Tegomo, Fabrice Arnaud; Zhong, Zhiwen; Njomoue, Achille Pandong; Okon, Samuel Ukpong; Ullah, Sami; Gray, Neveen Anandi; Chen, Kai; Sun, Y; Xiao, Jinxing; Wang, Lei; Ye, Ying; Huang, Hui; Shao, Qingjun (2022): Seawater carbonate chemistry and survival, health, growth, and meat quality of black sea bream (Acanthopagrus schlegelii) [dataset]. PANGAEA, https://doi.org/10.1594/PANGAEA.943513
Always quote citation above when using data! You can download the citation in several formats below.
Abstract:
Acidification (OA), a global threat to the world's oceans, is projected to significantly grow if CO2 continues to be emitted into the atmosphere at high levels. This will result in a slight decrease in pH. Since the latter is a logarithmic scale of acidity, the higher acidic seawater is expected to have a tremendous impact on marine living resources in the long-term. An 8-week laboratory experiment was designed to assess the impact of the projected pH in 2100 and beyond on fish survival, health, growth, and fish meat quality. Two projected scenarios were simulated with the control treatment, in triplicates. The control treatment had a pH of 8.10, corresponding to a pCO2 of 321.37 ± 11.48 µatm. The two projected scenarios, named Predict_A and Predict_B, had pH values of 7.80-pCO2 = 749.12 ± 27.03 and 7.40-pCO2 = 321.37 ± 11.48 µatm, respectively. The experiment was preceded by 2 weeks of acclimation. After the acclimation, 20 juvenile black sea breams (Acanthopagrus schlegelii) of 2.72 ± 0.01 g were used per tank. This species has been selected mainly due to its very high resistance to diseases and environmental changes, assuming that a weaker fish resistance will also be susceptibly affected. In all tanks, the fish were fed with the same commercial diet. The seawater's physicochemical parameters were measured daily. Fish samples were subjected to physiological, histological, and biochemical analyses. Fish growth, feeding efficiency, protein efficiency ratio, and crude protein content were significantly decreased with a lower pH. Scanning electron microscopy revealed multiple atrophies of microvilli throughout the small intestine's brush border in samples from Predict_A and Predict_B. This significantly reduced nutrient absorption, resulting in significantly lower feed efficiency, lower fish growth, and lower meat quality. As a result of an elevated pCO2 in seawater, the fish eat more than normal but grow less than normal. Liver observation showed blood congestion, hemorrhage, necrosis, vacuolation of hepatocytes, and an increased number of Kupffer cells, which characterize liver damage. Transmission electron microscopy revealed an elongated and angular shape of the mitochondrion in the liver cell, with an abundance of peroxisomes, symptomatic of metabolic acidosis.
Keyword(s):
Supplement to:
Tegomo, Fabrice Arnaud; Zhong, Zhiwen; Njomoue, Achille Pandong; Okon, Samuel Ukpong; Ullah, Sami; Gray, Neveen Anandi; Chen, Kai; Sun, Y; Xiao, Jinxing; Wang, Lei; Ye, Ying; Huang, Hui; Shao, Qingjun (2021): Experimental Studies on the Impact of the Projected Ocean Acidification on Fish Survival, Health, Growth, and Meat Quality; Black Sea Bream (Acanthopagrus schlegelii), Physiological and Histological Studies. Animals, 11(11), 3119, https://doi.org/10.3390/ani11113119
Further details:
Gattuso, Jean-Pierre; Epitalon, Jean-Marie; Lavigne, Héloïse; Orr, James (2021): seacarb: seawater carbonate chemistry with R. R package version 3.2.16. https://cran.r-project.org/web/packages/seacarb/index.html
Project(s):
Comment:
In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2021) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation by seacarb is 2022-04-24.
Parameter(s):
# | Name | Short Name | Unit | Principal Investigator | Method/Device | Comment |
---|---|---|---|---|---|---|
1 | Type | Type | Shao, Qingjun | study | ||
2 | Species | Species | Shao, Qingjun | |||
3 | Registration number of species | Reg spec no | Shao, Qingjun | WoRMS Aphia ID | ||
4 | Uniform resource locator/link to reference | URL ref | Shao, Qingjun | |||
5 | Treatment | Treat | Shao, Qingjun | |||
6 | Mass | Mass | g | Shao, Qingjun | Initial, per fish | |
7 | Mass, standard deviation | Mass std dev | ± | Shao, Qingjun | Initial, per fish | |
8 | Mass | Mass | g | Shao, Qingjun | Final, per fish | |
9 | Mass, standard deviation | Mass std dev | ± | Shao, Qingjun | Final, per fish | |
10 | Survival | Survival | % | Shao, Qingjun | ||
11 | Survival rate, standard deviation | Survival rate std dev | ± | Shao, Qingjun | ||
12 | Gain | gain | % | Shao, Qingjun | Weight | |
13 | Gain, standard deviation | Gain std dev | ± | Shao, Qingjun | Weight | |
14 | Specific growth rate | SGR | %/day | Shao, Qingjun | ||
