Assessing the drift of fish aggregating devices in the tropical Pacific Ocean

The tropical Pacific Ocean is characterized by its dominant zonal flow, strong climate dependence on the El Niño–Southern Oscillation (ENSO) and abundant tuna stocks. Tuna fisheries in the West and Central Pacific Ocean accounted for 55 % of the world-wide tuna catch in 2019 and are one of the main sources of income in many Pacific island nations. One of the dominant fishing methods in this region relies on the use of drifting fish aggregating devices (dFADs): rafts with long underwater appendages (on average 50 m deep) that aggregate fish. Although currents such as the North Equatorial Countercurrent (NECC) and South Equatorial Current (SEC) in the tropical Pacific Ocean vary strongly with ENSO, little is known about the impact of this variability in flow on dFAD dispersion. In this study, virtual Lagrangian particles are tracked for the period 2006 to 2021 over the domain in a 3D hydrodynamic model and are advected in simulations with only surface flow, as well as simulations using a depth-averaged horizontal flow over the upper 50 m, representing virtual dFADs. Zonal displacements, eddy-like behaviour and ENSO variability are then studied for both types of virtual particles. It was found that virtual particles advected by surface flow only are displaced up to 35 % farther than virtual dFADs subjected to a depth-averaged flow, but no other major differences were found in dispersion patterns. The strongest correlations between ENSO and virtual dFAD dispersion for the assessed variables were found in the West Pacific Ocean, with Pearson correlation coefficients of up to 0.59 for virtual dFAD displacement. Connections between ENSO and eddy-like behaviour were found in the western part of the SEC, indicating more circulation and meandering during El Niño. These findings may be useful for improving sustainable deployment strategies during ENSO events and understanding the ocean processes driving the distribution of dFADs

Real-Time Optical Tracking of Protein Corona Formation on Single Nanoparticles in Serum

The formation of a protein corona, where proteins spontaneously adhere to the surface of nanomaterials in biological environments, leads to changes in their physicochemical properties and subsequently affects their intended biomedical functionalities. Most current methods to study protein corona formation are ensemble-averaging and either require fluorescent labeling, washing steps, or are only applicable to specific types of particles. Here we introduce real-time all-optical nanoparticle analysis by scattering microscopy (RONAS) to track the formation of protein corona in full serum, at the single-particle level, without any labeling. RONAS uses optical scattering microscopy and enables real-time and in situ tracking of protein adsorption on metallic and dielectric nanoparticles with different geometries directly in blood serum. We analyzed the adsorbed protein mass, the affinity, and the kinetics of the protein adsorption at the single particle level. While there is a high degree of heterogeneity from particle to particle, the predominant factor in protein adsorption is surface chemistry rather than the underlying nanoparticle material or size. RONAS offers an in-depth understanding of the mechanisms related to protein coronas and, thus, enables the development of strategies to engineer efficient bionanomaterials.</p

Real-Time Optical Tracking of Protein Corona Formation on Single Nanoparticles in Serum

The formation of a protein corona, where proteins spontaneously adhere to the surface of nanomaterials in biological environments, leads to changes in their physicochemical properties and subsequently affects their intended biomedical functionalities. Most current methods to study protein corona formation are ensemble-averaging and either require fluorescent labeling, washing steps, or are only applicable to specific types of particles. Here we introduce real-time all-optical nanoparticle analysis by scattering microscopy (RONAS) to track the formation of protein corona in full serum, at the single-particle level, without any labeling. RONAS uses optical scattering microscopy and enables real-time and in situ tracking of protein adsorption on metallic and dielectric nanoparticles with different geometries directly in blood serum. We analyzed the adsorbed protein mass, the affinity, and the kinetics of the protein adsorption at the single particle level. While there is a high degree of heterogeneity from particle to particle, the predominant factor in protein adsorption is surface chemistry rather than the underlying nanoparticle material or size. RONAS offers an in-depth understanding of the mechanisms related to protein coronas and, thus, enables the development of strategies to engineer efficient bionanomaterials.</p

Efficiently simulating Lagrangian particles in large-scale ocean flows — Data structures and their impact on geophysical applications

