36 resultados para Dataset


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Large waves pose risks to ships, offshore structures, coastal infrastructure and ecosystems. This paper analyses 10 years of in-situ measurements of significant wave height (Hs) and maximum wave height (Hmax) from the ocean weather ship Polarfront in the Norwegian Sea. During the period 2000 to 2009, surface elevation was recorded every 0.59 s during sampling periods of 30 min. The Hmax observations scale linearly with Hs on average. A widely-used empirical Weibull distribution is found to estimate average values of Hmax/H s and Hmax better than a Rayleigh distribution, but tends to underestimate both for all but the smallest waves. In this paper we propose a modified Rayleigh distribution which compensates for the heterogeneity of the observed dataset: the distribution is fitted to the whole dataset and improves the estimate of the largest waves. Over the 10-year period, the Weibull distribution approximates the observed Hs and Hmax well, and an exponential function can be used to predict the probability distribution function of the ratio Hmax/Hs. However, the Weibull distribution tends to underestimate the occurrence of extremely large values of Hs and Hmax. The persistence of Hs and Hmax in winter is also examined. Wave fields with Hs > 12 m and Hmax > 16 m do not last longer than 3 h. Low-to-moderate wave heights that persist for more than 12 h dominate the relationship of the wave field with the winter NAO index over 2000–2009. In contrast, the inter-annual variability of wave fields with Hs > 5.5 m or Hmax > 8.5 m and wave fields persisting over ~2.5 days is not associated with the winter NAO index.

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Satellite-derived remote-sensing reflectance (Rrs) can be used for mapping biogeochemically relevant variables, such as the chlorophyll concentration and the Inherent Optical Properties (IOPs) of the water, at global scale for use in climate-change studies. Prior to generating such products, suitable algorithms have to be selected that are appropriate for the purpose. Algorithm selection needs to account for both qualitative and quantitative requirements. In this paper we develop an objective methodology designed to rank the quantitative performance of a suite of bio-optical models. The objective classification is applied using the NASA bio-Optical Marine Algorithm Dataset (NOMAD). Using in situRrs as input to the models, the performance of eleven semi-analytical models, as well as five empirical chlorophyll algorithms and an empirical diffuse attenuation coefficient algorithm, is ranked for spectrally-resolved IOPs, chlorophyll concentration and the diffuse attenuation coefficient at 489 nm. The sensitivity of the objective classification and the uncertainty in the ranking are tested using a Monte-Carlo approach (bootstrapping). Results indicate that the performance of the semi-analytical models varies depending on the product and wavelength of interest. For chlorophyll retrieval, empirical algorithms perform better than semi-analytical models, in general. The performance of these empirical models reflects either their immunity to scale errors or instrument noise in Rrs data, or simply that the data used for model parameterisation were not independent of NOMAD. Nonetheless, uncertainty in the classification suggests that the performance of some semi-analytical algorithms at retrieving chlorophyll is comparable with the empirical algorithms. For phytoplankton absorption at 443 nm, some semi-analytical models also perform with similar accuracy to an empirical model. We discuss the potential biases, limitations and uncertainty in the approach, as well as additional qualitative considerations for algorithm selection for climate-change studies. Our classification has the potential to be routinely implemented, such that the performance of emerging algorithms can be compared with existing algorithms as they become available. In the long-term, such an approach will further aid algorithm development for ocean-colour studies.

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We review current knowledge and understanding of the biology and ecology of Centropages typicus in the European shelf-seas (e.g. North Sea, English Channel and Bay of Biscay). Our study is based on observations at seven coastal time-series stations as well as on the Continuous Plankton Recorder dataset. This paper focuses on the influence of the environmental parameters (e.g. temperature and Chla) on the life cycle and distribution of C typicus and provides a comparison with its congeneric species C. hamatus and C. chierchiae in the study area. Data on abundance, seasonality and egg production have been used to define the temperature and chlorophyll optima for occurrence and reproduction of Centropages spp. within this region of the European shelf-seas. (C) 2007 Elsevier Ltd. All rights reserved.

