940 resultados para spatial and temporal variations
Resumo:
The densities of Pick bodies (PB), Pick cells (PC), senile plaques (SP) and neurofibrillary tangles (NFT) in the frontal and temporal lobe were determined in ten patients diagnosed with Pick's disease (PD). The density of PB was significantly higher in the dentate gyrus granule cells compared with the cortex and the CA sectors of the hippocampus. Within the hippocampus, the highest densities of PB were observed in sector CA1. PC were absent in the dentate gyrus and no significant differences in PC density were observed in the remaining brain regions. With the exception of two patients, the densities of SP and NFT were low with no significant differences in mean densities between cortical regions. In the hippocampus, the density of NFT was greatest in sector CA1. PB and PC densities were positively correlated in the frontal cortex but no correlations were observed between the PD and AD lesions. A principal components analysis (PCA) of the neuropathological variables suggested that variations in the densities of SP in the frontal cortex, temporal cortex and hippocampus were the most important sources of heterogeneity within the patient group. Variations in the densities of PB and NFT in the temporal cortex and hippocampus were of secondary importance. In addition, the PCA suggested that two of the ten patients were atypical. One patient had a higher than average density of SP and one familial patient had a higher density of NFT but few SP.
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A distinct feature of several recent models of contrast masking is that detecting mechanisms are divisively inhibited by a broadly tuned ‘gain pool’ of narrow-band spatial pattern mechanisms. The contrast gain control provided by this ‘cross-channel’ architecture achieves contrast normalisation of early pattern mechanisms, which is important for keeping them within the non-saturating part of their biological operating characteristic. These models superseded earlier ‘within-channel’ models, which had supposed that masking arose from direct stimulation of the detecting mechanism by the mask. To reveal the extent of masking, I measured the levels produced with large ranges of pattern spatial relationships that have not been explored before. Substantial interactions between channels tuned to different orientations and spatial frequencies were found. Differences in the masking levels produced with single and multiple component mask patterns provided insights into the summation rules within the gain pool. A widely used cross-channel masking model was tested on these data and was found to perform poorly. The model was developed and a version in which linear summation was allowed between all components within the gain pool but with the exception of the self-suppressing route typically provided the best account of the data. Subsequently, an adaptation paradigm was used to probe the processes underlying pooled responses in masking. This delivered less insight into the pooling than the other studies and areas were identified that require investigation for a new unifying model of masking and adaptation. In further experiments, levels of cross-channel masking were found to be greatly influenced by the spatio-temporal tuning of the channels involved. Old masking experiments and ideas relying on within-channel models were re-elevated in terms of contemporary cross-channel models (e.g. estimations of channel bandwidths from orientation masking functions) and this led to different conclusions than those originally arrived at. The investigation of effects with spatio-temporally superimposed patterns is focussed upon throughout this work, though it is shown how these enquiries might be extended to investigate effects across spatial and temporal position.
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The Ráckeve-Soroksár Danube has a great importance as it is the second largest side arm in the Hungarian section of the river Danube and many demands of exploitation are expected. The aim of this study is to analyse the spatial and temporal changes of the zooplankton (Copepoda, Cladocera) community in this river arm, moreover the similarity patterns of zooplankton communities in different Hungarian water bodies are presented in special consideration of the Ráckeve-Soroksár Danube. Basically this study is based on data from literature, however our data are also used for compiling the database for the spatio-temporal changes of the Ráckeve-Soroksár Danube. We put emphasis on the three typical sections of the side arm, as these are stressed due to hydromorphological aspects, but creating artificial borders are objectionable as well. The results show that both spatial and temporal changes are evident, what is more, the stagnant water character of the side arm should be underlined.
Resumo:
Elemental and isotopic composition of leaves of the seagrassThalassia testudinum was highly variable across the 10,000 km2 and 8 years of this study. The data reported herein expand the reported range in carbon:nitrogen (C:N) and carbon:phosphorus (C:P) ratios and δ13C and δ15N values reported for this species worldwide; 13.2–38.6 for C:N and 411–2,041 for C:P. The 981 determinations in this study generated a range of −13.5‰ to −5.2‰ for δ13C and −4.3‰ to 9.4‰ for δ15N. The elemental and isotope ratios displayed marked seasonality, and the seasonal patterns could be described with a simple sine wave model. C:N, C:P, δ13C, and δ15N values all had maxima in the summer and minima in the winter. Spatial patterns in the summer maxima of these quantities suggest there are large differences in the relative availability of N and P across the study area and that there are differences in the processing and the isotopic composition of C and N. This work calls into question the interpretation of studies about nutrient cycling and food webs in estuaries based on few samples collected at one time, since we document natural variability greater than the signal often used to imply changes in the structure or function of ecosystems. The data and patterns presented in this paper make it clear that there is no threshold δ15N value for marine plants that can be used as an unambiguous indicator of human sewage pollution without a thorough understanding of local temporal and spatial variability.
