GANs for Integration of Deterministic Model and Observations in Marine Ecosystem

Monitoring the marine ecosystem can be done via observations (either in-situ or satellite) and via deterministic models. However, each of these methods has some drawbacks: observations can be accurate but insufficient in terms of temporal and spatial coverage, while deterministic models cover the whole marine ecosystem but can be inaccurate. This work aims at developing a deep learning model to reproduce the biogeochemical variables in the Mediterranean Sea, integrating observations and the output of an existing deterministic model of the marine ecosystem. In particular, two deep learning architectures will be proposed and tested: first EmuMed, an emulator of the deterministic model, and then InpMed, which consists of an improvement of the latter by the addition of information provided by in-situ and satellite observations. Results show that EmuMed can successfully reproduce the output of the deterministic model, while ImpMed can successfully make use of the additional information provided, thus improving our ability to monitor the biogeochemical variables in the Mediterranean Sea

spatiotemporal variability of alkalinity in the mediterranean sea

Abstract. The paper provides a basin-scale assessment of the spatiotemporal distribution of alkalinity in the Mediterranean Sea. The assessment is made by integrating the available observations into a 3-D transport–biogeochemical model. The results indicate the presence of complex spatial patterns: a marked west-to-east surface gradient of alkalinity is coupled to secondary negative gradients: (1) from marginal seas (Adriatic and Aegean Sea) to the eastern Mediterranean Sea and (2) from north to south in the western region. The west–east gradient is related to the mixing of Atlantic water entering from the Strait of Gibraltar with the high-alkaline water of the eastern sub-basins, which is correlated to the positive surface flux of evaporation minus precipitation. The north-to-south gradients are related to the terrestrial input and to the input of the Black Sea water through the Dardanelles. In the surface layers, alkalinity has a relevant seasonal cycle (up to 40 μmol kg−1) that is driven by physical processes (seasonal cycle of evaporation and vertical mixing) and, to a minor extent, by biological processes. A comparison of alkalinity vs. salinity indicates that different regions present different relationships: in regions of freshwater influence, the two quantities are negatively correlated due to riverine alkalinity input, whereas they are positively correlated in open sea areas of the Mediterranean Sea

Exact Black Hole and Cosmological Solutions in a Two-Dimensional Dilaton-Spectator Theory of Gravity

Exact black hole and cosmological solutions are obtained for a special two-dimensional dilaton-spectator ($\phi-\psi$) theory of gravity. We show how in this context any desired spacetime behaviour can be determined by an appropriate choice of a dilaton potential function $V(\phi)$ and a ``coupling function'' $l(\phi)$ in the action. We illustrate several black hole solutions as examples. In particular, asymptotically flat double- and multiple- horizon black hole solutions are obtained. One solution bears an interesting resemblance to the $2D$ string-theoretic black hole and contains the same thermodynamic properties; another resembles the $4D$ Reissner-Nordstrom solution. We find two characteristic features of all the black hole solutions. First the coupling constants in $l(\phi)$ must be set equal to constants of integration (typically the mass). Second, the spectator field $\psi$ and its derivative $\psi^{'}$ both diverge at any event horizon. A test particle with ``spectator charge" ({\it i.e.} one coupled either to $\psi$ or $\psi^{'}$), will therefore encounter an infinite tidal force at the horizon or an ``infinite potential barrier'' located outside the horizon respectively. We also compute the Hawking temperature and entropy for our solutions. In $2D$ $FRW$ cosmology, two non-singular solutions which resemble two exact solutions in $4D$ string-motivated cosmology are obtained. In addition, we construct a singular model which describes the $4D$ standard non-inflationary big bang cosmology ($big-bang\rightarrow radiation\rightarrow dust$). Motivated by the similaritiesbetween $2D$ and $4D$ gravitational field equations in $FRW$ cosmology, we briefly discuss a special $4D$ dilaton-spectator action constructed from the bosonic part of the low energy heterotic string action andComment: 34 pgs. Plain Tex, revised version contains some clarifying comments concerning the relationship between the constants of integration and the coupling constants

Spatiotemporal variability of alkalinity in the Mediterranean Sea

The paper provides a basin-scale assessment of the spatiotemporal distribution of alkalinity in the Mediterranean Sea. The assessment is made by integrating the available observations into a 3-D transport–biogeochemical model. The results indicate the presence of complex spatial patterns: a marked west-to-east surface gradient of alkalinity is coupled to secondary negative gradients: (1) from marginal seas (Adriatic and Aegean Sea) to the eastern Mediterranean Sea and (2) from north to south in the western region. The west–east gradient is related to the mixing of Atlantic water entering from the Strait of Gibraltar with the high-alkaline water of the eastern sub-basins, which is correlated to the positive surface flux of evaporation minus precipitation. The north-to-south gradients are related to the terrestrial input and to the input of the Black Sea water through the Dardanelles. In the surface layers, alkalinity has a relevant seasonal cycle (up to 40 μmol kg−1) that is driven by physical processes (seasonal cycle of evaporation and vertical mixing) and, to a minor extent, by biological processes. A comparison of alkalinity vs. salinity indicates that different regions present different relationships: in regions of freshwater influence, the two quantities are negatively correlated due to riverine alkalinity input, whereas they are positively correlated in open sea areas of the Mediterranean Sea

