130,673 research outputs found
MEDUSA-2.0: an intermediate complexity biogeochemical model of the marine carbon cycle for climate change and ocean acidification studies
No full textMEDUSA-1.0 (Model of Ecosystem Dynamics, nutrient Utilisation, Sequestration and Acidification) was developed as an "intermediate complexity" plankton ecosystem model to study the biogeochemical response, and especially that of the so-called "biological pump", to anthropogenically driven change in the World Ocean (Yool et al., 2011). The base currency in this model was nitrogen from which fluxes of organic carbon, including export to the deep ocean, were calculated by invoking fixed C:N ratios in phytoplankton, zooplankton and detritus. However, due to anthropogenic activity, the atmospheric concentration of carbon dioxide (CO2) has significantly increased above its natural, inter-glacial background. As such, simulating and predicting the carbon cycle in the ocean in its entirety, including ventilation of CO2 with the atmosphere and the resulting impact of ocean acidification on marine ecosystems, requires that both organic and inorganic carbon be afforded a more complete representation in the model specification. Here, we introduce MEDUSA-2.0, an expanded successor model which includes additional state variables for dissolved inorganic carbon, alkalinity, dissolved oxygen and detritus carbon (permitting variable C:N in exported organic matter), as well as a simple benthic formulation and extended parameterizations of phytoplankton growth, calcification and detritus remineralisation. A full description of MEDUSA-2.0, including its additional functionality, is provided and a multi-decadal spin-up simulation (1860–2005) is performed. The biogeochemical performance of the model is evaluated using a diverse range of observational data, and MEDUSA-2.0 is assessed relative to comparable models using output from the Coupled Model Intercomparison Project (CMIP5)
Climate change and ocean acidification impacts on lower trophic levels and the export of organic carbon to the deep ocean
No full textMost future projections forecast significant and ongoing climate change during the 21st century, but with the severity of impacts dependent on efforts to restrain or reorganise human activity to limit carbon dioxide (CO2) emissions. A major sink for atmospheric CO2, and a key source of biological resources, the World Ocean is widely anticipated to undergo profound physical and – via ocean acidification – chemical changes as direct and indirect results of these emissions. Given strong biophysical coupling, the marine biota is also expected to experience strong changes in response to this anthropogenic forcing. Here we examine the large-scale response of ocean biogeochemistry to climate and acidification impacts during the 21st century for Representative Concentration Pathways (RCPs) 2.6 and 8.5 using an intermediate complexity global ecosystem model, MEDUSA-2.0. The primary impact of future change lies in stratification-led declines in the availability of key nutrients in surface waters, which in turn leads to a global decrease (1990s vs. 2090s) in ocean productivity (?6.3%). This impact has knock-on consequences for the abundance of the low trophic level biogeochemical actors modelled by MEDUSA-2.0 (?5.8%), and these would be expected to similarly impact higher trophic level elements such as fisheries. Related impacts are found in the flux of organic material to seafloor communities (?40.7% at 1000 m), and in the volume of ocean suboxic zones (+12.5%). A sensitivity analysis removing an acidification feedback on calcification finds that change in this process significantly impacts benthic communities, suggesting that a~better understanding of the OA-sensitivity of calcifying organisms, and their role in ballasting sinking organic carbon, may significantly improve forecasting of these ecosystems. For all processes, there is geographical variability in change – for instance, productivity declines ?21% in the Atlantic and increases +59% in the Arctic – and changes are much more pronounced under RCP 8.5 than the RCP 2.6 scenario
NutGEnIE 1.0: nutrient cycle extensions to the cGEnIE Earth system model to examine the long-term influence of nutrients on oceanic primary production
No full textUnderstanding the nuances of the effects of nutrient limitation on oceanic primary production has been the focus of many bioassay experiments by oceanographers. A theme of these investigations is that they identify the currently limiting nutrient at a given location, or in other words they identify the proximate limiting nutrient (PLN). However, the ultimate limiting nutrient (ULN; the nutrient whose supply controls system productivity over extensive timescales) can be different from the PLN. Our motivation is to investigate the identity of the ULN. The ULN constrains oceanic primary production over extensive timescales and consequently overall ocean fertility. The rate of oceanic photosynthesis affects planetary oxygen and carbon dioxide, impacting climate. Understanding past ocean fertility is fundamental to understanding Earth system history and biological evolution.Investigations that have considered the ULN have often utilised box models for example the work of, Tyrrell (1999) and Lenton and Watson (2000). To facilitate investigation of the ULN the carbon-centric Grid Enabled Integrated Earth system model (cGEnIE) nutrient cycles have been extended to create NutGEnIE. NutGEnIE incorporates three open nutrients cycles nitrogen, phosphorus, and iron. The impacts of diazotrophs, capable of fixing nitrogen, are represented alongside those of other phytoplankton. NutGEnIE is capable of extended duration model simulations necessary to investigate the ULN while, at the same time, including iron as a potentially limiting nutrient. NutGEnIE is described here, with particular focus on the biogeochemical cycles of iron, nitrogen and phosphorus. Model results are compared to ocean observational data to assess the degree of realism. Model-data comparisons include physical properties, nutrient concentrations, and process rates (e.g., export and nitrogen fixation). The comparisons of NutGEnIE to ocean observational data are largely positive, suggesting that the dynamics of NutGEnIE are valid. The validations, allied to the ability to run an Earth System model with open nutrients cycles of nitrogen, phosphorus, and iron over extensive time periods supports the proposed use of NutGEnIE to revisit the question of the ULN for oceanic primary production
