Forages for Conservation and Improved Soil Quality

Forages provide several soil benefits, including reduced soil erosion, reduced water runoff, improved soil physical properties, increased soil carbon, increased soil biologic activity, reduced soil salinity, and improved land stabilization and restoration when grown continuously or as part of a crop rotation. Ongoing research and synthesis of knowledge have improved our understanding of how forages alter and protect soil resources, thus providing producers, policymakers, and the general public information regarding which forage crops are best suited for a specific area or use (e.g. hay, grazing or bioenergy feedstock). Forages can be produced in forestland, range, pasture, and cropland settings. These land use types comprise 86% of non-Federal United States rural lands (Table 12.1). In the United States, active forage production occurs on 22.6 million ha and is used for hay, haylage, grass silage, and greenchop (Table 12.2). Forages are used as cover crops in several production systems, and approximately 4.2 million ha were recently planted in cover crops (Table 12.3). Currently, the highest cover crop use rates, as a percentage of total cropland within a given state, occur in the northeastern United States. Globally, permanent meadows and pastures account for over 3.3 billion ha, greater than arable land and permanent crops combined (Table 12.4). Within all regions of the world, except Europe, permanent meadows and pastures are a greater proportion of land cover than permanent crops. Pasture management information and resources are available for countries around the world (FAO 2017a,b). As seen in Tables 12.1–12.4, forages are used globally and can provide soil benefits across varied soil and climate types

Comparison of two soil quality indexes to evaluate cropping systems in northern Colorado

Various soil management or quality assessment tools have been proposed to evaluate the effects of land management practices on soil, air, and water resources. Two of them are the Soil Management Assessment Framework and the Soil Conditioning Index (SCI). This study was conducted to test the hypothesis that the Soil Quality Index (SQI) estimated by the Soil Management Assessment Framework can detect more minute changes in soil management than SCI and to test SCI response to other soil quality (SQ) indicators. These SQ indexes were tested on irrigated cropping systems near Fort Collins, Colorado, that included no-till and conventionally-tilled corn (Zea mays L.), and no-till corn with rotations including barley (Hordeum distichon L.), soybean (Glycine max (L.) Merr.), and dry bean (Phaeseolus vulgaris L.) at three levels of nitrogen varying from 0 to 224 kg N ha–1 (0 to 200 lb ac–1). Both SQ indexes clearly separated the plots with very high levels of N from plots with no N. However, for SQI the mid-level of N was statistically the same as both extreme levels. Statistical differences were observed among all N levels for the SCI. The SQI seemed to make more detailed differentiation among crop management systems than the SCI. The SCI separated the cropping systems into three groups with no overlap among groups. All no-till systems had the statistically same higher SCI than the conventionally-tilled continual corn system. The SQI separated the cropping systems into three groups with decreasing SQI as tillage intensity increased and as lower residue crops were introduced into the cropping system. The systems that included tillage and a low residue crop (soybean) had the lowest SQI. The SQI allowed overlap among cropping groups not recognized by SCI. Selection of the most appropriate SQ index seems to be a tradeoff between data requirements, resolution required, and the desired use of the evaluation tool

Measurement and data analysis methods for field-scale wind erosion studies and model validation

Accurate and reliable methods of measuring windblown sediment are needed to confirm, validate, and improve erosion models, assess the intensity of aeolian processes and related damage, determine the source of pollutants, and for other applications. This paper outlines important principles to consider in conducting field-scale wind erosion studies and proposes strategies of field data collection for use in model validation and development. Detailed discussions include consideration of field characteristics, sediment sampling, and meteorological stations. The field shape used in field-scale wind erosion research is generally a matter of preference and in many studies may not have practical significance. Maintaining a clear non-erodible boundary is necessary to accurately determine erosion fetch distance. A field length of about 300 m may be needed in many situations to approach transport capacity for saltation flux in bare agricultural fields. Field surface conditions affect the wind profile and other processes such as sediment emission, transport, and deposition and soil erodibility. Knowledge of the temporal variation in surface conditions is necessary to understand aeolian processes. Temporal soil properties that impact aeolian processes include surface roughness, dry aggregate size distribution, dry aggregate stability, and crust characteristics. Use of a portable 2 tall anemometer tower should be considered to quantify variability of friction velocity and aerodynamic roughness caused by surface conditions in field-scale studies. The types of samplers used for sampling aeolian sediment will vary depending upon the type of sediment to be measured. The Big Spring Number Eight (BSNE) and Modified Wilson and Cooke (MWAC) samplers appear to be the most popular for field studies of saltation. Suspension flux may be measured with commercially available instruments after modifications are made to ensure isokinetic conditions at high wind speeds. Meteorological measurements should include wind speed and direction, air temperature, solar radiation, relative humidity, rain amount, soil temperature and moisture. Careful consideration of the climatic, sediment, and soil surface characteristics observed in future field-scale wind erosion studies will ensure maximum use of the data collected

