16 research outputs found

    Modelling large-scale CO2 leakages in the North Sea

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    A three dimensional hydrodynamic model with a coupled carbonate speciation sub-model is used to simulate large additions of CO2into the North Sea, representing leakages at potential carbon sequestration sites. A range of leakage scenarios are conducted at two distinct release sites, allowing an analysis of the seasonal, inter-annual and spatial variability of impacts to the marine ecosystem. Seasonally stratified regions are shown to be more vulnerable to CO2release during the summer as the added CO2remains trapped beneath the thermocline, preventing outgasing to the atmosphere. On average, CO2 injected into the northern North Sea is shown to reside within the water column twice as long as an equivalent addition in the southern North Sea before reaching the atmosphere. Short-term leakages of 5000 tonnes CO2over a single day result in substantial acidification at the release sites (up to -1.92 pH units), with significant perturbations (greater than 0.1 pH units) generally confined to a 10 km radius. Long-term CO2leakages sustained for a year may result in extensive plumes of acidified seawater, carried by major advective pathways. Whilst such scenarios could be harmful to marine biota over confined spatial scales, continued unmitigated CO2emissions from fossil fuels are predicted to result in greater and more long-lived perturbations to the carbonate system over the next few decades

    Spatiotemporal scales of larval dispersal and connectivity among oil and gas structures in the North Sea

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    The ecological role of offshore man-made infrastructure is of growing international interest. By 2030, globally more than 7500 oil and gas platforms could be removed, many of which now host mature hard substrate ecosystems formed by sessile benthic species including sponges, corals and mussels. We investigated the spatiotemporal scales of generalised species dispersal and connectivity among oil and gas structures in the North Sea using strategically designed 3D advective passive particle tracking experiments forced by high resolution (1.8 km, hourly) velocity fields including tide-, density- and wind-driven currents. Trajectories from 2 seasonal releases during mixed winter (February) and stratified summer (July) conditions of 2010 were analysed for a variety of pelagic larval durations (PLDs) spanning 2 to 28 d. Particles dispersed on average 32 km away from their origins after just 5 d, 67 km after 15 d, and 109 km after 28 d, with considerable spatial variability and limited seasonal variations. Short (2 d) PLDs generated highly connected networks over smaller spatial scales, while longer PLDs (28 d) generated less fragmented networks covering a much larger area but with fewer connections. Tidally driven dispersal was isolated using a new method based on the harmonic analysis of the velocity fields: the resulting maximum linear dispersal distances varied from ~4 km in the northern North Sea to ~8 km in the southern North Sea. The present study provides baseline spatiotemporal scales of dispersal and connectivity patterns and optimized relocatable methods to assess connectivity in tidally active shelf seas

    Environmental heterogeneity decreases reproductive success via effects on foraging behaviour

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    Environmental heterogeneity shapes the uneven distribution of resources available to foragers, and is ubiquitous in nature. Optimal foraging theory predicts that an animal's ability to exploit resource patches is key to foraging success. However, the potential fitness costs and benefits of foraging in a heterogeneous environment are difficult to measure empirically. Heterogeneity may provide higher-quality foraging opportunities, or alternatively could increase the cost of resource acquisition because of reduced patch density or increased competition. Here, we study the influence of physical environmental heterogeneity on behaviour and reproductive success of black-legged kittiwakes, Rissa tridactyla. From GPS tracking data at 15 colonies throughout their British and Irish range, we found that environments that were physically more heterogeneous were associated with longer trip duration, more time spent foraging while away from the colony, increased overlap of foraging areas between individuals and lower breeding success. These results suggest that there is greater competition between individuals for finite resources in more heterogeneous environments, which comes at a cost to reproduction. Resource hotspots are often considered beneficial, as individuals can learn to exploit them if sufficiently predictable. However, we demonstrate here that such fitness gains can be countered by greater competition in more heterogeneous environments

