description: ABSTRACT: The goal of this study was to predict the global distribution of plant rooting depths based on data about global aboveground vegetation structure and climate. Vertical root distributions influence the fluxes of water, carbon, and soil nutrients and the distribution and activities of soil fauna. Roots transport nutrients and water upwards, but they are also pathways for carbon and nutrient transport into deeper soil layers and for deep water infiltration. Roots also affect the weathering rates of soil minerals. For calculating such processes on a global scale, data on vertical root distributions are needed as inputs to global biogeochemistry and vegetation models. In the Project for Intercomparison of Land Surface Parameterization Schemes (PILPS), rooting depth and vertical soil characteristics were the most important factors explaining scatter for simulated transpiration among 14 land-surface models. Recently, the Terrestrial Observation Panel for Climate of the Global Climate Observation System (GCOS) identified the 95% rooting depth as a key variable needed to quantify the interactions between the climate, soil, and plants, stating that the main challenge was to find the correlation between rooting depth and soil and climate features (GCOS/GTOS Terrestrial Observation Panel for Climate 1997). In response to this challenge, a data set of vertical rooting depths was collected from the literature in order to construct maps of global ecosystem rooting depths.The parameters included in these data sets are estimates for the soil depths containing 50% and 95% of all roots, termed 50% and 95% rooting depths (D50 and D95, respectively). Together, these variables can be used to calculate estimates for vertical root distributions, using a logistic equation provided in this documentation. The data represent mean ecosystem rooting depths for 1 by 1 degree grid cells. Related data sets: The ORNL DAAC offers related data sets by Jackson et al. (2003), Gordon and Jackson (2003), Schenk and Jackson (2003), and Gill and Jackson (2003).This data set is one of the products of the International Satellite Land-Surface Climatology Project, Initiative II (ISLSCP II) data collection which contains 50 global time series data sets for the ten-year period 1986 to 1995. Selected data sets span even longer periods. ISLSCP II is a consistent collection of data sets that were compiled from existing data sources and algorithms, and were designed to satisfy the needs of modelers and investigators of the global carbon, water and energy cycle. The data were acquired from a number of U.S. and international agencies, universities, and institutions. The global data sets were mapped at consistent spatial (1, 0.5 and 0.25 degrees) and temporal (monthly, with meteorological data at finer (e.g., 3-hour)) resolutions and reformatted into a common ASCII format. The data and documentation have undergone two peer reviews.ISLSCP is one of several projects of Global Energy and Water Cycle Experiment (GEWEX) [http://www.gewex.org/] and has the lead role in addressing land-atmosphere interactions -- process modeling, data retrieval algorithms, field experiment design and execution, and the development of global data sets.; abstract: ABSTRACT: The goal of this study was to predict the global distribution of plant rooting depths based on data about global aboveground vegetation structure and climate. Vertical root distributions influence the fluxes of water, carbon, and soil nutrients and the distribution and activities of soil fauna. Roots transport nutrients and water upwards, but they are also pathways for carbon and nutrient transport into deeper soil layers and for deep water infiltration. Roots also affect the weathering rates of soil minerals. For calculating such processes on a global scale, data on vertical root distributions are needed as inputs to global biogeochemistry and vegetation models. In the Project for Intercomparison of Land Surface Parameterization Schemes (PILPS), rooting depth and vertical soil characteristics were the most important factors explaining scatter for simulated transpiration among 14 land-surface models. Recently, the Terrestrial Observation Panel for Climate of the Global Climate Observation System (GCOS) identified the 95% rooting depth as a key variable needed to quantify the interactions between the climate, soil, and plants, stating that the main challenge was to find the correlation between rooting depth and soil and climate features (GCOS/GTOS Terrestrial Observation Panel for Climate 1997). In response to this challenge, a data set of vertical rooting depths was collected from the literature in order to construct maps of global ecosystem rooting depths.The parameters included in these data sets are estimates for the soil depths containing 50% and 95% of all roots, termed 50% and 95% rooting depths (D50 and D95, respectively). Together, these variables can be used to calculate estimates for vertical root distributions, using a logistic equation provided in this documentation. The data represent mean ecosystem rooting depths for 1 by 1 degree grid cells. Related data sets: The ORNL DAAC offers related data sets by Jackson et al. (2003), Gordon and Jackson (2003), Schenk and Jackson (2003), and Gill and Jackson (2003).This data set is one of the products of the International Satellite Land-Surface Climatology Project, Initiative II (ISLSCP II) data collection which contains 50 global time series data sets for the ten-year period 1986 to 1995. Selected data sets span even longer periods. ISLSCP II is a consistent collection of data sets that were compiled from existing data sources and algorithms, and were designed to satisfy the needs of modelers and investigators of the global carbon, water and energy cycle. The data were acquired from a number of U.S. and international agencies, universities, and institutions. The global data sets were mapped at consistent spatial (1, 0.5 and 0.25 degrees) and temporal (monthly, with meteorological data at finer (e.g., 3-hour)) resolutions and reformatted into a common ASCII format. The data and documentation have undergone two peer reviews.ISLSCP is one of several projects of Global Energy and Water Cycle Experiment (GEWEX) [http://www.gewex.org/] and has the lead role in addressing land-atmosphere interactions -- process modeling, data retrieval algorithms, field experiment design and execution, and the development of global data sets.