15 | Specific growth rate, standard deviation | SGR std dev | ± | Shao, Qingjun | ||
16 | Feed intake | Feed intake | %/day | Shao, Qingjun | ||
17 | Feed intake, standard deviation | Feed intake std dev | ± | Shao, Qingjun | ||
18 | Feed conversion ratio | FCR | Shao, Qingjun | |||
19 | Feed conversion ratio, standard deviation | FCR std dev | ± | Shao, Qingjun | ||
20 | Feed conversion efficiency | FCE | % | Shao, Qingjun | ||
21 | Feed conversion efficiency, standard deviation | FCE std dev | ± | Shao, Qingjun | ||
22 | Hepatosomatic index | HSI | % | Shao, Qingjun | ||
23 | Hepatosomatic index, standard deviation | HSI std dev | ± | Shao, Qingjun | ||
24 | Condition factor | CF | g/cm3 | Shao, Qingjun | ||
25 | Condition factor, standard deviation | CF std dev | ± | Shao, Qingjun | ||
26 | Protein efficiency ratio | PER | Shao, Qingjun | |||
27 | Protein efficiency ratio, standard deviation | PER std dev | ± | Shao, Qingjun | ||
28 | Category | Cat | Shao, Qingjun | |||
29 | Proximate composition | Proximate comp | % | Shao, Qingjun | Whole-body | |
30 | Proximate composition, standard deviation | Proximate comp std dev | ± | Shao, Qingjun | Whole-body | |
31 | Proximate composition | Proximate comp | % | Shao, Qingjun | Dorsal Muscle | |
32 | Proximate composition, standard deviation | Proximate comp std dev | ± | Shao, Qingjun | Dorsal Muscle | |
33 | Salinity | Sal | Shao, Qingjun | |||
34 | Salinity, standard deviation | Sal std dev | ± | Shao, Qingjun | ||
35 | Temperature, water | Temp | °C | Shao, Qingjun | ||
36 | Temperature, water, standard deviation | Temp std dev | ± | Shao, Qingjun | ||
37 | pH | pH | Shao, Qingjun | Potentiometric | NBS scale | |
38 | pH, standard deviation | pH std dev | ± | Shao, Qingjun | Potentiometric | NBS scale |
39 | Alkalinity, total | AT | µmol/kg | Shao, Qingjun | Potentiometric titration | |
40 | Alkalinity, total, standard deviation | AT std dev | ± | Shao, Qingjun | Potentiometric titration | |
41 | Partial pressure of carbon dioxide (water) at sea surface temperature (wet air) | pCO2water_SST_wet | µatm | Shao, Qingjun | Calculated using CO2calc | |
42 | Partial pressure of carbon dioxide, standard deviation | pCO2 std dev | ± | Shao, Qingjun | Calculated using CO2calc | |
43 | Bicarbonate ion | [HCO3]- | µmol/kg | Shao, Qingjun | Calculated using CO2calc | |
44 | Bicarbonate ion, standard deviation | [HCO3]- std dev | ± | Shao, Qingjun | Calculated using CO2calc | |
45 | Carbonate ion | [CO3]2- | µmol/kg | Shao, Qingjun | Calculated using CO2calc | |
46 | Carbonate ion, standard deviation | [CO3]2- std dev | ± | Shao, Qingjun | Calculated using CO2calc | |
47 | Carbon, inorganic, dissolved | DIC | µmol/kg | Shao, Qingjun | Calculated using CO2calc | |
48 | Carbon, inorganic, dissolved, standard deviation | DIC std dev | ± | Shao, Qingjun | Calculated using CO2calc | |
49 | Aragonite saturation state | Omega Arg | Shao, Qingjun | Calculated using CO2calc | ||
50 | Aragonite saturation state, standard deviation | Omega Arg std dev | ± | Shao, Qingjun | Calculated using CO2calc | |
51 | Calcite saturation state | Omega Cal | Shao, Qingjun | Calculated using CO2calc | ||
52 | Calcite saturation state, standard deviation | Omega Cal std dev | ± | Shao, Qingjun | Calculated using CO2calc | |
53 | Carbonate system computation flag | CSC flag | Yang, Yan | Calculated using seacarb after Nisumaa et al. (2010) | ||
54 | pH | pH | Yang, Yan | Calculated using seacarb after Nisumaa et al. (2010) | total scale | |
55 | Carbon dioxide | CO2 | µmol/kg | Yang, Yan | Calculated using seacarb after Nisumaa et al. (2010) | |
56 | Fugacity of carbon dioxide (water) at sea surface temperature (wet air) | fCO2water_SST_wet | µatm | Yang, Yan | Calculated using seacarb after Nisumaa et al. (2010) | |
57 | Partial pressure of carbon dioxide (water) at sea surface temperature (wet air) | pCO2water_SST_wet | µatm | Yang, Yan | Calculated using seacarb after Nisumaa et al. (2010) | |
58 | Bicarbonate ion | [HCO3]- | µmol/kg | Yang, Yan | Calculated using seacarb after Nisumaa et al. (2010) | |
59 | Carbonate ion | [CO3]2- | µmol/kg | Yang, Yan | Calculated using seacarb after Nisumaa et al. (2010) | |
60 | Carbon, inorganic, dissolved | DIC | µmol/kg | Yang, Yan | Calculated using seacarb after Nisumaa et al. (2010) | |
61 | Aragonite saturation state | Omega Arg | Yang, Yan | Calculated using seacarb after Nisumaa et al. (2010) | ||
62 | Calcite saturation state | Omega Cal | Yang, Yan | Calculated using seacarb after Nisumaa et al. (2010) |
License:
Creative Commons Attribution 4.0 International (CC-BY-4.0)
Status:
Curation Level: Enhanced curation (CurationLevelC)
Size:
651 data points