Impacts of land cover data selection and trait parameterisation on dynamic modelling of species' range expansion

Peer reviewedPublisher PD

Wetland distribution modelling for optimal land use options in Europe

This spatial study contributes to a modelling project that, in combination with biodiversity analyses and an economic model, evaluates potentials to preserve existing habitats, to restore formerly native habitats, as well as to create non-native managed habitats with respect to freshwater wetlands of the EU. This paper deals with the methodological development of the wetland distribution model and illustration of its results. Through a GIS-based model the extent of existing wetland distribution is visualised. Additionally, potential convertible sites are modelled for (re-) creation of wetland biotopes.wetlands, land use

Assessing the role of EO in biodiversity monitoring: options for integrating in-situ observations with EO within the context of the EBONE concept

The European Biodiversity Observation Network (EBONE) is a European contribution on terrestrial monitoring to GEO BON, the Group on Earth Observations Biodiversity Observation Network. EBONE’s aims are to develop a system of biodiversity observation at regional, national and European levels by assessing existing approaches in terms of their validity and applicability starting in Europe, then expanding to regions in Africa. The objective of EBONE is to deliver: 1. A sound scientific basis for the production of statistical estimates of stock and change of key indicators; 2. The development of a system for estimating past changes and forecasting and testing policy options and management strategies for threatened ecosystems and species; 3. A proposal for a cost-effective biodiversity monitoring system. There is a consensus that Earth Observation (EO) has a role to play in monitoring biodiversity. With its capacity to observe detailed spatial patterns and variability across large areas at regular intervals, our instinct suggests that EO could deliver the type of spatial and temporal coverage that is beyond reach with in-situ efforts. Furthermore, when considering the emerging networks of in-situ observations, the prospect of enhancing the quality of the information whilst reducing cost through integration is compelling. This report gives a realistic assessment of the role of EO in biodiversity monitoring and the options for integrating in-situ observations with EO within the context of the EBONE concept (cfr. EBONE-ID1.4). The assessment is mainly based on a set of targeted pilot studies. Building on this assessment, the report then presents a series of recommendations on the best options for using EO in an effective, consistent and sustainable biodiversity monitoring scheme. The issues that we faced were many: 1. Integration can be interpreted in different ways. One possible interpretation is: the combined use of independent data sets to deliver a different but improved data set; another is: the use of one data set to complement another dataset. 2. The targeted improvement will vary with stakeholder group: some will seek for more efficiency, others for more reliable estimates (accuracy and/or precision); others for more detail in space and/or time or more of everything. 3. Integration requires a link between the datasets (EO and in-situ). The strength of the link between reflected electromagnetic radiation and the habitats and their biodiversity observed in-situ is function of many variables, for example: the spatial scale of the observations; timing of the observations; the adopted nomenclature for classification; the complexity of the landscape in terms of composition, spatial structure and the physical environment; the habitat and land cover types under consideration. 4. The type of the EO data available varies (function of e.g. budget, size and location of region, cloudiness, national and/or international investment in airborne campaigns or space technology) which determines its capability to deliver the required output. EO and in-situ could be combined in different ways, depending on the type of integration we wanted to achieve and the targeted improvement. We aimed for an improvement in accuracy (i.e. the reduction in error of our indicator estimate calculated for an environmental zone). Furthermore, EO would also provide the spatial patterns for correlated in-situ data. EBONE in its initial development, focused on three main indicators covering: (i) the extent and change of habitats of European interest in the context of a general habitat assessment; (ii) abundance and distribution of selected species (birds, butterflies and plants); and (iii) fragmentation of natural and semi-natural areas. For habitat extent, we decided that it did not matter how in-situ was integrated with EO as long as we could demonstrate that acceptable accuracies could be achieved and the precision could consistently be improved. The nomenclature used to map habitats in-situ was the General Habitat Classification. We considered the following options where the EO and in-situ play different roles: using in-situ samples to re-calibrate a habitat map independently derived from EO; improving the accuracy of in-situ sampled habitat statistics, by post-stratification with correlated EO data; and using in-situ samples to train the classification of EO data into habitat types where the EO data delivers full coverage or a larger number of samples. For some of the above cases we also considered the impact that the sampling strategy employed to deliver the samples would have on the accuracy and precision achieved. Restricted access to European wide species data prevented work on the indicator ‘abundance and distribution of species’. With respect to the indicator ‘fragmentation’, we investigated ways of delivering EO derived measures of habitat patterns that are meaningful to sampled in-situ observations

