Knowledge Management and Decision Support for Sustainable Land Management

Much research has focused on desertification and land degradation assessments without putting sufficient emphasis on prevention and mitigation, although the concept of sustainable land management (SLM) is increasingly being acknowledged. A variety of SLM measures have already been applied at the local level, but they are rarely adequately recognised, evaluated, shared or used for decision support. WOCAT (World Overview of Technologies and Approaches) has developed an internationally recognised, standardised methodology to document and evaluate SLM technologies and approaches, including spatial distribution, allowing the sharing of SLM knowledge worldwide. The recent methodological integration into a participatory process allows now analysing and using this knowledge for decision support at the local and national level. The use of the WOCAT tools stimulates evaluation (self-evaluation as well as learning from comparing experiences) within SLM initiatives where all too often there is not only insufficient monitoring but also a lack of critical analysis. The comprehensive questionnaires and database system facilitate to document, evaluate and disseminate local experiences of SLM technologies and their implementation approaches. This evaluation process - in a team of experts and together with land users - greatly enhances understanding of the reasons behind successful (or failed) local practices. It has now been integrated into a new methodology for appraising and selecting SLM options. The methodology combines a local collective learning and decision approach with the use of the evaluated global best practices from WOCAT in a concise three step process: i) identifying land degradation and locally applied solutions in a stakeholder learning workshop; ii) assessing local solutions with the standardised WOCAT tool; iii) jointly selecting promising strategies for implementation with the help of a decision support tool. The methodology has been implemented in various countries and study sites around the world mainly within the FAO LADA (Land Degradation Assessment Project) and the EU-funded DESIRE project. Investments in SLM must be carefully assessed and planned on the basis of properly documented experiences and evaluated impacts and benefits: concerted efforts are needed and sufficient resources must be mobilised to tap the wealth of knowledge and learn from SLM successes.

Predictors of depressed mood 12 months after injury. Contribution of self-efficacy and social support

Abstract Purpose: There is evidence that depressed mood and perception of pain are related in patients with chronic illness. However, how individual resources such as self-efficacy and social support play a role in this association remains unclear. The aim of this study was to investigate the influence of both variables as either moderator or mediator. Method: In a longitudinal study, 274 injured workers (M = 43.24 years) were investigated. Data were collected on sociodemographics, depressed mood, pain, social support, and self-efficacy at three months post-injury, and depressed mood one year post-injury. Results: Hierarchical multiple linear regression analyses revealed that pain (β = 0.14; p < 0.01) and social support (β = -0.18; p < 0.001) were significant predictors of depressed mood. Self-efficacy moderated the relationship of pain (β = -0.12; p < 0.05) and depressed mood after one year. Lower self-efficacy in combination with pain had a stronger impact than higher self-efficacy and pain on depressed mood. Social support did not moderate the association. Conclusions: Self-efficacy for managing pain is important in the development of depressed mood. According to the results of this study, we suggest that the detection of low social support and low self-efficacy might be important in long-term rehabilitation process. Implications for Rehabilitation Risk for depressed mood one year after an accident is high: One in five workers report depressed mood. Protective factors for depressed mood in injured workers needs to be considered in the rehabilitation. Focusing on resources like social support and self-efficacy could be protective against depressed mood. The early detection of low social support and low self-efficacy might be important in long-term rehabilitation processes

Monitoring Programmes, Multiple Stress Analysis and Decision Support for River Basin Management

The identification of plausible causes for water body status deterioration will be much easier if it can build on available, reliable, extensive and comprehensive biogeochemical monitoring data (preferably aggregated in a database). A plausible identification of such causes is a prerequisite for well-informed decisions on which mitigation or remediation measures to take. In this chapter, first a rationale for an extended monitoring programme is provided; it is then compared to the one required by the Water Framework Directive (WFD). This proposal includes a list of relevant parameters that are needed for an integrated, a priori status assessment. Secondly, a few sophisticated statistical tools are described that subsequently allow for the estiation of the magnitude of impairment as well as the likely relative importance of different stressors in a multiple stressed environment. The advantages and restrictions of these rather complicated analytical methods are discussed. Finally, the use of Decision Support Systems (DSS) is advocated with regard to the specific WFD implementation requirements.