972 resultados para phytoplankton dynamics


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Sustainable management of coastal and coral reef environments requires regular collection of accurate information on recognized ecosystem health indicators. Satellite image data and derived maps of water column and substrate biophysical properties provide an opportunity to develop baseline mapping and monitoring programs for coastal and coral reef ecosystem health indicators. A significant challenge for satellite image data in coastal and coral reef water bodies is the mixture of both clear and turbid waters. A new approach is presented in this paper to enable production of water quality and substrate cover type maps, linked to a field based coastal ecosystem health indicator monitoring program, for use in turbid to clear coastal and coral reef waters. An optimized optical domain method was applied to map selected water quality (Secchi depth, Kd PAR, tripton, CDOM) and substrate cover type (seagrass, algae, sand) parameters. The approach is demonstrated using commercially available Landsat 7 Enhanced Thematic Mapper image data over a coastal embayment exhibiting the range of substrate cover types and water quality conditions commonly found in sub-tropical and tropical coastal environments. Spatially extensive and quantitative maps of selected water quality and substrate cover parameters were produced for the study site. These map products were refined by interactions with management agencies to suit the information requirements of their monitoring and management programs. (c) 2004 Elsevier Ltd. All rights reserved.

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Droughts are climatic phenomena whose frequency has increased in the last decades and also compromised drinkable water supplies in semiarid regions. The lack of rain combined with high evaporation rates promotes a significant reduction of the volume of reservoirs in these regions. Shallower conditions favors nutrients concentration and phytoplankton overgrowth, including potentially toxic cyanobacteria blooming. Therefore, there is a tendency to the intensification of eutrophication in those reservoirs during drought periods. Phytoplankton can respond quickly to environmental conditions related to light and nutrient availability by changes in algal biomass and composition, therefore it is considered a good predictor of environmental variables. Two functional approaches - Reynolds’s Functional Groups (FG) and Kruk’s Morphologically Based Functional Groups (MBFG) - were used to assess which environmental variables were responsible for phytoplankton dynamics, in addition to compare which functional approach explains environmental changes better. This study highlights that the reduction of 90% in the volume of a tropical reservoir of Brazilian semi-arid region, as well as light limitation and nutrient increase, can promote phytoplankton overgrowth. Multivariate analyses using both functional approaches indicated a clear separation between high volumes and low volumes conditions, showing that light and nutrient availability were the main variables that better explained the combination of functional groups. The composition of phytoplankton assemblage changed from species of meso-eutrophic habitats (FG: F and J; MBFG: VI), to organisms of eutrophic and turbid environments (FG: SN and M; MBFG: VIII and VII) during shallower conditions. Both ecological approaches described properly the phytoplankton dynamics according to light and trophic state alterations related to the water volume reduction, therefore they can be considered as equivalent approaches for using in similar environments.

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The Deep Convection cruise repeatedly sampled two locations in the North Atlantic, sited in the Iceland and Norwegian Basins, onboard the RV Meteor (19 March - 2 May 2012). Samples were collected from multiple casts of a conductivity-temperature-depth (CTD) - Niskin rosette at each station. Water samples for primary production rates, community structure, chlorophyll a [Chl a], calcite [PIC], particulate organic carbon [POC] and biogenic silicic acid [BSi] were collected from predawn casts from six light depths (55%, 20%, 14%, 7%, 5% and 1% of incident PAR). Additional samples for community structure and ancillary parameters were collected from a second cast. Carbon fixation rates were determined using the 13C stable isotope method. Water samples for diatom and micro zooplankton counts, collected from the predawn casts, were preserved with acidic Lugol's solution (2% final solution) and counted using an inverted light microscope. Water samples for coccolithophore counts were collected onto cellulose nitrate filters and counted using polarising light microscopy. Water samples for Chl a analysis were filtered onto MF300 and polycarbonate filters and extracted in 90% acetone. PIC and BSi samples were filtered onto polycarbonate filters and analysed using an inductively coupled plasma emission optical spectrometer and a SEAL QuAAtro autoanalyser respectively.

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A moratorium on further bivalve leasing was established in 1999–2000 in Prince Edward Island (Canada). Recently, a marine spatial planning process was initiated explore potential mussel culture expansion in Malpeque Bay. This study focuses on the effects of a projected expansion scenario on productivity of existing leases and available suspended food resources. The aim is to provide a robust scientific assessment using available datasets and three modelling approaches ranging in complexity: (1) a connectivity analysis among culture areas; (2) a scenario analysis of organic seston dynamics based on a simplified biogeochemical model; and (3) a scenario analysis of phytoplankton dynamics based on an ecosystem model. These complementary approaches suggest (1) new leases can affect existing culture both through direct connectivity and through bay-scale effects driven by the overall increase in mussel biomass, and (2) a net reduction of phytoplankton within the bounds of its natural variation in the area.

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How to regulate phytoplankton growth in water supply reservoirs has continued to occupy managers and strategists for some fifty years or so, now, and mathematical models have always featured in their design and operational constraints. In recent years, rather more sophisticated simulation models have begun to be available and these, ideally, purport to provide the manager with improved forecasting of plankton blooms, the likely species and the sort of decision support that might permit management choices to be selected with increased confidence. This account describes the adaptation and application of one such model, PROTECH (Phytoplankton RespOnses To Environmental CHange) to the problems of plankton growth in reservoirs. This article supposes no background knowledge of the main algal types; neither does it attempt to catalogue the problems that their abundance may cause in lakes and reservoirs.

