Climate change vulnerability assessments as catalysts for social learning: four case studies in south-eastern Australia

Technical assessments of vulnerability and/or risk are increasingly being undertaken to assess the impacts of climate change. Underlying this is the belief that they will bring clarity to questions regarding the scale of institutional investments required, plausible adaptation policies and measures, and the timing of their implementation. Despite the perceived importance of technical assessments in 'evidence-based' decision environments, assessments cannot be undertaken independent of values and politics, nor are they capable of eliminating the uncertainty that clouds decision-making on climate adaptation As such, assessments can trigger as many questions as they answer, leaving practitioners and stakeholders to question their value. This paper explores the value of vulnerability/risk assessments in climate change adaptation planning processes as a catalyst for learning in four case studies in Southeastern Australia. Data were collected using qualitative interviews with stakeholders involved in the assessments and analysed using a social learning framework. This analysis revealed that detailed and tangible strategies or actions often do not emerge directly from technical assessments. However, it also revealed that the assessments became important platforms for social learning. In providing these platforms, assessments present opportunities to question initial assumptions, explore multiple framings of an issue, generate new information, and galvanise support for collective actions. This study highlights the need for more explicit recognition and understanding of the important role social learning plays in climate change vulnerability assessments and adaptation planning more broadly.     

Modeling methods for managing raw material compositional uncertainty in alloy production

Operational uncertainties create disincentives for use of recycled materials in metal alloy production. One that greatly influences remelter batch optimization is variation in the raw material composition, particularly for secondary materials. Currently, to accommodate compositional variation, firms commonly set production targets well inside the window of compositional specification required for performance reasons. Window narrowing, while effective, does not make use of statistical sampling data, leading to sub-optimal usage of recycled materials. This paper explores the use of a chance-constrained optimization method, which allows explicit consideration of statistical information on composition. The framework and a case study of cast and wrought production with available scrap materials are presented. Results show that it is possible to increase the use of recycled material without compromising the likelihood of batch errors, when using this method compared to conventional window narrowing. This benefit of the chance-constrained method grows with increase in compositional uncertainty and is driven by scrap portfolio diversification.     

Method for the determination of sub-ppm concentrations of perfluoroalkylsulfonate anions in water

The determination of sub-ppm concentrations of aqueous perfluoroalkylsulfonate (PFSt) anions, including perfluorooctylsulfonate (PFOS), has been accomplished with a relatively simple mass spectrometric procedure that does not require extraction of the analytes into an organic solvent or a chromatographic separation prior to injection into the negative-ion electrospray ionization mass spectrometer. Sample pretreatment was minimized and consisted of dilution of the aqueous samples of groundwater, surface water, tap water, and distilled water with acetonitrile, addition of dodecylsulfate (DDS) as an internal standard, and, in some cases, addition of known amounts of perfluorobutylsulfonate (PFBS) or PFOS for standard-addition experiments. The linear-response range for PFOS is 25.0 microg L(-1) to 2.5 mg L(-1). The lower limit of this range is three orders of magnitude lower than an equally straightforward chromatographic method. The relative errors for standard aqueous solutions containing only 25.0 microg L(-1) and 2.5 mg L(-1) PFOS are +/- 14% and +/- 7%, respectively, with 133 microg L(-1) DDS as the internal standard. The detection limit and quantification limit for PFOS in these standards are 5.0 microg L(-1) and 25.0 microg L(-1), respectively. Six different PFS anions, containing three to eight carbon atoms, were identified and quantified in an aqueous film-forming foam (AFFF) formulation using the method of standard additions. Two alkylsulfate anions and two perfluoroalkylcarboxylate anions were also identified in the AFFF formulation.     

Characterization of high-tannin fractions from humus by carbon-13 cross-polarization and magic-angle spinning nuclear magnetic resonance

Condensed tannins can be found in various parts of many plants. Unlike lignin there has been little study of their fate as they enter the soil organic matter pool and their influence on nutrient cycling, especially through their protein-binding properties. We extracted and characterized tannin-rich fractions from humus collected in 1998 from a black spruce [Picea mariana (Mill.) Britton et al.] forest in Canada where a previous study (1995) showed high levels (3.8% by weight) of condensed tannins. A reference tannin purified from black spruce needles was characterized by solution 13C nuclear magnetic resonance (NMR) as a pure procyanidin with mainly cis stereochemistry and an average chain length of four to five units. The colorimetric proanthocyanidin (PA) assay, standardized against the black spruce tannin, showed that both extracted humus fractions had higher tannin contents than the original humus (2.84% and 11.17% vs. 0.08%), and accounted for 32% of humus tannin content. Consistent with the results from the chemical assay, the aqueous fraction showed higher tannin signals in the 13C cross-polarization and magic-angle spinning (CPMAS) NMR spectrum than the emulsified one. As both tannin-rich humus fractions were depleted in N and high in structures derived from lignin and cutin, they did not have properties consistent with recaldtrant tannin-protein complexes proposed as a mechanism for N sequestration in humus. Further studies are needed to establish if tannin-protein structures in humus can be detected or isolated, or if tannins contribute to forest management problems observed in these ecosystems by binding to and slowing down the activity of soil enzymes.     

Effectiveness of creativity training and its relation to selected personality factors

This exploratory study assesses the effectiveness of the Creative Problem Solving Program (Parnes, Noller and Biondi, 1977) for increasing the ideational fluency, flexibility and originality of trainees in a Master of Business Administration program. Pre- and post-training performances of trainees (N = 32) on the Torrance Tests of Creative Thinking (verbal) are compared with a control group of MBA students (N = 44). Compared to the control group, trainees demonstrate significant gains in originality. While both groups show an improvement in fluency. Trainees with high preferences for achievement and dominance but low preference for deference are less likely than average to self-select for creativity training. Performance in a creativity project is positively related to preference for autonomy and creative ability, and negatively related to preference for achievement. Implications of these findings for the effectiveness of creativity training and the attitudes and performance of high need achievers are discussed. Finally, we discuss issues in the generalization and transfer of training to non-training domains.     

