The Use of Sentinel-2 for Chlorophyll-a Spatial Dynamics Assessment: A Comparative Study on Different Lakes in Northern Germany

Eutrophication of inland waters is an environmental issue that is becoming more common with climatic variability. Monitoring of this aquatic problem is commonly based on the chlorophyll-a concentration monitored by routine sampling with limited temporal and spatial coverage. Remote sensing data can be used to improve monitoring, especially after the launch of the MultiSpectral Instrument (MSI) on Sentinel-2. In this study, we compared the estimation of chlorophyll-a (chl-a) from different bio-optical algorithms using hyperspectral proximal remote sensing measurements, from simulated MSI responses and from an MSI image. For the satellite image, we also compare different atmospheric corrections routines before the comparison of different bio-optical algorithms. We used in situ data collected in 2019 from 97 sampling points across 19 different lakes. The atmospheric correction assessment showed that the performances of the routines varied for each spectral band. Therefore, we selected C2X, which performed best for bands 4 (root mean square error—RMSE = 0.003), 5 (RMSE = 0.004) and 6 (RMSE = 0.002), which are usually used for the estimation of chl-a. Considering all samples from the 19 lakes, the best performing chl-a algorithm and calibration achieved a RMSE of 16.97 mg/m3. When we consider only one lake chain composed of meso-to-eutrophic lakes, the performance improved (RMSE: 10.97 mg/m3). This shows that for the studied meso-to-eutrophic waters, we can reliably estimate chl-a concentration, whereas for oligotrophic waters, further research is needed. The assessment of chl-a from space allows us to assess spatial dynamics of the environment, which can be important for the management of water resources. However, to have an accurate product, similar optical water types are important for the overall performance of the bio-optical algorithm

Land-use type temporarily affects active pond community structure but not gene expression patterns

Changes in land use and agricultural intensification threaten biodiversity and ecosystem functioning of small water bodies. We studied 67 kettle holes (KH) in an agricultural landscape in northeastern Germany using landscape-scale metatranscriptomics to understand the responses of active bacterial, archaeal and eukaryotic communities to land-use type. These KH are proxies of the millions of small standing water bodies of glacial origin spread across the northern hemisphere. Like other landscapes in Europe, the study area has been used for intensive agriculture since the 1950s. In contrast to a parallel environmental DNA study that suggests the homogenization of biodiversity across KH, conceivably resulting from long-lasting intensive agriculture, land-use type affected the structure of the active KH communities during spring crop fertilization, but not a month later. This effect was more pronounced for eukaryotes than for bacteria. In contrast, gene expression patterns did not differ between months or across land-use types, suggesting a high degree of functional redundancy across the KH communities. Variability in gene expression was best explained by active bacterial and eukaryotic community structures, suggesting that these changes in functioning are primarily driven by interactions between organisms. Our results indicate that influences of the surrounding landscape result in temporary changes in the activity of different community members. Thus, even in KH where biodiversity has been homogenized, communities continue to respond to land management. This potential needs to be considered when developing sustainable management options for restoration purposes and for successful mitigation of further biodiversity loss in agricultural landscapes

Principal components of thermal regimes in mountain river networks

Description of thermal regimes in flowing waters is key to understanding physical processes, enhancing predictive abilities, and improving bioassessments. Spatially and temporally sparse data sets, especially in logistically challenging mountain environments, have limited studies on thermal regimes, but inexpensive sensors coupled with crowd-sourced data collection efforts provide efficient means of developing large data sets for robust analyses. Here, thermal regimes are assessed using annual monitoring records compiled from several natural resource agencies in the northwestern United States that spanned a 5-year period (2011–2015) at 226 sites across several contiguous montane river networks. Regimes were summarized with 28 metrics and principal component analysis (PCA) was used to determine those metrics which best explained thermal variation on a reduced set of orthogonal axes. Four principal components (PC) accounted for 93.4&thinsp;% of the variation in the temperature metrics, with the first PC (49&thinsp;% of variance) associated with metrics that represented magnitude and variability and the second PC (29&thinsp;% of variance) associated with metrics representing the length and intensity of the winter season. Another variant of PCA, T-mode analysis, was applied to daily temperature values and revealed two distinct phases of spatial variability – a homogeneous phase during winter when daily temperatures at all sites were &lt;3&thinsp;∘C and a heterogeneous phase throughout the year's remainder when variation among sites was more pronounced. Phase transitions occurred in March and November, and coincided with the abatement and onset of subzero air temperatures across the study area. S-mode PCA was conducted on the same matrix of daily temperature values after transposition and indicated that two PCs accounted for 98&thinsp;% of the temporal variation among sites. The first S-mode PC was responsible for 96.7&thinsp;% of that variance and correlated with air temperature variation (r=0.92), whereas the second PC accounted for 1.3&thinsp;% of residual variance and was correlated with discharge (r=0.84). Thermal regimes in these mountain river networks were relatively simple and responded coherently to external forcing factors, so sparse monitoring arrays and small sets of summary metrics may be adequate for their description. PCA provided a computationally efficient means of extracting key information elements from the temperature data set used here and could be applied broadly to facilitate comparisons among more diverse stream types and develop classification schemes for thermal regimes.</p

