
Citation: | Baohong Chen, Kaiwen Zhou, Kang Wang, Jigang Wang, Sumin Wang, Xiuwu Sun, Jinmin Chen, Cai Lin, Hui Lin. Temporal and spatial distribution characteristics of nutrients in Clarion-Clipperton Fracture Zone in the Pacific in 2017[J]. Acta Oceanologica Sinica, 2022, 41(1): 1-10. doi: 10.1007/s13131-021-1931-y |
Deep-sea polymetallic nodules are potential sources of metals such as Fe, Mn, Ni, Cu and Co. Although deep-sea polymetallic nodules have been found in all oceans, only some areas have abundant nodule resources rich in elements of economic interest, and Clarion-Clipperton Fracture Zone (CCFZ) in the eastern tropical Pacific is one of these important areas causing growing interest in mining them (Wu et al., 2013). For this reason, 16 exploration contracts for large nodule fields within the CCFZ have been granted by the International Seabed Authority (ISA). Recent studies have demonstrated that planned mining activities have serious negative environmental impacts, and the post-disturbance recovery of the impacted ecosystem will be an extremely long process, measured in the scale of decades or even thousands of years (Jones et al., 2017). Because of concerns about the effects of mining on the functioning of deep-sea ecosystems and biodiversity, the ISA has identified “Areas of Particular Environmental Interest”. In the past few decades, as an important region for its role in climate variability due to the El Niño-Southern Oscillation (ENSO), in fish production, and in the global carbon cycle (Fiedler and Lavin, 2006), under the framework of the Tropical Ocean and Global Atmosphere and the World Ocean Circulation Experiment, there have been a number of observational investigation programs in the eastern tropical Pacific. However, studies about biogeochemical processes of nutrients in this area is still relatively insufficient to resolve seasonal and ENSO variability (Fiedler and Talley, 2006). As one part of the eastern tropical Pacific, reports about the baseline or changes of the environmental conditions in CCFZ are still insufficient (Menendez et al., 2019; Tu, 2006). As the primary elements of marine life, the distribution or circulation of nutrients in the ocean is important to understand the primary production or changes of marine ecosystem. However, studies about spatial and temporal changes of nutrients in CCFZ are still scares (Loubere, 2001; Tu, 2006). Therefore, here we present a study on (1) the baseline of spatial distribution characteristics of nutrients in 2017 and their physical or biological controlling factors, and (2) temporal changes of nutrient concentrations and molar ratios, comparing with the baseline investigation in 1990s−2000s. The main scientific objectives of this study are to give data basis to (1) discuss long-term changes of nutrient concentrations in CCFZ, (2) evaluate ecological changes in CCFZ under the background of eastern tropical Pacific, and (3) help to develope polymetallic nodules in CCFZ .
CCFZ is located in the eastern tropical Pacific, north of the equatorial zone. It comprises an area of about 6×106 km2, defined by two major transform faults, the Clarion Fracture Zone in the north and the Clipperton Fracture Zone in the south (Volz et al., 2018), extending from approximately 20°N, 120°W to 5°N, 160°W, with a total length of 7240 km (Menendez et al., 2019). Eastern tropical Pacific containing both the eastern terminus of the equatorial current system of the Pacific (Kessler, 2006) and the eastern Pacific warm pool that forms half of the western hemisphere warm pool straddling Central America (Wang and Enfield, 2001). The current in the north of eastern tropical Pacific is one of the most important current systems in the whole ocean circulation. This study area is mainly under the control of North Equatorial Current, South Equatorial Current and North Equatorial Countercurrent. In the west of this area is the warm tongue extending from the east of the western Pacific warm pool, and in the south of the area is the equatorial cold water tongue. The upper ocean in this area is mainly affected by these currents and water masses, and the flowing direction and velocity of the surface current are affected by ENSO events (Tu, 2006). Under the control of the northeast trade wind all the year round, the study area has the characteristics of paroxysmal and frequent precipitation because of its low latitude. And the study area belongs to the East Pacific Basin. From east to west, the water depth gradually deepens. While from north to south, the water depth gradually becomes shallow and the change range is small (Tu, 2006). Considering that abyssal benthic communities are limited by low carbon export from the euphotic zone (Smith et al., 2008), biodiversity in the CCFZ is surprisingly high (Glover et al., 2002). And as a consequence of microbial respiration in the water column and weak ocean ventilation, a pronounced oxygen minimum zone persists in the eastern equatorial Pacific (Kalvelage et al., 2015).
