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Introduction: ecological networks and greenways
No full textBrief review of the workshop contributions, which are all built around the different aspects of the presentday landscape
European Biodiversity Observation Network: D1.1 The Selection of Biodiversity indicators for EBONE Development Work
Full text linkThe main aim of this report is to assess which biodiversity indicators should be selected as the basis for developing new EBONE methodologies for assessing biodiversity. These methodologies will combine different types and scales of biodiversity relevant observations and form the basis of recommendations on the design and implementation of the European Biodiversity Observation Network.
2. The development of EBONE and the choice of these test indicators is set in the context of the emerging goal to develop a GEO (global) Biodiversity Observation Network (GEO BON) and its implementation within an institutional framework operating at the European level. One of the main requirements from EBONE will be to provide continued access to data for CBD reporting against the 2010 target at national and European levels. Hence, the indicator selection process began with a brief overview of biodiversity indicators used (or proposed) in large scale (national, continental or global ) programmes. It covered indicators in the GEO Global Biodiversity Observation Network (GEO BON), the European CBD indicators (SEBI), composite indicators and indicator taxa. It also made use of results and ongoing efforts of European research projects.
3. The lack of data is probably the biggest constraint on the development and use of indicators for large-scale (national, European and global) biodiversity assessments. Two of the key questions EBONE is addressing are: (i) can we make better use of the existing biodiversity observation data (e.g. to produce indicators) by combining them in novel ways and making better use of remote sensing technologies; and (ii) are there some simple observations that could be used across Europe within existing programmes that would give added value to existing data? The types of data we are looking to combine in this process are collected at different scales and with different methodologies and levels of sampling intensity. They include: (i) in-situ biodiversity survey and monitoring data on species or habitats i.e from field observations or samples; (ii) in-situ biodiversity data from Long-term Ecosystem Research Sites (LTER) in Europe; and (iii) remote sensing data, from both satellite and airborne data sources.
4. The EuMon database has shown that there are major gaps in the coverage of biodiversity data at the European level. Some of the most significant gaps for the delivery of biodiversity indicators are in relation to systems for monitoring changes in the extent and quality of habitats and the lack of systems and models for combining in situ observations with remotely sensed data to provide reliable European statistics and “wall to wall” assessments of a broader range of biodiversity indicators.
5. A habitat monitoring system (BioHab) has been developed that enables consistent recording and monitoring of habitats across Europe, and potentially, globally. The habitat monitoring system that EBONE is using is based on BioHab and has 154 General Habitat Categories (GHCs) derived from 16 easily identifiable Life-Forms and 18 Non Life Forms. BioHab provides an easily repeatable system for use in the field that can be cross-related to other habitat classification schemes such as Habitat Derective Annex I and EUNIS. The GHCs can be easily identified on the ground, because they are based on life forms. They may provide the lowest common denominator linking to other sources of data required for assessing biodiversity e.g. phytosociology, birds and butterflies. They may also be more easily discriminated from the air or space using remote sensing methods because of the system is based on habitat structure The BioHab approach provides an extremely powerful assessment tool for biodiversity, providing a missing link between detailed site-based species, population and community level measures and extensive assessments of habitats from remote sensing.
6. One of the main aims of EBONE is to develop and test methods aimed at realising the potential of BioHab as a core component of a European Biodiversity Observation system. To identify appropriate indicators for this development work we undertook an expert assessment of the SEBI “Streamlining European 2010 Biodiversity Indicators” set of 26 indicators taking account of: the availability of data; and the potential added value of combining data from different sources (including BioHab) to produce a more cost-effective set of indicators.
7. The conclusion of this assessment was that EBONE would focus its initial development work on three main headline indicators covering: (i) habitats of European interest in the context of a broad habitat assessment; (ii) abundance and distribution of selected species (birds, butterflies and plants); and (iii) fragmentation of natural and semi-natural areas.
8. Two additional indicators were also identified that might fill key gaps in the SEBI set. These were related to: (i) indicators of climate change impacts on biodiversity and ecosystems; and (ii) assessments of ecosystem services. These two areas may be considered again later in the project as methodologies for combining data from different sources are developed.
