Water quality trading: credit stacking and ancillary benefits

Ecosystems can provide many services. Wetlands, for example, can help mitigate water pollution from point sources as well as non-point sources, serve as habitat for wildlife, sequester carbon and serve as a place for recreation. Studies have found that these services can have substantial value to society. The sale of ecosystem credits has been found to be a possible way to finance construction investments in wetlands and easements to farmers to take their land out of production. At the same time, selling one ecosystem service credit may not always be enough to justify the investment. Traditionally market participants have only been allowed to sell a single credit from one piece of land, but recently there have been discussions about the possibility of selling more than one credit from a piece of land because it potentially could lead to more efficient ecosystem service provision. Selling multiple credits is sometimes referred to as credit stacking. This paper is an empirical study of the potential for credit stacking applied to the services provided by wetlands in the Upper Mississippi River Basin, specifically nitrogen, phosphorus and wildlife credits. In the setting of our study where costs are discrete rather than continuous we found that wetlands are a cost-effective way to reduce the nitrogen loads from wastewater treatment plants and that stacking nitrogen, phosphorus and wildlife credits may improve social welfare while leading to a higher level of ecosystem services. However, for credit stacking to be welfare improving we found that there needs to be a substantial demand for the credit that covers the majority of the investment in wetlands, while the credit aggregator has a choice between what ecosystem projects to undertake. If the credit that covers the majority of investment is sold first and is the sole basis of the investment decision and the objective is to improve welfare, a sequential implementation of ecosystem credits is not recommended; it would not lead to an increase in the total amount of ecosystem services provided though it would increase profit for the credit producer.

Characterization of the effect of nitrogen deficiency on above-ground plant phenotypes in relation to root complexity in maize

Nitrogen (N) is an essential plant nutrient in maize production, and if considering only natural sources, is often the limiting factor world-wide in terms of a plant’s grain yield. For this reason, many farmers around the world supplement available soil N with synthetic man-made forms. Years of over-application of N fertilizer have led to increased N in groundwater and streams due to leaching and run-off from agricultural sites. In the Midwest Corn Belt much of this excess N eventually makes its way to the Gulf of Mexico leading to eutrophication (increase of phytoplankton) and a hypoxic (reduced oxygen) dead zone. Growing concerns about these types of problems and desire for greater input use efficiency have led to demand for crops with improved N use efficiency (NUE) to allow reduced N fertilizer application rates and subsequently lower N pollution. It is well known that roots are responsible for N uptake by plants, but it is relatively unknown how root architecture affects this ability. This research was conducted to better understand the influence of root complexity (RC) in maize on a plant’s response to N stress as well as the influence of RC on other above-ground plant traits. Thirty-one above-ground plant traits were measured for 64 recombinant inbred lines (RILs) from the intermated B73 & Mo17 (IBM) population and their backcrosses (BCs) to either parent, B73 and Mo17, under normal (182 kg N ha-1) and N deficient (0 kg N ha-1) conditions. The RILs were selected based on results from an earlier experiment by Novais et al. (2011) which screened 232 RILs from the IBM to obtain their root complexity measurements. The 64 selected RILs were comprised of 31 of the lowest complexity RILs (RC1) and 33 of the highest complexity RILs (RC2) in terms of root architecture (characterized as fractal dimensions). The use of the parental BCs classifies the experiment as Design III, an experimental design developed by Comstock and Robinson (1952) which allows for estimation of dominance significance and level. Of the 31 traits measured, 12 were whole plant traits chosen due to their documented response to N stress. The other 19 traits were ear traits commonly measured for their influence on yield. Results showed that genotypes from RC1 and RC2 significantly differ for several above-ground phenotypes. We also observed a difference in the number and magnitude of N treatment responses between the two RC classes. Differences in phenotypic trait correlations and their change in response to N were also observed between the RC classes. RC did not seem to have a strong correlation with calculated NUE (ΔYield/ΔN). Quantitative genetic analysis utilizing the Design III experimental design revealed significant dominance effects acting on several traits as well as changes in significance and dominance level between N treatments. Several QTL were mapped for 26 of the 31 traits and significant N effects were observed across the majority of the genome for some N stress indicative traits (e.g. stay-green). This research and related projects are essential to a better understanding of plant N uptake and metabolism. Understanding these processes is a necessary step in the progress towards the goal of breeding for better NUE crops.