42 resultados para color changing


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Increasing availability and extent of biological ocean time series (from both in situ and satellite data) have helped reveal significant phenological variability of marine plankton. The extent to which the range of this variability is modified as a result of climate change is of obvious importance. Here we summarize recent research results on phenology of both phytoplankton and zooplankton. We suggest directions to better quantify and monitor future plankton phenology shifts, including (i) examining the main mode of expected future changes (ecological shifts in timing and spatial distribution to accommodate fixed environmental niches vs. evolutionary adaptation of timing controls to maintain fixed biogeography and seasonality), (ii) broader understanding of phenology at the species and community level (e.g. for zooplankton beyond Calanus and for phytoplankton beyond chlorophyll), (iii) improving and diversifying statistical metrics for indexing timing and trophic synchrony and (iv) improved consideration of spatio-temporal scales and the Lagrangian nature of plankton assemblages to separate time from space changes.

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Environmentally induced change appears to be impacting the recruitment of North Sea herring (Clupea harengus). Despite simultaneously having a large adult population, historically low exploitation, and Marine Stewardship Council accreditation (implying sustainability), there have been an unprecedented 6 sequential years of poor juvenile production (recruitment). Analysis suggests that the poor recruitment arises during the larval overwintering phase, with recent survival rates greatly reduced. Contemporary warming of the North Sea has caused significant changes in the plankton community, and a recently identified regime shift around 2000 shows close temporal agreement with the reduced larval survival. It is, therefore, possible that we are observing the first consequences of this planktonic change for higher trophic levels. There is no indication of a recovery in recruitment in the short term. Fishing mortality is currently outside the agreed management plan, and forecasts show a high risk of the stock moving outside safe biological limits soon, potentially precipitating another collapse of the stock. However, bringing the realized fishing mortality back in line with the management plan would likely alleviate the problem. This illustrates again that recruitment is influenced by more than just spawning-stock biomass, and that changes in other factors can be of equal, or even greater, importance. In such dynamically changing environments, recent management success does not necessarily guarantee future sustainability.

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Studies relating biodiversity to ecosystem processes typically do not take into account changes in biodiversity through time. Marine systems are highly dynamic, with biodiversity changing at diel, seasonal and inter-decadal timescales. We examined the dynamics of biodiversity in the Gulf of Maine pelagic zooplankton community. Taxonomic data came from the Gulf of Maine continuous plankton recorder (CPR) transect, spanning the years 1961–2006. The CPR transect also contains coincident information on temperature and phytoplankton biomass (measured by the phytoplankton color index). Taxonomic richness varied at all timescales considered. The relationships between temperature and richness, and between phytoplankton and richness, also depended on temporal scale. The temperature–richness relationship was monotonic at the multi-decadal scale, and tended to be hump-shaped at finer scales; the productivity–richness relationship was hump-shaped at the multi-decadal scale, and tended to be monotonic at finer scales. Seasonal biodiversity dynamics were linked to temperature; inter-decadal biodiversity dynamics were linked to phytoplankton.

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Phytoplankton, at the base of the marine food web, represent a fundamental food source in coral reef ecosystems. The timing (phenology) and magnitude of the phytoplankton biomass are major determinants of trophic interactions. The Red Sea is one of the warmest and most saline basins in the world, characterized by an arid tropical climate regulated by the monsoon. These extreme conditions are particularly challenging for marine life. Phytoplankton phenological indices provide objective and quantitative metrics to characterize phytoplank- ton seasonality. The indices i.e. timings of initiation, peak, termination and duration are estimated here using 15 years (1997–2012) of remote sensing ocean-color data from the European Space Agency (ESA) Climate Change Initiative project (OC-CCI) in the entire Red Sea basin. The OC-CCI product, comprising merged and bias-corrected observations from three independent ocean-color sensors (SeaWiFS, MODIS and MERIS), and processed using the POLYMER algorithm (MERIS period), shows a significant increase in chlorophyll data cover- age, especially in the southern Red Sea during the months of summer NW monsoon. In open and reef-bound coastal waters, the performance of OC-CCI chlorophyll data is shown to be comparable with the performance of other standard chlorophyll products for the global oceans. These features have permitted us to investigate phytoplankton phenology in the entire Red Sea basin, and during both winter SE monsoon and summer NW monsoon periods. The phenological indices are estimated in the four open water provinces of the basin, and further examined at six coral reef complexes of particular socio-economic importance in the Red Sea, including Siyal Islands, Sharm El Sheikh, Al Wajh bank, Thuwal reefs, Al Lith reefs and Farasan Islands. Most of the open and deeper waters of the basin show an apparent higher chlorophyll concentration and longer duration of phyto- plankton growth during the winter period (relative to the summer phytoplankton growth period). In contrast, most of the reef-bound coastal waters display equal or higher peak chlorophyll concentrations and equal or lon- ger duration of phytoplankton growth during the summer period (relative to the winter phytoplankton growth period). The ecological and biological significance of the phytoplankton seasonal characteristics are discussed in context of ecosystem state assessment, and particularly to support further understanding of the structure and functioning of coral reef ecosystems in the Red Sea.

