Analysis of historical changes in soil fertility and organic matter levels of the North American Great Plains

Non-Peer Reviewe

Evaluating Sensitivities of Economic Factors through Coupled Economics-ALMANAC Model System

Using crop models to simulate crop growth and productivity at a regional scale is a complex process designed to represent the observed impact of individual farmer decision-making on the agricultural landscape. Typically, during agricultural simulation efforts, the planting acreages have largely been based on a set of predetermined, static scenarios. In this study, we developed a system to dynamically enhance the Agricultural Land Management Alternative with Numerical Assessment Criteria (ALMANAC) crop simulation model through a two-way linkage with an economics land-use model. This coupled model approach integrated farmers’ land-use choices based on relative economic returns and produced dynamic land-use probabilities for ALMANAC simulations through a feedback loop. The coupled model approach was intercompared with static crop modeling through a historic acreage approach, and comparable accuracies were found from both modeling efforts for the 2014 growing season. Furthermore, as a proof-of-concept effort, the method was applied to evaluate the impact of two scenarios on crop simulations: major crops (maize, soybean, and wheat) intensification through price increases (e.g., market change) and incentivized grassland conservation (e.g., policy change). The results of this sensitivity study suggest that the coupled system has the capability to integrate economic factors into traditional crop simulation, allowing for insight into the impacts of changes in markets and policies on agricultural landscapes and crop yields

Modeling soil CO2 emissions from ecosystems

We present a new soil respiration model, describe a formal model testing procedure, and compare our model with five alternative models using an extensive data set of observed soil respiration. Gas flux data from rangeland soils that included a large number of measurements at low temperatures were used to model soil CO2 emissions as a function of soil temperature and water content. Our arctangent temperature function predicts that Q10 values vary inversely with temperature and that CO2 fluxes are significant below 0 °C. Independent data representing a broad range of ecosystems and temperature values were used for model testing. The effects of plant phenology, differences in substrate availability among sites, and water limitation were accounted for so that the temperature equations could be fairly evaluated. Four of the six tested models did equally well at simulating the observed soil CO2 respiration rates. However, the arctangent variable Q10 model agreed closely with observed Q10 values over a wide range of temperatures (r2 = 0.94) and was superior to published variable Q10 equations using the Akaike information criterion (AIC). The arctangent temperature equation explained 16–85% of the observed intra-site variability in CO2 flux rates. Including a water stress factor yielded a stronger correlation than temperature alone only in the dryland soils. The observed change in Q10 with increasing temperature was the same for data sets that included only heterotrophic respiration and data sets that included both heterotrophic and autotrophic respiration

Generalized model for N2 and N20 production from nitrification and denitrification

Eripainos MKF:llävo

Greenhouse gas mitigation potential of the world’s grazing lands: Modeling soil carbon and nitrogen fluxes of mitigation practices

This study provides estimates of the net GHG mitigation potential of a selected range of management practices in the world’s native and cultivated grazing lands. The Century and Daycent models are used to calculate the changes in soil carbon stocks, soil N2O emissions, and forage removals by ruminants associated with these practices. GLEAM is used in combination with these models to establish grazing area boundaries and to parameterize links between forage consumption, animal production and animal GHG emissions. This study provides an alternative to the usual approach of extrapolating from a small number of field studies and by modeling the linkage between soil, forage and animals it sheds new light on the net mitigation potential of C sequestration practices in the world’s grazing lands. Three different mitigation practices are assessed in this study, namely, improved grazing management, legume sowing and N fertilization. We estimate that optimization of grazing pressure could sequester 148 Tg CO2 yr−1. The soil C sequestration potential of 203 Tg CO2 yr−1 for legume sowing was higher than for improved grazing management, despite being applied over a much smaller total area. However, N2O emissions from legumes were estimated to offset 28% of its global C sequestration benefits, in CO2 equivalent terms. Conversely, N2O emissions from N fertilization exceeded soil C sequestration, in all regions. Our estimated potential for increasing C stocks though in grazing lands is lower than earlier worldwide estimates (Smith et al., 2007 and Lal, 2004), mainly due to the much smaller grazing land area over which we estimate mitigation practices to be effective. A big concern is the high risk of the practices, particularly legumes, increasing soil-based GHGs if applied outside of this relatively small effective area. More work is needed to develop indicators, based on biophysical and management characteristics of grazing lands, to identify amenable areas before these practices can be considered ready for large scale implementation. The additional ruminant GHG emissions associated with higher forage output are likely to substantially reduce the mitigation potential of these practices, but could contribute to more GHG-efficient livestock production