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initMIP-Antarctica
(2019)
Ice sheet numerical modeling is an important tool to estimate the dynamic contribution of the Antarctic ice sheet to sea level rise over the coming centuries. The influence of initial conditions on ice sheet model simulations, however, is still unclear. To better understand this influence, an initial state intercomparison exercise (initMIP) has been developed to compare, evaluate, and improve initialization procedures and estimate their impact on century-scale simulations. initMlP is the first set of experiments of the Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6), which is the primary Coupled Model Intercomparison Project Phase 6 (CMIP6) activity focusing on the Greenland and Antarctic ice sheets. Following initMlP-Greenland, initMlP-Antarctica has been designed to explore uncertainties associated with model initialization and spin-up and to evaluate the impact of changes in external forcings. Starting from the state of the Antarctic ice sheet at the end of the initialization procedure, three forward experiments are each run for 100 years: a control run, a run with a surface mass balance anomaly, and a run with a basal melting anomaly beneath floating ice. This study presents the results of initMlP-Antarctica from 25 simulations performed by 16 international modeling groups. The submitted results use different initial conditions and initialization methods, as well as ice flow model parameters and reference external forcings. We find a good agreement among model responses to the surface mass balance anomaly but large variations in responses to the basal melting anomaly. These variations can be attributed to differences in the extent of ice shelves and their upstream tributaries, the numerical treatment of grounding line, and the initial ocean conditions applied, suggesting that ongoing efforts to better represent ice shelves in continental-scale models should continue.
Across a landscape, aquatic-terrestrial interfaces within and between ecosystems are hotspots of organic matter (OM) mineralization. These interfaces are characterized by sharp spatio-temporal changes in environmental conditions, which affect OM properties and thus control OM mineralization and other transformation processes. Consequently, the extent of OM movement at and across aquatic-terrestrial interfaces is crucial in determining OM turnover and carbon (C) cycling at the landscape scale. Here, we propose expanding current concepts in aquatic and terrestrial ecosystem sciences to comprehensively evaluate OM turnover at the landscape scale. We focus on three main concepts toward explaining OM turnover at the landscape scale: the landscape spatiotemporal context, OM turnover described by priming and ecological stoichiometry, and anthropogenic effects as a disruptor of natural OM transfer magnitudes and pathways. A conceptual framework is introduced that allows for discussing the disparities in spatial and temporal scales of OM transfer, changes in environmental conditions, ecosystem connectivity, and microbial-substrate interactions. The potential relevance of priming effects in both terrestrial and aquatic systems is addressed. For terrestrial systems, we hypothesize that the interplay between the influx of OM, its corresponding elemental composition, and the elemental demand of the microbial communities may alleviate spatial and metabolic thresholds. In comparison, substrate level OM dynamics may be substantially different in aquatic systems due to matrix effects that accentuate the role of abiotic conditions, substrate quality, and microbial community dynamics. We highlight the disproportionate impact anthropogenic activities can have on OM cycling across the landscape. This includes reversing natural OM flows through the landscape, disrupting ecosystem connectivity, and nutrient additions that cascade across the landscape. This knowledge is crucial for a better understanding of OM cycling in a landscape context, in particular since terrestrial and aquatic compartments may respond differently to the ongoing changes in climate, land use, and other anthropogenic interferences.
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.
Wastewater treatment is crucial to environmental hygiene in urban environments. However, wastewater treatment plants (WWTPs) collect chemicals, organic matter, and microorganisms including pathogens and multi-resistant bacteria from various sources which may be potentially released into the environment via WWTP effluent. To better understand microbial dynamics in WWTPs, we characterized and compared the bacterial community of the inflow and effluent of a WWTP in Berlin, Germany using full-length 16S rRNA gene sequences, which allowed for species level determination in many cases and generally resolved bacterial taxa. Significantly distinct bacterial communities were identified in the wastewater inflow and effluent samples. Dominant operational taxonomic units (OTUs) varied both temporally and spatially. Disease associated bacterial groups were efficiently reduced in their relative abundance from the effluent by the WWTP treatment process, except for Legionella and Leptospira species which demonstrated an increase in relative proportion from inflow to effluent. This indicates that WWTPs, while effective against enteric bacteria, may enrich and release other potentially pathogenic bacteria into the environment. The taxonomic resolution of full-length 16S rRNA genes allows for improved characterization of potential pathogenic taxa and other harmful bacteria which is required to reliably assess health risk.
Influenza A viruses (IAV) are zoonotic pathogens relevant to human, domestic animal and wildlife health. Many avian IAVs are transmitted among waterfowl via a faecal-oral-route. Therefore, environmental water where waterfowl congregate may play an important role in the ecology and epidemiology of avian IAV. Water and sediment may sustain and transmit virus among individuals or species. It is unclear at what concentrations waterborne viruses are infectious or remain detectable. To address this, we performed lake water and sediment dilution experiments with varying concentrations or infectious doses of four IAV strains from seal, turkey, duck and gull. To test for infectivity of the IAV strains in a concentration dependent manner, we applied cultivation to specific pathogen free (SPF) embryonated chicken eggs and Madin-Darby Canine Kidney (MDCK) cells. IAV recovery was more effective from embryonated chicken eggs than MDCK cells for freshwater lake dilutions, whereas, MDCK cells were more effective for viral recovery from sediment samples. Low infectious dose (1 PFU/200 mu L) was sufficient in most cases to detect and recover IAV from lake water dilutions. Sediment required higher initial infectious doses (>= 100 PFU/200 mu L).
