A systematic study of zooplankton-based indices of marine ecological change and water quality: Application to the European marine strategy framework Directive (MSFD)

Marine zooplankton are central components of holistic ecosystem assessments due to their intermediary role in the food chain, linking the base of the food chain with higher trophic levels. As a result, these organisms incorporate the inherent properties and changes occurring atall levels of the marine ecosystem, temporally integrating signatures of physical and chemical conditions. For this reason, zooplankton-based biometrics are widely accepted as useful tools for assessing and monitoring the ecological health and integrity of aquatic systems. The European Marine Strategy Framework Directive (EU-MSFD) requires the use of different types of bio-monitors, including zooplankton, to monitor progress towards achieving specific environmental and water quality targets in EU. However, there is currently no comprehensive synthesis of zooplankton indices development, use, and associated challenges. We addressed this issue with a two-step approach. First, we formulated the indicator-metrics-indices cycle (IMIC) to redefine the closely related but often ambiguously utilized terms - indicator, metric and index, highlighting the convergence between them and the iterative nature of their interaction. Secondly, we formulated frameworks for synthesizing, presenting and systematically applying zooplankton indices based on the IMIC framework. The main benefits of the IMIC are twofold: 1). to disambiguate the key elements: indicators, metrics, and indices, revealing their links to an operational ecological indicator system, and 2) to serve as an organizing tool for the coherent classification of indices according to the MSFD descriptors. Using the IMIC framework, we identified and described two broad categories of indices namely the core biodiversity indices already in use in the Baltic Sea and North Atlantic regions, including the ‘Zooplankton Mean Size and Total Stock (zooplankton MSTS)’ and 'Plankton Lifeforms index (PLI)', and stressor-response indices retrieved from the existing literature, elucidating their applicability to different MSFD descriptors. Finally, major challenges of developing new indices and applying existing ones in the context of the MSFD were critically addressed and some solutions were proposed

100-years-changes in the phytoplankton community of Kiel Bight (Baltic Sea)

Literature data from 1905/06, 1912/13 and 1949/50 were compared with recent data (2001-2003) from Kiel Bight in order to investigate changes in phytoplankton composition and biomass, which may serve as indicators of environmental changes. In terms of biomass, diatomophyceae and dinophyceae are by far the most important groups. Their ratio is still close to unity. The share of diatomophyceae increased strongly in years with exceptionally high summer blooms (2001) or exceptionally early spring blooms (2003). The summer and autumn blooms of Chaetoceros and Skeletonema, detected in the early 20th century, are replaced by other diatoms (Cerataulina pelagica, Dactyliosolen fragilissimus, Proboscia alata, Pseudo-nitzschia spp.). Chaetoceros and Skeletonema are still important components of the spring blooms. Now as before, the autumn blooms are dominated by Ceratium spp., sometimes also by diatoms. Newly appearing bloom-forming species are mostly potentially toxic (Dicryocha speculum, Prorocentrum minimum, Pseudo-nitzschia spp.). The total phytoplankton biomass has roughly doubled in the course of the last century. The reference condition for phytoplankton biomass in Kiel Bight in the sense of the Water Framework Directive was defined at 55 mg C m(-3) (+/- 10%, annual mean). The mean annual biomass of diatomophyceae and dinophyceae was 25 mg C m-3 (+/- 40%) for each, indicating that the sum of their carbon biomass amounted to 90% (+/- 10%) of the total phytoplankton biomass on an annual average. Diatomophyceae represented at least 80% of carbon biomass in the spring bloom peak at the beginning of the 20th centur

Genetic analysis for a shared biological basis between migraine and coronary artery disease

OBJECTIVE: To apply genetic analysis of genome-wide association data to study the extent and nature of a shared biological basis between migraine and coronary artery disease (CAD). METHODS: Four separate methods for cross-phenotype genetic analysis were applied on data from 2 large-scale genome-wide association studies of migraine (19,981 cases, 56,667 controls) and CAD (21,076 cases, 63,014 controls). The first 2 methods quantified the extent of overlapping risk variants and assessed the load of CAD risk loci in migraineurs. Genomic regions of shared risk were then identified by analysis of covariance patterns between the 2 phenotypes and by querying known genome-wide significant loci. RESULTS: We found a significant overlap of genetic risk loci for migraine and CAD. When stratified by migraine subtype, this was limited to migraine without aura, and the overlap was protective in that patients with migraine had a lower load of CAD risk alleles than controls. Genes indicated by 16 shared risk loci point to mechanisms with potential roles in migraine pathogenesis and CAD, including endothelial dysfunction (PHACTR1) and insulin homeostasis (GIP). CONCLUSIONS: The results suggest that shared biological processes contribute to risk of migraine and CAD, but surprisingly this commonality is restricted to migraine without aura and the impact is in opposite directions. Understanding the mechanisms underlying these processes and their opposite relationship to migraine and CAD may improve our understanding of both disorders

Genetic analysis for a shared biological basis between migraine and coronary artery disease

OBJECTIVE: To apply genetic analysis of genome-wide association data to study the extent and nature of a shared biological basis between migraine and coronary artery disease (CAD). METHODS: Four separate methods for cross-phenotype genetic analysis were applied on data from 2 large-scale genome-wide association studies of migraine (19,981 cases, 56,667 controls) and CAD (21,076 cases, 63,014 controls). The first 2 methods quantified the extent of overlapping risk variants and assessed the load of CAD risk loci in migraineurs. Genomic regions of shared risk were then identified by analysis of covariance patterns between the 2 phenotypes and by querying known genome-wide significant loci. RESULTS: We found a significant overlap of genetic risk loci for migraine and CAD. When stratified by migraine subtype, this was limited to migraine without aura, and the overlap was protective in that patients with migraine had a lower load of CAD risk alleles than controls. Genes indicated by 16 shared risk loci point to mechanisms with potential roles in migraine pathogenesis and CAD, including endothelial dysfunction (PHACTR1) and insulin homeostasis (GIP). CONCLUSIONS: The results suggest that shared biological processes contribute to risk of migraine and CAD, but surprisingly this commonality is restricted to migraine without aura and the impact is in opposite directions. Understanding the mechanisms underlying these processes and their opposite relationship to migraine and CAD may improve our understanding of both disorders