Jenica Hanganu

Managing aquatic ecosystems and water resources under multiple stress--an introduction to the MARS project.

Water resources globally are affected by a complex mixture of stressors resulting from a range of drivers, including urban and agricultural land use, hydropower generation and climate change. Understanding how stressors interfere and impact upon ecological status and ecosystem services is essential for developing effective River Basin Management Plans and shaping future environmental policy. This paper details the nature of these problems for Europes water resources and the need to find solutions at a range of spatial scales. In terms of the latter, we describe the aims and approaches of the EU-funded project MARS (Managing Aquatic ecosystems and water Resources under multiple Stress) and the conceptual and analytical framework that it is adopting to provide this knowledge, understanding and tools needed to address multiple stressors. MARS is operating at three scales: At the water body scale, the mechanistic understanding of stressor interactions and their impact upon water resources, ecological status and ecosystem services will be examined through multi-factorial experiments and the analysis of long time-series. At the river basin scale, modelling and empirical approaches will be adopted to characterise relationships between multiple stressors and ecological responses, functions, services and water resources. The effects of future land use and mitigation scenarios in 16 European river basins will be assessed. At the European scale, large-scale spatial analysis will be carried out to identify the relationships amongst stress intensity, ecological status and service provision, with a special focus on large transboundary rivers, lakes and fish. The project will support managers and policy makers in the practical implementation of the Water Framework Directive (WFD), of related legislation and of the Blueprint to Safeguard Europes Water Resources by advising the 3rd River Basin Management Planning cycle, the revision of the WFD and by developing new tools for diagnosing and predicting multiple stressors.

Classifying aquatic macrophytes as indicators of eutrophication in European lakes

Aquatic macrophytes are one of the biological quality elements in the Water Framework Directive (WFD) for which status assessments must be defined. We tested two methods to classify macrophyte species and their response to eutrophication pressure: one based on percentiles of occurrence along a phosphorous gradient and another based on trophic ranking of species using Canonical Correspondence Analyses in the ranking procedure. The methods were tested at Europe-wide, regional and national scale as well as by alkalinity category, using 1,147 lakes from 12 European states. The grouping of species as sensitive, tolerant or indifferent to eutrophication was evaluated for some taxa, such as the sensitive Chara spp. and the large isoetids, by analysing the (non-linear) response curve along a phosphorous gradient. These thresholds revealed in these response curves can be used to set boundaries among different ecological status classes. In total 48 taxa out of 114 taxa were classified identically regardless of dataset or classification method. These taxa can be considered the most consistent and reliable indicators of sensitivity or tolerance to eutrophication at European scale. Although the general response of well known indicator species seems to hold, there are many species that were evaluated differently according to the database selection and classification methods. This hampers a Europe-wide comparison of classified species lists as used for the status assessment within the WFD implementation process.

Responses of ecotypes of Phragmites australis to increased seawater influence: a field study in the Danube Delta, Romania

Abstract The effects of locally increased salinity in a complex of Fine and Giant reed (Phragmites australis) clones were investigated in the Tataru channel (Danube Delta, Romania). Following digging of the Tataru channel, the area closest to the sea became isolated from freshwater input, causing saline conditions to develop due to its proximity to the sea. The other side of the channel remained a freshwater area. The impact of increased salinity on the regression of reed was studied and related to a possible difference in susceptibility to high salt concentrations between different clones (Octoploid Giant reed versus Tetraploid Fine reed). Measurements were made in survey plots situated on both sides of the channel. In freshwater, Giant reed had higher and thicker shoots than Fine reed, but stem density was much smaller, resulting in a lower biomass per surface area of Giant reed. Growth of both Giant and Fine reed was severely reduced at the saline east side of the channel. A significant interaction was found between reed type and salinity. Giant reed density, height, stem diameter and biomass were more strongly affected by saline conditions than Fine reed. The salinization of the parts east of the channel might thus have affected Giant reed stands more strongly than Fine reed stands. The implications for reed succession under increased salinity in the delta are discussed.

Phenotypic differences among ploidy levels of Phragmites australis growing in Romania

This paper presents data showing phenotypic differences of Phragmites australis (Cav.) Trin. ex Steud. (Common reed) growing in Comana lake and in the Danube Delta (Romania). In Comana lake, tetra- and octoploids were found, whereas in the Danube Delta also hexaploids occurred. In freshwater habitats, shoots of octoploids were longer and thicker with more nodes than those of tetraploids. Panicles of octopoids were also larger than those of tetraploids. The number of alive leaves did not differ between ploidy levels. Total leaf area, however was higher of octo- than of tetraploids, which indicates that octoploids produced larger leaves. Octoploids also had thicker rhizomes. No differences in allocation of dry matter to leaves, stems, and leaves (blades and sheaths) were found between tetra- and octoploids. Both tetra- and octoploids shoots were among the tallest in the central Danube Delta. Tetraploids were morphologically more diverse in Comana lake than in the central Danube Delta. Within areas, size of shoots could, however, not be related to water depth. Salinity reduced shoot size of tetraploids considerably. Under saline conditions, no differences in morphology of shoots were found between tetra- and hexaploids. ([KEYWORDS: Danube Delta; water depth; salinity;environmental stress; plant morphology; Phragmites australis]

Classification of Danube Delta lakes based on aquatic vegetation and turbidity

The aquatic vegetation present in lakes in the delta of the River Danube was studied using field survey data and satellite image. Based on the spectral information from satellite images, three categories of lakes were distinguished: clear / macrophyte-dominated, intermediate and turbid / poorly vegetated. The satellite-based classification was consistent with vegetation cover and water transparency measured in the field. Cluster analysis of vegetation data from 235 releves made in 22 lakes (1996-1998, each year in June) identified ten submerged vegetation types. The lakes were characterised by the frequency of occurrence of each vegetation type and ordinated, using Principal Components Analysis (PCA). A strong relationship appeared between the composition and density of aquatic vegetation and water transparency. Isolated lakes within the extensive beds of floating reed (plaur lakes) formed a separate group. Based on the ordination analysis, connectivity of lakes in the Danube Delta was concluded to be a major factor for the development of dense macrophyte vegetation.