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Agglomerative cluster analyses encompass many techniques, which have been widely used in various fields of science. In biology, and specifically ecology, datasets are generally highly variable and may contain outliers, which increase the difficulty to identify the number of clusters. Here we present a new criterion to determine statistically the optimal level of partition in a classification tree. The criterion robustness is tested against perturbated data (outliers) using an observation or variable with values randomly generated. The technique, called Random Simulation Test (RST), is tested on (1) the well-known Iris dataset [Fisher, R.A., 1936. The use of multiple measurements in taxonomic problems. Ann. Eugenic. 7, 179–188], (2) simulated data with predetermined numbers of clusters following Milligan and Cooper [Milligan, G.W., Cooper, M.C., 1985. An examination of procedures for determining the number of clusters in a data set. Psychometrika 50, 159–179] and finally (3) is applied on real copepod communities data previously analyzed in Beaugrand et al. [Beaugrand, G., Ibanez, F., Lindley, J.A., Reid, P.C., 2002. Diversity of calanoid copepods in the North Atlantic and adjacent seas: species associations and biogeography. Mar. Ecol. Prog. Ser. 232, 179–195]. The technique is compared to several standard techniques. RST performed generally better than existing algorithms on simulated data and proved to be especially efficient with highly variable datasets.

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Current climate change and overfishing are affecting the productivity and structure of marine ecosystems. This situation is unprecedented for the marine biosphere and it is essential to understand the mechanisms and pathways by which ecosystems respond. We report that climate change and overfishing are likely to be responsible for a rapid restructuring of a highly productive marine ecosystem with effects throughout the pelagos and the benthos. In the mid-1980s, climate change, consequent modifications in the North Sea plankton, and fishing, all reduced North Sea cod recruitment. In this region, production of many benthic species respond positively and immediately to temperature. Analysis of a long-term, spatially extensive biological (plankton and cod) and physical (sea surface temperature) dataset suggests that synchronous changes in cod numbers and sea temperature have established an extensive trophic cascade favoring lower trophic level groups over economic fisheries. A proliferation of jellyfish that we detect may signal the climax of these changes. This modified North Sea ecology may provide a clear indication of the synergistic consequences of coincident climate change and overfishing. The extent of the ecosystem restructuring that has occurred in the North Sea suggests we are unlikely to reverse current climate and human-induced effects through ecosystem resource management in the short term. Rather, we should understand and adapt to new ecological regimes. This implies that fisheries management policies will have to be fully integrated with the ecological consequences of climate change to prevent a similar collapse in an exploited marine ecosystem elsewhere.

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The Continuous Plankton Recorder (CPR) dataset on fish larvae has an extensive spatio-temporal coverage that allows the responses of fish populations to past changes in climate variability, including abrupt changes such as regime shifts, to be investigated. The newly available dataset offers a unique opportunity to investigate long-term changes over decadal scales in the abundance and distribution of fish larvae in relation to physical and biological factors. A principal component analysis (PCA) using 7 biotic and abiotic parameters is applied to investigate the impact of environmental changes in the North Sea on 5 selected taxa of fish larvae during the period 1960 to 2004. The analysis revealed 4 periods of time (1960–1976; 1977–1982; 1983–1996; 1997–2004) reflecting 3 different ecosystem states. The larvae of clupeids, sandeels, dab and gadoids seemed to be affected mainly by changes in the plankton ecosystem, while the larvae of migratory species such as Atlantic mackerel responded more to hydrographic changes. Climate variability seems more likely to influence fish populations through bottom-up control via a cascading effect from changes in the North Atlantic Oscillation (NAO) impacting on the hydro dynamic features of the North Sea, in turn impacting on the plankton available as prey for fish larvae. The responses and adaptability of fish larvae to changing environmental conditions, parti cularly to changes in prey availability, are complex and species-specific. This complexity is enhanced with fishing effects interacting with climate effects and this study supports furthering our under - standing of such interactions before attempting to predict how fish populations respond to climate variability

