Considerations for Manufacturing Bio-Based Plastic Products

One engine that drives the United States’ economic growth is an ever-increasing demand for manufactured products, both at home and abroad. This increase has created a major concern for the environment in terms of disposing used goods and ensuring that these products are safe. As environmental concerns grow, however, renewable resources are gaining increasing attention, especially as industrial ecology and product biodegradability gain importance. Added to this, biological materials are increasingly being utilized to replace traditional materials in manufacturing. To aid both educators as well as researchers, this paper examines several considerations that are essential for manufacturing plastic products that contain biomaterials. These include the selection of materials, the selection of manufacturing processes, manufacturing costs, and the quality of final products. Additionally, several standard methods that are commonly used for the determination of mechanical and physical properties are compiled; thus this paper should be a useful resource for both educators and researchers. The trends discussed here and their implications are critical for those involved in manufacturing, because contrary to conventional wisdom, simultaneously meeting the material production needs of our society, as well as that of the environment are not mutually-exclusive.     

Hot Spots of Perforated Forest in the Eastern United States

National assessments of forest fragmentation satisfy international biodiversity conventions, but they do not identify specific places where ecological impacts are likely. In this article, we identify geographic concentrations (hot spots) of forest located near holes in otherwise intact forest canopies (perforated forest) in the eastern United States, and we describe the proximate causes in terms of the nonforest land-cover types contained in those hot spots. Perforated forest, defined as a 0.09-ha unit of forest that is located at the center of a 7.29-ha neighborhood containing 60–99% forest with relatively low connectivity, was mapped over the eastern United States by using land-cover maps with roads superimposed. Statistically significant (P < 0.001) hot spots of high perforation rate (perforated area per unit area of forest) were then located by using a spatial scan statistic. Hot spots were widely distributed and covered 20.4% of the total area of the 10 ecological provinces examined, but 50.1% of the total hot-spot area was concentrated in only two provinces. In the central part of the study area, more than 90% of the forest edge in hot spots was attributed to anthropogenic land-cover types, whereas in the northern and southern parts it was more often associated with seminatural land cover such as herbaceous wetlands.     

Implications of different population model structures for management of threatened plants

Population viability analysis (PVA) is a reliable tool for ranking management options for a range of species despite parameter uncertainty. No one has yet investigated whether this holds true for model uncertainty for species with complex life histories and for responses to multiple threats. We tested whether a range of model structures yielded similar rankings of management and threat scenarios for 2 plant species with complex postfire responses. We examined 2 contrasting species from different plant functional types: an obligate seeding shrub and a facultative resprouting shrub. We exposed each to altered fire regimes and an additional, species‐specific threat. Long‐term demographic data sets were used to construct an individual‐based model (IBM), a complex stage‐based model, and a simple matrix model that subsumes all life stages into 2 or 3 stages. Agreement across models was good under some scenarios and poor under others. Results from the simple and complex matrix models were more similar to each other than to the IBM. Results were robust across models when dominant threats are considered but were less so for smaller effects. Robustness also broke down as the scenarios deviated from baseline conditions, likely the result of a number of factors related to the complexity of the species’ life history and how it was represented in a model. Although PVA can be an invaluable tool for integrating data and understanding species’ responses to threats and management strategies, this is best achieved in the context of decision support for adaptive management alongside multiple lines of evidence and expert critique of model construction and output.     

Comparison and Evaluation of Gridded Precipitation Datasets in a Kansas Agricultural Watershed Using SWAT

Gridded precipitation datasets are becoming a convenient substitute for gauge measurements in hydrological modeling; however, these data have not been fully evaluated across a range of conditions. We compared four gridded datasets (Daily Surface Weather and Climatological Summaries [DAYMET], North American Land Data Assimilation System [NLDAS], Global Land Data Assimilation System [GLDAS], and Parameter‐elevation Regressions on Independent Slopes Model [PRISM]) as precipitation data sources and evaluated how they affected hydrologic model performance when compared with a gauged dataset, Global Historical Climatology Network‐Daily (GHCN‐D). Analyses were performed for the Delaware Watershed at Perry Lake in eastern Kansas. Precipitation indices for DAYMET and PRISM precipitation closely matched GHCN‐D, whereas NLDAS and GLDAS showed weaker correlations. We also used these precipitation data as input to the Soil and Water Assessment Tool (SWAT) model that confirmed similar trends in streamflow simulation. For stations with complete data, GHCN‐D based SWAT‐simulated streamflow variability better than gridded precipitation data. During low flow periods we found PRISM performed better, whereas both DAYMET and NLDAS performed better in high flow years. Our results demonstrate that combining gridded precipitation sources with gauge‐based measurements can improve hydrologic model performance, especially for extreme events.