922,151 research outputs found

    Bayesian modeling of ecosystem services in human enviroment systems.

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    The adaptive management of ecosystem services requires knowledge about the interdependence of land use decision-making and the ecosystem features in a given landscape; and how this coupled humanenvironment system is influenced by drivers of global change. The problem in this context is, that both decisionmaking processes and the ecosystem changes are subject to large uncertainties and incomplete information. Furthermore, trade-offs between different ecosystem services and biodiversity exist and actors tend to maximize only one feature. The adaptive management of an entire system thus needs to find a solution, which optimizes all ecosystem services given uncertain information. For this purpose, we develop a Bayesian Network BN of the humanenvironment system allowing evaluating simultaneously the effect of different decision-making processes on ecosystem responses and updating the results when better information becomes available. We test the approach in a case study in the Swiss Alps, where we focus on integrating the value of different ecosystem services as a support for landscape planning. Results show that if uncertainties are not explicitly integrated into the modeling framework, the information provided to the decision-makers might be misleading. For a case study in a Costa Rican watershed, we expand the BN with exogenous drivers from market (e.g., change in price for crops), policy (e.g., change in national park border) and climate (e.g., change in frequency of heavy rainfall). Policy instruments like command and control, park zoning and payments for cosystem services can help reaching a more balanced management of a watershed. For the planning of those instruments, however, it is helpful to have a model which shows how the manager of individual land units, takes policy measures, together with expected market changes and climate change into account in his land use decision-making. For each management unit, the prior probability of a specific land use and cover is updated with a posterior probability, when additional information about the management unit (e.g., slope, soil type, governance) is available. This type of model can be used to plan and simulate new policy measures like payments for ecosystem services, because it simultaneously takes the ecosystem, socio-economic system and the policy system into account. The model allows identifying management units with high and low values for each ecosystem services and thus the targeting of available financial funds can be optimized. First working steps show that such a BN provides a robust modeling environment, useful for better informed and participatory decision-making

    A Market-Oriented Approach for Multiple Objective Optimization in Agro-Ecological Land Use Planning

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    The development of a third world country requires a conscious balance between different planning and policy issues, such as population growth rate, gross national income, self reliance and long-term sustainable ecological development. This paper reports on a cross-disciplinary project to design a decision support system (DSS) that aims to assist government policy makers in planning the regional agricultural development of the Bungoma region in Kenya. Contrary to previous research, which has taken the perspective of a central planner and a static market, this model extends the scope by introducing the market mechanisms and price subsidies. The model is based on the Agro-Ecological Zones (AEZ) model, a previously developed non-interactive optimization model that provides an agro-ecological and economic assessment of various types of land uses, including cash-crops, food production, grazing, forestation and farming. This paper maintains the decision analytic scope of the AEZ model to explicitly incorporate a multicriteria decomposition optimization formulation that facilitates a direct trade-off analysis between the various decision criteria within a user-interactive decision support modeling framework. The model uses in-depth information about the Bungoma region, extracted from a large scale FAO database on Kenya that includes information on various climate and soil characteristics (e.g., thermal and moisture regime, soil type, slope class) and socio-economic data (e.g., projected growth rate and product demand patterns) for 90,000 agro-ecological cells. At each stage of the analysis, our system offers the decision maker several alternative planning strategies with different suggested land uses for over 100 different types of crops, fuelwood and livestock land utilization types of evaluation, allowing the decision maker to take into account trade-offs between a number of planning and policy criteria, including food output, net revenue, gross value of output, self sufficiency, production costs, arable land use and degree of erosion.decision analysis, multicriteria decision making, integrated land-use planning and management, decision support systems, Land Economics/Use,

    EU WATER POLICY: RESEARCH DEVELOPMENTS AND NEW MANAGEMENT TOOLS

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    At the end of 2000, the European Commission published its Water Framework Directive (WFD) in the Official Journal of the European Communities (2000/60/EC). This new legislation provides for achieving the sustainable management of water resources through its 26 articles that focus primarily on the improvement and protection of the quality of European water resources. The WFD adopts an integrated approach, based upon general principles deriving mainly from four disciplinary approaches, Geography; Ecology; Economics and Sociology. The new challenges posed to the people responsible for the management of water resources across the European Union include the "marrying" of existing national policies with the stipulations of the WFD. Research can support this transition by identifying compatibility and conflicts between legislative instruments, and by encouraging trans-national cooperative relationships. A relevant role of research is also foreseen in providing criteria and tools for conflict resolution by representing the goals of sustainable management in an objective and transparent way. The elaboration required for making planning decisions are increasing in number and complexity, requiring tools that help to organise and communicate the data that should be used to describe the decision context in terms of sustainability, in a holistic way by including environmental, economic and social information. These problems are being addressed by the MULINO Project, a 3-year research program aiming at producing a Decision Support System that will assist water managers in responding to the evolution of policies and management methodologies. The development of the system, which will be prepared in a software format, is being steered by a group of people from European water authorities. This steering committee is contributing to the policy analysis component of the research and to the software design which aims to be applicable in five different national contexts. This paper addresses the challenges and innovations that have been encountered in the second phase of research in which the first prototype of the software has been developed to operate in specific decision situations in each of MULINO's six case studies.Sustainable water management, EU policy, DSS tool, Resource /Energy Economics and Policy,

