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The transition between coastal and offshore areas in the North Sea unraveled by suspended particle composition
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Identifying the mechanisms that contribute to the variability of suspended particulate matter concentrations in coastal areas is important but difficult, especially due to the complexity of physical and biogeochemical interactions involved. Our study addresses this complexity and investigates changes in the horizontal spread and composition of particles, focusing on cross-coastal gradients in the southern North Sea and the English Channel. A semi-empirical model is applied on in situ data of SPM and its organic fraction to resolve the relationship between organic and inorganic suspended particles. The derived equations are applied onto remote sensing products of SPM concentration, which provide monthly synoptic maps of particulate organic matter concentrations (here, particulate organic nitrogen) at the surface together with their labile and less reactive fractions. Comparing these fractions of particulate organic matter reveals their characteristic features along the coastal-offshore gradient, with an area of increased settling rate for particles generally observed between 5 and 30 km from the coast. We identify this area as the transition zone between coastal and offshore waters with respect to particle dynamics. Presumably, in that area, the turbulence range and particle composition favor particle settling, while hydrodynamic processes tend to transport particles of the seabed back towards the coast. Bathymetry plays an important role in controlling the range of turbulent dissipation energy values in the water column, and we observe that the transition zone in the southern North Sea is generally confined to water depths below 20 m. Seasonal variations in suspended particle dynamics are linked to biological processes enhancing particle flocculation, which do not affect the location of the transition zone. We identify the criteria that allow a transition zone and discuss the cases where it is not observed in the domain. The impact of these particle dynamics on coastal carbon storage and export is discussed.
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RBINS Staff Publications 2024 OA
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Lessons from the calibration and sensitivity analysis of a fish larval transport model
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ABSTRACT: Numerous fish populations show strong year-to-year variations in recruitment. The early life stages play a crucial role in determining recruitment and dispersal patterns. A helpful tool to understand recruitment and dispersal involves simulations with a Lagrangian transport model, which results from the coupling between a hydrodynamic model and an individual-based model. Larval transport models require sound knowledge of the biological processes governing larval dispersal, and they may be highly sensitive to the parameters selected. Various assumptions about larval traits, behaviour and other model parameters can be tested by comparing simulation results with field data to identify the most sensitive parameters and to improve model calibration. This study shows that biological parameterization is more important than inter-annual variability in explaining the year-to-year differences in larval recruitment of common sole in the North Sea and the eastern English Channel. In contrast, year-to-year variability of connectivity leads to higher variability than changes in the biological parameters. The most influential parameters are pelagic larval duration, spawning period and mortality. Calibration over a 12 yr recruitment survey shows that a scenario with low mortality associated with a long larval duration and behaviour involving nycthemeral and tidal migration best reproduces the observations. This research provides insights into factors influencing fish dispersal and recruitment, suggesting a strategy for enhancing the accuracy of models in upcoming studies. The study supports the improvement of larval dispersal modelling by incorporating an easily applicable sensitivity analysis for both calibration and validation. Incorporating sensitivity analyses enhances larval dispersal models, providing performing tools that can contribute to informed fisheries management and understanding of recruitment variability.
