Statistical analyses of regional surface water quality in southeastern Ontario

Historical records from Ontario's Provincial Water Quality Monitoring Network (PWQMN) for rivers and streams were analyzed to assess the feasibility of mapping regional water quality patterns in southeastern Ontario which spans two major geologic zones, the Precambrian Shield and the St. Lawrence Lowlands, thus serving as a paradigm for much of Ontario. Despite biases toward the populated Lowlands and associated pollution problems, general spatial trends are evident via the analysis of intervariable relations, individual parameter maps and multivariate analysis. Using a robust algorithm designed to identify outliers and abstract underlying bivariate relations, a linear regional hardness-alkalinity relation was derived, where most anomalies proved to be mine drainage impacted sites. Regionally, multivariate ordination reveals that central tendencies of common indicators of ionic strength and nutrient richness correlate positively and that site clusters broadly reflect the transition from oligotrophic Shield waters to eutrophic conditions of heavily agricultural Lowland streams. Results suggest that on the Shield more precisely delineated aquatic regions may be realized by applying GIS to integrate river and synoptic lake survey data. Further synthesis with bedrock and surficial geology, physiography, pedology and other temporally invariant spatial attributes should yield regional patterns of background quality from which locally attainable water objectives might be defined. Additional synoptic surveys of sedimentary Lowland streams may be required as most available sites relflect anthropogenic pollution.     

Robust graphical methods for diagnosing trend in irregularly spaced water quality time series

Graphical methods can play an important role in the reliable assessment of trends in typically ill behaved river quality data series both as diagnostic tools and as visual corroborative evidence when assumptions required for formal statistical tests are not met. Robust, graphically-oriented trend diagnosis procedures are presented for data series characterized by nonnormal populations, uneven time spacing, nonmonotonic trend and other factors which can create serious problems for standard parametric time series methods. Cleveland's robust locally weighted regression (RLWR) developed for investigating nonlinearity in x-y scatterplots is adapted as a robust/resistant smoothing filter for the analysis of irregular time series comprising quantitative observations. Low powered RLWR trend lines reveal temporally local phenomena, e.g. abrupt jumps (often associated with point source impacts) and periodicities, while higher powered RLWR yields smooth lines characterizing medium and longer term trends. Simple variants of Tukey smoothing concepts are developed for series with censored observations. Applications to Ontario river quality series reveal that graphical evidence is frequently sufficient to obviate the need for formal trend testing. The methods are generally applicable to most time series.     

The role of the rural settlements in the Brazilian savanna deforesting process

Although the drivers of deforestation in Brazil are relatively well known, there is still limited understanding of the role of family farm-based rural settlements in land cover changes, particularly in the Brazilian savanna. This research aims to identify land use patterns within rural settlements and examine how they are influenced by regional dynamics. The study is based on GIS techniques and satellite image classification (Landsat 5-TM and RapidEye imagery), combined with geo-referenced fieldwork data in three different regions of the State of Goiás. The results reveal that the deforestation arrangement within the studied rural settlements is very similar to the deforestation found in the surrounding regions. As a positive outcome, the rural settlements have a higher share of remnant vegetation when compared to the surrounding areas, but this is still concentrated within legal reserves. We conclude that the changing patterns of rural settlement land cover are highly influenced by regional dynamics.     

Sustainability Assessment for Agriculture Scenarios in Europe’s Mountain Areas: Lessons from Six Study Areas

Sustainability assessment (SA) is a holistic and long-range strategic instrument capable of assisting policy-making in electing, and deciding upon, future development priorities. The outcomes of an SA process become more relevant and strengthened when conducted with multi-stakeholder engagement, which provides for multiple dialogues and perspectives. This was the object of research of the SA team in the context of BioScene (Scenarios for Reconciling Biodiversity Conservation with Declining Agriculture Use in Mountain Areas in Europe), a three-year project (2002–2005) funded by the European Union 5th Framework Program, which aimed to investigate the implications of agricultural restructuring and decline for biodiversity conservation in the mountain areas of Europe, using three distinct methodological streams: the ecological, the socio-economic, and the SA approaches. The SA approach drew on the previous two to assess the importance for biodiversity management of different scenarios of agri-environmental change and rural policy in six countries (France, Greece, Norway, Slovakia, Switzerland, and the United Kingdom), develop causal chains, include stakeholder views, and identify potential contributions for, or conflicts with, sustainability. This article tells how SA was used, what sustainability meant in each study area through different objectives of sustainability considered, discusses the methods used in SA, and the benefits arising. The SA was conducted by a team independent of any study area, who developed and oversaw the application of the SA methodology, assisting national teams, and developing a cross-country understanding of the sustainability of proposed scenarios in the different geographical and social contexts, and their implications for policy-making. Finally, it reflects on the persistent challenges of interdisciplinary research, compounded by multi-cultural teams, and concludes on the BioScene’s lessons for the further development and application of SA.