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Climate effects have been shown to be at least partly responsible for the reorganisation in the plankton ecosystem on the shelf seas of NW Europe over the last 50 years. Most fish larvae feed primarily on zooplankton, so changes in zooplankton quantity, quality and seasonal timing have been hypothesized to be a key factor affecting their survival. To investigate this we have implemented a 1-dimensional trophodynamic growth model of cod larvae for the waters around the UK covering the period 1960 to 2003. Larval growth is modelled as the difference between the amount of food absorbed by the larva and its various metabolic costs. Prey availability is based upon the biomass and size of available preys (i.e. adults and nauplii copepods and cladocerans) taken from the Continuous Plankton Recorder dataset. Temperature and wind forcing are also taken into account. Results suggest that observed changes in plankton community structure may have had less impact than previously suggested. This is because changes in prey availability may be compensated for by increased temperatures resulting in little overall impact on potential larval growth. Stock recovery, at least in the short term is likely to be more dependent upon conserving the year classes recruited to allow spawning stock biomass to rebuild. If as our model suggests, the larvae are still able to survive in the changing environment, reduction in fishing on the adults is needed to allow the stock to recover.

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Changes in phytoplankton dynamics influence marine biogeochemical cycles, climate processes, and food webs, with substantial social and economic consequences. Large-scale estimation of phytoplankton biomass was possible via ocean colour measurements from two remote sensing satellites – the Coastal Zone Color Scanner (CZCS, 1979-1986) and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS, 1998-2010). Due to the large gap between the two satellite eras and differences in sensor characteristics, comparison of the absolute values retrieved from the two instruments remains challenging. Using a unique in situ ocean colour dataset that spans more than half a century, the two satellite-derived chlorophyll-a (Chl-a) eras are linked to assess concurrent changes in phytoplankton variability and bloom timing over the Northeast Atlantic Ocean and North Sea. Results from this unique re-analysis reflect a clear increasing pattern of Chl-a, a merging of the two seasonal phytoplankton blooms producing a longer growing season and higher seasonal biomass, since the mid-1980s. The broader climate plays a key role in Chl-a variability as the ocean colour anomalies parallel the oscillations of the Northern Hemisphere Temperature (NHT) since 1948.

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The assimilation and regeneration of dissolved inorganic nitrogen, and the concentration of N2O, was investigated at stations located in the NW European shelf sea during June/July 2011. These observational measurements within the photic zone demonstrated the simultaneous regeneration and assimilation of NH4+, NO2− and NO3−. NH4+ was assimilated at 1.82–49.12 nmol N L−1 h−1 and regenerated at 3.46–14.60 nmol N L−1 h−1; NO2− was assimilated at 0–2.08 nmol N L−1 h−1 and regenerated at 0.01–1.85 nmol N L−1 h−1; NO3− was assimilated at 0.67–18.75 nmol N L−1 h−1 and regenerated at 0.05–28.97 nmol N L−1 h−1. Observations implied that these processes were closely coupled at the regional scale and nitrogen recycling played an important role in sustaining phytoplankton growth during the summer. The [N2O], measured in water column profiles, was 10.13 ± 1.11 nmol L−1 and did not strongly diverge from atmospheric equilibrium indicating that sampled marine regions where neither a strong source nor sink of N2O to the atmosphere. Multivariate analysis of data describing water column biogeochemistry and its links to N-cycling activity failed to explain the observed variance in rates of N-regeneration and N-assimilation, possibly due to the limited number of process rate observations. In the surface waters of 5 further stations, Ocean Acidification (OA) bioassay experiments were conducted to investigate the response of NH4+ oxidising and regenerating organisms to simulated OA conditions, including the implications for [N2O]. Multivariate analysis was undertaken which considered the complete bioassay dataset of measured variables describing changes in N-regeneration rate, [N2O] and the biogeochemical composition of seawater. While anticipating biogeochemical differences between locations, we aimed to test the hypothesis that the underlying mechanism through which pelagic N-regeneration responded to simulated OA conditions was independent of location and that a mechanistic understanding of how NH4+ oxidation, NH4+ regeneration and N2O production responded to OA could be developed. Results indicated that N-regeneration process responses to OA treatments were location specific; no mechanistic understanding of how N-regeneration processes respond to OA in the surface ocean of the NW European shelf sea could be developed.