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In total 68 phytoplankton species were identified at the mouth of the Maheshkhali channel with the Bay of Bengal, among them 41 belong to Bacillariophyceae, 17 Dinophyceae, 7 Cyanophyceae and 3 to Chlorophyceae. The highest phytoplankton production was observed in November (578.0 x 105 cells/L) and the lowest in June (37.5 x 105 cells/L). Some hydrographic parameters e.g., surface water temperature, salinity and nutrients (N03-N and P04-P) were recorded and their relationship with the occurrence and abundance of phytoplankton population were also studied. Nutrient concentration was higher during the autumn months, when rain water provided the maximum outflow of rivers discharging into the channel. During the nutrient peak period, the total phytoplankton production was maximum. Bacillariophyceae was the dominant group of phytoplankton throughout the study period except in June and September, when Dinophyceae was dominant. Cyanophyceae was abundant in spring months when temperature began to rise.

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We studied the daily dynamics of nutrients (total phosphorus [TP], total nitrogen [TN], and dissolved silicate [SiO2]) and chlorophyll a (chl a) during a spring bloom in Xiangxi Bay of the Three Gorges Reservoir in year 2005. According to the daily dynamics of chl a, the bloom occurred in two stages (23 February-25 March and 26 March-28 April). The concentration of SiO2 decreased at different layers of the water column with the development of the bloom. However, the decrease of SiO2 in the layers with high concentration of chl a was more dramatic than in the layers with low concentration of chl a. The concentration of TP was lowest value a few days after the peak of chl a during the first bloom period, and the lowest value of TN was found a few days after the peak of chl a during the second bloom period. Correlative analyses indicated that SiO2 and TP were limiting factors in the first bloom period, and SiO2 and TN were limiting factors in the second bloom period.

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Distribution of dimethylsulfide (DMS) and/or particulate dimethylsulfoniopropionate (DMSPp) concentrations in the Jiaozhou Bay, Zhifu Bay and East China Sea were investigated during the period of 1994 - 1998. Both DMS and DMSPp levels showed remarkable temporal and spatial variations. High values occurred in the coastal or shelf waters and low values in the offshore waters. The highest levels were observed in spring or summer and lowest in autumn. DMS or DMSPp distribution patterns were associated with water mass on a large geographical scale, while biological and chemical factors were more likely influential on smaller-scale variations. Diatoms could play an important role in total DMS or DMSPp abundance in coastal waters. Nitrate was found to have a two-phase relationship with DMSPp concentrations: positive when nitrate concentration was lower than 1 mumol/L, and negative when it was above. Anthropogenic factors such as sewage input and aquaculture also showed influences on DMS or DMSPp concentration.

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The composition and distribution of phytoplankton assemblages around the tip of the Antarctic Peninsula were studied during two summer cruises (February/March 2008 and 2009). Water samples were collected for HPLC/CHEMTAX pigment and microscopic analysis. A great spatial variability in chlorophyll a (Chl a) was observed in the study area: highest levels in the vicinity of the James Ross Island (exceeding 7 mg m−3 in 2009), intermediate values (0.5 to 2 mg m−3) in the Bransfield Strait, and low concentrations in the Weddell Sea and Drake Passage (below 0.5 mg m−3). Phytoplankton assemblages were generally dominated by diatoms, especially at coastal stations with high Chl a concentration, where diatom contribution was above 90% of total Chl a. Nanoflagellates, such as cryptophytes and/or Phaeocystis antarctica, replaced diatoms in open-ocean areas (e.g., Weddell Sea). Many species of peridinin-lacking autotrophic dinoflagellates (e.g., Gymnodinium spp.) were also important to total Chl a biomass at well-stratified stations of Bransfield Strait. Generally, water column structure was the most important environmental factor determining phytoplankton communities’ biomass and distribution. The HPLC pigment data also allowed the assessment of different physiological responses of phytoplankton to ambient light variation. The present study provides new insights about the dynamics of phytoplankton in an undersampled region of the Southern Ocean highly susceptible to global climate change.

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Global ocean biogeochemistry models currently employed in climate change projections use highly simplified representations of pelagic food webs. These food webs do not necessarily include critical pathways by which ecosystems interact with ocean biogeochemistry and climate. Here we present a global biogeochemical model which incorporates ecosystem dynamics based on the representation of ten plankton functional types (PFTs); six types of phytoplankton, three types of zooplankton, and heterotrophic bacteria. We improved the representation of zooplankton dynamics in our model through (a) the explicit inclusion of large, slow-growing zooplankton, and (b) the introduction of trophic cascades among the three zooplankton types. We use the model to quantitatively assess the relative roles of iron vs. grazing in determining phytoplankton biomass in the Southern Ocean High Nutrient Low Chlorophyll (HNLC) region during summer. When model simulations do not represent crustacean macrozooplankton grazing, they systematically overestimate Southern Ocean chlorophyll biomass during the summer, even when there was no iron deposition from dust. When model simulations included the developments of the zooplankton component, the simulation of phytoplankton biomass improved and the high chlorophyll summer bias in the Southern Ocean HNLC region largely disappeared. Our model results suggest that the observed low phytoplankton biomass in the Southern Ocean during summer is primarily explained by the dynamics of the Southern Ocean zooplankton community rather than iron limitation. This result has implications for the representation of global biogeochemical cycles in models as zooplankton faecal pellets sink rapidly and partly control the carbon export to the intermediate and deep ocean.