Mari-Vaughn V. Johnson

Soil Organic C:N vs. Water-Extractable Organic C:N

Traditionally, soil-testing laboratories have used a variety of methods to determine soil organic matter, yet they lack a practical method to predict potential N mineralization/immobilization from soil organic matter. Soils with high microbial activity may experience N immobilization (or reduced net N mineralization), and this issue remains unresolved in how to predict these conditions of net mineralization or net immobilization. Prediction may become possible with the use of a more sensitive method to determine soil C:N ratios stemming from the water-extractable C and N pools that can be readily adapted by both commercial and university soil testing labs. Soil microbial activity is highly related to soil organic C and N, as well as to water-extractable organic C (WEOC) and water-extractable organic N (WEON). The relationship between soil respiration and WEOC and WEON is stronger than between respiration and soil organic C (SOC) and total organic N (TON). We explored the relationship between soil organic C:N and water-extractable organic C:N, as well as their relationship to soil microbial activity as measured by the flush of CO2 following rewetting of dried soil. In 50 different soils, the relationship between soil microbial activity and water-extractable organic C:N was much stronger than for soil organic C:N. We concluded that the water-extractable organic C:N was a more sensitive measurement of the soil substrate which drives soil microbial activity. We also suggest that a water-extractable organic C:N level >20 be used as a practical threshold to separate those soils that may have immobilized N with high microbial activity.

Clash of the Titans: Comparing Productivity Via Radiation Use Efficiency for Two Grass Giants of the Biofuel Field

The comparative productivity of switchgrass (Panicum virgatum L.) and Miscanthus (Miscanthus × giganteus) is of critical importance to the biofuel industry. The radiation use efficiency (RUE), when derived in an environment with non-limiting soil water and soil nutrients, provides one metric of relative productivity. The objective of this study was to compare giant Miscanthus to available switchgrass cultivars, using established methods to calculate RUE of the two species at two disparate sites. Measurements of fraction intercepted photosynthetically active radiation (PAR) and dry matter were taken on plots at Elsberry, MO (Miscanthus and the switchgrass cultivars Alamo, Kanlow, and Cave-in-Rock) and at Gustine, TX (Miscanthus and Alamo switchgrass, irrigated with dairy wastewater and a non-irrigated control). In MO, Miscanthus mean RUE (3.71) was less than Alamo switchgrass mean RUE (4.30). In TX under irrigation, Miscanthus mean RUE was 2.24 and Alamo switchgrass mean RUE was 3.20. In MO, the more northern lowland switchgrass cultivar, Kanlow, showed similar mean RUE (3.70) as Miscanthus. In MO, the northern upland cultivar Cave-in-Rock had a mean RUE (3.17) that was only 85% of that for Miscanthus at MO. Stress (water and nutrients) had a greater effect on Miscanthus RUE than on switchgrass RUE in TX. These results provide realistic RUE values for simulating these important biofuel grasses in diverse environmental conditions.

Comparing Biomass Yields of Low-Input High-Diversity Communities with Managed Monocultures Across the Central United States

Biofuel cropping expansion is increasing pressure on food, grazing, and conservation lands. Debate over the efficacy of converting diverse native plant communities to managed monocultures prompted us to explore the extensive crop and ecological site productivity databases maintained by US Department of Agriculture-Natural Resources Conservation Service. We compared annual net primary productivity (ANPP) of diverse native plant communities to ANPP of alfalfa (Medicago sativa L.) in Nebraska, Kansas, and Oklahoma; to coastal bermudagrass (Cynodon dactylon [L.] Pers.) in northern and central Texas; and to buffelgrass (Pennisetum ciliare [L.] Link.) in extreme southern Texas. In only 21% of the 1,238 sites in Nebraska, Kansas, and Oklahoma did native communities produce more or equivalent ANPP compared with managed alfalfa or coastal bermudagrass. In contrast, southern Texas native communities had greater ANPP than did buffelgrass at 81% of the sites. Regression analyses based on these results suggested that managed switchgrass (Panicum virgatum L.) ANPP would consistently exceed native community ANPP. We identified the type of sites that could remain in diverse communities or be converted to diverse communities and have productivity as great as or greater than highly managed monocultures of alfalfa, coastal bermudagrass, or buffelgrass. However, because of the low ANPP on these sites, biomass production may not be the optimal use of such sites. These lands may be better suited to providing other ecosystem services.

Western Lake Erie Basin: Soft-data-constrained, NHDPlus resolution watershed modeling and exploration of applicable conservation scenarios.

Complex watershed simulation models are powerful tools that can help scientists and policy-makers address challenging topics, such as land use management and water security. In the Western Lake Erie Basin (WLEB), complex hydrological models have been applied at various scales to help describe relationships between land use and water, nutrient, and sediment dynamics. This manuscript evaluated the capacity of the current Soil and Water Assessment Tool (SWAT) to predict hydrological and water quality processes within WLEB at the finest resolution watershed boundary unit (NHDPlus) along with the current conditions and conservation scenarios. The process based SWAT model was capable of the fine-scale computation and complex routing used in this project, as indicated by measured data at five gaging stations. The level of detail required for fine-scale spatial simulation made the use of both hard and soft data necessary in model calibration, alongside other model adaptations. Limitations to the models predictive capacity were due to a paucity of data in the region at the NHDPlus scale rather than due to SWAT functionality. Results of treatment scenarios demonstrate variable effects of structural practices and nutrient management on sediment and nutrient loss dynamics. Targeting treatment to acres with critical outstanding conservation needs provides the largest return on investment in terms of nutrient loss reduction per dollar spent, relative to treating acres with lower inherent nutrient loss vulnerabilities. Importantly, this research raises considerations about use of models to guide land management decisions at very fine spatial scales. Decision makers using these results should be aware of data limitations that hinder fine-scale model interpretation.