The global effective plant rooting depth (unit: meter) datasets contains a climatological map of mean effective plant rooting depth over 1982-2010 at 0.5 degree spatial resolution based on Guswa's Carbon Cost-Benefit model. A detailed description of the method, input data and hydrological validation of the effectiveness of the estimated rooting depth can be found in Yang et al. (2016).

Reference: Guswa, A.J. (2008), The influence of climate on root depth: A carbon cost-benefit analysis, Water Resources Research, 44(2), W02427, doi: 10.1029/2007WR006384.

Yang, Y.T., Donohue, R.J., McVicar, T.R. (2016), Global estimation of effective plant rooting depth: Implication for hydrological modelling, Water Resource Research, In press.

The data collection contains 171 root samples, where the root mass, the root length and the root depth are given. Furthermore, the database contains the main environmental parameters that influence rooting (climate, land use, soil, vegetation composition). The rooting data are provided separately for three root categories: (1) very fine roots (diameter between 0 - 1 mm), (2) fine roots (diameter between 1 - 5 mm), and (3) coarse roots (diameter between 5 - 20 mm). Roots of woody species with a diameter larger than 20 mm were not considered, as the distribution and diameter of coarse roots (especially trees) in the soil vary greatly spatially. The rooting samples were taken between 1994 and 2017 in the most widespread vegetation communities and land-use types in 13 Alpine study sites along a north-south transect from Tyrol (Austria) via South Tyrol to Trentino (both in Italy). 15 samples were taken from arable land, 56 samples from intensively used hay meadows, 15 samples from extensively managed hay meadows, 16 samples from lightly stocked pastures, 32 samples from agriculturally unused grasslands, and 37 samples from forests. The roots were collected with core samplers of 6.8–7.7 cm diameter and a maximum core depth of 70 cm. In the laboratory, the soil cores were split into the O-horizon (if present) and mineral soil layers of various thicknesses (0–3 cm, 3–8 cm, 8–13 cm, 13–23 cm, 23–38 cm, 38–53 cm, and >53 cm). Root extraction was performed manually with the roots cleared of soil in sieving cascades under running water. The root mass was weighed and based on the mass, the root length and root depth distribution were determined according to the method of Tasser et al. (2005). As environmental parameters 79 potential impact variables on rooting, including 19 site variables, six land-use variables and 53 vegetation variables, are present in the database. The vegetation variables are based on vegetation relevées after Braun-Blanquet, in whose center the root samples were taken. Meteorological parameters were measured in the most study sites at a distance of < 150 m from the rooting samples using different microclimate stations. For detailed soil characterization, soil profiles were investigated directly at the sample site or at a representative site with the same land-use type and identical plant communities in the immediate vicinity (<50 m distance). For all soil samples, we analyzed pore size distribution, soil bulk density, soil particle density, total soil porosity, soil texture, and soil organic C and pH. Furthermore, we calculated mean Ellenberg's indicator values (EIV) for temperature (T), moisture (F), soil reaction (R) and soil productivity or fertility (N) for all study sites. Past and present management practices at the study sites were recorded by interviewing landowners.

