Economic assessment of dredging operations in Mobile Bay,USA and some additional notes on sustainable management of dredged material

This paper describes a study that was performed to determine the cost-effective method of dredging in Mobile Bay in the United States and to explore the possibility of utilizing the dredged materials in an environmentally sustainable way. An analysis of the historical cost and working time data for hopper dredging and pipeline dredging for Mobile Bay showed that there was not a substantial difference in unit costs between the two methods. However, while the disposal methods for dredged materials were taken into consideration, the pipeline dredging seemed to be a more desirable and environmentally friendly option for dredging in Mobile Bay. In addition to cost analysis, the paper discusses several possible ways of sustainable management of dredged materials. The paper also indicates that if the sediment in Mobile Bay is found to be contaminated by the Deepwater Horizon oil spill, the pipeline dredging will become a more desirable dredging alternative.     

Bio-Based Polymers and End-of-Life Vehicles

As new materials, such as bio-based plastics and composites, are introduced in vehicles for their improved environmental performance, it is necessary to understand how to efficiently recover these biodegradable materials. This paper provides an overview of the end-of-life phase for automobiles, focusing on the dismantling and shredding processes, and the recovery of materials. Targeted unit operations, such as dismantling of components from vehicles and pretreatment prior to shredding, along with design-for-environment principles, should enable the efficient recovery of materials at the end-of-life phase compared with popularly conceived all-in-one-approaches because of the diverse arrangement of material components.     

The adaptation and control model of user needs: A new direction for housing research

The Canadian context of user needs research in housing is briefly outlined. The Needs and Preferences research model is described and three basic assumptions are outlined. Challenges to the three assumptions are identified, and two empirical studies are invoked to substantiate the critique. An Adaptation and Control Model of user needs research in housing is presented as a possible alternative model that has implications for methodological change and refinement. The opinion is advanced that this model potentially remedies some of the shortcomings of the Needs and Preferences Model.     

GOLD-MINING EFFECTS ON HEAVY METALS IN STREAMS,CIRCLE QUADRANGLE,ALASKA1

Placer gold mining, which extracts gold from buried or exposed alluvia, is often conducted on or near streams. Such mining has the potential to adversely affect water quality. Other heavy metals associated with the gold (such as arsenic, cadmium, lead, zinc, and copper) may be freed to enter streams. Mercury may also enter streams if miners are using it to recover fine particles of gold. These heavy metals are toxic and thus may be harmful to the aquatic life of the streams receiving effluent or runoff from placer mines. In 1982 we sampled two streams intensively - one heavily mined and one unmined - for total recoverable arsenic, mercury, lead, zinc, and copper. Only mercury was not significantly higher in concentration in the mined streams. In 1983 we sampled two stream pairs three times, and 10 other sites at least once, for total and dissolved arsenic, cadmium, mercury, lead, zinc, and copper. Mercury and cadmium were not significantly elevated in mined streams, but the concentrations of total arsenic, lead, zinc, and copper, and dissolved arsenic and zinc were significantly higher in streams below active placer mining sites than in these that were not being mined or those that had never been mined. Additionally, total arsenic, lead, zinc, and copper and dissolved arsenic and copper became elevated after mining began in 1983 on a previously unmined stream.     

Scouts behave as streakers in honeybee swarms

Harmonic radar tracking was used to record the flights of scout bees during takeoff and initial flight path of two honeybee swarms. One swarm remained intact and performed a full flight to a destination beyond the range of the harmonic radar, while a second swarm disintegrated within the range of the radar and most of the bees returned to the queen. The initial stretch of the full flight is characterized by accelerating speed, whereas the disintegrating swarm flew steadily at low speed. The two scouts in the swarm displaying full flight performed characteristic flight maneuvers. They flew at high speed when traveling in the direction of their destination and slowed down or returned over short stretches at low speed. Scouts in the disintegrating swarm did not exhibit the same kind of characteristic flight performance. Our data support the streaker bee hypothesis proposing that scout bees guide the swarm by traveling at high speed in the direction of the new nest site for short stretches of flight and slowing down when reversing flight direction.     

Dominance of the odometer over serial landmark learning in honeybee navigation

Honeybees use their visual flow field to measure flight distance. It has been suggested that the experience of serial landmarks encountered on the flight toward a feeding place contributes to distance estimation. Here, we address this question by tracing the flight paths of individual bees with a harmonic radar system. Bees were trained along an array of three landmarks (tents), and the distance between these landmarks was either increased or decreased under two test conditions. We find that absolute distance estimation dominates the search for the feeding place, but serial position effects are also found. In the latter case, bees search only or additionally at locations determined by serial experience of the landmarks.     

