Template FAQ
Is your question related to using the database or contributing to it?
Using the Database
Getting Started
To get acquainted with using ISRaD Data in R, check out our user manual for a quick tutorial.
General Radiocarbon Guidelines
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ISRaD accepts fraction modern and Δ14C radiocarbon units. Only fill in the data reported in the paper. Unit conversions performed separately and included in ISRaD_extra data object, which is part of the ISRaD R-package
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If the data is reported as a calibrated date, it cannot be included in ISRaD. Uncalibrated radiocarbon ages can be converted to fraction modern values (see below).
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age = -8033 * ln (Fm)
Some additional information on radiocarbon units and calculations is available here.
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Use the following formula (Stenström et al., 2011):
error_Fm = Fm * errorage / 8033
where Fm is fraction modern.
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Convert radiocarbon age to Fraction modern using:
age = -8033 * ln (Fm)
and ignore δ14C values. Be sure to mark down the year of observation which is important for the conversion of Fm to Δ14C.
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Calculate Δ14C using the following formula:
Δ14C = δ14C - (2*δ13C + 50)(1 + δ14C / 1000)
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Leave the field blank and add a note that data is available but has to be mined for. Do not enter a fraction modern value of 1! This is misleading during data analysis!
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As explained in the Template Information File, the Observation Year refers to the date at which the soil sample was collected whereas the Radiocarbon Analysis Year refers to the year at which the sample was actually analyzed for radiocarbon.
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As explained in the Template Information File, lyr_14c_sigma is the standard deviation reported by the AMS facility as an analytical error estimate. This is the most common case and applicable where the author has reported individual measurements. In cases where only the mean values are reported, the lyr_14c_sd field should be used. This is the sample standard deviation calculated from multiple (replicated) measurements. When possible please report individual measurements.
Questions about specific tabs?
Feel free to take a look at and add questions or answers to our FAQ document.
Questions about specific tabs?
Metadata / General
The metadata table provides information for the characterization of the entry itself. Required metadata include the entry name, the DOI, the data curator (the person who oversees template entry), and their contact information. The entry name is the key variable used to match the entry with measurements reported at the other data levels.
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No, only some columns are required. The required columns are indicated in the Template Information File (by “yes” in the “Required” column) and also using red font in the template. Although we encourage you to fill out as many fields as possible, it is perfectly ok if many columns are left empty and some columns are only partly filled in. Please leave the fields with missing data empty (i.e., do not fill in zeros or NAs).
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Yes, deleting non-required columns (i.e., those not indicated in red) or changing order of any of the columns is fine and will not cause the template to fail QA/QC.
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If the data are unpublished but you expect them to be published in the future (thus obtaining DOI), you can submit the template without DOI and then later submit a correction of the template with DOI. If you take this approach please fill in “israd” into the “doi” field in the metadata tab. Also note that data from this entry will not be compiled in the R-package data objects until a DOI is added.
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Yes, this may be done with various softwares or on-line tools, such as such as WebPlotDigitizer. However, it is important to note in the metadata_note field that this was done. For example, “GPS coordinates and variables x,y, and z were extracted from figures.” While the raw data from the author or supplementary information is preferable, digitized data is also welcome in ISRaD.
Is there any rule on how many decimal places are reasonable to enter when data are digitized from a plot?
No, use your best guess about the appropriate number of decimal places based on expected precision of plot digitization and/or data acquisition.
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Convert to organic carbon using
organic carbon = organic matter/1.724
and mention this in the lyr_note or other relevant field.
Contributing to the Database
Filling out a template can be confusing! Here you’ll find helpful guidelines for filling out templates and getting your data ready for inclusion in ISRaD.
Site
Site-level data are limited to the geospatial details defining the coarsest scale of the study area(s) included in each entry. We define a site as a spatially defined location that includes one or more soil profiles. By convention, we define a site as having a ≥ 5 km radius, i.e., samples collected within 5 km of each other should be grouped under the same “site” designation. However, the 5 km radius is a convention only, as the distinction between site and profile may be study-specific, and geospatial data at this resolution are not always available for legacy datasets.
Spatial coordinates are required to designate a site, and thus the required fields at the site level are limited to the site name, latitude, and longitude. Every entry must specify a minimum of one site location but can include multiple sites that do not need to be located in close proximity. For entries that do not report spatial coordinates, the data curator may estimate latitude and longitude based on the description of the study area using any of the widely acceptable mapping software (e.g., Google Earth, Google Maps, etc.). The site table does not include fields for reporting site properties. Such directly measured variables are reported at the profile level. The intended purpose of the site-level data is to provide at least coarse-scale geospatial coordinates for extracting consistently sourced parameters from geospatial datasets, which can then be compared against the range of measurements reported at the profile level.
