ALBERT

Beschreibung: Mass mortality events (MMEs) are defined as the death of large numbers of fish over a short period of time. These events can result in catastrophic losses to the Atlantic salmon aquaculture industry and the local economy. However, they are challenging to understand because of their relative infrequency and the high number of potential factors involved. As a result, the causes and consequences of MMEs in Atlantic salmon aquaculture are not well understood. In this study, we developed a structural network of causal risk factors for MMEs for aquaculture and the communities that depend on Atlantic salmon aquaculture. Using the Interpretive Structural Modeling (ISM) technique, we analysed the causes of Atlantic salmon mass mortalities due to environmental (abiotic), biological (biotic) and nutritional risk factors. The consequences of MMEs were also assessed for the occupational health and safety of aquaculture workers and their implications for the livelihoods of local communities. This structural network deepens our understanding of MMEs and points to management actions and interventions that can help mitigate mass mortalities. MMEs are typically not the result of a single risk factor but are caused by the systematic interaction of risk factors related to the environment, fish diseases, feeding/nutrition and cage-site management. Results also indicate that considerations of health and safety risk, through pre- and post-event risk assessments, may help to minimize workplace injuries and eliminate potential risks of human fatalities. Company and government assisted socio-economic measures could help mitigate post-mass mortality impacts. Appropriate and timely management actions may help reduce MMEs at Atlantic salmon cage sites and minimize the physical and social vulnerabilities of workers and local communities.

Beschreibung: Coastal upwelling, driven by alongshore winds and characterized by cold sea surface temperatures and high upper-ocean nutrient content, is an important physical process sustaining some of the oceans’ most productive ecosystems. To fully understand the ocean properties in eastern boundary upwelling systems, it is important to consider the depth of the source waters being upwelled, as it affects both the SST and the transport of nutrients toward the surface. Here, we construct an upwelling source depth distribution for parcels at the surface in the upwelling zone. We do so using passive tracers forced at the domain boundary for every model depth level to quantify their contributions to the upwelled waters. We test the dependence of this distribution on the strength of the wind stress and stratification using high-resolution regional ocean simulations of an idealized coastal upwelling system. We also present an efficient method for estimating the mean upwelling source depth. Furthermore, we show that the standard deviation of the upwelling source depth distribution increases with increasing wind stress and decreases with increasing stratification. These results can be applied to better understand and predict how coastal upwelling sites and their surface properties have and will change in past and future climates.

Beschreibung: Heat stress is projected to intensify with global warming, causing significant socioeconomic impacts and threatening human health. Wet-bulb temperature (WBT), which combines temperature and humidity effects, is a useful indicator for assessing regional and global heat stress variability and trends. However, the variations of European WBT and their underlying mechanisms remain unclear. Using observations and reanalysis datasets, we demonstrate a remarkable warming of summer WBT during the period 1958–2021 over Europe. Specifically, the European summer WBT has increased by over 1.08C in the past 64 years. We find that the increase in European summer WBT is driven by both near-surface warming temperatures and increasing atmospheric moisture content. We identify four dominant modes of European summer WBT variability and investigate their linkage with the large-scale atmospheric circulation and sea surface temperature anomalies. The first two leading modes of the European WBT variability exhibit prominent interdecadal to long-term variations, mainly driven by a circumglobal wave train and concurrent sea surface temperature variations. The last two leading modes of European WBT variability mainly show interannual variations, indicating a direct and rapid response to large-scale atmospheric dynamics and nearby sea surface temperature variations. Further analysis shows the role of global warming and changes in midlatitude circulations in the variations of summer WBT. Our findings can enhance the understanding of plausible drivers of heat stress in Europe and provide valuable insights for regional decision-makers and climate adaptation planning.

Beschreibung: A fundamental statistic of climate variability is its spatiotemporal correlation function. Its complex structure can be concisely summarized by a frequency-dependent measure of the effective spatial degrees of freedom (ESDOF). Here we present, for the first time, frequency-dependent ESDOF estimates of global natural surface temperature variability from purely instrumental measurements, using the HadCRUT4 dataset (1850-2014). The approach is based on a newly developed method for estimating the frequency-dependent spatial correlation function from gappy data fields. Results reveal a multicomponent structure of the spatial correlation function, including a large-amplitude short-distance component (with weak time scale dependence) and a small-amplitude long-distance component (with increasing relative amplitude toward the longer time scales). Two frequency-dependent ESDOF measures are applied, each responding mainly to either of the two components. Both measures exhibit a significant ESDOF reduction from monthly to multidecadal time scales, implying an increase of the effective spatial scale of natural surface temperature fluctuations. Moreover, it is found that a good approximation to the global number of equally spaced samples needed to estimate the variance of global mean temperature is given, at any frequency, by the greater one of the two ESDOF measures, decreasing from ;130 at monthly to ;30 at multidecadal time scales. Finally, the multicomponent structure of the correlation function together with the detected ESDOF scaling properties indicate that the ESDOF reduction toward the longer time scales cannot be explained simply by diffusion acting on stochastically driven anomalies, as it might be suggested f rom simple stochastic-diffusive energy balance models.

