Well-managed grazing systems: A forgotten hero of conservation

Ecologically sound grazing management is an underused and underappreciated conservation tool in the eastern United States. We contend that significant policy and educational barriers stand in the way of expanding the use of this conservation tool. Well-managed pasture systems combine vigorous perennial vegetation cover, reduced pesticide and fertilizer inputs, and lower costs of production using ecological approaches to generate ecosystem services for society, as well as economic sustainability for the producer. The majority of currently available conservation policy tools were designed to address either rangeland grazing situations in the western United States or conservation cropping in the eastern United States. To promote well-managed pastures in the eastern United States, resource managers and government agencies struggle to adapt programs that are really designed for annual row crop systems. Additional educational and technical assistance resources are needed for promoting well-managed pasture-based farming in the region. This paper summarizes the potential of well-managed pasture systems to provide ecosystem services, provides thoughts for discussion on the barriers to adoption of such systems in the eastern United States, and offers some solutions to move such systems forward through policy and educational efforts. These ideas were first presented at a symposium as part of the 2011 Annual Conference of the Soil and Water Conservation Society in Washington, DC

MAGGnet : an international network to foster mitigation of agricultural greenhouse gases

Liebig, M. A. USDA-ARS, Mandan, ND, USA.Franzluebbers, A. J. USDA-ARS, Raleigh, NC, USA.Alvarez, C. Instituto Nacional de Tecnología Agropecuaria (INTA). Centro Regional Córdoba. Estación Experimental Agropecuaria Manfredi (EEA Manfredi). Córdoba, Argentina.Chiesa, T. D. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura (IFEVA). Buenos Aires, Argentina.Lewczuk, N. Instituto Nacional de Tecnología Agropecuaria (INTA). Buenos Aires, Argentina.Piñeiro, Gervasio. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura (IFEVA). Buenos Aires, Argentina.Posse, Graciela Noemí. Instituto Nacional de Tecnología Agropecuaria (INTA). Buenos Aires, Argentina.Yahdjian, María Laura. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura (IFEVA). Buenos Aires, Argentina.8Research networks provide a framework for review, synthesis and systematic testing of theories by multiple scientists across international borders critical for addressing global-scale issues. In 2012, a GHG research network referred to as MAGGnet (Managing Agricultural Greenhouse Gases Network) was established within the Croplands Research Group of the Global Research Alliance on Agricultural Greenhouse Gases (GRA). With involvement from 46 alliance member countries, MAGGnet seeks to provide a platform for the inventory and analysis of agricultural GHG mitigation research throughout the world. To date, metadata from 315 experimental studies in 20 countries have been compiled using a standardized spreadsheet. Most studies were completed (74%) and conducted within a 1-3-year duration (68%). Soil carbon and nitrous oxide emissions were measured in over 80% of the studies. Among plant variables, grain yield was assessed across studies most frequently (56%), followed by stover (35%) and root (9%) biomass. MAGGnet has contributed to modeling efforts and has spurred other research groups in the GRA to collect experimental site metadata using an adapted spreadsheet. With continued growth and investment, MAGGnet will leverage limited-resource investments by any one country to produce an inclusive, globally shared meta-database focused on the science of GHG mitigation

The moisture response of soil heterotrophic respiration: Interaction with soil properties

Soil moisture is of primary importance for predicting the evolution of soil carbon stocks and fluxes, both because it strongly controls organic matter decomposition and because it is predicted to change at global scales in the following decades. However, the soil functions used to model the heterotrophic respiration response to moisture have limited empirical support and introduce an uncertainty of at least 4% in global soil carbon stock predictions by 2100. The necessity of improving the representation of this relationship in models has been highlighted in recent studies. Here we present a data-driven analysis of soil moisture-respiration relations based on 90 soils. With the use of linear models we show how the relationship between soil heterotrophic respiration and different measures of soil moisture is consistently affected by soil properties. The empirical models derived include main effects and moisture interaction effects of soil texture, organic carbon content and bulk density. When compared to other functions currently used in different soil biogeochemical models, we observe that our results can correct biases and reconcile differences within and between such functions. Ultimately, accurate predictions of the response of soil carbon to future climate scenarios will require the integration of soil-dependent moisture-respiration functions coupled with realistic representations of soil water dynamic

