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Multiscale sea ice algae observations are fundamentally important for projecting changes to sea ice ecosystems, as the physical environment continues to change. In this study, we developed upon previously established methodologies for deriving sea ice-algal chlorophyll a concentrations (chl a) from spectral radiation measurements, and applied these to larger-scale spectral surveys. We conducted four different under-ice spectral measurements: irradiance, radiance, transmittance, and transflectance, and applied three statistical approaches: Empirical Orthogonal Functions (EOF), Normalized Difference Indices (NDI), and multi-NDI. We developed models based on ice core chl a and coincident spectral irradiance/transmittance (N = 49) and radiance/transflectance (N = 50) measurements conducted during two cruises to the central Arctic Ocean in 2011 and 2012. These reference models were ranked based on two criteria: mean robustness R2 and true prediction error estimates. For estimating the biomass of a large-scale data set, the EOF approach performed better than the NDI, due to its ability to account for the high variability of environmental properties experienced over large areas. Based on robustness and true prediction error, the three most reliable models, EOF-transmittance, EOF-transflectance, and NDI-transmittance, were applied to two remotely operated vehicle (ROV) and two Surface and Under-Ice Trawl (SUIT) spectral radiation surveys. In these larger-scale chl a estimates, EOF-transmittance showed the best fit to ice core chl a. Application of our most reliable model, EOF-transmittance, to an 85 m horizontal ROV transect revealed large differences compared to published biomass estimates from the same site with important implications for projections of Arctic-wide ice-algal biomass and primary production.

Der Glaziologe Dr. Hans Oerter unternahm etliche Expeditionen in beide Polarregionen, bohrte tiefe Löcher ins Eis der Antarktis und erforschte dabei 800.000 Jahre Klimageschichte. Er stellt dar, was wir aus den Eiskernen auch für unser zukünftiges Klima lernen können.

Abstract The dynamics of diatoms and dinoflagellates have been monitored for many decades at the Helgoland Roads Long-Term Ecological Research site and are relatively well understood. In contrast, small-sized eukaryotic microbes and their community changes are still much more elusive, mainly due to their small size and uniform morphology, which makes them difficult to identify microscopically. By using next-generation sequencing, we wanted to shed light on the Helgoland planktonic community dynamics, including nano- and picoplankton, during a spring bloom. We took samples from March to May 2016 and sequenced the V4 region of the 18S rDNA. Our results showed that mixotrophic and heterotrophic taxa were more abundant than autotrophic diatoms. Dinoflagellates dominated the sequence assemblage, and several small-sized eukaryotic microbes like Haptophyta, Choanoflagellata, Marine Stramenopiles and Syndiniales were identified. A diverse background community including taxa from all size classes was present during the whole sampling period. Five phases with several communities were distinguished. The fastest changes in community composition took place in phase 3, while the communities from phases 1 to 5 were more similar to each other despite contrasting environmental conditions. Synergy effects of next-generation sequencing and traditional methods may be exploited in future long-term observations.