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RBINS Staff Publications 2024
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Discovery-defense strategy as a mechanism of social foraging of ants in tropical rainforest canopies
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RBINS Staff Publications 2017
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Distance–decay patterns differ between canopy and ground ant assemblages in a tropical rainforest
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RBINS Staff Publications 2017
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Spatial and functional structure of an entire ant assemblage in a lowland Panamanian rainforest
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ABSTRACT Ants are a major ecological group in tropical rainforests. Few studies in the Neotropics have documented the distribution of ants from the ground to the canopy, and none have included the understorey. A previous analysis of an intensive arthropod study in Panama, involving 11 sampling methods, showed that the factors influencing ant beta diversity (i.e., changes in assemblage composition) were, in decreasing order of importance, the vertical (height), temporal (season), and horizontal (geographic distance) dimensions. In the present study, we went one step further and aimed (1) to identify the best sampling methods to study the entire ant assemblage across the three strata, (2) to test if all strata show a similar horizontal beta diversity and (3) to analyze the functional structure of the entire ant assemblage. We identified 405 ant species from 11 subfamilies and 68 genera. Slightly more species were sampled in the canopy than on the ground; they belonged to distinct sub-assemblages. The understorey fauna was mainly a mixture of species found in the other two strata. The horizontal beta diversity between sites was similar for the three strata. About half of the ant species foraged in two (29%) or three (25%) strata. A single method, aerial flight interception traps placed alongside tree trunks, acting as arboreal pitfall traps, collected half of the species and reflected the vertical stratification. Using the functional traits approach, we observed that generalist species with mid-sized colonies were by far the most numerous (31%), followed by ground- or litter-dwelling species, either specialists (20%), or generalists (16%), and arboreal species, either generalists (19%) or territorially dominant (8%), and finally army ants (5%). Our results reinforce the idea that a proper understanding of the functioning of ant assemblages requires the inclusion of arboreal ants in survey programs.
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RBINS Staff Publications 2017
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Inter‐specific aggression generates ant mosaics in canopies of primary tropical rainforest
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RBINS Staff Publications 2017
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Rapid assessment of the three‐dimensional distribution of dominant arboreal ants in tropical forests
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RBINS Staff Publications 2017
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A decomposition approach to cyclostratigraphic signal processing
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Sedimentary rocks can record signals produced by highly complex processes. These signals are generated by a progressive deposition of sediments which can be affected, mainly through the climate system, by regular astronomical cycles (i.e. Milankovitch cycles), and by irregular oscillations like the El Niño-Southern Oscillation. Also, usually through biological, chemical and/or physical post-depositional processes, the sedimentary records can be affected by pattern-creating heterogeneous processes. The noise in the signals further complicates the records, and the deposition rate (or sedimentation rate) can fluctuate, which greatly reduces the effectiveness of the classical stationary time-series analysis methods commonly used in cyclostratigraphy (i.e. the study of the cycles found in the sedimentary records). Faced with this multiplicity of processes, a common approach used in cyclostratigraphy is to reduce each signal to more manageable sub-signals, either over a given range of frequencies (e.g., by filtering), or by considering a continuum of constant frequencies (e.g., using transforms). This makes it possible to focus on the features of interest, commonly astronomical cycles. However, working with sub-signals is not trivial. Firstly, sub-signals have a certain amount of cross-cancellation when they are summed back to reconstruct the initial signal. This means that in filters and in transforms, wiggles that are not present in the initial signal can appear in the sub-signals. Secondly, the sub-signals considered often cannot be summed to reconstruct the initial signal: this means that there are processes affecting the signal which remain unstudied. It is possible to take cross-cancellation into account and to consider the entire content of a signal by dividing the signal into a decomposition: a set of sub-signals that can be added back together to reconstruct the original signal. We discuss here how to reframe commonly used time-series analysis techniques in the context of decomposition, how they are affected by cross-cancellation, and how adequate they are for comprehending the whole signals. We also show that decomposition can be carried out by non-stationary time-series methods, which can minimise cross-cancellation, and have now reached sufficient maturity to tackle sedimentary records signals. We present novel tools to adapt non-stationary decomposition for cyclostratigraphic purposes, based on the concepts of Empirical Mode Decomposition (EMD) and Instantaneous Frequency (IF), mainly: (1) a fast Ensemble Empirical Mode Decomposition (EEMD) algorithm, (2) quality metrics for decomposition, and (3) plots to visualise instantaneous frequency, amplitude and frequency ratio. We illustrate the use of these tools by applying them on a greyscale signal from the site 926 of the Ocean Drilling Program, at Ceara Rise (western equatorial Atlantic), especially to identify and characterise the expression of astronomical cycles. The main goal is to show that by minimising cross-cancellation, we can apply in real signals what we call the wiggle-in-signal approach: making the sub-signals in the decomposition more representative of the expression, wiggle by wiggle, of all the processes affecting the signal (e.g., astronomical cycles). We finally argue that decomposition could be used as a practical standard output for time-series analysis interpretation of cyclostratigraphic signals.