No description is available. Visit https://dataone.org/datasets/ess-dive-3e3ca22cd60ddff-20250328T165904713 for complete metadata about this dataset.

Rooting depths were estimated from a global database of root profiles that was assembled from the primary literature to study relationships of abiotic and biotic factors associated with belowground vegetation structure. Variables used to characterize belowground vegetation structure include the depths above which 50% of all roots and 95% of all roots are located in the profile. For each root profile, information recorded includes latitude and longitude, elevation, soil texture, depth of organic horizons, type of roots measured (e.g., fine or total, live or dead), sampling methods, units of measurements (root mass, length, number, surface area), and sampling depth.

A database of vertical root profiles for global terrestrial ecosystems was assembled from the primary literature in order to characterize the belowground structure of global vegetation types and to study relationships of belowground vegetation structure with climate, soil characteristics, and aboveground vegetation structure.

Variables used to characterize belowground vegetation structure include the depth above which 50 percent of all roots are located and the depth above which 95 percent of all roots are located in the profile. For each root profile, information recorded includes latitude and longitude, elevation, soil texture, depth of organic horizons, type of roots measured (e.g., fine or total, live or dead), sampling methods, units of measurements (root mass, length, number, surface area), and sampling depth. Some profiles lack information on one or more of these variables. Also recorded are presence and dominance of plant life forms (including succulents, forbs, grasses, semi-shrubs, shrubs, and four categories of trees: needle-leaved vs. broadleaved, evergreen vs. deciduous) and whether the vegetation was relatively natural or altered by humans (e.g., forest plantations and pastures). The database also includes data on mean annual precipitation and the seasonal distribution of precipitation.

Data sets that are related to this root profile data set include root nutrient concentrations (for approximately 372 site-pit-depths from 56 papers in Gordon and Jackson 2000) and root turnover rates (data for approximately 188 sites from 152 papers that were used to estimate root turnover rates for 341 site-vegetation combinations in Gill and Jackson 2000). The three recent papers include most of the data contained in the initial root data set; however, some observations may have been excluded because of more stringent selection criteria. Many of the source papers provided data for all three of the rooting data sets and users are encouraged to review all three data sets.

The Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC) for Biogeochemistry Dynamics organized and formatted these data for long-term archive. The archived data are contained in two files: (1) The ecosystem root profiles file, containing estimated 50 percent rooting depths (D50) and 95 percent rooting depths (D95) plus information on sampling methods, vegetation, climate, and soil, and (2) a file containing the references to file (1). These files were obtained from H. Jochen Schenk, Department of Biological Science, California State University Fullerton, California, in February 2003. The data were placed into a spreadsheet format and stored as an ASCII comma-separated (.csv) file. Missing values are represented by -999.

