Particle Dynamics Particulate Carbon And The Oxygen Minimum In An Estuary

Profiles of suspended particulate load and its organic and inorganic carbon contents as well as salinity, dissolved oxygen, ammonia and divalent manganese have been recorded throughout the mixing region of the Tamar Estuary,Southwest England, in late summer when there was pronounced net oxygen consumption. The results indicate that trapping of particulate organic detritus (of both riverine and marine origins) within the high turbidity zone contributes to the localisation and buffering of the seasonal oxygen demand exerted within the low salinity region of the estuary.

Population-Dynamics And Production Of Euphausiids .2. Thysanoessa-Inermis And Thysanoessa-Raschi In The North-Sea And American Coastal Waters

Results from the Continuous Plankton Recorder (CPR) survey for 1966 and 1967 are used to describe seasonal changes in abundance, size and aspects of the population structure of Thysanoessa inermis (Krøyer) and T. raschi (M. Sars) at a depth of 10 m in the North Sea and in American coastal waters from the Grand Banks to the Gulf of Maine. Production and dry weight were estimated from these data. Two year-groups were usually present in the breeding population, the proportion surviving into a second year being higher in American waters than in the North Sea. Annual production for each species was within the range 0.69 to 4.66 mg m-3 and the ratio between production and biomass (P:B) was between 1.3 and 4.2; values outside these ranges were obtained only for American coastal waters in 1967, when the frequency of sampling was low.

Defining seasonal marine microbial community dynamics

Here we describe, the longest microbial time-series analyzed to date using high-resolution 16S rRNA tag pyrosequencing of samples taken monthly over 6 years at a temperate marine coastal site off Plymouth, UK. Data treatment effected the estimation of community richness over a 6-year period, whereby 8794 operational taxonomic units (OTUs) were identified using single-linkage preclustering and 21 130 OTUs were identified by denoising the data. The Alphaproteobacteria were the most abundant Class, and the most frequently recorded OTUs were members of the Rickettsiales (SAR 11) and Rhodobacteriales. This near-surface ocean bacterial community showed strong repeatable seasonal patterns, which were defined by winter peaks in diversity across all years. Environmental variables explained far more variation in seasonally predictable bacteria than did data on protists or metazoan biomass. Change in day length alone explains >65% of the variance in community diversity. The results suggested that seasonal changes in environmental variables are more important than trophic interactions. Interestingly, microbial association network analysis showed that correlations in abundance were stronger within bacterial taxa rather than between bacteria and eukaryotes, or between bacteria and environmental variables.

Seasonal dynamics of the carbonate system in the Western English Channel

We present over 900 carbonate system observations collected over four years (2007–2010) in the Western English Channel (WEC). We determined CO2 partial pressure (pCO2), Total Alkalinity (TA) and Dissolved Inorganic Carbon (DIC) along a series of 40 km transects, including two oceanographic stations (L4 and E1) within a sustained coastal observatory. Our data follow a seasonal pattern of CO2 undersaturation from January to August, followed by supersaturation in September–October and a return to near-equilibrium thereafter. This pattern is explained by the interplay of thermal and biological sinks in winter and spring–summer, respectively, followed by the breakdown of stratification and mixing with deeper, high-CO2 water in autumn. The drawdown of DIC and inorganic N between March and June with a C:N ratio of 8.7–9.5 was consistent with carbon over-consumption during phytoplankton growth. Monthly mean surface pCO2 was strongly correlated with depth integrated chlorophyll a highlighting the importance of subsurface chlorophyll a maxima in controlling C-fluxes in shelf seas. Mixing of seawater with riverine freshwater in near-shore samples caused a reduction in TA and the saturation state of calcite minerals, particularly in winter. Our data show that the L4 and E1 oceanographic stations were small, net sinks for atmospheric CO2 over an annual cycle (−0.52±0.66 mol C m−2 y−1 and −0.62±0.49 mol C m−2 y−1, respectively).

