National Soil Erosion Research Laboratory

West Lafayette, IN, United States

National Soil Erosion Research Laboratory

West Lafayette, IN, United States
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Da Silva A.M.,São Paulo State University | Huang C.H.,National Soil Erosion Research Laboratory | Francesconi W.,International Center for Tropical Agriculture | Saintil T.,Florida A&M University | Villegas J.,Northeastern Illinois University
Ecological Indicators | Year: 2015

Methods of recording soil erosion using photographs exist but they are not commonly considered in scientific studies. Digital images may hold an expressive amount of information that can be extracted quickly in different manners. The investigation of several metrics that were initially developed for landscape ecology analysis constitutes one method. In this study we applied a method of landscape metrics to quantify the spatial configuration of surface micro-topography and erosion-related features, in order to generate a possible complementary tool for environmental management. In a 3.7 m wide and 9.7 m long soil box used during a rainfall simulation study, digital images were systematically acquired in four instances: (a) when the soil was dry; (b) after a short duration rain for initial wetting; (c) after the first erosive rain; and (d) after the 2nd erosive rain. Thirteen locations were established in the box and digital photos were taken at these locations with the camera positioned at the same orthogonal distance from the soil surface under the same ambient light intensity. Digital photos were converted into bimodal images and seven landscape metrics were analyzed: percentage of land, number of patches, density of patches, largest patch index, edge density, shape index, and fractal dimension. Digital images were an appropriate tool because they can generate data very quickly. The landscape metrics were sensitive to changes in soil surface micro-morphology especially after the 1st erosive rain event, indicating significant erosional feature development between the initial wetting and first erosive rainfall. The method is considered suitable for spatial patterns of soil micro-topography evolution from rainfall events that bear similarity to landscape scale pattern evolution from eco-hydrological processes. Although much more study is needed for calibrating the landscape metrics at the micro-scale, this study is a step forward in demonstrating the advantages of the method. © 2015 Elsevier Ltd. All rights reserved.

Francesconi W.,Ziegler | Francesconi W.,National Soil Erosion Research Laboratory | Nair P.K.R.,Ziegler | Levey D.J.,University of Florida | And 3 more authors.
Agroforestry Systems | Year: 2013

Agroforestry practices, such as Shaded Coffee and Homegardens, may provide habitat for forest butterflies and contribute to their conservation in fragmented agricultural landscapes. To determine the influence of agroforestry practices in an agricultural mosaic, the distribution of fruit-feeding butterflies was studied using a systematic approach that compared butterfly species richness in six land-use practices (Eucalyptus [Eucalyptus spp.], Shaded Coffee, Homegardens, Secondary Growth, Pastures, and monocultures of Cassava [Manihot esculenta] and Sugarcane [Saccharum officinarum]), and in natural habitat (secondary Forest Edge and Interior) in two study areas (agricultural landscapes). In each study area, Van Someren-Rydon butterfly traps were placed as a grid every 150 m, creating quadrants of 2.2 and 2.4 km2 that encompassed the different land-use practices. Land-use, plot area, number of traps and distance to the forest were set as covariates to compare species richness values. Butterfly species composition was compared using linear discriminant analysis (LDA). With the exception of Pastures, Cassava and Sugarcane, significant differences were not identified between the rest of the agricultural land-use practices and the forest habitats (edge and interior). The species composition in the agricultural practices was however, different to that found in forest habitats. Overall, Shaded Coffee practices that represent long-term mixed tree and crop stands have a better potential of conserving forest butterfly species compared to monoculture practices. © 2013 Springer Science+Business Media Dordrecht.

Radcliffe D.E.,University of Georgia | Keith Reid D.,Agriculture and Agri Food Canada | Blomback K.,Swedish University of Agricultural Sciences | Bolster C.H.,U.S. Department of Agriculture | And 14 more authors.
Journal of Environmental Quality | Year: 2015

Most phosphorus (P) modeling studies of water quality have focused on surface runoff loses. However, a growing number of experimental studies have shown that P losses can occur in drainage water from artificially drained fields. In this review, we assess the applicability of nine models to predict this type of P loss. A model of P movement in artificially drained systems will likely need to account for the partitioning of water and P into runoff, macropore flow, and matrix flow. Within the soil profile, sorption and desorption of dissolved P and filtering of particulate P will be important. Eight models are reviewed (ADAPT, APEX, DRAINMOD, HSPF, HYDRUS, ICECREAMDB, PLEASE, and SWAT) along with P Indexes. Few of the models are designed to address P loss in drainage waters. Although the SWAT model has been used extensively for modeling P loss in runoff and includes tile drain flow, P losses are not simulated in tile drain flow. ADAPT, HSPF, and most P Indexes do not simulate flow to tiles or drains. DRAINMOD simulates drains but does not simulate P. The ICECREAMDB model from Sweden is an exception in that it is designed specifically for P losses in drainage water. This model seems to be a promising, parsimonious approach in simulating critical processes, but it needs to be tested. Field experiments using a nested, paired research design are needed to improve P models for artificially drained fields. Regardless of the model used, it is imperative that uncertainty in model predictions be assessed. © American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America.

Francesconi W.,International Center for Tropical Agricuture | Smith D.R.,Soil and Water Research Laboratory | Flanagan D.C.,National Soil Erosion Research Laboratory | Huang C.-H.,National Soil Erosion Research Laboratory | Wang X.,Texas A&M University
Journal of Great Lakes Research | Year: 2015

Evaluation of USDA conservation programs are required as part of the Conservation Effects Assessment Project (CEAP). The Agricultural Policy/Environmental eXtender (APEX) model was applied to the St. Joseph River watershed, one of CEAP's benchmark watersheds. Using a previously calibrated and validated APEX model, the simulation of various conservation practices (single and combined) was conducted at the field scale. Seven variables [runoff, sediment, total phosphorus (TP), dissolved reactive phosphorus (DRP), soluble nitrogen (SN), tile flow, and soluble nitrogen in tile (SN-Tile)], were compared between the simulated practices. The field-scale outputs were extrapolated to the areas encompassed by the different conservation practices at the watershed scale. The speculative estimations are presented as percentage reductions compared to the baseline scenario. When single conservation practices were implemented, reductions were 39% for sediment, 7% for TP, and 24% for SN-Tile. In contrast, losses of DRP and SN increased by 5% and 57%, respectively. When the conservation practices were combined, percentage reductions increased for all variables. The total reductions for combined two and three practices were 68% and 91% for sediments, 35% and 74% for TP, 1% and 48% for DRP, -. 43% and 28% for SN, and 50% and 85% for SN-Tile. Negative reductions were due to the slightly higher DRP and SN loads in no-till, mulch-till, and conservation crop rotation practices, and their greater extent of incorporation at the watershed scale. Overall, the cumulative and combined effects of field conservation practices can help address the watershed's excess nutrient and sediment concerns and improve water quality. © 2015.

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