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3,682 results for “ROOTS”
Patterns of root biomass, productivity, and turnover in riverine and scrub mangroves post-Hurricane Wilma in the Everglades, Florida, USA, 2012-2013
Mangrove root biomass, productivity, and turnover in the shallow (0-45 cm depth) root zone were estimated at Florida Coastal Everglades Long Term Ecological Research (FCE-LTER) Program Shark River (SRS4, SRS5, SRS6) and Taylor River (TS/Ph6b, TS/Ph7b) mangrove sites during 2012-2013 following Hurricane Wilma’s impacts in October 2005. Root biomass was estimated at all sites in May 2012 with a PVC coring device (10.2 cm diameter x 45 cm length) using the same sampling protocol previously published for the study area (Castañeda-Moya et al. 2011). After collection, root cores were processed individually and initially rinsed with water through a 1-mm screen mesh to remove soil particles. Live roots were separated manually based on their buoyancy, turgor, and color (Castañeda-Moya et al. 2011; Cormier et al. 2015; Medina-Calderon et al. 2021). Live roots were further sorted into three size diameter classes including fine (<2 mm), small (2-5 mm), and coarse (5-20 mm). Roots greater than 20 mm in diameter were not included in this study due to sampling limitations (i.e., core area). All root samples were oven-dried at 60°C to a constant mass and weighed to estimate root biomass (g m-2). Root productivity was estimated with the ingrowth core technique (Vogt et al., 1998) using the same sampling protocol previously published for the study area (Castañeda-Moya et al. 2011). Ingrowth cores (10.2 cm diameter x 45 cm length) were made of synthetic material (3 mm mesh) and filled with root-free commercial sphagnum peat moss. This material has similar soil properties (i.e., bulk density, organic matter content, total C and N) as mangrove peat in our study sites. Ingrowth cores were installed in each of the cored holes formed during sampling of root biomass. At each site, ingrowth cores were deployed vertically into the soil to a depth of 45 cm and retrieved one year later (June 2013). Root growth within the ingrowth core was used to estimate annual root production (g m-2 yr-1) in
Root Decomposition and root in-growth rates for GCE marsh sites 6-9 from June 2003 to June 2004
Rates of decomposition and root in-growth were measured in four tidal marshes of the Georgia coast (USA) that vary in freshwater input. Replicate nylon mesh bags containing roots of dominant plant species were buried 20cm deep in marsh sediments at stream-side levee and marsh plain locations within GCE sampling sites 6, 7, 8 and 9 in June 2003. Dry weight, carbon, nitrogen and phosphorus content, and root in-growth were measured initially and every three months to evaluate the effects of freshwater input on root decomposition and growth rates. This study was part of the GCE-LTER soil monitoring program.
Climate Change Across Seasons Experiment (CCASE) at the Hubbard Brook Experimental Fine Root Damage
Root damage, as relative electrolyte leakage, was assessed following winter freeze-thaw cycle experimental treatments in 2014 and 2015 on all Climate Change Across Seasons Experiment (CCASE) plots. Reference (or control) plots are shared with the collaborating Northern Forest DroughtNet experiment. There are six plots total (each 11 x 14m). Two are warmed 5 degrees C throughout the growing season (Plots 3 and 4). Two others are warmed 5 degrees C in the growing season and have snow removed during winter to induce soil freeze/thaw cycles (Plots 5 and 6). Four kilometers (2.5 mi) of heating cable are buried in the soil to warm these four plots. Two additional plots serve as controls for our experiment (Plots 1 and 2). Analysis and results from these data are presented in Sanders-DeMott 2018. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station. Sanders-DeMott, R., Sorensen, P.O., Reinmann, A.B. et al. Growing season warming and winter freeze–thaw cycles reduce root nitrogen uptake capacity and increase soil solution nitrogen in a northern forest ecosystem. Biogeochemistry 137, 337–349 (2018). https://doi.org/10.1007/s10533-018-0422-5
