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ISMIP6 Antarctica
(2020)
Ice flow models of the Antarctic ice sheet are commonly used to simulate its future evolution in response to different climate scenarios and assess the mass loss that would contribute to future sea level rise. However, there is currently no consensus on estimates of the future mass balance of the ice sheet, primarily because of differences in the representation of physical processes, forcings employed and initial states of ice sheet models. This study presents results from ice flow model simulations from 13 international groups focusing on the evolution of the Antarctic ice sheet during the period 2015-2100 as part of the Ice Sheet Model Intercomparison for CMIP6 (ISMIP6). They are forced with outputs from a subset of models from the Coupled Model Intercomparison Project Phase 5 (CMIP5), representative of the spread in climate model results. Simulations of the Antarctic ice sheet contribution to sea level rise in response to increased warming during this period varies between 7:8 and 30.0 cm of sea level equivalent (SLE) under Representative Concentration Pathway (RCP) 8.5 scenario forcing. These numbers are relative to a control experiment with constant climate conditions and should therefore be added to the mass loss contribution under climate conditions similar to present-day conditions over the same period. The simulated evolution of the West Antarctic ice sheet varies widely among models, with an overall mass loss, up to 18.0 cm SLE, in response to changes in oceanic conditions. East Antarctica mass change varies between 6 :1 and 8.3 cm SLE in the simulations, with a significant increase in surface mass balance outweighing the increased ice discharge under most RCP 8.5 scenario forcings. The inclusion of ice shelf collapse, here assumed to be caused by large amounts of liquid water ponding at the surface of ice shelves, yields an additional simulated mass loss of 28mm compared to simulations without ice shelf collapse. The largest sources of uncertainty come from the climate forcing, the ocean-induced melt rates, the calibration of these melt rates based on oceanic conditions taken outside of ice shelf cavities and the ice sheet dynamic response to these oceanic changes. Results under RCP 2.6 scenario based on two CMIP5 climate models show an additional mass loss of 0 and 3 cm of SLE on average compared to simulations done under present-day conditions for the two CMIP5 forcings used and display limited mass gain in East Antarctica.
Coastal areas are highly diverse, ecologically rich, regions of key socio-economic activity, and are particularly sensitive to sea-level change. Over most of the 20th century, global mean sea level has risen mainly due to warming and subsequent expansion of the upper ocean layers as well as the melting of glaciers and ice caps. Over the last three decades, increased mass loss of the Greenland and Antarctic ice sheets has also started to contribute significantly to contemporary sea-level rise. The future mass loss of the two ice sheets, which combined represent a sea-level rise potential of similar to 65 m, constitutes the main source of uncertainty in long-term (centennial to millennial) sea-level rise projections. Improved knowledge of the magnitude and rate of future sea-level change is therefore of utmost importance. Moreover, sea level does not change uniformly across the globe and can differ greatly at both regional and local scales. The most appropriate and feasible sea level mitigation and adaptation measures in coastal regions strongly depend on local land use and associated risk aversion. Here, we advocate that addressing the problem of future sea-level rise and its impacts requires (i) bringing together a transdisciplinary scientific community, from climate and cryospheric scientists to coastal impact specialists, and (ii) interacting closely and iteratively with users and local stakeholders to co-design and co-build coastal climate services, including addressing the high-end risks.
Recovering genomics clusters of secondary metabolites from lakes using genome-resolved metagenomics
(2018)
Metagenomic approaches became increasingly popular in the past decades due to decreasing costs of DNA sequencing and bioinformatics development. So far, however, the recovery of long genes coding for secondary metabolites still represents a big challenge. Often, the quality of metagenome assemblies is poor, especially in environments with a high microbial diversity where sequence coverage is low and complexity of natural communities high. Recently, new and improved algorithms for binning environmental reads and contigs have been developed to overcome such limitations. Some of these algorithms use a similarity detection approach to classify the obtained reads into taxonomical units and to assemble draft genomes. This approach, however, is quite limited since it can classify exclusively sequences similar to those available (and well classified) in the databases. In this work, we used draft genomes from Lake Stechlin, north-eastern Germany, recovered by MetaBat, an efficient binning tool that integrates empirical probabilistic distances of genome abundance, and tetranucleotide frequency for accurate metagenome binning. These genomes were screened for secondary metabolism genes, such as polyketide synthases (PKS) and non-ribosomal peptide synthases (NRPS), using the Anti-SMASH and NAPDOS workflows. With this approach we were able to identify 243 secondary metabolite clusters from 121 genomes recovered from our lake samples. A total of 18 NRPS, 19 PKS, and 3 hybrid PKS/NRPS clusters were found. In addition, it was possible to predict the partial structure of several secondary metabolite clusters allowing for taxonomical classifications and phylogenetic inferences. Our approach revealed a high potential to recover and study secondary metabolites genes from any aquatic ecosystem.