Eight stations were investigated in Chinese contract area in CCFZ in this cruise (Fig. 1 and Table 1), from August 21 to October 8 in 2017, which was organized by Third Institute of Oceanography, Ministry of Natural Resources of China. At each station, temperature (T), salinity (S), pressure and chlorophyll a (Chl a) concentration were recorded by a conductivity-temperature-depth (CTD) profiler (Sea-Bird, SBE 911plus, Table 2). Water samples were collected at different layers (5 m, 50 m, 75 m, 100 m, 200 m, 500 m, 1000 m, 2500 m, 4500 m, 5000 m) with Niskin bottles mounted onto a rosette sampler attached to the CTD. Nutrients (
Station | Latitude | Longitude | Date | Depth/m |
CC-S06 | 12°58.115 1' N | 153°14.585 2' W | Agu. 21 | 5 447 |
CC-S01 | 8°30.025 6' N | 154°15.151 1' W | Agu. 25 | 5 187 |
KW1-S37 | 9°30.103 0' N | 154°14.884 1' W | Spet. 4−5 | 5 133 |
KW1-S05 | 10°04.973 9' N | 154°20.038 5' W | Sept. 9−10 | 5 173 |
KW1-S01 | 11°00.011 8' N | 154°15.006 0' W | Sept. 17 | 5 240 |
KW1-S40 | 10°11.506 6' N | 154°35.663 3' W | Sept. 19 | 5 148 |
CC-S09 | 12°59.669 3' N | 154°15.523 0' W | Oct. 7 | 5 414 |
CC-S10 | 11°59.999 0' N | 154°15.006 2' W | Oct. 8 | 5 008 |
Parameters | Wave length | Sensitibity | Resolution | Range |
Turbidity | 700 nm | 0.01 NTU | 0.007 NTU | 0−25 NTU |
Chl a | 470/695 nm | 0.025 μg/L | 0.013 μg/L | 0−50 μg/L |
Concentration of nutrients (
Parameters | pH | ${\rm{NO} }_3^ -\text{-} {\rm{N} }$ /(μmol·L−1) | ${\rm{NO}}_2^ -{\text -} {\rm{N}} $ /(μmol·L−1) | ${\rm{NH}}_4^+ {\text - }{\rm {N}} $ /(μmol·L−1) | ${\rm{SiO}}_3^{2 - } {\text -} {\rm{Si}}$ /(μmol·L−1) | ${\rm{PO}}_4^{3 - }{\text -}{\rm{P}} $ /(μmol·L−1) | DO /(μmol·L−1) |
Range | − | 0.05−16.0 | 0.02−4.00 | 0.03−8.00 | 0.10−25.0 | 0.02−4.80 | 5.3−1.0×103 |
Accuracy | ±0.02 | C=2.0, RE=±7.0%; C=10.0, RE=±4.0%. | C= 0.5, RE=±5.0%; C=1.00, RE=±3.0%. | C=1.0, RE=±7.0%; C=7.0, RE=±4.0%. | C=4.5, RE=±5.0%. − − | C=0.20, RE=±10%; C=2.0, RE=±3.5%. | − − − − |
Precision | ±0.01 | C=5.0, RSD=±4.0%; C=10.0, RSD=±3.0%. | C=0.3, RSD=±5.0%; C=1.00, RSD=±2.0%. | C=1.00, RSD=±7.0%; C=7.00, RSD=±3.0%. | C=4.5, RSD=±4.0%. − − | C=0.20, RSD=±10%; C=2.0, RSD=±3.0%. | C<160, SD=±2.8; C≥550, SD=±4.0. |
Note: − repersents no data; C represents concentration; RSD, relative standard deviation; SD, standard deviation; RE, relative error. |
Generalized Additive Models (GAMs) (Hastie and Tibshirani, 1990) is an additive non-linear regression model for response variable Y that follows an exponential family distribution. This is a mathematical model based on data analysis. Data determines the relationship between response variables and predictors, rather than a parameter relationship assumed by the impact mechanism. The model can effectively reveal the nonlinear and nonmonotonic potential relationship between response variables and prediction factors, and it has been widely used in ecology and oceanography to study potential relationship between Chl a and various environmental parameters (Raitsos et al., 2012; Song et al., 2014; Zhou et al., 2014; Qiao et al., 2017; Zhang et al., 2019) .
Here we used the function GAM in the R package MGCV developed by Wood (2006) to model the functional response of abundances of phytoplankton community (Chl a) to environmental parameters. As the distribution of Chl a concentration is highly right-skewed, we loge-transformed them to lgChl a, respectively, to satisfy a roughly normal distribution. The new variables were named “lgChl a”. Furthermore, we focused on identifying the explanatory variables that were strongly correlated with measured Chl a, rather than the prediction or forecasting of Chl a (Chen et al., 2012).
During this cruise in Chinese contract area, T ranged from 1.38°C to 28.81°C with an average of 12.13°C. Sectional distribution of T decreased from surface to about 3 500 m, then it was comparably stable from 3500 m to the bottom. The average T at surface layer was about 28.5°C. The stratification of T was obvious and the thermocline occurred at the depth of about 30−90 m. The uniform upper layer of T in the southern stations is about 80 m, which is obviously deeper than that in the north (Fig. 2), just as previous record by Tu (2006). Salinity ranged from 34.10 to 34.73 with an average of 34.56. Sectional distribution of S increased first from surface to about 100 m with a high-value patch >34.80 at northern station, then decreased in subsurface layer from 100 m to 150 m, and increased again from 150 m to about 200 m with a high-value >34.70. The surface S in most stations was lower than 34.20, and it was comparably stable from 200 m to the bottom with a range of 34.50−34.70 (Fig. 2). The water in this study area was mainly controlled by currents of North Equatorial Current, and North Equatorial Countercurrent (Fiedler and Talley, 2006). The water layer in this study area could be divided into 3 parts, the upper water body, the middle water body and the bottom water body (Fig. 3). The upper water body was formed by tropical surface water, equatorial surface water and subtropical underwater. The middle water body was formed by Antarctic intermediate water and the bottom water was formed by lower circumpolar water (Ni et al., 2011). Therefore the hydrological condition in this study area was much complicated (Fiedler and Talley, 2006).
