Localised anthropogenic wake generates a predictable foraging hotspot for top predators

Lilian Lieber et al. examined seabird foraging around natural and man-made wakes, finding that wake from a turbine structure generates a more intense and predictable foraging hotspot for seabirds. This shows the importance of changes in physical forcing to top predators when installing or removing offshore structures

Selective foraging behavior of seabirds in small-scale slicks

Lieber L, Füchtencordsjürgen C, Hilder RL, et al. Selective foraging behavior of seabirds in small-scale slicks. Limnology and Oceanography Letters . 2022.Marine predator foraging opportunities are often driven by dynamic physical processes enhancing prey accessibility. Surface slicks are ubiquitous yet ephemeral ocean features where convergent flows accumulate flotsam, concentrating marine organisms and pollutants. Slicks can manifest on the sea surface as meandering lines and seabirds often associate with slicks. Yet, how slicks may influence the fine-scale foraging behavior of seabirds is only coarsely resolved. Here we show that seabirds selectively forage in small-scale slicks. We used aerial drone technology to track surface-foraging terns (Sternidae, 107 tracks) over evolving slicks advected by the mean flow and reshaped by localized turbulence at scales of meters and seconds. Terns were more likely to switch into high-tortuosity foraging behavior when over slicks, with plunge-dive events occurring significantly more often within slicks. As we demonstrate that terns select dynamic slicks for foraging, our approach will also lend itself to interaction studies with pollutants, plumes, and fronts

A physics-enabled flow restoration algorithm for sparse PIV and PTV measurements

The gaps and noise present in particle image velocimetry (PIV) and particle tracking velocimetry (PTV) measurements affect the accuracy of the data collected. Existing algorithms developed for the restoration of such data are only applicable to experimental measurements collected under well-prepared laboratory conditions (i.e. where the pattern of the velocity flow field is known), and the distribution, size and type of gaps and noise may be controlled by the laboratory set-up. However, in many cases, such as PIV and PTV measurements of arbitrarily turbid coastal waters, the arrangement of such conditions is not possible. When the size of gaps or the level of noise in these experimental measurements become too large, their successful restoration with existing algorithms becomes questionable. Here, we outline a new physics-enabled flow restoration algorithm (PEFRA), specially designed for the restoration of such velocity data. Implemented as a 'black box' algorithm, where no user-background in fluid dynamics is necessary, the physical structure of the flow in gappy or noisy data is able to be restored in accordance with its hydrodynamical basis. The use of this is not dependent on types of flow, types of gaps or noise in measurements. The algorithm will operate on any data time-series containing a sequence of velocity flow fields recorded by PIV or PTV. Tests with numerical flow fields established that this method is able to successfully restore corrupted PIV and PTV measurements with different levels of sparsity and noise. This assessment of the algorithm performance is extended with an example application to in situ submersible 3D-PTV measurements collected in the bottom boundary layer of the coastal ocean, where the naturally-occurring plankton and suspended sediments used as tracers causes an increase in the noise level that, without such denoising, will contaminate the measurements

Increasing the Depth of Current Understanding: Sensitivity Testing of Deep-Sea Larval Dispersal Models for Ecologists

Larval dispersal is an important ecological process of great interest to conservation and the establishment of marine protected areas. Increasing numbers of studies are turning to biophysical models to simulate dispersal patterns, including in the deep-sea, but for many ecologists unassisted by a physical oceanographer, a model can present as a black box. Sensitivity testing offers a means to test the models' abilities and limitations and is a starting point for all modelling efforts. The aim of this study is to illustrate a sensitivity testing process for the unassisted ecologist, through a deep-sea case study example, and demonstrate how sensitivity testing can be used to determine optimal model settings, assess model adequacy, and inform ecological interpretation of model outputs. Five input parameters are tested (timestep of particle simulator (TS), horizontal (HS) and vertical separation (VS) of release points, release frequency (RF), and temporal range (TR) of simulations) using a commonly employed pairing of models. The procedures used are relevant to all marine larval dispersal models. It is shown how the results of these tests can inform the future set up and interpretation of ecological studies in this area. For example, an optimal arrangement of release locations spanning a release area could be deduced; the increased depth range spanned in deep-sea studies may necessitate the stratification of dispersal simulations with different numbers of release locations at different depths; no fewer than 52 releases per year should be used unless biologically informed; three years of simulations chosen based on climatic extremes may provide results with 90% similarity to five years of simulation; and this model setup is not appropriate for simulating rare dispersal events. A step-by-step process, summarising advice on the sensitivity testing procedure, is provided to inform all future unassisted ecologists looking to run a larval dispersal simulation

