scholarly journals Variability‐based constraint on ocean primary production models

Author(s):  
B. B. Cael
Oceanology ◽  
2016 ◽  
Vol 56 (6) ◽  
pp. 799-808
Author(s):  
A. B. Demidov ◽  
S. V. Sheberstov ◽  
S. V. Vazyulya ◽  
V. A. Artemiev ◽  
S. A. Mosharov ◽  
...  

2008 ◽  
Vol 28 (10-11) ◽  
pp. 1340-1351 ◽  
Author(s):  
Kimberly J.W. Hyde ◽  
John E. O’Reilly ◽  
Candace A. Oviatt

2003 ◽  
Vol 15 (1) ◽  
pp. 77-84 ◽  
Author(s):  
R. BARBINI ◽  
F. COLAO ◽  
R. FANTONI ◽  
L. FIORANI ◽  
A. PALUCCI ◽  
...  

The Southern Ocean plays an important role in the global carbon cycle and, as a consequence, in the planetary climate equilibrium. The Ross Sea is one of the more productive regions in the Southern Ocean, due to strong phytoplankton blooms occurring during summer. Satellite remote sensing is a powerful tool for investigating such phenomena, especially if the bio-optical algorithms are tuned with in situ data. In this paper, after having compared the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and the ENEA Lidar Fluorosensor (ELF), the SeaWiFS chlorophyll a (Chl a) algorithm is tuned in the Ross Sea by means of the ELF measurements. The Chl a concentrations obtained in this way have been the basis for estimating productivity values and their evolution during summer 1997–98. Three primary production models have been used, providing information on their accuracy and performance in the Antarctic environment. Our investigations suggest that the primary production was lower than usual during the period 3 December 1997–16 January 1998.


2004 ◽  
Vol 179 (2) ◽  
pp. 221-233 ◽  
Author(s):  
R. Pastres ◽  
D. Brigolin ◽  
A. Petrizzo ◽  
M. Zucchetta

2020 ◽  
pp. 169-182
Author(s):  
Michael J. Fogarty ◽  
Jeremy S. Collie

The development of ecosystem models can be size-based, species-based, or trophocentric. In all cases, equilibrium mass-balance descriptions of ecosystems can be translated to dynamic models. Linear network models trace the flow of energy through food webs. Starting from the base of the food web, they can be solved from the bottom up to calculate how many predators can be supported for a given level of primary production. Conversely, the food web can be solved from the top down to calculate how much primary production is required to support fisheries yield, given the dietary requirements of top predators. These models typically employ species-level and/or trophic-level designations for the nodes in the model. Biomass-spectrum models in contrast are based on body size dimensions (typically weight) rather than any taxonomic designation. Biogeochemical models provide another approach to developing ecosystem production models by making the connection between the availability of key nutrients and ecosystem production.


2013 ◽  
Vol 83 ◽  
pp. 30-39 ◽  
Author(s):  
Cristina García-Muñoz ◽  
Ángel López-Urrutia ◽  
Luis M. Lubián ◽  
Carlos M. García ◽  
Santiago Hernández-León

Ocean Science ◽  
2013 ◽  
Vol 9 (2) ◽  
pp. 431-445 ◽  
Author(s):  
A. Cherkasheva ◽  
E.-M. Nöthig ◽  
E. Bauerfeind ◽  
C. Melsheimer ◽  
A. Bracher

Abstract. Current estimates of global marine primary production range over a factor of two. Improving these estimates requires an accurate knowledge of the chlorophyll vertical profiles, since they are the basis for most primary production models. At high latitudes, the uncertainty in primary production estimates is larger than globally, because here phytoplankton absorption shows specific characteristics due to the low-light adaptation, and in situ data and ocean colour observations are scarce. To date, studies describing the typical chlorophyll profile based on the chlorophyll in the surface layer have not included the Arctic region, or, if it was included, the dependence of the profile shape on surface concentration was neglected. The goal of our study was to derive and describe the typical Greenland Sea chlorophyll profiles, categorized according to the chlorophyll concentration in the surface layer and further monthly resolved profiles. The Greenland Sea was chosen because it is known to be one of the most productive regions of the Arctic and is among the regions in the Arctic where most chlorophyll field data are available. Our database contained 1199 chlorophyll profiles from R/Vs Polarstern and Maria S. Merian cruises combined with data from the ARCSS-PP database (Arctic primary production in situ database) for the years 1957–2010. The profiles were categorized according to their mean concentration in the surface layer, and then monthly median profiles within each category were calculated. The category with the surface layer chlorophyll (CHL) exceeding 0.7 mg C m−3 showed values gradually decreasing from April to August. A similar seasonal pattern was observed when monthly profiles were averaged over all the surface CHL concentrations. The maxima of all chlorophyll profiles moved from the greater depths to the surface from spring to late summer respectively. The profiles with the smallest surface values always showed a subsurface chlorophyll maximum with its median magnitude reaching up to three times the surface concentration. While the variability of the Greenland Sea season in April, May and June followed the global non-monthly resolved relationship of the chlorophyll profile to surface chlorophyll concentrations described by the model of Morel and Berthon (1989), it deviated significantly from the model in the other months (July–September), when the maxima of the chlorophyll are at quite different depths. The Greenland Sea dimensionless monthly median profiles intersected roughly at one common depth within each category. By applying a Gaussian fit with 0.1 mg C m−3 surface chlorophyll steps to the median monthly resolved chlorophyll profiles of the defined categories, mathematical approximations were determined. They generally reproduce the magnitude and position of the CHL maximum, resulting in an average 4% underestimation in Ctot (and 2% in rough primary production estimates) when compared to in situ estimates. These mathematical approximations can be used as the input to the satellite-based primary production models that estimate primary production in the Arctic regions.


