990 resultados para Importance Sampling


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Atmospheric inputs of mineral dust supply iron and other trace metals to the remote ocean and can influence the marine carbon cycle due to iron's role as a potentially limiting micronutrient. Dust generation, transport, and deposition are highly heterogeneous, and there are very few remote marine locations where dust concentrations and chemistry (e.g., iron solubility) are routinely monitored. Here we use aerosol and rainwater samples collected during 10 large-scale research cruises to estimate the atmospheric input of iron, aluminum, and manganese to four broad regions of the Atlantic Ocean over two 3 month periods for the years 2001–2005. We estimate total inputs of these metals to our study regions to be 4.2, 17, and 0.27 Gmol in April–June and 4.9, 14, and 0.19 Gmol in September–November, respectively. Inputs were highest in regions of high rainfall (the intertropical convergence zone and South Atlantic storm track), and rainfall contributed higher proportions of total input to wetter regions. By combining input estimates for total and soluble metals for these time periods, we calculated overall percentage solubilities for each metal that account for the contributions from both wet and dry depositions and the relative contributions from different aerosol types. Calculated solubilities were in the range 2.4%–9.1% for iron, 6.1%–15% for aluminum, and 54%–73% for manganese. We discuss sources of uncertainty in our estimates and compare our results to some recent estimates of atmospheric iron input to the Atlantic.

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The Continuous Plankton Recorder has been sampling the northeast Pacific on a routine basis since 2000. Although this is a relatively short time series still, climate variability within that time has caused noticeable related changes in the plankton. The earlier part of the time series followed the 1999 La Nina and conditions were cool, but conditions between 2003 and 2005 were anomalously warm. Oceanic zooplankton have responded to this warming in several ways that are discernible in CPR data. The seasonal cycle of mesozooplankton biomass in the eastern Gulf of Alaska has shifted earlier in the spring by a few weeks (sampling resolution is too coarse to be more accurate). The copepod Neocalanus plumchruslflemingeri is largely responsible as it makes up a high proportion of the spring surface biomass and stage-based determinations have shown an earlier maximum in warmer years across much of the northeast Pacific, spanning nearly 20 degrees of latitude. Summer copepod populations are more diverse than in spring, although lower in biomass. The northwards extension of southern taxa in the summer correlates with surface temperature and in warmer years southern taxa are found further north than in cooler years. These findings support the importance of monitoring the open ocean particularly as it is an important foraging ground for large fish, birds and mammals. Higher trophic levels may time their reproduction or migration to coincide with the abundance of particular prey which may be of a different composition and/or lower abundance at a particular time in warmer conditions.

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Phytoplankton abundance in the NW Atlantic was measured by continuous plankton recorder (CPR) sampling along tracks between Iceland and the western Scotian Shelf from 1998 to 2006, when sea-surface chlorophyll (SSChl) measurements were also being made by ocean colour satellite imagery using the SeaWiFS sensor. Seasonal and inter-annual changes in phytoplankton abundance were examined using data collected by both techniques, averaged over each of four shelf regions and four deep ocean regions. CPR sampling had gaps (missing months) in all regions and in the four deep ocean regions satellite observations were too sparse between November and February to be of use. Average seasonal cycles of SSChl were similar to those of total diatom abundance in seven regions, to those of the phytoplankton colour index in six regions, but were not similar to those of total dinoflagellate abundance anywhere. Large inter-annual changes in spring bloom dynamics were captured by both samplers in shelf regions. Changes in annual (or 8 months) averages of SSChl did not generally follow those of the CPR indices within regions and multi-year averages of SSChl, and the three CPR indices were generally higher in shelf than in deep ocean regions. Remote sensing and CPR sampling provide complementary ways of monitoring phytoplankton in the ocean: the former has superior temporal and spatial coverage and temporal resolution, and the latter provides better taxonomic information.

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Evidence for climate-correlated low frequency variability of various components of marine ecosystems has accumulated rapidly over the past 2 decades. There has also been a growing recognition that society needs to learn how the fluctuations of these various components are linked, and to predict the likely amplitude and steepness of future changes. Demographic characteristics of marine zooplankton make them especially suitable for examining variability of marine ecosystems at interannual to decadal time scales. Their life cycle duration is short enough that there is little carryover of population membership from year to year, but long enough that variability can be tracked with monthly-to-seasonal sampling. Because zooplankton are rarely fished, comparative analysis of changes in their abundance can greatly enhance our ability to evaluate the importance of and interaction between physical environment, food web, and fishery harvest as causal mechanisms driving ecosystem level changes. A number of valuable within-region analyses of zooplankton time series have been published in the past decade, covering a variety of modes of variability including changes in total biomass, changes in size structure and species composition, changes in spatial distribution, and changes in seasonal timing. But because most zooplankton time series are relatively short compared to the time scales of interest, the statistical power of local analyses is often low, and between-region and between-variable comparisons are also needed. In this paper, we review the results of recent within- and between-region analyses, and suggest some priorities for future work.

