983 resultados para Biology, Oceanography


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The Red Sea is a semi-enclosed tropical marine ecosystem that stretches from the Gulf of Suez and Gulf of Aqaba in the north, to the Gulf of Aden in the south. Despite its ecological and economic importance, its biological environment is relatively unexplored. Satellite ocean-colour estimates of chlorophyll concentration (an index of phytoplankton biomass) offer an observational platform to monitor the health of the Red Sea. However, little is known about the optical properties of the region. In this paper, we investigate the optical properties of the Red Sea in the context of satellite ocean-colour estimates of chlorophyll concentration. Making use of a new merged ocean-colour product, from the European Space Agency (ESA) Climate Change Initiative, and in situ data in the region, we test the performance of a series of ocean-colour chlorophyll algorithms. We find that standard algorithms systematically overestimate chlorophyll when compared with the in situ data. To investigate this bias we develop an ocean-colour model for the Red Sea, parameterised to data collected during the Tara Oceans expedition, that estimates remote-sensing reflectance as a function of chlorophyll concentration. We used the Red Sea model to tune the standard chlorophyll algorithms and the overestimation in chlorophyll originally observed was corrected. Results suggest that the overestimation was likely due to an excess of CDOM absorption per unit chlorophyll in the Red Sea when compared with average global conditions. However, we recognise that additional information is required to test the influence of other potential sources of the overestimation, such as aeolian dust, and we discuss uncertainties in the datasets used. We present a series of regional chlorophyll algorithms for the Red Sea, designed for a suite of ocean-colour sensors, that may be used for further testing.

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There is ongoing debate as to whether the oligotrophic ocean is predominantly net autotrophic and acts as a CO2 sink, or net heterotrophic and therefore acts as a CO2 source to the atmosphere. This quantification is challenging, both spatially and temporally, due to the sparseness of measurements. There has been a concerted effort to derive accurate estimates of phytoplankton photosynthesis and primary production from satellite data to fill these gaps; however there have been few satellite estimates of net community production (NCP). In this paper, we compare a number of empirical approaches to estimate NCP from satellite data with in vitro measurements of changes in dissolved O2 concentration at 295 stations in the N and S Atlantic Ocean (including the Antarctic), Greenland and Mediterranean Seas. Algorithms based on power laws between NCP and particulate organic carbon production (POC) derived from 14C uptake tend to overestimate NCP at negative values and underestimate at positive values. An algorithm that includes sea surface temperature (SST) in the power function of NCP and 14C POC has the lowest bias and root-mean square error compared with in vitro measured NCP and is the most accurate algorithm for the Atlantic Ocean. Nearly a 13 year time series of NCP was generated using this algorithm with SeaWiFS data to assess changes over time in different regions and in relation to climate variability. The North Atlantic subtropical and tropical Gyres (NATL) were predominantly net autotrophic from 1998 to 2010 except for boreal autumn/winter, suggesting that the northern hemisphere has remained a net sink for CO2 during this period. The South Atlantic subtropical Gyre (SATL) fluctuated from being net autotrophic in austral spring-summer, to net heterotrophic in austral autumn–winter. Recent decadal trends suggest that the SATL is becoming more of a CO2 source. Over the Atlantic basin, the percentage of satellite pixels with negative NCP was 27%, with the largest contributions from the NATL and SATL during boreal and austral autumn–winter, respectively. Variations in NCP in the northern and southern hemispheres were correlated with climate indices. Negative correlations between NCP and the multivariate ENSO index (MEI) occurred in the SATL, which explained up to 60% of the variability in NCP. Similarly there was a negative correlation between NCP and the North Atlantic Oscillation (NAO) in the Southern Sub-Tropical Convergence Zone (SSTC),which explained 90% of the variability. There were also positive correlations with NAO in the Canary Current Coastal Upwelling (CNRY) and Western Tropical Atlantic (WTRA)which explained 80% and 60% of the variability in each province, respectively. MEI and NAO seem to play a role in modifying phases of net autotrophy and heterotrophy in the Atlantic Ocean.