The sectional distribution of DO concentration was opposite to those of nutrient concentrations in general (Fig. 4), which was highest (more than 400 μmol/L) in the upper layer (<100 m). It decreased from about 100 m to 200−400 m, then increased from 200−400 m to the bottom (Fig. 4) with a range of 16.9−432 μmol/L and an average of 269 μmol/L. The vertical gradient of DO concentration was greatest in the layer of 80−150 m. The minimum layer of DO concentration (MLD) was located between 200 m and 400 m with the value about 10.0 μmol/L.
This sectional distribution characteristics of DO concentration was supported by the conclusion of Tu (2006). According to previous studies, MLD in eastern tropical Pacific, lying between the pycnocline and intermediate waters, is remarkable for its size and degree of hypoxia (Kamykowski and Zentara, 1990), which is attributable to several factors: (1) high phytoplankton production; (2) a sharp permanent pycnocline that prevents local ventilation of subsurface waters; (3) a sluggish and convoluted deep circulation and therefore old ‘‘age’’ of subpycnocline waters (Fiedler and Talley, 2006). There are three major oxygen deficient zones (ODZs) in the world: the eastern tropical north Pacific (ETNP), the eastern tropical south Pacific (ETSP) and Arabian Sea (Codispoti and Christensen, 1985). And CCFZ is located in ETNP. Previous studies showed that denitrification occurs in these three major ODZs (Codispoti et al., 2001) and these regions contribute to a significant fraction of the global N2O balance (Bange et al., 2000). Therefore, there maybe denitrification happened between 200 m and 400 m in CCFZ and associated N2O fluxes toward the atmosphere (Chang et al., 2010). However, in this cruise, we did not sample and analyse N2O levels in the water column. More studies are needed in the future.
The eastern equatorial Pacific plays an important role in marine chemical cycles (Loubere, 2001), where fluxes and distributions of nutrients are controlled by interaction of circulation with biological processes. Nutrient concentrations were generally lowest in the upper layer of the ocean, which was mainly controlled by or related to biological activities, cause phytoplankton need to absorb nutrients to synthesize organic matter in the euphotic zone. The generally sectional distribution characteristics of nutrients in CCFZ were similar as follows (Fig. 4): nutrients concentration were lowest in the upper layer, which increased from the upper layer to some depths and reached the highest value, and then decreased a little until the bottom, just in accordance with previous report (Tu, 2006).
Furthermore, the uniform upper layer gradually became shallow from southern stations to northern ones (Fig. 4). And the study area has a shallow mixing layer and a thin thermocline. In the vertical direction, the water column has obvious stratification phenomenon (Tu, 2006).
During July to August in 2017, a cruise was carried out in three seamounts (ie., the seamounts Demao Guyot and Batiza Guyot (NA), Niulang Guyot (NLG) and McDonnell Guyot (MP4), respectively) and a untitled sea basin (named C1) in the subtropical western Pacific Ocean (SWPO) by Third Institute of Oceanography, Ministry of Natural Resources of China (unpublished data) with same methods of sampling and analysis (General Administration of Quality Supervision, Inspection and Quarantine of the People’s Republic of China and Standardization Administration, 2008). Comparing nutrient concentrations in SWPO and CCFZ (Tables 4 and 5, Figs 5 and 6), it could be concluded that both in the whole water column and euphotic zone (0−100 m), concentrations of DIN,
Area | DIN/(μmol·L−1) | ${\rm{PO}}_4^{3 - }{\text -}{\rm{ P}} $/(μmol·L−1) | ${\rm{SiO}}_3^{2 - } {\text -} {\rm{Si}} $/(μmol·L−1) | N/P | N/Si | Si/P | |
NA | range | nd−56.8 | nd−2.91 | 0.29−208 | 1.21−2284 | 0.00−2.90 | 11.6−1372 |
average | 18.1±20.8 | 1.08±1.27 | 50.0±63.5 | 151±392 | 0.73±0.73 | 405±419 | |
NLG | range | nd−46.1 | nd−2.93 | 0.36−145 | 0.94−1157 | 0.01−2.90 | 10.8−1784 |
average | 17.3±18.6 | 1.20±1.27 | 50.4±59.5 | 83.4±182 | 0.73±0.76 | 285±433 | |
MP4 | range | nd−46.3 | nd−2.91 | 0.31−153 | 0.50−956 | nd−3.00 | 8.57−1166 |
average | 18.1±20.1 | 1.15±1.27 | 50.3±61.6 | 79.5±162 | 0.68±0.71 | 283±353 | |
C1 | range | 0.02−42.8 | nd−2.75 | 0.50−140 | 13.6−106 | 0.04−1.75 | 21.9−1114 |
average | 18.6±19.5 | 1.19±1.25 | 52.4±60.4 | 46.1±25.3 | 0.66±0.57 | 288±385 | |
