scholarly journals A database of global coastal conditions

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Mariana Castaneda-Guzman ◽  
Gabriel Mantilla-Saltos ◽  
Kris A. Murray ◽  
Robert Settlage ◽  
Luis E. Escobar

AbstractRemote sensing satellite imagery has the potential to monitor and understand dynamic environmental phenomena by retrieving information about Earth’s surface. Marine ecosystems, however, have been studied with less intensity than terrestrial ecosystems due, in part, to data limitations. Data on sea surface temperature (SST) and Chlorophyll-a (Chlo-a) can provide quantitative information of environmental conditions in coastal regions at a high spatial and temporal resolutions. Using the exclusive economic zone of coastal regions as the study area, we compiled monthly and annual statistics of SST and Chlo-a globally for 2003 to 2020. This ready-to-use dataset aims to reduce the computational time and costs for local-, regional-, continental-, and global-level studies of coastal areas. Data may be of interest to researchers in the areas of ecology, oceanography, biogeography, fisheries, and global change. Target applications of the database include environmental monitoring of biodiversity and marine microorganisms, and environmental anomalies.

1992 ◽  
Vol 6 ◽  
pp. 295-295
Author(s):  
Garland R. Upchurch

The Cretaceous rise of flowering plants marked an important transition in the modernization of terrestrial ecosystems. Well documented is the diversification of angiosperm pollen during the mid-Cretaceous and the migration of angiosperms from low latitudes to middle and high latitudes during the Barremian to Cenomanian. Global compilations of “species” diversity indicate a rapid rise in angiosperm diversity during the Albian to Cenomanian. This rise parallels a decline in the species diversity of archaic pteridophytes and the gymnosperm orders Cycadales, Bennettitales, Ginkgoales, Czekanowskiales, and Caytoniales. Late Cretaceous floras show more gradual trends in species diversity than mid-Cretaceous floras.Megafloral reconstructions of vegetation and climate for North America and other continents indicate warm temperatures in coastal regions of middle to high latitudes. Cretaceous biomes, however, often cannot be compared closely with Recent biomes. During much of the Cretaceous, conifers and other gymnosperms shared dominance with angiosperms in tropical and subtropical vegetation, unlike the Recent. During the Late Cretaceous, tropical rainforest was areally restricted. The few known leaf megafloras from equatorial regions indicate subhumid, rather than rainforest, conditions. Desert and semi-desert were widespread at lower latitudes and are documented by the occurrence of evaporite minerals in China, Africa, Spain, Mexico, and South America. Mid-latitude vegetation consisted of open-canopy broadleaved and coniferous evergreen woodlands that existed under subhumid conditions and low seasonality. High-latitude vegetation of the Northern Hemisphere consisted of coniferous and broadleaved deciduous forest, rather than boreal forest and tundra. High-latitude vegetation from coastal regions of the Southern Hemisphere consisted of evergreen conifers and angiosperms. Rainforest conditions appear to have been largely restricted to polar latitudes.Data on relative abundance, though often incomplete, indicate that angiosperms became ecologically important in tropical to warm subtropical broadleaved evergreen forests and woodlands by the Cenomanian. However, their rise to dominance took longer in other biomes. Conifers formed an important component of many Late Cretaceous biomes, and the persistence of archaic gymnosperms was strongly influenced by climate. Deciduous Ginkgoales, Czekanowskiales, Bennettitales, and Caytoniales are rare to absent in Late Cretaceous megafloras from warm subtropical to tropical climates, but they persist in megafloras from cooler climates. Archaic conifers such as Frenelopsis occur in megafloras representing low-latitude desert and semi-desert, but they are generally absent in more humid assemblages. Within mid-latitude broadleaved and coniferous evergreen woodland from North America, conifers show evidence for co-dominance with angiosperms into the early Maastrichtian. However, this co-dominance appears to have ended by latest Maastrichtian, which implies that vegetational reorganization occurred during the last few million years of the Cretaceous in North America.