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The Arctic Ocean is one of the fastest changing oceans, plays an important role in global carbon cycling and yet is a particularly challenging ocean to study. Hence, observations tend to be relatively sparse in both space and time. How the Arctic functions, geophysically, but also ecologically, can have significant consequences for the internal cycling of carbon, and subsequently influence carbon export, atmospheric CO2 uptake and food chain productivity. Here we assess the major carbon pools and associated processes, specifically summarizing the current knowledge of each of these processes in terms of data availability and ranges of rates and values for four geophysical Arctic Ocean domains originally described by Carmack & Wassmann (2006): inflow shelves, which are Pacific-influenced and Atlantic-influenced; interior, river-influenced shelves; and central basins. We attempt to bring together knowledge of the carbon cycle with the ecosystem within each of these different geophysical settings, in order to provide specialist information in a holistic context. We assess the current state of models and how they can be improved and/or used to provide assessments of the current and future functioning when observational data are limited or sparse. In doing so, we highlight potential links in the physical oceanographic regime, primary production and the flow of carbon within the ecosystem that will change in the future. Finally, we are able to highlight priority areas for research, taking a holistic pan-Arctic approach.

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The Arctic Ocean is, on average, the shallowest of Earth’s oceans. Its vast continental shelf areas, which account for approximately half of the Arctic Ocean’s total area, are heavily influenced by the surrounding land masses through river run-off and coastal erosion. As a main area of deep water formation, the Arctic is one of the main «engines» of global ocean circulation, due to large freshwater inputs, it is also strongly stratified. The Arctic Ocean’s complex oceanographic configuration is tightly linked to the atmosphere, the land, and the cryosphere. The physical dynamics not only drive important climate and global circulation patterns, but also control biogeochemical cycles and ecosystem dynamics. Current changes in Arctic sea-ice thickness and distribution, air and water temperatures, and water column stability are resulting in measurable shifts in the properties and functioning of the ocean and its ecosystems. The Arctic Ocean is forecast to shift to a seasonally ice-free ocean resulting in changes to physical, chemical, and biological processes. These include the exchange of gases across the atmosphere-ocean interface, the wind-driven ciruclation and mixing regimes, light and nutrient availability for primary production, food web dynamics, and export of material to the deep ocean. In anticipation of these changes, extending our knowledge of the present Arctic oceanography and these complex changes has never been more urgent.

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Phytoplankton total chlorophyll concentration (TCHLa) and phytoplankton size structure are two important ecological indicators in biological oceanography. Using high performance liquid chromatography (HPLC) pigment data, collected from surface waters along the Atlantic Meridional Transect (AMT), we examine temporal changes in TCHLa and phytoplankton size class (PSC: micro-, nano- and pico-phytoplankton) between 2003 and 2010 (September to November cruises only), in three ecological provinces of the Atlantic Ocean. The HPLC data indicate no significant change in TCHLa in northern and equatorial provinces, and an increase in the southern province. These changes were not significantly different to changes in TCHLa derived using satellite ocean-colour data over the same study period. Despite no change in AMT TCHLa in northern and equatorial provinces, significant differences in PSC were observed, related to changes in key diagnostic pigments (fucoxanthin, peridinin, 19′-hexanoyloxyfucoxanthin and zeaxanthin), with an increase in small cells (nano- and pico-phytoplankton) and a decrease in larger cells (micro-phytoplankton). When fitting a three-component model of phytoplankton size structure — designed to quantify the relationship between PSC and TCHLa to each AMT cruise, model parameters varied over the study period. Changes in the relationship between PSC and TCHLa have wide implications in ecology and marine biogeochemistry, and provide key information for the development and use of empirical ocean-colour algorithms. Results illustrate the importance of maintaining a time-series of in-situ observations in remote regions of the ocean, such as that acquired in the AMT programme.

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This paper reviews research into the potential environmental impacts of leakage from geological storage of CO2 since the publication of the IPCC Special Report on Carbon Dioxide Capture and Storage in 2005. Possible impacts are considered on onshore (including drinking water aquifers) and offshore ecosystems. The review does not consider direct impacts on man or other land animals from elevated atmospheric CO2 levels. Improvements in our understanding of the potential impacts have come directly from CO2 storage research but have also benefitted from studies of ocean acidification and other impacts on aquifers and onshore near surface ecosystems. Research has included observations at natural CO2 sites, laboratory and field experiments and modelling. Studies to date suggest that the impacts from many lower level fault- or well-related leakage scenarios are likely to be limited spatially and temporarily and recovery may be rapid. The effects are often ameliorated by mixing and dispersion of the leakage and by buffering and other reactions; potentially harmful elements have rarely breached drinking water guidelines. Larger releases, with potentially higher impact, would be possible from open wells or major pipeline leaks but these are of lower probability and should be easier and quicker to detect and remediate.