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Human use of the oceans is increasingly in conflict with conservation of endangered species. Methods for managing the spatial and temporal placement of industries such as military, fishing, transportation and offshore energy, have historically been post hoc; i.e. the time and place of human activity is often already determined before assessment of environmental impacts. In this dissertation, I build robust species distribution models in two case study areas, US Atlantic (Best et al. 2012) and British Columbia (Best et al. 2015), predicting presence and abundance respectively, from scientific surveys. These models are then applied to novel decision frameworks for preemptively suggesting optimal placement of human activities in space and time to minimize ecological impacts: siting for offshore wind energy development, and routing ships to minimize risk of striking whales. Both decision frameworks relate the tradeoff between conservation risk and industry profit with synchronized variable and map views as online spatial decision support systems.
For siting offshore wind energy development (OWED) in the U.S. Atlantic (chapter 4), bird density maps are combined across species with weights of OWED sensitivity to collision and displacement and 10 km2 sites are compared against OWED profitability based on average annual wind speed at 90m hub heights and distance to transmission grid. A spatial decision support system enables toggling between the map and tradeoff plot views by site. A selected site can be inspected for sensitivity to a cetaceans throughout the year, so as to capture months of the year which minimize episodic impacts of pre-operational activities such as seismic airgun surveying and pile driving.
Routing ships to avoid whale strikes (chapter 5) can be similarly viewed as a tradeoff, but is a different problem spatially. A cumulative cost surface is generated from density surface maps and conservation status of cetaceans, before applying as a resistance surface to calculate least-cost routes between start and end locations, i.e. ports and entrance locations to study areas. Varying a multiplier to the cost surface enables calculation of multiple routes with different costs to conservation of cetaceans versus cost to transportation industry, measured as distance. Similar to the siting chapter, a spatial decisions support system enables toggling between the map and tradeoff plot view of proposed routes. The user can also input arbitrary start and end locations to calculate the tradeoff on the fly.
Essential to the input of these decision frameworks are distributions of the species. The two preceding chapters comprise species distribution models from two case study areas, U.S. Atlantic (chapter 2) and British Columbia (chapter 3), predicting presence and density, respectively. Although density is preferred to estimate potential biological removal, per Marine Mammal Protection Act requirements in the U.S., all the necessary parameters, especially distance and angle of observation, are less readily available across publicly mined datasets.
In the case of predicting cetacean presence in the U.S. Atlantic (chapter 2), I extracted datasets from the online OBIS-SEAMAP geo-database, and integrated scientific surveys conducted by ship (n=36) and aircraft (n=16), weighting a Generalized Additive Model by minutes surveyed within space-time grid cells to harmonize effort between the two survey platforms. For each of 16 cetacean species guilds, I predicted the probability of occurrence from static environmental variables (water depth, distance to shore, distance to continental shelf break) and time-varying conditions (monthly sea-surface temperature). To generate maps of presence vs. absence, Receiver Operator Characteristic (ROC) curves were used to define the optimal threshold that minimizes false positive and false negative error rates. I integrated model outputs, including tables (species in guilds, input surveys) and plots (fit of environmental variables, ROC curve), into an online spatial decision support system, allowing for easy navigation of models by taxon, region, season, and data provider.