Tunnelling Studies of Two-Dimensional States in Semiconductors with Inverted Band Structure: Spin-orbit Splitting, Resonant Broadening

The results of tunnelling studies of the energy spectrum of two-dimensional (2D) states in a surface quantum well in a semiconductor with inverted band structure are presented. The energy dependence of quasimomentum of the 2D states over a wide energy range is obtained from the analysis of tunnelling conductivity oscillations in a quantizing magnetic field. The spin-orbit splitting of the energy spectrum of 2D states, due to inversion asymmetry of the surface quantum well, and the broadening of 2D states at the energies, when they are in resonance with the heavy hole valence band, are investigated in structures with different strength of the surface quantum well. A quantitative analysis is carried out within the framework of the Kane model of the energy spectrum. The theoretical results are in good agreement with the tunnelling spectroscopy data.Comment: 29 pages, RevTeX, submitted in Phys.Rev.B. Figures available on request from [email protected]

Anomalous magneto-oscillations in two-dimensional systems

The frequencies of Shubnikov-de Haas oscillations have long been used to measure the unequal population of spin-split two-dimensional subbands in inversion asymmetric systems. We report self-consistent numerical calculations and experimental results which indicate that these oscillations are not simply related to the zero-magnetic-field spin-subband densities.Comment: 4 pages, 3 figures; changed content (clarifications

Connectivity and Synchronisation of Lake Ecosystems in Space and Time - CONNECT

Within the project CONNECT we are establishing a collaborative network between experts in remote sensing (RS) and freshwater ecology to study connectivity and coherence of lake ecosystems in a regional context at unprecedented temporal and spatial resolution. The overall aim is to understand the yet unexplained variation in phytoplankton dynamics among river-connected German lowland lakes, many of which are presently classified as in poor to bad ecological status. These lakes often face a high risk of eutrophication, mass development of harmful algal blooms, and high production of greenhouse gases. We suggest if measured on adequate temporal and spatial scales much of the among-lake variation in phytoplankton dynamics to be explained by the strength of hydrological lake-to-lake and lake-to-catchment connectivity as modulated by lake depth and mixing regime. This may have profound implications for the maximum intensity, spatial range and regional-scale magnitude of eutrophication impacts. We will use (i) a large-scale experimental manipulation of lake connectivity, and (ii) an observational field campaign contrasting deep and shallow river-connected lakes, to challenge this research frontier by an innovative combination of automatic high- frequency in situ measurements with state of the art near-to-far RS technology. Climate change is expected to alter the hydrology, and thus the connectivity of lake-river systems. However, it is also predicted to increase extreme weather events leading to an increased input of nutrients as well as colored dissolved organic matter (cDOM). By providing data of high spatio-temporal coverage, CONNECT will provide basic high quality data to better understand mechanisms of eutrophication at the local and regional scale. Our data, thus, provide a valuable basis to improve current management of such river-connected lake ecosystems under future climate scenarios. To reach this ambitious goal, the project will (i) build a cross- disciplinary collaborative network of excellence, (ii) develop a mechanistic understanding of lake ecosystem functioning at local and regional scale, (iii) improve future environmental monitoring and interpretation of available data from inland waters, and (iv) support more effective integrated management of river-connected lakes to mitigate eutrophication impacts

Repeat Composition of CenH3-chromatin and H3K9me2-marked heterochromatin in Sugar Beet (Beta vulgaris)

Kowar T, Zakrzewski F, Macas J, et al. Repeat Composition of CenH3-chromatin and H3K9me2-marked heterochromatin in Sugar Beet (Beta vulgaris). BMC Plant Biology. 2016;16(1): 120.Background Sugar beet (Beta vulgaris) is an important crop of temperate climate zones, which provides nearly 30 % of the world’s annual sugar needs. From the total genome size of 758 Mb, only 567 Mb were incorporated in the recently published genome sequence, due to the fact that regions with high repetitive DNA contents (e.g. satellite DNAs) are only partially included. Therefore, to fill these gaps and to gain information about the repeat composition of centromeres and heterochromatic regions, we performed chromatin immunoprecipitation followed by sequencing (ChIP-Seq) using antibodies against the centromere-specific histone H3 variant of sugar beet (CenH3) and the heterochromatic mark of dimethylated lysine 9 of histone H3 (H3K9me2). Results ChIP-Seq analysis revealed that active centromeres containing CenH3 consist of the satellite pBV and the Ty3-gypsy retrotransposon Beetle7, while heterochromatin marked by H3K9me2 exhibits heterogeneity in repeat composition. H3K9me2 was mainly associated with the satellite family pEV, the Ty1-copia retrotransposon family Cotzilla and the DNA transposon superfamily of the En/Spm type. In members of the section Beta within the genus Beta, immunostaining using the CenH3 antibody was successful, indicating that orthologous CenH3 proteins are present in closely related species within this section. Conclusions The identification of repetitive genome portions by ChIP-Seq experiments complemented the sugar beet reference sequence by providing insights into the repeat composition of poorly characterized CenH3-chromatin and H3K9me2-heterochromatin. Therefore, our work provides the basis for future research and application concerning the sugar beet centromere and repeat rich heterochromatic regions characterized by the presence of H3K9me2