Impact of the Agricultural Research Service Watershed Assessment Studies on the Conservation Effects Assessment Project Cropland National Assessment

WATERSHED MODELING AND USDA CONSERVATION POLICY PLANNING The Soil and Water Resources Conservation Act (RCA) of 1977 provides the USDA broad strategic assessment and planning authority for the conservation, protection, and enhancement of soil, water, and related natural resources (USDA NRCS 2011). Through RCA, USDA appraises the status and trends of soil, water, and related resources on nonfederal land and assesses their capability to meet present and future demands; evaluates current programs, policies, and authorities; and develops a national soil and water conservation program to give direction to USDA soil and water conservation activities. The 1985 RCA Appraisal was the first to use a comprehensive model (EPIC; Erosion Productivity Impact Calculator) to estimate the impact of soil erosion on crop productivity (Williams et al. 1984). EPIC is a field-scale model, and thousands of representative fields were modeled across the agricultural regions of the continental United States. The first watershed-based RCA assessment, called the Hydrologic Unit Model for the United States (HUMUS), was undertaken for the 1997 RCA Appraisal (Srinivasan et al. 1998; Arnold et al. 1999). HUMUS provides the necessary technical basis that enables the status of the nations water resources to be determined at the national scale. The HUMUS framework enables modeling of spatially…

Indirect Measurement of Leaf Area Index in Sagebrush-Steppe Rangelands

Abstract Leaf area index (LAI) is defined as the one-sided area of leaves above a unit area of ground. It is a fundamental ecosystem parameter that is a required input of process-based plant growth and biogeochemical models. Direct measurement of LAI is the most accurate method, but is destructive, time-consuming, and labor-intensive. LAI is highly variable in time and space on sagebrush-steppe rangelands, and a rapid, nondestructive method is desirable to understand ecosystem processes. The point-intercept method is nondestructive and has been demonstrated to provide accurate LAI estimates, but the method is time-consuming. LAI measurement with the Accupar ceptometer (Decagon Devices, Pullman, WA) is nondestructive and faster than the point-intercept method, but has not been evaluated on sagebrush-steppe rangelands. The objective of this study was to evaluate the ceptometer for measurement of LAI in sagebrush-steppe rangelands. Ceptometer and point-intercept LAI data were collected at six sites in sagebrush-steppe rangelands and the values were compared. We found that 1) ceptometer LAI data were consistently greater than point-intercept LAI data, 2) ceptometer data were much more variable than the point-intercept data based on standard deviations, and 3) the overall correlation between the two methods was very weak (r2  =  0.15). The much greater ceptometer LAI values were, at least partly, due to the large woody component of the vegetative cover. We attribute the high variability of ceptometer-measured LAI to high instrument sensitivity of the angle of the instrument relative to the sun.

Surface-Applied Biosolids Enhance Soil Organic Carbon and Nitrogen Stocks but Have Contrasting Effects on Soil Physical Quality

Mid- to long-term impacts of land applying biosolids will depend on application rate, duration, and method; biosolids composition; and site-specific characteristics (e.g., climate, soils). This study evaluates the effects of surface-broadcast biosolids application rate and duration on soil organic carbon (SOC) stocks, soil aggregate stability, and selected soil hydraulic properties in a municipally operated, no-till forage production system. Total SOC stocks (0–45 cm soil) increased nonlinearly with application rate in perennial grass fields treated for 8 years with 0, 20, 40, or 60 Mg of Class B biosolids (DM) ha−1 yr−1 (midterm treatments). Soil organic C stocks in long-term treatment fields receiving 20 years of 20 Mg ha−1 yr−1 were 36% higher than those in midterm fields treated at the same rate. Surface-applying biosolids had contrasting effects on soil physical properties. Soil bulk density was little affected by biosolids applications, but applications were associated with decreased water-stable soil aggregates, increased soil water retention, and increased available water-holding capacity. This study contrasts the potential for C storage in soils treated with surface-applied biosolids with application effects on soil physical properties, underscoring the importance of site-specific management decisions for the beneficial reuse of biosolids in agricultural settings.

The Rancher’s ALMANAC

The mathematical Agricultural Land Management Alternatives with Numerical Assessment Criteria (ALMANAC) Model simulates shortand longterm western rangeland vegetation response to various conservation strategies. The model was chosen by the Rangeland Conservation Effects Assessment Program to assess rangeland health across the western United States. Here we demonstrate the model’s accuracy as compared to NRCS Ecological Site Description data at sites in Nevada, Utah, and California. The model is free and available to the public. The USDA–ARS Grassland, Soil, and Water Research Lab at Temple, Texas (http://www.ars.usda.gov/spa/gswrl), conducts free seminars on input parameter development and ALMANAC simulation training. The United States’ western rangelands are a valuable national natural resource. Rangelands provide important ecological benefi t: storing carbon in the soils, mitigating soil loss, and supporting a diversity of plant, animal, and fungal species. Their economic services are comparably important; they support a vibrant and varied livestock industry, maintain wildlife habitat, and provide recreational opportunity to hikers, birders, wildlife photographers, and off-road enthusiasts. They also are valued by the scientifi c community, including geologists, hydrologists, plant and animal ecologists, and soil scientists, to name a few. However, these lands face mounting pressures from urban and suburban expansion, exotic species invasions, changing fi re dynamics, and increased human use. We must determine the best management strategies for these lands to maintain their sustainability for perpetuity, so that we can enjoy the resource now while maintaining it for future generations. Here we demonstrate the applicability of a promising decision support tool to help guide us towards sustainable management decisions: the ALMANAC model.