The root shoot database is a collection of literature data gathered over the space of a year covering studies up until the end of 2022. The primary driver for the development of the root shoot database was to provide root and shoot estimates for key European crops. The specific criteria for a study to be included in the data base are the following: Overall criteria for a study to qualify: 1) Contain root and shoot estimates and/or RS ratios 2) Originate from annual and perennial crops grown in Europe (according to list of countries defined by EJP Soil) 3) Include a minimum of necessary meta-data 4) Originates from field studies (i.e. pot studies were excluded because of artificial effects on roots) During the initial literature survey, a range of existing databases were assessed to identify suitable articles for inclusion in this analysis. This included existing data collections, data from partners and literature review: • Data from Martin Bolinder’s (SLU) collection • Data from several project partners (From France, Denmark, Portugal, Switzerland) • GrooT and TRY database screening In addition to gathering data from published articles, where appropriate, contact was made with corresponding authors to resolve uncertainties and fill gaps in the associated meta data. This resulted in a library of assessments for each country and entries in the RS database. In total we identified 23 studies resulting in 451 individual measurements across 11 countries in Europe (including the UK).

This data set is a digital soil survey and generally is the most detailed level of soil geographic data developed by the National Cooperative Soil Survey. The information was prepared by digitizing maps, by compiling information onto a planimetric correct base and digitizing, or by revising digitized maps using remotely sensed and other information. This data set consists of georeferenced digital map data and computerized attribute data. The map data are in a soil survey area extent format and include a detailed, field verified inventory of soils and miscellaneous areas that normally occur in a repeatable pattern on the landscape and that can be cartographically shown at the scale mapped. A special soil features layer (point and line features) is optional. This layer displays the location of features too small to delineate at the mapping scale, but they are large enough and contrasting enough to significantly influence use and management. The soil map units are linked to attributes in the National Soil Information System relational database, which gives the proportionate extent of the component soils and their properties.

The above- and below-ground sizes and shapes of plants strongly influence plant competition, community structure, and plant-environment interactions, but the plant size and shape across climate regimes remain incompletely understood. In this study I seek to understand how plant geometries respond to varying climates via trade-offs in shoot height and width, and root depth and spread. I more than doubled the Root Systems of Individual Plants (RSIP) database to contain 5,647 observations, to our knowledge the largest database describing the maximum rooting depth, lateral spread, and shoot size of terrestrial plants in the world. Shoot size and root system size strongly covary. Across climatic gradients woody plants show deeper-narrower root systems in arid climates and taller shoots in humid climates. Phylogeny greatly influences shoot size. Rooting depth is primarily influenced by climate seasonality and lateral root spread is strongly influenced by shoot size. Using our newly expanded global database I found that shoot size covaries strongly with rooting system size; however, these relationships are not static across the climate space, as the geometries of plants shift considerably.

Rooting depths were estimated from a global database of root profiles that was assembled from the primary literature to study relationships of abiotic and biotic factors associated with belowground vegetation structure. Variables used to characterize belowground vegetation structure include the depths above which 50% of all roots and 95% of all roots are located in the profile. For each root profile, information recorded includes latitude and longitude, elevation, soil texture, depth of organic horizons, type of roots measured (e.g., fine or total, live or dead), sampling methods, units of measurements (root mass, length, number, surface area), and sampling depth.

Nutrient measurements for fine roots were compiled from 56 published studies providing information on 372 different combinations of species, root diameter, rooting depths, and soils at a variety of locations. The compilation was used to examine dynamics of 14 nutrients, including translocation properties of roots of varying size and status.

Fine roots are an important source and sink for nutrients in terrestrial biogeochemistry. The data collected come from 56 published studies that give information on fine root (less than 5-mm diameter) nutrient concentrations, root diameters, and retranslocation of nutrients. These studies include diverse vegetation and biomes, including grass, shrub, and tree functional types from temperate, tropical, boreal and tundra systems. The preponderance of data comes from experiments with temperate and coniferous trees. Study sites were a mixture of natural and manipulated ecosystems, including old growth, secondary growth, old fields, and tundra systems. Data from fertilized, potted or greenhouse experiments were excluded. Data are available by diameter class. This listing builds on the database of Jackson et al (1996, 1997). Please see Gordon and Jackson (2000) for more information.

