Decision-Support tools for assessing land degradation and realising sustainable land management, Study Case of El Mkhachbiya Catchment, Northwest of Tunisia

Land degradation is intrinsically complex and involves decisions by many agencies and individuals, land degradation map- ping should be used as a learning tool through which managers, experts and stakeholders can re-examine their views within a wider semantic context. In this paper, we introduce an analytical framework for mapping land degradation, developed by World Overview for Conservation Approaches and technologies (WOCAT) programs, which aims to develop some thematic maps that serve as an useful tool and including effective information on land degradation and conservation status. Consequently, this methodology would provide an important background for decision-making in order to launch rehabilitation/remediation actions in high-priority intervention areas. As land degradation mapping is a problem-solving task that aims to provide clear information, this study entails the implementation of WOCAT mapping tool, which integrate a set of indicators to appraise the severity of land degradation across a representative watershed. So this work focuses on the use of the most relevant indicators for measuring impacts of different degradation processes in El Mkhachbiya catchment, situated in Northwest of Tunisia and those actions taken to deal with them based on the analysis of operating modes and issues of degradation in different land use systems. This study aims to provide a database for surveillance and monitoring of land degradation, in order to support stakeholders in making appropriate choices and judge guidelines and possible suitable recommendations to remedy the situation in order to promote sustainable development. The approach is illustrated through a case study of an urban watershed in Northwest of Tunisia. Results showed that the main land degradation drivers in the study area were related to natural processes, which were exacerbated by human activities. So the output of this analytical framework enabled a better communication of land degradation issues and concerns in a way relevant for policymakers.

Decision Support Models for Composing and Navigating through e-Learning Objects

Libraries of learning objects may serve as basis for deriving course offerings that are customized to the needs of different learning communities or even individuals. Several ways of organizing this course composition process are discussed. Course composition needs a clear understanding of the dependencies between the learning objects. Therefore we discuss the metadata for object relationships proposed in different standardization projects and especially those suggested in the Dublin Core Metadata Initiative. Based on these metadata we construct adjacency matrices and graphs. We show how Gozinto-type computations can be used to determine direct and indirect prerequisites for certain learning objects. The metadata may also be used to define integer programming models which can be applied to support the instructor in formulating his specifications for selecting objects or which allow a computer agent to automatically select learning objects. Such decision models could also be helpful for a learner navigating through a library of learning objects. We also sketch a graph-based procedure for manual or automatic sequencing of the learning objects.

Randomized trial of a computerized coronary heart disease risk assessment tool in HIV-infected patients receiving combination antiretroviral therapy

Exposure to combination antiretroviral therapy (cART) can lead to important metabolic changes and increased risk of coronary heart disease (CHD). Computerized clinical decision support systems have been advocated to improve the management of patients at risk for CHD but it is unclear whether such systems reduce patients' risk for CHD.

Tools for better SLM knowledge management and informed decision-making in addressing land degradation at different scales: the WOCAT–LADA–DESIRE methodology

Desertification research conventionally focuses on the problem – that is, degradation – while neglecting the appraisal of successful conservation practices. Based on the premise that Sustainable Land Management (SLM) experiences are not sufficiently or comprehensively documented, evaluated, and shared, the World Overview of Conservation Approaches and Technologies (WOCAT) initiative (www.wocat.net), in collaboration with FAO’s Land Degradation Assessment in Drylands (LADA) project (www.fao.org/nr/lada/) and the EU’s DESIRE project (http://www.desire-project.eu/), has developed standardised tools and methods for compiling and evaluating the biophysical and socio-economic knowledge available about SLM. The tools allow SLM specialists to share their knowledge and assess the impact of SLM at the local, national, and global levels. As a whole, the WOCAT–LADA–DESIRE methodology comprises tools for documenting, self-evaluating, and assessing the impact of SLM practices, as well as for knowledge sharing and decision support in the field, at the planning level, and in scaling up identified good practices. SLM depends on flexibility and responsiveness to changing complex ecological and socioeconomic causes of land degradation. The WOCAT tools are designed to reflect and capture this capacity of SLM. In order to take account of new challenges and meet emerging needs of WOCAT users, the tools are constantly further developed and adapted. Recent enhancements include tools for improved data analysis (impact and cost/benefit), cross-scale mapping, climate change adaptation and disaster risk management, and easier reporting on SLM best practices to UNCCD and other national and international partners. Moreover, WOCAT has begun to give land users a voice by backing conventional documentation with video clips straight from the field. To promote the scaling up of SLM, WOCAT works with key institutions and partners at the local and national level, for example advisory services and implementation projects. Keywords: Sustainable Land Management (SLM), knowledge management, decision-making, WOCAT–LADA–DESIRE methodology.