    Improving smoking cessation care in pregnancy at Aboriginal Medical Services: 'ICAN QUIT in Pregnancy' step-wedge cluster randomised study

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    Planning is critical to mitigating the sudden and potentially catastrophic impact of an infectious disease pandemic on society. National pandemic policy documents cover a wide variety of control options, often with nonspecific recommendations for action. Despite advances in analytical methods for gaining early situational awareness (i.e., of a disease’s transmissibility and severity) and for predicting the likely effectiveness of interventions, a major gap exists globally in terms of integrating these outputs with the advice contained in policy documents. Decision models (and decision science as a field, more broadly) provide an approach to defining and evaluating alternative policy options under complex and changing conditions. A decision model for infectious disease pandemics is an appropriate method for integrating evidence from situational and intervention analysis tools, along with the information in policy documents, to provide robust advice on possible response options (including uncertainty). A decision model for pandemic response cannot capture all of the social, political, and ethical considerations that impact decision-making. Such a model should therefore be embedded in a decision support system that emphasizes this broader context.Freya M. Shearer, Robert Moss, Jodie McVernon, Joshua V. Ross, James M. McCa

    Reduction of inequalities in health: assessing evidence-based tools

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    BACKGROUND: The reduction of health inequalities is a focus of many national and international health organisations. The need for pragmatic evidence-based approaches has led to the development of a number of evidence-based equity initiatives. This paper describes a new program that focuses upon evidence- based tools, which are useful for policy initiatives that reduce inequities. METHODS: This paper is based on a presentation that was given at the "Regional Consultation on Policy Tools: Equity in Population Health Reports," held in Toronto, Canada in June 2002. RESULTS: Five assessment tools were presented. 1. A database of systematic reviews on the effects of educational, legal, social, and health interventions to reduce unfair inequalities is being established through the Cochrane and Campbell Collaborations. 2 Decision aids and shared decision making can be facilitated in disadvantaged groups by 'health coaches' to help people become better decision makers, negotiators, and navigators of the health system; a pilot study in Chile has provided proof of this concept. 3. The CIET Cycle: Combining adapted cluster survey techniques with qualitative methods, CIET's population based applications support evidence-based decision making at local and national levels. The CIET map generates maps directly from survey or routine institutional data, to be used as evidence-based decisions aids. Complex data can be displayed attractively, providing an important tool for studying and comparing health indicators among and between different populations. 4. The Ottawa Equity Gauge is applying the Global Equity Gauge Alliance framework to an industrialised country setting. 5 The Needs-Based Health Assessment Toolkit, established to assemble information on which clinical and health policy decisions can be based, is being expanded to ensure a focus on distribution and average health indicators. CONCLUSION: Evidence-based planning tools have much to offer the goal of equitable health development

    GIS-Based Energy Consumption Model at the Urban Scale for the Building Stock

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    Energy efficient buildings’ issue integrated into the district and CO2 emission reduction strategies and policies are one of the main concerns in the European Union (EU). In order to achieve an effective impact, instead of just concentrating on the improvement in terms of energy efficiency to one particular building, this approach requires challenges to be solved in an entire municipality or an entire district. Accordingly, it is significant understanding the comprehensive residential building stock models in the urban environment able to promote a sustainable energy planning. In this paper we describe a new methodology based on two different modelling approaches top-down and bottom-up with the aim to evaluate the buildings energy consumption model of a municipality. This methodology is mainly based on information that is already available on building stock from the literature and data collection (i.e., technical department of the municipality, web, energy auditors and others) which is later transferred into the Geographic information system (GIS). Into this, in future studies GIS platform provides the information on energy performance in the whole city as well as creating the urban energy maps for assessing retrofitting scenarios and support decision making for policy implementation to achieve sustainable urban planning. This study is part of an ongoing Smart City research study, national cluster project named Zero Energy Buildings in Smart Urban Districts (EEB) and is tested in a medium sized town in the Piedmont region (Italy), and the results are discussed

    Developing a regional environmental information system based on macro-level waste indicators