Modeling perennial groundcover effects on annual maize grain crop growth with the Agricultural Production Systems sIMulator

The inclusion of perennial groundcover (PGC) in maize production offers a tenable solution to natural resources-related concerns associated with conventional maize; however, insight into system management and key information gaps is needed to guide future research. We therefore extended the Agricultural Production Systems sIMulator (APSIM) to an annual and perennial intercrop by integrating annual and perennial APSIM modules. These were parameterized for Kentucky bluegrass (KB) (Poa pratensis L.) or creeping red fescue (CF) (Festuca rubra L.) as PGC using a three-year dataset. Our objectives for this intercropping modeling study were to: i) simultaneously model a PGC and annual cash crop using APSIM software; ii) utilize APSIM to understand interactive processes in the maize-PGC system; and iii) utilize the calibrated model to explore both production and environmental benefits via scenario modeling. For objective I, the integrated model successfully predicted maize total aboveground biomass (TAB) (relative root mean square error, RRMSE of 13- 27%) and PGC above- and belowground tissue N concentration (RRMSE of 11-18%). The calibrated model effectively captured observed trends in PGC biomass accumulation and soil nitrate (NO3). For objective II, model analysis showed that competition for light was the primary maize yield penalty factor from PGC, while water and N impacted maize yield later in the maize growing season. In objective III, we concluded that effective PGC suppression produces minimal maize yield loss and significant environmental benefits; conversely, poor groundcover suppression may produce unfavorable environmental consequences and decrease maize grain yield. Effective PGC suppression is key for long-term system success

MAGGnet: an international network to foster mitigation of agricultural greenhouse gases.

Research networks provide a framework for review, synthesis and systematic testing of theories by multiple scientists across international borders critical for addressing global-scale issues. In 2012, a GHG research network referred to as MAGGnet (Managing Agricultural Greenhouse Gases Network) was established within the Croplands Research Group of the Global Research Alliance on Agricultural Greenhouse Gases (GRA). With involvement from 46 alliance member countries, MAGGnet seeks to provide a platform for the inventory and analysis of agricultural GHG mitigation research throughout the world. To date, metadata from 315 experimental studies in 20 countries have been compiled using a standardized spreadsheet. Most studies were completed (74%) and conducted within a 1-3-year duration (68%). Soil carbon and nitrous oxide emissions were measured in over 80% of the studies. Among plant variables, grain yield was assessed across studies most frequently (56%), followed by stover (35%) and root (9%) biomass. MAGGnet has contributed to modeling efforts and has spurred other research groups in the GRA to collect experimental site metadata using an adapted spreadsheet. With continued growth and investment, MAGGnet will leverage limited-resource investments by any one country to produce an inclusive, globally shared meta-database focused on the science of GHG mitigation

Land‐use intensity and biodiversity effects on infiltration capacity and hydraulic conductivity of grassland soils in southern Germany

Evidence from experimental and established grasslands indicates that plant biodiversity can modify the water cycle. One suspected mechanism behind this is a higher infiltration capacity (ν$_{B}$) and hydraulic conductivity (K) of the soil on species-rich grasslands. However, in established and agriculturally managed grasslands, biodiversity effects cannot be studied independent of land-use effects. Therefore, we investigated in established grassland systems how land-use intensity and associated biodiversity of plants and soil animals affect νB and K at and close to saturation. On 50 grassland plots along a land-use intensity gradient in the Biodiversity Exploratory Schwäbische Alb, Germany, we measured νB with a hood infiltrometer at several matrix potentials and calculated the saturated and unsaturated K. We statistically analysed the relationship between ν$_{B}$ or K and land-use information (e.g., fertilising intensity), abiotic (e.g., soil texture) and biotic data (e.g., plant species richness, earthworm abundance). Land-use intensity decreased and plant species richness increased ν$_{B}$ and K, while the direction of the effects of soil animals was inconsistent. The effect of land-use intensity on ν$_{B}$ and K was mainly attributable to its negative effect on plant species richness. Our results demonstrate that plant species richness was a better predictor of ν$_{B}$ and K at and close to saturation than land-use intensity or soil physical properties in the established grassland systems of the Schwäbische Alb