Implications of Nutrient Enrichment and Related Environmental Impacts in the Pearl River Estuary, China: Characterizing the Seasonal Influence of Riverine Input

Round 1

Reviewer 1 Report

Overall, the study is interesting. The flow is logical. The work can be published in the journal. However, the only concern is that the authors should report the data as mean ± S.D. in the text as well as in the figures. The authors should also state whether the number of readings taken to report the data. 

Comments for author File: Comments.pdf

Author Response

Comments and Suggestions for Authors:

Overall, the study is interesting. The flow is logical. The work can be published in the journal. However, the only concern is that the authors should report the data as mean ± S.D. in the text as well as in the figures. The authors should also state whether the number of readings taken to report the data. 

Response: The authors would like to thank the reviewer for the positive evaluations on this work, and have totally improved the manuscript according to the suggestions. The authors agreed with the reviewer and have changed the data format in the subsections of ‘3.1. Variations in hydrographic properties’, ‘3.2. Nutrient dynamics in the aquatic environment’, and ‘3.3. Biological variable (in terms of chlorophyll)’ in the main text. The authors have also added the number of samples for reporting the data.

In the subsection of 3.1. Variations in hydrographic properties, the changes are shown as :

Salinity levels fluctuated widely during the study period (Figure 3). Surface salinity was higher in the dry season (e.g., Feb and Nov) than in the flood season (e.g., May and Aug): a range of 1.50–34.46‰ (N=180) was observed in Feb (mean±SD, 23.93±9.64‰), 0.52–34.75‰ in May (19.71±12.77‰), 0.60–33.68‰ in Aug (14.11±11.28‰), and 0.90–33.44‰ in Nov (24.93±9.86‰). Bottom salinity levels showed a relatively small difference, with mean values of 26.46‰, 25.15‰, 21.23‰, and 27.87‰ in four seasons (N=168), respectively. (Page 6: Line 143-148)

In-depth variation of SPM was found: 4.0–77.8 mg/L in Feb (15.32±12.55 mg/L) and 0.8–139.1 mg/L in May (15.84±23.41 mg/L).  (Page 6: Line 152-153)

In the subsection of 3.2. Nutrient dynamics in the aquatic environment, the adjustments are displayed as:

The DIN ranged from 0.012–2.938 mg/L in the entire study area (N=345), with a mean value of 0.700 mg/L (Figure 4). Vertically, DIN concentrations decreased over the water depth: 0.012–2.938 mg/L (0.803±0.763 mg/L; N=180) for the surface waters and 0.013–2.346 mg/L (0.588±0.692 mg/L; N=165) for the bottom samples. Over the entire study site, DIN exhibited a decreasing trend from the river channel to the ocean sea; higher values were concentrated in the upper PRE, with a mean value of 1.75 mg/L; the concentrations in the west were relatively much higher. Over time, depth-averaged DIN varied from 0.075–2.635 mg/L (0.671±0.667 mg/L), 0.012–2.352 mg/L (0.537±0.665 mg/L), 0.030–2.337 mg/L (1.086±0.769 mg/L), and 0.043–2.244 mg/L (0.568±0.639 mg/L) in Feb, May, Aug, and Nov, respectively. (Page 7: Line 162-170)

By weight, NO₃ was the predominant composition of DIN in the entire area, as discussed from previous studies [23,35], and in-depth levels ranged from 0.004–2.025 mg/L (0.554±0.580 mg/L).  (Page 8: Line 171-172)

The DIP ranged from 0.002–0.231 mg/L (0.024±0.034 mg/L; N=348) in the entire study area. The DIP concentrations varied from 0.001–0.231 mg/L (0.025±0.034 mg/L; N=180) for the surface samples, and 0.002–0.083 mg/L (0.018±0.017 mg/L; N=168) for the bottom waters. Mean values were 0.014 mg/L, 0.014 mg/L, 0.042 mg/L, and 0.027 mg/L in Feb, May, Aug, and Nov, respectively. In addition, higher DIP levels (>0.03 mg/L) were detected in the east zone, be different when compared with DIN trends. The DSi ranged from 0.039–4.905 mg/L (mean 1.219±1.211 mg/L; N=348) in the entire area (Figure 4). The surface DSi was moderately higher than the bottom, 0.031–4.89 mg/L (1.331±1.273 mg/L) and 0.047–4.92 mg/L (1.019±1.178 mg/L), respectively. (Page 8: Line 177-185)

In the subsection of 3.3. Biological variable (in terms of chlorophyll)

The phytoplankton chlorophyll was at a relatively higher level in this estuary, averaged 3.14 µg/L (N=348) in 2016 in the estuary (Feb, 1.81±1.28 µg/L; May, 4.04±3.73 µg/L; Aug, 4.60±3.85 µg/L; and Nov, 2.74±2.96 µg/L). The in-depth chlorophyll varied from 0.31–16.34 µg/L (mean 3.30±3.29 µg/L) in the entire estuary. One-way analysis of variance showed a significant difference among seasons and sites (p<0.05).  (Page 8: Line 214-218)

Reviewer 2 Report

Thank you for a well written manuscript. I found the document informative, scientifically strong, and very easy to read. I found the discussion of how you quantified the relationship between dam construction the change in downstream trophic status to be very informative.

My question\comment is: Is this the first study of this kind for the Pearl River Estuary. If so, that information should be introduced early in the manuscript.  If not, then explain what makes this study unique and the information contained therein will be useful for additional studies.

Minor comments: all trendlines need to be darker (example Figure 6)

Author Response

Comments and Suggestions for Authors:

(1) Thank you for a well written manuscript. I found the document informative, scientifically strong, and very easy to read. I found the discussion of how you quantified the relationship between dam construction the change in downstream trophic status to be very informative.

My question\comment is: Is this the first study of this kind for the Pearl River Estuary. If so, that information should be introduced early in the manuscript. If not, then explain what makes this study unique and the information contained therein will be useful for additional studies.

Response: The authors would like to thank the reviewer for the positive reviews on this study, and have provided more details in the manuscript. The spatiotemporal characteristics of nutrient levels in the Pearl River estuary have been investigated (Lu et al., 2009; Zhang et al., 2016; Chen et al., 2019; Niu et al., 2020; Tao et al., 2020), however, the riverine influence on environmental stress was poorly documented. This study thus was the first of this kind study in the Pearl River estuary. In the Introduction, the authors have stated the related information, shown as:

The case study of pollutant-enriched Pearl River estuary (PRE) examines nutrient-related pollution and the river’s ecological response. Extensive studies have been carried out in this estuary, including the characterization of hydrographic properties [20], nutrient dynamics [2,21], biological features [4,22,23], and their relationships [24,25]. The seasonal dynamics of nutrients are significant [24,26]: in the dry season, the thermocline can effectively block the vertical exchanges of nutrients, and then confine the phytoplankton at a shallow surface layer [27]. During a flood season, nutrient input from riverine inflows largely enrich the estuary, and high-salinity water induced by the upwelling winds from the ocean also partially contribute to the nutrient enrichment [28]. The estuarine biogeochemical processes of nutrients vary spatiotemporally, and highly depend on the specific properties of estuarine systems [29,30]. These distinguished processes are involved with the nutrient requirements for primary producers; related environmental pollution with economic impacts are associated with nutrient over-enrichment. However, the importance of estuarine processes for determining the spatiotemporal variations of nutrient characteristics has scarcely been documented. And knowledge of how riverine nutrient input influence coastal ecosystems that are different from either the upstream or open sea environments is still being developed. In light of the above discussion, the objectives of this field investigation are designed to (1) assess the seasonality of nutrients and related ecosystem responses in this large-scale estuary; (2) capture the seasonal trends of influencing factors that contribute to eutrophication including dissolved nutrients, chlorophyll a, and dissolved oxygen; and (3) identify factors (e.g., salinity, suspended particulate matter, and river discharge) that influence nutrient enrichment.  (Page 2: Line 43-62)

References:

Chen, Y., Cheng, W., Zhang, H., Qiao, J., Liu, J., Shi, Z., Gong, W., 2019. Evaluation of the total maximum allocated load of dissolved inorganic nitrogen using a watershed coastal ocean Coupled model. Sci. Total Environ. 673, 734–749. https://0-doi-org.brum.beds.ac.uk/10. 1016/j.scitotenv.2019.04.036.