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Zooplankton play a key role in climate change through the transfer of large quantities of CO sub(2) to the deep ocean by a process known as the biological pump. Plankton composition is crucial as associated mineral material facilitates sinking of carbon rich debris and some taxa package faecal and detrital material. Ocean acidification may impact calcareous groups. Zooplankton have also been shown to be highly sensitive indicators of environmental change. Results will be presented to show that ocean temperature, circulation and planktonic ecosystems (using data from the Continuous Plankton Recorder, CPR survey) in the North Atlantic are changing rapidly in concert and that there is evidence to suggest that the changes are an ocean wide response to global warming with potential feedback effects. Given the importance of the oceans to the carbon cycle, even a minor change in the flux of carbon to the deep ocean would have a big impact increasing growth of atmospheric CO sub(2). We have virtually no understanding of the spatial and temporal variability in the efficiency of the biological pump for most of the world's ocean. Establishing new plankton monitoring programmes backed up by appropriate research to help understand processes is needed to address this gap in knowledge. There is little doubt within a global change context and the future of mankind that a potential acceleration in the growth of atmospheric carbon due to a reduction in the efficiency of the biological pump is a key issue for future research in zooplankton ecology.

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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.

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Data on the abundance and biomass of zooplankton off the northwestern Portuguese coast, separately estimated with a Longhurst-Hardy Plankton Recorder (LHPR) and a Bongo net, were analysed to assess the comparative performance of the samplers. Zooplankton was collected along four transects perpendicular to the coast, deployments alternating between samplers. Total zooplankton biomass measured using the LHPR was significantly higher than that using the Bongo net. Apart from Appendicularia and Cladocera, abundances of other taxa (Copepoda, Mysidacea, Euphausiacea, Decapoda larvae, Amphipoda, Siphonophora, Hydromedusae, Chaetognatha and Fish eggs) were also consistently higher in the LHPR. Some of these differences were probably due to avoidance by the zooplankton of the Bongo net. This was supported by a comparative analysis of prosome length of the copepod Calanus helgolandicus sampled by the two nets that showed that Calanus in the LHPR samples were on average significantly larger, particularly in day samples. A ratio estimator was used to produce a factor to convert Bongo net biomass and abundance estimates to equate them with those taken with the LHPR. This method demonstrates how results from complementary zooplankton sampling strategies can be made more equivalent.

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Satellite ocean-colour sensors have life spans lasting typically five-to-ten years. Detection of long-term trends in chlorophyll-a concentration (Chl-a) using satellite ocean colour thus requires the combination of different ocean-colour missions with sufficient overlap to allow for cross-calibration. A further requirement is that the different sensors perform at a sufficient standard to capture seasonal and inter-annual fluctuations in ocean colour. For over eight years, the SeaWiFS, MODIS-Aqua and MERIS ocean-colour sensors operated in parallel. In this paper, we evaluate the temporal consistency in the monthly Chl-a time-series and in monthly inter-annual variations in Chl-a among these three sensors over the 2002–2010 time period. By subsampling the monthly Chl-a data from the three sensors consistently, we found that the Chl-a time-series and Chl-a anomalies among sensors were significantly correlated for >90% of the global ocean. These correlations were also relatively insensitive to the choice of three Chl-a algorithms and two atmospheric-correction algorithms. Furthermore, on the subsampled time-series, correlations between Chl-a and time, and correlations between Chl-a and physical variables (sea-surface temperature and sea-surface height) were not significantly different for >92% of the global ocean. The correlations in Chl-a and physical variables observed for all three sensors also reflect previous theories on coupling between physical processes and phytoplankton biomass. The results support the combining of Chl-a data from SeaWiFS, MODIS-Aqua and MERIS sensors, for use in long-term Chl-a trend analysis, and highlight the importance of accounting for differences in spatial sampling among sensors when combining ocean-colour observations.

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Largely used as a natural biological tag in studies of dispersal/connectivity of fish, otolith elemental fingerprinting is usually analyzed by laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS). LA-ICP-MS produces an elemental fingerprint at a discrete time-point in the life of a fish and can generate data on within-otolith variability of that fingerprint. The presence of within-otolith variability has been previously acknowledged but not incorporated into experimental designs on the presumed, but untested, grounds of both its negligibility compared to among-otolith variability and of spatial autocorrelation among multiple ablations within an otolith. Here, using a hierarchical sampling design of spatial variation at multiple scales in otolith chemical fingerprints for two Mediterranean coastal fishes, we explore: 1) whether multiple ablations within an otolith can be used as independent replicates for significance tests among otoliths, and 2) the implications of incorporating within-otolith variability when assessing spatial variability in otolith chemistry at a hierarchy of spatial scales (different fish, from different sites, at different locations on the Apulian Adriatic coast). We find that multiple ablations along the same daily rings do not necessarily exhibit spatial dependency within the otolith and can be used to estimate residual variability in a hierarchical sampling design. Inclusion of within-otolith measurements reveals that individuals at the same site can show significant variability in elemental uptake. Within-otolith variability examined across the spatial hierarchy identifies differences between the two fish species investigated, and this finding leads to discussion of the potential for within-otolith variability to be used as a marker for fish exposure to stressful conditions. We also demonstrate that a 'cost'-optimal allocation of sampling effort should typically include some level of within-otolith replication in the experimental design. Our findings provide novel evidence to aid the design of future sampling programs and improve our general understanding of the mechanisms regulating elemental fingerprints.