2002 ◽  
Vol 8 (1) ◽  
pp. 14-45
Author(s):  
Gavan Conlon

Successive governments in the United Kingdom have consistently attempted to increase the skills base by encouraging younger members of society to remain in education, increasing access to higher and further education and by removing barriers to learning later in life. Although there are estimates of the incidence of educational participation2 and the economic rewards achieved by those in possession of formally recognised qualifications, either in terms of labour market outcomes or earnings, little is known about the personal or family characteristics associated with those engaged in learning later in life. There is no formal definition of what exactly late learning refers to, insufficient quantitative information3 relating to the incidence of adult learning, the associated costs and benefits or even whether the type of qualification or the method by which the qualification is undertaken is important. This article makes a provisional attempt to answer some of these questions. The conclusions are not intended to be definitive, but should be seen as a basis for other possible research work. However, some conclusions are clear and unambiguous. Learning undertaken later in life is widespread. Approximately one in three of the hours of education and training received by working-age individuals in the United Kingdom are attributable to those above the age of 25. This figure is substantially higher than the received wisdom in the academic arena. The costs and benefits associated with learning later in life remain difficult to compute due to the data limitations; however, it is illustrated that there is a sizeable penalty in terms of hourly wages and hours worked for late learners. Additional work must be undertaken as superior sources of data become available, as this area of work is currently under-researched. Rather than being at the periphery of education and training policy in the United Kingdom, late learning should continue to be seen as an important pillar within the general attempt to build the knowledge base within the United Kingdom.


2017 ◽  
Vol 2017 ◽  
pp. 1-16 ◽  
Author(s):  
Marcos Paulo Santos Pereira ◽  
Marcos Heil Costa ◽  
Flavio Justino ◽  
Ana Cláudia Mendes Malhado

Global warming in the first half of the 21st century is likely to have profound influences on South American vegetation and climate. Although coupled atmosphere-biosphere models have been widely used to forecast future vegetation patterns under various scenarios of global warming, they have not been used to assess the potentially critical role of variations in sea surface temperature (SST) in modifying the climate-vegetation interactions. Here, we use monthly output of a 100-year coupled model run to investigate the relationship between SST, precipitation, and productivity of vegetation. Specifically, we assess statistical correlations between SST variability and vegetation in six different South America regions: Northern South America, Western Amazonia, Eastern Amazonia, Northeast Brazil, Central Brazil, and Patagonia. Our model robustly simulates changes in mean precipitation, net primary production (NPP), upper canopy leaf area index (LAI), and lower canopy LAI under warming and nonwarming scenarios. Most significantly, we demonstrate that spatial-temporal variability in SST exerts a strong influence over the vegetation dynamics in all six South American regions.


2020 ◽  
Vol 12 (22) ◽  
pp. 3742
Author(s):  
Eun-Young Lee ◽  
Kyung-Ae Park

Validation of daily Optimum Interpolation Sea Surface Temperature (OISST) data from 1982 to 2018 was performed by comparison with quality-controlled in situ water temperature data from Korea Meteorological Administration moored buoys and Korea Oceanographic Data Center observations in the coastal regions around the Korean Peninsula. In contrast to the relatively high accuracy of the SSTs in the open ocean, the SSTs of the coastal regions exhibited large root-mean-square errors (RMSE) ranging from 0.75 K to 1.99 K and a bias ranging from −0.51 K to 1.27 K, which tended to be amplified towards the coastal lines. The coastal SSTs in the Yellow Sea presented much higher RMSE and bias due to the appearance of cold water on the surface induced by vigorous tidal mixing over shallow bathymetry. The long-term trends of OISSTs were also compared with those of in situ water temperatures over decades. Although the trends of OISSTs deviated from those of in situ temperatures in coastal regions, the spatial patterns of the OISST trends revealed a similar structure to those of in situ temperature trends. The trends of SSTs using satellite data explained about 99% of the trends in in situ temperatures in offshore regions (>25 km from the shoreline). This study discusses the limitations and potential of global SSTs as well as long-term SST trends, especially in Korean coastal regions, considering diverse applications of satellite SSTs and increasing vulnerability to climate change.


