Methane and sulphate consumption in different habitats of the Håkon Mosby Mud Volcano (HMMV)

The Hakon Mosby Mud Volcano is a highly active methane seep hosting different chemosynthetic communities such as thiotrophic bacterial mats and siboglinid tubeworm assemblages. This study focuses on in situ measurements of methane fluxes to and from these different habitats, in comparison to benthic methane and oxygen consumption rates. By quantifying in situ oxygen, methane, and sulfide fluxes in different habitats, a spatial budget covering areas of 10-1000 -m diameter was established. The range of dissolved methane efflux (770-2 mmol m-2 d-1) from the center to the outer rim was associated with a decrease in temperature gradients from 46°C to < 1°C m-1, indicating that spatial variations in fluid flow control the distribution of benthic habitats and activities. Accordingly, total oxygen uptake (TOU) varied between the different habitats by one order of magnitude from 15 mmol m-2 d-1 to 161 mmol m-2 d-1. High fluid flow rates appeared to suppress benthic activities by limiting the availability of electron acceptors. Accordingly, the highest TOU was associated with the lowest fluid flow and methane efflux. This was most likely due to the aerobic oxidation of methane, which may be more relevant as a sink for methane as previously considered in submarine ecosystems.

(Supplemet S1) Silicon oxide and Potassium + Sodium oxide from the PACManus hydrothermal area

This study presents a systematic analysis and interpretation of autonomous underwater vehicle-based microbathymetry combined with remotely operated vehicle (ROV) video recordings, rock analyses and temperaturemeasurements within the PACManus hydrothermal area located on Pual Ridge in the Bismarck Sea of eastern Manus Basin. The data obtained during research cruise Magellan-06 and So-216 provides a framework for understanding the relationship between the volcanism, tectonismand hydrothermal activity. PACManus is a submarine felsic vocanically-hosted hydrothermal area that hosts multiple vent fields locatedwithin several hundredmeters of one another but with different fluid chemistries, vent temperatures and morphologies. The total area of hydrothermal activity is estimated to be 20,279m**2. Themicrobathymetrymaps combinedwith the ROV video observations allow for precise high-resolution mapping estimates of the areal extents of hydrothermal activity.We find the distribution of hydrothermal fields in the PACManus area is primarily controlled by volcanic features that include lava domes, thick andmassive blocky lava flows, breccias and feeder dykes. Spatial variation in the permeability of local volcanic facies appears to control the distribution of venting within a field.We define a three-stage chronological sequence for the volcanic evolution of the PACManus based on lava flow morphology, sediment cover and lava SiO2 concentration. In Stage-1, sparsely to moderately porphyritic dacite lavas (68-69.8 wt.% SiO2) erupted to form domes or cryptodomes. In Stage-2, aphyric lava with slightly lower SiO2 concentrations (67.2-67.9 wt.% SiO2) formed jumbled and pillowed lava flows. In the most recent phase Stage-3, massive blocky lavaswith 69 to 72.5wt.% SiO2were erupted throughmultiple vents constructing a volcanic ridge identified as the PACManus neovolcanic zone. The transition between these stages may be gradual and related to progressive heating of a silicic magma following a recharge event of hot, mantle-derived melts.

EPANET Input Files of New York tunnels and Pacific City used in a metamodel-based optimization study

Metamodels have proven be very useful when it comes to reducing the computational requirements of Evolutionary Algorithm-based optimization by acting as quick-solving surrogates for slow-solving fitness functions. The relationship between metamodel scope and objective function varies between applications, that is, in some cases the metamodel acts as a surrogate for the whole fitness function, whereas in other cases it replaces only a component of the fitness function. This paper presents a formalized qualitative process to evaluate a fitness function to determine the most suitable metamodel scope so as to increase the likelihood of calibrating a high-fidelity metamodel and hence obtain good optimization results in a reasonable amount of time. The process is applied to the risk-based optimization of water distribution systems; a very computationally-intensive problem for real-world systems. The process is validated with a simple case study (modified New York Tunnels) and the power of metamodelling is demonstrated on a real-world case study (Pacific City) with a computational speed-up of several orders of magnitude.

Size-partitioned phytoplankton carbon concentrations retrieved from ocean color data, links to data in netCDF format

Owing to their important roles in biogeochemical cycles, phytoplankton functional types (PFTs) have been the aim of an increasing number of ocean color algorithms. Yet, none of the existing methods are based on phytoplankton carbon (C) biomass, which is a fundamental biogeochemical and ecological variable and the "unit of accounting" in Earth system models. We present a novel bio-optical algorithm to retrieve size-partitioned phytoplankton carbon from ocean color satellite data. The algorithm is based on existing methods to estimate particle volume from a power-law particle size distribution (PSD). Volume is converted to carbon concentrations using a compilation of allometric relationships. We quantify absolute and fractional biomass in three PFTs based on size - picophytoplankton (0.5-2 µm in diameter), nanophytoplankton (2-20 µm) and microphytoplankton (20-50 µm). The mean spatial distributions of total phytoplankton C biomass and individual PFTs, derived from global SeaWiFS monthly ocean color data, are consistent with current understanding of oceanic ecosystems, i.e., oligotrophic regions are characterized by low biomass and dominance of picoplankton, whereas eutrophic regions have high biomass to which nanoplankton and microplankton contribute relatively larger fractions. Global climatological, spatially integrated phytoplankton carbon biomass standing stock estimates using our PSD-based approach yield - 0.25 Gt of C, consistent with analogous estimates from two other ocean color algorithms and several state-of-the-art Earth system models. Satisfactory in situ closure observed between PSD and POC measurements lends support to the theoretical basis of the PSD-based algorithm. Uncertainty budget analyses indicate that absolute carbon concentration uncertainties are driven by the PSD parameter No which determines particle number concentration to first order, while uncertainties in PFTs' fractional contributions to total C biomass are mostly due to the allometric coefficients. The C algorithm presented here, which is not empirically constrained a priori, partitions biomass in size classes and introduces improvement over the assumptions of the other approaches. However, the range of phytoplankton C biomass spatial variability globally is larger than estimated by any other models considered here, which suggests an empirical correction to the No parameter is needed, based on PSD validation statistics. These corrected absolute carbon biomass concentrations validate well against in situ POC observations.