CCFZ | range | nd−61.5 | 0.10−3.34 | 0.14−174 | 0.01−21.7 | 0.00−3.09 | 1.05−80.0 |
average | 25.8±19.3 | 1.79±1.17 | 64.6±63.0 | 10.7±6.64 | 0.55±0.50 | 27.3±23.2 | |
Note: nd represents under detection limit. |
Area | DIN/(μmol·L−1) | ${\rm{PO}}_4^{3 - }{\text -}{\rm{ P}} $/(μmol·L−1) | ${\rm{SiO}}_3^{2 - } {\text -} {\rm{Si}} $/(μmol·L−1) | N/P | N/Si | Si/P | Chl a/(μg·L−1) | |
NA | range | nd−0.44 | nd | 0.29−1.01 | 0.54−442 | 0.00−0.89 | 286−1007 | nd−0.17 |
average | 0.06±0.11 | nd±0.00 | 0.67±0.21 | 57.6±108 | 0.12±0.24 | 666±208 | 0.08±0.05 | |
NLG | range | 0.01−0.52 | nd−0.10 | 0.36−1.61 | 0.43−523 | 0.01−1.47 | 11.7−1611 | nd−0.39 |
average | 0.10±0.13 | 0.01±0.02 | 0.99±0.35 | 79.8±132 | 0.14±0.30 | 617±456 | 0.12±0.10 | |
MP4 | range | nd−0.43 | nd−0.05 | 0.36−0.87 | 0.54−432 | 0.00−0.54 | 10.9−867 | nd−0.32 |
average | 0.08±0.12 | 0.00±0.01 | 0.59±0.17 | 78.4±127 | 0.13±0.16 | 512±244 | 0.10±0.09 | |
C1 | range | 0.02−0.05 | nd | 0.50−1.01 | 19.5−48.0 | 0.02−0.10 | 495−1007 | 0.05−0.19 |
average | 0.03±0.01 | nd±0.00 | 0.70±0.22 | 32.6±13.1 | 0.05±0.03 | 704±219 | 0.11±0.06 | |
CCFZ | range | 0.00−12.4 | 0.10−1.11 | 0.14−8.73 | 0.00−29.3 | 0.00−9.10 | 1.05−40.4 | 0.01−1.02 |
average | 1.34±2.75 | 0.27±0.24 | 1.99±2.16 | 5.79±7.61 | 1.19±2.22 | 7.36±6.98 | 0.28±0.30 | |
Note: nd represents under detection limit. |
Comparing nutrients ratios in SWPO and this study area (Tables 4 and 5, Figs 5 and 6), it could be concluded that P was the main limited nutrient in SWPO, however in CCFZ, N limited the growth of phytoplankton especially in euphotic zone. Under the condition of N limitation, phytoplankton can use total organic nitrogen as nitrogen source for its growth (Libby and Wheeler, 1997), and Ni (2011) reported that total organic nitrogen accounting more than 75% of total nitrogen in this study area.
In 1991, the application of China Ocean Committee (COM) as a pioneer investor in polymetallic nodules was approved by the ISA. To implement obligation and responsibility to investigate and study the possible environmental impact of mining activities, the COM promoted an investigation about baseline and natural changes in Chinese contract area in CCFZ in 1998−2003, including the baseline characteristics of spatial distribution of nutrients (Tu, 2006). In 2017, the TIO again carried out this cruise to study the environmental conditions in this area. The results of changes of nutrient concentrations in this 20 years are showed in Table 6. In the investigation in 1998−2003,
Sampling time | ${\rm{PO}}_4^{3 - }{\text -}{\rm{ P}} $ | ${\rm{SiO}}_3^{2 - } {\text -} {\rm{Si}} $ | ${\rm{NO}}_3^ - {\text -} {\rm{N}} $ | ${\rm{NO}}_2^ - {\text -} {\rm{N}} $ | ${\rm{NH}}_4^+ {\text - }{\rm {N}} $ | DO |
Aug. 1998 | 0.07−3.09 | 0.00−165.9 | 0.00−64.12 | 0.00−0.85 | 0.00−2.04 | 32.8−440.2 |
Oct. 1999 | 0.00−3.28 | 0.00−178.3 | 0.00−64.35 | 0.01−1.58 | − | 28.8−438.9 |
Oct. 2001 | 0.02−3.19 | 0.40−152.8 | 0.13−54.15 | 0.00−0.73 | 0.49−1.07 | 22.4−442.4 |
Sept. 2002 | 0.10−3.10 | 0.62−133.9 | 0.01−50.31 | − | − | 44.5−426.3 |
Sept.−Oct. 2003 | 0.05−3.22 | 2.94−152.8 | 0.00−52.56 | 0.00−0.54 | − | 15.0−457.5 |
Aug.−Oct. 2017 | 0.11−3.34 | 0.14−172.0 | 0.00−49.77 | 0.00−0.99 | 0.00−1.05 | 16.9−424.6 |
Note: − represents no data. |
The direct reason of nutrients deficiency in euphotic zone especially in the upper layer of oceans is the absorption by phytoplankton (Tu, 2006). In this study area, Chl a concentration ranged from 0.01 μg/L to 1.02 μg/L in euphotic zone (0−100 m), with an average of 0.28 μg/L. The sectional distribution of Chl a concentration increased from surface to about 100 m, where the subsurface chlorophyll maximum (SCM) was located, with the highest value occurring at central stations of southern region in this study area (Fig. 4). Then with the limitation of light, Chl a concentration decreased from 100 m to about 150 m, where Chl a concentration was under detection limit again (Fig. 4). In the upper layer (<50 m), Chl a concentration was almost <0.10 μg/L. And the depth of SCM increased from southern stations to northern ones (Fig. 4), which was also supported by previous research (Tu, 2006). Study found that light and nutrients together control SCM in oceans (Bahamón et al., 2003). In this study area, N was the main limited nutrient to phytoplankton growth, and nitrate was the main form of dissolved inorganic nitrogen (Fig. 4). It could be found that SCM located near nitracline, this phenomenon was recorded in the tropical Atlantic Ocean by Bahamón et al. (2003) too.
