Modelling trade offs between public and private conservation policies

To reduce global biodiversity loss, there is an urgent need to determine the most efficient allocation of conservation resources. Recently, there has been a growing trend for many governments to supplement public ownership and management of reserves with incentive programs for conservation on private land. This raises important questions, such as the extent to which private land conservation can improve conservation outcomes, and how it should be mixed with more traditional public land conservation. We address these questions, using a general framework for modelling environmental policies and a case study examining the conservation of endangered native grasslands to the west of Melbourne, Australia. Specifically, we examine three policies that involve i) spending all resources on creating public conservation areas; ii) spending all resources on an ongoing incentive program where private landholders are paid to manage vegetation on their property with 5-year contracts; and iii) splitting resources between these two approaches. The performance of each strategy is quantified with a vegetation condition change model that predicts future changes in grassland quality. Of the policies tested, no one policy was always best and policy performance depended on the objectives of those enacting the policy. Although policies to promote conservation on private land are proposed and implemented in many areas, they are rarely evaluated in terms of their ecological consequences. This work demonstrates a general method for evaluating environmental policies and highlights the utility of a model which combines ecological and socioeconomic processes.

When do conservation planning methods deliver? Quantifying the consequences of uncertainty

The rapid global loss of biodiversity has led to a proliferation of systematic conservation planning methods. In spite of their utility and mathematical sophistication, these methods only provide approximate solutions to real-world problems where there is uncertainty and temporal change. The consequences of errors in these solutions are seldom characterized or addressed. We propose a conceptual structure for exploring the consequences of input uncertainty and oversimpli?ed approximations to real-world processes for any conservation planning tool or strategy. We then present a computational framework based on this structure to quantitatively model species representation and persistence outcomes across a range of uncertainties. These include factors such as land costs, landscape structure, species composition and distribution, and temporal changes in habitat. We demonstrate the utility of the framework using several reserve selection methods including simple rules of thumb and more sophisticated tools such as Marxan and Zonation. We present new results showing how outcomes can be strongly affected by variation in problem characteristics that are seldom compared across multiple studies. These characteristics include number of species prioritized, distribution of species richness and rarity, and uncertainties in the amount and quality of habitat patches. We also demonstrate how the framework allows comparisons between conservation planning strategies and their response to error under a range of conditions. Using the approach presented here will improve conservation outcomes and resource allocation by making it easier to predict and quantify the consequences of many different uncertainties and assumptions simultaneously. Our results show that without more rigorously generalizable results, it is very dif?cult to predict the amount of error in any conservation plan. These results imply the need for standard practice to include evaluating the effects of multiple real-world complications on the behavior of any conservation planning method.

Web based expert elicitation of uncertainties in environmental model inputs

When constructing and using environmental models, it is typical that many of the inputs to the models will not be known perfectly. In some cases, it will be possible to make observations, or occasionally physics-based uncertainty propagation, to ascertain the uncertainty on these inputs. However, such observations are often either not available or even possible, and another approach to characterising the uncertainty on the inputs must be sought. Even when observations are available, if the analysis is being carried out within a Bayesian framework then prior distributions will have to be specified. One option for gathering or at least estimating this information is to employ expert elicitation. Expert elicitation is well studied within statistics and psychology and involves the assessment of the beliefs of a group of experts about an uncertain quantity, (for example an input / parameter within a model), typically in terms of obtaining a probability distribution. One of the challenges in expert elicitation is to minimise the biases that might enter into the judgements made by the individual experts, and then to come to a consensus decision within the group of experts. Effort is made in the elicitation exercise to prevent biases clouding the judgements through well-devised questioning schemes. It is also important that, when reaching a consensus, the experts are exposed to the knowledge of the others in the group. Within the FP7 UncertWeb project (http://www.uncertweb.org/), there is a requirement to build a Webbased tool for expert elicitation. In this paper, we discuss some of the issues of building a Web-based elicitation system - both the technological aspects and the statistical and scientific issues. In particular, we demonstrate two tools: a Web-based system for the elicitation of continuous random variables and a system designed to elicit uncertainty about categorical random variables in the setting of landcover classification uncertainty. The first of these examples is a generic tool developed to elicit uncertainty about univariate continuous random variables. It is designed to be used within an application context and extends the existing SHELF method, adding a web interface and access to metadata. The tool is developed so that it can be readily integrated with environmental models exposed as web services. The second example was developed for the TREES-3 initiative which monitors tropical landcover change through ground-truthing at confluence points. It allows experts to validate the accuracy of automated landcover classifications using site-specific imagery and local knowledge. Experts may provide uncertainty information at various levels: from a general rating of their confidence in a site validation to a numerical ranking of the possible landcover types within a segment. A key challenge in the web based setting is the design of the user interface and the method of interacting between the problem owner and the problem experts. We show the workflow of the elicitation tool, and show how we can represent the final elicited distributions and confusion matrices using UncertML, ready for integration into uncertainty enabled workflows.We also show how the metadata associated with the elicitation exercise is captured and can be referenced from the elicited result, providing crucial lineage information and thus traceability in the decision making process.