Climate Change Across Seasons Experiment (CCASE) at the Hubbard Brook Experimental Root Nitrogen Uptake Capacity
Fine root nitrogen uptake capacity was measured on excised roots prior to experimental treatment in 2013 and throughout the growing seasons of 2014 and 2015 on all Climate Change Across Seasons Experiment (CCASE) plots. Reference (or control) plots are shared with the collaborating Northern Forest DroughtNet experiment. There are six plots total (each 11 x 14m). Two are warmed 5 degrees C throughout the growing season (Plots 3 and 4). Two others are warmed 5 degrees C in the growing season and have snow removed during winter to induce soil freeze/thaw cycles (Plots 5 and 6). Four kilometers (2.5 mi) of heating cable are buried in the soil to warm these four plots. Two additional plots serve as controls for our experiment (Plots 1 and 2). Analysis and results from these data are presented in Sanders-DeMott 2018. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station. Sanders-DeMott, R., Sorensen, P.O., Reinmann, A.B. et al. Growing season warming and winter freeze–thaw cycles reduce root nitrogen uptake capacity and increase soil solution nitrogen in a northern forest ecosystem. Biogeochemistry 137, 337–349 (2018). https://doi.org/10.1007/s10533-018-0422-5
Multiple Element Limitation in Northern Hardwood Ecosystems (MELNHE): Root biomass and growth responses to nitrogen and phosphorus
The Multiple Element Limitation in Northern Hardwood Ecosystems (MELNHE) project studies N , P, and Ca acquisition and limitation of forest productivity through a series of nutrient manipulations in northern hardwood forests. This data set includes data testing effects of elevated N and P availability on fine root growth (using ingrowth cores) and biomass in the MELNHE project. Subsets of ingrowth cores were treated with nutrients differing from the plot-scale nutrient treatments to test fine root foraging. Additional detail on the MELNHE project, including a datatable of site descriptions and a pdf file with the project description and diagram of plot configuration can be found in this data package: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-hbr&identifier=344 These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station.
Effects of microarthropod exclusion and water amendments on fluffgrass growth, root nitrogen, and mite and nematode abundance at the Jornada Basin LTER site, 1986-1987
This data package contains data on microarthropods, nematodes, fluff-grass (Dasyochloa pulchella) growth, and root nitrogen in samples from study plots sampled approximately monthly between May 1986 and August 1987 at the Jornada Basin LTER site in southern New Mexico USA. The purpose of this study was to test how watering, and changing densities of soil microarthropods and nematodes, results in changes in fluff grass growth and root nitrogen. Twenty 6 x 6 m plots were established with a 3 m buffer between plots. Five plots were randomly assigned to one of four treatments: 1) Chlordane to exclude microarthropods, 2) Chlordane and water, 3) Water, and 4) Control. At monthly intervals, randomly selected fluff grass plants were collected from each plot. This data set consists of plant diameters (cm), mite soil weight (g), root weight (g), nematode soil weight (g), root total nitrogen (mg/g), and nematode number. This study was completed in November 1987.
Nitrate, ammonium, and water content of mesquite root tube soil from three habitats at the Jornada Basin LTER site, 1987
This data package contains data on measured root tube soil nutrients from soil cores collected under mesquite (Prosopis glandulosa)at three habitat types of the Jornada Experimental Range and New Mexico State University College Ranch. These habitat types include: 1)playa, 2)dunes, and (4)grassland. Soil core samples were collected in 1987 by hand-augering a reference core and a root tube core. Subsamples were analyzed for nitrate, ammonium, and soil moisture contents. This data set consists of the date of collection, collection site, nitrate concentration, ammonium concentration, and percent soil moisture. Collected variables also include treatments (irradiation and nematicide) that are not well-documented at this time. Data collection was completed in 1987.