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We present an extensive dataset of dimethylsulphide (DMS, n = 651) and dimethylsulphoniopropionate (DMSP, n = 590) from the Atlantic Meridional Transect programme. These data are used to derive representative depth profiles that illustrate observed natural variations and can be used for DMS and DMSP model-validation in oligotrophic waters. To further understand our dataset, we interpret the data with a wide range of accompanying parameters that characterise the prevailing biogeochemical conditions and phytoplankton community physiology, activity, taxonomic composition, and capacity to cope with light stress. No correlations were observed with typical biomarker pigments for DMSP-producing species. However, strong correlations were found between DMSP and primary production by cells >2 µm in diameter, and between DMSP and some photo-protective pigments. These parameters are measures of mixed phytoplankton communities, so we infer that such associations are likely to be stronger in DMSP-producing organisms. Further work is warranted to develop links between community parameters, DMS and DMSP at the global scale.

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Dimethylsulphide (DMS) is a globally important aerosol precurser. In 1987 Charlson and others proposed that an increase in DMS production by certain phytoplankton species in response to a warming climate could stimulate increased aerosol formation, increasing the lower-atmosphere's albedo, and promoting cooling. Despite two decades of research, the global significance of this negative climate feedback remains contentious. It is therefore imperative that schemes are developed and tested, which allow for the realistic incorporation of phytoplankton DMS production into Earth System models. Using these models we can investigate the DMS-climate feedback and reduce uncertainty surrounding projections of future climate. Here we examine two empirical DMS parameterisations within the context of an Earth System model and find them to perform marginally better than the standard DMS climatology at predicting observations from an independent global dataset. We then question whether parameterisations based on our present understanding of DMS production by phytoplankton, and simple enough to incorporate into global climate models, can be shown to enhance the future predictive capacity of those models. This is an important question to ask now, as results from increasingly complex Earth System models lead us into the 5th assessment of climate science by the Intergovernmental Panel on Climate Change. Comparing observed and predicted inter-annual variability, we suggest that future climate projections may underestimate the magnitude of surface ocean DMS change. Unfortunately this conclusion relies on a relatively small dataset, in which observed inter-annual variability may be exaggerated by biases in sample collection. We therefore encourage the observational community to make repeat measurements of sea-surface DMS concentrations an important focus, and highlight areas of apparent high inter-annual variability where sampling might be carried out. Finally, we assess future projections from two similarly valid empirical DMS schemes, and demonstrate contrasting results. We therefore conclude that the use of empirical DMS parameterisations within simulations of future climate should be undertaken only with careful appreciation of the caveats discussed.

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Summary The response to sulfate deficiency of plants and freshwater green algae has been extensively analysed by system biology approaches. By contrast, seawater sulfate concentration is high and very little is known about the sulfur metabolism of marine organisms. Here, we used a combination of metabolite analysis and transcriptomics to analyse the response of the marine microalga Emiliania huxleyi as it acclimated to sulfate limitation. Lowering sulfate availability in artificial seawater from 25 to 5 mM resulted in significant reduction in growth and intracellular concentrations of dimethylsulfoniopropionate and glutathione. Sulfate-limited E. huxleyi cells showed increased sulfate uptake but sulfate reduction to sulfite did not seem to be regulated. Sulfate limitation in E. huxleyi affected expression of 1718 genes. The vast majority of these genes were upregulated, including genes involved in carbohydrate and lipid metabolism, and genes involved in the general stress response. The acclimation response of E. huxleyi to sulfate deficiency shows several similarities to the well-described responses of Arabidopsis and Chlamydomonas, but also has many unique features. This dataset shows that even though E. huxleyi is adapted to constitutively high sulfate concentration, it retains the ability to re-program its gene expression in response to reduced sulfate availability.

