Comprehensive utilization of residues of Magnolia officinalis based on fiber characteristics

Journal of Material Cycles and Waste Management - The traditional Chinese medicinal plant Magnolia officinalis has a wide range of applications; including more than 200 kinds of patented Chinese...     

Processing and Morphology Impacts on Mechanical Properties of Fungal Based Biopolymer Composites

Fungal based biopolymer matrix composites with lignocellulosic agricultural waste as the filler are a viable alternative for some applications of synthetic polymers. This research provides insight into the impact of the processing method and composition of agriwaste/fungal biopolymer composites on structure and mechanical properties. The impact of nutrition during inoculation and after a homogenization step on the three-point bend flexural modulus and strength was determined. Increasing supplemental nutrition at inoculation had little effect on the overall composite strength or modulus; however, increasing carbohydrate loading after a homogenization step increased flexural stress at yield and bulk flexural modulus. The contiguity of the network formed was notably higher in the latter scenario, suggesting that the increase in modulus and strength of the final composite after homogenization was the result of contiguous hyphal network formation, which improves the integrity of the matrix and the ability to transfer load to the filler particles.     

Characterizing spatial structure of sediment E. coli populations to inform sampling design

Escherichia coli can persist in streambed sediments and influence water quality monitoring programs through their resuspension into overlying waters. This study examined the spatial patterns in E. coli concentration and population structure within streambed morphological features during baseflow and following stormflow to inform sampling strategies for representative characterization of E. coli populations within a stream reach. E. coli concentrations in bed sediments were significantly different (p?=?0.002) among monitoring sites during baseflow, and significant interactive effects (p?=?0.002) occurred among monitoring sites and morphological features following stormflow. Least absolute shrinkage and selection operator (LASSO) regression revealed that water velocity and effective particle size (D ₁₀) explained E. coli concentration during baseflow, whereas sediment organic carbon, water velocity and median particle diameter (D ₅₀) were important explanatory variables following stormflow. Principle Coordinate Analysis illustrated the site-scale differences in sediment E. coli populations between disconnected stream segments. Also, E. coli populations were similar among depositional features within a reach, but differed in relation to high velocity features (e.g., riffles). Canonical correspondence analysis resolved that E. coli population structure was primarily explained by spatial (26.9–31.7 %) over environmental variables (9.2–13.1 %). Spatial autocorrelation existed among monitoring sites and morphological features for both sampling events, and gradients in mean particle diameter and water velocity influenced E. coli population structure for the baseflow and stormflow sampling events, respectively. Representative characterization of streambed E. coli requires sampling of depositional and high velocity environments to accommodate strain selectivity among these features owing to sediment and water velocity heterogeneity.     

Drought,water access,and urban agriculture: a case study from Silicon Valley

In California, the growing popularity of urban agriculture (UA) has unfolded against a backdrop of historic drought. While UA is often celebrated as an urban sustainability strategy, it must be able to persist during drought if it is to perform these functions. Using Santa Clara County – the geographic core of Silicon Valley – as a case study, we use interviews and surveys to explore the implications of drought for UA. We show how developing an understanding of water access for UA during a drought requires examining the social and institutional context of water management and use. In metropolitan California, the highly decentralised water supply system combined with the diverse institutional arrangements that support UA create an uneven landscape of water access. Consequently, the pressure to change water-consuming practices – that is, the stress that institutional drought responses place on different water users – is geographically and socially differentiated. Among UA water users, responses to drought have also varied, in part because the possibilities for change are constrained by the sociotechnical arrangements of UA sites and the different purposes of UA.     