Crop, Tillage, and Landscape Effects on Near-Surface Soil Quality Indices in Indiana

Soil quality is a critical link between land management and water quality. We aimed to assess soil quality within the Cedar Creek Watershed, a pothole- dominated subwatershed within the St. Joseph River watershed that drains into the Western Lake Erie Basin in northeastern Indiana. The Soil Management Assessment Framework (SMAF) with 10 soil quality indicators was used to assess inherent and dynamic soil and environmental characteristics across crop rotations, tillage practices, and landscape positions. Surface physical, chemical, and nutrient component indices were high, averaging 90, 93, and 98% of the optimum, respectively. Surface biology had the lowest component score, averaging 69% of the optimum. Crop rotation, tillage, and landscape position effects were assessed using ANOVA. Crop selection had a greater impact on soil quality than tillage, with perennial grass systems having higher values than corn (Zea mays L.) or soybean [Glycine max (L.) Merr.]. Furthermore, soybean rotations often scored higher than corn rotations. Uncultivated perennial grass systems had higher overall soil quality index (SQI) values and physical, chemical, and biological component values than no-till or chisel–disk systems. Chisel–disk effects on overall and component SQI values were generally not significantly different from no-till management except for a few physical indicators. Toe-slopes had higher physical, biological, and overall SQI values than summit positions but toe-slope values were not significantly different from those of mid-slope positions. This work highlights the positive effects of perennial grass systems, the negative effects of corn-based systems, and the neutral effects of tillage on soil quality

Rugosidade da superfície do solo sob diferentes sistemas de manejo e influenciada por chuva artificial Soil surface roughness under diferent management systems and artificial rainfall

A rugosidade da superfície do solo é influenciada pelo manejo, formada em especial pelo tipo de preparo e reduzida pela ação da chuva, principalmente. O objetivo deste estudo foi avaliar a influência de diferentes sistemas de manejo do solo e da aplicação de chuva artificial na rugosidade da superfície do solo. Os tratamentos estudados resultaram da combinação de três sistemas de manejo do solo, semeadura direta (SD), preparo convencional (PC) e cultivo mínimo (CM), com três doses de resíduo vegetal seco de soja (Glycine max L. Merrill): 0, 2 e 4 Mg ha-1. Nas unidades experimentais foram aplicadas sete chuvas, com intensidade de precipitação pluvial de 60 mm h-1 e duração de 60 min cada, totalizando 420 mm de lâmina de chuva. A rugosidade foi avaliada imediatamente antes e após o preparo do solo e imediatamente após a aplicação de cada uma das sete chuvas artificiais. Obtiveram-se valores do índice de rugosidade ao acaso entre 1,88 e 5,41 mm na semeadura direta; entre 3,88 e 8,30 mm no preparo convencional; e entre 8,99 e 17,45 mm no cultivo mínimo. Concluiu-se que: as operações de preparo do solo aumentaram a rugosidade da sua superfície, em geral; o cultivo mínimo foi o sistema de preparo do solo que proporcionou os maiores valores de rugosidade ao acaso; e nos tratamentos semeadura direta com cobertura do solo a ação da chuva não promoveu decaimento do microrrelevo do solo.<br>Soil roughness is influenced by soil management, particularly by soil tillage and mainly reduced by rainfall action. This study aimed to evaluate the influence of different systems of soil management and artificial rainfall application on soil surface roughness. The treatments were a result of the combination of three systems: no-tillage, conventional tillage and minimum tillage, with three levels of dry soybean (Glycine max L. Merrill): residue: 0; 2; and 4 Mg ha-1. Experimental units received artificial rain (seven rains), at an intensity of 60 mm h-1 and during 60 min each, amounting to 420 mm rain. Roughness was evaluated immediately before and after tilling and immediately after the rainfalls. Roughness values between 1.88 and 5.41 mm were found under no-tillage, 3.88 and 8.30 mm under conventional tillage, and 3.31 and 17.45 mm under minimum tillage. It was concluded that soil tillage operations generally increased surface roughness. Values of random roughness were highest under minimum tillage; rain did not deteriorate the soil microrelief in the no-tillage treatments with soil cover