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RADIALES (IEO), with the support of the Korea Institute for Ocean Science and Technology (KIOST) Versión del editor

RADIALES (IEO), with the support of the Korea Institute for Ocean Science and Technology (KIOST)

RADIALES (IEO), with the support of the Korea Institute for Ocean Science and Technology (KIOST)

presentación Marine ecosystem variability shows large fluctuations on a wide variety of scales, from seconds to millennia and from local to global. This limits our ability to observe these systems and to develop good tools to predict how changes in the environment may affect their physical and biological properties. It also limits our ability to differentiate anthropogenic from natural processes. An example is how difficult it is to compare data collected in different sampling locations and at different times. Time series data help resolve both short- and longer-term scales of variability and provide context for traditional process-oriented studies. Time series projects focusing on biogeochemical and ecological observations have yielded important scientific results. They have helped to: (i) evaluate the statistical significance of the ranges of variability of many parameters and environmental variables and biological communities, and (ii) quantify and evaluate the dimension of the interactions between key physical/chemical oceanographic processes and biological rates in plankton communities. As a result, time series are helping estimate warming rates and trends as well as the effects of global change on biota. They have established reference baselines to evaluate the magnitude of environmental perturbations and estimate recovery times on biodiversity and productivity of specific trophic levels. In spite of their scientific value, marine time series are difficult to maintain over time because of costs and availability of trained personnel. Only a few survive beyond a decade. There is great potential in sharing and combining marine data sets from different time series programs from around the world. This allows for comparisons of changes occurring in distant locations, and helps detect changes that occur at broad scales, perhaps even global scales, and to distinguish them from local imbalances or fluctuation. Sharing data can have important economic and social benefits. For instance, efficient use of existing marine data represents a significant cost saving from the 2 billion Euro spent each year now in the EU collecting and accessing to marine data. From the social point of view, the demand from different stakeholders for answers to the challenges posed by changes in the marine environment is growing rapidly. Sharing and accessing time series data would reduce the uncertainties in the management of marine resources and ecosystem services. The UNESCO IOC advocates that: (i) an observation not made today is lost forever, (ii) existing observations are lost if not made accessible, (iii) the collective value of data sets is greater than its dispersed value, and (iv) open access to standardised time series data must be pursued as a common, coordinated international goal. IOC-UNESCO, IEO

Ship-based biogeochemical and ecological time series are one of the most valuable tools to characterize and quantify ocean ecosystems. These programs continuously provided major breakthroughs in understanding ecosystem variability, allow quantification of the ocean carbon cycle, and help understand the processes that link biodiversity, food webs, and changes in services that benefit human societies. A quantum jump in regional and global ocean ecosystem science can be gained by aggregating observations from individual time series that are distributed across different oceans and which are managed by different countries. The collective value of these data is greater than that provided by each time series individually. However, maintaining time series requires a commitment by the science community and sponsor agencies.. Based on the success of existing initiatives, e.g. ICES and SCOR working groups, IOC-UNESCO launched the International Group for Marine Ecological Time Series (IGMETS, http://igmets.net) to promote collaborations across different individual projects, and jointly look at holistic changes within different ocean regions. The effort explores the reasons and connections for changes in phytoplankton and zooplankton at a global level and identifies locations where particularly large changes may be ocurring. This compilation will facilitate better coordination, communication, and data intercomparability among time series. IEO (RADIALES) IOC-UNESCO

Within the framework of the RADIALES time series monitoring program carried out by the Instituto Español de Oceanografía (IEO), 10 stations were monthly sampled for zooplankton biomass, abundance and taxonomic composition. Additionally, hydrographic features and nutrient concentrations were also measured. From the beginning of the program, a total of 2179 zooplankton samples have been collected. The sampling stations are located along four coastal-ocean sections in the Northwest and North Iberian shelf, off Vigo, A Coruña, Gijón and Santander beginning in 1994, 1991, 2001, 1992, respectively. There is classically a contrasted situation between the Galician and the Cantabrian coast. Since the Galician coast represents the northern limit of the Canary upwelling system, coastal upwelling has a major influence on their hydrodynamic behavior and nutrient distributions. In the Cantabrian coast, upwelling is restricted to occasional events during summer and nutrient fertilization depends mostly on the deep convection occurring during winter. In this communication we aim to describe the long-term dynamics of zooplankton biomass for oceanic and shelf waters of the northwest and north Iberian Peninsula focusing in the common period sampled in all the stations (2001-2013, representing 1405 sampling events). We used a method able to cope with the non-stationary nature of the data, namely wavelet analysis. It allows describing the periodic components of the signal as classically obtained with the Fourier analysis. But in addition, the wavelet analysis approach provides information of the variability of the periodic components along the time series. Indeed the principal periodic components (1, 1,5 and 3 years) appear to be transient in both hydrologic and zooplankton biomass series. A pair-wise comparison between the power spectrum matrices of each zooplankton biomass time series allowed us to detect common dynamics between the coastal Cantabrian stations, the oceanic Cantabrian stations and the Galician ones.