Designing and Implementing a Network for Sensing Water Quality and Hydrology across Mountain to Urban Transitions

Water resources are increasingly impacted by growing human populations, land use, and climate changes, and complex interactions among biophysical processes. In an effort to better understand these factors in semiarid northern Utah, United States, we created a real‐time observatory consisting of sensors deployed at aquatic and terrestrial stations to monitor water quality, water inputs, and outputs along mountain to urban gradients. The Gradients Along Mountain to Urban Transitions (GAMUT) monitoring network spans three watersheds with similar climates and streams fed by mountain winter‐derived precipitation, but that differ in urbanization level, land use, and biophysical characteristics. The aquatic monitoring stations in the GAMUT network include sensors to measure chemical (dissolved oxygen, specific conductance, pH, nitrate, and dissolved organic matter), physical (stage, temperature, and turbidity), and biological components (chlorophyll‐a and phycocyanin). We present the logistics of designing, implementing, and maintaining the network; quality assurance and control of numerous, large datasets; and data acquisition, dissemination, and visualization. Data from GAMUT reveal spatial differences in water quality due to urbanization and built infrastructure; capture rapid temporal changes in water quality due to anthropogenic activity; and identify changes in biological structure, each of which are demonstrated via case study datasets.     

Twentieth century droughts and agriculture: Examples from impacts on soybean production in Kentucky,USA

Drought is a significant natural hazard that slowly evolves over time. Because of its character, drought is difficult to monitor and impacts are often poorly documented. Agriculture is one of the most sensitive sectors that are prone to drought. The objective of this research is to assess the impacts of drought on soybean production and revenue in Kentucky. Soybeans are one of Kentucky’s most important commodities. In this study, impacts of 1930–1931, 1940–1942, 1952–1955, 1987–1988, 1999–2000, and 2007 droughts were considered. It was found that over the recent years, up to 56 % of the revenue from soybeans was lost due to drought. During the first half of the twentieth century, revenue loss reached up to 77 %. This research is valuable to the general public as well as planners and policy makers. Proper documentation of impacts of past droughts will help identify drought vulnerabilities and results in better risk management and mitigation.     

Development of a new risk-based framework to guide investment in water quality monitoring

An innovative framework for optimising investments in water quality monitoring has been developed for use by water and environmental agencies. By utilising historical data, investigating the accuracy of monitoring methods and considering the risk tolerance of the management agency, this new methodology calculates optimum water quality monitoring frequencies for individual water bodies. Such information can be applied to water quality constituents of concern in both engineered and natural water bodies and will guide the investment of monitoring resources. Here we present both the development of the framework itself and a proof of concept by applying it to the occurrence of hazardous cyanobacterial blooms in freshwater lakes. This application to existing data demonstrates the robustness of the approach and the capacity of the framework to optimise the allocation of both monitoring and mitigation resources. When applied to cyanobacterial blooms in the Swan Coastal Plain of Western Australia, we determined that optimising the monitoring regime at individual lakes could greatly alter the overall monitoring schedule for the region, rendering it more risk averse without increasing the amount of monitoring resources required. For water resources with high-density temporal data related to constituents of concern, a similar reduction in risk may be observed by applying the framework.     

Trait space of rare plants in a fire‐dependent ecosystem

The causes of species rarity are of critical concern because of the high extinction risk associated with rarity. Studies examining individual rare species have limited generality, whereas trait‐based approaches offer a means to identify functional causes of rarity that can be applied to communities with disparate species pools. Differences in functional traits between rare and common species may be indicative of the functional causes of species rarity and may therefore be useful in crafting species conservation strategies. However, there is a conspicuous lack of studies comparing the functional traits of rare species and co‐occurring common species. We measured 18 important functional traits for 19 rare and 134 common understory plant species from North Carolina's Sandhills region and compared their trait distributions to determine whether there are significant functional differences that may explain species rarity. Flowering, fire, and tissue‐chemistry traits differed significantly between rare and common, co‐occurring species. Differences in specific traits suggest that fire suppression has driven rarity in this system and that changes to the timing and severity of prescribed fire may improve conservation success. Our method provides a useful tool to prioritize conservation efforts in other systems based on the likelihood that rare species are functionally capable of persisting.