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Biological responses to climate change are typically communicated in generalized terms such as poleward and altitudinal range shifts, but adaptation efforts relevant to management decisions often require forecasts that incorporate the interaction of multiple climatic and nonclimatic stressors at far smaller spatiotemporal scales. We argue that the desire for generalizations has, ironically, contributed to the frequent conflation of weather with climate, even within the scientific community. As a result, current predictions of ecological responses to climate change, and the design of experiments to understand underlying mechanisms, are too often based on broad-scale trends and averages that at a proximate level may have very little to do with the vulnerability of organisms and ecosystems. The creation of biologically relevant metrics of environmental change that incorporate the physical mechanisms by which climate trains patterns of weather, coupled with knowledge of how organisms and ecosystems respond to these changes, can offer insight into which aspects of climate change may be most important to monitor and predict. This approach also has the potential to enhance our ability to communicate impacts of climate change to nonscientists and especially to stakeholders attempting to enact climate change adaptation policies.

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We investigated 32 net primary productivity (NPP) models by assessing skills to reproduce integrated NPP in the Arctic Ocean. The models were provided with two sources each of surface chlorophyll-a concentration (chlorophyll), photosynthetically available radiation (PAR), sea surface temperature (SST), and mixed-layer depth (MLD). The models were most sensitive to uncertainties in surface chlorophyll, generally performing better with in situ chlorophyll than with satellite-derived values. They were much less sensitive to uncertainties in PAR, SST, and MLD, possibly due to relatively narrow ranges of input data and/or relatively little difference between input data sources. Regardless of type or complexity, most of the models were not able to fully reproduce the variability of in situ NPP, whereas some of them exhibited almost no bias (i.e., reproduced the mean of in situ NPP). The models performed relatively well in low-productivity seasons as well as in sea ice-covered/deep-water regions. Depth-resolved models correlated more with in situ NPP than other model types, but had a greater tendency to overestimate mean NPP whereas absorption-based models exhibited the lowest bias associated with weaker correlation. The models performed better when a subsurface chlorophyll-a maximum (SCM) was absent. As a group, the models overestimated mean NPP, however this was partly offset by some models underestimating NPP when a SCM was present. Our study suggests that NPP models need to be carefully tuned for the Arctic Ocean because most of the models performing relatively well were those that used Arctic-relevant parameters.

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Atmospheric sulfur dioxide (SO2) was measured continuously from the Penlee Point Atmospheric Observatory(PPAO) near Plymouth, United Kingdom between May 2014 and November 2015. This coastal site is exposed to marine air across a wide wind sector. The predominant southwesterly winds carry relatively clean background Atlantic air. In contrast, air from the southeast is heavily influenced by exhaust plumes from ships in the English Channel as well as near the Plymouth Sound. New International Maritime Organization (IMO) regulation came into force in January 2015 to reduce sulfur emissions tenfold in Sulfur Emission Control Areas such as the English Channel. Our observations suggest a three-fold reduction from 2014 to 2015 in ship-emitted SO2 from that direction. Apparent fuel sulfur content calculated from coincidental SO2 and carbon dioxide (CO2) peaks from local ship plum es show a high level of compliance to the IMO regulation (> 95 %) in both years. Dimethylsulfide (DMS) is an important source of atmospheric SO2 even in this semi-polluted region. The relative contribution of DMS oxidation to the SO2 burden over the English Channel increased from ~ 1/3 in 2014 to ~ 1/2 in 2015 due to the reduction in ship sulfur emissions. Our diel analysis suggests that SO2 is removed from the marine atmospheric boundary layer in about half a day, with dry deposition to the ocean accounting for a quarter of the total loss.

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Assigning uncertainty to ocean-color satellite products is a requirement to allow informed use of these data. Here, uncertainty estimates are derived using the comparison on a 12th-degree grid of coincident daily records of the remote-sensing reflectance RRS obtained with the same processing chain from three satellite missions, MERIS, MODIS and SeaWiFS. The approach is spatially resolved and produces σ, the part of the RRS uncertainty budget associated with random effects. The global average of σ decreases with wavelength from approximately 0.7– 0.9 10−3 sr−1 at 412 nm to 0.05–0.1 10−3 sr−1 at the red band, with uncertainties on σ evaluated as 20–30% between 412 and 555 nm, and 30–40% at 670 nm. The distribution of σ shows a restricted spatial variability and small variations with season, which makes the multi-annual global distribution of σ an estimate applicable to all retrievals of the considered missions. The comparison of σ with other uncertainty estimates derived from field data or with the support of algorithms provides a consistent picture. When translated in relative terms, and assuming a relatively low bias, the distribution of σ suggests that the objective of a 5% uncertainty is fulfilled between 412 and 490 nm for oligotrophic waters (chlorophyll-a concentration below 0.1 mg m−3). This study also provides comparison statistics. Spectrally, the mean absolute relative difference between RRS from different missions shows a characteristic U-shape with both ends at blue and red wavelengths inversely related to the amplitude of RRS. On average and for the considered data sets, SeaWiFS RRS tend to be slightly higher than MODIS RRS, which in turn appear higher than MERIS RRS. Biases between mission-specific RRS may exhibit a seasonal dependence, particularly in the subtropical belt.