WAT04 Root decomposition and nutrient dynamics are resistant to rainfall legacies in tallgrass prairie
Purpose: Litter decomposition is an important component of carbon (C) and nitrogen (N) cycling, and rates of mass loss and nutrient release are sensitive to current climate conditions. Growing evidence suggests that past climate conditions can exert legacies on soil C and N cycling, but little is known about how belowground decomposition dynamics relate to these climate legacies. Results: Root litter mass loss was resistant to most climate treatments. Contrary to expectations, decomposition rates were slowest in plots with a history of long-term irrigation and fastest under drought in lowland prairie. Similarly, mass loss rates were overall faster in the drier uplands. Changes in N concentration as a function of mass loss were similar across treatments and patterns of litter N release largely tracked mass loss. Conclusions: Changes in the decomposer community with long-term release from water stress may have led to slowed root decomposition, but these effects were subtle. Our results suggest that changes in decomposition rates are not a cause of observed climate legacy effects on C and N cycling in prairies.
PRW01 Fine root density and turnover based on root window observations
Eight root windows (40cm x 40cm) were used to measure fine root production and decay over three years in a 2 factor-factorial experiment (Burning, Mowing). Root lengths were traced every two weeks during the growing season. Production, disappearance and standing crops (lengths) were calculated by 10 cm increments.
Krummholz island soil N and root ingrowth data for East of Tvan, 1996 - 1997.
Previous work has shown that passage of Engelmann spruce (Picea engelmannii) and subalpine fir (Abies lasiocarpa) tree islands across tundra lowers the soil carbon and nitrogen storage capacity of the top 15cm of soil (A horizon) (Pauker and Seastedt 1996). The presence of tree islands (krummholz) on the tundra acts as a 'snowfence' causing snow to drift within the krummholz and in a semi-circular area leeward of the krummholz. This drifting causes soil within and leeward of the krummholz to have a much deeper, more consistent and longer lasting snow-cover than the adjacent tundra soils. The snowdrifts form a permanent cover over the leeward and krummholz sites from November through June, helping to insulate the soils beneath from the extreme low temperatures and supplying significantly more meltwater in the spring. In contrast, high winds cause the adjacent tundra to be free from snow and exposed to extremely cold temperatures for much of the winter. Studies have shown that atmospheric nitrogen deposition accumulates on snowpacks throughout the winter months and that this is released as a 'pulse' of nitrogen ions at snowmelt (Williams et al. 1996). We hypothesized that accumulation of snowpacks in krummholz and leeward sites may alter nitrogen dynamics in these areas relative to tundra, by either (a) affecting microbial activity via its insulating effect or (b) accumulating large amounts of atmospherically deposited N and releasing it as a pulse at snowmelt. This study sought to examine the nitrogen inputs into tundra, krummholz, and leeward soils over an entire winter season (using buried ion exchange resin bags which collect ions percolating down at snowmelt and early spring rains) and over a short period in spring, immediately following snowmelt (using microlysimeters to collect soil water over a 24 hour period). Belowground NPP (determined from root ingrowth cores) and d13C values of tundra and krummholz vegetation are also presented in this file. NH4+ and NO3-
Root endophyte colonization in the black sand extended growing season experiment for Audubon, Lefty, East Knoll and Trough sites, 2023.
This dataset contains detailed microscopy-based observations of root colonization by three major fungal guilds—arbuscular mycorrhizal fungi (AMF), dark septate endophytes (DSE), and fine root endophytes (FRE)—across multiple alpine plant species sampled from experimental black sand (early snowmelt) plots in the Rocky Mountains. Root samples were collected from plots subjected to different snowmelt timing treatments ("Early" and "Control") using black sand to cause early snowmelt to investigate the effects of phenological shifts in plants on fungal colonization. Each sample includes metadata on collection date, field location, plant species, and staining/scoring logistics, as well as quantified colonization metrics such as hyphae, arbuscules, vesicles, and other fungal structures. This dataset supports ongoing research into how alpine plant–fungal interactions respond to changing environmental conditions and may help identify shifts in mutualistic and non-mutualistic associations under climate-altered snowmelt regimes.
Fine root biomass and N content data for Saddle, South of saddle, North of saddle, 1994.
