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Gerard Litjens is enthousiast over de kwaliteit van de natuurontwikkeling langs de Waal, resultaat van onder meer Ruimte voor de Rivier-projecten. Hij maakt zich echter grote zorgen over de erosie van de rivierbodem, waardoor de uiterwaarden dreigen te verdrogen en dat is desastreus voor de natuur langs de rivier. Hij neemt ons mee naar het uiterste westen van Gelderland, het Munnikenland. Gerard Litjens is een van de oprichters en directeurs van Bureau Stroming en heeft meegewerkt aan de Integrale Planstudie, de MER, het Inrichtingsplan en het Beheerplan voor dit gebied.

Responding to different questions generated by biodiversity and ecosystem services policy or management requires different forms of knowledge (e.g. scientific, experiential) and knowledge synthesis. Additionally, synthesis methods need to be appropriate to policy context (e.g. question types, budget, timeframe, output type, required scientific rigour). In this paper we present a range of different methods that could potentially be used to conduct a knowledge synthesis in response to questions arising from knowledge needs of decision makers on biodiversity and ecosystem services policy and management. Through a series of workshops attended by natural and social scientists and decision makers we compiled a range of question types, different policy contexts and potential methodological approaches to knowledge synthesis. Methods are derived from both natural and social sciences fields and reflect the range of question and study types that may be relevant for syntheses. Knowledge can be available either in qualitative or quantitative form and in some cases also mixed. All methods have their strengths and weaknesses and we discuss a sample of these to illustrate the need for diversity and importance of appropriate selection. To summarize this collection, we present a table that identifies potential methods matched to different combinations of question types and policy contexts, aimed at assisting teams undertaking knowledge syntheses to select appropriate methods.

The absence of a good interface between scientific and other knowledge holders and decision-makers in the area of biodiversity and ecosystem services has been recognised for a long time. Despite recent advancements, e.g. with the Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES), challenges remain, particularly concerning the timely provision of consolidated views from different knowledge domains. To address this challenge, a strong and flexible networking approach is needed across knowledge domains and institutions. Here, we report on a broad consultation process across Europe to develop a Network of Knowledge on biodiversity and ecosystem services (NoK), an approach aiming at (1) organising institutions and knowledge holders in an adaptable and responsive framework and (2) informing decision-makers with timely and accurate biodiversity knowledge. The consultation provided a critical analysis of the needs that should be addressed by a NoK and how it could complement existing European initiatives and institutions at the interface between policy and science. Among other functions, the NoK provides consolidated scientific views on contested topics, identification of research gaps to support relevant policies, and horizon scanning activities to anticipate emerging issues. The NoK includes a capacity building component on interfacing activities and contains mechanisms to ensure its credibility, relevance and legitimacy. Such a network would need to ensure credibility, relevance and legitimacy of its work by maximizing transparency and flexibility of processes, quality of outputs, the link to data and knowledge provision, the motivation of experts for getting involved and sound communication and capacity building.

A major challenge is to develop a biodiversity observation system that is cost effective and applicable inany geographic region. Measuring and reliable reporting of trends and changes in biodiversity requiresamongst others detailed and accurate land cover and habitat maps in a standard and comparable way. The objective of this paper is to assess the EODHaM (EO Data for Habitat Mapping) classification resultsfor a Dutch case study. The EODHaM system was developed within the BIO SOS (The BIOdiversity multi-SOurce monitoring System: from Space TO Species) project and contains the decision rules for each landcover and habitat class based on spectral and height information. One of the main findings is that canopyheight models, as derived from LiDAR, in combination with very high resolution satellite imagery providesa powerful input for the EODHaM system for the purpose of generic land cover and habitat mapping forany location across the globe. The assessment of the EODHaM classification results based on field datashowed an overall accuracy of 74% for the land cover classes as described according to the Food andAgricultural Organization (FAO) Land Cover Classification System (LCCS) taxonomy at level 3, while theoverall accuracy was lower (69.0%) for the habitat map based on the General Habitat Category (GHC)system for habitat surveillance and monitoring. A GHC habitat class is determined for each mapping uniton the basis of the composition of the individual life forms and height measurements. The classificationshowed very good results for forest phanerophytes (FPH) when individual life forms were analyzed interms of their percentage coverage estimates per mapping unit from the LCCS classification and validatedwith field surveys. Analysis for shrubby chamaephytes (SCH) showed less accurate results, but might alsobe due to less accurate field estimates of percentage coverage. Overall, the EODHaM classification resultsencouraged us to derive the heights of all vegetated obje