Studying oceanography by using Lagrangian simulations has been adopted for a range of scenarios, such as the determining the fate of microplastics in the ocean, simulating the origin locations of microplankton used for palaeoceanographic reconstructions, and for studying the impact of fish aggregation devices on the migration behaviour of tuna. These simulations are complex and represent a considerable runtime effort to obtain trajectory results, which is the prime motivation for enhancing the performance of Lagrangian particle simulators. This paper assesses established performance enhancing techniques from Eulerian simulators in light of computational conditions and demands of Lagrangian simulators. A performance enhancement strategy specifically targeting physics-based Lagrangian particle simulations is outlined to address the performance gaps, and techniques for closing the performance gap are presented and implemented. Realistic experiments are derived from three specific oceanographic application scenarios, and the suggested performance-enhancing techniques are benchmarked in detail, so to allow for a good attribution of speed-up measurements to individual techniques. The impacts and insights of the performance enhancement strategy are further discussed for Lagrangian simulations in other geoscience applications. The experiments show that I/O-enhancing techniques, such as dynamic loading and buffering, lead to considerable speed-up on-par with an idealised parallelisation of the process over 20 nodes. Conversely, while the cache-efficient structure-of-arrays collection yields a visible speed-up, other alternative data structures fail in fulfilling the theoretically-expected performance increase. This insight demonstrates the importance of good data alignment in memory and caches for Lagrangian physics simulations

Individual based model simulations indicate a non-linear catch equation of drifting Fish Aggregating Device-associated tuna

Catch per unit of fishing effort (CPUE) is often used as an indicator of tuna abundance, where it is assumed that the two are proportional to each other. Tuna catch is therefore typically simplified in tuna population dynamics models and depends linearly on their abundance. In this paper, we use an individual-based model of tuna and their interactions with drifting Fish Aggregating Devices (dFADs) to identify which behavioural, ocean flow, and fishing strategy scenarios lead to an emergent, non-linear dependency between catch, and both tuna and dFAD density at the ∼1○ grid scale. We apply a series of catch response equations to evaluate their ability to model associated catch rate, using tuna and dFAD density as terms. Our results indicate that, regardless of ocean flow, behavioural, or fisher strategy scenario, simulated catch is best modelled with a non-linear dependence on both tuna and dFAD abundance. We discuss how estimators of CPUE at the population scale are potentially biased when assuming a linear catch response

Modelling of tuna around fish aggregating devices: The importance of ocean flow and prey

Catch and distribution of tuna in the ocean are typically investigated with ocean basin-scale models. Due to their large scale, such models must greatly simplify tuna behaviour occurring at a scale below 100 km, despite interactions at this level potentially being important to both catch and distribution of tuna. For example, the associative behaviour of tuna with man-made floating objects, that are deployed by fishers to improve their catch rates (Fish Aggregating Devices; FADs), are usually ignored or simplified. Here we present a model that can be used to investigate the influence of tuna dynamics below the 100 km scale on larger scales. It is an Individual-Based Model (IBM) of a hypothetical, tuna-like species, that includes their interactions with each other, free-floating FADs and prey. In this IBM, both tuna and FADs are represented by Lagrangian particles that are advected by an ocean flow field, with tuna also exhibiting active swimming based on internal states such as stomach fullness. We apply the IBM in multiple configurations of idealized flow and prey fields, alongside differing interaction strengths between agents. When tuna swimming behaviour is influenced equally by prey and FADs, we find that the model simulations compare well with observations at the km scale. For instance, compared to observations, tuna particles have a similar stomach fullness when associated or non-associated to a FAD, tuna colonize at similar timescales at FADs after their deployment and tuna particles exhibit similar variations in continuous residence times. However, we find large differences in emergent dynamics such as residence and catch among different flow configurations, because the flow determines the time scale at which tuna encounter FADs. These findings are discussed in the context of directing future research, and an improved interpretation of tuna catch and other data for the sustainable management of these economically important species

Improved Model-Data Agreement With Strongly Eddying Ocean Simulations in the Middle-Late Eocene