River ecosystems receive and process vast quantities of terrestrial organic carbon, the fate of which depends strongly on microbial activity. Variation in and controls of processing rates, however, are poorly characterized at the global scale. In response, we used a peer-sourced research network and a highly standardized carbon processing assay to conduct a global-scale field experiment in greater than 1000 river and riparian sites. We found that Earth’s biomes have distinct carbon processing signatures. Slow processing is evident across latitudes, whereas rapid rates are restricted to lower latitudes. Both the mean rate and variability decline with latitude, suggesting temperature constraints toward the poles and greater roles for other environmental drivers (e.g., nutrient loading) toward the equator. These results and data set the stage for unprecedented “next-generation biomonitoring” by establishing baselines to help quantify environmental impacts to the functioning of ecosystems at a global scale.
Online hate is a topic that has received considerable interest lately, as online hate represents a risk to self-determination and peaceful coexistence in societies around the globe. However, not much is known about the explanations for adolescents posting or forwarding hateful online material or how adolescents cope with this newly emerging online risk. Thus, we sought to better understand the relationship between a bystander to and perpetrator of online hate, and the moderating effects of problem-focused coping strategies (e.g., assertive, technical coping) within this relationship. Self-report questionnaires on witnessing and committing online hate and assertive and technical coping were completed by 6829 adolescents between 12 and 18 years of age from eight countries. The results showed that increases in witnessing online hate were positively related to being a perpetrator of online hate. Assertive and technical coping strategies were negatively related with perpetrating online hate. Bystanders of online hate reported fewer instances of perpetrating online hate when they reported higher levels of assertive and technical coping strategies, and more frequent instances of perpetrating online hate when they reported lower levels of assertive and technical coping strategies. In conclusion, our findings suggest that, if effective, prevention and intervention programs that target online hate should consider educating young people about problem-focused coping strategies, self-assertiveness, and media skills. Implications for future research are discussed.
Pluvial flood risk is mostly excluded in urban flood risk assessment. However, the risk of pluvial flooding is a growing challenge with a projected increase of extreme rainstorms compounding with an ongoing global urbanization. Considered as a flood type with minimal impacts when rainfall rates exceed the capacity of urban drainage systems, the aftermath of rainfall-triggered flooding during Hurricane Harvey and other events show the urgent need to assess the risk of pluvial flooding. Due to the local extent and small-scale variations, the quantification of pluvial flood risk requires risk assessments on high spatial resolutions. While flood hazard and exposure information is becoming increasingly accurate, the estimation of losses is still a poorly understood component of pluvial flood risk quantification. We use a new probabilistic multivariable modeling approach to estimate pluvial flood losses of individual buildings, explicitly accounting for the associated uncertainties. Except for the water depth as the common most important predictor, we identified the drivers for having loss or not and for the degree of loss to be different. Applying this approach to estimate and validate building structure losses during Hurricane Harvey using a property level data set, we find that the reliability and dispersion of predictive loss distributions vary widely depending on the model and aggregation level of property level loss estimates. Our results show that the use of multivariable zero-inflated beta models reduce the 90% prediction intervalsfor Hurricane Harvey building structure loss estimates on average by 78% (totalling U.S.$3.8 billion) compared to commonly used models.
The link between streamflow extremes and climatology has been widely studied in recent decades. However, a study investigating the effect of large-scale circulation variations on the distribution of seasonal discharge extremes at the European level is missing. Here we fit a climate-informed generalized extreme value (GEV) distribution to about 600 streamflow records in Europe for each of the standard seasons, i.e., to winter, spring, summer and autumn maxima, and compare it with the classical GEV distribution with parameters invariant in time. The study adopts a Bayesian framework and covers the period 1950 to 2016. Five indices with proven influence on the European climate are examined independently as covariates, namely the North Atlantic Oscillation (NAO), the east Atlantic pattern (EA), the east Atlantic-western Russian pattern (EA/WR), the Scandinavia pattern (SCA) and the polar-Eurasian pattern (POL). It is found that for a high percentage of stations the climate-informed model is preferred to the classical model. Particularly for NAO during winter, a strong influence on streamflow extremes is detected for large parts of Europe (preferred to the classical GEV distribution for 46% of the stations). Climate-informed fits are characterized by spatial coherence and form patterns that resemble relations between the climate indices and seasonal precipitation, suggesting a prominent role of the considered circulation modes for flood generation. For certain regions, such as northwestern Scandinavia and the British Isles, yearly variations of the mean seasonal climate indices result in considerably different extreme value distributions and thus in highly different flood estimates for individual years that can also persist for longer time periods.
Compound flooding, such as the co-occurrence of fluvial floods and extreme coastal water levels (CWL), may lead to significant impacts in densely-populated Low Elevation Coastal Zones. They may overstrain disaster management owing to the co-occurrence of inundation from rivers and the sea. Recent studies are limited by analyzing joint dependence between river discharge and either CWL or storm surges, and little is known about return levels of compound flooding, accounting for the covariance between drivers. Here, we assess the compound flood severity and identify hotspots for northwestern Europe during 1970–2014, using a newly developed Compound Hazard Ratio (CHR) that compares the severity of compound flooding associated with extreme CWL with the unconditional T-year fluvial peak discharge. We show that extreme CWL and stronger storms greatly amplify fluvial flood hazards. Our results, based on frequency analyses of observational records during 2013/2014’s winter storm Xaver, reveal that the river discharge of the 50-year compound flood is up to 70% larger, conditioned on the occurrence of extreme CWL, than that of the at-site peak discharge. For this event, nearly half of the stream gauges show increased flood hazards, demonstrating the importance of including the compounding effect of extreme CWL in river flood risk management.