Observing and modelling phytoplankton community structure in the North Sea

© Author(s) 2017. CC Attribution 3.0 License. Phytoplankton form the base of the marine food chain, and knowledge of phytoplankton community structure is fundamental when assessing marine biodiversity. Policy makers and other users require information on marine biodiversity and other aspects of the marine environment for the North Sea, a highly productive European shelf sea. This information must come from a combination of observations and models, but currently the coastal ocean is greatly under-sampled for phytoplankton data, and outputs of phytoplankton community structure from models are therefore not yet frequently validated. This study presents a novel set of in situ observations of phytoplankton community structure for the North Sea using accessory pigment analysis. The observations allow a good understanding of the patterns of surface phytoplankton biomass and community structure in the North Sea for the observed months of August 2010 and 2011. Two physical-biogeochemical ocean models, the biogeochemical components of which are different variants of the widely used European Regional Seas Ecosystem Model (ERSEM), were then validated against these and other observations. Both models were a good match for sea surface temperature observations, and a reasonable match for remotely sensed ocean colour observations. However, the two models displayed very different phytoplankton community structures, with one better matching the in situ observations than the other. Nonetheless, both models shared some similarities with the observations in terms of spatial features and inter-annual variability. An initial comparison of the formulations and parameterizations of the two models suggests that diversity between the parameter settings of model phytoplankton functional types, along with formulations which promote a greater sensitivity to changes in light and nutrients, is key to capturing the observed phytoplankton community structure. These findings will help inform future model development, which should be coupled with detailed validation studies, in order to help facilitate the wider application of marine biogeochemical modelling to user and policy needs

Radioactive Iodine Therapy Decreases Recurrence in Thyroid Papillary Microcarcinoma

Background. The most appropriate therapy for papillary microcarcinoma (PMC) is controversial. Methods. We reviewed the therapy and outcome of 407 patients with PMC. Results. Three hundred-eighty patients underwent total thyroidectomy, and 349 patients received I-131 therapy. The median followup was 5.3 years. Forty patients developed recurrent disease. On univariate analysis, development of disease recurrence was correlated with histological tumor size > 0.8 cm (P = 0.0104), age < 45 years (P = 0.043), and no I-131 therapy (P < 0.0001). On multivariate analysis, histological tumor size > 0.8 cm, positive lymph nodes, and no I-131 therapy were significant. The 5-year RFS for patients treated with I-131 was 95.0% versus 78.6% (P < 0.0001) for patients not treated with I-131. Patients with lymph node metastasis who did not receive I-131 had a 5-year RFS of 42.9% versus 93.2% (P < 0.0001) for patients who received I-131. Conclusions. Recommend I-131 remnant ablation for patients with PMC, particularly patients with lymph node metastasis

Stereotactic body radiation therapy for the treatment of early-stage minimally invasive adenocarcinoma or adenocarcnioma in situ (formerly bronchioloalveolar carcinoma): A patterns of failure analysis

INTRODUCTION: Ongoing prospective trials exploring stereotactic body radiation therapy (SBRT) for early stage non-small cell lung cancer (NSCLC) often exclude minimally invasive adenocarcinoma or adenocarcnioma in situ, formerly bronchioloalveolar carcinoma (BAC), due to concerns for accurate target delineation on CT. We performed a patterns of failure analysis to compare outcomes between BAC and other NSCLC subtypes. METHODS: One hundred twenty patients with early stage NSCLC were treated with SBRT from 2004–2009. Pathologic confirmation of NSCLC was obtained in 97 patients. Radiotherapy was delivered according to RTOG guidelines. The log-rank test was used to compare outcomes between BAC and other NSCLC. RESULTS: Median follow-up was 29 months. The median SBRT dose was 5400 cGy. Thirteen patients had radiographically diagnosed BAC and five patients had biopsy confirmed BAC, of which two had both. The three-year local control was 100% for biopsy-proven or radiographically diagnosed BAC (n = 18) and 86% for all other NSCLC subtypes (n = 102) (p = 0.13). Likewise, no significant difference was detected between BAC and other NSCLC for 3-year regional failure (12% vs. 20%, p = 0.45), progression-free survival (57.6% vs. 53.5%, p = 0.84) or overall survival (35% vs. 47%, p = 0.66). There was a trend towards lower three-year rates of freedom from distant failure in patients with any diagnosis of BAC compared to those without (26% vs. 38%, p = 0.053). CONCLUSIONS: Compared to other NSCLC subtypes, BAC appears to have similar patterns of failure and survival after treatment with SBRT, however there may be an increased risk of distant metastases with BAC. RTOG guideline-based target delineation provides encouraging local control rates for patients with BAC

Comprehensive climate system modeling on massively parallel computers

A better understanding of both natural and human induced changes to the Earth`s climate is necessary for policy makers to make informed decisions regarding energy usage and other greenhouse gas producing activities. To achieve this, substantial increases in the sophistication of climate models are required. Coupling between the climate subsystems of the atmosphere, oceans, cryosphere and biosphere is only now beginning to be explored in global models. the enormous computational expenses of such models is one significant factor limiting progress. A comprehensive climate system model targeted to distributed memory massively parallel processing (MPP) computers is under development at Lawrence Livermore National Laboratory. This class of computers promises the computational power to permit the timely execution of climate models of substantially more sophistication than current generation models. Our strategy for achieving high performance on large numbers of processors is to exploit the multiple layers of parallelism naturally contained within highly coupled global climate models. The centerpiece of this strategy is the concurrent execution of multiple independently parallelized components of the climate system model. This methodology allows the assignment of an arbitrary number of processors to each of the major climate subsystems. Hence, a higher total number of processors may be efficiently used. Furthermore, load imbalances arising from the coupling of submodels may be minimized by adjusting the distribution of processors among the submodels