Anthropogenic carbon dioxide emissions cause a chemical phenomenon known as Ocean Acidification (OA). The associated changes in seawater chemistry are believed to have significant impact especially on coccolithophores, unicellular calcifying primary producers that take an outstanding role in the regulation of the marine carbon pumps. This thesis investigated the calcifying diploid and the non-calcifying haploid life-cycle stages of the globally dominant coccolithophore Emiliania huxleyi, and their responses to OA. Emphasis was put on investigating the role of energy-availability (i.e., irradiance) in the manifestation of OA-responses. A suite of methods was applied to resolve the effects on the phenomenological level (growth, elemental quotas and production), the physiological level (photosynthesis, carbon acquisition) and the level of gene expression (transcriptomics). In publication I, haploid and diploid cells were compared using microarray-based transcriptome profiling to assess stage-specific gene expression. The study identified genes related to distinct cell-biological traits, such as calcification in the diplont as well as flagellae and lipid respiration in the haplont. It further revealed that the diploid stage needs to make more regulatory efforts to epigenetically administrate its double amount of DNA, and therefore strongly controls its gene expression on the basis of transcription. The haplont in turn, possessing only a single sized genome, does not require these administrative efforts and seems to drive a more unrestricted gene expression. The proteome is apparently regulated on the basis of rapid turnover, i.e., post-translational. The haploid and diploid genomes may therefore be regarded as cellular ‘operating systems’ that streamline the life-cycle stages to occupy distinct ecological niches. Publication II investigated the responses of the life-cycle stages to OA under limiting and saturating light intensities. Growth rates as well as quotas and production rates of carbon (C) and nitrogen (N) were measured. In addition, inorganic C acquisition and photosynthesis were determined with a 14C-tracer technique and mass spectrometrybased gas-flux measurements. Under OA, the diploid stage shunted resources from calcification towards biomass production, yet keeping the production of total particulate carbon constant. In the haploid stage, elemental composition and production rates were more or less unaffected although major physiological acclimations were evident, pointing towards efforts to maintain homeostasis. Apparently, both life-cycle stages pursue distinct strategies to deal with OA. As a general pattern, OA-responses were strongly modulated by energy availability and typically most pronounced under low light. A concept explaining the energy-dependence of responses was proposed. In publication III, microarray-based transcriptome profiling was used to screen for cellular processes that underlie the observed phenomenological and physiological responses observed in the life-cycle stages (publication II). In the diplont, the increased biomass production under OA seems to be caused by production of glycoconjugates and lipids. 8 The lowered calcification may be attributed to impaired signal-transduction and iontransport mechanisms. The haplont utilized genes and metabolic pathways distinct from the diploid stage, reflecting the stage-specific usage of certain portions of the genome. With respect to functionality and energy-dependence, however, the transcriptomic OAresponses resembled those of the diplont. In both stages, signal transduction and ionhomeostasis were equally OA-sensitive under all light intensities. The effects on carbon metabolism and photophysiology, however, were clearly modulated by light availability. These interactive effects can be explained with the influence of both OA and light on the cellular ‘redox hub’, a major sensory system controlling the network of metabolic sources and sinks of reductive energy. In the general discussion, the newly gained views on the life-cycle stages are synthesized and biogeochemical implications of light-dependent OA-effects on coccolithophore calcification are considered. Furthermore, emerging physiological response patterns are identified to develop unifying concepts that can explain the energy-dependence of physiological effects. Finally, the critical role of redox regulation in the responses to changing environmental parameters is argued and research perspectives are given how to further resolve effects of the changing environment on marine phytoplankton.

The size and shape of snow grains directly impacts the reflection by a snowpack. In this article, different approaches to retrieve the optical-equivalent snow grain size (ropt) or, alternatively, the specific surface area (SSA) using satellite, airborne, and ground-based observations are compared and used to evaluate ICON-ART (ICOsahedral Nonhydrostatic—Aerosols and Reactive Trace gases) simulations. The retrieval methods are based on optical measurements and rely on the ropt-dependent absorption of solar radiation in snow. The measurement data were taken during a three-week campaign that was conducted in the North of Greenland in March/April 2018, such that the retrieval methods and radiation measurements are affected by enhanced uncertainties under these low-Sun conditions. An adjusted airborne retrieval method is applied which uses the albedo at 1700 nm wavelength and combines an atmospheric and snow radiative transfer model to account for the direct-to-global fraction of the solar radiation incident on the snow. From this approach, we achieved a significantly improved uncertainty (ropt of 15 µm within a five-day period after a snowfall event which is small compared to previous observations under similar temperature regimes. ICON-ART captured the observed change of ropt during snowfall events, but systematically overestimated the subsequent snow grain growth by about 100%. Adjusting the growth rate factor to 0.012 µm2 s−1 minimized the difference between model and observations. Satellite-based and airborne retrieval methods showed higher ropt over sea ice (<300 µm) than over land surfaces (<100 µm) which was reduced by data filtering of surface roughness features. Moderate-Resolution Imaging Spectroradiometer (MODIS) retrievals revealed a large spread within a series of subsequent individual overpasses, indicating their limitations in observing the snow grain size evolution in early spring conditions with low Sun.