Comparing transport emissions and impacts for energy recovery from domestic waste (EfW): centralised and distributed disposal options for two UK Counties

Many local authorities (LAs) are currently working to reduce both greenhouse gas emissions and the amount of municipal solid waste (MSW) sent to landfill. The recovery of energy from waste (EfW) can assist in meeting both of these objectives. The choice of an EfW policy combines spatial and non-spatial decisions which may be handled using Multi-Criteria Analysis (MCA) and Geographic Information Systems (GIS). This paper addresses the impact of transporting MSW to EfW facilities, analysed as part of a larger decision support system designed to make an overall policy assessment of centralised (large-scale) and distributed (local-scale) approaches. Custom-written ArcMap extensions are used to compare centralised versus distributed approaches, using shortest-path routing based on expected road speed. Results are intersected with 1-kilometre grids and census geographies for meaningful maps of cumulative impact. Case studies are described for two counties in the United Kingdom (UK); Cornwall and Warwickshire. For both case study areas, centralised scenarios generate more traffic, fuel costs and emitted carbon per tonne of MSW processed.

Automatic processing, quality assurance and serving of real-time weather data over lightweight protocols

Recent advances in technology have produced a significant increase in the availability of free sensor data over the Internet. With affordable weather monitoring stations now available to individual meteorology enthusiasts a reservoir of real time data such as temperature, rainfall and wind speed can now be obtained for most of the United States and Europe. Despite the abundance of available data, obtaining useable information about the weather in your local neighbourhood requires complex processing that poses several challenges. This paper discusses a collection of technologies and applications that harvest, refine and process this data, culminating in information that has been tailored toward the user. In this case we are particularly interested in allowing a user to make direct queries about the weather at any location, even when this is not directly instrumented, using interpolation methods. We also consider how the uncertainty that the interpolation introduces can then be communicated to the user of the system, using UncertML, a developing standard for uncertainty representation.

Renal dopamine and salt-retaining states

Although generally regarded as a neurotransmitter, dopamine is also known to be secreted by the kidney whereby it promotes sodium excretion in its role as a natriuretic honnone. Peripheral dopamine may be formed by two alternative pathways; the decarboxylation of circulating L-Dopa by L-aromatic amino acid decarboxylase (LAAAD), and the desulphation of dopamine sulphate by arylsulphatase A (ASA), the latter being poorly represented in the literature. In many conditions and diseases with which sodium retention is associated, a reduced urinary excretion of dopamine has been noted implicating the involvement of dopamine in the maintenance of sodium homeostasis.This study investigates renal dopamine production via the desulphation of dopamine sulphate in a sample cohort during normal unregulated dietary sodium intake and following a low sodium regimen. After dietary salt restriction urinary dopamine sulphate levels were significantly increased, indicating that dopamine sulphate is indeed a physiological reservoir of active free dopamine, the necessity for which is reduced during self depletion. This confirmed the dopamine/dopamine sulphate pathway as one which may be relevant to the maintenance of sodium homeostasis. The activity of urinary ASA was investigated in diabetes mellitus as an example of a sodium-retaining state, and compared with that in a matched normal control group. A decreased ASA activity was anticipated, given the blunted dopamine excretion observed in many sodium-retaining states, however an unexpected increase in activity in the diabetic group was observed. Enzyme kinetic analysis of ASA showed that this was not due to the existence of an isoform having an altered affinity for dopamine sulphate. This rather paradoxical situation, that urinary-dopamine is decreased while ASA activity is increased, may be explained by the sequestering of free dopamine by autoxidation to 6-hydroxydopamine as has been hypothesised recently to occur in diabetes mellitus. To confirm the homogeneity of ASA in the normal and diabetic groups, four amplicons spanning the 3637bp intronic and exonic regions of the gene were generated by PCR. These were sequence utilising a fluorescent-dye terminator reaction using the forward PCR primer as sequencing primer. Although single nucleotide polymorphisms were observed between the two groups these occurred either in intronic regions or, when exonic, generated silent mutations, supporting the enzyme kinetic data. The expression of ASA was investigated to determine the basis of the increased activity observed in diabetes mellitus. Although a validated comparative RT-PCR assay was developed for amplification of arsa transcripts from fresh blood samples, expression analysis from archived paraffin-embedded renal tissue was complicated by the low yield and degradation of unprotected mRNA. Suggestions for the development of this work using renal cell-culture are discussed.