For predicting cetacean density within the inner waters of British Columbia (chapter 3), I calculated density from systematic, line-transect marine mammal surveys over multiple years and seasons (summer 2004, 2005, 2008, and spring/autumn 2007) conducted by Raincoast Conservation Foundation. Abundance estimates were calculated using two different methods: Conventional Distance Sampling (CDS) and Density Surface Modelling (DSM). CDS generates a single density estimate for each stratum, whereas DSM explicitly models spatial variation and offers potential for greater precision by incorporating environmental predictors. Although DSM yields a more relevant product for the purposes of marine spatial planning, CDS has proven to be useful in cases where there are fewer observations available for seasonal and inter-annual comparison, particularly for the scarcely observed elephant seal. Abundance estimates are provided on a stratum-specific basis. Steller sea lions and harbour seals are further differentiated by ‘hauled out’ and ‘in water’. This analysis updates previous estimates (Williams & Thomas 2007) by including additional years of effort, providing greater spatial precision with the DSM method over CDS, novel reporting for spring and autumn seasons (rather than summer alone), and providing new abundance estimates for Steller sea lion and northern elephant seal. In addition to providing a baseline of marine mammal abundance and distribution, against which future changes can be compared, this information offers the opportunity to assess the risks posed to marine mammals by existing and emerging threats, such as fisheries bycatch, ship strikes, and increased oil spill and ocean noise issues associated with increases of container ship and oil tanker traffic in British Columbia’s continental shelf waters.
Starting with marine animal observations at specific coordinates and times, I combine these data with environmental data, often satellite derived, to produce seascape predictions generalizable in space and time. These habitat-based models enable prediction of encounter rates and, in the case of density surface models, abundance that can then be applied to management scenarios. Specific human activities, OWED and shipping, are then compared within a tradeoff decision support framework, enabling interchangeable map and tradeoff plot views. These products make complex processes transparent for gaming conservation, industry and stakeholders towards optimal marine spatial management, fundamental to the tenets of marine spatial planning, ecosystem-based management and dynamic ocean management.
Resumo:
BACKGROUND: Chromatin containing the histone variant CENP-A (CEN chromatin) exists as an essential domain at every centromere and heritably marks the location of kinetochore assembly. The size of the CEN chromatin domain on alpha satellite DNA in humans has been shown to vary according to underlying array size. However, the average amount of CENP-A reported at human centromeres is largely consistent, implying the genomic extent of CENP-A chromatin domains more likely reflects variations in the number of CENP-A subdomains and/or the density of CENP-A nucleosomes within individual subdomains. Defining the organizational and spatial properties of CEN chromatin would provide insight into centromere inheritance via CENP-A loading in G1 and the dynamics of its distribution between mother and daughter strands during replication. RESULTS: Using a multi-color protein strategy to detect distinct pools of CENP-A over several cell cycles, we show that nascent CENP-A is equally distributed to sister centromeres. CENP-A distribution is independent of previous or subsequent cell cycles in that centromeres showing disproportionately distributed CENP-A in one cycle can equally divide CENP-A nucleosomes in the next cycle. Furthermore, we show using extended chromatin fibers that maintenance of the CENP-A chromatin domain is achieved by a cycle-specific oscillating pattern of new CENP-A nucleosomes next to existing CENP-A nucleosomes over multiple cell cycles. Finally, we demonstrate that the size of the CENP-A domain does not change throughout the cell cycle and is spatially fixed to a similar location within a given alpha satellite DNA array. CONCLUSIONS: We demonstrate that most human chromosomes share similar patterns of CENP-A loading and distribution and that centromere inheritance is achieved through specific placement of new CENP-A near existing CENP-A as assembly occurs each cell cycle. The loading pattern fixes the location and size of the CENP-A domain on individual chromosomes. These results suggest that spatial and temporal dynamics of CENP-A are important for maintaining centromere identity and genome stability.
Resumo:
Centromeres are essential chromosomal loci at which kinetochore formation occurs for spindle fiber attachment during mitosis and meiosis, guiding proper segregation of chromosomes. In humans, centromeres are located at large arrays of alpha satellite DNA, contributing to but not defining centromere function. The histone variant CENP-A assembles at alpha satellite DNA, epigenetically defining the centromere. CENP-A containing chromatin exists as an essential domain composed of blocks of CENP-A nucleosomes interspersed with blocks of H3 nucleosomes, and is surrounded by pericentromeric heterochromatin. In order to maintain genomic stability, the CENP-A domain is propagated epigenetically over each cell division; disruption of propagation is associated with chromosome instabilities such as aneuploidy, found in birth defects and in cancer.
The CENP-A chromatin domain occupies 30-45% of the alpha satellite array, varying in genomic distance according to the underlying array size. However, the molecular mechanisms that control assembly and organization of CENP-A chromatin within its genomic context remain unclear. The domain may shift, expand, or contract, as CENP-A is loaded and dispersed each cell cycle. We hypothesized that in order to maintain genome stability, the centromere is inherited as static chromatin domains, maintaining size and position within the pericentric heterochromatin. Utilizing stretched chromatin fibers, I found that CENP-A chromatin is limited to a sub-region of the alpha satellite array that is fixed in size and location through the cell cycle and across populations.