Space-borne study of seasonal, multi-year, and decadal phytoplankton dynamics in the Bay of Biscay

Seasonal and inter-annual variations in phytoplankton community abundance in the Bay of Biscay are studied. Preliminarily processed by the National Aeronautics and Space Administration (NASA) to yield normalized water-leaving radiance and the top-of-the-atmosphere solar radiance, Sea-viewing Wide Field-of-View Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS), and Coastal Zone Color Scanner (CZCS) data are further supplied to our dedicated retrieval algorithms to infer the sought for parameters. By applying the National Oceanic and Atmospheric Administration's (NOAA's) Advanced Very High Resolution Radiometer (AVHRR) data, the surface reflection coefficient in the only band in the visible spectrum is derived and employed for analysis. Decadal bridged time series of variations of diatom-dominated phytoplankton and green dinoflagellate Lepidodinium chlorophorum within the shelf zone and the coccolithophore Emiliania huxleyi in the pelagic area of the Bay are documented and analysed in terms of impacts of some biogeochemical and geophysical forcing factors.

Comparative seasonal dynamics of Centropages typicus at seven coastal monitoring stations in the North Sea, English Channel and Bay of Biscay

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.

Seasonal plankton dynamics along a cross-shelf gradient off northern Spain

The development of population models able to reproduce the dynamics of zooplankton is a central issue when trying to understand how a changing environment would affect zooplankton in the future. Using 10 years of monthly data on phytoplankton and zooplankton abundance in the Bay of Biscay from the IEO's RADIALES time-series programme, we built non-parametric Generalized Additive Models (GAMs) able to reproduce the dynamics of plankton on the basis of environmental factors (nutrients, temperature, upwelling and photoperiod). We found that the interaction between these two plankton components is approximately linear, whereas the effects of environmental factors are non-linear. With the inclusion of the environmental variability, the main seasonal and inter-annual dynamic patterns observed within the studied plankton assemblage indicate the prevalence of bottom-up regulatory control. The statistically deduced models were used to simulate the dynamics of the phytoplankton and zooplankton. A good agreement between observations and simulations was obtained, especially for zooplankton. We are presently developing spatio-temporal GAM models for the North Sea based on the Continuous Plankton Recorder database.

How many Coccolithovirus genotypes does it take to terminate an Emiliania huxleyi bloom?

Giant viruses are known to be significant mortality agents of phytoplankton, often being implicated in the terminations of large Emiliania huxleyi blooms. We have previously shown the high temporal variability of E. huxleyi-infecting coccolithoviruses (EhVs) within a Norwegian fjord mesocosm. In the current study we investigated EhV dynamics within a naturally-occurring E. huxleyi bloom in the Western English Channel. Using denaturing gradient gel electrophoresis and marker gene sequencing, we uncovered a spatially highly dynamic Coccolithovirus population that was associated with a genetically stable E. huxleyi population as revealed by the major capsid protein gene (mcp) and coccolith morphology motif (CMM), respectively. Coccolithoviruses within the bloom were found to be variable with depth and unique virus populations were detected at different stations sampled indicating a complex network of EhV-host infections. This ultimately will have significant implications to the internal structure and longevity of ecologically important E. huxleyi blooms.

Impact of zooplankton food selectivity on plankton dynamics and nutrient cycling

Within models, zooplankton grazing is typically defined as being dependent on total prey concentration, with feeding selectivity expressed only as a function of prey size. This behavior ignores taxonomic preferences shown by the preda- tors and the capacity of some zooplankton to actively select or reject individual prey items from mixtures. We carried out two model experiments comparing impacts of zooplankton displaying passive and active selection, which resulted in contrasting dynamics for the pelagic system. Passive selection by the grazer resulted in a top down control on the prey with a fast turn-over of nutrients. Active selection, on the other hand led to a bottom-up control, with slower nutrient turnover constraining primary production by changing the system toward export of particulate matter. Our results suggest that selective feeding behavior is an important trait, and should be considered alongside size and taxonomy when studying the role of zooplankton impact in the ecosystem.