Assessing and mapping LD and SLM to directly support the planning and scaling up of SLM interventions to combat desertification

Global investment in Sustainable Land Management (SLM) has been substantial, but knowledge gaps remain. Overviews of where land degradation (LD) is taking place and how land users are addressing the problem using SLM are still lacking for most individual countries and regions. Relevant maps focus more on LD than SLM, and they have been compiled using different methods. This makes it impossible to compare the benefits of SLM interventions and prevents informed decision-making on how best to invest in land. To fill this knowledge gap, a standardised mapping method has been collaboratively developed by the World Overview of Conservation Approaches and Technologies (WOCAT), FAO’s Land Degradation Assessment in Drylands (LADA) project, and the EU’s Mitigating Desertification and Remediating Degraded Land (DESIRE) project. The method generates information on the distribution and characteristics of LD and SLM activities and can be applied at the village, national, or regional level. It is based on participatory expert assessment, documents, and surveys. These data sources are spatially displayed across a land-use systems base map. By enabling mapping of the DPSIR framework (Driving Forces-Pressures-State-Impacts-Responses) for degradation and conservation, the method provides key information for decision-making. It may also be used to monitor LD and conservation following project implementation. This contribution explains the mapping method, highlighting findings made at different levels (national and local) in South Africa and the Mediterranean region. Keywords: Mapping, Decision Support, Land Degradation, Sustainable Land Management, Ecosystem Services, Participatory Expert Assessment

Guidelines for WB3 Part III: Stakeholder workshop 2: Selection and decision on prevention and mitigation strategies to be implemented

These guidelines were developed in the context of working block 3 of the DESIRE project. They address the facilitators in the 18 DESIRE study sites and support them in conducting stakeholder workshops aiming at the selection and decision on mitigation strategies to be implemented in the study site context. The decision-making process is supported by a multi-objective decision support system (MODSS) Software called 'Facilitator'.

Transmission dynamics of Chlamydia trachomatis affect the impact of screening programmes

To assess the impact of screening programmes in reducing the prevalence of Chlamydia trachomatis, mathematical and computational models are used as a guideline for decision support. Unfortunately, large uncertainties exist about the parameters that determine the transmission dynamics of C. trachomatis. Here, we use a SEIRS (susceptible-exposed-infected-recovered-susceptible) model to critically analyze the turnover of C. trachomatis in a population and the impact of a screening programme. We perform a sensitivity analysis on the most important steps during an infection with C. trachomatis. Varying the fraction of the infections becoming symptomatic as well as the duration of the symptomatic period within the range of previously used parameter estimates has little effect on the transmission dynamics. However, uncertainties in the duration of temporary immunity and the asymptomatic period can result in large differences in the predicted impact of a screening programme. We therefore analyze previously published data on the persistence of asymptomatic C. trachomatis infection in women and estimate the mean duration of the asymptomatic period to be longer than anticipated so far, namely 433 days (95% CI: 420-447 days). Our study shows that a longer duration of the asymptomatic period results in a more pronounced impact of a screening programme. However, due to the slower turnover of the infection, a substantial reduction in prevalence can only be achieved after screening for several years or decades.

SMARTDIAB: a communication and information technology approach for the intelligent monitoring, management and follow-up of type 1 diabetes patients

SMARTDIAB is a platform designed to support the monitoring, management, and treatment of patients with type 1 diabetes mellitus (T1DM), by combining state-of-the-art approaches in the fields of database (DB) technologies, communications, simulation algorithms, and data mining. SMARTDIAB consists mainly of two units: 1) the patient unit (PU); and 2) the patient management unit (PMU), which communicate with each other for data exchange. The PMU can be accessed by the PU through the internet using devices, such as PCs/laptops with direct internet access or mobile phones via a Wi-Fi/General Packet Radio Service access network. The PU consists of an insulin pump for subcutaneous insulin infusion to the patient and a continuous glucose measurement system. The aforementioned devices running a user-friendly application gather patient's related information and transmit it to the PMU. The PMU consists of a diabetes data management system (DDMS), a decision support system (DSS) that provides risk assessment for long-term diabetes complications, and an insulin infusion advisory system (IIAS), which reside on a Web server. The DDMS can be accessed from both medical personnel and patients, with appropriate security access rights and front-end interfaces. The DDMS, apart from being used for data storage/retrieval, provides also advanced tools for the intelligent processing of the patient's data, supporting the physician in decision making, regarding the patient's treatment. The IIAS is used to close the loop between the insulin pump and the continuous glucose monitoring system, by providing the pump with the appropriate insulin infusion rate in order to keep the patient's glucose levels within predefined limits. The pilot version of the SMARTDIAB has already been implemented, while the platform's evaluation in clinical environment is being in progress.

