Protective forests are an effective Forest-based Solution (FbS) for Ecosystem-based Disaster Risk Reduction (Eco-DRR) and are part of an integrated risk management (IRM) of natural hazards. However, their utilization requires addressing conflicting interests as well as considering relevant spatial and temporal scales. Decision support systems (DSS) can improve the quality of such complex decision-making processes regarding the most suitable and accepted combinations of risk mitigation measures. We introduce four easy-to-apply DSS to foster an ecosystem-based and integrated management of natural hazard risks as well as to increase the acceptance of protective forests as FbS for Eco-DRR: (1) the Flow-Py simulation tool for gravitational mass flows that can be used to model forests with protective functions and to estimate their potential for reducing natural hazards’ energy, (2) an exposure assessment model chain for quantifying forests’ relevance for reducing natural hazard risks, (3) the Rapid Risk management Appraisal (RRA), a participatory method aiming to identify IRM strengths and points for improvement, and (4) the Protective Forest Assessment Tool (FAT), an online DSS for comparing different mitigation measures. These are only a few examples covering various aims and spatial and temporal scales. Science and practice need to collaborate to provide applied DSS for an IRM of natural hazards.

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<p>The last decades have seen a higher attention payed to natural hazards due to the increasing losses and economic damages caused by them. Researchers, practitioners and local administrations studied the best way to mitigate and prevent them, using both structural and non-structural  defense techniques. Even though there are now several possible solutions to be used, it is not always easy for decision makers to choose the best option from both a technical and an economical point of view.</p><p>With the FAT tool we aimed at providing a useful mean for practitioners to help them choose between various protection options. The FAT tool is an online platform where the user, inserting a limited number of input data (e.g. slope profile, slope width, forest cover), is provided with an easily understandable output, that being a comparison of the costs and the benefits generated by different protection solutions.</p><p>The tool is built on an empirical, profile-based hazard model and deals with avalanches, rockfall and shallow landslides. The outputs of the hazard models are used to dimension and calculate the costs and benefits of several protection options and the damages avoided by those. The possible solutions considered are: ecosystem based solutions (e.g. protection forest), technical measures (e.g. snow fences, catching dams, rockfall nets), avoidance measures (e.g. road closure, building evacuation) and a combination of these. The most innovative part of the tool is the importance given to the role of the forest, and generally to the Eco-DRR solutions, on the hazard track, where a forest protection effect indicator is calculated to assess the effectiveness of a stand in mitigating the risk on the chosen profile. The outputs of the FAT tool, consisting in the index and the economic values of different alternative protection measures, can help the user identify the areas where the forests have the highest mitigation effect and choose where to allocate forest management resources.</p>

The International Journal of Disaster Risk Reduction (IJDRR) is the journal for researchers, policymakers and practitioners across diverse disciplines: earth sciences and their implications; environmental sciences; engineering; urban studies; geography; and the social sciences. IJDRR publishes fundamental and applied research, critical reviews, policy papers and case studies with a particular focus on multidisciplinary research that aims to reduce the impact of natural, technological, social and intentional disasters. IJDRR stimulates exchange of ideas and knowledge transfer on disaster research, mitigation, adaptation, prevention and risk reduction at all geographical scales: local, national and international. Key topics:-multifaceted disaster and cascading disasters the development of disaster risk reduction strategies and techniques discussion and development of effective warning and educational systems for risk management at all levels disasters associated with climate change vulnerability analysis and vulnerability trends emerging risks resilience against disasters The journal particularly encourages papers that approach risk from a multidisciplinary perspective.

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