Lateral diffusivity coefficients from the dynamics of a SF6 patch in a coastal environment

The dispersion of a patch of the tracer sulfur hexafluoride (SF6) is used to assess the lateral diffusivity in the coastal waters of the western part of the Gulf of Lion (GoL), northwestern Mediterranean Sea, during the Latex10 experiment (September 2010). Immediately after the release, the spreading of the patch is associated with a strong decrease of the SF6 concentrations due to the gas exchange from the ocean to the atmosphere. This has been accurately quantified, evidencing the impact of the strong wind conditions during the first days of this campaign. Few days after the release, as the atmospheric loss of SF6 decreased, lateral diffusivity coefficient at spatial scales of 10 km has been computed using two approaches. First, the evolution of the patch with time was combined with a diffusion-strain model to obtain estimates of the strain rate (γ = 2.5 10- 6 s- 1) and of the lateral diffusivity coefficient (Kh = 23.2 m2s− 1). Second, a steady state model was applied, showing Kh values similar to the previous method after a period of adjustment between 2 and 4.5 days. This implies that after such period, our computation of Kh becomes insensitive to the inclusion of further straining of the patch. Analysis of sea surface temperature satellite imagery shows the presence of a strong front in the study area. The front clearly affected the dynamics within the region and thus the temporal evolution of the patch. Our results are consistent with previous studies in open ocean and demonstrate the success and feasibility of those methods also under small-scale, rapidly-evolving dynamics typical of coastal environments.

Ecological equivalence of species within phytoplankton functional groups

1.There are tens of thousands of species of phytoplankton found throughout the tree of life. Despite this diversity, phytoplankton are often aggregated into a few functional groups according to metabolic traits or biogeochemical role. We investigate the extent to which phytoplankton species dynamics are neutral within functional groups. 2.Seasonal dynamics in many regions of the ocean are known to affect phytoplankton at the functional group level leading to largely predictable patterns of seasonal succession. It is much more difficult to make general statements about the dynamics of individual species. 3.We use a 7 year time-series at station L4 in the Western English Channel with 57 diatom and 17 dinoflagellate species enumerated weekly to test if the abundance of diatom and dinoflagellate species vary randomly within their functional group envelope or if each species is driven uniquely by external factors. 4.We show that the total biomass of the diatom and dinoflagellate functional groups is well predicted by irradiance and temperature and quantify trait values governing the growth rate of both functional groups. The biomass dynamics of the functional groups are not neutral and each has their own distinct responses to environmental forcing. Compared to dinoflagellates, diatoms have faster growth rates, and grow faster under lower irradiance, cooler temperatures, and higher nutrient conditions. 5.The biomass of most species vary randomly within their functional group biomass envelope, most of the time. As a consequence, modelers will find it difficult to predict the biomass of most individual species. Our analysis supports the approach of using a single set of traits for a functional group and suggests that it should be possible to determine these traits from natural communities.

Spatio-temporal Bayesian network models with latent variables for revealing trophic dynamics and functional networks in fisheries ecology

Ecosystems consist of complex dynamic interactions among species and the environment, the understanding of which has implications for predicting the environmental response to changes in climate and biodiversity. However, with the recent adoption of more explorative tools, like Bayesian networks, in predictive ecology, few assumptions can be made about the data and complex, spatially varying interactions can be recovered from collected field data. In this study, we compare Bayesian network modelling approaches accounting for latent effects to reveal species dynamics for 7 geographically and temporally varied areas within the North Sea. We also apply structure learning techniques to identify functional relationships such as prey–predator between trophic groups of species that vary across space and time. We examine if the use of a general hidden variable can reflect overall changes in the trophic dynamics of each spatial system and whether the inclusion of a specific hidden variable can model unmeasured group of species. The general hidden variable appears to capture changes in the variance of different groups of species biomass. Models that include both general and specific hidden variables resulted in identifying similarity with the underlying food web dynamics and modelling spatial unmeasured effect. We predict the biomass of the trophic groups and find that predictive accuracy varies with the models' features and across the different spatial areas thus proposing a model that allows for spatial autocorrelation and two hidden variables. Our proposed model was able to produce novel insights on this ecosystem's dynamics and ecological interactions mainly because we account for the heterogeneous nature of the driving factors within each area and their changes over time. Our findings demonstrate that accounting for additional sources of variation, by combining structure learning from data and experts' knowledge in the model architecture, has the potential for gaining deeper insights into the structure and stability of ecosystems. Finally, we were able to discover meaningful functional networks that were spatially and temporally differentiated with the particular mechanisms varying from trophic associations through interactions with climate and commercial fisheries.