Towards improving an Area of Concern: Main-channel habitat rehabilitation priorities for the Maumee River

The Maumee River watershed in the Laurentian Great Lakes Basin has been impacted by decades of pollution and habitat modification due to human settlement and development. As such, the lower 35 km of the Maumee River and several smaller adjacent watersheds comprising over 2000 km² were designated the Maumee Area of Concern (AOC) under the revised Great Lakes Water Quality Agreement in 1987. As part of pre-rehabilitation assessments in the Maumee AOC, we assessed fish and invertebrate communities in river km 24–11 of the Maumee River to identify: 1) areas that exhibit the highest biodiversity, 2) habitat characteristics associated with high biodiversity areas, 3) areas in need of protection from further degradation, and 4) areas that could feasibly be rehabilitated to increase biodiversity. Based on benthic trawl data, shallow water habitats surrounding large island complexes had the highest fish diversity and catch per unit effort (CPUE). Electrofishing displayed similar fish diversity and CPUE patterns across habitat types early in the study but yielded no discernable fish diversity or CPUE patterns towards the end of our study. Although highly variable among study sites, macroinvertebrate density was greatest in shallow water habitats <2.5 m and around large island complexes. Our results provide valuable baseline data that could act as a foundation for developing rehabilitation strategies in the lower Maumee River and for assessing the effectiveness of future aquatic habitat rehabilitation projects. In addition to increasing in-channel habitat, watershed-scale improvements of water quality might be necessary to ensure rehabilitation strategies are successful.     

Evidence of successful river spawning by lake trout (Salvelinus namaycush) in the Lower Niagara River,Lake Ontario

Restoration of a wild-produced lake trout Salvelinus namaycush population in Lake Ontario has not been successful despite the adult population often meeting or exceeding restoration targets. Lack of high-quality spawning habitat in Lake Ontario is suggested as one impediment to recruitment of wild lake trout, although the quantity and location of spawning habitat is poorly understood. If high-quality spawning habitat is limited in Lake Ontario, lake trout may be using uncommon spawning locations such as rivers. Anecdotal angler accounts point to the Niagara River as a lake trout spawning location. To better understand the potential of the Niagara River as a spawning location, egg and juvenile fish collections were conducted 12–14 river kilometers from the mouth of the Niagara River from 2010 to 2012; and mature female lake trout with surgically implanted acoustic tags were monitored from 2015 to 2019. Genetic analyses confirmed 60% of collected eggs and 93% of collected post-hatch juvenile fish in the Niagara River were lake trout. Tagged female lake trout returned to the Niagara River over consecutive years during the spawning season. The short duration of lake trout presence in the river (mean = 56 days/year) suggests female lake trout use the Niagara River primarily for spawning. Diversity in spawning locations may provide lake trout population’s resilience against environmental variability through a portfolio effect. Improved identification of riverine spawning locations, including their overall contribution to wild recruitment, may be a useful tool for managers to restore a wild-produced population of lake trout in Lake Ontario.     

Genome-wide genetic diversity may help identify fine-scale genetic structure among lake whitefish spawning groups in Lake Erie

In Lake Erie, lake whitefish Coregonus clupeaformis supported lucrative fisheries before populations were decimated by overfishing and water quality degradation. In recent years, there has been a renewed interest in lake whitefish and management of the fishery they support. Lake whitefish spawn on several reefs throughout Lake Erie, but the relative recruitment dynamics and contributions of spawning groups to the fishery are not well understood. Modern high-throughput sequencing approaches offer new opportunities to census population diversity and to identify subtle differences among closely related populations. We used high-throughput sequencing data to evaluate the genetic structure and diversity of lake whitefish collected opportunistically across broad spatial scales in Lake Erie. Using RAD-capture (Rapture), we sequenced and genotyped individuals (N = 88) from the west, central, and east basin of Lake Erie at 120,268 single nucleotide polymorphisms (SNPs). Lake whitefish from Niagara and Crib Reefs (west basin) diverged from the three collections. Interestingly, these were the only lake whitefish collected during the act of spawning (late November), and all other fish were collected pre-spawn (August-early November). These results suggest that some lake whitefish spawning reefs may be reproductively isolated, though definition of these groups into stocks will require more intentional sampling during the act of spawning.     

Mining Web navigation patterns with a path traversal graph

Understanding the navigational behaviour of website visitors is a significant factor of success in the emerging business models of electronic commerce and even mobile commerce. However, Web traversal patterns obtained by traditional Web usage mining approaches are ineffective for the content management of websites. They do not provide the big picture of the intentions of the visitors. The Web navigation patterns, termed throughout-surfing patterns (TSPs) as defined in this paper, are a superset of Web traversal patterns that effectively display the trends toward the next visited Web pages in a browsing session. TSPs are more expressive for understanding the purposes of website visitors. In this paper, we first introduce the concept of throughout-surfing patterns and then present an efficient method for mining the patterns. We propose a compact graph structure, termed a path traversal graph, to record information about the navigation paths of website visitors. The graph contains the frequent surfing paths that are required for mining TSPs. In addition, we devised a graph traverse algorithm based on the proposed graph structure to discover the TSPs. The experimental results show the proposed mining method is highly efficient to discover TSPs.     

