Marius Lucian Matache

Plants accumulating heavy metals in the Danube River wetlands

BackgroundWe present herein our results regarding the accumulation of four heavy metals (copper, cadmium, lead, and zinc) in four aquatic species plants (Ceratophyllum demersum, Potamogeton pectinatus, Potamogeton lucens, Potamogeton perfoliatus) collected from the Danube River, South-Western part of Romania and their possible use as indicators of aquatic ecosystems pollution with heavy metals.MethodsElements concentration from the vegetal material was determined through Inductively Coupled Plasma – Mass Spectrometry.ResultsThe species were chosen based on their previous use as bioindicators in aquatic ecosystems and due to the fact they are one of the most frequent aquatic plant species of the Danube River ecosystems within the Iron Gates Natural Park. Highest amounts are recorded for Ceratophyllum demersum (3.52 μg/g for Cd; 22.71 μg/g for Cu; 20.06 μg/g for Pb; 104.23 μg/g for Zn). Among the Potamogeton species, the highest amounts of heavy metals are recorded in Potamogeton perfoliatus (1.88 μg/g for Cd; 13.14 μg/g for Cu; 13.32 μg/g for Pb; 57.96 μg/g for Zn). The sequence for the bioconcentration factors (BCFs) calculated in order to describe the accumulation of the four metals is Cd >> Zn > Pb > Cu. Increase of the zinc concentration determines an increase of the cadmium concentration (Spearman rho=0.40, p=0.02).ConclusionsDespite the low ambiental levels of heavy metals, the four aquatic plants have the ability to accumulate significant amounts, which make them useful as biological indicators. BCF value for Ceratophyllum demersum indicated this species as a cadmium hyperaccumulator.

Seasonal variation in trace metals concentrations in the Ialomita River, Romania

Sampling streams for metals is an important aspect of water-quality monitoring. Using ICP-AES the concentration of some microelements in the Ialomiţa River (Romania) were determined. In order to grasp the different phases of the river regime, samples were collected from its water–sediment interface at seven locations along the river, during three campaigns: during snow melting periods in the mountain zones (April), the period of reduced flow and high water temperature (August) and the period of high precipitations (November). HNO3 was added to the samples for fixation. Cadmium and copper appear accidentally; lead was detected only in samples collected in the vicinity of roads; the MAC (maximum admitted concentration) for surface waters is exceeded for nickel and chromium in samples collected in April and respectively in April and November; zinc concentrations were usually above the MAC; molybdenum concentration was above the set reference value, especially for samples collected in April and November. Possible explanations are given for the presence of the investigated microelements along the river.

Environmental impact assessment of the vegetable cultivations using the Pimentel-Euleistein model. Case study arges lower watershed

The culture of vegetables is characterized by a high level of energy inputs required for high production. For this reason the effects upon the environment are complex and diverse. The lower watershed of Arges River is characterized by a large area of vegetables cultivations and the presence of an important sale market (Bucharest City) . For the assessment of environmental impact caused by the above mentioned factors, the Pimentel-Euleistein Energetic Model was used. We evaluated the amount of energy that is entering the agroecosystem (pesticides, seeds, electricity, etc.) and we calculated the energetic efficiency η as a relation between the energy amount yielded by the agroecosystem (Qo) and the amount provided by human intervention (Qi) . Based on η, we calculated the entropy amount, the critical energetic limit (the maximum value of Qi for which the agroecosystem remains sustainable) and the sustainable production (the maximum amount extracted from the agroecosystem without causing unbalance) .

Empirical analysis and modelling of Argos Doppler location errors in Romania

Advancements in tracking technology allow researchers to understand the spatial ecology of many terrestrial and aquatic species. Argos Doppler is a widely used technology for wildlife telemetry as it suits smaller species and have longer life span than miniaturized GPS. In practice, large Argos location errors often occur due to communication conditions such as transmitters settings, local environment, area of reception, behaviour of tracked individual, etc. Considering the specificity of errors and the lack of benchmark studies in Eastern Europe, our research objectives are (1) to provide empirical evidences of the accuracy of Argos Doppler locations in Romania, (2) investigate the effectiveness of straight forward destructive filters for improving Argos data quality, and (3) to provide guidance for handling Argos wildlife monitoring data to researchers in Eastern Europe. We assessed the errors associated to Argos locations in 4 geographic locations from Romania in static, low speed and high-speed tests and then we evaluated the effectiveness of Douglas Argos distance angle filter algorithm to minimize location errors. Argos locations received in our tests had larger horizontal errors than those indicated by the operator of the Argos system, including when reception conditions are ideal. The errors are highly variable within each location class, however, positions from location class 0 were constantly prone to large errors. The errors were anisotropic, predominantly oriented East and West, a pattern confirmed by the larger longitudinal errors in the vast majority of data. Errors were mostly related to movement speed of Argos transmitter at the time of reception, but other factors such as topographic conditions and position of the device toward the sky at the time of the transmission contribute at receiving low quality data.Douglas-Argos filter successfully excluded largest errors while retained a large amount of data when the threshold was properly defined for local scale (2 km). Thus, filter selection requires previous knowledge about the movement patterns and behaviour of the species of interest, and parametrisation of the selected filter must follow a trial and error approach.