for Producing Three-Dimensional Infrared Video of Freezing in Plants

Freezing in plants can be monitored using infrared (IR) thermography, because when water freezes, it gives off heat. However, problems with color contrast make 2-dimensions (2D) infrared images somewhat difficult to interpret. Viewing an IR image or the video of plants freezing in 3 dimensions (3D) would allow a more accurate identification of sites for ice nucleation as well as the progression of freezing. In this paper, we demonstrate a relatively simple means to produce a 3D infrared video of a strawberry plant freezing. Strawberry is an economically important crop that is subjected to unexpected spring freeze events in many areas of the world. An accurate understanding of the freezing in strawberry will provide both breeders and growers with more economical ways to prevent any damage to plants during freezing conditions.
The technique involves a positioning of two IR cameras at slightly different angles to film the strawberry freezing. The two video streams will be precisely synchronized using a screen capture software that records both cameras simultaneously. The recordings will then be imported into the imaging software and processed using an anaglyph technique. Using red-blue glasses, the 3D video will make it easier to determine the precise site of ice nucleation on leaf surfaces.

Here, we present a protocol to image a strawberry plant freezing in 3 dimensions. Two infrared cameras positioned at slightly different angles are used to produce a red-blue anaglyph video to observe the freezing of the plant in 3 dimensions.

Freezing in plants can be monitored using infrared (IR) thermography, because when water freezes, it gives off heat. However, problems with color contrast ...

Characterizing Microbiome Dynamics &#8211; Flow Cytometry Based Workflows from Pure Cultures to Natural Communities

The investigation of pure cultures and monitoring of microbial community dynamics is vital to understand and control natural ecosystems and technical applications driven by microorganisms. Next generation sequencing methods are widely utilized to resolve microbiomes, but they are generally resource and time intensive and deliver mostly qualitative information. Flow cytometric microbiome analysis does not suffer from those disadvantages and can provide relative subcommunity abundances and absolute cell numbers at-line. Although it does not deliver direct phylogenetic information, it can enhance the analysis depth and resolution of sequencing approaches. In sharp contrast to medical applications in both research and routine settings, flow cytometry is still not widely used for microbiome analysis. Missing information on sample preparation and data analysis pipelines may create an entry barrier for the researchers facing microbiome analysis challenges that would often be textbook flow cytometry applications. Here, we present three comprehensive workflows for pure cultures, complex communities in clear medium and complex communities in challenging matrices, respectively. We describe individual sampling and fixation procedures and optimized staining protocols for the respective sample sets. We elaborate the cytometric analysis with a complex research centered and an application focused bench top device, describe the cell sorting procedure and suggest data analysis packages. We furthermore propose important experimental controls and apply the presented workflows to the respective sample sets.

Flow cytometric analysis has proven valuable for investigating pure cultures and monitoring microbial community dynamics. We present three comprehensive workflows, from sampling to data analysis, for pure cultures and complex communities in clear medium as well as in challenging matrices, respectively.

The investigation of pure cultures and monitoring of microbial community dynamics is vital to understand and control natural ecosystems and technical ...

Detached Leaf Assays to Simplify Gene Expression Studies in Potato During Infestation by Chewing Insect Manduca sexta

The multitrophic nature of gene expression studies of insect herbivory demands large numbers of biological replicates, creating the need for simpler, more streamlined herbivory protocols. Perturbations of chewing insects are usually studied in whole plant systems. While this whole organism strategy is popular, it is not necessary if similar observations can be replicated in a single detached leaf. The assumption is that basic elements required for signal transduction are present within the leaf itself. In the case of early events in signal transduction, cells need only to receive the signal from the perturbation and transmit that signal to neighboring cells which are assayed for gene expression.
The proposed method simply changes the timing of the detachment. In whole plant experiments, larvae are confined to a single leaf which is eventually detached from the plant and assayed for gene expression. If the order of excision is reversed, from last in whole plant studies, to first in the detached study, the feeding experiment is simplified.
Solanum tuberosum var. Kennebec is propagated by nodal transfer in a simple tissue culture medium and transferred to soil for further growth if desired. Leaves are excised from the parent plant and relocated to Petri dishes where the feeding assay is conducted with the larval stages of M. sexta. Damaged leaf tissue is assayed for the expression of relatively early events in signal transduction. Gene expression analysis identified infestation-specific Cys2-His2 (C2H2) transcription factors, confirming the success of using detached leaves in early response studies. The method is easier to perform than whole plant infestations and uses less space.