Lu F., Ni H., Liu F., Zeng E.Y., 2009. Occurrence of nutrients in riverine runoff of the Pearl River Delta, South China. J. Hydrol. 376, 107-115. doi:10.1016/j.jhydrol.2009.07.018

Niu L.; Luo X.; Hu S.; Liu F.; Cai H.; Ren L.; Ou S.; Zeng D.; Yang Q., 2020. Impact of anthropogenic forcing on the environmental controls of phytoplankton dynamics between 1974 and 2017 in the Pearl River estuary, China. Ecol. Indic. 116, 106484.

Tao W., Niu L., Liu F., Cai H., Ou S., Zeng D., Lou Q., Yang Q., 2020. Influence of river-tide dynamics on phytoplankton variability and their ecological implications in two Chinese tropical estuaries. Ecol. Indic. 115, 106458. https://0-doi-org.brum.beds.ac.uk/10.1016/j.ecolind.2020.106458

Zhang L., Shi Z., Zhang J., Jiang Z., Huang L., Huang X., 2016. Characteristics of nutrients and phytoplankton productivity in Guangdong coastal regions, South China. Marine Pollution Bulletin 113, 572-578. http://0-dx-doi-org.brum.beds.ac.uk/10.1016/j.marpolbul.2016.08.081

(2) Minor comments: all trendlines need to be darker (example Figure 6)

Response: The authors agreed with the reviewer and have adjusted all the trend lines in the figures (Figures 2-3, and Figures 5-10).

 

Author Response File: Author Response.doc

Reviewer 3 Report

The data reported in the manuscript are interesting, also because they can be compared to a rather long-term information gathered by the Chinese Government in the past decades. The studied area is subjected to several anthropogenic forcings, and the river discharge and sediment loads are well documented. In addition, the number of samples is relevant.

Unfortunately, the description of the data is very confusing and also the interpretation of the results is too much general. Sometimes the interpretation can be affected by some errors, that can depend on wrong cut-paste or not correct English.

I suggest the Authors to deeply rework the text.

 

Material and Methods:

in the Discussion the Authors refer to spring period, please report in the description of the study area which of the samplings is spring and so on.

line 69: please be more specific about what estuarine dynamics are.

lines 74-76: maybe I did not understand exactly, but the monthly water discharge was  40.3 km3 during flood season and 18.2 km3 in the dry one. Have I to multiply 6 times the first and 6 time the second to obtain the yearly value? I think so, having a look to Fig. 2B. But 28.2 km3 as a yearly value for the past years is a too low value. Is it monthly? The same for the sediment load.

line 86: can the Authors better describe the deeper sampling depth? In the upper PRE it seems only 10 m, in the lower PRE more than 30 m. Were the upper PRE deeper samples actually different from the surface ones?

lines 92-99: I’ve tried to find the cited reference, but it was not possible to see all the methods reported in the book. Can the Authors add references for each analysis? What does it mean that the concentrations of SPM were reweighted?

line 106: were the data transformed-normalised-standardised before PCA?

Description of the two-end-member mixing model: is it correct to use as end members values that belong to the analysed data set?

 

Results:

The results are very difficult to read and understand, due to the high number of values that could be summarised in a Table. To provide ranges without indicating where (site and depth) they belong to cannot give a proper information, nor the average values without the sd.

Figure 3 shows too much values, please simplify.

No statistical difference (ANOVA) can be find using the whole data set without a priori ordination of the data. See comment on line 86.

Line 127: it seems that you applied a cluster analysis, if not please use this information in the Discussion, if it is so please describe the method.

The title 3.1 is not correct, the Authors have described also depth-related and site related changes.

Lines 142-143: discussion

No description of T, DO, COD, TN and TP was provided.

The description of the results dealing with the model have to be given in the Results section, not in the discussion, similarly to other statistical results. Use tables.

 

Discussion:

Lines 181-184: I suggest to use these references to support the findings of the study, not as an introduction.

Line 188: define more clearly the interactions between sea and river.

Lines 190-193: Material and Methods.

Line 197 and following: all the correlations, regressions, ANOVAs should be provided with further information, such as number of observation, p, F value. All these data have to be transferred to the Results section.

line 198: it is not possible to say that different values of r indicate higher or lower significance without p values. Correlation cannot say if one variable depends on another one, they simply correlate.

line 201: the level of mixing depends on the presence of stratification. Have the Authors any information related to vertical density?

line 205: the desorption from sediment can be observed as an increase in concentration in the deeper layer. Have the Authors observed such processes?

The explanation for the origin of the higher concentrations of nutrients is rather clear, but too much general and repeated several times. I think we need a more detailed description and interpretation of the data. Some info is reported in the last part of the Discussion (the changes of the anthropogenic pressures, for instance), although general.

Line 215: nutrients don’t settle, particles do.

Line 220-221: can the Authors explain better?

line 224: have the Authors observed wind-wave events or awful meteorological conditions?

line 233: check the sentence.

The interpretation of the model results is arbitrary. The model says that in some date and stations there is an input or a removal of nutrients, but it doesn’t indicate which process is responsible for this. Having a look to the external forcing and to the chlorophyll-a data, I suppose that the anthropogenic inputs are the major responsible of the high DIN values, not the biological recycling. Consider also the bacterial uptake.

Figure 7: what are the numerical limits (upper and lower) of each nutrient deviation to be certain that the difference from 0 is significant?

lines 245-246: check the sentence, but how can a short water residence time influence  phytoplankton?

line 249: not significant

 lines 256-258: why?

line 260: what replenished for P?

line 266: is there any correlation with chlorophyll-a?

lines 268-281: numerical-statistical evidence should be provided.

line 284: please describe briefly the method to calculate E. Maybe this can be provided in M&M and the results in Results.

line 295-296: reference on residence time

line 307: something’s wrong with this sentence. Phytoplankton growth means more photosynthesis, and more oxygen as a by-product. Please, explain it better.

Paragraph 4.3: the biological response was already introduced in the paragraph before.

lines 311-314: if you use the Redfield ratio (N/P=16), why N or P limitation is indicated by 10?

line 324: I can’t find Si limitation.

Line 334: if the PCA results are the same for all the months, why don’t provide only one total PCA?

lines 336-341: except for point 3, the other observations are not so clear. Please, explain better.

line 353: why “however”?

Table 1: Nov 3 is missing.

lines 354-358: this part should be moved to the initial part of Discussion.

Fig. 10. The nutrients, despite a general statistic, do not seem to increase from 2011 to 2016 for DIN and DIP.

lines 375-383: these are mainly the places where DIN comes from, not the reason that is anthropogenic input.

lines 384-386: reference

line 389: I couldn’t find Rhizoctonia in the World Register of Marine Species (WoRMS). What is it?