Advancing multi-vehicle deployments in oceanographic field experiments

Our research concerns the coordination and control of robotic vehicles for upper water-column oceanographic observations. In such an environment, operating multiple vehicles to observe dynamic oceanographic phenomena, such as ocean processes and marine life, from fronts to cetaceans, has required that we design, implement and operate software, methods and processes which can support opportunistic needs in real-world settings with substantial constraints. In this work, an approach for coordinated measurements using such platforms, which relate directly to task outcomes, is presented. We show the use and operational value of a new Artificial Intelligence based mixed-initiative system for handling multiple platforms along with the networked infrastructure support needed to conduct such operations in the open sea. We articulate the need and use of a range of middleware architectures, critical for such deployments and ground this in the context of a field experiment in open waters of the mid-Atlantic in the summer of 2015.Advancing multi-vehicle deployments in oceanographic field experimentsacceptedVersio

Total water column analysis shows the importance of a single species in subsurface chlorophyll maximum thin layers in stratified waters

Marine phytoplankton form the base of marine food webs and are the driving force of the marine carbon cycle, so understanding the dynamics of their blooms is critical. While near-surface marine productivity (<10 m water depths) is extensively documented, that of the subsurface is less well characterised. Increasing evidence of the importance of subsurface chlorophyll maxima (SCM) and climatically driven increases in stratification of surface waters that promote SCM development call for improved sampling of the subsurface. To address this, we targeted the summer stratified waters of the Western English Channel, part of the NW European shelf seas, where SCM are commonly developed. In situ holography was applied to undertake the highest ever resolution, total water column, quantitative analysis of microplankton distribution, and demonstrated the importance of a SCM, collocated with the thermocline, dominated by a single species, the dinoflagellate Ceratium fusus. This species was dominant in the SCM over a wide area of the NW European shelf in the June/ July 2015 study period and comprised up to 85% of the SCM biomass. Analysis of similarity and multivariate non-metric multidimensional scaling showed the phytoplankton community of the SCM to be statistically distinct from those of the surface and deep waters. Holography also revealed a fine scale layering of taxa at different levels within the SCM, likely reflecting ecological differences. Some taxa followed the peak abundance of C. fusus, while others reached maximum abundances immediately below or above the C. fusus maximum, suggesting the possible operation of exclusion mechanisms. Additionally, the detection of abundant aggregates located only within and beneath the SCM demonstrates the potential importance of this deep production for the export of carbon to the sea floor. Some predictions of phytoplankton productivity propose a shift to smaller cells in the more stratified oceans of the future resulting in declining production and export. Results presented here, however, contribute to a growing body of evidence that suggests, on the contrary, that key species among the larger celled/ colonial, SCM-adapted diatoms and dinoflagellates may instead be selected in stratified conditions, driving increased production and export

Radiative transfer modelling for sun glint correction in marine satellite imagery

Remote sensing is a powerful tool for studying the marine environment; however, many images are contaminated by sun glint, the specular reflection of light from the water surface. Improved radiative transfer modelling could lead to better methods for estimating and correcting sunglint. This thesis explores the effect of using detailed numerical models of the sea surface when investigating the transfer of light through the atmosphere-ocean system. New numerical realisations that model both the shape and slope of the sea surface have been created; these contrast with existing radiative transfer models, where the air-water interface has slope but not elevation. Surface realisations including features on a scale from 3 mm to 200 m were created by a Fourier synthesis method, using up to date spectra of the wind-blown sea surface. The surfaces had mean square slopes and elevation variances in line with those of observed seas, for wind speeds up to 15 m/s. Ray-tracing using the new surfaces gave estimates of reflected radiance that were similar to those made using slope statistics methods, but significantly different in 41% of cases tested. The mean difference in the reflected radiance at these points was 19%, median 7%. Elevation-based surfaces give increased sideways scattering and reduced forward scattering of light incident on the sea surface. The elevation-based models have been applied to estimate pixel-pixel variation in ocean colour imagery and to simulate scenes viewed by three types of sensor. The simulations correctly estimated the size and position of the glint zone. Simulations of two ocean colour images gave a lower peak reflectance than the original values, but higher reflectance at the edge of the glint zone. The use of the simulation to test glint correction methods has been demonstrated, as have global Monte Carlo techniques for investigating sensitivity and uncertainty in sun glint correction. This work has shown that elevation-based sea surface models can be created and tested using readily-available computer hardware. The new model can be used to simulate glint in a variety of situations, giving a tool for testing glint correction methods. It could also be used for glint correction directly, by predicting the level of sun glint in a given set of conditions.EThOS - Electronic Theses Online ServiceGreat Western Research : ARGANS LtdGBUnited Kingdo