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In a recent letter, Thomsen & Wernberg (2015) rean-alyzed data compiled for our recent paper (Lyonset al., 2014). In that paper, we examined the effectsof macroalgal blooms and macroalgal mats on sevenimportant measures of community structure and eco-system functioning and explored several ecologicaland methodological factors that might explain someof the variation in the observed effects. Thomsen &Wernberg (2015) re-analyzed two small subsets of the data, focusing on experimental studies examining effects of blooms/mats on invertebrate abundance.Their analyses revealed two interesting patterns.First, they showed that macroalgal blooms reducedthe abundance of communities that Thomsen andWernberg categorized as ‘mainly infauna’, whileincreasing the abundance of communities categorized as ‘mainly epifauna’. Second, they showed that theimpacts of macroalgal blooms on ‘mainly infauna’communities increased with algal density in experiments that included multiple levels of algal density.These findings, as well as the conclusions that Thomsen & Wernberg (2015) draw from them, are largely consistent with our own expectations and interpretations. However, we also feel that some caution is required when interpreting the results of their analyses.

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Disentangling the roles of environmental change and natural environmental variability on biologically mediated ecosystem processes is paramount to predict future marine ecosystem functioning. Bioturbation, the biogenic mixing of sediments, has a regulating role in marine biogeochemical processes. However, our understanding of bioturbation as a community level process and of its environmental drivers is still limited by loose use of terminology, and a lack of consensus about what bioturbation is. To help resolve these challenges, this empirical study investigated the links between four different attributes of bioturbation (bioturbation depth, activity and distance, and biodiffusive transport); the ability of an index of bioturbation (BPc) to predict each of them; and their relation to seasonality, in a shallow coastal system – the Western Channel Observatory, UK. Bioturbation distance depended on changes in benthic community structure, while the other three attributes were more directly influenced by seasonality in food availability. In parallel, BPc successfully predicted bioturbation distance but not the other attributes of bioturbation. This study therefore highlights that community bioturbation results from this combination of processes responding to environmental variability at different time-scales. However, community level measurements of bioturbation across environmental variability are still scarce, and BPc is calculated using commonly available data on benthic community structure and the functional classification of invertebrates. Therefore, BPc could be used to support the growth of landscape scale bioturbation research, but future uses of the index need to consider which bioturbation attributes the index actually predicts. As BPc predicts bioturbation distance, estimated here using a random-walk model applicable to community settings, studies using either of the metrics should be directly comparable and contribute to a more integrated future for bioturbation research.

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Phytoplankton size structure is an important indicator of the state of the pelagic ecosystem. Stimulated by the paucity of in situ observations on size structure, and by the sampling advantages of autonomous remote platforms, new efforts are being made to infer the size-structure of the phytoplankton from oceanographic variables that may be measured at high temporal and spatial resolution, such as total chlorophyll concentration. Large-scale analysis of in situ data has revealed coherent relationships between size-fractionated chlorophyll and total chlorophyll that can be quantified using the three-component model of Brewin et al. (2010). However, there are variations surrounding these general relationships. In this paper, we first revise the three-component model using a global dataset of surface phytoplankton pigment measurements. Then, using estimates of the average irradiance in the mixed-layer, we investigate the influence of ambient light on the parameters of the three-component model. We observe significant relationships between model parameters and the average irradiance in the mixed-layer, consistent with ecological knowledge. These relationships are incorporated explicitly into the three-component model to illustrate variations in the relationship between size-structure and total chlorophyll, ensuing from variations in light availability. The new model may be used as a tool to investigate modifications in size-structure in the context of a changing climate.

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Broad-scale patterns in the distribution of deep-sea pelagic species and communities are poorly known. An important question is whether biogeographic boundaries identified from surface features are important in the deep mesopelagic and bathypelagic. We present community analyses of discrete-depth samples of mesozooplankton and micronekton to full-ocean depth collected in the area where the Mid-Atlantic Ridge is crossed by the Subpolar Front. The results show that the distributional discontinuity associated with the front, which is strong near the surface, decreases with increasing depth. Both the frontal separation near the surface and the community convergence at increasing depths were clearer for mesozooplankton than for micronekton.

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Human activity causes ocean acidification (OA) though the dissolution of anthropogenically generated CO2 into seawater, and eutrophication through the addition of inorganic nutrients. Eutrophication increases the phytoplankton biomass that can be supported during a bloom, and the resultant uptake of dissolved inorganic carbon during photosynthesis increases water-column pH (bloom-induced basification). This increased pH can adversely affect plankton growth. With OA, basification commences at a lower pH. Using experimental analyses of the growth of three contrasting phytoplankton under different pH scenarios, coupled with mathematical models describing growth and death as functions of pH and nutrient status, we show how different conditions of pH modify the scope for competitive interactions between phytoplankton species. We then use the models previously configured against experimental data to explore how the commencement of bloom-induced basification at lower pH with OA, and operating against a background of changing patterns in nutrient loads, may modify phytoplankton growth and competition. We conclude that OA and changed nutrient supply into shelf seas with eutrophication or de-eutrophication (the latter owing to pollution control) has clear scope to alter phytoplankton succession, thus affecting future trophic dynamics and impacting both biogeochemical cycling and fisheries.