Beschreibung: 〈jats:title〉Abstract〈/jats:title〉 〈jats:p〉This study quantifies the state-of-the-art in the rapidly growing field of seasonal Arctic sea ice prediction. A novel multi-model dataset of retrospective seasonal predictions of September Arctic sea ice is created and analyzed, consisting of community contributions from 17 statistical models and 17 dynamical models. Prediction skill is compared over the period 2001–2020 for predictions of Pan-Arctic sea ice extent (SIE), regional SIE, and local sea ice concentration (SIC) initialized on June 1, July 1, August 1, and September 1. This diverse set of statistical and dynamical models can individually predict linearly detrended Pan-Arctic SIE anomalies with skill, and a multi-model median prediction has correlation coefficients of 0.79, 0.86, 0.92, and 0.99 at these respective initialization times. Regional SIE predictions have similar skill to Pan-Arctic predictions in the Alaskan and Siberian regions, whereas regional skill is lower in the Canadian, Atlantic, and Central Arctic sectors. The skill of dynamical and statistical models is generally comparable for Pan-Arctic SIE, whereas dynamical models outperform their statistical counterparts for regional and local predictions. The prediction systems are found to provide the most value added relative to basic reference forecasts in the extreme SIE years of 1996, 2007, and 2012. SIE prediction errors do not show clear trends over time, suggesting that there has been minimal change in inherent sea ice predictability over the satellite era. Overall, this study demonstrates that there are bright prospects for skillful operational predictions of September sea ice at least three months in advance.〈/jats:p〉

Beschreibung: The sinking of particulate matter from the upper ocean dominates the export and sequestration of organic carbon by the biological pump, a critical component of the Earth's carbon cycle. Controls on carbon export are thought to be driven by ecological processes that produce and repackage sinking biogenic particles. Here, we present observations during the demise of the Northeast Atlantic Ocean spring bloom illustrating the importance of storm-induced turbulence on the dynamics of sinking particles. A sequence of four large storms caused upper layer mean turbulence levels to vary by more than three orders of magnitude. Large particle (>0.1 to 10 mm) abundance and size changed accordingly: increasing via shear coagulation when turbulence was moderate and decreasing rapidly when turbulence was intense due to shear disaggregation. Particle export was also tied to storm forcing as large particles were mixed to depth during mixed layer deepening. After the mixed layer shoaled, these particles, now isolated from intense surface mixing, grew larger and subsequently sank. This sequence of events matched the timing of sinking particle flux observations. Particle export was influenced by increases in aggregate abundance and porosity, which appeared to be enhanced by the repeated creation and destruction of aggregates. Last, particle transit efficiency through the mesopelagic zone was reduced by presumably biotic processes that created small particles (〈0.5 mm) from larger ones. Our results demonstrate that ocean turbulence significantly impacts the nature and dynamics of sinking particles, strongly influencing particle export and the efficiency of the biological pump.

Beschreibung: Warmer temperatures and higher sea level than today characterized the Last Interglacial interval [Pleistocene, 128 to 116 thousand years ago (ka)]. This period is a remarkable deep-time analog for temperature and sea-level conditions as projected for 2100 AD, yet there has been no evidence of fossil assemblages in the equatorial Atlantic. Here, we report foraminifer, metazoan (mollusks, bony fish, bryozoans, decapods, and sharks among others), and plant communities of coastal tropical marine and mangrove affinities, dating precisely from a ca. 130 to 115 ka time interval near the Equator, at Kourou, in French Guiana. These communities include ca. 230 recent species, some being endangered today and/or first recorded as fossils. The hyperdiverse Kourou mollusk assemblage suggests stronger affinities between Guianese and Caribbean coastal waters by the Last Interglacial than today, questioning the structuring role of the Amazon Plume on tropical Western Atlantic communities at the time. Grassland-dominated pollen, phytoliths, and charcoals from younger deposits in the same sections attest to a marine retreat and dryer conditions during the onset of the last glacial (ca. 110 to 50 ka), with a savanna-dominated landscape and episodes of fire. Charcoals from the last millennia suggest human presence in a mosaic of modern-like continental habitats. Our results provide key information about the ecology and biogeography of pristine Pleistocene tropical coastal ecosystems, especially relevant regarding the—widely anthropogenic—ongoing global warming.

Beschreibung: Significance Particulate organic carbon (POC) formed by photosynthesis in the sunlit surface ocean fuels the ecosystems in the dark ocean below. We show that mesoscale fronts and eddies, which are ubiquitous physical features in subtropical oceans, generate three-dimensional intrusions connecting the surface to deep ocean. Intrusions are enriched in total POC due to enhancement of small, nonsinking photosynthetic plankton and free-living bacteria that resemble surface microbial communities. Flow-driven export of POC, estimated using an approximation of eddy physics, is the same order of magnitude as export by sinking POC, which was previously thought to dominate export. These observations reveal coupling of surface and deep ocean productivity and biodiversity and give insight into mechanisms by which the ocean transports carbon to depth. Abstract Subtropical oceans contribute significantly to global primary production, but the fate of the picophytoplankton that dominate in these low-nutrient regions is poorly understood. Working in the subtropical Mediterranean, we demonstrate that subduction of water at ocean fronts generates 3D intrusions with uncharacteristically high carbon, chlorophyll, and oxygen that extend below the sunlit photic zone into the dark ocean. These contain fresh picophytoplankton assemblages that resemble the photic-zone regions where the water originated. Intrusions propagate depth-dependent seasonal variations in microbial assemblages into the ocean interior. Strikingly, the intrusions included dominant biomass contributions from nonphotosynthetic bacteria and enrichment of enigmatic heterotrophic bacterial lineages. Thus, the intrusions not only deliver material that differs in composition and nutritional character from sinking detrital particles, but also drive shifts in bacterial community composition, organic matter processing, and interactions between surface and deep communities. Modeling efforts paired with global observations demonstrate that subduction can flux similar magnitudes of particulate organic carbon as sinking export, but is not accounted for in current export estimates and carbon cycle models. Intrusions formed by subduction are a particularly important mechanism for enhancing connectivity between surface and upper mesopelagic ecosystems in stratified subtropical ocean environments that are expanding due to the warming climate.