Retrieval of water constituents from hyperspectral in-situ measurements under variable cloud cover
(2018)
Remote sensing and field spectroscopy of natural waters is typically performed under clear skies, low wind speeds and low solar zenith angles. Such measurements can also be made, in principle, under clouds and mixed skies using airborne or in-situ measurements; however, variable illumination conditions pose a challenge to data analysis. In the present case study, we evaluated the inversion of hyperspectral in-situ measurements for water constituent retrieval acquired under variable cloud cover. First, we studied the retrieval of Chlorophyll-a (Chl-a) concentration and colored dissolved organic matter (CDOM) absorption from in-water irradiance measurements. Then, we evaluated the errors in the retrievals of the concentration of total suspended matter (TSM), Chl-a and the absorption coefficient of CDOM from above-water reflectance measurements due to highly variable reflections at the water surface. In order to approximate cloud reflections, we extended a recent three-component surface reflectance model for cloudless atmospheres by a constant offset and compared different surface reflectance correction procedures. Our findings suggest that in-water irradiance measurements may be used for the analysis of absorbing compounds even under highly variable weather conditions. The extended surface reflectance model proved to contribute to the analysis of above-water reflectance measurements with respect to Chl-a and TSM. Results indicate the potential of this approach for all-weather monitoring.
Marine snow aggregates represent heterogeneous agglomerates of dead and living organic matter. Composition is decisive for their sinking rates, and thereby for carbon flux to the deep sea. For oligotrophic oceans, information on aggregate composition is particularly sparse. To address this, the taxonomic composition of aggregates collected from the subtropical and oligotrophic Sargasso Sea (Atlantic Ocean) was characterized by 16S and 18S rRNA gene sequencing. Taxonomy assignment was aided by a collection of the contemporary plankton community consisting of 75 morphologically and genetically identified plankton specimens. The diverse rRNA gene reads of marine snow aggregates, not considering Trichodesmium puffs, were dominated by copepods (52%), cnidarians (21%), radiolarians (11%), and alveolates (8%), with sporadic contributions by cyanobacteria, suggesting a different aggregate composition than in eutrophic regions. Composition linked significantly with sampling location but not to any measured environmental parameters or plankton biomass composition. Nevertheless, indicator and network analyses identified key roles of a few rare taxa. This points to complex regulation of aggregate composition, conceivably affected by the environment and plankton characteristics. The extent to which this has implications for particle densities, and consequently for sinking rates and carbon sequestration in oligotrophic waters, needs further interrogation.
Cost degression in photovoltaics, wind-power and battery storage has been faster than previously anticipated. In the future, climate policy to limit global warming to 1.5–2 °C will make carbon-based fuels increasingly scarce and expensive. Here we show that further progress in solar- and wind-power technology along with carbon pricing to reach the Paris Climate targets could make electricity cheaper than carbon-based fuels. In combination with demand-side innovation, for instance in e-mobility and heat pumps, this is likely to induce a fundamental transformation of energy systems towards a dominance of electricity-based end uses. In a 1.5 °C scenario with limited availability of bioenergy and carbon dioxide removal, electricity could account for 66% of final energy by mid-century, three times the current levels and substantially higher than in previous climate policy scenarios assessed by the Intergovernmental Panel on Climate Change. The lower production of bioenergy in our high-electrification scenarios markedly reduces energy-related land and water requirements.