The following hypotheses were examined (Gordon and Jackson 2000) for fine root nutrients by analyzing these data: (1) that there is an inverse relationship of fine root nutrient concentrations with root diameter, and (2) that retranslocation of nutrients out of fine roots is minimal. Nutrient concentrations of roots less than or equal to 5 mm in diameter were analyzed as a function of root diameter and root status (live, dead, and undifferentiated), including a comparison for coniferous and broad-leaved trees. From the results, mean N concentrations in live and dead fine roots were identical and may imply little retranslocation of root N with senescence, but conflicting evidence from C:N ratios highlights the need for further research (Gordon and Jackson 2000). These results have practical implications for various ecological methods and for the representation of roots in biogeochemical models.

A PDF copy of the Gordon and Jackson (2000) paper is available at http://www.biology.duke.edu/jackson/Ecol99.htm.

This data set builds on the initial root data compiled by R. B. Jackson in the mid-1990s (see Jackson et al. 1996; Jackson et al. 1997). The expanded and updated data set (Gordon and Jackson 2000) contains nutrient concentrations for approximately 372 site-pit-depths from 56 papers. In addition, the initial Jackson data set has been expanded for studies with root turnover rates (data for 341 site-vegetation combinations for approximately 188 sites from 152 papers in Gill and Jackson (2000) and rooting depth (data for approximately 298 sites with 565 profiles in Schenk and Jackson 2002). The three recent papers include most of the data contained in the initial root data set; however, some observations may have been excluded because of more stringent selection criteria. Many of the source papers provided data for the three recent rooting papers and users are encouraged to review all three data sets.

The FungalRoot database accumulates information about plant mycorrhizal status and root colonization intensity, The database was assembled based on previously published reviews, local databases and a large number of yet neglected case studies and recent studies published in nine globally most important languages. The database enables to distinguish between reports of a presence of a particular mycorrhizal type, and reports where the plants were checked for all existing mycorrhizal types. In addition, our database provides information about the locality, ecosystem type, soil chemical data, and the method of mycorrhizal assessment that enable users to build more specific, local reference databases. The database contains 36,303 species by site observations for 14,870 plant species.

Fine root biomass to 30cm depth via soil core sampling. Includes root carbon (C) and nitrogen (N) concentrations and stable isotopes.

The HC27 soil profile database consists of generic soil profiles developed by John Dimes and Jawoo Koo. The 27 soil profiles were generated based on three criteria that crop models are most responsive to: texture, rooting depth (proxy of water availability), and organic carbon content (proxy of fertility). Three levels for each category were classified using the boundary conditions based on the meta-analysis of WISE 1.1 soil profiles measured at crop land areas in Sub-Saharan Africa. < p>There are multiple ways to utilize these generic soil profiles in crop modeling applications, especially when soil measurement data is not available for the study site. For example, (1) users can choose the one that best matches the soil typically found in the study area by following the decision tree of three multiple-choice questions and use it as a starting point, or (2) users can run models with all 27 soil profiles for a given study site to create a possible range of simulation results, which can be narrowed down later as more site-specific information becomes available. These generic soil profiles does not replace existing soil mapping efforts nor site-specific soil measurements. Instead this approach addresses the need for a set of reasonably representative and prototypical soil profiles in certain types of crop modeling applications (e.g., global-scale modeling studies). Due to the nature of being "generic," there will be applications for which the use of HC27 is not desirable, especially where detailed soil property dynamics beyond the three criter ia are emphasized.

This data set provides two estimates of the geographic distribution of the total plant-available soil water storage capacity of the rooting zone ("rooting zone water storage size") on a 1.0 degree global grid. Two inverse modeling methods were used. The first modeling approach (optimization) was based on the assumption that vegetation has adapted to the environment such that it makes optimum use of water (Kleidon and Heimann 1998). The second method (assimilation) was based on the assumption that green vegetation indicates sufficient available water for transpiration (Knorr 1997). The data set was developed to provide alternative means to describe rooting characteristics of the global vegetation cover for land surface and climate models in support of the ISLSCP Initiative II data collection. There are three files in this data set.