Mechanistic site-based emulation of a global ocean biogeochemical model (MEDUSA 1.0) for parametric analysis and calibration: an application of the Marine Model Optimization Testbed (MarMOT 1.1)
No full textBiogeochemical ocean circulation models used to investigate the role of plankton ecosystems in global change rely on adjustable parameters to compensate for missing biological complexity. In principle, optimal parameter values can be estimated by fitting models to observational data, including satellite ocean colour products such as chlorophyll that achieve good spatial and temporal coverage of the surface ocean. However, comprehensive parametric analyses require large ensemble experiments that are computationally infeasible with global 3-D simulations. Site-based simulations provide an efficient alternative but can only be used to make reliable inferences about global model performance if robust quantitative descriptions of their relationships with the corresponding 3-D simulations can be established
MeSH term explosion and author rank improve expert recommendations
No full textInformation overload is an often-cited phenomenon that reduces the productivity, efficiency and efficacy of scientists. One challenge for scientists is to find appropriate collaborators in their research. The literature describes various solutions to the problem of expertise location, but most current approaches do not appear to be very suitable for expert recommendations in biomedical research. In this study, we present the development and initial evaluation of a vector space model-based algorithm to calculate researcher similarity using four inputs: 1) MeSH terms of publications; 2) MeSH terms and author rank; 3) exploded MeSH terms; and 4) exploded MeSH terms and author rank. We developed and evaluated the algorithm using a data set of 17,525 authors and their 22,542 papers. On average, our algorithms correctly predicted 2.5 of the top 5/10 coauthors of individual scientists. Exploded MeSH and author rank outperformed all other algorithms in accuracy, followed closely by MeSH and author rank. Our results show that the accuracy of MeSH term-based matching can be enhanced with other metadata such as author rank
EMPOWER-1.0: an Efficient Model of Planktonic ecOsystems WrittEn in R
No full textModelling marine ecosystems requires insight and judgement when it comes to deciding upon appropriate model structure, equations and parameterisation. Many processes are relatively poorly understood and tough decisions must be made as to how to mathematically simplify the real world. Here, we present an efficient plankton modelling testbed, EMPOWER-1.0 (Efficient Model of Planktonic ecOsystems WrittEn in R), coded in the freely available language R. The testbed uses simple two-layer "slab" physics whereby a seasonally varying mixed layer which contains the planktonic marine ecosystem is positioned above a deep layer that contains only nutrient. As such, EMPOWER-1.0 provides a readily available and easy to use tool for evaluating model structure, formulations and parameterisation. The code is transparent and modular such that modifications and changes to model formulation are easily implemented allowing users to investigate and familiarise themselves with the inner workings of their models. It can be used either for preliminary model testing to set the stage for further work, e.g. coupling the ecosystem model to 1-D or 3-D physics, or for undertaking front line research in its own right. EMPOWER-1.0 also serves as an ideal teaching tool. In order to demonstrate the utility of EMPOWER-1.0, we implemented a simple nutrient–phytoplankton–zooplankton–detritus (NPZD) ecosystem model and carried out both a parameter tuning exercise and structural sensitivity analysis. Parameter tuning was demonstrated for four contrasting ocean sites, focusing on station BIOTRANS in the North Atlantic (47° N, 20° W), highlighting both the utility of undertaking a planned sensitivity analysis for this purpose, yet also the subjectivity which nevertheless surrounds the choice of which parameters to tune. Structural sensitivity tests were then performed comparing different equations for calculating daily depth-integrated photosynthesis, as well as mortality terms for both phytoplankton and zooplankton. Regarding the calculation of daily photosynthesis, for example, results indicated that the model was relatively insensitive to the choice of photosynthesis–irradiance curve, but markedly sensitive to the method of calculating light attenuation in the water column. The work highlights the utility of EMPOWER-1.0 as a means of comprehending, diagnosing and formulating equations for the dynamics of marine ecosystems
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Role of epidermal growth factor receptor in feline oral squamous cell carcinoma
No full textFeline oral squamous cell carcinomas (FOSCCs) are locally aggressive
tumours and a common cause of mortality and morbidity. Current treatment
options are rarely successful and animals are frequently euthanised upon
diagnosis due to their grave prognosis. Epidermal Growth Factor Receptor
(EGFR) is a tyrosine kinase receptor which is frequently dysregulated in SCC
of the head and neck (HNSCC) in man. Recent advances in human medicine
have identified EGFR as a therapeutic target in HNSCC.
In this study the role of EGFR in FOSCC was investigated. Sixty seven
biopsy samples were immunohistochemically labelled for EGFR and Ki67, a
proliferation marker. The tyrosine kinase region of feline EGFR was cloned
and sequenced, and six small interfering RNAs (siRNAs) targeting the
tyrosine kinase region were developed. The most effective siRNA as well as
an EGFR specific tyrosine kinase inhibitor, gefitinib, was then used on a
feline SCC cell line (SCCF1), and the effect of EGFR targeting alone, or in
combination with irradiation, on the cell line was determined.
The majority of the biopsy samples were labelled positively for EGFR
and Ki67, and high proliferation corresponded with poor prognosis. The
siRNA caused reduction in EGFR mRNA by Real-Time Polymerase Chain
Reaction and protein levels as assessed by western blot analysis. Reduced
cell proliferation and migration were also observed by proliferation assays
and scratch assays respectively. Combining EGFR knockdown with
irradiation caused an additive effect on the ability of the cell line to form
colonies. These results support the role of EGFR as a potential therapeutic
target in FOSCCs
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