Retrieval of water constituents from hyperspectral in-situ measurements under variable cloud cover
(2018)
Remote sensing and field spectroscopy of natural waters is typically performed under clear skies, low wind speeds and low solar zenith angles. Such measurements can also be made, in principle, under clouds and mixed skies using airborne or in-situ measurements; however, variable illumination conditions pose a challenge to data analysis. In the present case study, we evaluated the inversion of hyperspectral in-situ measurements for water constituent retrieval acquired under variable cloud cover. First, we studied the retrieval of Chlorophyll-a (Chl-a) concentration and colored dissolved organic matter (CDOM) absorption from in-water irradiance measurements. Then, we evaluated the errors in the retrievals of the concentration of total suspended matter (TSM), Chl-a and the absorption coefficient of CDOM from above-water reflectance measurements due to highly variable reflections at the water surface. In order to approximate cloud reflections, we extended a recent three-component surface reflectance model for cloudless atmospheres by a constant offset and compared different surface reflectance correction procedures. Our findings suggest that in-water irradiance measurements may be used for the analysis of absorbing compounds even under highly variable weather conditions. The extended surface reflectance model proved to contribute to the analysis of above-water reflectance measurements with respect to Chl-a and TSM. Results indicate the potential of this approach for all-weather monitoring.
Recovering genomics clusters of secondary metabolites from lakes using genome-resolved metagenomics
(2018)
Metagenomic approaches became increasingly popular in the past decades due to decreasing costs of DNA sequencing and bioinformatics development. So far, however, the recovery of long genes coding for secondary metabolites still represents a big challenge. Often, the quality of metagenome assemblies is poor, especially in environments with a high microbial diversity where sequence coverage is low and complexity of natural communities high. Recently, new and improved algorithms for binning environmental reads and contigs have been developed to overcome such limitations. Some of these algorithms use a similarity detection approach to classify the obtained reads into taxonomical units and to assemble draft genomes. This approach, however, is quite limited since it can classify exclusively sequences similar to those available (and well classified) in the databases. In this work, we used draft genomes from Lake Stechlin, north-eastern Germany, recovered by MetaBat, an efficient binning tool that integrates empirical probabilistic distances of genome abundance, and tetranucleotide frequency for accurate metagenome binning. These genomes were screened for secondary metabolism genes, such as polyketide synthases (PKS) and non-ribosomal peptide synthases (NRPS), using the Anti-SMASH and NAPDOS workflows. With this approach we were able to identify 243 secondary metabolite clusters from 121 genomes recovered from our lake samples. A total of 18 NRPS, 19 PKS, and 3 hybrid PKS/NRPS clusters were found. In addition, it was possible to predict the partial structure of several secondary metabolite clusters allowing for taxonomical classifications and phylogenetic inferences. Our approach revealed a high potential to recover and study secondary metabolites genes from any aquatic ecosystem.
Citizen science projects have a long history in ecological studies. The research usefulness of such projects is dependent on applying simple and standardized methods. Here, we conducted a citizen science project that involved more than 3500 Swedish high school students to examine the temperature difference between surface water and the overlying air (T-w-T-a) as a proxy for sensible heat flux (Q(H)). If Q(H) is directed upward, corresponding to positive T-w-T-a, it can enhance CO2 and CH4 emissions from inland waters, thereby contributing to increased greenhouse gas concentrations in the atmosphere. The students found mostly negative T-w-T-a across small ponds, lakes, streams/rivers and the sea shore (i.e. downward Q(H)), with T-w-T-a becoming increasingly negative with increasing T-a. Further examination of T-w-T-a using high-frequency temperature data from inland waters across the globe confirmed that T-w-T-a is linearly related to T-a. Using the longest available high-frequency temperature time series from Lake Erken, Sweden, we found a rapid increase in the occasions of negative T-w-T-a with increasing annual mean T-a since 1989. From these results, we can expect that ongoing and projected global warming will result in increasingly negative T-w-T-a, thereby reducing CO2 and CH4 transfer velocities from inland waters into the atmosphere.
Aerobic anoxygenic phototrophs (AAPs) have been shown to exist in numerous marine and brackish environments where they are hypothesized to play important ecological roles. Despite their potential significance, the study of freshwater AAPs is in its infancy and limited to local investigations. Here, we explore the occurrence, diversity and distribution of AAPs in lakes covering a wide latitudinal gradient: Mongolian and German lakes located in temperate regions of Eurasia, tropical Great East African lakes, and polar permanently ice-covered Antarctic lakes. Our results show a widespread distribution of AAPs in lakes with contrasting environmental conditions and confirm that this group is composed of different members of the Alpha- and Betaproteobacteria. While latitude does not seem to strongly influence AAP abundance, clear patterns of community structure and composition along geographic regions were observed as indicated by a strong macro-geographical signal in the taxonomical composition of AAPs. Overall, our results suggest that the distribution patterns of freshwater AAPs are likely driven by a combination of small-scale environmental conditions (specific of each lake and region) and large-scale geographic factors (climatic regions across a latitudinal gradient).