Sep 24, 2024
USDA LTAR Common Experiment measurement: Sediment flux
- Brandon L. Edwards1,
- Nicholas P. Webb2,
- Justin W. Van Zee2,
- Ericha M. Courtright2
- 1New Mexico State University, Jornada Experimental Range, Las Cruces, NM;
- 2USDA Agricultural Research Service, Range Management Research, Las Cruces, NM
External link: https://ltar.ars.usda.gov
Protocol Citation: Brandon L. Edwards, Nicholas P. Webb, Justin W. Van Zee, Ericha M. Courtright 2024. USDA LTAR Common Experiment measurement: Sediment flux. protocols.io https://dx.doi.org/10.17504/protocols.io.6qpvr8x23lmk/v1
License: This is an open access protocol distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Protocol status: Working
We use this protocol and it's working
Created: January 08, 2024
Last Modified: September 24, 2024
Protocol Integer ID: 97110
Keywords: Long-Term Agroecosystem Research, LTAR, USDA LTAR, Common Experiment, crops, wind erosion, environmental quality, land use, sediments, soil, texture, Aeolian EROsion (AERO) model, soil surface texture, ground cover, foliar cover, sediment flux wind erosion from agroecosystem, field measurements of wind erosion, sediment flux wind erosion, national wind erosion research network, managing wind erosion, wind erosion, generating sediment flux estimate, sediment flux estimate, aeolian erosion, predictive models across different land use, vegetation canopy gap length, usda ltar common experiment measurement, data on soil surface texture, soil surface texture, different land use, agroecosystem, sediment, soil, ecosystem function, foliar cover, ecosystem, canopy height, canopy
Funders Acknowledgements:
United States Department of Agriculture
Grant ID: -
Abstract
Wind erosion from agroecosystems can harm ecosystem functions, environmental quality, and human health. Wind erosion can also lead to reduced economic returns through damage to property and compensatory increases in supplemental fertility. Field measurements of wind erosion are resource- and time-intensive, necessitating using predictive models across different land uses. Here, we briefly describe field measurements necessary for generating sediment flux estimates using the Aeolian EROsion (AERO) model. This model requires data on soil surface texture, ground and foliar cover, canopy height, and vegetation canopy gap lengths. Methods align with those used by the National Wind Erosion Research Network, which aims to develop decision-support tools for managing wind erosion and its impacts.
Troubleshooting
Overview
Sediment flux estimates from the AERO model require three types of inputs for each monitoring location: 1) soil surface texture, 2) ground and foliar cover and vegetation height measurements, and 3) canopy gap observations (Edwards et al., 2022).
The particle size distribution (PSD) of near-surface (0-1 cm) soil provides information to estimate the threshold shear velocity for aeolian sediment transport initiation. Assessments are made at field scale using a stratified random sampling design using composite samples from 0 to 1 cm depth. Soil PSDs are estimated for minimally and fully dispersed samples from 0.4 to 2000 µm using a Beckman Coulter LS 13 320 laser diffraction particle sizer or comparable instrument. Details are outlined by Edwards et al. (2022) and adapted in summary form below.
Ground and foliar cover and height
The cover, height, and distribution of vegetation affect the wind shear stress (horizontal force at the surface) that can erode soil surfaces. Accordingly, assessments of vegetation attributes are important for understanding their effectiveness in reducing wind erosion. Ground and foliar measurements using the line-point intercept (LPI) method are conducted along three (3) transects, which are 100 meters long across a representative 1 ha site within a field. Plots can be scaled to smaller areas, although it is important to ensure that transect lengths and LPI and vegetation height sampling intervals appropriately describe the spatial variability of ground cover elements. A link to instructional videos for establishing transects and understanding the LPI method is provided below. Details are outlined by Herrick et al. (2018), Webb et al. (2015), and Edwards et al. (2022) and adapted in summary form below.
Canopy gap observations
Canopy gap observations provide insight into the distribution and horizontal structure of the plant community. Make observations along the same transects used for other vegetation assessments. A link to an instructional video for the canopy gap intercept method is provided below. Details are outlined by Herrick et al. (2018), Webb et al. (2015), and Edwards et al. (2022) and adapted in summary form below.
Always conduct bare soil, ground cover, and canopy height and gap measurements at project initiation. The frequency of subsequent measurements will depend on the temporal dynamics of vegetation cover and structure. Measurement frequency for croplands should capture changes in biomass throughout the growing season and in response to management practices and field activities (e.g., tillage, planting, harvest, cover crop interseeding, residue removal, etc.). Moreover, measurements should be conducted at cropland sites during fallow phases to capture changes in ground cover. For rangelands, measurement frequency should capture seasonal vegetation cover and structure changes. Vegetation assessment times should be flexible to account for inter-annual variability in production and management.
Soil characteristics
Identify a representative plot area measuring 100m x 100m in size.
Partition the site into nine equivalently sized areas using a 3 × 3 grid.
Randomly assign three sampling locations within each grid cell to Sample Groups 1, 2, and 3 (Fig. 1).
Fig. 1. Soil sampling design diagram (from Webb et al., 2015).
Use a flat-bottomed aggregate stability scoop to collect ~250 g of soil from the 0-1 cm depth at each location. Combine samples across Sample Groups to form three composite samples.
Air-dry samples at room temperature for a minimum of 1 week before conducting lab analyses.
Hand sieve samples to remove rock fragments >2 mm, plus to remove litter that is >1 mm wide and/or >2 cm long.
Measure soil PSDs using a laser diffraction particle sizer.
Note
Measure soil PSD at project initiation. Although a single baseline measurement will suffice at most sites, subsequent measurements may be necessary if sites are experiencing considerable erosion/deposition.