The gateway south of South Africa constitutes an integral inter-ocean link in the global thermohaline circulation (THC) since it allows the exchange of shallow- and deepwater masses between the Indian and the Atlantic. Thus understanding past variations of this current system is important for improving our knowledge of the global climate. The long-term changes in deepwater flow in the Atlantic-Indian gateway during the Cenozoic have been initially studied using reflection seismic profiles. But in many cases the seismic stratigraphy is poorly constrained and not further resolved within the time period from the late Miocene to present. In particular, there are limited Pliocene records that can be used to investigate the influence of climatic (e.g. Antartic ice volume) and tectonic (e.g. closure of the central American seaway) on the deep-water variability. Here we focus on the bottom water flow around the Agulhas Plateau, a location proximal to the entrance of North Atlantic Deep Water (NADW) to the Southern Ocean and South Indian Ocean. IODP Expedition 361 (SAFARI) Site U1475 was drilled in 2669 m water depth into a sediment drift that is deposited on the southwestern flank of Agulhas Plateau and comprises a complete stratigraphic section of the last ∼7 Ma. We present cleaned, edited, and spliced high-resolution data sets of sediment physical properties measured at Site U1475. Synthetic seismograms generated from the velocity and bulk density core scanning records allow a detailed correlation oft the drilling results with the Site survey seismic reflection profiles. Seismic reflectors at 3.75 and 3.87 s (two-way-traveltime) correspond to major increases in acoustic impedance at ∼110 and ∼216 meters below seafloor. Based on the preliminary shipboard biostratigraphic age model sediments at these depths have ages of ∼4.0 and ∼5.1 Ma, respectively. Furthermore spectral analyses of physical property records such as natural gamma radiation and colour reflectance reveal climate variability on orbital and suborbital timescales.

Abstract The Lena Delta in Siberia is the largest delta in the Arctic and as a snow-dominated ecosystem particularly vulnerable to climate change. Using the two decades of MODerate resolution Imaging Spectroradiometer satellite acquisitions, this study investigates interannual and spatial variability of snow-cover duration and summer vegetation vitality in the Lena Delta. We approximated snow by the application of the normalized difference snow index and vegetation greenness by the normalized difference vegetation index (NDVI). We consolidated the analyses by integrating reanalysis products on air temperature from 2001 to 2021, and air temperature, ground temperature, and the date of snow-melt from time-lapse camera (TLC) observations from the Samoylov observatory located in the central delta. We extracted spring snow-cover duration determined by a latitudinal gradient. The ‘regular year’ snow-melt is transgressing from mid-May to late May within a time window of 10 days across the delta. We calculated yearly deviations per grid cell for two defined regions, one for the delta, and one focusing on the central delta. We identified an ensemble of early snow-melt years from 2012 to 2014, with snow-melt already starting in early May, and two late snow-melt years in 2004 and 2017, with snow-melt starting in June. In the times of TLC recording, the years of early and late snow-melt were confirmed. In the three summers after early snow-melt, summer vegetation greenness showed neither positive nor negative deviations. Whereas, vegetation greenness was reduced in 2004 after late snow-melt together with the lowest June monthly air temperature of the time series record. Since 2005, vegetation greenness is rising, with maxima in 2018 and 2021. The NDVI rise since 2018 is preceded by up to 4 °C warmer than average June air temperature. The ongoing operation of satellite missions allows to monitor a wide range of land surface properties and processes that will provide urgently needed data in times when logistical challenges lead to data gaps in land-based observations in the rapidly changing Arctic.