Developing European conservation and mitigation tools for pollination services: approaches of the STEP (Status and Trends of European Pollinators) project

Pollinating insects form a key component of European biodiversity, and provide a vital ecosystem service to crops and wild plants. There is growing evidence of declines in both wild and domesticated pollinators, and parallel declines in plants relying upon them. The STEP project (Status and Trends of European Pollinators, 2010-2015, www.step-project.net) is documenting critical elements in the nature and extent of these declines, examining key functional traits associated with pollination deficits, and developing a Red List for some European pollinator groups. Together these activities are laying the groundwork for future pollinator monitoring programmes. STEP is also assessing the relative importance of potential drivers of pollinator declines, including climate change, habitat loss and fragmentation, agrochemicals, pathogens, alien species, light pollution, and their interactions. We are measuring the ecological and economic impacts of declining pollinator services and floral resources, including effects on wild plant populations, crop production and human nutrition. STEP is reviewing existing and potential mitigation options, and providing novel tests of their effectiveness across Europe. Our work is building upon existing and newly developed datasets and models, complemented by spatially-replicated campaigns of field research to fill gaps in current knowledge. Findings are being integrated into a policy-relevant framework to create evidence-based decision support tools. STEP is establishing communication links to a wide range of stakeholders across Europe and beyond, including policy makers, beekeepers, farmers, academics and the general public. Taken together, the STEP research programme aims to improve our understanding of the nature, causes, consequences and potential mitigation of declines in pollination services at local, national, continental and global scales.

Compensability index for compensation radiotherapy after treatment interruptions

Background The goal of our work was to develop a simple method to evaluate a compensation treatment after unplanned treatment interruptions with respect to their tumour- and normal tissue effect. Methods We developed a software tool in java programming language based on existing recommendations to compensate for treatment interruptions. In order to express and visualize the deviations from the originally planned tumour and normal tissue effects we defined the compensability index. Results The compensability index represents an evaluation of the suitability of compensatory radiotherapy in a single number based on the number of days used for compensation and the preference of preserving the originally planned tumour effect or not exceeding the originally planned normal tissue effect. An automated tool provides a method for quick evaluation of compensation treatments. Conclusions The compensability index calculation may serve as a decision support system based on existing and established recommendations.

GIS based Watershed Classification in Lao PDR

Every inclined land surface has a potential for soil and water degradation, the seriousness depends on a multitude of parameters such as slope, soil type, geomorphology, rainfall, land use and natural vegetation cover. In Laos this intensified land use leads to reduced vegetation cover, to increased soil erosion, decreasing yield, and finally is likely to influence the hydrological regime. Against this background the Mekong River Commission (MRC) elaborated a spatial explicit Watershed Classification (WSC) for the Lower Mekong Basin. Based on topographic factors derived from a high-resolution Digital Terrain Model, five watershed classes are calculated, giving indication about the sensitivity to resource degradation by soil erosion. The WSC allows spatial priority setting for watershed management and generally supports informed decision making on reconnaissance level. In the conclusions focus is laid on general considerations when GIS techniques are used for spatial decision support in a development context.

Red cell survival in relation to changes in the hematocrit: more important than you think

The management of anemia in patients with chronic renal failure has greatly improved with the availability of recombinant human erythropoietin in the late 1980s, leading to a considerable reduction in mortality and morbidity and to an improvement in quality of life. The findings from recent controlled clinical outcome trials have resulted in a rather narrow, generally accepted therapeutic hematocrit target range. However, currently available dosing algorithms do not permit achievement and maintenance of target values within the therapeutic range in many patients. One possible explanation for this failure may be the ignorance of a finite erythrocyte lifespan not integrated into most algorithms. The purpose of this article is to underline the essential role played by the erythrocyte lifespan in the erythropoietic response to recombinant human erythropoietin and to encourage the integration of this concept in the future development of computer-assisted decision support systems.

Appraising and selecting conservation measures to mitigate desertification and land degradation based on stakeholder participation and global best practices

Most desertification research focuses on degradation assessments without putting sufficient emphasis on prevention and mitigation strategies, although the concept of Sustainable Land Management (SLM) is increasingly being acknowledged. A variety of already applied conservation measures exist at the local level, but they are not adequately recognised, evaluated and shared, either by land users, technicians, researchers, or policy makers. Likewise, collaboration between research and implementation is often insufficient. The aim of this paper is to present a new methodology for a participatory process of appraising and selecting desertification mitigation strategies, and to present first experiences from its application in the EU-funded DESIRE project. The methodology combines a collective learning and decision approach with the use of evaluated global best practices. In three parts, it moves through a concise process, starting with identifying land degradation and locally applied solutions in a stakeholder workshop, leading to assessing local solutions with a standardised evaluation tool, and ending with jointly selecting promising strategies for implementation with the help of a decision support tool. The methodology is currently being applied in 16 study sites. Preliminary analysis from the application of the first part of the methodology shows that the initial stakeholder workshop results in a good basis for stakeholder cooperation, and in promising land conservation practices for further assessment. Study site research teams appreciated the valuable results, as burning issues and promising options emerged from joint reflection. The methodology is suitable to initiate mutual learning among different stakeholder groups and to integrate local and scientific knowledge.

A neural network approach for insulin regime and dose adjustment in type 1 diabetes

A decision support system based on a neural network approach is proposed to advise on insulin regime and dose adjustment for type 1 diabetes patients.