968 resultados para Longitudinal Data Analysis and Time Series
Resumo:
This work is based on a long time series of data collected in the well-preserved Bay of Calvi (Corsica island, Ligurian Sea, NW Mediterranean) between 1979 and 2011, which include physical characteristics (31 years), chlorophyll a (chl a, 15 years), and inorganic nutrients (13 years). Because samples were collected at relatively high frequencies, which ranged from daily to biweekly during the winter-spring period, it was possible to (1) evidence the key role of two interacting physical variables, i.e. water temperature and wind intensity, on nutrient replenishment and phytoplankton dynamics during the winter-spring period, (2) determine critical values of physical factors that explained interannual variability in the replenishment of surface nutrients and the winter-spring phytoplankton bloom, and (3) identify previously unrecognized characteristics of the planktonic ecosystem. Over the >30 year observation period, the main driver of nutrient replenishment and phytoplankton (chl a) development was the number of wind events (mean daily wind speed >5 m s-1) during the cold-water period (subsurface water <13.5°C). According to winter intensity, there were strong differences in both the duration and intensity of nutrient fertilization and phytoplankton blooms (chl a). The trophic character of the Bay of Calvi changed according to years, and ranged from very oligotrophic (i.e. subtropical regime, characterized by low seasonal variability) to mesotrophic (i.e. temperate regime, with a well-marked increase in nutrient concentrations and chl a during the winter-spring period) during mild and moderate winters, respectively. A third regime occurred during severe winters characterized by specific wind conditions (i.e. high frequency of northeasterly winds), when Mediterranean "high nutrient - low chlorophyll" conditions occurred as a result of enhanced crossshore exchanges and associated offshore export of the nutrient-rich water. There was no long-term trend (e.g. climatic) in either nutrient replenishment or the winter-spring phytoplankton bloom between 1979 and 2011, but both nutrients and chl a reflected interannual and decadal changes in winter intensity.
Resumo:
Time series length-frequency data are presented for Themisto amphipods collected as swimmers by moored sediment traps since 2000 at the AWI deep-sea observatory HAUSGARTEN (79°N/4°E) in the eastern Fram Strait. Amphipod occurrences increased significantly from 2000 to 2009 at 200-300 m depth, and the North Atlantic species Themisto compressa was continuously present in the samples starting in 2004. We present year-round records of large adult Themisto amphipods, including the appearance of Themisto libellula with a total body length of up to 56.7 mm and juveniles starting from 4.0 mm. The length of Themisto abyssorum ranged from 4.2 to 25.6 mm, whereas it varied for Themisto compressa from 8.8 to 24.4 mm. Length-frequency analysis indicated a life span of 2 years for T. abyssorum and at least 3 years for T. libellula. The absence of juveniles for T. compressa suggested its reproduction in southern subarctic areas and its occasional northward migration with warmer Atlantic water into the eastern Fram Strait. The seasonal and long-term size structures of the three pelagic species were consistent over the course of the study, indicating no changes occurred in cohort development due to increasing abundances or warming water temperatures.
Resumo:
Ongoing zooplankton research at the Plymouth Marine Laboratory has established a time series of zooplankton species since 1988 at L4, a coastal station off Plymouth. Samples were collected by vertical net hauls (WP2 net, mesh 200 µm; UNESCO 1968) from the sea floor (approximately 50 m) to the surface and stored in 4% formalin. Much of the zooplankton analysis has been to the level of "major taxonomic groups" only, and a number of different analysts have participated over the years. The level of expertise has generally been consistent, but the user should be aware that levels of taxonomic discrimination may vary during the course of the dataset. The dominant calanoid copepods are generally well discriminated to species throughout. Calanus has not been routinely examined for species determination, the assumption being that the local population is entirely composed of Calanus helgolandicus. In certain years there has been a particular interest in Temora stylifera, Centropages cherchiae and other species reflected in the dataset. The lack of records in other previous years does not necessarily reflect species absence. We view it as essential for all users of L4 plankton data to establish and maintain contact with the nominated current data originators as well as fully consulting the metadata. While not impinging on free data access, this ensures that this large, species-rich but slightly complex species database is being used in the correct way, and any potential issues with the data are clarified. Furthermore, a proper dialogue with these local experts on the time series will enable where appropriate the most recent sampling timepoints to be used. The data can be downloaded from BODC or from doi:10.1594/PANGAEA.778092 as files for each year by searching for "L4 zooplankton". The most comprehensive dataset is the version downloadable directly from this page. The entire set of zooplankton samples is stored at the Plymouth Marine Laboratory in buffered formalin, and may be available for further taxonomic analysis on request.
Resumo:
The analysis of time-dependent data is an important problem in many application domains, and interactive visualization of time-series data can help in understanding patterns in large time series data. Many effective approaches already exist for visual analysis of univariate time series supporting tasks such as assessment of data quality, detection of outliers, or identification of periodically or frequently occurring patterns. However, much fewer approaches exist which support multivariate time series. The existence of multiple values per time stamp makes the analysis task per se harder, and existing visualization techniques often do not scale well. We introduce an approach for visual analysis of large multivariate time-dependent data, based on the idea of projecting multivariate measurements to a 2D display, visualizing the time dimension by trajectories. We use visual data aggregation metaphors based on grouping of similar data elements to scale with multivariate time series. Aggregation procedures can either be based on statistical properties of the data or on data clustering routines. Appropriately defined user controls allow to navigate and explore the data and interactively steer the parameters of the data aggregation to enhance data analysis. We present an implementation of our approach and apply it on a comprehensive data set from the field of earth bservation, demonstrating the applicability and usefulness of our approach.