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    Waste information is necessary for proper management planning. However, data on waste generation and management are sometimes not reliable enough, do not exist or are not useful for the sector. This is due to the high number of waste types and flows, and actors (producers, managers and administrations),which make data collection and treatment difficult. Furthermore, data loss occurs because some waste flows have economic value and return to the second-hand markets without monitoring. The development of a waste information system for a region is more than just about establishing a routine data collection on waste. It is a way to support the challenges of decision-making on waste management. These challenges range from strategic issues of waste management in the national government to the basic challenges of running local governments. In the Cantabrian region, three indicator sets were defined to constitute the waste information system:(a) a Basic Indicator Set, which provides an overview of the status of the generation and management of the main waste streams, giving a national and international comparative analysis of the situation; (b) a Specific Indicator Set, which monitors the objectives of the different waste policies, and (c) a Transverse Indicator Set, which analyses the influence of different economic and social variables on the generation of specific waste streams. The Waste Information System of the Cantabrian Region has been created using a specific methodology for developing indicator sets with multiple objectives. This methodology consists of seven steps: (i) the synthesis, selection of the indicators sets; (ii) analysis of the system under study and data sources;(iii) evaluation of the indicators proposed; (iv) application and interpretation; (v) public review, dissemination and updating protocol; (vi) improvement of indicators sets using SWOT analysis; and (vii) aggregation of all indicators in an aggregated index. These indicator sets with a total of 27 indicators allow tracking the evolution of generation and management of waste streams and the achievement of the policy objectives, establishing a data record, evaluating the data and sources of data, monitoring proposed action and its effectiveness summarizing large amounts of data on waste in order to spread it to the public and finally, aggregate all information in a single index that allows the evaluation of the evolution of all waste sectors in time.This work has been supported by the Cantabrian Government R&D project entitled “Establishing the set of indicators for sustainable resource and waste flow in the region of Cantabria”. Eva Cifrianwas funded by the University of Cantabria on a Ph.D. fellowship

    An evaluation of data quality in Canada’s Continuing Care Reporting System (CCRS): secondary analyses of Ontario data submitted between 1996 and 2011

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    Abstract Background Evidence informed decision making in health policy development and clinical practice depends on the availability of valid and reliable data. The introduction of interRAI assessment systems in many countries has provided valuable new information that can be used to support case mix based payment systems, quality monitoring, outcome measurement and care planning. The Continuing Care Reporting System (CCRS) managed by the Canadian Institute for Health Information has served as a data repository supporting national implementation of the Resident Assessment Instrument (RAI 2.0) in Canada for more than 15 years. The present paper aims to evaluate data quality for the CCRS using an approach that may be generalizable to comparable data holdings internationally. Methods Data from the RAI 2.0 implementation in Complex Continuing Care (CCC) hospitals/units and Long Term Care (LTC) homes in Ontario were analyzed using various statistical techniques that provide evidence for trends in validity, reliability, and population attributes. Time series comparisons included evaluations of scale reliability, patterns of associations between items and scales that provide evidence about convergent validity, and measures of changes in population characteristics over time. Results Data quality with respect to reliability, validity, completeness and freedom from logical coding errors was consistently high for the CCRS in both CCC and LTC settings. The addition of logic checks further improved data quality in both settings. The only notable change of concern was a substantial inflation in the percentage of long term care home residents qualifying for the Special Rehabilitation level of the Resource Utilization Groups (RUG-III) case mix system after the adoption of that system as part of the payment system for LTC. Conclusions The CCRS provides a robust, high quality data source that may be used to inform policy, clinical practice and service delivery in Ontario. Only one area of concern was noted, and the statistical techniques employed here may be readily used to target organizations with data quality problems in that (or any other) area. There was also evidence that data quality was good in both CCC and LTC settings from the outset of implementation, meaning data may be used from the entire time series. The methods employed here may continue to be used to monitor data quality in this province over time and they provide a benchmark for comparisons with other jurisdictions implementing the RAI 2.0 in similar populations.http://deepblue.lib.umich.edu/bitstream/2027.42/112338/1/12911_2012_Article_635.pd

    Strengthening America's Best Idea: An Independent Review of the National Park Service's Natural Resource Stewardship and Science Directorate

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    NRSS requested that an independent panel of the National Academy conduct a review of its effectiveness in five core functions, its relationships with key internal stakeholders, and its performance measurement system. Among other things, the National Park Service's Natural Resource Stewardship and Science Directorate (NRSS) is responsible for providing usable natural and social science information throughout the National Park Service (NPS). NRSS leadership requested this review of the directorate's performance on five core functions, its relationships with key internal NPS stakeholders, and its performance measurement system.Main FindingsThe panel determined that NRSS is a highly regarded organization that provides independent, credible scientific expertise and technical information. The panel also found that NRSS and NPS have additional opportunities to advance natural resource stewardship throughout the Service. If implemented, the panel's eight major recommendations will: (1) help the Service respond to the parks' environmental challenges while raising public awareness about the condition of these special places; (2) strengthen NRSS as an organization; (3) promote scientifically based decision-making at the national, regional, and park levels; and (4) improve the existing performance measurement system
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