A novel framework for analysis of cross-media environmental effects from agricultural conservation practices

Agricultural ecosystems are a source of greenhouse gas (GHGs) emissions and losses of nutrients to waterways. Several studies have recognized this and have documented the potential to reduce GHG fluxes and nutrient loss to waterways by using carbon offsets to fund the implementation of land retirement and afforestation. However, the ability to use land for both agricultural production and environmental conservation is also important. This study develops a novel analytical framework that is used to examine the cross-media (water and air) environmental effects of implementing offset-funded conservation practices in a working-lands setting. The framework is applied to a case study which examines the extent to which carbon pricing can affect practice implementation costs and the optimal distribution of these practices throughout an agricultural watershed. Results indicate that carbon offsets can reduce conservation practice implementation costs and have the potential to reduce greater amounts of nonpoint source pollution for a given cost of implementation. This conclusion has significant implications for policymaking, particularly with regard to using markets for GHG emissions to achieve water quality improvements where water quality trading or government conservation programs have historically been unsuccessful.     

Modeling the impacts of temperature and precipitation changes on soil CO2 fluxes from a Switchgrass stand recently converted from cropland

Switchgrass(Panicum virgatum L.) is a perennial C_4 grass native to North America and successfully adapted to diverse environmental conditions. It offers the potential to reduce soil surface carbon dioxide(CO_2) fluxes and mitigate climate change. However, information on how these CO_2 fluxes respond to changing climate is still lacking. In this study, CO_2 fluxes were monitored continuously from 2011 through 2014 using high frequency measurements from Switchgrass land seeded in 2008 on an experimental site that has been previously used for soybean(Glycine max L.) in South Dakota, USA. DAYCENT, a process-based model, was used to simulate CO_2 fluxes. An improved methodology CPTE[Combining Parameter estimation(PEST) with "Trial and Error" method] was used to calibrate DAYCENT. The calibrated DAYCENT model was used for simulating future CO_2 emissions based on different climate change scenarios. This study showed that:(i) the measured soil CO_2 fluxes from Switchgrass land were higher for 2012 which was a drought year, and these fluxes when simulated using DAYCENT for long-term(2015–2070) provided a pattern of polynomial curve;(ii) the simulated CO_2 fluxes provided different patterns with temperature and precipitation changes in a long-term,(iii) the future CO_2 fluxes from Switchgrass land under different changing climate scenarios were not significantly different, therefore, it can be concluded that Switchgrass grown for longer durations could reduce changes in CO_2 fluxes from soil as a result of temperature and precipitation changes to some extent.