 

Conclusions: again too much results, please remove the numbers and check for the given conclusions.

Author Response

Comments and Suggestions for Authors:

(1) The data reported in the manuscript are interesting, also because they can be compared to a rather long-term information gathered by the Chinese Government in the past decades. The studied area is subjected to several anthropogenic forcings, and the river discharge and sediment loads are well documented. In addition, the number of samples is relevant.

Unfortunately, the description of the data is very confusing and also the interpretation of the results is too much general. Sometimes the interpretation can be affected by some errors, that can depend on wrong cut-paste or not correct English.

I suggest the Authors to deeply rework the text.

Response: The authors would like to thank the reviewer for the positive and valuable comments on this work. The authors agreed with the reviewer and have the sections of Materials and methods, Results, Discussion, and Conclusions to be rewritten in a more concise and crisp manner. The authors have reconstructed the sections of Results and Discussion. In some paragraphs, the authors mixed the results and discussion, and thus provided a new section of ‘Results and discussion’. The authors also have the whole text proofread by Letpub.

The subheadings in the Results and discussion are presented as:

3.Results and discussion

3.1. Variations in hydrographic properties

3.2. Nutrient dynamics in the aquatic environment

3.2.1. Nutrient distributions

3.2.2. Nutrient ratios (mol:mol) in the water column

3.3. Biological variable (in terms of chlorophyll)

3.4. Cause-effect chains of nutrient distributions

3.3.1. Hydrological factors

3.3.2. Effect of the Pearl River discharge

3.3.3. Contributions to phytoplankton chlorophyll

3.5. Environmental effects of nutrient over-enrichment

3.6. Significance of ecological resources exposed to rapid development of the Pearl River Delta

 

(2) Material and Methods:

in the Discussion the Authors refer to spring period, please report in the description of the study area which of the sampling is spring and so on.

Response: The authors agreed with the reviewer and have provided the related information of sampling sites, shown as:

Four surveys were conducted in the PRE in 2016 (Feb, May, Aug, and Nov). The sampling site locations, named P01-45, are presented in Figure 1. All the sampling sites were designed for four seasons. (Page 4: Line 81-83)

 

(3) line 69: please be more specific about what estuarine dynamics are.

Response: The authors agreed with the reviewer and have added the specific characteristics of estuarine dynamics, shown as:

The case study area was divided into different zones according to the estuarine dynamics of interactions between seawater currents and freshwater inflow: upper-PRE (< 10‰), middle-PRE (10-20‰), and lower-PRE (> 20‰). (Page 3: Line 70-72)

 

(4) lines 74-76: maybe I did not understand exactly, but the monthly water discharge was 40.3 km3 during flood season and 18.2 km3 in the dry one. Have I to multiply 6 times the first and 6 time the second to obtain the yearly value? I think so, having a look to Fig. 2B. But 28.2 km3 as a yearly value for the past years is a too low value. Is it monthly? The same for the sediment load.

Response: The authors agreed with the reviewer and have adjusted the confused sentences. The units and data of water discharge and sediment load have been checked.

It is shown as:

The Pearl River has the second highest freshwater discharge of rivers in China (333.8 Km³/yr), only behind the Changjiang River (951.3 Km³/yr). The monthly and yearly variations in freshwater discharge and sediment load are displayed in Figure 2. The seasonal variation in hydrology in 2016 is significant; the monthly water discharge was 40.3 Km³ (Apr-Sep) and 18.2 Km³ (Jan-Mar, Oct-Dec) in the flood and dry seasons, respectively, with the corresponding monthly sediment loads of 3.6 Mt and 0.8 Mt. The annual water discharge and sediment load over the past two decades (1997–2016) were 281.8 Km³/yr and 34.9 Mt/yr, respectively. (Page 3: Line 73-79)

(5) line 86: can the Authors better describe the deeper sampling depth? In the upper PRE it seems only 10 m, in the lower PRE more than 30 m. Were the upper PRE deeper samples actually different from the surface ones?

Response: The authors agreed with the reviewer and have adjusted the related description of sampling in the water column. Two layers were collected at some sampling sites when the depth was less than 15 m, and six layers were collected when the depth was larger than 15 m. Our study examined the seasonality of nutrient dynamics, identified related environmental responses, and evaluated how river discharge regulated nutrient sink and source. The samples at surface and bottom layers were focused. Vertically, nutrient concentrations decreased over the water depth, levels at the surface waters higher than that at the bottom.

It is shown as:  

Water samples were collected in Niskin bottles mounted on a rosette sampler according to the specification of marine monitoring (GB17378-2007). Surface samples were collected when the water depth was less than 5 m; samples at surface and bottom layers were collected when the water depth was at 5-15 m; six layers were collected when the depth was larger than 15 m. (Page 4: Line 90-93)

 

(6) lines 92-99: I’ve tried to find the cited reference, but it was not possible to see all the methods reported in the book. Can the Authors add references for each analysis? What does it mean that the concentrations of SPM were reweighted?

Response: The authors agreed with the reviewer. The collection, storage, transportation, and processing of all water samples were followed the requirements of ‘Specification of Marine Monitoring’ (GB17378-2007) and ‘Specification of Oceanographic Survey’ in China (GB12763-2007). The authors have added the details of sample analysis in the section of Materials and methods (Table 1; Page 5). The concentration of suspended particulate matter (SPM) was weighed in lab using gravimetric analysis.

GB 17378.4-2007. The specification for marine monitoring—Part 4:Seawater analysis. 2007, p160.

(7) line 106: were the data transformed-normalised-standardised before PCA?

Response: The authors agreed with the reviewer. In this study, principal component analysis (PCA) was introduced to test the strength of the linear associations between environmental variables, and to distinguish the major factors which represented the most variances. The data should be processed (e.g., normalization, standardization) before PCA because the variables have different units and inconsistency.

 

(8) Description of the two-end-member mixing model: is it correct to use as end members values that belong to the analysed data set?

Response: The authors agreed with the reviewer. The authors have checked the model and its application in this estuary. The end-member mixing model was based on mass balance equations for potential salinity, water temperature, and the fractions of freshwater and seawater in estuary where strong interactions between freshwater and seawater occurred. In this study, the two end-member mixing model was performed to differentiate the physically induced alterations in dissolved nutrients (DIN, DIP, DSi) from the biological uptake in this estuary system, as used in the previous studies (Han et al., 2012; Wu et al., 2016; and Li et al., 2017). This model qualitatively described the nutrient sink and source in estuary.

References:

Han A., Dai M., Kao S., Gan J., Li Q., Wang L., Zhai W., Wang L., 2012. Nutrient dynamics and biological consumption in a large continental shelf system under the influence of both a river plume and coastal upwelling. Limnology and Oceanography 57, 486-502.

Li, R., Xu, J., Li, X., Shi, Z., Harrison, P., 2017. Spatiotemporal variability in phosphorus species in the Pearl River estuary: influence of the river discharge. Scientific Reports 7, 13649.

Wu M., Hong Y., Yin J., Dong J., Wang Y., 2016. Evolution of the sink and source of dissolved inorganic nitrogen with salinity as a tracer during summer in the Pearl River Estuary. Scientific Reports 6, 36638.

 

(9) Results:

The results are very difficult to read and understand, due to the high number of values that could be summarised in a Table. To provide ranges without indicating where (site and depth) they belong to cannot give a proper information, nor the average values without the sd.

