Refine
Document Type
- Article (1)
- Doctoral Thesis (1)
Language
- English (2) (remove)
Has Fulltext
- yes (2)
Is part of the Bibliography
- no (2) (remove)
Keywords
- environmental management (2) (remove)
Institute
Planted forests of alien tree species make significant contributions to the economy and provide multiple products and ecosystem services On the other hand, non-native trees now feature prominently on the lists of invasive alien plants in many parts of the world, and in some areas non-native woody species are now among the most conspicuous, damaging and, in some cases, best-studied invasive species. Afforestation and reforestation policies, both on public and private land, need to include clearly stated objectives and principles to reduce impacts of invasive trees outside areas set aside for forestry. With the intention of encouraging national authorities to implement general principles of prevention and mitigation of the risks posed by invasive alien tree species used in plantation forestry into national environmental policies, the Council of Europe facilitated the preparation of a Code of Conduct on Planted Forest and Invasive Alien Trees. This new voluntary Code, comprising 14 principles, complements existing codes of conduct dealing with horticulture and botanic gardens. The Code is addressed to all relevant stakeholders and decision makers in the 47 Member States of the Council of Europe. It aims to enlist the co-operation of the forest sector (trade and industry, national forest authorities, certification bodies and environmental organizations) and associated professionals in preventing new introductions and reducing, controlling and mitigating negative impacts due to tree invasions that arise, directly or indirectly, as a consequence of plantation forestry.
Bayesian Networks are computer-based environmental models that are frequently used to support decision-making under uncertainty. Under data scarce conditions, Bayesian Networks can be developed, parameterized, and run based on expert knowledge only. However, the efficiency of expert-based Bayesian Network modeling is limited by the difficulty in deriving model inputs in the time available during expert workshops. This thesis therefore aimed at developing a simple and robust method for deriving conditional probability tables from expert estimates in a time-efficient way. The design and application of this new elicitation and conversion method is demonstrated using a case study in Xinjiang, Northwest China. The key characteristics of this method are its time-efficiency and the approach to use different conversion tables based on varying levels of confidence. Although the method has its limitations, e.g. it can only be applied for variables with one conditioning variable; it provides the opportunity to support the parameterization of Bayesian Networks which would otherwise remain half-finished due to time constraints. In addition, a case study in the Murray-Darling Basin, Australia, is used to compare Bayesian Network types and software to improve the presentation clarity of large Bayesian Networks. Both case studies aimed at gaining insights on how to improve the applicability of Bayesian Networks to support environmental management.