2007 ◽  
Vol 24 (4) ◽  
pp. 681-687 ◽  
Author(s):  
Zijun Gan ◽  
Youfang Yan ◽  
Yiquan Qi

Abstract Based on the data of optimum interpolation sea surface temperature (OISST), the temporal correlations of the sea surface temperature anomaly (SSTA) in the South China Sea (SCS) are studied by using the rescaled range analysis (R/S) and detrended fluctuation analysis (DFA). The results show that the scaling exponents of SSTAs are larger than 0.8. This finding indicates that the SSTAs in the SCS exhibit persistent long-range time correlation of the fluctuations and the interval spreads over a wide period, from about 1 month to 4.5 yr (4∼235 weeks). In addition, the “degree” of the correlations depends very much on the geographic locations: near to the coastal regions, the value is small, while far from the coastline, the value is relatively larger. This means that SSTAs in the central SCS are smoother than those of the coastal regions. The persistence of SST in the SCS may be used as a “minimum skill” to assess the ocean models and to evaluate their performance.


2001 ◽  
Vol 1 (1) ◽  
pp. 167-192 ◽  
Author(s):  
H. W. Bange ◽  
M. O. Andreae ◽  
S. Lal ◽  
C. S. Law ◽  
S. W. A. Naqvi ◽  
...  

Abstract. We computed high-resolution (1o latitude × 1o longitude) seasonal and annual nitrous oxide (N2O) concentration fields for the Arabian Sea surface layer using a database containing more than 2400 values measured between December 1977 and July 1997. N2O concentrations are highest during the southwest (SW) monsoon along the southern Indian continental shelf. Annual emissions range from 0.33 to 0.70 Tg N2O and are dominated by fluxes from coastal regions during the SW and northeast monsoons. However, the tendency to focus on measurements in locally restricted features in combination with insufficient seasonal data coverage leads to considerable uncertainties of the concentration fields and thus in the flux estimates, especially in the coastal zones of the northern and eastern Arabian Sea.


2019 ◽  
Author(s):  
Tomás Sherwen ◽  
Rosie J. Chance ◽  
Liselotte Tinel ◽  
Daniel Ellis ◽  
Mat J. Evans ◽  
...  

Abstract. Iodide in the sea-surface plays an important role in the Earth system. It modulates the oxidising capacity of the troposphere and provides iodine to terrestrial ecosystems. However, our understanding of its distribution is limited due to a paucity of observations. Previous efforts to generate global distributions have generally fitted sea-surface iodide observations to relatively simple functions of sea-surface temperature (Chance et al., 2014; MacDonald et al., 2014). This approach fails to account for coastal influences and variation in the bio-geochemical environment. Here we use a machine learning regression approach (Random Forest Regression) to generate a high resolution (0.125° x 0.125°, ∼ 12.5 km), monthly dataset of present-day global sea-surface iodide. We use a compilation of iodide observations (Chance et al., 2019b) that is 45 % larger than has been used previously (Chance et al., 2014) as the dependent variable and co-located ancillary parameters (temperature, nitrate, phosphate, salinity, shortwave radiation, topographic depth, mixed layer depth, and chlorophyll-a) from global climatologies as the independent variables. We investigate the regression models generated using different combinations of ancillary parameters and select the ten best-performing models to be included in an ensemble prediction. We then use this ensemble of models, combined with global fields of the ancillary parameters, to predict a new high resolution global sea-surface iodide field. Sea-surface temperature is the most important variable in all of the top ten models. We estimate a global average sea-surface iodide concentration of 106 nM (with an uncertainty of ∼ 20 %), which is within the range of previous estimates (60–130 nM). Similar to previous work, higher concentrations are predicted for the tropics than for the extra-tropics. Unlike the previous parameterisations, higher concentrations are also predicted for shallow areas such as coastal regions and the South China Sea. Compared to previous work, the new parameterisation better captures observed variability. The iodide concentrations calculated here are significantly higher (40 % on a global basis) than the commonly used MacDonald et al. (2014) parameterisation, with implications for our understanding of iodine in the atmosphere. The global iodide dataset is made freely available to the community (DOI: https://doi.org/10/gfv5v3) and as new observations are made, we will update the global dataset through a "living data" model.


PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11112
Author(s):  
Clara Jégousse ◽  
Pauline Vannier ◽  
René Groben ◽  
Frank Oliver Glöckner ◽  
Viggó Marteinsson

Marine microorganisms contribute to the health of the global ocean by supporting the marine food web and regulating biogeochemical cycles. Assessing marine microbial diversity is a crucial step towards understanding the global ocean. The waters surrounding Iceland are a complex environment where relatively warm salty waters from the Atlantic cool down and sink down to the deep. Microbial studies in this area have focused on photosynthetic micro- and nanoplankton mainly using microscopy and chlorophyll measurements. However, the diversity and function of the bacterial and archaeal picoplankton remains unknown. Here, we used a co-assembly approach supported by a marine mock community to reconstruct metagenome-assembled genomes (MAGs) from 31 metagenomes from the sea surface and seafloor of four oceanographic sampling stations sampled between 2015 and 2018. The resulting 219 MAGs include 191 bacterial, 26 archaeal and two eukaryotic MAGs to bridge the gap in our current knowledge of the global marine microbiome.


Ocean Science ◽  
2022 ◽  
Vol 18 (1) ◽  
pp. 67-88
Author(s):  
Alizée Roobaert ◽  
Laure Resplandy ◽  
Goulven G. Laruelle ◽  
Enhui Liao ◽  
Pierre Regnier

Abstract. The temporal variability of the sea surface partial pressure of CO2 (pCO2) and the underlying processes driving this variability are poorly understood in the coastal ocean. In this study, we tailor an existing method that quantifies the effects of thermal changes, biological activity, ocean circulation and freshwater fluxes to examine seasonal pCO2 changes in highly variable coastal environments. We first use the Modular Ocean Model version 6 (MOM6) and biogeochemical module Carbon Ocean Biogeochemistry And Lower Trophics version 2 (COBALTv2) at a half-degree resolution to simulate coastal CO2 dynamics and evaluate them against pCO2 from the Surface Ocean CO2 Atlas database (SOCAT) and from the continuous coastal pCO2 product generated from SOCAT by a two-step neuronal network interpolation method (coastal Self-Organizing Map Feed-Forward neural Network SOM-FFN, Laruelle et al., 2017). The MOM6-COBALT model reproduces the observed spatiotemporal variability not only in pCO2 but also in sea surface temperature, salinity and nutrients in most coastal environments, except in a few specific regions such as marginal seas. Based on this evaluation, we identify coastal regions of “high” and “medium” agreement between model and coastal SOM-FFN where the drivers of coastal pCO2 seasonal changes can be examined with reasonable confidence. Second, we apply our decomposition method in three contrasted coastal regions: an eastern (US East Coast) and a western (the Californian Current) boundary current and a polar coastal region (the Norwegian Basin). Results show that differences in pCO2 seasonality in the three regions are controlled by the balance between ocean circulation and biological and thermal changes. Circulation controls the pCO2 seasonality in the Californian Current; biological activity controls pCO2 in the Norwegian Basin; and the interplay between biological processes and thermal and circulation changes is key on the US East Coast. The refined approach presented here allows the attribution of pCO2 changes with small residual biases in the coastal ocean, allowing for future work on the mechanisms controlling coastal air–sea CO2 exchanges and how they are likely to be affected by future changes in sea surface temperature, hydrodynamics and biological dynamics.


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