Root production was estimated in dry, moist, and wet meadow communities on Niwot Ridge using a root-ingrowth core method. Columns of root-free soil were established on 1 June 1994 and were re-cored on 10 August and 23 September 1994 for measurement of fine root mass and nitrogen content.
Visualization of Marsh Grass Roots and Rhizomes by CT imaging: VCR salt marshes, summer 2012
Computer-aided tomography and image processing previously has been used to accurately and rapidly quantify coarse root mass in coastal wetlands (Davey et al. 2011. Ecological Applications). The data in this data base are being used to develop the technique to allow for resolution of fine roots. The contribution of Spartina alterniflora roots-and-rhizomes (hereafter, roots) to soil volume is measured in VCR mainland marsh soils. Soil cores were collected several different marshes with differing soil types (mineral vs peaty). The cores were scanned by computer-aided tomography and image processing was used to determine the volume of living roots. Our results show that CT imaging may also be used to quantify coarse and fine root volume in salt marsh soils and that in peaty soils, coarse roots make an important contribution to soil volume (up to 53% of the soil volume is live roots). The dataset includes an extensive manual of methods, along with instructional videos.
Raw data used in Kumar et al. 2020: Barley shoot biomass responds strongly to N:P stoichiometry and intraspecific competition, whereas roots only alter their foraging
<p>Raw data used in Kumar et al. 2020: Barley shoot biomass responds strongly to N:P stoichiometry and intraspecific competition, whereas roots only alter their foraging</p>
Fig. 1 in Lysinimonas yzui sp. nov., isolated from cattail root soil from mine tailings
Fig. 1. Neighbour-joining phylogenetic tree based on 16S rRNA gene sequences, showing positions of N7XX-4T and related taxa within the family Microbacteriaceae. Bootstrap values of over 60% (based on 1000 replicates) are shown at branching points. Dots indicate that the corresponding branches were also recovered in the maximum parsimony tree. Bar, 0.01 substitutions per nucleotide.
Generalized linear model with elastic net regularization and convolutional neural network for evaluating Aphanomyces root rot severity in lentil
<p>Red-Green-Blue (RGB) imaging was used to evaluate Aphanomyces root rot in 547 lentil accessions and lines. The root images were pre-processed by removing image background. This dataset (6,460 root images) was used to build two machine learning models — generalized linear model with elastic net regularization and convolutional neural network— to classify root images into three classes. Details about the methodology and results are described in Marzougui et al. (2020, Plant Phenomics).</p> <p>The excel file includes Aphanomyces root rot disease visual scores (<em>Root_Rating</em>), unique identifier for each lentil accession/line (<em>Lentil_ID</em>), unique identifier for each experiment (<em>Experiment</em>), and unique identifier for each image (<em>Lab_ID</em>).</p>
Accounting for environmental variation in co‐occurrence modelling reveals the importance of positive interactions in root‐associated fungal communities
<p>Understanding the role of interspecific interactions in shaping ecological communities is one of the central goals in community ecology. In fungal communities, measuring interspecific interactions directly is challenging because these communities are composed of large numbers of species, many of which are unculturable. An indirect way of assessing the role of interspecific interactions in determining community structure is to identify the species co-occurrences that are not constrained by the environmental conditions. In this study, we investigated co-occurrences among root-associated fungi, asking whether fungi co-occur more or less strongly than expected based on the environmental conditions and the host plant species examined. For this purpose, we generated molecular data on root-associated fungi of five plant species evenly sampled along an elevational gradient at a high Arctic site. We analysed the data using a joint species distribution modelling approach that allowed us to identify those co-occurrences that could be explained by the environmental conditions and the host plant species, as well as those co-occurrences that remained unexplained and thus more likely reflect interactive associations. Our results indicate that positive interactions play an important role in shaping microbial communities in arctic plant roots. In particular, we found that mycorrhizal fungi are especially prone to positively co-occur with other fungal species. Our results bring new understanding to the structure of arctic interaction networks by suggesting that interactions among root-associated fungi are predominantly positive.</p>
Can root-associated fungi mediate the impact of abiotic conditions on the growth of a High Arctic herb?