To study how environmental factors especially light and nutrients control the biomass of phytoplankton community, this paper used a model named GAMs to analysis the bottom-up process. In marine science, GAMs have been used in modeling phytoplankton biomass (Deng et al., 2015; Song et al., 2014; Zhou et al., 2014; Raitsos et al., 2012; Kim et al., 2019). GAMs allow the effects of individual environmental parameters to be examined and the underlying controlling mechanisms being inferred (Chen et al., 2012). To discuss how environmental parameters especially nutrient concentrations affect Chl a concentration by bottom-up process, environmental factors including of temperature, salinity, depth, DIN,
Depth | Temperature | Salinity | DO | DIN | ${\rm{PO}}_4^{3 - }{\text -}{\rm{ P}} $ | ${\rm{SiO}}_3^{2 - } {\text -} {\rm{Si}} $ | N/P | N/Si | Si/P | |
Initial | 6.59 | 10.18 | 2.63 | 9.38 | 31.88 | 35.45 | 64.36 | 14.58 | 4.53 | 13.42 |
Ultimate | 6.51 | 9.32 | 2.61 | 7.54 | − | 8.48 | − | 7.84 | 3.68 | 1.16 |
Note: − represents no data. |
Model | GCV | n | |
lgChl a=s(depth)+s(salinity)+s(${\rm{PO}}_4^{3 - }{\text -}{\rm{P}} $)+b | 0.863 | 0.280 | 41 |
Note: R2 represents the adjusted proportion of total variability explained by the model; GCV, generalized cross validation score; n, the total number of samples; s, thin plate regression spline; b, a mean constant. |
(1) Dissolved inorganic nutrient (N, P and Si) concentrations in CCFZ were lowest in the upper layer, and increased from surface to some depth, then decreased a little to the bottom. N was the limited nutrient factor for the growth of phytoplankton community in this area.
(2) The sectional distribution of DO concentration was opposite to those of nutrient concentrations in general.
(3) Nutrient concentrations and molar ratios have no obvious changes in 2017 comparing with those in the investigation in 1998−2003.
(4) Nutrient concentrations in the study area was higher than those in the seamounts and Station ALOHA in the North Pacific, because they were supplemented from the equatorial Pacific with high nutrients, and also from regenerated within the water column themself.
(5) Depth, salinity and
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Station | Latitude | Longitude | Date | Depth/m |
CC-S06 | 12°58.115 1' N | 153°14.585 2' W | Agu. 21 | 5 447 |
CC-S01 | 8°30.025 6' N | 154°15.151 1' W | Agu. 25 | 5 187 |
KW1-S37 | 9°30.103 0' N | 154°14.884 1' W | Spet. 4−5 | 5 133 |
KW1-S05 | 10°04.973 9' N | 154°20.038 5' W | Sept. 9−10 | 5 173 |
KW1-S01 | 11°00.011 8' N | 154°15.006 0' W | Sept. 17 | 5 240 |
KW1-S40 | 10°11.506 6' N | 154°35.663 3' W | Sept. 19 | 5 148 |
CC-S09 | 12°59.669 3' N | 154°15.523 0' W | Oct. 7 | 5 414 |
CC-S10 | 11°59.999 0' N | 154°15.006 2' W | Oct. 8 | 5 008 |
Parameters | Wave length | Sensitibity | Resolution | Range |
Turbidity | 700 nm | 0.01 NTU | 0.007 NTU | 0−25 NTU |
Chl a | 470/695 nm | 0.025 μg/L | 0.013 μg/L | 0−50 μg/L |
Parameters | pH | ${\rm{NO} }_3^ -\text{-} {\rm{N} }$ /(μmol·L−1) | ${\rm{NO}}_2^ -{\text -} {\rm{N}} $ /(μmol·L−1) | ${\rm{NH}}_4^+ {\text - }{\rm {N}} $ /(μmol·L−1) | ${\rm{SiO}}_3^{2 - } {\text -} {\rm{Si}}$ /(μmol·L−1) | ${\rm{PO}}_4^{3 - }{\text -}{\rm{P}} $ /(μmol·L−1) | DO /(μmol·L−1) |
