958 resultados para Coastal plains


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Phosphonates are organic compounds that contain a C-P bond and are a poorly characterized component of the marine phosphorus cycle. They may represent a potential source of bioavailable phosphorus, particularly in oligotrophic conditions. This study has investigated the distribution of the phnA gene which encodes phosphonoacetate hydrolase, the enzyme that mineralizes phosphonoacetate. Using newly designed degenerate primers targeting the phnA gene we analysed the potential for phosphonoacetate utilization in DNA and cDNA libraries constructed from a phytoplankton bloom in the Western English Channel during July 2006. Total RNA was isolated and reverse transcribed and phosphonoacetate hydrolase (phnA) transcripts were PCR amplified from the cDNA with the degenerate primers, cloned and sequenced. Phylogenetic analysis demonstrated considerable diversity with 14 sequence types yielding five unique phnA protein groups. We also identified 28 phnA homologues in a 454-pyrosequencing metagenomic and metatranscriptomic study from a coastal marine mesocosm, indicating that > 3% of marine bacteria in this study contained phnA. phnA homologues were also present in a metagenomic fosmid library from this experiment. Finally, cultures of four isolates of potential coral pathogens belonging to the Vibrionaceae contained the phnA gene. In the laboratory, these isolates were able to grow with phosphonoacetate as sole P and C source. The fact that the capacity to utilize phosphonoacetate was evident in each of the three coastal environments suggests the potential for widespread utilization of this bioavailable P source.

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Survival, growth, above ground biomass accumulation, soil surface elevation dynamics and nitrogen accumulation in accreted sediments were studied in experimental treatments planted with four different densities (6.96, 3.26, 1.93 and 0.95 seedlings m-2) of the mangrove Rhizophora mucronata in Puttalam Lagoon, Sri Lanka. Measurements were taken over a period of 1171 days and were compared with those from unplanted controls. Trees at the lowest density showed significantly reduced survival, whilst measures of individual tree growth did not differ significantly among treatments. Rates of surface sediment accretion (means ± S.E.) were 13.0 (±1.3), 10.5 (±0.9), 8.4 (±0.3), 6.9 (±0.5) and 5.7 (±0.3) mm yr-1 at planting densities of 6.96, 3.26, 1.93, 0.95, and 0 (unplanted control) seedlings m-2, respectively, showing highly significant differences among treatments. Mean (± S.E.) rates of surface elevation change were much lower than rates of accretion at 2.8 (±0.2), 1.6 (±0.1), 1.1 (±0.2), 0.6 (±0.2) and -0.3 (±0.1) mm yr-1 for 6.96, 3.26, 1.93, 0.95, and 0 seedlings m-2, respectively. All planted treatments appeared to accumulate greater nitrogen concentrations in the sediment compared to the unplanted control, and suggests one potential causal mechanism for the facilitatory effects observed; high densities of plants potentially contribute to the accretion of greater amounts of nutrient rich sediment. While this potential process needs further study, this study demonstrated how higher densities of mangroves enhance rates of sediment accretion and surface elevation, processes that may be crucial in mangrove ecosystem adaptation to sea level rise. There was no evidence that increasing plant density evoked a trade-off with growth and survival of the planted trees. Rather facilitatory effects enhanced survival at high densities, suggesting that local land managers may be able to take advantage of plantation densities to help mitigate sea-level rise effects by encouraging positive soil surface elevation increment, and perhaps even greater nutrient retention to promote mangrove growth and ameliorate nearshore eutrophication in tropical island environments.

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This study assessed nearshore, marine ecosystem function around Trinidad and Tobago (TT). The coastline of TT is highly complex, bordered by the Atlantic Ocean, the Caribbean Sea, the Gulf of Paria and the Columbus Channel, and subject to local terrestrial runoff and regional riverine inputs (e.g. the Orinoco and Amazon rivers). Coastal organisms can assimilate energy from allochthonous and autochthonous Sources, We assessed whether stable isotopes delta C-13 and delta N-15 Could be used to provide a rapid assessment of trophic interactions in primary consumers around the islands. Filter-feeding (bivalves and barnacles) and grazing organisms (gastropods and chitons) were collected from 40 marine sites during the wet season. The flesh of organisms was analysed for delta C-13 and delta N-15. Results indicate significant variation in primary consumers (by feeding guild and sampling zone). This variation was linked to different energy Sources being assimilated by consumers. Results suggest that offshore production is fuelling intertidal foodwebs; for example, a depleted delta C-13 signature in grazers from the Gulf of Paria, Columbus Channel and the Caribbean and Atlantic coastline of 9 Tobago indicates that carbon with an offshore origin (e.g. phytoplankton and dissolved organic matter) is more important than benthic or littoral algae (luring the wet season. Results also confirm findings from other studies indicating that much of the coastline is subject to Cultural eutrophication. This Study revealed that ecosystem function is spatially variable around the coastline of TT, This has clear implications for marine resource management, as a single management approach is unlikely to be successful at a national level.