2012 ◽  
Vol 9 (6) ◽  
pp. 3567-3591
Author(s):  
A. Cherkasheva ◽  
A. Bracher ◽  
E.-M. Nöthig ◽  
E. Bauerfeind ◽  
C. Melsheimer

Abstract. Current estimates of global marine primary production range over a factor of two. At high latitudes, the uncertainty is even larger than globally because here in-situ data and ocean color observations are scarce, and the phytoplankton absorption shows specific characteristics due to the low-light adaptation. The improvement of the primary production estimates requires an accurate knowledge on the chlorophyll vertical profile, which is the basis for most primary production models. To date, studies describing the typical chlorophyll profile based on the chlorophyll in the surface layer did not include the Arctic region or, if it was included, the dependence of the profile shape on surface concentration was neglected. The goal of our study was to derive and describe the typical Greenland Sea chlorophyll profiles, categorized according to the chlorophyll concentration in the surface layer and further monthly resolved. The Greenland Sea was chosen because it is known to be one of the most productive regions of the Arctic and is among the Arctic regions where most chlorophyll field data are available. Our database contained 1199 chlorophyll profiles from R/Vs Polarstern and Maria S Merian cruises combined with data of the ARCSS-PP database (Arctic primary production in-situ database) for the years 1957–2010. The profiles were categorized according to their mean concentration in the surface layer and then monthly median profiles within each category were calculated. The category with the surface layer chlorophyll exceeding 0.7 mg C m−3 showed a clear seasonal cycle with values gradually decreasing from April to August. Chlorophyll profiles maxima moved from lower depths in spring towards the surface in late summer. Profiles with smallest surface values always showed a subsurface chlorophyll maximum with its median magnitude reaching up to three times the surface concentration. While the variability in April, May and June of the Greenland Sea season is following the global non-monthly resolved relationship of the chlorophyll profile to surface chlorophyll concentrations described by the model of Morel and Berthon (1989), it deviates significantly from that in other months (July–September) where the maxima of the chlorophyll are at quite different depths. The Greenland Sea dimensionless monthly median profiles intersect roughly at one common depth within each category. Finally, by applying a Gaussian fitting with 0.1 mg C m−3 surface chlorophyll steps to the median monthly resolved chlorophyll profiles of the defined categories, mathematical approximations have been determined. These will be used as the input to the satellite-based primary production models estimating primary production in Arctic regions.


Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5072
Author(s):  
Ilaria Cesana ◽  
Mariano Bresciani ◽  
Sergio Cogliati ◽  
Claudia Giardino ◽  
Remika Gupana ◽  
...  

The aim of this study is to test a series of methods relying on hyperspectral measurements to characterize phytoplankton in clear lake waters. The phytoplankton temporal evolutions were analyzed exploiting remote sensed indices and metrics linked to the amount of light reaching the target (EPAR), the chlorophyll-a concentration ([Chl-a]OC4) and the fluorescence emission proxy. The latter one evaluated by an adapted version of the Fluorescence Line Height algorithm (FFLH). A peculiar trend was observed around the solar noon during the clear sky days. It is characterized by a drop of the FFLH metric and the [Chl-a]OC4 index. In addition to remote sensed parameters, water samples were also collected and analyzed to characterize the water body and to evaluate the in-situ fluorescence (FF) and absorbed light (FA). The relations between the remote sensed quantities and the in-situ values were employed to develop and test several phytoplankton primary production (PP) models. Promising results were achieved replacing the FA by the EPAR or FFLH in the equation evaluating a PP proxy (R2 > 0.65). This study represents a preliminary outcome supporting the PP monitoring in inland waters by means of remote sensing-based indices and fluorescence metrics.


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