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The nano- and picoplankton community at Station L4 in the Western English Channel was studied between 2007 and 2013 by flow cytometry to quantify abundance and investigate seasonal cycles within these communities. Nanoplankton included both photosynthetic and heterotrophic eukaryotic single-celled organisms while the picoplankton included picoeukaryote phytoplankton, Synechococcus sp. cyanobacteria and heterotrophic bacteria. A Box–Jenkins Transfer Function climatology analysis of surface data revealed that Synechococcus sp., cryptophytes, and heterotrophic flagellates had bimodal annual cycles. Nanoeukaryotes and both high and low nucleic acid-containing bacteria (HNA and LNA, respectively) groups exhibited unimodal annual cycles. Phaeocystis sp., whilst having clearly defined abundance maxima in spring was not detectable the rest of the year. Coccolithophores exhibited a weak seasonal cycle, with abundance peaks in spring and autumn. Picoeukaryotes did not exhibit a discernable seasonal cycle at the surface. Timings of maximum group abundance varied through the year. Phaeocystis sp. and heterotrophic flagellates peaked in April/May. Nanoeukaryotes and HNA bacteria peaked in June/July and had relatively high abundance throughout the summer. Synechococcus sp., cryptophytes and LNA bacteria all peaked from mid to late September. The transfer function model techniques used represent a useful means of identifying repeating annual cycles in time series data with the added ability to detect trends and harmonic terms at different time scales from months to decades.

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Naturally occurring red tides and harmful algal blooms (HABs) are of increasing importance in the coastal environment and can have dramatic effects on coastal benthic and epipelagic communities worldwide. Such blooms are often unpredictable, irregular or of short duration, and thus determining the underlying driving factors is problematic. The dinoflagellate Karenia mikimotoi is an HAB, commonly found in the western English Channel and thought to be responsible for occasional mass finfish and benthic mortalities. We analysed a 19-year coastal time series of phytoplankton biomass to examine the seasonality and interannual variability of K. mikimotoi in the western English Channel and determine both the primary environmental drivers of these blooms as well as the effects on phytoplankton productivity and oxygen conditions. We observed high variability in timing and magnitude of K. mikimotoi blooms, with abundances reaching >1000 cells mL�1 at 10 m depth, inducing up to a 12-fold increase in the phytoplankton carbon content of the water column. No long-term trends in the timing or magnitude of K. mikimotoi abundance were evident from the data. Key driving factors were identified as persistent summertime rainfall and the resultant input of low-salinity high-nutrient river water. The largest bloom in 2009 was associated with highest annual primary production and led to considerable oxygen depletion at depth, most likely as a result of enhanced biological breakdown of bloom material; however, this oxygen depletion may not affect zooplankton. Our data suggests that K. mikimotoi blooms are not only a key and consistent feature of western English Channel productivity, but importantly can potentially be predicted from knowledge of rainfall or river discharge.

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Primary productivity and subsequent carbon cycling in the coastal zone have a significant impact on the global carbon budget. It is currently unclear how anthropogenic activity could alter these budgets but long term coastal time series of hydrological, biogeochemical and biological measurements represent a key means to better understand past drivers, and hence to predicting future seasonal and inter-annual variability in carbon fixation in coastal ecosystems. An 8-year time series of primary production from 2003 to 2010, estimated using a recently developed absorption-based algorithm, was used to determine the nature and extent of change in primary production at a coastal station (L4) in the Western English Channel (WEC). Analysis of the seasonal and inter-annual variability in production demonstrated that on average, nano- and pico-phytoplankton account for 48% of the total carbon fixation and micro-phytoplankton for 52%. A recent decline in the primary production of nano- and pico-phytoplankton from 2005 to 2010 was observed, corresponding with a decrease in winter nutrient concentrations and a decrease in the biomass of Phaeocystis sp. Micro-phytoplankton primary production (PPM) remained relatively constant over the time series and was enhanced in summer during periods of high precipitation. Increases in sea surface temperature, and decreases in wind speeds and salinity were associated with later spring maxima in PPM. Together these trends indicate that predicted increases in temperature and decrease in wind speeds in future would drive later spring production whilst predicted increases in precipitation would also continue these blooms throughout the summer at this site.