Response: The authors agreed with the reviewer and have adjusted the confused descriptions. The authors have provided a table (Table 1; Page 5) to summarize the basic statistics (min, max, mean, and standard deviation) of water quality indicators. The authors described the data as mean±SD in the main text.

(10) Figure 3 shows too much values, please simplify.

Response: The authors agreed with the reviewer and have simplified Figure 3. A new Table 1 has been added to display the basic information of water quality parameters (see Response 9).

 

(11) No statistical difference (ANOVA) can be find using the whole data set without a priori ordination of the data. See comment on line 86.

Response: The authors agreed with the reviewer. Analysis of variance (ANOVA) was used to examine whether nutrient concentrations differed spatially among stations in various water quality. The data preparation of ANOVA, Pearson correlation, and PCA was processed in IBM SPSS Statistics. The data should be standardized prior the analysis. Several statistical analyses were applied in this study, and the main results were displayed in the text. In the correlation analysis, the level of statistical significance less than 0.05 was defined as statistically significant.

(12) Line 127: it seems that you applied a cluster analysis, if not please use this information in the Discussion, if it is so please describe the method.

Response: The authors agreed with the reviewer. The details of cluster analysis for distinguishing the turbidity maximum zone has been described in our previous study (Tao et al., 2020). Herein, only simple introduction was presented to support this work.

A turbid zone (TZ) with high SPM concentrations was found near the west shoal [16]. (Page 6: Line 154)

Reference:

Tao W.; Niu L.; Liu F.; Cai H.; Ou S.; Zeng D.; Lou Q.; Yang Q. Influence of river-tide dynamics on phytoplankton variability and their ecological implications in two Chinese tropical estuaries. Ecol. Indic., 2020, 115, 106458.

(13) The title 3.1 is not correct, the Authors have described also depth-related and site related changes.

Response: The authors agreed with the reviewer and have changed the title of section 3.1, shown as:

3.1 Variations in hydrographic properties (Page 6: Line 140)

 

(14) Lines 142-143: discussion

No description of T, DO, COD, TN and TP was provided.

Response: The authors agreed with the reviewer and have added the related information in the text (see Table 1; Page 5).

(15) The description of the results dealing with the model have to be given in the Results section, not in the discussion, similarly to other statistical results. Use tables.

Response: The authors agreed with the reviewer. Some discussion were shown in the section of Results, and some results were also shown in the section of Discussion. The authors mixed them into a new section of Results and discussion, and have re-constructed this section. The Pearson correlations of nutrient levels and hydrological factors were displayed in the table below. In the manuscript, the contributions of salinity and SPM, indicators of marine currents and river inflow, were plotted in Figure 6. And the discussion on the influences of DO and COD was related to eutrophication and phytoplankton chlorophyll (Figure 8 and 9). For the two end-member model, two much information were involved in the calculation (such as the results in Feb as follows), the authors thus presented them in a figure (Figure 7).

(16) Discussion:

Lines 181-184: I suggest to use these references to support the findings of the study, not as an introduction.

Response: The authors agreed with the reviewer and have moved these sentences into the main text to support our study. The first sentence was moved to section 3.2 Nutrient dynamics in the aquatic environment, shown as:

The PRE was characterized by nutrient enrichment. Dissolved nutrient concentrations such as DIN, DIP, and DSi showed significant variability, temporally and spatially. Nutrients exhibited a clear decreasing trend along the salinity gradient. (Page 7: Line 159-161)

The second sentence was moved to Introduction, shown as:

Any changes in riverine nutrient input and their forms can cause alterations of the associated marine community and might shape the ecological stability [1, 5]. (Page 2: Line 24-26)

 

(17) Line 188: define more clearly the interactions between sea and river.

Response: The authors agreed with the reviewer and have provided the specific information of interactions between sea and water, shown as:

Strong interactions between sea and river reduced the residence time of dissolved nutrients in the water column, and would promote the vertical exchange, which then resulted in a change of phytoplankton distribution [43]. In the winter, the mixing of weak freshwater and strong marine current diluted the nutrient concentration; in the summer, the mixing of weak marine current and strong river flow carried more nutrients. (Page 10: Line 222-226)

 

(18) Lines 190-193: Material and Methods.

Response: The authors agreed with the reviewer and have moved these sentences to the subsection 2.3 Statistical analysis of Materials and methods, shown as:

Horizontal distributions of observed nutrients were plotted with Golden Software Surfer 13 (Golden Software, Inc., Golden, CO, USA). Correlations between variables were tested with Pearson correlation. Analysis of variance (ANOVA) was used to examine whether nutrient concentrations differed spatially among stations in various water quality and phytoplankton chlorophyll. The dilution-mixing process of oceanic current on dissolved nutrients was discussed through the interplay between salinity and nutrients. The role of suspended sediment on the dissolved nutrients was investigated by the regression analysis. Principal component analysis (PCA) was introduced to test the strength of the linear associations between chlorophyll and associated environmental variables [32, 33]. Principal components (PCs) with eigenvalues greater than 1 were extracted. A method of varimax rotation (Kaiser normalization) generated more meaningful representations of the underlying PCs. The data preparations for PCA, linear regression, and Pearson correlation analyzes were conducted using the statistical package IBM SPSS Statistics 26. (Page 5: Line 107-118)

(19) Line 197 and following: all the correlations, regressions, ANOVAs should be provided with further information, such as number of observation, p, F value. All these data have to be transferred to the Results section.

Response: The authors agreed with the reviewer. The authors have mixed the sections of Results and Discussion which could be more suitable for presenting the results and discussing them. The Pearson correlation results between nutrients and salinity are shown as:

Considering the in-depth analysis, the Pearson correlations between salinity and various dissolved nutrients were significant: R = -0.65, -0.93, -0.49, -0.45, and -0.93 for NO₂, NO₃, NH₄, PO₄, and SiO₄ in the surface waters (N= 180 for each variable; p< 0.01, two-tailed); R = -0.77, -0.94, -0.50, -0.69, and -0.93 in the bottom layer (N=157 for each variable; p<0.01, two-tailed), respectively. Moreover, the influence of salinity on nitrogen and silicate was stronger than that on phosphorus. (Page 10: Line 230-235)

 

(20) line 198: it is not possible to say that different values of r indicate higher or lower significance without p values. Correlation cannot say if one variable depends on another one, they simply correlate.

Response: The authors agreed with the reviewer and have added the significance level in the text. In the correlation analysis, the level of statistical significance less than 0.05 was defined as statistically significant (p< 0.05).  

(21) line 201: the level of mixing depends on the presence of stratification. Have the Authors any information related to vertical density?

Response: The authors agreed with the reviewer. The authors have calculated the layering efficiency (LE), an indicator of water mixing, described as: , in which ΔS was the salinity difference between the surface layer and the bottom layer and  the vertically averaged salinity. The LE ranged at 0.0005-1.46. Most of LE values fluctuated between 0.01 and 1, suggesting a partial mixing in this case; when the LE values larger than 1 indicated a high mixing.

 

(22) line 205: the desorption from sediment can be observed as an increase in concentration in the deeper layer. Have the Authors observed such processes?

Response: The authors agreed with the reviewer. Actually, the authors did not do these kinds of experiments for investigating the adsorption/desorption of nutrients from sediments in the aquatic environment. The authors simply discussed the implied information from the results and previous studies (Lai and Lam, 2008; Wang et al., 2010; Nguyen et al., 2019). The authors will improve the P process and its reactivity with sediment in future.