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The assimilation and regeneration of dissolved inorganic nitrogen, and the concentration of N2O, was investigated at stations located in the NW European shelf sea during June/July 2011. These observational measurements within the photic zone demonstrated the simultaneous regeneration and assimilation of NH4+, NO2− and NO3−. NH4+ was assimilated at 1.82–49.12 nmol N L−1 h−1 and regenerated at 3.46–14.60 nmol N L−1 h−1; NO2− was assimilated at 0–2.08 nmol N L−1 h−1 and regenerated at 0.01–1.85 nmol N L−1 h−1; NO3− was assimilated at 0.67–18.75 nmol N L−1 h−1 and regenerated at 0.05–28.97 nmol N L−1 h−1. Observations implied that these processes were closely coupled at the regional scale and nitrogen recycling played an important role in sustaining phytoplankton growth during the summer. The [N2O], measured in water column profiles, was 10.13 ± 1.11 nmol L−1 and did not strongly diverge from atmospheric equilibrium indicating that sampled marine regions where neither a strong source nor sink of N2O to the atmosphere. Multivariate analysis of data describing water column biogeochemistry and its links to N-cycling activity failed to explain the observed variance in rates of N-regeneration and N-assimilation, possibly due to the limited number of process rate observations. In the surface waters of 5 further stations, Ocean Acidification (OA) bioassay experiments were conducted to investigate the response of NH4+ oxidising and regenerating organisms to simulated OA conditions, including the implications for [N2O]. Multivariate analysis was undertaken which considered the complete bioassay dataset of measured variables describing changes in N-regeneration rate, [N2O] and the biogeochemical composition of seawater. While anticipating biogeochemical differences between locations, we aimed to test the hypothesis that the underlying mechanism through which pelagic N-regeneration responded to simulated OA conditions was independent of location and that a mechanistic understanding of how NH4+ oxidation, NH4+ regeneration and N2O production responded to OA could be developed. Results indicated that N-regeneration process responses to OA treatments were location specific; no mechanistic understanding of how N-regeneration processes respond to OA in the surface ocean of the NW European shelf sea could be developed.

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A global dataset of in situ particulate absorption spectra has been decomposed into component functions representing absorption by phytoplankton pigments and non-algal particles. The magnitudes of component Gaussian functions, used to represent absorption by individual or groups of pigments, are well correlated with pigment concentrations determined using High Performance Liquid Chromatography. We are able to predict the presence of chlorophylls a,ba,b, and cc, as well as two different groups of summed carotenoid pigments with percent errors between 30% and 57%. Existing methods of analysis of particulate absorption spectra measured in situ provide for only chlorophyll aa; the method presented here, using high spectral resolution particulate absorption, shows the ability to obtain the concentrations of additional pigments, allowing for more detailed studies of phytoplankton ecology than currently possible with in-situ spectroscopy.

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Using the Food and Agriculture Organization’s (FAO) Mediterranean capture fisheries production dataset in conjunction with global and Mediterranean sea surface temperatures, we investigated trends in fisheries landings and landings per unit of effort of commercially important marine organisms, in relation to temperature oscillations. In addition to the overall warming trend, a temperature shift was detected in the Mediterranean Sea in the late 1990s. Fisheries landings fluctuations were examined for the most abundant commercial species (59 species) and showed significant year-to-year correlations with temperature for nearly 60 % of the cases. From these, the majority (~70 %) were negatively related and showed a reduction of 44 % on average. Increasing trends were found, mainly in the landings of species with short life spans, which seem to have benefited from the increase in water temperature. Τhe effect of oceanic warming is apparent in most species or groups of species sharing ecological (e.g. small and medium pelagic, demersal fish) or taxonomic (e.g. cephalopods, crustaceans) traits. A landings-per-unit-of-effort (LPUE) proxy, using data from the seven Mediterranean European Union member states, also showed significant correlation with temperature fluctuations for six out of the eight species examined, indicating the persistence of temperature influence on landings when the fishing effect is accounted for. The speed of response of marine landings to the warming of the Mediterranean Sea possibly shows both the sensitivity and the vulnerable state of the fish stocks and indicates that climate should be examined together with fisheries as a factor shaping stock fluctuations.