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You can digitize the coordinates from the figure, or find the site location on Google maps or similar. Please use the metadata_note field to indicate this (e.g. “Coordinates were extracted from figures” or "Coordinates were estimated from site descriptions").
Profile
Profile-level data include details pertaining to specific sampling locations. If available, profile-scale spatial coordinates should be provided in addition to site-scale coordinates.
Many variables that may initially appear to belong at the site level are instead included at the profile level to facilitate accurate representation of spatial heterogeneity at a finer scale than the site level (e.g., for multiple profiles observed at the same site). Examples include local mean annual temperature and precipitation, soil taxonomic classification, vegetation type, land cover, depth to bedrock, and parent material composition. Other than the entry name and site name, the only additional required variable at the profile level is the profile name.
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FAO, USDA and other soil classification systems are not readily interchangeable, so this can be tricky. These tables can help: (1) a table for converting between FAO and USDA and (2) a table with FAO number, USDA classifications, and USCS classifications. The issue of converting between soil classification systems has been discussed here.
Finally, if you feel uncomfortable with this conversion, mention this in the email submitting your template, and an expert reviewer can double check this field for you.
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In order to accommodate a range of classification schemes, we consider multiple categories of land cover and vegetation information. The combination of one or more categories (described below) along with the latitude allows the end user to classify profiles into more general or more specific categories. In addition, we encourage you to include as much detail as possible about land cover and vegetation in the pro_veg_note column.
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This is the general land cover category; the options are bare, cultivated, forest, rangeland/grassland, shrubland, urban, wetland, and tundra. In some cases, this may be the only vegetation column that you will be able to fill in. This column is optional, and may be left blank if the land cover type is truly unknown, but users are asked to make sure this column is filled in.
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Forest and shrubland vegetation types may or may not lose their leaves on an annual cycle. If trees or shrubs retain their leaves all year, either because the local climate allows year-round growth, or because trees are adapted to never lose leaves (e.g., most conifers), then they should be categorized as evergreen. Trees or shrubs that lose leaves annually should be categorized as deciduous. If a forest contains an equal amount of both types, it may be categorized as mixed. This column should be left blank for land cover types other than forest and shrubland, or if the phenology is truly unknown.
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Forests may be categorized as broadleaf, needleleaf, or mixed. Note that this is independent of phenology. This column should be left blank for land cover types other than forest, or if the leaf type is truly unknown.
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This is the metabolic pathway employed by the local vegetation for photosynthesis. This is mainly applicable to grasses, which may use either the C3 or C4 pathway, and we expect this column will be left blank for all other land cover types. We also include the CAM pathway, in the unlikely event that a profile is best characterized with this type of vegetation. This column should be left blank if the photosynthetic pathway is unknown.
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Please include as much detailed information as you are able about the local land cover conditions and vegetation. For example, species names, spatial distribution, and evidence of disturbance, could all prove valuable in future analyses, and we encourage you to provide as much detail as possible.
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Please copy/paste or use Excel's "fill handle" to enter the information into each of the profiles. Because each profile CAN have its own vegetation characteristics, we want to have this information at the profile level, even if it's just the same thing over and over for each profile at the site.
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If you are interested in learning how to enter it, post a question on the Github issues page or contact info.israd@gmail.com. If not, mention this in the metadata_note field so that one day someone can come back to this.
Flux
Soil flux data present a special case of observations that correspond to the profile level of the database hierarchy. Flux-level data allow for reporting temporally explicit measurements of mass or energy transfer occurring at the profile scale. Both gas and liquid analytes (e.g., CO2, CH4, dissolved OC, particulate OC, etc.) may be reported in flux data. In addition to the profile name, records with flux data must also include the observation date (flx_obs_date). Data measured at multiple time points in a single location will have identical profile names but unique temporal data.
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Total soil respiration should be entered as an ecosystem in the flx_ecosystem_component column. If a trenched chamber system (i.e. roots were cut) was used or the vegetation was removed, this data should be entered as a heterotrophic ecosystem component.