References:

Lai, D.Y.F., Lam, K.C., 2008. Phosphorus retention and release by sediments in the eutrophic Mai Po Marshes, Hong Kong. Marine Pollution Bulletin 57, 349-356. https://0-doi-org.brum.beds.ac.uk/10.1016/j.marpolbul.2008.01.038.

Nguyen T.T.N., Némery J., Gratiot N., Garnier G., Strady E., Tran V.Q., Nguyen A.T., Nguyen T.N.T., Golliet C., Aimé J., 2019. Phosphorus adsorption/desorption processes in the tropical Saigon River estuary (Southern Vietnam) impacted by a megacity. Estuarine, Coastal and Shelf Science 227, 106321. https://0-doi-org.brum.beds.ac.uk/10.1016/j.ecss.2019.106321

Wang, Q., Li, Y., 2010. Phosphorus adsorption and desorption behavior on sediments of different origins. Journal of Soils and Sediments 10, 1159-1173. https://0-doi-org.brum.beds.ac.uk/10.1007/s11368-010-0211-9.

(23) The explanation for the origin of the higher concentrations of nutrients is rather clear, but too much general and repeated several times. I think we need a more detailed description and interpretation of the data. Some info is reported in the last part of the Discussion (the changes of the anthropogenic pressures, for instance), although general.

Response: The authors agreed with the reviewer and have the section of Results and discussion to be improved. The authors have checked the explanations and have deleted the repeated descriptions. The subheadings in the Results and discussion are presented as:

3.Results and discussion

3.1. Variations in hydrographic properties

3.2. Nutrient dynamics in the aquatic environment

3.2.1. Nutrient distributions

3.2.2. Nutrient ratios (mol:mol) in the water column

3.3. Biological variable (in terms of chlorophyll)

3.4. Cause-effect chains of nutrient distributions

3.3.1. Hydrological factors

3.3.2. Effect of the Pearl River discharge

3.3.3. Contributions to phytoplankton chlorophyll

3.5. Environmental effects of nutrient over-enrichment

3.6. Significance of ecological resources exposed to rapid development of the Pearl River Delta

(24) Line 215: nutrients don’t settle, particles do.

Response: The authors agreed with the reviewer and have adjusted the misused sentence, shown as:

The destination of nutrients was either dissolved in the waters, or adsorbed onto the suspended sediments. (Page 11: Line 249-250)

(25) Line 220-221: can the Authors explain better?

Response: The authors agreed with the reviewer and have changed the sentence, shown as:  

The influence of SPM on silicate was stronger than that on nitrogen and phosphorus. (Page 11: Line 254-255)

 

(26) line 224: have the Authors observed wind-wave events or awful meteorological conditions?

Response: The authors agreed with the reviewer and would like to thank the reviewer for the valuable comments. The extreme events (e.g., storm events, typhoon, or other meteorological events) would moderately or significantly influence the nutrient distributions in estuary. No extreme event data were detected during our field work. The authors will investigate the related study in future.

(27) line 233: check the sentence.

Response: The authors agreed with the reviewer and have improved the sentence, shown as:

Variations in nutrient dynamics were largely modulated by biological uptake processes, combined with the effects of physical mixing. (Page 11: Line 267-268)

 

(28) The interpretation of the model results is arbitrary. The model says that in some date and stations there is an input or a removal of nutrients, but it doesn’t indicate which process is responsible for this. Having a look to the external forcing and to the chlorophyll-a data, I suppose that the anthropogenic inputs are the major responsible of the high DIN values, not the biological recycling. Consider also the bacterial uptake.

Response: The authors agreed with the reviewer and have adjusted the related sentences. The authors have provided more details of the nutrient sink and source in the manuscript, have deleted the repeated information, and have improved the interpretation.

It is shown as:

3.4.2. Effects of the Pearl River discharge

Seasonal change in the Pearl River discharge significantly impacted both the hydrographic factors and nutrient dynamics in the PRE. Variations in nutrient dynamics were largely modulated by biological uptake processes, combined with the effects of physical mixing. The plot of nutrient deviation against salinity identified the physical mixing and other biological response (Figure 7). It is observed that the main activity of DIN showed removal in the estuary according to the conservative values in Feb, May, and Aug. And in Nov, removal and production of DIN equally dominated. Among these, the DIN removal during the dry season (as in Feb, Nov) was mainly caused by the estuarine mixing with the reduction of river discharge; and during the flood season (as in May, Aug), they were mainly caused by the biological uptake, corresponding to the high chlorophyll levels (mean 4.2 μg/L) and lower DO (mean 5.5 mg/L). The silicate activities has similar behaviors to nitrogen along the salinity gradient. To be different, the DIP in the dry season shown to be an addition induced by a buffer mechanism [29], particularly in the middle and lower estuary; it appeared to be a deficit in the flood season, caused by the biological uptake. (Page 11: Line 266-278)

 

These DIN results suggested that the main N addition was intended to the land-based sources (e.g., sewage emissions from coastal cities) and internal nitrogen cycling [34] because of the weak river discharge with relatively lower amount of nutrients. The nitrogen input was mainly from river inflow. The DIN concentrations in many samples were relatively higher in the western zone of the PRE than the levels predicted from the simple effects of physical processes. Strong interactions during summer potentially decreased the residence time of dissolved nutrients, and may promoted the desorption of nutrients from suspended particles. The relatively short residence time of water with extremely high nutrient concentration was thus one of the driving factors that probably controlled the phytoplankton variability [47, 48]. The phytoplankton chlorophyll level was relatively high, thus nitrogen may be also removed by the sedimentation of microorganisms [29]. However, the relationship between chlorophyll and DIN was not significant (p>0.05). Vertical mixing was weak in the western and northern zones of the PRE where the salinity level was low and the freshwater inflow was strong (Figure 3). The net nitrogen removal efficiency was probably confined by the N regeneration from particulate organic matter [36]. For example, nitrogen species were potentially discharged into the estuarine system through different paths such as land-based runoff, effluent discharges, atmospheric deposition, and the degradation of microorganisms [36, 37]. (Page 12: Line 279-294)

 

The DIP removal was induced by phytoplankton uptake and absorption process on sediment in May and Aug while phosphorus production that detected in Nov was probably caused by the phosphorus replenishment (e.g., sewage discharge, atmospheric deposition). These positive and negative DIP deviations also demonstrated that the P species mainly derived from the effluent discharge in the upper PRE, as the freshwater end-member, rather than the riverine input; in the middle estuary, they were derived from the terrestrial emissions of coastal cities such as Dongguan, Zhuhai, and Shenzhen; in the lower estuary, land-based sources from Zhuhai, HongKong, and Macao contributed much. Considering the humamn activities (e.g., dam constructions in the upper channel), the decreased sediment load would influenced the amount of P species due to their capacity of desorption/absorption to P. The DSi deviation had similar behavior to DIN along the salinity gradient. Rapid removal of DSi often occurred in the region of low salinity (<10‰) of the estuary. The input of DSi largely came from river discharge, and their removal was mostly uptake by the pelagic and benthic diatoms. (Page 12: Line 295-307)

 

In summary, an analysis of the interplay between salinity and nutrients (R= -0.93, -0.45, and -0.92 for DIN, DIP, and DSi, respectively; p<0.05) incorporating the marine water and river discharge provided an effective way to distinguish the sinks and sources of nutrients in the PRE. Sewage treatment plants and other nutrient inputs from the surrounding regions, especially from the large city groups of Guangzhou, Dongguan, Zhuhai, and Shenzhen were important contributors to the estuarine pollutants. Atmospheric deposition was also another important nutrient source. The removal of DIN was different from DIP and DSi, with a special mechanism involved in DIN removal in the specific estuary; DIN was less active to sediment particles but removed by biological processes such as denitrification behavior in estuary. Meanwhile, DIP was strongly particle active and was easily adsorbed on sediments. These factors resulted in different degrees of nutrient dynamics for different nutrients. In addition, geomorphology, water age, and other environmental factors also influenced the behaviors of estuarine nutrients. Consequently, the sinks and sources of nutrients strongly depended on specific characteristics of the estuarine systems. Therefore, individual strategies for managing the aquatic environment of the PRE are required to effectively reduce riverine inputs to sea waters. (Page 13: Line 308-321)

 

(29) Figure 7: what are the numerical limits (upper and lower) of each nutrient deviation to be certain that the difference from 0 is significant?