Motivation: As genome-wide reconstruction of phylogenetic trees becomes more widespread, limitations of available data are being appreciated more than ever before. One issue is that phylogenomic datasets are riddled with missing data, and gene trees, in particular, almost always lack representatives from some species otherwise available in the dataset. Since many downstream applications of gene trees require or can benefit from access to complete gene trees, it will be beneficial to algorithmically complete gene trees. Also, gene trees are often unrooted, and rooting them is useful for downstream applications. While completing and rooting a gene tree with respect to a given species tree has been studied, those problems are not studied in depth when we lack such a reference species tree.

Results: We study completion of gene trees without a need for a reference species tree. We formulate an optimization problem to complete the gene trees while minimizing their quartet distance to the given set of gene trees. We extend a seminal algorithm by Brodal et al. to solve this problem in quasi-linear time. In simulated studies and on a large empirical dataset, we show that completion of gene trees using other gene trees is relatively accurate and, unlike the case where a species tree is available, is unbiased.

Availability and implementation: Our method, tripVote, is available at https://github.com/uym2/tripVote.

List of studies compiled in the global database of vertical root profiles.

The genetic basis of increased rooting below the plough layer, post-anthesis in the field, of an elite wheat line (Triticum aestivum ‘Shamrock’) with recent introgression from wild emmer (T. dicoccoides), is investigated. Shamrock has a non-glaucous canopy phenotype mapped to the short arm of chromosome 2B (2BS), derived from the wild emmer. A secondary aim was to determine whether genetic effects found in the field could have been predicted by other assessment methods. Roots of doubled haploid (DH) lines from a winter wheat (‘Shamrock’ × ‘Shango’) population were assessed using a seedling screen in moist paper rolls, in rhizotrons to the end of tillering, and in the field post-anthesis. A linkage map was produced using single nucleotide polymorphism markers to identify quantitative trait loci (QTLs) for rooting traits. Shamrock had greater root length density (RLD) at depth than Shango, in the field and within the rhizotrons. The DH population exhibited diversity for rooting traits within the three environments studied. QTLs were identified on chromosomes 5D, 6B and 7B, explaining variation in RLD post-anthesis in the field. Effects associated with the non-glaucous trait on RLD interacted significantly with depth in the field, and some of this interaction mapped to 2BS. The effect of genotype was strongly influenced by the method of root assessment, e.g. glaucousness expressed in the field was negatively associated with root length in the rhizotrons, but positively associated with length in the seedling screen. To our knowledge, this is the first study to identify QTLs for rooting at depth in field-grown wheat at mature growth stages. Within the population studied here, our results are consistent with the hypothesis that some of the variation in rooting is associated with recent introgression from wild emmer. The expression of genetic effects differed between the methods of root assessment.

Estimates of root turnover rates were calculated from measurements of live root standing crop and belowground net primary production (BNPP) compiled from the primary literature. Vegetation characteristics, soil properties, and climate conditions were associated with turnover rates to examine patterns and controls for biomes worldwide. Building on prior analyses (Jackson et al. 1996, 1997), data were compiled from approximately 190 papers from additional journals, book chapters, technical reports, and unpublished manuscripts that included information on live root standing crop and belowground BNPP. The papers described research on every continent except Antarctica, although the majority were from North America. In the database, the plant functional type and biome coverage were most abundant for grasslands and temperate zones.

The FIFE Root Biomass data were collected from 16 locations within the FIFE study area during the 1987 growing season. They provide a measure of the below-ground biomass for the study area. Biomass reported as grams per square m assumes that the depth of the core samples is sufficient to include all root biomass under the surface to an infinite depth. Prairie vegetation does possess roots deeper than the 20 cm coring, however, the fraction of total root biomass below 20 cm is minuscule and safely ignored in a study of biomass.