The short-term effects of crude oil on the survival of different size-classes of cladoceran Daphnia magna (Straus, 1820)

We studied the acute effects of crude oil on the size-class population structure of the cladoceran Daphnia magna. D. magna were tested in three size-classes: small (1.4 mm, SE = 0.013), medium (2.5 mm, SE = 0.026), and large (3.1 mm, SE = 0.022) with six concentrations of crude oil (10, 50, 100, 400, 600, and 1700 mg L−1). The most important results of our experiment were as follows: (1) Crude oil had no significantly effect on D. magna below concentration 100 mg L−1. (2) An increasing crude oil concentration above 100 mg L−1 sharply decreased the survival of D. magna, (3) and survival varied among size classes. Being in contact with the concentration of 400 mg L−1 and above, all cladoceran specimens died after 96 h

Predicting Species Cover of Marine Macrophyte and Invertebrate Species Combining Hyperspectral Remote Sensing, Machine Learning and Regression Techniques

<div><p>In order to understand biotic patterns and their changes in nature there is an obvious need for high-quality seamless measurements of such patterns. If remote sensing methods have been applied with reasonable success in terrestrial environment, their use in aquatic ecosystems still remained challenging. In the present study we combined hyperspectral remote sensing and boosted regression tree modelling (BTR), an ensemble method for statistical techniques and machine learning, in order to test their applicability in predicting macrophyte and invertebrate species cover in the optically complex seawater of the Baltic Sea. The BRT technique combined with remote sensing and traditional spatial modelling succeeded in identifying, constructing and testing functionality of abiotic environmental predictors on the coverage of benthic macrophyte and invertebrate species. Our models easily predicted a large quantity of macrophyte and invertebrate species cover and recaptured multitude of interactions between environment and biota indicating a strong potential of the method in the modelling of aquatic species in the large variety of ecosystems.</p></div

Boosting the monitoring of phytoplankton in optically complex coastal waters by combining pigment-based chemotaxonomy and in situ radiometry

Research about the occurrence and extent of the cyanobacterial blooms in the Baltic Sea is critical due to their increased magnitude and frequency. Monitoring of the blooms is complicated due to their spatially and tem- porally heterogeneous nature. For adequate assessment of the water quality, phytoplankton dynamics needs to be tracked in large areas with high monitoring frequency. The main objectives of this study were (1) to describe phytoplankton community composition by pigment-based chemotaxonomy and validate the results with mi- croscopy; (2) to improve the retrieval of information about phytoplankton community by combining remote sensing with laboratory based approaches (3) to develop a region-specific algorithm to calculate cyanobacteria biomass from reflectance spectra; (4) to detect and quantify potentially toxic bloom-forming cyanobacteria with molecular methods. In our study the reflectance-based chlorophyll a (Chl a) values overestimated the High- performance Liquid Chromatography (HPLC) values although the correlations with HPLC Chl a measurements were very strong (rp ∼ 0.8, p < 0.001). We found that 709 nm/620 nm reflectance ratio correlated strongly (rp = 0.75, p < 0.01) to cyanobacteria wet biomass in CDOM-rich Väinameri even at low cyanobacterial bio- mass levels. Correlations between pigment-based chemotaxonomy and microscopy were significant in case of cyanobacteria (rp = 0.73, p < 0.01), cryptophytes (rp = 0.71, p < 0.05) and dinoflagellates (rp = 0.64, p < 0.05).This work was supported by Estonian Ministry of Education and Research (IUT 21-02), Estonian Science Foundation (ETF9102, ETF8576), Estonian Research Council (PUTJD719), base-financed pro- ject P180023PKKH of Estonian University of Life Sciences and by Estonian Doctoral School of Earth Sciences and Ecology. We thank Dr Teele Ligi (University of Tartu) for valuable help, Simon Wright and other developers of CHEMTAX program (Australian Antarctic Division, CSIRO). The authors acknowledge CYANOCOST-COST ES 1105 for networking and sharing knowledge.This work was supported by Estonian Ministry of Education and Research (IUT 21-02), Estonian Science Foundation (ETF9102, ETF8576), Estonian Research Council (PUTJD719), base-financed pro- ject P180023PKKH of Estonian University of Life Sciences and by Estonian Doctoral School of Earth Sciences and Ecology. We thank Dr Teele Ligi (University of Tartu) for valuable help, Simon Wright and other developers of CHEMTAX program (Australian Antarctic Division, CSIRO). The authors acknowledge CYANOCOST-COST ES 1105 for networking and sharing knowledge

DNA metabarcoding : Guidelines to monitor phytoplankton diversity and distribution in marine and brackish waters

We present guidelines for using environmental DNA metabarcoding, together with conventional techniques, to monitor the taxonomic diversity of phytoplankton in marine and brackish waters. The focus is on eukaryotic and prokaryotic phytoplankton using 18S and 16S rRNA primers and high-throughput sequencing. Information and recommendations on sampling, sample processing, molecular biological work, quality control, bioinformatics, data storage and management and cost estimates are included so that the method can be used to complement standardized light microscopy. A scientific literature review, discussion on future perspectives, reference databases and standardization are included. Using eDNA metabarcoding to complement standardized light microscopy advances conventional monitoring and research on phytoplankton communities to assess biodiversity and the state of the marine environment