3 resultados para Interaction fluide-structure
em Plymouth Marine Science Electronic Archive (PlyMSEA)
Resumo:
There has been much debate on the extent to which resource availability (bottom-up) versus predation pressure from fish (top-down) modulates the dynamics of plankton in marine systems. Physico/chemical bottom-up forcing has been considered to be the main mechanism structuring marine ecosystems, although some field observations and empirical correlations support top-down modulation. Models have indicated possible feedback loops to the plankton and other studies have interpreted a grazing impact from long-term changes in fish stocks. In freshwater systems, evidence for top-down forcing by fish and trophic cascading is well documented. First, evidence for equivalent top-down effects in the marine environment is presented, with an overview of relevant publications. In the second part, time series, averaged for the North Sea (when possible from 1948 to 1997), of fish catch, recruitment, and spawning stock biomass are related to the abundance of species or larger groupings of zooplankton and phytoplankton from the Continuous Plankton Recorder survey and selected environmental parameters. Preliminary analysis suggests that there is strong interaction between different fish species and the plankton and that the fishery, through top-down control, may at times be an important contributor to changes in the North Sea ecosystem.
Resumo:
Traditionally, marine ecosystem structure was thought to be bottom-up controlled. In recent years, a number of studies have highlighted the importance of top-down regulation. Evidence is accumulating that the type of trophic forcing varies temporally and spatially, and an integrated view – considering the interplay of both types of control – is emerging. Correlations between time series spanning several decades of the abundances of adjacent trophic levels are conventionally used to assess the type of control: bottom-up if positive or top-down if this is negative. This approach implies averaging periods which might show time-varying dynamics and therefore can hide part of this temporal variability. Using spatially referenced plankton information extracted from the Continuous Plankton Recorder, this study addresses the potential dynamic character of the trophic structure at the planktonic level in the North Sea by assessing its variation over both temporal and spatial scales. Our results show that until the early-1970s a bottom-up control characterized the base of the food web across the whole North Sea, with diatoms having a positive and homogeneous effect on zooplankton filter-feeders. Afterwards, different regional trophic dynamics were observed, in particular a negative relationship between total phytoplankton and zooplankton was detected off the west coast of Norway and the Skagerrak as opposed to a positive one in the southern reaches. Our results suggest that after the early 1970s diatoms remained the main food source for zooplankton filter-feeders east of Orkney–Shetland and off Scotland, while in the east, from the Norwegian Trench to the German Bight, filter-feeders were mainly sustained by dinoflagellates.
Resumo:
We examined how marine plankton interaction networks, as inferred by multivariate autoregressive (MAR) analysis of time-series, differ based on data collected at a fixed sampling location (L4 station in the Western English Channel) and four similar time-series prepared by averaging Continuous Plankton Recorder (CPR) datapoints in the region surrounding the fixed station. None of the plankton community structures suggested by the MAR models generated from the CPR datasets were well correlated with the MAR model for L4, but of the four CPR models, the one most closely resembling the L4 model was that for the CPR region nearest to L4. We infer that observation error and spatial variation in plankton community dynamics influenced the model performance for the CPR datasets. A modified MAR framework in which observation error and spatial variation are explicitly incorporated could allow the analysis to better handle the diverse time-series data collected in marine environments.