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Chlorophyll-a is an essential climate variable. Chlorophyll-a in situ measurements are usually used for the validation of satellite images. Previous intercomparisons have shown that there can be substantial differences between in situ laboratories. In order to shed light on these differences, we arranged international chlorophyll-a intercomparisons with eight participating laboratories during 1–2 July 2021. We performed two dedicated transects through Bråviken bay (NW Baltic proper) and sampled four stations in each transect along a chlorophyll-a gradient. We took three surface replicates per laboratory and per station, i.e., 24 samples per laboratory. The samples were filtered through Whatman GF/F filters, and filters were frozen in liquid nitrogen and distributed in dry ice to all laboratories together with chlorophyll-a standards. The results between labs compared quite well. The mean normalized bias (MNB) of the standard measurements ranged between −23% and +19% for all laboratories and −7% to +19% for the Baltic Sea laboratories compared to high-performance liquid chromatography. The MNB of the two Bråviken transects ranged between −23 and +17% for all laboratories (compared to the median of all spectrophotometric and fluorometric measurements) and between −2 and +17% for the Baltic Sea laboratories. On average, the chlorophyll-a concentrations measured by the fluorometric method were about 13% higher than those measured by spectrophotometry, and fluorometry samples tended to have more scatter. The largest uncertainties seem to be caused by variable storage and extraction methods and are not fully captured in this intercomparison. This is demonstrated by analyzing historical comparisons revealing very large uncertainties (root mean square difference (RMSD) up to 109% and bias up to 68%), possibly due to too low filtration volumes and due to different extraction and storage methods. Our recommendation is to flash-freeze samples in liquid nitrogen and store them at −80°C. After storage, they should be extracted and measured at room temperature within 6–24 h. Our results also indicate that ethanol is much more efficient in extracting Chl-a than acetone. Last but not least, we would like to point out that the uncertainties in measuring chlorophyll-a by satellite are now within the range of in situ data, as shown here by comparing the in situ results from this study with published remote sensing results from the literature.

Lignin accumulates in the cell walls of specialized cell types to enable plants to stand upright and conduct water and minerals, withstand abiotic stresses, and defend themselves against pathogens. These functions depend on specific lignin concentrations and subunit composition in different cell types and cell wall layers. However, the mechanisms controlling the accumulation of specific lignin subunits, such as coniferaldehyde, during the development of these different cell types are still poorly understood. We herein validated the Wiesner test (phloroglucinol/HCl) for the restrictive quantitative in situ analysis of coniferaldehyde incorporation in lignin. Using this optimized tool, we investigated the genetic control of coniferaldehyde incorporation in the different cell types of genetically-engineered herbaceous and woody plants with modified lignin content and/or composition. Our results demonstrate that the incorporation of coniferaldehyde in lignified cells is controlled by (a) autonomous biosynthetic routes for each cell type, combined with (b) distinct cell-to-cell cooperation between specific cell types, and (c) cell wall layer-specific accumulation capacity. This process tightly regulates coniferaldehyde residue accumulation in specific cell types to adapt their property and/or function to developmental and/or environmental changes.

Successful management of coastal environments requires reliable monitoring methods and indicators. Besides Chlorophyll-a concentration (Chl-a), water transparency measured as Secchi Depth (ZSD) is widely used in Baltic Sea management for water quality assessment as eutrophication indicator. However, in many coastal waters not only phytoplankton but also colored dissolved organic matter (CDOM) and suspended particulate matter (SPM) influence the under-water light field, and therefore the ZSD. In this study all three main optical variables (CDOM, Chl-a, and SPM [organic and inorganic]) as well as ZSD were measured in three Swedish regions: the Bothnian Sea, the Baltic Proper, and the Skagerrak in 2010–2014. Regional multiple regressions with Chl-a, CDOM, and inorganic SPM as predictors explained the variations in ZSD well (Radj2 = 0.53–0.84). Commonality analyses of the regressions indicated considerable differences between regions regarding the contribution of each factor to the variance, Radj2, in ZSD. CDOM explained most of the variance in the Bothnian Sea and the Skagerrak; in general, Chl-a contributed only modestly to the ZSD variance. In the Baltic Proper the largest contribution was from the interaction of all three variables. As expected, the link between Chl-a and ZSD was much weaker in the Bothnian Sea with high CDOM absorption and SPM concentration. When applying the Swedish EU Water Framework Directive threshold for Good/Moderate Chl-a status in the models it was shown that ZSD is neither a sufficient indicator for eutrophication, nor for changes in Chl-a. Natural coastal gradients in CDOM and SPM influence the reference conditions for ZSD and other eutrophication indicators, such as the depth distribution of macro-algae. Hence, setting targets for these indicators based on reference Chl-a concentrations and simple Chl-a to ZSD relationships might in some cases be inappropriate and misleading due to overestimation of water transparency under natural conditions.

There are three optical in-water components that, besides water itself, govern the under-water light field: phytoplankton, total suspended matter (TSM), and colored dissolved organic matter (CDOM). In essence, it is the spectral absorption and scattering properties of each optical component that govern the underwater light field, and also the color of the sea that we can perceive, and that can also be measured remotely from space. The Baltic Sea is optically dominated by CDOM, apart from cyanobacteria blooms that often cover most of the Baltic proper during summer. Remote sensing images of TSM reveal large-and mesoscale features and currents, especially in the Southern Baltic, which are influenced both by atmospheric Rossby waves and the Coriolis force. In coastal waters, the optical properties are strongly influenced by inorganic suspended matter, which may originate from coastal erosion and from run-off from land, streams, and rivers. In this paper, we evaluate the distribution of TSM across the Baltic Sea using remote sensing data and statistically compare the TSM loads in the different Helsinki Commission (HELCOM)-defined basins. The total suspended matter (TSM) loads during summer vary substantially in the different basins, with the south-eastern Baltic overall being most influenced by cyanobacteria blooms. The Gdansk basin and the Gulf of Riga were distinguished both by relatively high TSM loads with high standard deviations, indicating strong fluvial input and/or resuspension of sediments. We also evaluate a coastal TSM transect in Himmerfjärden bay, which is located at the Swedish East coast in the Western Gotland Basin. The effect of wind-wave stirring on the distribution of TSM from source (shore) to sink (open sea) can be assessed using satellite data from European Space Agency's (ESA) MEdium Resolution Imaging Spectrometer (MERIS) mission (2002–2012) with 300 m resolution. The TSM transect data from areas with low wind exposure and a stable thermocline showed a gradient distribution perpendicular to the coast for summer seasons 2009, 2010, 2011, and a 3-year summer composite, confirming a previous bio-optical study from the Western Gotland basin.