Uncertainties in Ecosystem Service Maps: A Comparison on the European Scale

Safeguarding the benefits that ecosystems provide to society is increasingly included as a target in international policies. To support such policies, ecosystem service maps are made. However, there is little attention for the accuracy of these maps. We made a systematic review and quantitative comparison of ecosystem service maps on the European scale to generate insights in the uncertainty of ecosystem service maps and discuss the possibilities for quantitative validation. Maps of climate regulation and recreation were reasonably similar while large uncertainties among maps of erosion protection and flood regulation were observed. Pollination maps had a moderate similarity. Differences among the maps were caused by differences in indicator definition, level of process understanding, mapping aim, data sources and methodology. Absence of suitable observed data on ecosystem services provisioning hampers independent validation of the maps. Consequently, there are, so far, no accurate measures for ecosystem service map quality. Policy makers and other users need to be cautious when applying ecosystem service maps for decision-making. The results illustrate the need for better process understanding and data acquisition to advance ecosystem service mapping, modelling and validation

GMES-service for assessing and monitoring subsidence hazards in coastal lowland areas around Europe. SubCoast D3.5.1

This document is version two of the user requirements for SubCoast work package 3.5, it is SubCoast deliverable 3.5.1. Work package 3.5 aims to provide a European integrated GIS product on subsidence and relative sea level rise. The first step of this process was to contact the European Environment Agency as the main user to discover their user requirements. This document presents these requirments, the outline methodology that will be used to carry out the integration and the datasets that will be used. In outline the main user requirements of the EEA are: 1. Gridded approach using an Inspire compliant grid 2. The grid would hold data on: a. Likely rate of subsidence b. RSLR c. Impact (Vulnerability) d. Certainty (confidence map) e. Contribution of ground motion to RSLR f. A measure of certainty in the data provided g. Metadata 3. Spatial Coverage - Ideally entire coastline of all 37 member states a. Spatial resolution - 1km 4. Provide a measure of the degree of contribution of ground motion to RSLR The European integration will be based around a GIS methodology. Datasets will be integrated and interpreted to provide information on data vlues above. The main value being a likelyhood of Subsidence. This product will initially be developed at it’s lowest level of detail for the London area. BGS have a wealth of data for london this will enable this less detialed product to be validated and also enable the generation of a more detailed product usig the best data availible. One the methodology has been developed it will be pushed out to other areas of the ewuropean coastline. The initial input data that have been reviewed for their suitability for the European integration are listed below. Thesea re the datasets that have European wide availibility, It is expected that more detailed datasets will be used in areas where they are avaiilble. 1. Terrafirma Data 2. One Geology 3. One Geology Europe 4. Population Density (Geoland2) 5. The Urban Atlas (Geoland2) 6. Elevation Data a. SRTM b. GDEM c. GTOPO 30 d. NextMap Europe 7. MyOceans Sea Level Data 8. Storm Surge Locations 9. European Environment Agencya. Elevation breakdown 1km b. Corine Land Cover 2000 (CLC2000) coastline c. Sediment Discharges d. Shoreline e. Maritime Boundaries f. Hydrodynamics and Sea Level Rise g. Geomorphology, Geology, Erosion Trends and Coastal Defence Works h. Corine land cover 1990 i. Five metre elevation contour line 10. FutureCoas