First steps in the Central-Baltic intercalibration exercise on lake macrophytes: where do we start?

The Water Framework Directive (WFD 2000) defines macrophytes as one of the biological groups required for the ecological assessment of European surface waters. Several indices for macrophyte assessment have been proposed or are currently in use by different European states. As a first step towards performing an intercalibration of these indices a common dataset was developed. This dataset contains abundance data on 789 macrophyte species from 316 different lake sites in ten European countries. Various common species and genera were identified as indicators of reference and impacted conditions within the dataset. Cluster analysis of macrophyte data, supported by non-metric multidimensional scaling, indicated that clusters formed were more reflective of their source country rather than lake type. This might be caused by differences in regional climate, biogeography, monitoring techniques, or a combination of these factors. A total of six national indices were applied to assign quality classes to the lakes. However, this produced results that often differed by one or two quality classes for the same site. We foresee that a more precise intercalibration exercise is necessary, and it should be based on more detailed data considering both seasonality and the latitudinal differences within the area covered.

IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING SYNERGY BETWEEN LiDAR, RADARSAT-2 AND SPOT-5 IMAGES FOR THE DETECTION AND MAPPING OF WETLAND VEGETATION IN THE DANUBE DELTA

Wetlands are among the most productive natural environments on Earth, as they harbor exceptional biological diversity. For this paper, our study site was the Danube Delta. The biodiversity of the Danube Delta is extraordinary and it possesses one of the largest reed beds in the world. The main goal of our paper was to recognize, characterize, and map the main vegetation units of the Danube Delta. The paper emphasizes the importance of the joint use of LiDAR measurements (acquired in May 2011), RADARSAT-2 radar data (acquired on June 4, 2011), and SPOT-5 optical data (acquired on May 25, 2011). LiDAR data allow for the characterization of vegetation height within centimeter accuracy (10 cm). The radar measurements are based on C-band, providing additional information about the structure of the vegetation cover. The simultaneous acquisition of HH, HV, VV, and VH polarizations enabled us to discriminate between the targets, depending on their responses to the various polarizations, by calculating their polarimetric signatures. By linking multispectral LiDAR and radar data, information can be obtained about vegetation reflectance and height as well as the backscattering mechanism, allowing for improved mapping and characterization accuracy (90.60% mean accuracy). An accuracy assessment of the classification results was evaluated against the vegetation data recorded in the field.

Change detection in floodable areas of the Danube delta using radar images

In the wetlands of the Danube delta floodplain, flooding is a major natural risk. The coastal wetlands have been seriously impacted by floods in 2002, 2005, 2006 and 2010. Using hydrological and satellite observations acquired in 2009 and during the summer of 2010, this paper tackles the issue of forecasting risk based on land cover information and observations. A major objective of this methodological work consists in exploring several types of data from the Japanese ALOS satellite. These data are used to illustrate a multi-temporal radar data processing methodology based on temporal entropy analysis that enables change detection in the floodable areas of the Danube delta.

Alteration and Remediation of Coastal Wetland Ecosystems in the Danube Delta. A Remote-Sensing Approach

Wetlands are important and valuable ecosystems; yet, since 1900, more than 50% of wetlands have been lost worldwide. An example of altered and partially restored coastal wetlands is the Danube Delta in Romania. Over time, human intervention has manifested itself in more than one-quarter of the entire Danube surface. This intervention was brutal and has rendered ecosystem restoration very difficult. Studies for rehabilitation/re-vegetation were begun immediately after the Danube Delta was declared a Biosphere Reservation in 1990. Remote sensing offers accurate methods for detecting changes in restored wetlands. Vegetation change detection is a powerful indicator of restoration success. The restoration projects use vegetative cover as an important indicator of restoration success. To follow the evolution of the vegetation cover of the restored areas, images obtained by radar and optical satellites, such as Sentinel-1 and Sentinel-2, have been used. The sensitivity of such sensors to the landscape depends on the wavelength of the radar or optical detection system and, for radar data, on polarization. Combining these types of data, which are associated with the density and size of the vegetation, is particularly relevant for the classification of wetland vegetation. In addition, the high temporal acquisition frequencies used by Sentinel-1, which are not sensitive to cloud cover, allow the use of temporal signatures of different land covers. Thus, to better understand the signatures of the different study classes, we analyze the polarimetric and temporal signatures of Sentinel-1 data. In a second phase, we perform classifications based on the Random Forest supervised classification algorithm involving the entire Sentinel-1 time series, proceeding through a Sentinel-2 collection and finally involving combinations of Sentinel-1 and-2 data. The supervised classifier used is the Random Forest algorithm that is available in the OrfeoToolbox (version 5.6) free software. Random Forest is an ensemble learning technique that builds upon multiple decision trees and is particularly relevant when combining different types 2 of indicators. The results of this study relate to the use of combinations of data from different satellite sensors (multi-date Sentinel-1, Sentinel-2) to improve the accuracy of recognition and mapping of major vegetation classes in the restoring areas of the Danube Delta. First, the data from each sensor are classified and analyzed. The results obtained in the first step show quite good classification performance for only one Sentinel-2 data (87.5% mean accuracy), in contrast to the very good results obtained using the Sentinel-1 time series (95.7% mean accuracy). The combination of Sentinel-1 time series and optical data from Sentinel-2 improved the performance of the classification (97.1%).