The silent majority: Pico- and nanoplankton as ecosystem health indicators for marine policy

A healthy marine ecosystem is a fully functioning system, able to supply ecosystem services whilst still maintaining resilience to human-induced environmental change. Monitoring and managing the health of resilient marine ecosystems requires indicators that can assess their biodiversity state and food web functioning. Plankton are crucial components of pelagic habitats, occupying the base of the pelagic food web. Larger plankton have long been used to monitor ecosystem productivity and biodiversity due to their identification via traditional light microscopy. In contrast, the regular monitoring of pico- and nanoplankton (<20 µm; hereafter called “tiny plankton”) only started with the development of flow cytometry techniques, which has limited their inclusion as ecosystem health indicators. Four UK plankton surveys have sampled and identified these tiny plankton for up to 14 years, providing an opportunity to test their suitability as indicators of ecosystem state. We investigated six groups of tiny plankton, including heterotrophic nanoeukaryotes, photosynthetic nanoeukaryotes, photosynthetic picoeukaryotes, and Synechococcus cyanobacteria, and two groups of heterotrophic bacteria. Flow cytometry and light microscopy data from an inshore Western English Channel station revealed that 99.98 % of plankton abundance and 71 % of plankton biomass was derived from tiny plankton cells too small to be quantified accurately under a light microscope and thus not adequately considered in assessments of pelagic habitats. Different UK marine and coastal regions showed consistency in peak abundances of these tiny plankton. We used a novel wavelet coherence method to identify time-based relationships between tiny plankton and environmental variables linked to human pressures. Relationships were found between nitrogenous nutrients and all tiny plankton groups, most commonly at sub-annual to annual time scales. Photosynthetic picoeukaryotes, heterotrophic nanoeukaryotes, and HNA-bacteria were associated with high sea surface temperatures. Given the here established relationship between tiny plankton and environmental variables, and their importance in the full plankton assemblage, we recommend that, alongside existing microplankton lifeforms, tiny plankton groups can be used as plankton lifeforms, either individually or in combination, to inform biodiversity indicators that meet policy obligations under the EU Marine Strategy Framework Directive (MSFD), (Oslo-Paris Convention) OSPAR strategies, and the UK Marine Strategy

Optimized plankton imaging, clustering and visualization workflows through integrative data management and application of artificial intelligence

Phytoplankton is a diverse group of photosynthesizing organisms which account for approximately fifty percent of the primary production on Earth. Increasing our knowledge on phytoplankton dynamics (and plankton in general) is therefore of major importance. In the present research, we aimed to reveal the spatiotemporal dynamics of the phyto- and zooplankton community in the Eastern English Channel, Southern Bight of the North Sea and the Thames estuary. To do so, we organized a JERICO-NEXT Lifewatch cruise in May 2017 on board of the RV Simon Stevin and sampled 44 stations, involving five research institutions from France (CNRS-LOG,), The Netherlands (RWS, NIOZ) and Belgium (UGENT, VLIZ). To quantify the biomass of the phytoplankton community we used a unique combination of three flow cytometers and two Fast Repetition Rate Fluorometerss that were coupled to the underway ferrybox system. These observations were complemented with Water Insight Spectrometer and water profile data (by means of a CTD) and samples for zooplankton, pigment and nutrient analysis. A dedicated data workshop was organized with all partners to conduct a joint analysis on both the biotic and abiotic data. A first exploration of the data, by means of regression-based models and multivariate statistics, suggested that mainly nutrient discharges from the rivers influence the plankton structure. Furthermore, water turbidity is controlling photosynthetic activity and horizontal and vertical variations of photosynthetic properties can be discriminated

A multi-component flood risk assessment in the Maresme coast (NW Mediterranean)

Coastal regions are the areas most threatened by natural hazards, with floods being the most frequent and significant threat in terms of their induced impacts, and therefore, any management scheme requires their evaluation. In coastal areas, flooding is a hazard associated with various processes acting at different scales: coastal storms, flash floods, and sea level rise (SLR). In order to address the problem as a whole, this study presents a methodology to undertake a preliminary integrated risk assessment that determines the magnitude of the different flood processes (flash flood, marine storm, SLR) and their associated consequences, taking into account their temporal and spatial scales. The risk is quantified using specific indicators to assess the magnitude of the hazard (for each component) and the consequences in a common scale. This allows for a robust comparison of the spatial risk distribution along the coast in order to identify both the areas at greatest risk and the risk components that have the greatest impact. This methodology is applied on the Maresme coast (NW Mediterranean, Spain), which can be considered representative of developed areas of the Spanish Mediterranean coast. The results obtained characterise this coastline as an area of relatively low overall risk, although some hot spots have been identified with high-risk values, with flash flooding being the principal risk process

Harmful algal blooms and climate change: exploring future distribution changes

Harmful algae can cause death in fish, shellfish, marine mammals, and humans, via their toxins or from effects associated with their sheer quantity. There are many species, which cause a variety of problems around north-west Europe, and the frequency and distribution of algal blooms have altered in the recent past. Species distribution modelling was used to understand how harmful algal species may respond in the future to climate change, by considering environmental preferences and how these may shift. Most distribution studies to date use low resolution global model outputs. In this study, high resolution, downscaled shelf seas climate projections for the north-west European shelf were nested within lower resolution global projections, to understand how the distribution of harmful algae may change by the mid to end of century. Projections suggest that the habitat of most species (defined by temperature, salinity, depth, and stratification) will shift north this century, with suitability increasing in the central and northern North Sea. An increase in occurrence here might lead to more frequent detrimental blooms if wind, irradiance and nutrient levels are also suitable. Prioritizing monitoring of species in these susceptible areas could help in establishing early-warning systems for aquaculture and health protection schemes