The presented method creates natural herbivore damaged plant tissue through the application of Manduca sexta larvae to detached leaves of potato. The plant tissue is assayed for expression of six transcription factor homologs involved in early responses to insect herbivory.

The multitrophic nature of gene expression studies of insect herbivory demands large numbers of biological replicates, creating the need for simpler, more ...

Estimation of Crystalline Cellulose Content of Plant Biomass using the Updegraff Method

Cellulose is the most abundant polymer on Earth generated by photosynthesis and the main load-bearing component of cell walls. The cell wall plays a significant role in plant growth and development by providing strength, rigidity, rate and direction of cell growth, cell shape maintenance, and protection from biotic and abiotic stressors. The cell wall is primarily composed of cellulose, lignin, hemicellulose and pectin. Recently plant cell walls have been targeted for the second-generation biofuel and bioenergy production. Specifically, the cellulose component of the plant cell wall is used for the production of cellulosic ethanol. Estimation of cellulose content of biomass is critical for fundamental and applied cell wall research. The Updegraff method is simple, robust, and the most widely used method for the estimation of crystalline cellulose content of plant biomass. The alcohol insoluble crude cell wall fraction upon treatment with Updegraff reagent eliminates the hemicellulose and lignin fractions. Later, the Updegraff reagent resistant cellulose fraction is subjected to sulfuric acid treatment to hydrolyze the cellulose homopolymer into monomeric glucose units. A regression line is developed using various concentrations of glucose and used to estimate the amount of the glucose released upon cellulose hydrolysis in the experimental samples. Finally, the cellulose content is estimated based on the amount of glucose monomers by colorimetric anthrone assay.

The Updegraff method is the most widely used method for the cellulose estimation. The main purpose of this demonstration is to provide a detailed Updegraff protocol for estimation of cellulose content in plant biomass samples.

Cellulose is the most abundant polymer on Earth generated by photosynthesis and the main load-bearing component of cell walls. The cell wall plays a ...

Extraction of Cofactor F420 for Analysis of Polyglutamate Tail Length from Methanogenic Pure Cultures and Environmental Samples

The cofactor F420 plays a central role as a hydride carrier in the primary and secondary metabolism of many bacterial and archaeal taxa. The cofactor is best known for its role in methanogenesis, where it facilitates thermodynamically difficult reactions. As the polyglutamate tail varies in length between different organisms, length profile analyses might be a powerful tool for distinguishing and characterizing different groups and pathways in various habitats. Here, the protocol describes the extraction and optimization of cofactor F420 detection by applying solid-phase extraction combined with high-performance liquid chromatography analysis independent of cultural or molecular biological approaches. The method was applied to gain additional information on the expression of cofactor F420 from microbial communities in soils, anaerobic sludge, and pure cultures and was evaluated by spiking experiments. Thereby, the study succeeded in generating different F420 tail-length profiles for hydrogenotrophic and acetoclastic methanogens in controlled methanogenic pure cultures as well as from environmental samples such as anaerobic digester sludge and soils.

Extraction of Cofactor F420 for Analysis of Polyglutamate Tail Length from Methanogenic Pure Cultures and Environmental Samples

A method for the extraction of cofactor F420 from pure cultures was optimized for the liquid chromatographic separation and analysis of F420 tail length in pure culture and environmental samples.

The cofactor F420 plays a central role as a hydride carrier in the primary and secondary metabolism of many bacterial and archaeal taxa. The cofactor is ...