scholarly journals Variations in and environmental controls of primary productivity in the Amundsen Sea

2021 ◽  
Author(s):  
Jianlong Feng ◽  
Delei Li ◽  
Jing Zhang ◽  
Liang Zhao
Keyword(s):  
Primary Production ◽  
Primary Productivity ◽  
Sea Surface ◽  
Iron Nitrate ◽  
Amundsen Sea ◽  
Dissolved Iron ◽  
Environmental Controls ◽  
Long Term Changes ◽  
Temporal And Spatial

Abstract. The Amundsen Sea is one of the regions with the highest primary productivity in the Antarctic. To better understand the role of the Southern Ocean in the global carbon cycle and in climate regulation, a better understanding of the variations in and environmental controls of primary productivity is needed. Using cluster analysis, the Amundsen Sea was divided into nine bioregions. The biophysical differences among bioregions enhanced confidence to identify priorities and regions to study the temporal and spatial variations in primary productivity. Four nearshore bioregions with high net primary productivity or rapidly increasing rates were selected to analyze temporal and spatial variations in primary productivity in the Amundsen Sea. Due to changes in net solar radiation and sea ice, primary production had significant seasonal variation in these four bioregions. The phenology had changed at two bioregions (3 and 5), which has the third and fourth highest primary production, due to changes in the dissolved iron, nitrate, phosphate, and silicate concentrations. Annual primary production showed increasing trends in these four bioregions. The variation in primary production in the bioregion (9), which has the highest primary production, was mainly affected by variations in sea surface temperatures. In the bioregion, which has the second-highest primary production (8), the primary production was significantly positively correlated with sea surface temperature and significantly negatively correlated with sea ice thickness. The long-term changes of primary productivity in bioregions 3 and 5 were thought to be related to changes in the dissolved iron, nitrate, phosphate, and silicate concentrations, and dissolved iron was the limiting factor in these two bioregions. Bioregionalization not only disentangle multiple factors that control the spatial differences, but also disentangle limiting factors that affect the phenology, decadal and long-term changes in primary productivity.

scholarly journals Multiple Evidence for Climate Patterns Influencing Ecosystem Productivity across Spatial Gradients in the Venice Lagoon

2021 ◽  
Vol 9 (4) ◽  
pp. 363
Author(s):  
Camilla Bertolini ◽  
Edouard Royer ◽  
Roberto Pastres
Keyword(s):  
Time Series ◽  
Primary Productivity ◽  
Clustering Analysis ◽  
Venice Lagoon ◽  
Spatial Effects ◽  
Spatial Gradients ◽  
Climate Forecasting ◽  
Oxygen Production Rate ◽  
Temporal And Spatial

Effects of climatic changes in transitional ecosystems are often not linear, with some areas likely experiencing faster or more intense responses, which something important to consider in the perspective of climate forecasting. In this study of the Venice lagoon, time series of the past decade were used, and primary productivity was estimated from hourly oxygen data using a published model. Temporal and spatial patterns of water temperature, salinity and productivity time series were identified by applying clustering analysis. Phytoplankton and nutrient data from long-term surveys were correlated to primary productivity model outputs. pmax, the maximum oxygen production rate in a given day, was found to positively correlate with plankton variables measured in surveys. Clustering analysis showed the occurrence of summer heatwaves in 2008, 2013, 2015 and 2018 and three warm prolonged summers (2012, 2017, 2019) coincided with lower summer pmax values. Spatial effects in terms of temperature were found with segregation between confined and open areas, although the patterns varied from year to year. Production and respiration differences showed that the lagoon, despite seasonality, was overall heterotrophic, with internal water bodies having greater values of heterotrophy. Warm, dry years with high salinity had lower degrees of summer autotrophy.

Long-term assessment of surface dynamics in the Tyrrhenian Sea

2020 ◽  
Author(s):  
Enrico Zambianchi ◽  
Naomi Krauzig ◽  
Pierpaolo Falco
Keyword(s):  
Sea Level ◽  
Spatial Scales ◽  
Sea Surface ◽  
Extreme Weather Events ◽  
Tyrrhenian Sea ◽  
Surface Dynamics ◽  
Surface Circulation ◽  
Spatial Coverage ◽  
Temporal And Spatial

<p>The variability of surface dynamics has been investigated extensively in the Mediterranean Sea for different temporal and spatial coverage, whereas a specific evaluation for the area of the Tyrrhenian Sea does not exist. Thus, this study is focused on the Tyrrhenian basin, a subbasin of the western Mediterranean, which is considered sensitive to climatic variations due to its small size and isolated nature. The main scope is to provide a comprehensive and up-to-date assessment of the sea surface warming, the sea level changes and the general surface circulation in the Tyrrhenian Sea, as well as to improve the understanding of the relation to large-scale teleconnection patterns and to regional air-sea interaction. The long-term spatio-temporal variability and trends were investigated using satellite-derived, in-situ and reanalysis-based datasets up to the end of 2018. Further, the possible linkage with the occurrence of extreme weather events was assessed using observations from the European Severe Weather Database. The different datasets cover multiple temporal and spatial scales and enable the investigation of the potential physical processes related to the non-homogeneous, time-depended spatial variability. The results indicate a significant increase in sea level and sea surface temperature which appears to be linked with the North Atlantic Oscillation (NAO) and the Atlantic Multidecadal Oscillation (AMO), respectively. Moreover, analysis of the basin’s surface circulation together with local air-sea exchanges of heat, freshwater and momentum indicated a significant influence of the wind-driven Ekman pumping variability.</p>

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