9. Work will now focus on the statistical aspects of inter-calibration and the development of criteria for assessing the added value of combining data from different sources
Landscape fragmentation as an indicator of coastal landscape quality: an application along the Apulian coast (southern Italy),45. MININNI M., MINUNNO F., LERONNI V., TARANTINO C. MAIROTA P..(2007), Landscape fragmentation as an indicator of coastal landscape quality: an application along the Apulian coast (southern Italy),
No full textThis work has being carried out within the framework of the IMCA (Integrated Monitoring of Coastal Areas) Research Project, among the activities aimed at drawing coastal landscape quality maps through the use of indicators derived from satellite RS images. The overall research project, moving from the experience of the European Landscape Convention, tackles the landscape quality issue via a multi temporal and spatial scale approach.
The present contribution focuses on fragmentation as this phenomenon, as well as the loss of heterogeneity, initiated by urban settlement processes of dislocation and diffusion, represents the main cause of the landscape ecological efficiency decrease, of the area decay and of the beginning of diseconomy in its management (Forman, 1995).
In order to quantify fragmentation, at a given spatial scale (defined in terms of both grain and extent), a set of LPI (ED, LSI, ENN_AM, PLADJ, MESH, SHDI) was computed at the landscape level on a sample plot population, extracted via an unaligned random samplingprocedure from the whole southernmost part of the Apulian peninsula (Southern Italy) and for which intepretation of recent aerial photographs had already been performed within the framework of the IMCA research project (Miacola et al. 2006). The same protocol was applied to categorical maps of the same area, derived, both by past aerial photointerpretation and by (unsupervided and supervised) segmentation, from medium (Landsat TM) resolution satellite images of two time steps.
Preliminary results are encouraging in many respects. The distribution analysis performed on the indexes computed on the different data sets show, for this particular landscape at the given scale, a significant trend towards a normal distribution model, thus contributing to the ongoing debate (Remmel and Csillag 2003) on the uncertainties about the possibility to statistically compare indexes computed in different times and places, deriving by the lack of knowledge about their distribution. Principal component analysis performend on the indexes obtained from the different data sets, yields the ordination of sample plots along a fragmentation gradient, that migth be used to construct framentation intensity maps at the subregional scale, as well as to interpreting the change processes and obtain intelligent maps based upon the integration of field (aerial-photo interpetation) and and RS data, thus achieving the twofold purpouse of performing a phenomenological study aimed both at tmodelling coastal landscape transformations and identifying new survey categories that may have the temporal dimension as a reading parameter (e.g.. speed of change). As far as the relations between the indexes computed on the different data sets are concerned, they allow for the assessment of the potentials for using unsupervised categorical maps for the description and monitoring of landscapes fragmentation, as well as for testing hypoteses concerning fragmentation scaling relations in both space and time (Wu, 2004; Jelinski and Wu 1996
Research Agenda Setting for the Argentinean Chaco : Biofuels, cattle breeding and sustainable development in the Chaco of Argentina = Construyendo una agenda conjunta para la investigación en el Chaco Argentino : biocombustibles, ganadero y desarrollo sostenible en el Chaco Argentina
No full textThis report is the result of a project carried out on request of the Dutch Embassy in Buenos Aires for identification of the potential developments of agricultural developments and its environmental and land use implications in the Argentinean Chaco. A joint Argentinean Dutch workshop has been held in Santiago del Estero with invited guests from various Argentinean interest groups. The workshop had the form of a SWOT analysis. The results are presented in this report.EEA Santiago del EsteroFil: Nijhof, B.S.J. Wageningen University. Alterra; HolandaFil: Prieto Garra, Daniel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santiago del Estero; ArgentinaFil: Bindraban, P.S. Wageningen University. Plant Research International; HolandaFil: Mansfeld, M.J.M. van. Wageningen University. Alterra; HolandaFil: Jongman, R.H.G. Wageningen University. Alterra; HolandaFil: Querner, E.P. Wageningen University. Alterra; Holand
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