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An oceanic cruise (October 2007) revealed the widespread occurrence of Pelagia noctiluca in the NE Atlantic just prior to a major fish kill induced by P. noctiluca in Irish coastal waters.

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Jellyfish (medusae) are sometimes the most noticeable and abundant members of coastal planktonic communities, yet ironically, this high conspicuousness is not reflected in our overall understanding of their spatial distributions across large expanses of water. Here, we set out to elucidate the spatial (and temporal) patterns for five jellyfish species (Phylum Cnidaria, Orders Rhizostomeae and Semaeostomeae) across the Irish & Celtic Seas, an extensive shelf-sea area at Europe's northwesterly margin encompassing several thousand square kilometers. Data were gathered using two independent methods: (1) surface-counts of jellyfish from ships of opportunity, and (2) regular shoreline surveys for stranding events over three consecutive years. Jellyfish species displayed distinct species-specific distributions, with an apparent segregation of some species. Furthermore, a different species composition was noticeable between the northern and southern parts of the study area. Most importantly, our data suggests that jellyfish distributions broadly reflect the major hydrographic regimes (and associated physical discontinuities) of the study area, with mixed water masses possibly acting as a trophic barrier or non-favourable environment for the successful growth and reproduction of jellyfish species.

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Leatherback turtles (Dermochelys coriacea) are obligate predators of gelatinous zooplankton. However, the spatial relationship between predator and prey remains poorly understood beyond sporadic and localized reports. To examine how jellyfish (Phylum Cnidaria: Orders Semaeostomeae and Rhizostomeae) might drive the broad-scale distribution of this wide ranging species, we employed aerial surveys to map jellyfish throughout a temperate coastal shelf area bordering the northeast Atlantic. Previously unknown, consistent aggregations of Rhizostoma octopus extending over tens of square kilometers were identified in distinct coastal

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The validation of variable-density flow models simulating seawater intrusion in coastal aquifers requires information about concentration distribution in groundwater. Electrical resistivity tomography (ERT) provides relevant data for this purpose. However, inverse modeling is not accurate because of the non-uniqueness of solutions. Such difficulties in evaluating seawater intrusion can be overcome by coupling geophysical data and groundwater modeling. First, the resistivity distribution obtained by inverse geo-electrical modeling is established. Second, a 3-D variable-density flow hydrogeological model is developed. Third, using Archie's Law, the electrical resistivity model deduced from salt concentration is compared to the formerly interpreted electrical model. Finally, aside from that usual comparison-validation, the theoretical geophysical response of concentrations simulated with the groundwater model can be compared to field-measured resistivity data. This constitutes a cross-validation of both the inverse geo-electrical model and the groundwater model.
[Comte, J.-C., and O. Banton (2007), Cross-validation of geo-electrical and hydrogeological models to evaluate seawater intrusion in coastal aquifers, Geophys. Res. Lett., 34, L10402, doi:10.1029/2007GL029981.]

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The long-term morphodynamic ordering of gravel-dominated coastal systems (GDCS), many of which serve as coastal defences in northwest Europe, is dominated by extreme events that generate barrier crest overflow. An understanding of this morphodynamic ordering is fraught with several unresolved difficulties. These are related to the twin problems of the inadequacy of pertinent morphodynamic parameterisation and of obtaining data from modern shores enabling such parameterisation. Major uncertainties concern the timing of over-crest flow in terms of return period of extreme elevation; the intensity and structure of the overflow field; antecedent beachface characteristics in response to storms; the rate of relative sea-level change; tidal stage control; and barrier resistance to forcing, itself determined by a number of unknowns including barrier form and size, sediment size and mosaics, and barrier resilience. While generalised extreme value modelling may provide a means of characterising overwashing return-period and its variability, exceptional tsunami events are outside the scope of such modelling. The characterisation of GDCS morphodynamics in terms of the forcing extreme events will necessitate integrating some or all of these parameters into a single model.