Response: The authors agreed with the reviewer. The end-member model was based on the mass balance equations. The nutrient deviations were calculated according to the differences between the observed nutrients and conservative mixing values which supposed no extra nutrient activities along the salinity gradient. The difference reflected the amount of nutrients produced (negative) or removed (positive) associated with biological processes. The difference equal to 0 indicated that the nutrient remove was balanced by the input. During summer, the nutrient dynamics were largely modulated by biological uptake (corresponding to the higher values of chlorophyll), and during winter, nutrient activities were controlled by the physical mixing. The levels of nutrient deviation also showed the degree of nutrient activities. The limit of each deviation was calculated using the 95% confidence interval (α=0.05), mean value (μ), and standard deviation (σ): lower limit= μ-n*σ; upper limit= μ+n*σ (n=1.96 when α=0.05).

(30) lines 245-246: check the sentence, but how can a short water residence time influence phytoplankton?

Response: The authors agreed with the reviewer and have improved the interpretation. The residence time is a convenient parameter representing the time scale of physical transport processes, and often used for comparison with time scales of biogeochemical processes (Wang et al., 2004; Delhez and Deleersnijder, 2010). During summer (e.g., May, August), strong interactions of river and sea decreased the residence time of dissolved or particulate nutrients in the estuary, which would then influence the biological uptake. Moreover, the occurrence of eutrophication problems can be related to the increased residence time in coastal waters ( Wang et al., 2004).

It is shown as:

Strong interactions during summer potentially decreased the residence time of dissolved nutrients, and may promoted the desorption of nutrients from suspended particles. The relatively short residence time of water with extremely high nutrient concentration was thus one of the driving factors that controlled the phytoplankton variability [47, 48]. (Page 12: Line 283-287)

 

References:

Delhez E.J.M., Deleersnijder E., 2010. Residence time and exposure time of sinking phytoplankton in the euphotic layer. Journal of Theoretical Biology 262, 505-516. https://0-doi-org.brum.beds.ac.uk/10.1016/j.jtbi.2009.10.004

 

Wang C., Hsu M., Kuo A.Y., 2004. Residence time of the Danshuei River estuary, Taiwan. Estuarine, Coastal and Shelf Science 60, 381-393. doi:10.1016/j.ecss.2004.01.013

 

(31) line 249: not significant

Response: The authors agreed with the reviewer and have changed the sentence, shown as:

However, the relationship between chlorophyll and DIN was not significant (p>0.05). (Page 12: Line 288-289)

 

(32) lines 256-258: why?

Response: The authors agreed with the reviewer and adjusted the interpretation. The sentence stated the statistics of DIP deviations in four seasons, and the following sentence explained the results, shown as:

The DIP removal was induced by phytoplankton uptake and absorption process on sediment in May and Aug while phosphorus production that detected in Nov was probably caused by the phosphorus replenishment (e.g., sewage discharge, atmospheric deposition). (Page 12: Line 295-297)

 

(33) line 260: what replenished for P?

Response: The authors agreed with the reviewer and have improved the explanation. The major P species were derived from land-based sources, accounting for ~99%, and the sources of atmospheric deposition and marine currents were only contributed 1%. Among the land-based sources, sewage discharge was the first contributor to P sources.

It is shown as:

The DIP removal was induced by phytoplankton uptake and absorption process on sediment in May and Aug while phosphorus production that detected in Nov was probably caused by the phosphorus replenishment (e.g., sewage discharge, atmospheric deposition). (Page 12: Line 295-297)

 

(34) line 266: is there any correlation with chlorophyll-a?

Response: The authors agreed with the reviewer. The nutrient deviations were closely correlated with the distribution of chlorophyll. The authors have improved these kinds of discussion in the manuscript.

 

(35) lines 268-281: numerical-statistical evidence should be provided.

Response: The authors agreed with the reviewer and have added the related information in the paragraph, shown as:

In summary, an analysis of the interplay between salinity and nutrients (R= -0.93, -0.45, and -0.92 for DIN, DIP, and DSi, respectively; p<0.05) incorporating the marine water and river discharge provided an effective way to distinguish the sinks and sources of nutrients in the PRE. (Page 13: Line 308-310)

 

(36) line 284: please describe briefly the method to calculate E. Maybe this can be provided in M&M and the results in Results.

Response: The authors agreed with the reviewer and have added the method of eutrophication in the section of Materials and methods, shown as:

To evaluate water quality in estuary, eutrophication level (E) was introduced to identify the nutrient-related pollution [16], E=DIN×DIP×COD×106/4500. Water bodies were classified as slight eutrophic when the eutrophication was larger than 1 (E>1), moderately eutrophic when 1<E<5, and severe eutrophic when E>5. (Page 5: Line 119-122)

 

(37)line 295-296: reference on residence time

Response: The authors agreed with the reviewer and have added the related references on the residence time, shown as:

The waters at the mouth of the PRE had a longer residence time, and the pollutants diffused slowly during movement of the water column [47, 48]. (Page 15: Line 365-366)

 

(38) line 307: something’s wrong with this sentence. Phytoplankton growth means more photosynthesis, and more oxygen as a by-product. Please, explain it better.

Response: The authors agreed with the reviewer and have adjusted the sentence, shown as:

Higher E values tended to the more active activities of marine organisms, the phytoplankton growth was thus promoted in the water body, and more oxygen was consumed [53]; the degradation of organic pollutants also required the consumption of DO, which would lead to decreased DO; the non-significant correlation (e.g., in Feb) indicated that the DO distribution was not only related to influences of seawater and temperature, but also related to the DO input from river inflow and rainfall. The oxygen levels were negatively correlated with the trends of phytoplankton chlorophyll (R= -0.88). The oxygen balance was also an indicator of the condition of the entire ecosystem. (Page 15: Line 375-382)

 

(39) Paragraph 4.3: the biological response was already introduced in the paragraph before.

Response: The authors agreed with the reviewer and have re-constructed the section of ‘Results and discussion’. The authors have deleted the repeated sentences and have improved the main text.

 

(40) lines 311-314: if you use the Redfield ratio (N/P=16), why N or P limitation is indicated by 10?

Response: The authors agreed with the reviewer. The optimal Redfield atomic ratio for N:P:Si was 16:1:16. In this investigation, the improved nutrient limitations based on the Redfield ratio were applied. It is shown as:

The optimal Redfield atomic ratio for N:P:Si was 16:1:16, which was the stoichiometric requirement for phytoplankton growth [49, 50]. The improved nutrient limitations based on the Redfield ratio were applied in this investigation [50], shown as follows: N was limiting if N:P<10 and Si:N>1, P was limiting when Si:P>22 and N:P>22, and Si was limiting if Si:P<10 and Si: N<1. (Page 13: Line 323-326)

 

(41) line 324: I can’t find Si limitation.