The average amount of CENP-A at human centromeres is largely consistent, implying that the variation in size of CENP-A domains reflects variations in the number of CENP-A subdomains and/or the density of CENP-A nucleosomes. Multi-color nascent protein labeling experiments were utilized to examine the distribution and incorporation of distinct pools of CENP-A over several cell cycles. I found that in each cell cycle there is independent CENP-A distribution, occurring equally between sister centromeres across all chromosomes, in similar quantities. Furthermore, centromere inheritance is achieved through specific placement of CENP-A, following an oscillating pattern that fixes the location and size of the CENP-A domain. These results suggest that spatial and temporal dynamics of CENP-A are important for maintaining centromere and genome stability.
Resumo:
The amount and quality of available biomass is a key factor for the sustainable livestock industry and agricultural management related decision making. Globally 31.5% of land cover is grassland while 80% of Ireland’s agricultural land is grassland. In Ireland, grasslands are intensively managed and provide the cheapest feed source for animals. This dissertation presents a detailed state of the art review of satellite remote sensing of grasslands, and the potential application of optical (Moderate–resolution Imaging Spectroradiometer (MODIS)) and radar (TerraSAR-X) time series imagery to estimate the grassland biomass at two study sites (Moorepark and Grange) in the Republic of Ireland using both statistical and state of the art machine learning algorithms. High quality weather data available from the on-site weather station was also used to calculate the Growing Degree Days (GDD) for Grange to determine the impact of ancillary data on biomass estimation. In situ and satellite data covering 12 years for the Moorepark and 6 years for the Grange study sites were used to predict grassland biomass using multiple linear regression, Neuro Fuzzy Inference Systems (ANFIS) models. The results demonstrate that a dense (8-day composite) MODIS image time series, along with high quality in situ data, can be used to retrieve grassland biomass with high performance (R2 = 0:86; p < 0:05, RMSE = 11.07 for Moorepark). The model for Grange was modified to evaluate the synergistic use of vegetation indices derived from remote sensing time series and accumulated GDD information. As GDD is strongly linked to the plant development, or phonological stage, an improvement in biomass estimation would be expected. It was observed that using the ANFIS model the biomass estimation accuracy increased from R2 = 0:76 (p < 0:05) to R2 = 0:81 (p < 0:05) and the root mean square error was reduced by 2.72%. The work on the application of optical remote sensing was further developed using a TerraSAR-X Staring Spotlight mode time series over the Moorepark study site to explore the extent to which very high resolution Synthetic Aperture Radar (SAR) data of interferometrically coherent paddocks can be exploited to retrieve grassland biophysical parameters. After filtering out the non-coherent plots it is demonstrated that interferometric coherence can be used to retrieve grassland biophysical parameters (i. e., height, biomass), and that it is possible to detect changes due to the grass growth, and grazing and mowing events, when the temporal baseline is short (11 days). However, it not possible to automatically uniquely identify the cause of these changes based only on the SAR backscatter and coherence, due to the ambiguity caused by tall grass laid down due to the wind. Overall, the work presented in this dissertation has demonstrated the potential of dense remote sensing and weather data time series to predict grassland biomass using machine-learning algorithms, where high quality ground data were used for training. At present a major limitation for national scale biomass retrieval is the lack of spatial and temporal ground samples, which can be partially resolved by minor modifications in the existing PastureBaseIreland database by adding the location and extent ofeach grassland paddock in the database. As far as remote sensing data requirements are concerned, MODIS is useful for large scale evaluation but due to its coarse resolution it is not possible to detect the variations within the fields and between the fields at the farm scale. However, this issue will be resolved in terms of spatial resolution by the Sentinel-2 mission, and when both satellites (Sentinel-2A and Sentinel-2B) are operational the revisit time will reduce to 5 days, which together with Landsat-8, should enable sufficient cloud-free data for operational biomass estimation at a national scale. The Synthetic Aperture Radar Interferometry (InSAR) approach is feasible if there are enough coherent interferometric pairs available, however this is difficult to achieve due to the temporal decorrelation of the signal. For repeat-pass InSAR over a vegetated area even an 11 days temporal baseline is too large. In order to achieve better coherence a very high resolution is required at the cost of spatial coverage, which limits its scope for use in an operational context at a national scale. Future InSAR missions with pair acquisition in Tandem mode will minimize the temporal decorrelation over vegetation areas for more focused studies. The proposed approach complements the current paradigm of Big Data in Earth Observation, and illustrates the feasibility of integrating data from multiple sources. In future, this framework can be used to build an operational decision support system for retrieval of grassland biophysical parameters based on data from long term planned optical missions (e. g., Landsat, Sentinel) that will ensure the continuity of data acquisition. Similarly, Spanish X-band PAZ and TerraSAR-X2 missions will ensure the continuity of TerraSAR-X and COSMO-SkyMed.