    Ocean sprawl facilitates dispersal and connectivity of protected species

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    Highly connected networks generally improve resilience in complex systems. We present a novel application of this paradigm and investigated the potential for anthropogenic structures in the ocean to enhance connectivity of a protected species threatened by human pressures and climate change. Biophysical dispersal models of a protected coral species simulated potential connectivity between oil and gas installations across the North Sea but also metapopulation outcomes for naturally occurring corals downstream. Network analyses illustrated how just a single generation of virtual larvae released from these installations could create a highly connected anthropogenic system, with larvae becoming competent to settle over a range of natural deep-sea, shelf and fjord coral ecosystems including a marine protected area. These results provide the first study showing that a system of anthropogenic structures can have international conservation significance by creating ecologically connected networks and by acting as stepping stones for cross-border interconnection to natural populations

    Assessing the influence of behavioural parameterisation on the dispersal of larvae in marine systems

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    Predicting dispersal and quantifying ecological connectivity are increasingly referenced as fundamental to understanding how biodiversity is structured across space and time. Dispersal models can provide insight, but their predictions are influenced by our capacity to simulate the biology and physics known to influence dispersal. In a marine context, vertical swimming behaviour is considered important in influencing the spatial organisation of species across seascapes, but the mechanisms underpinning these movements remain unresolved, making it unclear how best to incorporate behaviour within models. Here, using a 3-D hydrodynamic model coupled with a Lagrangian particle tracker, we show how different modelled larval behaviours, alongside spatial and temporal hydrodynamic changes, influence larval dispersal predictions. Additionally, we compare the application of a novel approach of reverse-engineered larval swimming behaviour against two commonly modelled behaviours: passive dispersal and tidal vertical migration (TVM). We used statistical models (LME and GAM) to test the effects of change in tidal state conditions, season, and planktonic larval duration in conjunction with behavioural parameters on dispersal. For shorter PLDs (i.e., 1 day), we find that passive models match ‘behaving’ model outputs, but for longer PLDs, excluding behaviour leads to overestimates of dispersal; an effect that increases with time. Our results highlight the sensitivity of biophysical models to behavioural inputs, specifically how vertical migration behaviour can significantly reduce dispersal distance - especially for species with longer planktonic durations. This study demonstrates the disproportionate effects that even a single behaviour - vertical swimming - can have on model predictions, our understanding of ecosystem functioning, and ultimately, the ecological coherence of marine systems

    Anthropogenic Mixing in Seasonally Stratified Shelf Seas by Offshore Wind Farm Infrastructure

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    The offshore wind energy sector has rapidly expanded over the past two decades, providing a renewable energy solution for coastal nations. Sector development has been led in Europe, but is growing globally. Most developments to date have been in well-mixed, i.e., unstratified, shallow-waters near to shore. Sector growth is, for the first time, pushing developments to deep water, into a brand new environment: seasonally stratified shelf seas. Seasonally stratified shelf seas, where water density varies with depth, have a disproportionately key role in primary production, marine ecosystem and biogeochemical cycling. Infrastructure will directly mix stratified shelf seas. The magnitude of this mixing, additional to natural background processes, has yet to be fully quantified. If large enough it may erode shelf sea stratification. Therefore, offshore wind growth may destabilize and fundamentally change shelf sea systems. However, enhanced mixing may also positively impact some marine ecosystems. This paper sets the scene for sector development into this new environment, reviews the potential physical and environmental benefits and impacts of large scale industrialization of seasonally stratified shelf seas and identifies areas where research is required to best utilize, manage, and mitigate environmental change.</jats:p

    Lagrangian ocean analysis: fundamentals and practices

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    Lagrangian analysis is a powerful way to analyse the output of ocean circulation models and other ocean velocity data such as from altimetry. In the Lagrangian approach, large sets of virtual particles are integrated within the three-dimensional, time-evolving velocity fields. Over several decades, a variety of tools and methods for this purpose have emerged. Here, we review the state of the art in the field of Lagrangian analysis of ocean velocity data, starting from a fundamental kinematic framework and with a focus on large-scale open ocean applications. Beyond the use of explicit velocity fields, we consider the influence of unresolved physics and dynamics on particle trajectories. We comprehensively list and discuss the tools currently available for tracking virtual particles. We then showcase some of the innovative applications of trajectory data, and conclude with some open questions and an outlook. The overall goal of this review paper is to reconcile some of the different techniques and methods in Lagrangian ocean analysis, while recognising the rich diversity of codes that have and continue to emerge, and the challenges of the coming age of petascale computing
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