Response: Silicate levels only influenced the amount of diatoms. The silicate limitation was determined if Si:P<10 and Si:N<1 (Page 13: Line 326). Nutrient atomic ratios were displayed in Figure 5, only several sites were classified as silicate limitation, and the aquatic environment was P-limited in most of the PRE.

(42) Line 334: if the PCA results are the same for all the months, why don’t provide only one total PCA?

Response: The authors agreed with the reviewer. Similar contributions of nutrients and hydrological factors on the phytoplankton chlorophyll were detected in Feb, May, Aug, and Nov. The authors thus provided a total plot to show all the information of four seasons (Page 14: Figure 8).

(43) lines 336-341: except for point 3, the other observations are not so clear. Please, explain better.

Response: The authors agreed with the reviewer and have improved the explanation, shown as:

These PCA findings demonstrated the underlying mechanisms involved in environmental stress: the role of salinity on affecting the level of nutrients was significant; negative correlations between salinity and nutrients co-influenced phytoplankton growth; the direct role of SPM on chlorophyll was not significant; the contribution of P element on the chlorophyll was stronger than nitrogen and silicate. (Page 14: Line 349-353)

(44) line 353: why “however”?

Response: The authors agreed with the reviewer. The word of ‘However’ herein was misused and has been deleted.

It is shown as:

Compared with many coastal waters worldwide, nutrient concentrations were still relatively high in the PRE, such as the Cross River [39], Caeté estuary [3], and Cochin estuary [40, 41]. (Page 9: Line 192-194)

 (45) Table 1: Nov 3 is missing.

Response: PCA was introduced to test the strength of the linear associations between phytoplankton chlorophyll and associated environmental variables. Principal components (PCs) with eigenvalues greater than 1 were extracted (a new Table 2; Page 14). In Feb, May, and Aug, three components (PC1, PC2, and PC3) were extracted to represent the most variances; and in Nov, two components (PC1 and PC2) were extracted.

(46) lines 354-358: this part should be moved to the initial part of Discussion.

Response: PCA The authors agreed with the reviewer and have moved these sentences into the subsection ‘3.2 Nutrient dynamics in the aquatic environment’, behind the paragraph of describing the nutrient distributions.

The PRE was regarded as having severely polluted waters caused by rapid industrialization and urbanization of the last few decades, compared with levels in some other estuarine systems. The DIN levels in this area were higher than in some large estuaries in China, such as the Yangtze [36, 37] and Yellow River estuaries [38]. Compared with many coastal waters worldwide, nutrient concentrations were still relatively high in the PRE, such as the Cross River [39], Caeté estuary [3], and Cochin estuary [40, 41]. The DIP level in our study was higher than in the Yellow River estuary [38], and was lower than that in the Yangtze estuary [37], which received superfluous P from agricultural or urban waste water. These higher levels of nutrients have raised the urgent need to pay more attention for managing riverine input. (Page 9: Line 189-197)

 (47) The nutrients, despite a general statistic, do not seem to increase from 2011 to 2016 for DIN and DIP.

Response: The authors agreed with the reviewer. The authors presented the historical nutrient data from 1997-2016, which showed a gradually increase. The DIN concentration increased by 109% from 1997 (0.589 mg/L) to 2016 (1.23 mg/L), while PO₄ and DSi increased non-significantly.

It is shown as:

Historical nutrient levels tended to increase gradually, with slope values of 0.043, 0.001, and 0.020 for DIN, DIP, and DSi, respectively, based on Mann-Kendall test [55]. The DIN increased significantly over the past two decades (y = 0.0581x+0.2999, R² = 0.56); both PO₄ (R² = 0.10) and DSi (R² = 0.04) increased non-significantly. Before 1990, the nutrient level was non-eutrophic [56]. After 1990, the nutrient concentrations were increased, and the aquatic environment in the PRE was then classified as eutrophic [4,16,20]. The DIN concentration increased by 109% from 1997 (0.589 mg/L) to 2016 (1.23 mg/L). The mean DIN, DIP, and DSi concentrations over the past two decades were 1.25 mg/L, 0.030 mg/L, and 2.83 mg/L, respectively. In contrast to nitrogen, DSi showed a gradually increasing trend until 2002 and then decreased. The decrease in DSi was attributed to human activity, such as the construction of dams in the upstream channel. (Page 16: Line 394-404)

 

(48) lines 375-383: these are mainly the places where DIN comes from, not the reason that is anthropogenic input.

Response: The authors agreed with the reviewer. This paragraph intended to imply the major nutrient emissions from coastal cities in the upper-, middle-, and lower-PRE, shown as:

The rapid development of industrialization and urbanization in this region has resulted increased levels of the nitrogen species in estuary as a consequence of population growth. There were several possible reasons to explain the above findings. First, the upstream zone at Humen, Jiaomen, Hongqimen, and Hengmen received nutrients and other pollutants from the major economic zones of Guangzhou, Dongguan, and Foshan, which has a maximum contribution to the upper PRE. These cities alone have a population approximately equal to the region of greater Shanghai or about 30 million people (data derived from the Ministry of Natural Resources of the People’s Republic of China, accessible through http://www.mnr.gov.cn/sj/tjgb/). Second, the pollutants released from Shenzhen, Zhuhai, and Zhongshan contributed greatly to the concentration of pollutants in the middle PRE. Thirdly, pollutants from Hong Kong, Zhuhai, and Macao, were the main contributors to the pollutants in the lower PRE. (Page 17: Line 405-415)

(49)lines 384-386: reference

Response: The authors agreed with the reviewer and have added the data sources in the main text, shown as:

Additionally, the common pollutant-related issues in the water bodies of the PRE were high microorganism populations along with increases in organic matter, eutrophication, and oil in the water (Guangdong Provincial Marine Environmental Quality Bulletin, web-link through http://gdee.gd.gov.cn/hjzkgb/content/post_2466217.html). (Page 18: Line 416-419)

 

(50) line 389: I couldn’t find Rhizoctonia in the World Register of Marine Species (WoRMS). What is it?

Response: The authors agreed with the reviewer. The red tide in 2016 was mainly caused by Akashiwo sanguinea and Noctiluca scintillans, which threatened the estuarine environment. The authors have checked the names of red tide algae occurred in 2016, shown as:

The water environmental quality of the PRE in 2016 was detected as eutrophic, which promoted the growth of phytoplankton, triggered bloom events (N = 13); red tide algae, caused by Akashiwo sanguinea and Noctiluca scintillans, and threatened the fishing resources and estuarine environment. (Page 18: Line 420-423)

 

(51) Conclusions: again too much results, please remove the numbers and check for the given conclusions.

Response: The authors agreed with the reviewer and have improved the Conclusions.