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Although soil algae are among the main primary producers in most terrestrial ecosystems of continental Antarctica, there are very few quantitative studies on their relative proportion in the main algal groups and on how their distribution is affected by biotic and abiotic factors. Such knowledge is essential for understanding the functioning of Antarctic terrestrial ecosystems. We therefore analyzed biological soil crusts from northern Victoria Land to determine their pH, electrical conductivity (EC), water content (W), total and organic C (TC and TOC) and total N (TN) contents, and the presence and abundance of photosynthetic pigments. In particular, the latter were tested as proxies for biomass and coarse-resolution community structure. Soil samples were collected from five sites with known soil algal communities and the distribution of pigments was shown to reflect differences in the relative proportions of Chlorophyta, Cyanophyta and Bacillariophyta in these sites. Multivariate and univariate models strongly indicated that almost all soil variables (EC, W, TOC and TN) were important environmental correlates of pigment distribution. However, a significant amount of variation is independent of these soil variables and may be ascribed to local variability such as changes in microclimate at varying spatial and temporal scales. There are at least five possible sources of local variation: pigment preservation, temporal variations in water availability, temporal and spatial interactions among environmental and biological components, the local-scale patchiness of organism distribution, and biotic interactions.
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Previous studies about the strength of the lithosphere in the Iberia centre fail to resolve the depth of earthquakes because of the rheological uncertainties. Therefore, new contributions are considered (the crustal structure from a density model) and several parameters (tectonic regime, mantle rheology, strain rate) are checked in this paper to properly examine the role of lithospheric strength in the intraplate seismicity and the Cenozoic evolution. The strength distribution with depth, the integrated strength, the effective elastic thickness and the seismogenic thickness have been calculated by a finite element modelling of the lithosphere across the Central System mountain range and the bordering Duero and Madrid sedimentary basins. Only a dry mantle under strike-slip/extension and a strain rate of 10-15 s-1, or under extension and 10-16 s-1, causes a strong lithosphere. The integrated strength and the elastic thickness are lower in the mountain chain than in the basins. These anisotropies have been maintained since the Cenozoic and determine the mountain uplift and the biharmonic folding of the Iberian lithosphere during the Alpine deformations. The seismogenic thickness bounds the seismic activity in the upper–middle crust, and the decreasing crustal strength from the Duero Basin towards the Madrid Basin is related to a parallel increase in Plio–Quaternary deformations and seismicity. However, elasto–plastic modelling shows that current African–Eurasian convergence is resolved elastically or ductilely, which accounts for the low seismicity recorded in this region.
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Tidal stream turbines could have several direct impacts upon pursuit-diving seabirds foraging within tidal stream environments (mean horizontal current speeds > 2 ms−1), including collisions and displacement. Understanding how foraging seabirds respond to temporally variable but predictable hydrodynamic conditions immediately around devices could identify when interactions between seabirds and devices are most likely to occur; information which would quantify the magnitude of potential impacts, and also facilitate the development of suitable mitigation measures. This study uses shore-based observational surveys and Finite Volume Community Ocean Model outputs to test whether temporally predictable hydrodynamic conditions (horizontal current speeds, water elevation, turbulence) influenced the density of foraging black guillemots Cepphus grylle and European shags Phalacrocorax aristotelis in a tidal stream environment in Orkney, United Kingdom, during the breeding season. These species are particularly vulnerable to interactions with devices due to their tendency to exploit benthic and epi-benthic prey on or near the seabed. The density of both species decreased as a function of horizontal current speeds, whereas the density of black guillemots also decreased as a function of water elevation. These relationships could be linked to higher energetic costs of dives in particularly fast horizontal current speeds (>3 ms−1) and deeper water. Therefore, interactions between these species and moving components seem unlikely at particularly high horizontal current speeds. Combining this information, with that on the rotation rates of moving components at lower horizontal current speeds, could be used to assess collision risk in this site during breeding seasons. It is also likely that moderating any device operation during both lowest water elevation and lowest horizontal current speeds could reduce the risk of collisions for these species in this site during this season. The approaches used in this study could have useful applications within Environmental Impact Assessments, and should be considered when assessing and mitigating negative impacts from specific devices within development sites.