Range | − | 0.05−16.0 | 0.02−4.00 | 0.03−8.00 | 0.10−25.0 | 0.02−4.80 | 5.3−1.0×103 |
Accuracy | ±0.02 | C=2.0, RE=±7.0%; C=10.0, RE=±4.0%. | C= 0.5, RE=±5.0%; C=1.00, RE=±3.0%. | C=1.0, RE=±7.0%; C=7.0, RE=±4.0%. | C=4.5, RE=±5.0%. − − | C=0.20, RE=±10%; C=2.0, RE=±3.5%. | − − − − |
Precision | ±0.01 | C=5.0, RSD=±4.0%; C=10.0, RSD=±3.0%. | C=0.3, RSD=±5.0%; C=1.00, RSD=±2.0%. | C=1.00, RSD=±7.0%; C=7.00, RSD=±3.0%. | C=4.5, RSD=±4.0%. − − | C=0.20, RSD=±10%; C=2.0, RSD=±3.0%. | C<160, SD=±2.8; C≥550, SD=±4.0. |
Note: − repersents no data; C represents concentration; RSD, relative standard deviation; SD, standard deviation; RE, relative error. |
Area | DIN/(μmol·L−1) | ${\rm{PO}}_4^{3 - }{\text -}{\rm{ P}} $/(μmol·L−1) | ${\rm{SiO}}_3^{2 - } {\text -} {\rm{Si}} $/(μmol·L−1) | N/P | N/Si | Si/P | |
NA | range | nd−56.8 | nd−2.91 | 0.29−208 | 1.21−2284 | 0.00−2.90 | 11.6−1372 |
average | 18.1±20.8 | 1.08±1.27 | 50.0±63.5 | 151±392 | 0.73±0.73 | 405±419 | |
NLG | range | nd−46.1 | nd−2.93 | 0.36−145 | 0.94−1157 | 0.01−2.90 | 10.8−1784 |
average | 17.3±18.6 | 1.20±1.27 | 50.4±59.5 | 83.4±182 | 0.73±0.76 | 285±433 | |
MP4 | range | nd−46.3 | nd−2.91 | 0.31−153 | 0.50−956 | nd−3.00 | 8.57−1166 |
average | 18.1±20.1 | 1.15±1.27 | 50.3±61.6 | 79.5±162 | 0.68±0.71 | 283±353 | |
C1 | range | 0.02−42.8 | nd−2.75 | 0.50−140 | 13.6−106 | 0.04−1.75 | 21.9−1114 |
average | 18.6±19.5 | 1.19±1.25 | 52.4±60.4 | 46.1±25.3 | 0.66±0.57 | 288±385 | |
CCFZ | range | nd−61.5 | 0.10−3.34 | 0.14−174 | 0.01−21.7 | 0.00−3.09 | 1.05−80.0 |
average | 25.8±19.3 | 1.79±1.17 | 64.6±63.0 | 10.7±6.64 | 0.55±0.50 | 27.3±23.2 | |
Note: nd represents under detection limit. |
Area | DIN/(μmol·L−1) | ${\rm{PO}}_4^{3 - }{\text -}{\rm{ P}} $/(μmol·L−1) | ${\rm{SiO}}_3^{2 - } {\text -} {\rm{Si}} $/(μmol·L−1) | N/P | N/Si | Si/P | Chl a/(μg·L−1) | |
NA | range | nd−0.44 | nd | 0.29−1.01 | 0.54−442 | 0.00−0.89 | 286−1007 | nd−0.17 |
average | 0.06±0.11 | nd±0.00 | 0.67±0.21 | 57.6±108 | 0.12±0.24 | 666±208 | 0.08±0.05 | |
NLG | range | 0.01−0.52 | nd−0.10 | 0.36−1.61 | 0.43−523 | 0.01−1.47 | 11.7−1611 | nd−0.39 |
average | 0.10±0.13 | 0.01±0.02 | 0.99±0.35 | 79.8±132 | 0.14±0.30 | 617±456 | 0.12±0.10 | |
MP4 | range | nd−0.43 | nd−0.05 | 0.36−0.87 | 0.54−432 | 0.00−0.54 | 10.9−867 | nd−0.32 |
average | 0.08±0.12 | 0.00±0.01 | 0.59±0.17 | 78.4±127 | 0.13±0.16 | 512±244 | 0.10±0.09 | |
C1 | range | 0.02−0.05 | nd | 0.50−1.01 | 19.5−48.0 | 0.02−0.10 | 495−1007 | 0.05−0.19 |
average | 0.03±0.01 | nd±0.00 | 0.70±0.22 | 32.6±13.1 | 0.05±0.03 | 704±219 | 0.11±0.06 | |
CCFZ | range | 0.00−12.4 | 0.10−1.11 | 0.14−8.73 | 0.00−29.3 | 0.00−9.10 | 1.05−40.4 | 0.01−1.02 |
average | 1.34±2.75 | 0.27±0.24 | 1.99±2.16 | 5.79±7.61 | 1.19±2.22 | 7.36±6.98 | 0.28±0.30 | |
Note: nd represents under detection limit. |
Sampling time | ${\rm{PO}}_4^{3 - }{\text -}{\rm{ P}} $ | ${\rm{SiO}}_3^{2 - } {\text -} {\rm{Si}} $ | ${\rm{NO}}_3^ - {\text -} {\rm{N}} $ | ${\rm{NO}}_2^ - {\text -} {\rm{N}} $ | ${\rm{NH}}_4^+ {\text - }{\rm {N}} $ | DO |
Aug. 1998 | 0.07−3.09 | 0.00−165.9 | 0.00−64.12 | 0.00−0.85 | 0.00−2.04 | 32.8−440.2 |
