Macroscale factors affecting diatom abundance: a synergistic use of Continuous Plankton Recorder and satellite remote sensing data

Diatoms exist in almost every aquatic regime; they are responsible for 20% of global carbon fixation and 25% of global primary production, and are regarded as a key food for copepods, which are subsequently consumed by larger predators such as fish and marine mammals. A decreasing abundance and a vulnerability to climatic change in the North Atlantic Ocean have been reported in the literature. In the present work, a data matrix composed of concurrent satellite remote sensing and Continuous Plankton Recorder (CPR) in situ measurements was collated for the same spatial and temporal coverage in the Northeast Atlantic. Artificial neural networks (ANNs) were applied to recognize and learn the complex non-monotonic and non-linear relationships between diatom abundance and spatiotemporal environmental factors. Because of their ability to mimic non-linear systems, ANNs proved far more effective in modelling the diatom distribution in the marine ecosystem. The results of this study reveal that diatoms have a regular seasonal cycle, with their abundance most strongly influenced by sea surface temperature (SST) and light intensity. The models indicate that extreme positive SSTs decrease diatom abundances regardless of other climatic conditions. These results provide information on the ecology of diatoms that may advance our understanding of the potential response of diatoms to climatic change.

Case history and persistence of the non-indigenous diatom Coscinodiscus wailesii in the north-east Atlantic

The introduction of non-indigenous marine plankton species can have a considerable ecological and economic effect on regional systems. Their presence, however, can go unnoticed until they reach nuisance status and as a consequence few case histories exist containing information on their initial appearance and their spatio-temporal patterns. Here we report on the occurrence of the non-indigenous diatom Coscinodiscus wailesii in 1977 in the English Channel, its subsequent geographical spread into European shelf seas, and its persistence as a significant member of the diatom community in the north-east Atlantic from 1977-1995.

Automated analysis of non-mass-enhancing lesions in breast MRI based on morphological, kinetic, and spatio-temporal moments and joint segmentation-motion compensation technique

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) represents an established method for the detection and diagnosis of breast lesions. While mass-like enhancing lesions can be easily categorized according to the Breast Imaging Reporting and Data System (BI-RADS) MRI lexicon, a majority of diagnostically challenging lesions, the so called non-mass-like enhancing lesions, remain both qualitatively as well as quantitatively difficult to analyze. Thus, the evaluation of kinetic and/or morphological characteristics of non-masses represents a challenging task for an automated analysis and is of crucial importance for advancing current computer-aided diagnosis (CAD) systems. Compared to the well-characterized mass-enhancing lesions, non-masses have no well-defined and blurred tumor borders and a kinetic behavior that is not easily generalizable and thus discriminative for malignant and benign non-masses. To overcome these difficulties and pave the way for novel CAD systems for non-masses, we will evaluate several kinetic and morphological descriptors separately and a novel technique, the Zernike velocity moments, to capture the joint spatio-temporal behavior of these lesions, and additionally consider the impact of non-rigid motion compensation on a correct diagnosis.

Non-linearities, regime shifts and recovery: The recent influence of climate on Black Sea chlorophyll

The Black Sea ecosystem experienced severe eutrophication-related degradation during the 1970s and 1980s. However, in recent years the Black Sea has shown some signs of recovery which are often attributed to a reduction in nutrient loading. Here, SeaWiFS chlorophyll a (chl a), a proxy for phytoplankton biomass, is used to investigate spatio-temporal patterns in Black Sea phytoplankton dynamics and to explore the potential role of climate in the Black Sea's recovery. Maps of chl a anomalies, calculated relative to the 8 year mean, emphasize spatial and temporal variability of phytoplankton biomass in the Black Sea, particularly between the riverine-influenced Northwest Shelf and the open Black Sea. Evolution of phytoplankton biomass has shown significant spatial variability of persistence of optimal bloom conditions between three major regions of the Black Sea. With the exception of 2001, chl a has generally decreased during our 8 year time-series. However, the winter of 2000–2001 was anomalously warm with low wind stress, resulting in reduced vertical mixing of the water column and retention of nutrients in the photic zone. These conditions were associated with anomalously high levels of chl a throughout much of the open Black Sea during the following spring and summer. The unusual climatic conditions occurring in 2001 may have triggered a shift in the Black Sea's chl a regime. The long-term significance of this recent shift is still uncertain but illustrates a non-linear response to climate forcing that makes future ecosystem changes in the pelagic Black Sea ecosystem difficult to predict.

Plankton indicators and ocean observing systems: support to the marine ecosystem state assessment

Ecological indicators are used extensively as tools to manage environmental resources. In the oceans, indicators of plankton can be measured using a variety of observing systems including: mooring stations, ships, autonomous floats and ocean colour remote sensing. Given the broad range of temporal and spatial sampling resolutions of these different observing systems, as well as discrepancies in measurements obtained from different sensors, the estimation and interpretation of plankton indicators can present significant challenges. To provide support to the assessment of the state of the marine ecosystem, we propose a suite of plankton indicators and subsequently classify them in an ecological framework that characterizes key attributes of the ecosystem. We present two case studies dealing with plankton indicators of biomass, size structure and phenology, estimated using the most spatially extensive and longest in situ and remote-sensing observations. Discussion of these studies illustrates how some of the challenges in estimating and interpreting plankton indicators may be addressed by using for example relative measurement thresholds, interpolation procedures and delineation of biogeochemical provinces. We demonstrate that one of the benefits attained, when analyzing a suite of plankton indicators classified in an ecological framework, is the elucidation of non-trivial changes in composition, structure and functioning of the marine ecosystem.