Simulating the value of collaboration in multi-actor conservation planning

The loss of habitat and biodiversity worldwide has led to considerable resources being spent for conservation purposes on actions such as the acquisition and management of land, the rehabilitation of degraded habitats, and the purchase of easements from private landowners. Prioritising these actions is challenging due to the complexity of the problem and because there can be multiple actors undertaking conservation actions, often with divergent or partially overlapping objectives. We use a modelling framework to explore this issue with a study involving two agents sequentially purchasing land for conservation. We apply our model to simulated data using distributions taken from real data to simulate the cost of patches and the rarity and co-occurence of species. In our model each agent attempted to implement a conservation network that met its target for the minimum cost using the conservation planning software Marxan. We examine three scenarios where the conservation targets of the agents differ. The first scenario (called NGO-NGO) models the situation where two NGOs are both are targeting different sets of threatened species. The second and third scenarios (called NGO-Gov and Gov-NGO, respectively) represent a case where a government agency attempts to implement a complementary conservation network representing all species, while an NGO is focused on achieving additional protection for the most endangered species. For each of these scenarios we examined three types of interactions between agents: i) acting in isolation where the agents are attempting to achieve their targets solely though their own actions ii) sharing information where each agent is aware of the species representation achieved within the other agent’s conservation network and, iii) pooling resources where agents combine their resources and undertake conservation actions as a single entity. The latter two interactions represent different types of collaborations and in each scenario we determine the cost savings from sharing information or pooling resources. In each case we examined the utility of these interactions from the viewpoint of the combined conservation network resulting from both agents' actions, as well as from each agent’s individual perspective. The costs for each agent to achieve their objectives varied depending on the order in which the agents acted, the type of interaction between agents, and the specific goals of each agent. There were significant cost savings from increased collaboration via sharing information in the NGO-NGO scenario were the agent’s representation goals were mutually exclusive (in terms of specie targeted). In the NGO-Gov and Gov-NGO scenarios, collaboration generated much smaller savings. If the two agents collaborate by pooling resources there are multiple ways the total cost could be shared between both agents. For each scenario we investigate the costs and benefits for all possible cost sharing proportions. We find that there are a range of cost sharing proportions where both agents can benefit in the NGO-NGO scenarios while the NGO-Gov and Gov-NGO scenarios again showed little benefit. Although the model presented here has a range of simplifying assumptions, it demonstrates that the value of collaboration can vary significantly in different situations. In most cases, collaborating would have associated costs and these costs need to be weighed against the potential benefits from collaboration. The model demonstrates a method for determining the range of collaboration costs that would result in collaboration providing an efficient use of scarce conservation resources.

Epidemiology of community-acquired meticillin-resistant Staphylococcus aureus obtained from the UK West Midlands region

Between January 2005 and December 2005, 199 meticillin-resistant Staphylococcus aureus (MRSA) isolates were obtained from nonhospitalised patients presenting skin and soft tissue infections to local general practitioners. The study area incorporated 57 surgeries from three Primary Care Trusts in the Lichfield, Tamworth, Burntwood, North and East Birmingham regions of Central England, UK. Following antibiotic susceptibility testing, pulsed-field gel electrophoresis, Panton-Valentine leukocidin gene detection and SCCmec element assignment, 95% of the isolates were shown to be related to hospital epidemic strains EMRSA-15 and EMRSA-16. In total 87% of the isolate population harboured SCCmec IV, 9% had SCCmec II and 4% were identified as carrying novel SCCmec IIIa-mecI. When mapped to patient home postcode, a diverse distribution of isolates harbouring SCCmec II and SCCmec IV was observed; however, the majority of isolates harbouring SCCmec IIIa-mecI were from patients residing in the north-west of the study region, highlighting a possible localised clonal group. Transmission of MRSA from the hospital setting into the surrounding community population, as demonstrated by this study, warrants the need for targeted patient screening and decolonisation in both the clinical and community environments.

Automatic processing, quality assurance and serving of real-time weather data

Recent advances in technology have produced a significant increase in the availability of free sensor data over the Internet. With affordable weather monitoring stations now available to individual meteorology enthusiasts a reservoir of real time data such as temperature, rainfall and wind speed can now be obtained for most of the United States and Europe. Despite the abundance of available data, obtaining useable information about the weather in your local neighbourhood requires complex processing that poses several challenges. This paper discusses a collection of technologies and applications that harvest, refine and process this data, culminating in information that has been tailored toward the user. In this case we are particularly interested in allowing a user to make direct queries about the weather at any location, even when this is not directly instrumented, using interpolation methods. We also consider how the uncertainty that the interpolation introduces can then be communicated to the user of the system, using UncertML, a developing standard for uncertainty representation.