<p>This is a dataset containing fragments of internal transcribed spacer 2 (ITS2) extracted from <em>Bistorta vivipara</em> root-associated fungi, sampled from snow fence experiment in Adventdalen, Svalbard. </p> <p>This dataset was used in Wutkowska et al., 2020, Can root-associated fungi mediate the impact of abiotic conditions on the growth of a High Arctic herb?Can root-associated fungi mediate the impact of abiotic conditions on the growth of a High Arctic herb? [available at biorXiv.org, DOI: 10.1101/2020.06.20.157099]</p> <p>Now the manuscript is available as a peer-reviewed paper:</p> <p>Wutkowska, Magdalena, Dorothee Ehrich, Sunil Mundra, Anna Vader, and Pernille Bronken Eidesen. 2021. ‘Can Root-Associated Fungi Mediate the Impact of Abiotic Conditions on the Growth of a High Arctic Herb?’ <em>Soil Biology and Biochemistry</em> 159:108284. doi: 10.1016/j.soilbio.2021.108284.</p> <p> </p> <p>All other corresponding data are available here: https://github.com/magdawutkowska/bistorta</p>
Root multiple ion uptake kinetics data for maize NAM founders, statistical code, and RhizoFlux hardware plans
<p>This repository contains tabular data, R statistical code, protocols, and hardware plans associated with the following manuscript:</p> <p><strong>A multiple ion-uptake phenotyping platform reveals shared mechanisms that affect nutrient uptake by maize roots</strong></p> <p>Marcus Griffiths, Sonali Roy, Haichao Guo, Anand Seethepalli, David Huhman, Yaxin Ge, Robert E. Sharp, Felix B. Fritschi, Larry M. York</p> <p>Plant Physiology; doi: <a href="https://doi.org/10.1093/plphys/kiaa080">https://doi.org/10.1093/plphys/kiaa080</a></p> <p><strong>Equipment designs.zip</strong> - Contains the hardware plans, parts lists, and experimental protocol</p> <p><strong>ImageJ_macro.zip</strong> - Contains scripts to use within ImageJ to segment images to calculate leaf area</p> <p><strong>Supplementary_Data.zip</strong> - Contains the actual supplemental figures and tables for the manuscript as well as RNAseq data</p> <p><strong>R code & raw data.zip</strong> - Contains a single .R text file containing all the R code to generate all the figures and and supplemental figures from the include raw data files</p> <p>E-mail mgriffiths at danforthcenter.org or lmyork at noble.org with any questions.</p> <p>Version 1 was used for the preprint.</p> <p>Version 2 was used for the final submitted manuscript.</p> <p>Version 3 is the final published version.</p>
Root phenotyping data
<p>Dataset presenting the root phenotyping analysis performed in the paper:</p> <blockquote> <p>Bouché F, D’Aloia M, Tocquin P, Lobet G, Detry N, Périlleux C. 2016. Integrating roots into a whole plant network of flowering time genes in Arabidopsis thaliana. Scientific Reports.</p> </blockquote> <p>The dataset contains:</p> <p>- <strong>01-raw_images.zip</strong>: the orignal images of the petri dishes used for the analysis. The scale is 370 DPI</p> <p>- <strong>02-processed_images.zip</strong>: images enhanced, cropped and renamed for the analysis. Analysis was performed using SmartRoot (Lobet et al. 2011). Each image has its corresponding RSML file containing the root architecture data. </p> <p>- <strong>plate_image_treatment.ijm</strong>: ImageJ macro for a pre-processing of the images, before the SmartRoot analysis </p> <p>- <strong>root_architecture_analysis.R</strong>: R script used for the architecture data analysis</p> <p>- <strong>root_architecture_data.csv</strong> : architecture data exported from SmartRoot.</p> <p>- <strong>images.zip</strong>: the plots generated using the R script</p> <p> </p>
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