Layer
Layer-level data correspond to measurements made for a specific depth increment collected from a soil profile. The required variables at the layer level include layer name, depth of layer top, and depth of layer bottom. The latter two variables describe the upper and lower range of the sampling depth, respectively, in units of centimeters. We use a depth reporting system where the top of the mineral soil is denoted as zero and subsequent depths below that point are reported with incrementally increasing positive values. Organic horizons are thus reported as negative depth intervals. Special indicator fields (e.g., lyr_all_ org_neg) are used when the depth to the mineral soil is unknown, e.g., for deep organic horizons or peats.
The layer level is where most common measurements of soil physical, chemical, and/or biological properties are reported. As such, there is an ever-increasing list of variables that may be reported in the layer table. Users should consult the up-to-date template instruction file for the complete list of accepted variables.
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If paper has radiocarbon data but does not report the observation year, estimate it by subtracting 3 years from the year of publication and note in the lyr_note field or other relevant note field. (e.g. “observation date estimated from year of publication”)
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Zero is defined as the mineral-organic interface. Positive depths increase into the mineral soil. Organic horizons have negative depths. Please convert your data to follow this convention. If data must be reported from the soil surface, use the lyr_all_org_neg column to flag this.
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Write "Inf" as infinity in the lyr_bot field.
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This column is used to flag studies where depths are reported from the soil surface, if the depth of the mineral-organic interface is unknown. For example, this is frequently the case in peatlands.
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Additionally, it is critical that you denote this layer as a composite by marking "y" in the lyr_composite field.
Interstitial
The interstitial level is a special case of layer-level data. Specifically, interstitial data refer to measurements made on material occupying the interstices of the soil structure. In most cases, this material can be thought of as being mobile relative to the rest of the soil matter. Some common examples include gases, liquids, and colloids. Like flux data, the interstitial data table accommodates repeated measurements of these properties through time, and as such, the observation date must be recorded for each record in the interstitial table. Because interstitial records may not correspond to the same depth increments defined for solid phase analyses, separate depth reporting is used in the interstitial table distinct from what is reported in the layer table. Both sampling methodology as well as the properties of interstitial samples are reported in the interstitial table.
Fraction
For new users of the ISRaD database, entering soil fractionation data can be daunting, particularly given the diverse and sometimes complicated methodologies used to fractionate soils. One of the most challenging scenarios occurs when multiple fractionation schemes are combined sequentially in the same study. In such cases, as well as in simpler examples, the following concepts are helpful for understanding the best practice for reporting soil fraction data into the ISRaD template.
An important goal when reporting soil fraction data in the ISRaD template is to represent fraction information such that the individual fractions can be totaled to calculate the bulk soil value. This equates to a conservation of mass, where fraction weights are reported.
Another useful goal for representing a fractionation scheme in the database, is that end users should be able to use the data to construct a box and arrow diagram that accurately describes the fractionation procedure, starting from bulk soil through to the end products that have been measured.
Accomplishing goals, (1) and (2) above requires paying careful attention to what is reported in the frc_input field. For single scheme fractionations, this is often just the bulk soil layer name. In more complex fractionation approaches, which combine multiple schemes, this column is key to reconstructing the order in which various steps are linked.
Another critical concept for accomplishing goals (1) and (2) is the use of “dummy fractions,” which we define as named fractions included in the data entry but that have not actually been directly measured. In some cases, they simply represent a portion of the sample and carbon mass that could be calculated by difference. In other cases, they represent a terminal byproduct of the method, which was not measured due to the scope of the study. In the latter scenario, it may not be possible to fully reconstruct the bulk radiocarbon values from the sum of the parts, but it is still important that end users understand that some portion whole was excluded.
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A heavy liquid is used to float off the "light-fraction" organics, thereby separating them from mineral material. The remaining mineral material is then further partitioned into a series of fractions isolated by incrementally increasing the density of the heavy liquid used for the separation.
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A physical fractionation scheme where heavy liquid is used to float off organics, thereby separating them from mineral material. This can be done with or without disruption of aggregates by sonication or shaking.
Example template: Swanston_2005
Incubation
Flux rates and isotopic signatures of laboratory-incubated samples are reported in the incubation table. Sample processing data (e.g., whether or not roots have been removed from samples prior to incubation) are recorded as well as incubation conditions (e.g., temperature, moisture, and duration). Repeat measurements, such as incubation time series, can also be recorded. Incubation records must be linked either to a layer or both a fraction and a layer, e.g., roots isolated from a specific bulk layer sample.
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This is not the primary focus of our database. However, if you wish to include it, it goes under the flux tab (here).