tMonitoring land cover and habitat change is a key issue for conservation managers because of its poten-tial negative impact on biodiversity. The Land Cover Classification System (LCCS) and the General HabitatCategories (GHC) System have been proposed by the remote sensing and ecological research community,respectively, for the classification of land covers and habitats across various scales. Linking the two sys-tems can be a major step forward towards biodiversity monitoring using remote sensing. The translationbetween the two systems has proved to be challenging, largely because of differences in definitions andrelated difficulties in creating one-to-one relationships between the two systems. This paper proposesa system of rules for linking the two systems and additionally identifies requirements for site-specificcontextual and environmental information to enable the translation. As an illustration, the LCCS clas-sification of the Le Cesine protected area in Italy is used to show rules for translating the LCCS classesto GHCs. This study demonstrates the benefits of a translation system for biodiversity monitoring usingremote sensing data but also shows that a successful translation is often depending on the degree ofecological knowledge of the habitats and its relationship with land cover and contextual information.

Om de biodiversiteit te versterken moeten dieren en planten kunnen gaan en staan waar ze willen. Natuurgebieden moeten daarom op Europees niveau op elkaar aansluiten. Onderzoekers van Wageningen UR maakten een eerste kaart van zo’n ecologisch netwerk. De praktische uitwerking vraagt nog veel afstemming tussen lidstaten

Both science and policy require a practical, transmissible, and reproducible procedure for surveillance and monitoring of European habitats, which can produce statistics integrated at the landscape level. Over the last 30 years, landscape ecology has developed rapidly, and many studies now require spatial data on habitats. Without rigorous rules, changes from baseline records cannot be separated reliably from background noise. A procedure is described that satisfies these requirements and can provide consistent data for Europe, to support a range of policy initiatives and scientific projects. The methodology is based on classical plant life forms, used in biogeography since the nineteenth century, and on their statistical correlation with the primary environmental gradient. Further categories can therefore be identified for other continents to assist large scale comparisons and modelling. The model has been validated statistically and the recording procedure tested in the field throughout Europe. A total of 130 General Habitat Categories (GHCs) is defined. These are enhanced by recording environmental, site and management qualifiers to enable flexible database interrogation. The same categories are applied to areal, linear and point features to assist recording and subsequent interpretation at the landscape level. The distribution and change of landscape ecological parameters, such as connectivity and fragmentation, can then be derived and their significance interpreted.

Powerpointpresentatie over biodiesel uit Brazilië: technieken en duurzaamheid

Powerpoint presentation about biodiesel. In order to meat the EU targets, the Netherlands could be an important importer of biodiesel. Brazil could be an important exporter of biodiesel. Presentation of a case study with Brazil and the Netherlands

Brief review of the workshop contributions, which are all built around the different aspects of the presentday landscapes

Definitions of landscape ecology and the three basic categories of geographical area - 'natural systems of landscapes (Naturräume)', 'landscapes as natural-technical categories (=cultural landscapes)' and 'socioeconomic regions' - form the basis for a discussion of reference areas in landscape ecology. It is concluded that there is no scientific justification for having one, universally applicable, reference area for landscape ecology research. The most useful and relevant reference area must be chosen afresh each time a new issue relating to land use and its effect on the European cultural landscapes is tackled. This concept is illustrated using landscape units and watersheds as examples. In the future we need to find a way of integrating the different reference areas within a stringent scalar hierarchy of landscape ecological spatial categories.