How have we,do we,and will we measure time perspective? A review of methodological and measurement issues

Despite the demonstrated importance of time perspective on key outcomes, its growing popularity, and its wide reach in terms of samples and disciplines, the construct has been plagued with definitional and measurement problems since its inception. Given the historical and current confusion regarding both conceptualization and operationalization, the purpose of this article is to provide an overview of methodological and measurement issues related to time perspective. Clearly, definitional and measurement clarity are critical for the success of future research. Through integrating the fragmented and eclectic time perspective literature fraught with ambiguity, we help to clarify measurement options and their psychometric evidence for future researchers. Specifically, we provide an in-depth comparison of four (and their offshoots) commonly used, scale-based measures of time perspective with respect to their dimensional content, psychometric properties, and validation evidence. We end with recommendations for time perspective research.     

An introduction to decision science for conservation

Biodiversity conservation decisions are difficult, especially when they involve differing values, complex multidimensional objectives, scarce resources, urgency, and considerable uncertainty. Decision science embodies a theory about how to make difficult decisions and an extensive array of frameworks and tools that make that theory practical. We sought to improve conceptual clarity and practical application of decision science to help decision makers apply decision science to conservation problems. We addressed barriers to the uptake of decision science, including a lack of training and awareness of decision science; confusion over common terminology and which tools and frameworks to apply; and the mistaken impression that applying decision science must be time consuming, expensive, and complex. To aid in navigating the extensive and disparate decision science literature, we clarify meaning of common terms: decision science, decision theory, decision analysis, structured decision-making, and decision-support tools. Applying decision science does not have to be complex or time consuming; rather, it begins with knowing how to think through the components of a decision utilizing decision analysis (i.e., define the problem, elicit objectives, develop alternatives, estimate consequences, and perform trade-offs). This is best achieved by applying a rapid-prototyping approach. At each step, decision-support tools can provide additional insight and clarity, whereas decision-support frameworks (e.g., priority threat management and systematic conservation planning) can aid navigation of multiple steps of a decision analysis for particular contexts. We summarize key decision-support frameworks and tools and describe to which step of a decision analysis, and to which contexts, each is most useful to apply. Our introduction to decision science will aid in contextualizing current approaches and new developments, and help decision makers begin to apply decision science to conservation problems.     

Integrated spatiotemporal trends using TRMM 3B42 data for the Upper São Francisco River basin,Brazil

Trend analysis is an important issue for the decision-making processes. Thus, trends of rainfall, consecutive dry days (CDD), and consecutive wet days (CWD) in the Upper São Francisco River basin, Brazil, using daily rainfall data from the Tropical Rainfall Measuring Mission (TRMM) for recent 18 years, were analyzed. Instead of analyzing the trend of one average time series for one specific confidence level, a spatiotemporal analysis over the entire area with 169 continuous time series is done by applying the nonparametric Mann-Kendall and Sen tests for simultaneously 13 confidence levels and a new integrated confidence classification is proposed. The results show that the rainfall has increased during the less rainy periods (from June to October) and has decreased in the rainy periods (from November to May), with the highest and lowest confidence levels, respectively. An analysis of CDD and CWD shows that the number of CDD has decreased, while the number of CWD has increased, which revealed that the dry periods are more frequently interrupted for the period studied.     

Sediment quality triad assessment of an industrialized estuary of the northeastern USA

The lower Passaic River in northern New Jersey (USA) has been heavily industrialized since the mid-nineteenth century and its shoreline and aquatic habitats degraded or destroyed. Similar to other urban systems, Passaic River sediments, both surface and buried, historically have contained elevated levels of numerous contaminants that may pose risks to ecological receptors and humans. Sediments from 15 stations in the lower Passaic River and 3 reference stations in the Mullica River in southern New Jersey were sampled in 1999 and characterized for chemical contamination, toxicity, and impairment of the benthic community. The objective of this study was to determine the incidence, degree, and nature of degraded surficial sediments in the area to support subsequent plans for restoration of the system. Results demonstrated that Passaic River sediments had concentrations of many organic and inorganic contaminants at levels significantly greater than the reference area and effect-based guidelines. Sediments were toxic to marine amphipods at 11 stations and the benthic assemblages were impaired relative to the reference area at all stations. The weight-of-evidence of this sediment quality triad (SQT) assessment indicates that impacts from multiple contaminants are occurring throughout the lower Passaic River and, that these impacts must be evaluated further and addressed as part of ongoing restoration initiatives for the river.