Establish transects
Assess ground and foliar cover on three (3) 100 m transects.
Transects should follow bearings of 0°, 60°, and 120°, intersecting at the center of the site (Fig. 2).
Fig. 2. Proposed orientation of transects for ground and foliar measurements (from Webb et al., 2015).
Mark transect start and end points to ensure transect lines are in the same place in subsequent measurements.
It is acceptable if an entire transect falls in a crop interrow.
Bare soil
Make LPI measurements at a sampling interval of 0.25 m (maximum) for bare soil and ground cover.
Bare soil represents a ‘hit’ that contacts soil (< 2 mm), loose erodible soil (if the category is recorded), aggregate soil (> 2 mm), or physical crust.
Points with plant cover (which includes both foliar and basal elements) or litter over soil do not count as bare soil. Also, rock fragments do not count as bare soil.
Ground cover
Ground cover comprises all non-soil elements (e.g., vegetation, litter, rocks, and biocrust).
Ground cover and bare soil may not sum to 100% across a single transect as this depends on how indicators are calculated. It is best if ground cover indicators are calculated using the terradactyl R package described by McCord et al. 2022.
Vegetation canopy height
Measurements of vegetation canopy height are conducted concurrently with bare soil and ground cover measurements.
Record canopy height (cm) as the maximum height of any vegetation element (leaf or stem) within a 15 cm radius every 2 m along each transect. The plant does not have to root within the 15 cm radius.
If no vegetation is present, record the height as zero.
- Canopy gaps are interrupted by any plant species.
- Canopy occurs any time 50% of any 3 cm segment of tape edge intercepts live or dead plant canopy, based on a vertical projection from the canopy to the ground.
- Record canopy gap lengths ≥5 cm along each transect.
Illustrative media and data recording sheets
Instructional videos for vegetation assessments are available at The Landscape Toolbox: Training Videos (https://landscapetoolbox.org/training-videos)
- Establish a Transect
- Line-Point Intercept
- Canopy Gap Intercept
Data recording sheets in PDF and Excel formats are available at https://winderosionnetwork.org/documents
- Cropland Management Recording Sheet
- Rangeland Management Recording Sheet
- Line-Point Intercept and Vegetation Height Recording Sheet
- Vegetation Canopy Gap Recording Sheet
Recommendations for data collection
Table 1. Summary of recommendations for measuring Aeolian Erosion (AERO) model inputs for sediment flux estimation.
| A | B | C | D | |
| Attribute | Preferred | Minimum | Comments | |
| Spatial scale | Field | Methodology applicable to field scale only | ||
| Soil assessments | Recurring measurement | One measurement at project initiation | The frequency of soil particle size distribution measurement depends on the extent of soil erosion/deposition at the site | |
| Vegetation assessments | Quarterly | Annually | Vegetation assessments may be restricted to spring, summer, and fall at locations with snow cover during the winter | |
| Covariate metrics | Oriented roughness | Conducted concurrently with vegetation assessments | ||
| Other | Management records | Record equipment changeouts or issues, plus planting and harvesting activities |
Additional considerations
Sites that belong to the National Wind Erosion Research Network should follow the expanded assessment protocols outlined in Webb et al. (2015). Supplementary resources are available at https://winderosionnetwork.org/
Recorded data should be entered into a Database for Inventory, Monitoring, and Assessment and sent to Landscape Data Commons or NWERN personnel to ingest and process the data (McCord et al., 2022).
Protocol references
Edwards, B.L., Webb, N.P., Galloza, M.S., Van Zee, J.W., Courtright, E.M., Cooper, B.F., Metz, L.J., Herrick, J.E., Okin, G.S., Duniway, M.C., Tatarko, J., Tedala, N.H., Moriasi, D.N., Newingham, B.A., Pierson, F.B., Toledo, D., & Van Pelt, R.S. (2022). Parameterizing an aeolian erosion model for rangelands. Aeolian Res. 54, 100769. https://doi.org/10.1016/j.aeolia.2021.100769
Herrick, J.E., Van Zee, J.W., McCord, S.E., Courtright, E.M., Karl, J.W., & Burkett, L.M. (2018). Monitoring Manual for Grassland, Shrubland, and Savanna Ecosystems, Volume 1: Core Methods, Second Edition. USDA-ARS Jornada Experimental Range, Las Cruces, New Mexico. https://www.landscapetoolbox.org/manuals/monitoring-manual/
McCord, S.E., Brehm, J.R., Burnett, S.H., Dietrich, C. Edwards, B., Metz, L.J., Narvaez, M.H., Pierson, F., Ramirez, K.S., Stauffer, N.G., Webb, N.P, & Tweedie, C.E. (2022). A framework and toolset for standardizing agroecosystem indicators. Ecol. Indicators. 144, 109511. https://doi.org/10.1016/j.ecolind.2022.109511
Webb, N.P., Herrick, J.E., Van Zee, J.W., Hugenholtz, C.H., Zobeck, T.M., & Okin, G.S. (2015). Standard Methods for Wind Erosion Research and Model Development: Protocol for the National Wind Erosion Research Network. USDA-ARS Jornada Experimental Range, Las Cruces, USA. https://winderosionnetwork.org/documents
Acknowledgements
This research is a contribution from the Long-Term Agroecosystem Research (LTAR) network. LTAR is supported by the United States Department of Agriculture. The use of trade, firm, or corporation names in this publication is for the information and convenience of the reader. Such use does not constitute an official endorsement or approval by the United States Department of Agriculture or the Agricultural Research Service of any product or service to the exclusion of others that may be suitable. USDA is an equal opportunity provider and employer.