This manuscript reports on the change in the undergraduate Agronomy student population at Iowa State University since instigating a marketing campaign. The most important elements in the development of the marketing campaign were a simple message, artistic style, branding, and advertising in smart locations. After four years, one hundred and six more students were studying Agronomy, which was an increase of 91%.
We estimated the pre-settlement density and area of different classes of palustrine wetlands on the Des Moines Lobe based on soil characteristics. Prior to drainage, wetlands covered nearly half of the Des Moines Lobe and there were differences in both the types and relative abundance of wetlands among the four geologic subdivisions of the Lobe (Bemis, Altamont, and Algona till plains and Altamont Lake).
The integration of soil survey maps with Geographic Information Systems (GIS) allows for an almost infinite level of collaboration across disciplines that use information related to soil databases. This study created a Quaternary geologic map by categorizing soil descriptions into a geologic context and joining the attributes with the Soil Survey Geographic (SSURGO) database in ArcGIS®. The resulting map communicates many of the spatial intricacies of the Des Moines Lobe landform with 15 map units based on geologic units.
Nitrate concentration and stream discharge data from USGS National Stream Quality Accounting Network monitoring stations in the upper Mississippi River (UMR) and Ohio River basins were used to calculate stream nitrate loading and annual flow-weighted average (FWA) nitrate concentrations. The model accounts for 90% of the variation among stations in long term FWA nitrate concentrations and was used to estimate FWA nitrate concentrations for a 100 ha grid across the UMR and Ohio River basins. To estimate potential nitrate removal by wetlands across the same grid area, mass balance simulations were used to estimate percent nitrate reduction for hypothetical wetland sites distributed across the UMR and Ohio River basins. Modeling results suggest that a 30% reduction in nitrate load from the UMR and Ohio River basins could be achieved using 210,000-450,000 ha of wetlands targeted on the highest nitrate contributing areas.