Model simulations of past climates are increasingly found to compare well with proxy data at a global scale, but regional discrepancies remain. A persistent issue in modeling past greenhouse climates has been the temperature difference between equatorial and (sub-)polar regions, which is typically much larger in simulations than proxy data suggest. Particularly in the Eocene, multiple temperature proxies suggest extreme warmth in the southwest Pacific Ocean, where model simulations consistently suggest temperate conditions. Here, we present new global ocean model simulations at 0.1° horizontal resolution for the middle-late Eocene. The eddies in the high-resolution model affect poleward heat transport and local time-mean flow in critical regions compared to the noneddying flow in the standard low-resolution simulations. As a result, the high-resolution simulations produce higher surface temperatures near Antarctica and lower surface temperatures near the equator compared to the low-resolution simulations, leading to better correspondence with proxy reconstructions. Crucially, the high-resolution simulations are also much more consistent with biogeographic patterns in endemic-Antarctic and low-latitude-derived plankton, and thus resolve the long-standing discrepancy of warm subpolar ocean temperatures and isolating polar gyre circulation. The results imply that strongly eddying model simulations are required to reconcile discrepancies between regional proxy data and models, and demonstrate the importance of accurate regional paleobathymetry for proxy-model comparisons

Regulation and quantification of cellular mitochondrial morphology and content

Mitochondria play a key role in signal transduction, redox homeostasis and cell survival, which extends far beyond their classical functioning in ATP production and energy metabolism. In living cells, mitochondrial content (“mitochondrial mass”) depends on the cell-controlled balance between mitochondrial biogenesis and degradation. These processes are intricately linked to changes in net mitochondrial morphology and spatiotemporal positioning (“mitochondrial dynamics”), which are governed by mitochondrial fusion, fission and motility. It is becoming increasingly clear that mitochondrial mass and dynamics, as well as its ultrastructure and volume, are mechanistically linked to mitochondrial function and the cell. This means that proper quantification of mitochondrial morphology and content is of prime importance in understanding mitochondrial and cellular physiology in health and disease. This review first presents how cellular mitochondrial content is regulated at the level of mitochondrial biogenesis, degradation and dynamics. Next we discuss how mitochondrial dynamics and content can be analyzed with a special emphasis on quantitative live-cell microscopy strategies.acceptedVersio

An expanded database of Southern Hemisphere surface sediment dinoflagellate cyst assemblages and their oceanographic affinities

Dinoflagellate cyst assemblages present a valuable proxy to infer paleoceanographic conditions, yet factors influencing geographic distributions of species remain largely unknown, especially in the Southern Ocean. Strong lateral transport, sea-ice dynamics, and a sparse and uneven geographic distribution of surface sediment samples have limited the use of dinocyst assemblages as a quantitative proxy for paleo-environmental conditions such as sea surface temperature (SST), nutrient concentrations, salinity, and sea ice (presence). In this study we present a new set of surface sediment samples (nCombining double low line66) from around Antarctica, doubling the number of Antarctic-proximal samples to 100 (dataset wsi_100) and increasing the total number of Southern Hemisphere samples to 655 (dataset sh_655). Additionally, we use modelled ocean conditions and apply Lagrangian techniques to all Southern Hemisphere sample stations to quantify and evaluate the influence of lateral transport on the sinking trajectory of microplankton and, with that, to the inferred ocean conditions. k-means cluster analysis on the wsi_100 dataset demonstrates the strong affinity of Selenopemphix antarctica with sea-ice presence and of Islandinium spp. with low-salinity conditions. For the entire Southern Hemisphere, the k-means cluster analysis identifies nine clusters with a characteristic assemblage. In most clusters a single dinocyst species dominates the assemblage. These clusters correspond to well-defined oceanic conditions in specific Southern Ocean zones or along the ocean fronts. We find that, when lateral transport is predominantly zonal, the environmental parameters inferred from the sea floor assemblages mostly correspond to those of the overlying ocean surface. In this case, the transport factor can thus be neglected and will not represent a bias in the reconstructions. Yet, for some individual sites, e.g. deep-water sites or sites under strong-current regimes, lateral transport can play a large role. The results of our study further constrain environmental conditions represented by dinocyst assemblages and the location of Southern Ocean frontal systems