Oct. 1999 | 0.00−3.28 | 0.00−178.3 | 0.00−64.35 | 0.01−1.58 | − | 28.8−438.9 |
Oct. 2001 | 0.02−3.19 | 0.40−152.8 | 0.13−54.15 | 0.00−0.73 | 0.49−1.07 | 22.4−442.4 |
Sept. 2002 | 0.10−3.10 | 0.62−133.9 | 0.01−50.31 | − | − | 44.5−426.3 |
Sept.−Oct. 2003 | 0.05−3.22 | 2.94−152.8 | 0.00−52.56 | 0.00−0.54 | − | 15.0−457.5 |
Aug.−Oct. 2017 | 0.11−3.34 | 0.14−172.0 | 0.00−49.77 | 0.00−0.99 | 0.00−1.05 | 16.9−424.6 |
Note: − represents no data. |
Depth | Temperature | Salinity | DO | DIN | ${\rm{PO}}_4^{3 - }{\text -}{\rm{ P}} $ | ${\rm{SiO}}_3^{2 - } {\text -} {\rm{Si}} $ | N/P | N/Si | Si/P | |
Initial | 6.59 | 10.18 | 2.63 | 9.38 | 31.88 | 35.45 | 64.36 | 14.58 | 4.53 | 13.42 |
Ultimate | 6.51 | 9.32 | 2.61 | 7.54 | − | 8.48 | − | 7.84 | 3.68 | 1.16 |
Note: − represents no data. |
Model | GCV | n | |
lgChl a=s(depth)+s(salinity)+s(${\rm{PO}}_4^{3 - }{\text -}{\rm{P}} $)+b | 0.863 | 0.280 | 41 |
Note: R2 represents the adjusted proportion of total variability explained by the model; GCV, generalized cross validation score; n, the total number of samples; s, thin plate regression spline; b, a mean constant. |
Station | Latitude | Longitude | Date | Depth/m |
CC-S06 | 12°58.115 1' N | 153°14.585 2' W | Agu. 21 | 5 447 |
CC-S01 | 8°30.025 6' N | 154°15.151 1' W | Agu. 25 | 5 187 |
KW1-S37 | 9°30.103 0' N | 154°14.884 1' W | Spet. 4−5 | 5 133 |
KW1-S05 | 10°04.973 9' N | 154°20.038 5' W | Sept. 9−10 | 5 173 |
KW1-S01 | 11°00.011 8' N | 154°15.006 0' W | Sept. 17 | 5 240 |
KW1-S40 | 10°11.506 6' N | 154°35.663 3' W | Sept. 19 | 5 148 |
CC-S09 | 12°59.669 3' N | 154°15.523 0' W | Oct. 7 | 5 414 |
CC-S10 | 11°59.999 0' N | 154°15.006 2' W | Oct. 8 | 5 008 |
Parameters | Wave length | Sensitibity | Resolution | Range |
Turbidity | 700 nm | 0.01 NTU | 0.007 NTU | 0−25 NTU |
Chl a | 470/695 nm | 0.025 μg/L | 0.013 μg/L | 0−50 μg/L |
Parameters | pH | ${\rm{NO} }_3^ -\text{-} {\rm{N} }$ /(μmol·L−1) | ${\rm{NO}}_2^ -{\text -} {\rm{N}} $ /(μmol·L−1) | ${\rm{NH}}_4^+ {\text - }{\rm {N}} $ /(μmol·L−1) | ${\rm{SiO}}_3^{2 - } {\text -} {\rm{Si}}$ /(μmol·L−1) | ${\rm{PO}}_4^{3 - }{\text -}{\rm{P}} $ /(μmol·L−1) | DO /(μmol·L−1) |
Range | − | 0.05−16.0 | 0.02−4.00 | 0.03−8.00 | 0.10−25.0 | 0.02−4.80 | 5.3−1.0×103 |
Accuracy | ±0.02 | C=2.0, RE=±7.0%; C=10.0, RE=±4.0%. | C= 0.5, RE=±5.0%; C=1.00, RE=±3.0%. | C=1.0, RE=±7.0%; C=7.0, RE=±4.0%. | C=4.5, RE=±5.0%. − − | C=0.20, RE=±10%; C=2.0, RE=±3.5%. | − − − − |
Precision | ±0.01 | C=5.0, RSD=±4.0%; C=10.0, RSD=±3.0%. | C=0.3, RSD=±5.0%; C=1.00, RSD=±2.0%. | C=1.00, RSD=±7.0%; C=7.00, RSD=±3.0%. | C=4.5, RSD=±4.0%. − − | C=0.20, RSD=±10%; C=2.0, RSD=±3.0%. | C<160, SD=±2.8; C≥550, SD=±4.0. |
Note: − repersents no data; C represents concentration; RSD, relative standard deviation; SD, standard deviation; RE, relative error. |
Area | DIN/(μmol·L−1) | ${\rm{PO}}_4^{3 - }{\text -}{\rm{ P}} $/(μmol·L−1) | ${\rm{SiO}}_3^{2 - } {\text -} {\rm{Si}} $/(μmol·L−1) | N/P | N/Si | Si/P | |
NA | range | nd−56.8 | nd−2.91 | 0.29−208 | 1.21−2284 | 0.00−2.90 | 11.6−1372 |
average | 18.1±20.8 | 1.08±1.27 | 50.0±63.5 | 151±392 | 0.73±0.73 | 405±419 | |
NLG | range | nd−46.1 | nd−2.93 | 0.36−145 | 0.94−1157 | 0.01−2.90 | 10.8−1784 |
