The use of remote sensing to characterise hydromorphological properties of European rivers

Remote sensing (RS) technology offers unparalleled opportunities to explore river systems using RADAR, multispectral, hyperspectral, and LIDAR data. The accuracy reached by these technologies recently has started to satisfy the spatial and spectral resolutions required to properly analyse the hydromorphological character of river systems at multiple scales. Using the River Hierarchical Framework (RHF) as a reference we describe the state-ofthe- art RS technologies that can be implemented to quantify hydromorphological characteristics at each of the spatial scales incorporated in the RHF (i.e. catchment, landscape unit, river segment, river reach, sub-reach - geomorphic and hydraulic units). We also report the results of a survey on RS data availability in EU member states that provides the basis for a discussion on the current potential to derive RHF hydromorphological indicators from high-resolution multispectral images and topographic LiDAR at the national scale across Europe. This paper shows that many of the assessment indicators proposed by the RHF can be already derived by different RS sources and existing methodologies, and that EU countries have sufficient RS data at present to already begin their incorporation into hydromorphology assessment and monitoring, as mandated by WFD, which so far have been insufficiently addressed by the member states due to the demanding efforts it would require. With cooperation and planning, RS data can form a fundamental component of hydromorphological assessment and monitoring in the future to help support the effective and sustainable management of rivers, and this would be done most effectively through the establishment of multi-purpose RS acquisition campaigns and the development of shared and standardized hydromorphological RS databases updated regularly through planned resurveyed campaigns.JRC.H.1-Water Resource

The hydrodynamic drag of full scale trees

River hydrodynamicsOverbank flows and vegetatio

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

A multi-scale hierarchical framework for developing understanding of river behaviour to support river management

The work leading to this paper was funded through the European Union’s FP7 programme under Grant Agreement No. 282656 (REFORM). The framework methodology was developed within the context of Deliverable D2.1 of the REFORM programme, and all partners who contributed to the development of the four parts of this deliverable are included in the author list of this paper. More details on the REFORM framework can be obtained from part 1 of Deliverable D2.1 (Gurnell et al. 2014), which is downloadable from http://​www.​reformrivers.​eu/​results/​deliverables

Policy Issues in NEG Models: Established Results and Open Questions

This paper provides a non-technical overview of NEG models dealing with policy issues. Considered policy measures include alternative categories of public expenditure, international tax competition, unilateral actions of protection/liberalisation, and trade agreements. The implications of public intervention in two-region NEG models are discussed by unfolding the impact of policy measures on agglomeration/dispersion forces. Results are described in contrast with those obtained in standard non-NEG theoretical models. The high degree of abstraction limits the applicability of NEG models to real world policy issues. We discuss in some detail two extensions of NEG models to reduce this applicability gap: the cases of multi-regional frameworks and firm heterogeneity

Root-emitted volatile organic compounds: can they mediate belowground plant-plant interactions?

peer reviewedBackground Aboveground, plants release volatile organic compounds (VOCs) that act as chemical signals between neighbouring plants. It is now well documented that VOCs emitted by the roots in the plant rhizosphere also play important ecological roles in the soil ecosystem, notably in plant defence because they are involved in interactions between plants, phytophagous pests and organisms of the third trophic level. The roles played by root-emitted VOCs in between- and within-plant signalling, however, are still poorly documented in the scientific literature. Scope Given that (1) plants release volatile cues mediating plant-plant interactions aboveground, (2) roots can detect the chemical signals originating from their neighbours, and (3) roots release VOCs involved in biotic interactions belowground, the aim of this paper is to discuss the roles of VOCs in between- and within-plant signalling belowground. We also highlight the technical challenges associated with the analysis of root-emitted VOCs and the design of experiments targeting volatile-mediated root-root interactions. Conclusions We conclude that root-root interactions mediated by volatile cues deserve more research attention and that both the analytical tools and methods developed to study the ecological roles played by VOCs in interplant signalling aboveground can be adapted to focus on the roles played by root-emitted VOCs in between- and within-plant signalling

Longitudinal segmentation and characterization of river features based on Remote Sensing

International audienc