Developing the scientific basis for assessing cumulative effects of wetland loss and degradation on landscape functions: Status,perspectives, and prospects

The incongruity between the regional and national scales at which wetland losses are occurring, and the project-specific scale at which wetlands are regulated and studied, has become obvious. This article presents a synthesis of recent efforts by the US Environmental Protection Agency and the Ecosystems Research Center at Cornell University to bring wetland science and regulation into alignment with the reality of the cumulative effects of wetland loss and degradation on entire landscapes and regions. The synthesis is drawn from the other articles in this volume, the workshop that initiated them, and the scientific literature. It summarizes the status of our present scientific understanding, discusses means by which to actualize the existing potential for matching the scales of research and regulation with the scales at which effects are observed, and provides guidelines for building a stronger scientific base for landscape-level assessments of cumulative effects. It also provides the outlines for a synoptic and qualitative approach to cumulative effects assessment based on a reexamination of the generic assessment framework we proposed elsewhere in this volume.The primary conclusion to be drawn from the articles and the workshop is that a sound scientific basis for regulation will not come merely from acquiring more information on more variables. It will come from recognizing that a perceptual shift to larger temporal, spatial, and organizational scales is overdue. The shift in scale will dictate different—not necessarily more—variables to be measured in future wetland research and considered in wetland regulation.     

Evaluating cumulative effects on wetland functions: A conceptual overview and generic framework

This article outlines conceptual and methodological issues that must be confronted in developing a sound scientific basis for investigating cumulative effects on freshwater wetlands. We are particularly concerned with: (1) effects expressed at temporal and spatial scales beyond those of the individual disturbance, specific project, or single wetland, that is, effects occurring at the watershed or regional landscape level; and (2) the scientific (technical) component of the overall assessment process. Our aim is to lay the foundation for a research program to develop methods to quantify cumulative effects of wetland loss or degradation on the functioning of interacting systems of wetlands. Toward that goal we: (1) define the concept of cumulative effects in terms that permit scientific investigation of effects; (2) distinguish the scientific component of cumulative impact analysis from other aspects of the assessment process; (3) define critical scientific issues in assessing cumulative effects on wetlands; and (4) set up a hypothetical and generic structure for measuring cumulative effects on the functioning of wetlands as landscape systems.We provide a generic framework for evaluating cumulative effects on three basic wetland landscape functions: flood storage, water quality, and life support. Critical scientific issues include appropriate delineations of scales, identification of threshold responses, and the influence on different functions of wetland size, shape, and position in the landscape.The contribution of a particular wetland to landscape function within watersheds or regions will be determined by its intrinsic characteristics, e.g., size, morphometry, type, percent organic matter in the sediments, and hydrologic regime, and by extrinsic factors, i.e., the wetland's context in the landscape mosaic. Any cumulative effects evaluation must take into account the relationship between these intrinsic and extrinsic attributes and overall landscape function. We use the magnitude of exchanges among component wetlands in a watershed or larger landscape as the basis for defining the geographic boundaries of the assessment. The time scales of recovery for processes controlling particular wetland functions determine temporal boundaries. Landscape-level measures are proposed for each function.     

The effect of urban quality improvements on economic activity

This paper is concerned with the link between urban quality improvements and economic activity. A key question is whether improvements in the urban environment which might be achieved, for instance, through pedestrianisation, will affect business location choices - for example, are office or retail businesses particularly keen to locate in more pleasant urban places? The paper outlines the current state of development of the literature with respect to the influence of urban quality on economic activity, and proposes a framework for forecasting economic impacts based on three communities of reference: customers, employees, and the businesses themselves. The results from original modelling of a case study area in Manchester, England are reported and suggest that the positive uplifts that may be expected from environmental improvement programmes may well be on a scale which is significant. The research is obviously important for the urban regeneration and renaissance agendas which posit attractive and well-designed environments as a way to create the right conditions for promoting economic growth.     

The Regionalization of National‐Scale SPARROW Models for Stream Nutrients1

Schwarz, Gregory E., Richard B. Alexander, Richard A. Smith, and Stephen D. Preston, 2011. The Regionalization of National‐Scale SPARROW Models for Stream Nutrients. Journal of the American Water Resources Association (JAWRA) 47(5):1151‐1172. DOI: 10.1111/j.1752‐1688.2011.00581.x Abstract: This analysis modifies the parsimonious specification of recently published total nitrogen (TN) and total phosphorus (TP) national‐scale SPAtially Referenced Regressions On Watershed attributes models to allow each model coefficient to vary geographically among three major river basins of the conterminous United States. Regionalization of the national models reduces the standard errors in the prediction of TN and TP loads, expressed as a percentage of the predicted load, by about 6 and 7%. We develop and apply a method for combining national‐scale and regional‐scale information to estimate a hybrid model that imposes cross‐region constraints that limit regional variation in model coefficients, effectively reducing the number of free model parameters as compared to a collection of independent regional models. The hybrid TN and TP regional models have improved model fit relative to the respective national models, reducing the standard error in the prediction of loads, expressed as a percentage of load, by about 5 and 4%. Only 19% of the TN hybrid model coefficients and just 2% of the TP hybrid model coefficients show evidence of substantial regional specificity (more than ±100% deviation from the national model estimate). The hybrid models have much greater precision in the estimated coefficients than do the unconstrained regional models, demonstrating the efficacy of pooling information across regions to improve regional models.