A combined fuzzy linear regression and fuzzy multiple objective programming approach for setting target levels in quality function deployment

Quality function deployment (QFD) is a systematic process for translating customer needs into engineering characteristics, and then communicating them throughout the enterprise in a way to ensure that details are quantified and controlled. The inherent fuzziness of relationships in QFD modeling justifies the use of fuzzy regression for estimating the relationships between both customer needs and engineering characteristics, and among engineering characteristics. Albeit QFD aims to maximize customer satisfaction, requirements related to enterprise satisfaction such as cost budget, extendibility, and technical difficulty also need to be considered. This paper presents a fuzzy multiple objective decision framework that includes not only fulfillment of engineering characteristics to maximize customer satisfaction, but also maximization of extendibility and minimization of technical difficulty of engineering characteristics as objectives subject to a financial budget constraint to determine target levels of engineering characteristics in product design. A real-world quality improvement problem is presented to illustrate the application of the decision approach.     

Deriving industrial logistics hub reference models for manufacturing based economies

Global enterprises require extended logistics operations that integrate channel intermediaries into the network. The method for deriving integrated models for logistics hubs that improve the efficiency of manufacturers’ global operations is the focus of this paper. Under government sponsorship, six industrial logistics hubs were implemented by leading manufacturing sectors across Taiwan over a five year period from 2004 until 2008. Each industry sector had unique industry characteristics, business strategies, and logistics models. Therefore, this paper describes how generalized and quick to implement integrated logistics hubs are developed by studying the successful reference models and systems used by six independent industrial sectors. The research results provide a field tested method for deriving integrated logistics hub models in different manufacturing economies with notes that provide sufficient methodological detail for repeating the construction of logistics hubs in other manufacturing economies.     

An integrated method for finding key suppliers in SCM

Association rule is a widely used data mining technique that searches through an entire data set for rules revealing the nature and frequency of relationships or associations between data entities. Supplier selection is a significant work in supply chain management. Often, there will be thousands of potential suppliers and identifying a subset of these suppliers can be a complex process of determining a satisfactory subset based on a number of factors. In this paper, the supplier selection can be viewed as the problem of mining a large database of shipment. The proposed method incorporates the extended association rule algorithm of data mining with that of set theory to find key suppliers. This research has employed a numerical example for the integrated method to develop suitable supplier clusters. The results show that the method is effective and applicable.     

An overview of the model integration process: From pre-integration assessment to testing

Integration of models requires linking models which can be developed using different tools, methodologies, and assumptions. We performed a literature review with the aim of improving our understanding of model integration process, and also presenting better strategies for building integrated modeling systems. We identified five different phases to characterize integration process: pre-integration assessment, preparation of models for integration, orchestration of models during simulation, data interoperability, and testing. Commonly, there is little reuse of existing frameworks beyond the development teams and not much sharing of science components across frameworks. We believe this must change to enable researchers and assessors to form complex workflows that leverage the current environmental science available. In this paper, we characterize the model integration process and compare integration practices of different groups. We highlight key strategies, features, standards, and practices that can be employed by developers to increase reuse and interoperability of science software components and systems.     

Improvement of adhesive bonding of grit-blasted steel substrates by using diluted resin as a primer

This study reveals the micro-structural details on the metal substrate surface prepared by grit blasting, and then proposes a simple resin pre-coating method aiming at full wetting of the substrate surface for stronger adhesive bonding. The resin pre-coating solution consisting of around 90% acetone and around 10% resin without hardener is used as a primer, which can be sprayed or blushed onto the grit-blasted metal substrate. The acetone solution can carry resin deep into micro-cavities created by grit blasting and effectively coat and wet micro-debris so that micro-voids or gaps between the adhesive joint and metal substrate can be removed. Since the resin pre-coating does not contain hardener and remains wet, the wettability of the substrate is also improved. The normal epoxy adhesive with hardener can then be applied onto the substrate surface. Despite having the primer-like function, the proposed resin pre-coating method still maintains the simplicity of one epoxy resin system. Based on the current study, a resin and acetone solution without hardener does not seem to have adverse effects on the final bonding strengths of adhesive joints, although acetone is known to have detrimental effects on resin and hardener adhesive systems. Four different surface conditions are examined, each having 14 specimens: (1) Grit-Blasted (GB) surface, (2) GB-surface with ultrasonic cleaning, (3) GB-surface with resin Pre-Coating (PC) only, and (4) GB-surface with both ultrasonic cleaning and PC. 25% improvement in the shear strength has been achieved by the resin pre-coating method, even without ultrasonic cleaning, in comparison with 8% improvement after ultrasonic cleaning. These results show GB-surface with PC is beneficial to adhesive bonding, which can be adopted for structural applications even if thorough substrate surface cleaning on site is not possible. The improved wettability of metal substrates after resin pre-coating contributes to the maximum possible utilization of the contact areas over the roughened substrate surfaces and thus leads to the enhanced adhesive bond strength.     

Residential energy efficiency retrofits: How program design affects participation and outcomes

Better methods of characterizing and addressing heterogeneity in preferences and decision making are needed to stimulate reductions in household greenhouse gas emissions. Four residential energy efficiency programs were delivered consecutively in the Region of Waterloo, Canada, between 1999 and 2011, and each offered a unique combination of information, financial reward structure, and price. A natural quasi-experimental intervention design was employed to assess differences in outcomes across these program structures. Participation at the initial (evaluation by an energy advisor) and follow-up (verification of retrofit) stages, and the material characteristics (e.g., energy performance) were measured and compared between the groups of houses included in each program at each stage. The programs appealed to people with different types of material concerns; each phase of the program was associated with houses with a different mix of material characteristics and depths of recommended and achieved changes. While a performance-based reward attracted fewer houses at each stage than a larger list-based reward, older houses with poorer energy performance were included at each stage. The findings support experimentation with program designs to target sub-populations of housing stock; future program designs should experiment more carefully and with larger performance-based rewards and test parallels with potential carbon market structures.