International audience; Bacteria of the Vibrio genus are the most predominant infectious agents threatening marine wildlife and aquaculture. Due to the large genetic diversity of these pathogens, the molecular determinants of Vibrio virulence are only poorly understood. Furthermore, studies tend to ignore co-evolutionary interactions between different host populations and their locally encountered Vibrio communities. Here, we explore the molecular targets of such co-evolutionary interactions by analyzing the genomes of nine Vibrio strains from the Splendidus-clade showing opposite virulence patterns towards two populations of Pacific oysters introduced into European Wadden Sea. By contrasting Vibrio phylogeny to their host specific virulence patterns, we could identify two core genome genes (OG1907 and OG 3159) that determine the genotype by genotype (G × G) interactions between oyster larvae and their sympatric Vibrio communities. Both genes show positive selection between locations targeting only few amino acid positions. Deletion of each gene led to a loss of the host specific virulence patterns while complementation with OG3159 alleles from both locations could recreate the wild type phenotypes matching the origin of the allele. This indicates that both genes can act as a genetic switch for Vibrio-oyster coevolution demonstrating that local adaptation in distinct Vibrio lineages can rely on only few genes independent of larger pathogenicity islands or plasmids.

Most dynamic sea ice models for climate type simulations are based on the viscous-plastic (VP) rheology. New rheologies such as the Maxwell-Elasto-Brittle (MEB) rheology are usually compared against traditional VP-schemes, but the new schemes also require revisiting the validity of VP-schemes. So far, comparisons between different schemes are confounded by factors unrelated to rheology, such as grid resolution, advection schemes, forcing by atmosphere and ocean, and last but not least, by differences in numerical details of different model codes. The sea ice component of the Massachusetts Institute of Technology general circulation model (MITgcm) offers an easy-to-use testbed for comparing different sea ice rheologies and implementation that avoids any confounders because all solvers share the same code and configuration environment. VP-rheologies with different flavors of Picard (or fixed point iterative) solvers, Newton methods, and different variants of the Elastic-Viscous-Plastic solver have been evaluated in this framework. With this framework, a new implementations such as an MEB solver may be compared to these traditional solvers in idealized geometries and in realistic Arctic configurations.

The unique feature of permafrost in the Arctic is the presence of a large amount of ice below the earth surface. Thermal degradation and subsequent permafrost destabilization causes thaw subsidence and thermokarst development. Because these processes are difficult to detect due to the lack of timely and accurate elevation datasets they have received not much attention, despite their potentially global significance through the permafrost carbon feedback. Thanks to remote sensing pioneering works in Alaska and Siberia, widespread thaw subsidence has been documented and is increasingly perceived as a potentially widespread permafrost landscape response to contemporary climate change. Clearly, however, detailed local inventories are required to calibrate regional long and short-term assessments for measuring surface deformation due to permafrost thaw. The objective of our study is to analyze time series of repeat terrestrial, air-, and space borne laser scanning (rLiDAR) for quantification of land surface lowering due to permafrost thaw, which is poorly resolved in terms of recent landscape development in the Arctic. Our work aims at finding commonalities and differences of change or no change on ground-ice-rich primary surfaces that are preserved as uplands, which cover 15 to 20% of the Teshekpuk Lake Special Area on the Arctic Coastal Plain of northern Alaska. Our approach focuses on quantifying modern thaw subsidence and thermokarst rates with high spatial resolution data over several decades as well as high temporal resolution data of inter-annual intervals. Multi-annual measurements of rLiDAR over Arctic Alaska have been made by aircraft in 2016 and in 2015+2017 through on-site surveys during field expeditions. These in situ data serve as a basis for large scale surface change assessments using time series of photogrammetrically derived elevation data from very high resolution historical aerial photographs and modern satellite imagery. The synergistic data fusion approach enhances permafrost degradation monitoring and better resolves surface deformation associated with thaw subsidence. The novel datasets also provide insights into previously unrecognized patterns of rapid permafrost thaw and related interconnections.