Process design optimization and risk analysis

Hazard identification and risk assessment are key aspects in process plant design. They are often applied in the final stages of the process at whatever the cost, unless financial constraints are imposed. However, a much better solution would be to introduce risk analysis earlier by including it in earlier stages of the design process, such as when the cost of a plant and the cost of any accidents that may occur are estimated. In this paper, an optimization methodology is proposed, in which both cost and risk (with a deterministic approach) are taken into account, to improve on the current situation. If a decision variable is chosen, an objective function will be established that makes it possible to analyze variations in overall costs, including the cost of the investment and the cost of accidents. This leads to an optimum situation in which costs are kept to a minimum. Of course, this optimization is subject to constraints, the greatest of which is the fact that risk must not exceed tolerated threshold levels. The procedure is explained and two examples, one involving a toxic release and the other a BLEVE/fireball, are used to illustrate it.     

Use of hairy roots extracts for 2,4-DCP removal and toxicity evaluation by Lactuca sativa test

2,4-Dichlorophenol (2,4-DCP) is widely distributed in wastewaters discharged from several industries, and it is considered as a priority pollutant due to its high toxicity. In this study, the use of different peroxidase extracts for 2,4-DCP removal from aqueous solutions was investigated. Tobacco hairy roots (HRs), wild-type (WT), and double-transgenic (DT) for tomato basic peroxidases (TPX1 and TPX2) were used to obtain different peroxidase extracts: total peroxidases (TPx), soluble peroxidases (SPx), and peroxidases ionically bound to the cell wall (IBPx). All extracts derived from DT HRs exhibited higher peroxidase activity than those obtained from WT HRs. TPx and IBPx DT extracts showed the highest catalytic efficiency values. The optimal conditions for 2,4-DCP oxidation were pH 6.5, H₂O₂ 0.5 mM, and 200 U mL^?1 of enzyme, for all extracts analyzed. Although both TPx extracts were able to oxidize different 2,4-DCP concentrations, the removal efficiency was higher for TPx DT. Polyethylene glycol addition slightly improved 2,4-DCP removal efficiency, and it showed some protective effect on TPx WT after 2,4-DCP oxidation. In addition, using Lactuca sativa test, a reduction of the toxicity of post removal solutions was observed, for both TPx extracts. The results demonstrate that TPx extracts from both tobacco HRs appear to be promising candidate for future applications in removing 2,4-DCP from wastewaters. This is particularly true considering that these peroxidase sources are associated with low costs and are readily available. However, TPx DT has increased peroxidase activity, catalytic efficiency, and higher removal efficiency than TPx WT, probably due to the expression of TPX1 and TPX2 isoenzymes.     

Adaptive Management: From More Talk to Real Action

The challenges currently facing resource managers are large-scale and complex, and demand new approaches to balance development and conservation goals. One approach that shows considerable promise for addressing these challenges is adaptive management, which by now is broadly seen as a natural, intuitive, and potentially effective way to address decision-making in the face of uncertainties. Yet the concept of adaptive management continues to evolve, and its record of success remains limited. In this article, we present an operational framework for adaptive decision-making, and describe the challenges and opportunities in applying it to real-world problems. We discuss the key elements required for adaptive decision-making, and their integration into an iterative process that highlights and distinguishes technical and social learning. We illustrate the elements and processes of the framework with some successful on-the-ground examples of natural resource management. Finally, we address some of the difficulties in applying learning-based management, and finish with a discussion of future directions and strategic challenges.     

Phytoremediation: Modeling removal of TNT and its breakdown products

Contamination of soil and groundwater by trinitrotoluene (TNT) is a widespread problem confronting military bases and ammunition manufacturing facilities throughout the United States. Phytoremediation provides a promising treatment of TNT-contaminated groundwater and wastewater because many plants contain the necessary enzymes to degrade explosives such as TNT. Two phytoremediation methods are proposed in this article: controlled reactors and constructed wetlands. Controlled reactors provide greater control of operating parameters, a reduced possibility of contaminant migration, control of animals feeding on the plants, and minimization of competition from other plant species. Constructed wetlands have relatively low capital costs, and the wetland becomes a desirable ecological resource. Because cost, as opposed to reactor size, appears to be the most significant factor for military base cleanup, this project focused on the constructed wetland approach. To estimate the disappearance of TNT and its breakdown products from a constructed wetland, a first-order, nonreversible reaction, plug-flow, finite-difference model was developed. Batch scale experiments were conducted to define disappearance kinetics for individual chemical species. The results of the model suggest that reasonably sized wetlands may be used to treat a wastestream with an influent TNT concentration of 2.25 ppm at flow rates ranging from 10 to 5,000 gpm. Economic comparisons to other published costs for competing technologies are promising.