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This study seeks to understand how the physiological constraints of diving may change on a daily and seasonal basis. Dive data were obtained from southern elephant seals (Mirounga leonina) from South Georgia using satellite relay data loggers. We analysed the longest (95th percentile) dive durations as proxies for physiological dive limits. A strong, significant relationship existed between the duration of these dives and the time of day and week of year in which they were performed. The depth of the deepest dives also showed a significant, but far less consistent, relationship with local time of day and season. Changes in the duration of the longest dives occurred irrespective of their depth. Dives were longest in the morning (04:00-12:00 h) and shortest in the evening (16:00-00:00 h). The size of the fluctuation varied among animals from 4.0 to 20.0 min. The daily pattern in dive depth was phase-shifted in relation to the diurnal rhythm in dive duration. Dives were deeper at midday and shallower around midnight. Greater daily changes in duration occurred in seals feeding in the open ocean than in those foraging on the continental shelf. The seasonal peak in the duration of the longest dives coincided with austral midwinter. The size of the increase in dive duration from autumn/spring to winter ranged from 11.5 to 30.0 min. Changes in depth of the longest dives were not consistently associated with particular times of year. The substantial diurnal and seasonal fluctuations in maximum dive duration may be a result of changes in the physiological capacity to remain submerged, in addition to temporal changes in the ecological constraints on dive behaviour. We speculate about the role of melatonin as a hormonal mediator of diving capability.
Resumo:
The Mediterranean Sea constitutes a unique environment to study cold-seep ecosystems due to the presence of different geodynamic settings, from an active margin along the Mediterranean Ridge (MR) to a passive margin in the Nile Deep-Sea Fan (NDSF). We attempted to identify the structure of benthic communities associated with the Napoli and Amsterdam mud volcanoes (MVs) located on the MR and to establish the links between faunal distribution and environmental conditions at different spatial scales. Comparison between the 2 MVs revealed that the faunal distribution seemed to be mainly controlled by the characteristics of the microhabitats. On both geological structures, the variability between the different microhabitats was higher than the variability observed between replicates of the same microhabitat, and the distribution of macro-fauna was apparently linked to gradients in physico-chemical conditions. The peripheral sites from Napoli were generally more oxygenated and harboured lower species richness than the active sites. The reduced sediment microhabitat from Amsterdam presented the highest methane concentrations and was mainly colonised by symbiont-bearing vesicomyid bivalves and heterotrophic dorvilleid polychaetes. Overall, a higher taxonomic diversity was observed on Napoli. Sub-stratum type was hypothesised to be the second factor influencing faunal distribution. The results of this study highlight the high heterogeneity of faunal communities associated with seep ecosystems within this region and the need to pursue investigations at various spatial and temporal scales.
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Numerous ecological problems of continental shelf ecosystems require a refined knowledge of the evolution of suspended sediment concentrations (SSC). The present investigation focuses on the spatial and temporal variabilities of near-surface SSC in coastal waters of the English Channel (western Europe) by exploiting numerical predictions from the Regional Ocean Modeling System ROMS. Extending previous investigations of ROMS performances in the Channel, this analysis refines, with increased spatial and temporal resolutions, the characterization of near-surface SSC patterns revealing areas where concentrations are highly correlated with evolutions of tides and waves. Significant tidal modulations of near-surface concentrations are thus found in the eastern English Channel and the French Dover Strait while a pronounced influence of waves is exhibited in the Channel Islands Gulf. Coastal waters present furthermore strong SSC temporal variations, particularly noticeable during storm events of autumn and winter, with maximum near-surface concentrations exceeding 40 mg l−1 and increase by a factor from 10 to 18 in comparison with time-averaged concentrations. This temporal variability strongly depends on the granulometric distribution of suspended sediments characterized by local bi-modal contributions of silts and sands off coastal irregularities of the Isle of Wight, the Cotentin Peninsula and the southern Dover Strait.