An Approach for Evaluating the Repeatability of Rapid Wetland Assessment Methods: The Effects of Training and Experience

We sampled 92 wetlands from four different basins in the United States to quantify observer repeatability in rapid wetland condition assessment using the Delaware Rapid Assessment Protocol (DERAP). In the Inland Bays basin of Delaware, 58 wetland sites were sampled by multiple observers with varying levels of experience (novice to expert) following a thorough training workshop. In the Nanticoke (Delaware/Maryland), Cuyahoga (Ohio), and John Day (Oregon) basins, 34 wetlands were sampled by two expert teams of observers with minimal protocol training. The variance in observer to observer scoring at each site was used to calculate pooled standard deviations (SD_pool), coefficients of variation, and signal-to-noise ratios for each survey. The results showed that the experience level of the observer had little impact on the repeatability of the final rapid assessment score. Training, however, had a large impact on observer to observer repeatability. The SD_pool in the Inland Bay survey with training (2.2 points out of a 0–30 score) was about half that observed in the other three basins where observers had minimal training (SD_pool = 4.2 points). Using the results from the survey with training, we would expect that two sites assessed by different, trained observers who obtain DERAP scores differing by more than 4 points are highly likely to differ in ecological condition, and that sites with scores that differ by 2 or fewer points are within variability that can be attributed to observer differences.     

Land-use forecasting and hydrologic model integration for improved land-use decision support

This paper develops a methodology for integrating a land-use forecasting model with an event scale, rainfall-runoff model in support of improving land-use policy formulation at the watershed scale. The models selected for integration are loosely coupled, structured upon a common GIS platform that facilitates data exchange. The hydrologic model HEC-HMS is calibrated for a specific storm event that occurred within central Washington State. The land-use forecasting model, What If? is implemented to forecast future spatial distributions of low-density residential land-uses under low and high population growth estimates. Forecasted land-use distribution patterns for the years 2015, 2025, and 2050 are then used as land-use data input for the calibrated hydrologic model, keeping all other parameters constant. Impacts to the stream discharge hydrograph are predicted as the study area becomes increasingly developed as forecasted by What If?. The initial results of this integration process demonstrate the synergy that can be generated through the linkage of the selected models. The ability to quantifiably forecast the potential hydrologic implications of proposed land-use policies before their implementation offers land-use decision-makers a valuable tool for discerning which proposed land-use alternatives will be effective at minimizing storm water runoff.     

Renewable energy in remote communities

This research has demonstrated that even in a small urbanised country like Britain, communities can still be remote. The paper analyses the nature of remote settlements and suggests that beyond the rural idyll, there are deprived communities. In order to obtain real data, a study area in the North Pennines was selected. The types of remote communities were evident throughout the study area and one of each type was selected for further study. It became clear that villages with an industrial base had most potential, due to high energy demand, vulnerability and community involvement. A village with a high measure of multiple deprivation and suffering from fuel poverty was chosen for a more detailed investigation. Energy demand profiles were developed and candidate technologies nominated. The latter were tested by filters that assessed fitness for application, robustness and autonomy. The most appropriate combinations of technologies were proposed. The residents and their community representatives were involved in the process and recognised the benefits of the proposals to themselves and others.     

Estimating carbon in savanna ecosystems: rational distribution of effort

Minimising the cost of repeatedly estimating C (C) stocks is crucial to the financial viability of projects that seek to sell C credits. Depending on the price of C, this may imply less or more sampling effort than would be applied for science objectives. In systems with heterogeneous C pools, such as savannas, this translates into a variable-effort sampling strategy that maximises the marginal additional C that can be claimed per incremental unit of effort expended. Analysis of a savanna in north-eastern South Africa indicates relatively modest returns per hectare due to the small C quantities and low sequestration rates. Under these conditions, areas in excess of 1,000 ha and infrequent sampling frequencies of 5–10 years are required to make such projects financially viable. For such projects the sample variance, number of samples, cost per sample and establishment costs have negligible impacts on financial viability. It was also found that the soil-C pool contributes up to three times the net returns of the aboveground C pool and provides a strong argument to monitor soil C for certification and market trading. The financial viability estimates, however, do not include the management or opportunity costs incurred in changing the land use. The economies of scale identified in this study combined with the massive area covered by savannas indicate that these additional costs can be covered. Further research is recommended to quantify these costs and interrogate the feasibility of large scale (in excess of 10,000 ha) C-sink projects in savanna systems.     

Software tools to support incident reporting in safety-critical systems

Incident reporting systems are playing an increasingly important role in the development and maintenance of safety-critical applications. The perceived success of the FAA's Aviation Safety Reporting System (ASRS) and the FDA's MedWatch has led to the establishment of similar national and international schemes. These enable individuals and groups to report their safety concerns in a confidential or anonymous manner. Unfortunately, many of these systems are becoming victims of their own success. The ASRS and MedWatch have both now received over 500,000 submissions. In consequence, the administrators of incident reporting systems increasingly rely upon software tools to support the administration of their systems. In the past, these systems have relied upon ad hoc applications of conventional database technology. However, there are several reasons why this technology is inadequate for many large-scale reporting schemes. In particular, the problems of query formation often result in poor precision and recall. This, in turn, has profound implications for safety-critical applications. Users may fail to identify similar incidents within national or international collections. These ad hoc approaches also neglect the opportunities provided by recent developments in computer assisted interviewing and in the monitoring of retrieval activities to build models of user behavior. These techniques offer a number of potential benefits. For instance, it is possible to automatically detect potential biases in the way that investigators analyze particular incidents.     

How to integrate information strategy planning with environmental management information systems—part I

Rational, cost-effective provision of mission-critical environmental management information remains elusive for almost all large enterprises. Even among the best performing companies—best performing from the perspectives of profitability, quality and/or environmental stewardship—environmental management information systems (EMIS) are usually comprised of dozens to hundreds of individual, isolated applications that require costly data capture, training, and maintenance. This article, the first of two, will discuss ways to coordinate information infrastructures with strategic goals and business processes.     

Adaptive co-management and network learning in the Room for the River programme

Adaptive co-management and learning are paramount for integrated flood risk management. Relevant literature focuses on adaptation at the level of physical and societal systems. The level of projects and programmes is largely overlooked, but they comprise interventions that adapt our physical systems and they provide opportunities for learning to contribute to transitions of societal systems. This paper aims to increase understanding on how learning takes place and can be stimulated within a programme. The mixed-method case study of Room for the River, a €2.3 billion programme for flood risk management, shows that a programme can be organised using various governance arrangements to stimulate learning and be a means for adaptive co-management to deliver upon environmental objectives.