A model for the trophic food web of the Gulf of Trieste

The Gulf of Trieste is located in the northernmost part of the Adriatic Sea. It exhibits high variable hydrodynamical and trophic conditions, due to the interactions among the wind regime, characterised by impulsive strong wind events (Bora), the fresh water –nutrient rich- run off, especially from Isonzo river, the interaction with the general circulation of North Adriatic Sea, the seasonal heating and cooling of water and alternation of mixing and stratification of water column. Gulf is also characterised by occurrence of anomaly events as mucilagine. Despite the high inter-annual biological variability, it is possible to recognise the seasonal succession of two trophic structures: the classical food chain which starts with the spring diatom bloom and the microbial food web during summer stratification. As a first step in the formulation of a comprehensive model for the Gulf of Trieste, able to reproduce the fundamental functioning of the ecosystem and to investigate the occurrence of anomalies, we have developed a food web model describing the fluxes of carbon and of phosphorous, the later being thought as the limiting nutrient in the Gulf. The model considers two groups of phytoplankton: diatom and nano-pico phytoplankton; two groups of zooplankton: the first represented by mixed filter feeders, and the second consisted by microzooplankton and by fine filter feeder, mainly represented by summer cladocera Penilia avirostris. Heterotrophic bacteria are explicitly included in the model, in order to describe their role in P cycle either as remineralization agents or as nanophytoplankton competitors, and their role in DOC degradation. The content of P and C in POM and DOM compartments are also included to better reproduce the uncoupling of the P and C cycles in seawater system. The model, forced by nutrient availability and climatological factors, reproduces the seasonal succession between classical food chain and microbial food web. Sensitivity analysis (Morris’s method) applied to the model permits to highlight the most important factor in controlling the evolution of the system

PPCon 1.0: Biogeochemical-Argo profile prediction with 1D convolutional networks

Effective observation of the ocean is vital for studying and assessing the state and evolution of the marine ecosystem and for evaluating the impact of human activities. However, obtaining comprehensive oceanic measurements across temporal and spatial scales and for different biogeochemical variables remains challenging. Autonomous oceanographic instruments, such as Biogeochemical (BGC)-Argo profiling floats, have helped expand our ability to obtain subsurface and deep-ocean measurements, but measuring biogeochemical variables, such as nutrient concentration, still remains more demanding and expensive than measuring physical variables. Therefore, developing methods to estimate marine biogeochemical variables from high-frequency measurements is very much needed. Current neural network (NN) models developed for this task are based on a multilayer perceptron (MLP) architecture, trained over point-wise pairs of input–output features. Although MLPs can produce smooth outputs if the inputs change smoothly, convolutional neural networks (CNNs) are inherently designed to handle profile data effectively. In this study, we present a novel one-dimensional (1D) CNN model to predict profiles leveraging the typical shape of vertical profiles of a variable as a prior constraint during training. In particular, the Predict Profiles Convolutional (PPCon) model predicts nitrate, chlorophyll, and backscattering (bbp700) starting from the date and geolocation and from temperature, salinity, and oxygen profiles. Its effectiveness is demonstrated using a robust BGC-Argo dataset collected in the Mediterranean Sea for training and validation. Results, which include quantitative metrics and visual representations, prove the capability of PPCon to produce smooth and accurate profile predictions improving upon previous MLP applications.</p

Interactive effects of fishing effort reduction and climate change in a central Mediterranean fishing area: Insights from bio-economic indices derived from a dynamic food-web model

Disentangling the effects of mixed fisheries and climate change across entire food-webs requires a description of ecosystems using tools that can quantify interactive effects as well as bio-economic aspects. A calibrated dynamic model for the Sicily Channel food web, made up of 72 functional groups and including 13 fleet segments, was developed. A temporal simulation until 2050 was conducted to evaluate the bio-economic interactive effects of the reduction of bottom trawling fishing effort by exploring different scenarios that combine fishery and climate change. Our results indicate that direct and indirect effects produce a net increase in biomass of many functional groups with immediate decline of trawlers’ catches and economic incomes, followed by a long term increase mainly due to biomass rebuilding of commercial species which lasts 5-10 years after fishing reduction. Synergistic and antagonistic effects caused by changes in the fishing effort and in climate characterize a specific functional group’s response in biomass which, in turn, modulate also the catch and income of the other fleets, and especially of those sharing target resources. However, trawler’s intra-fleet competition is higher than the others fleet effects. In the medium term, the effects of fishing effort reduction are higher than those of climate change and seem to make exploitation of marine resources more sustainable over time and fishery processes more efficient by improving ecosystem health

Modeling Carbon Budgets and Acidification in the Mediterranean Sea Ecosystem Under Contemporary and Future Climate

We simulate and analyze the effects of a high CO2 emission scenario on the Mediterranean Sea biogeochemical state at the end of the XXI century, with a focus on carbon cycling, budgets and fluxes, within and between the Mediterranean subbasins, and on ocean acidification. As a result of the overall warming of surface water and exchanges at the boundaries, the model results project an increment in both the plankton primary production and the system total respiration. However, productivity increases less than respiration, so these changes yield to a decreament in the concentrations of total living carbon, chlorophyll, particulate organic carbon and oxygen in the epipelagic layer, and to an increment in the DIC pool all over the basin. In terms of mass budgets, the large increment in the dissolution of atmospheric CO2 results in an increment of most carbon fluxes, including the horizontal exchanges between eastern and western sub-basins, in a reduction of the organic carbon component, and in an increament of the inorganic one. The eastern sub-basin accumulates more than 85% of the absorbed atmospheric CO2. A clear ocean acidification signal is observed all over the basin, quantitatively similar to those projected in most oceans, and well detectable also down to the mesopelagic and bathypelagic layers