Why organizational and community diversity matter:the emergence of incivility and organizational outcomes

Integrating sociological and psychological perspectives, this research considers the value of organizational ethnic diversity as a function of community diversity. Employee and patient surveys, census data, and performance indexes relevant to 142 hospitals in the United Kingdom suggest that intraorganizational ethnic diversity is associated with reduced civility toward patients. However, the degree to which organizational demography was representative of community demography was positively related to civility experienced by patients and ultimately enhanced organizational performance. These findings underscore the understudied effects of community context and imply that intergroup biases manifested in incivility toward out-group members hinder organizational performance.

Managing uncertainty in integrated environmental modelling:the UncertWeb framework

Web-based distributed modelling architectures are gaining increasing recognition as potentially useful tools to build holistic environmental models, combining individual components in complex workflows. However, existing web-based modelling frameworks currently offer no support for managing uncertainty. On the other hand, the rich array of modelling frameworks and simulation tools which support uncertainty propagation in complex and chained models typically lack the benefits of web based solutions such as ready publication, discoverability and easy access. In this article we describe the developments within the UncertWeb project which are designed to provide uncertainty support in the context of the proposed ‘Model Web’. We give an overview of uncertainty in modelling, review uncertainty management in existing modelling frameworks and consider the semantic and interoperability issues raised by integrated modelling. We describe the scope and architecture required to support uncertainty management as developed in UncertWeb. This includes tools which support elicitation, aggregation/disaggregation, visualisation and uncertainty/sensitivity analysis. We conclude by highlighting areas that require further research and development in UncertWeb, such as model calibration and inference within complex environmental models.

Geospatial data quality indicators

Indicators which summarise the characteristics of spatiotemporal data coverages significantly simplify quality evaluation, decision making and justification processes by providing a number of quality cues that are easy to manage and avoiding information overflow. Criteria which are commonly prioritised in evaluating spatial data quality and assessing a dataset’s fitness for use include lineage, completeness, logical consistency, positional accuracy, temporal and attribute accuracy. However, user requirements may go far beyond these broadlyaccepted spatial quality metrics, to incorporate specific and complex factors which are less easily measured. This paper discusses the results of a study of high level user requirements in geospatial data selection and data quality evaluation. It reports on the geospatial data quality indicators which were identified as user priorities, and which can potentially be standardised to enable intercomparison of datasets against user requirements. We briefly describe the implications for tools and standards to support the communication and intercomparison of data quality, and the ways in which these can contribute to the generation of a GEO label.

Developing a forest data portal to support multi-scale decision making

Forests play a pivotal role in timber production, maintenance and development of biodiversity and in carbon sequestration and storage in the context of the Kyoto Protocol. Policy makers and forest experts therefore require reliable information on forest extent, type and change for management, planning and modeling purposes. It is becoming increasingly clear that such forest information is frequently inconsistent and unharmonised between countries and continents. This research paper presents a forest information portal that has been developed in line with the GEOSS and INSPIRE frameworks. The web portal provides access to forest resources data at a variety of spatial scales, from global through to regional and local, as well as providing analytical capabilities for monitoring and validating forest change. The system also allows for the utilisation of forest data and processing services within other thematic areas. The web portal has been developed using open standards to facilitate accessibility, interoperability and data transfer.

UncertWeb processing service:making models easer to access on the web

Models are central tools for modern scientists and decision makers, and there are many existing frameworks to support their creation, execution and composition. Many frameworks are based on proprietary interfaces, and do not lend themselves to the integration of models from diverse disciplines. Web based systems, or systems based on web services, such as Taverna and Kepler, allow composition of models based on standard web service technologies. At the same time the Open Geospatial Consortium has been developing their own service stack, which includes the Web Processing Service, designed to facilitate the executing of geospatial processing - including complex environmental models. The current Open Geospatial Consortium service stack employs Extensible Markup Language as a default data exchange standard, and widely-used encodings such as JavaScript Object Notation can often only be used when incorporated with Extensible Markup Language. Similarly, no successful engagement of the Web Processing Service standard with the well-supported technologies of Simple Object Access Protocol and Web Services Description Language has been seen. In this paper we propose a pure Simple Object Access Protocol/Web Services Description Language processing service which addresses some of the issues with the Web Processing Service specication and brings us closer to achieving a degree of interoperability between geospatial models, and thus realising the vision of a useful 'model web'.