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RBINS Staff Publications 2021
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Optimizing multiple non-invasive techniques (PXRF, pMS, IA) to characterize coarse-grained igneous rocks used as building stones.
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We present a workflow to conduct a full characterization of medium to coarse-grained igneous rocks, using portable, non-invasive, and reproducible approaches. This includes: (i) Image Analysis (IA) to quantify mineral phase proportions, grain size distribution using the Weka trainable machine learning algorithm. (ii) Portable X-ray fluorescence spectrometer (PXRF, Bruker Tracer IV) to quantify the whole-rock's chemical composition. For this purpose, a specific calibration method dedicated to igneous rocks using the open-source CloudCal app was developed. It was then validated for several key elements (Si, Al, K, Ti, Ca, Fe, Mn, Sr, Ga, Ba, Rb, Zn, Nb, Zr, and Y) by analyzing certified standard reference igneous rocks. (iii) Portable Magnetic Susceptibilimeter (pMS, Bartington MS2K system) to constrain the mineralogical contribution of the samples. The operational conditions for these three methods were tested and optimized by analyzing five unprepared surfaces of igneous rocks ranging from a coarse-grained alkaline granite to a fine-grained porphyric diorite and hence, covering variable grain sizes, mineralogical contents, and whole-rock geochemical compositions. For pMS and PXRF tools, one hundred analyses were conducted as a 10 cm × 10 cm square grid on each sample. Bootstrap analysis was implemented to establish the best grid size sampling to reach an optimized reproducibility of the whole-rock signature. For PXRF analysis, averaged compositions were compared to PXRF analysis on press-pellets and laboratory WD-XRF analysis on fused disk and solution ICP-OES (for major) and solution-ICPMS (for trace element concentrations). Ultimately, this workflow was applied in the field on granitoids from three Roman quarrying sites in the Lavezzi archipelago (southern Corsica) and tested against the Bonifacio granitic War Memorial, for which its provenance is established. Our results confirm this information and open the door to geoarchaeological provenance studies with a high spatial resolution.
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RBINS Staff Publications 2021
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Brussels’ bedrock paleorelief from borehole-controlled power laws linking polarised H/V resonance frequencies and sediment thickness
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The empirical power law relation (PR) between resonance frequency (f0), obtained from H/V spectral ratio analysis of ambient noise, and sediment thickness (h), obtained from boreholes, is frequently used in microzonation studies to predict bedrock depth. In this study, we demonstrate (i) how to optimally construct a PR by including the error on the picked f0 in the regression, and (ii) how to evaluate a regression quality by identifying the under- or overestimation of the sediment thickness prediction. We apply this methodology on f0 data derived from 74 ambient noise recordings acquired above boreholes that reach the Brabant Massif bedrock below Brussels (Belgium). Separating the f0 data into different subset based on the cover geology does not significantly improve the bedrock depth prediction because the cover geology in Brussels has common base layers. In Brussels, the PR relation h = 88.631.f0−1.683 is the best candidate to convert f0 to depth, with a prediction error of 10%. The Brussels PR was subsequently applied on a local survey (404 measurements; 25 km2) in southern Brussels with the aim to study Brussels’ Brabant Massif bedrock paleorelief. By linking the obtained paleorelief, Bouguer gravity data and aeromagnetic data, a NNW-SSE oriented, 20 m-high subsurface ridge could be identified. This ridge stands out because of differential erosion between less-resistant and hard quartzitic rock formations of the Brabant Massif. This subsurface ridge deflects the local radiation of seismic energy resulting in an anomaly in the otherwise regional consistent azimuthal dependency of the resonance frequency. We conclude that adding a polarisation analysis to a microzonation survey analysis allows detecting anomalous features in the paleorelief.
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RBINS Staff Publications 2021