average | 17.3±18.6 | 1.20±1.27 | 50.4±59.5 | 83.4±182 | 0.73±0.76 | 285±433 | |
MP4 | range | nd−46.3 | nd−2.91 | 0.31−153 | 0.50−956 | nd−3.00 | 8.57−1166 |
average | 18.1±20.1 | 1.15±1.27 | 50.3±61.6 | 79.5±162 | 0.68±0.71 | 283±353 | |
C1 | range | 0.02−42.8 | nd−2.75 | 0.50−140 | 13.6−106 | 0.04−1.75 | 21.9−1114 |
average | 18.6±19.5 | 1.19±1.25 | 52.4±60.4 | 46.1±25.3 | 0.66±0.57 | 288±385 | |
CCFZ | range | nd−61.5 | 0.10−3.34 | 0.14−174 | 0.01−21.7 | 0.00−3.09 | 1.05−80.0 |
average | 25.8±19.3 | 1.79±1.17 | 64.6±63.0 | 10.7±6.64 | 0.55±0.50 | 27.3±23.2 | |
Note: nd represents under detection limit. |
Area | DIN/(μmol·L−1) | ${\rm{PO}}_4^{3 - }{\text -}{\rm{ P}} $/(μmol·L−1) | ${\rm{SiO}}_3^{2 - } {\text -} {\rm{Si}} $/(μmol·L−1) | N/P | N/Si | Si/P | Chl a/(μg·L−1) | |
NA | range | nd−0.44 | nd | 0.29−1.01 | 0.54−442 | 0.00−0.89 | 286−1007 | nd−0.17 |
average | 0.06±0.11 | nd±0.00 | 0.67±0.21 | 57.6±108 | 0.12±0.24 | 666±208 | 0.08±0.05 | |
NLG | range | 0.01−0.52 | nd−0.10 | 0.36−1.61 | 0.43−523 | 0.01−1.47 | 11.7−1611 | nd−0.39 |
average | 0.10±0.13 | 0.01±0.02 | 0.99±0.35 | 79.8±132 | 0.14±0.30 | 617±456 | 0.12±0.10 | |
MP4 | range | nd−0.43 | nd−0.05 | 0.36−0.87 | 0.54−432 | 0.00−0.54 | 10.9−867 | nd−0.32 |
average | 0.08±0.12 | 0.00±0.01 | 0.59±0.17 | 78.4±127 | 0.13±0.16 | 512±244 | 0.10±0.09 | |
C1 | range | 0.02−0.05 | nd | 0.50−1.01 | 19.5−48.0 | 0.02−0.10 | 495−1007 | 0.05−0.19 |
average | 0.03±0.01 | nd±0.00 | 0.70±0.22 | 32.6±13.1 | 0.05±0.03 | 704±219 | 0.11±0.06 | |
CCFZ | range | 0.00−12.4 | 0.10−1.11 | 0.14−8.73 | 0.00−29.3 | 0.00−9.10 | 1.05−40.4 | 0.01−1.02 |
average | 1.34±2.75 | 0.27±0.24 | 1.99±2.16 | 5.79±7.61 | 1.19±2.22 | 7.36±6.98 | 0.28±0.30 | |
Note: nd represents under detection limit. |
Sampling time | ${\rm{PO}}_4^{3 - }{\text -}{\rm{ P}} $ | ${\rm{SiO}}_3^{2 - } {\text -} {\rm{Si}} $ | ${\rm{NO}}_3^ - {\text -} {\rm{N}} $ | ${\rm{NO}}_2^ - {\text -} {\rm{N}} $ | ${\rm{NH}}_4^+ {\text - }{\rm {N}} $ | DO |
Aug. 1998 | 0.07−3.09 | 0.00−165.9 | 0.00−64.12 | 0.00−0.85 | 0.00−2.04 | 32.8−440.2 |
Oct. 1999 | 0.00−3.28 | 0.00−178.3 | 0.00−64.35 | 0.01−1.58 | − | 28.8−438.9 |
Oct. 2001 | 0.02−3.19 | 0.40−152.8 | 0.13−54.15 | 0.00−0.73 | 0.49−1.07 | 22.4−442.4 |
Sept. 2002 | 0.10−3.10 | 0.62−133.9 | 0.01−50.31 | − | − | 44.5−426.3 |
Sept.−Oct. 2003 | 0.05−3.22 | 2.94−152.8 | 0.00−52.56 | 0.00−0.54 | − | 15.0−457.5 |
Aug.−Oct. 2017 | 0.11−3.34 | 0.14−172.0 | 0.00−49.77 | 0.00−0.99 | 0.00−1.05 | 16.9−424.6 |
Note: − represents no data. |
Depth | Temperature | Salinity | DO | DIN | ${\rm{PO}}_4^{3 - }{\text -}{\rm{ P}} $ | ${\rm{SiO}}_3^{2 - } {\text -} {\rm{Si}} $ | N/P | N/Si | Si/P | |
Initial | 6.59 | 10.18 | 2.63 | 9.38 | 31.88 | 35.45 | 64.36 | 14.58 | 4.53 | 13.42 |
Ultimate | 6.51 | 9.32 | 2.61 | 7.54 | − | 8.48 | − | 7.84 | 3.68 | 1.16 |
Note: − represents no data. |
Model | GCV | n | |
lgChl a=s(depth)+s(salinity)+s(${\rm{PO}}_4^{3 - }{\text -}{\rm{P}} $)+b | 0.863 | 0.280 | 41 |
Note: R2 represents the adjusted proportion of total variability explained by the model; GCV, generalized cross validation score; n, the total number of samples; s, thin plate regression spline; b, a mean constant. |