The Pearl River estuary (PRE) was affluent in riverine nutrients and was specialized by a strong interplay between marine water and river inflow. The seasonality of nutrient dynamics was significant (p<0.05). Correspondingly, the levels of dissolved nutrients were relatively higher in the flood season than those in the dry season. Increased fluvial discharge distinctly influenced concentrations of nutrients and phytoplankton chlorophyll. Insufficient phosphorus was predominantly discovered in most of the PRE, resulted from the increases of DIN and DSi fluxes. Observed nutrient concentrations deviated from the predicted values induced by the physical mixing, suggesting that both biological uptake and production of nutrients co-occurred in this estuary. Moreover, riverine input was responsible for the aquatic environment in the upper PRE, and the nutrients and other pollutants released from the larger coastal cities of Shenzhen, Zhuhai, Hongkong, and Macao were the major contributors to the nutrient status in the middle and lower PRE. Consequently, the sinks and sources of nutrients were largely controlled by their specific biogeochemical characteristics of the estuarine systems. This field investigation helps us better understand the estuarine environment and determine how nutrient production and consumption are involved with riverine input, salinity gradients, and biological uptake. (Page 18: Line 429-443)

Author Response File: Author Response.doc

Round 2

Reviewer 3 Report

In some places I had again problems with English, can the authors check carefully the text?

page 4 line 81-83. Maybe it seems quite redundant, but can the authors add in the parentheses something like: February- winter, May - spring etc., just because in my country February at sea is generally considered spring and not winter. A simple detail to be clearer.

point (7): so, did the authors use normalisation? Or other transformations? Please specify. The Kaiser normalisation seems to have been applied after PCA.

point (11): use the response in the text to improve point (7).

I think that a distinction between Results and Discussion has to be done. The reader is still overwhelmed by all the numerical information, with the result of losing the observations of the Authors about their data. The Authors have provided tables or figures in the Response, but they did not use them in the text. Some of them would be useful. For instance, the correlation analysis results. The values are given in fig 6, but a table would help and would make the text to be more fluid. Why the authors provided seasonal values for correlations in the response? The same for the end-member-model results. They all can be given as appendix.

 

In table 1 a question mark has to be changed to °C.

 

point (14): the average values of the missing variables have been  given, a little comment would be useful in order to have a better use of these data in PCA.

 

point (15): regarding the deviations given by the model: are the lines added to the figures those indicating the observations where a significant removal or input of nutrients can be found? If so (add in the caption) the number of actual deviations is quite low. Can the authors comment it?

 

point (21): were the LEs useful? Why the authors did not use these evaluations in the text? The LE can be very useful in the 3.1.1 paragraph.

 

point (22): the question remains, the Authors transported the same paragraph to new line 329, indicating that positive correlation between SPM and nutrients means desorption of nutrients from particles (if “desorption of sediment on nutrients” means this). Actually, due to the number of nutrient sources, I don’t think that this process can be demonstrated by simple correlations. In addition, SPM is not strictly sediment, but organic and inorganic particles that can have also a pelagic origin, not entirely benthonic.

 

point (25): the sentence was quite clear, but the observation needs a little reference.

 

point (26): the paragraph mixes literature data with Author observations, that can be useful, but then the Authors need a reference also for the summer re-suspension of sediment. Or this must be supported by the data.

 

point (29): add the information in the text

 

point (30): I think that the residence time data and interpretation should be added to the text, given that they are “a convenient parameter representing the time scale of physical transport processes, and often used for comparison with time scales of biogeochemical processes (Wang et al., 2004; Delhez and Deleersnijder, 2010).”. However, in the text I did not find the answer to my question: I’m sure it is explained by the references 47 and 48, but a simple explanatory sentence would help the reader.

 

point (33) add to the text the information provided in the response (and references).

 

new line 362 (marked manuscript): please explain the buffer mechanism.

 

point (40): please let me understand why the threshold “10” for N and P limitation and the “22” for Si limitation were used instead of 16.

 

point (41): in fact the authors don’t need an explanation for Si, the third point of explanation (lines 448-449 marked manuscript).

 

point (43): OK, except for ammonia. Was it the results of the eutrophication of the system? I mean: higher chlorophyll due to higher DIP, higher organic matter production that leads to higher degradation confirmed by lower DO and higher ammonia concentrations. This is quite trivial, but maybe the literature about the eutrophication of the area can confirm it. The authors have detailed some parts of these processes in the new lines 491-501(marked manuscript) but I think that some improvements can be done. For instance, DO doesn’t contribute to eutrophication, but at least to the E value (subtle but significant difference). Can the authors explain: “Higher E  values   tended  to the  more active  activities  of marine organisms”? How can DO be influenced by rainfall?

 

point (47): please, add p values for DIN.

Author Response

Response to Reviewer #3’s Comments:

Comments and Suggestions for Authors:

In some places I had again problems with English, can the authors check carefully the text?

Response: The authors would like to thank the reviewer for her/his time and the valuable comments on this work. The authors agreed with the reviewer and have carefully proofread the whole text.

page 4 line 81-83. Maybe it seems quite redundant, but can the authors add in the parentheses something like: February- winter, May - spring etc., just because in my country February at sea is generally considered spring and not winter. A simple detail to be clearer.

Response: The authors agreed with the reviewer. The four seasons in China are  generally defined as March-May (spring), June-August (summer), September-November (autumn), and December-February (winter). The seasonal changes of nutrient levels during the flood (April-September) and dry (October-March) seasons were our major concern. The authors have provided the details for defining the flood and dry seasons, shown as:

Seasonal variation  in  hydrology  occurs  in  both  the  flood  (Apr  to  Sep)  and  dry  seasons  (Oct  to  Mar)  [21]. (Page 3: Line 66-67)

point (7): so, did the authors use normalisation? Or other transformations? Please specify. The Kaiser normalisation seems to have been applied after PCA.

Response: The authors agreed with the reviewer. The data should be standardized  before PCA because the variables have different units and inconsistency. To obtain a clear pattern of the factor loadings, we rotated the axes in any direction without any changes. There were many different types of rotations that can be applied after the initial extraction of components. In our analysis, the PCA with an orthogonal rotation method of Varimax with Kaiser normalization was preferred to determine what the components represented. 

It is shown as:

Principal components (PCs) with eigenvalues greater than 1 were extracted. The data were standardized before PCA because the variables had different units and inconsistency. A method of varimax rotation (Kaiser normalization) generated more meaningful representations of the underlying PCs.  (Page 5: Line 115-118)

point (11): use the response in the text to improve point (7).

Response: The authors agreed with the reviewer and have provided the related information in the text (see the above Response).

I think that a distinction between Results and Discussion has to be done. The reader is still overwhelmed by all the numerical information, with the result of losing the observations of the Authors about their data. The Authors have provided tables or figures in the Response, but they did not use them in the text. Some of them would be useful. For instance, the correlation analysis results. The values are given in fig 6, but a table would help and would make the text to be more fluid. Why the authors provided seasonal values for correlations in the response? The same for the end-member-model results. They all can be given as appendix.

 Response: The authors agreed with the reviewer and have provided more details for better understanding the estuarine characteristics of nutrients in the Pearl River estuary. The authors have added the Pearson correlation analysis between nutrients and hydrological factors, shown as a new table (Table 2) in the text.

One of the objectives in the present study was to investigate the seasonal change of nutrients. The seasonal variation of riverine input largely influenced the nutrient distributions in the Pearl River estuary. The authors thus discussed the related issues with season and site. The author have provided the two end-member mixing model results in the text, shown in the supplementary materials (as Table A1 to A4).

In table 1 a question mark has to be changed to °C.

Response: The authors agreed with the reviewer and have changed it in Table 1, shown as:

point (14): the average values of the missing variables have been given, a little comment would be useful in order to have a better use of these data in PCA.

Response: The authors agreed with the reviewer and have provided the related information in the text, shown as:

The basic statistics of water quality indicators were presented in Table 1. The variable of DO ranged from 1.9 to 10.48 mg/L (6.5±1.39 mg/L) in the entire area, and COD varied at 0.19-3.36 mg/L (1.16±0.65 mg/L). (Page 6: Line 142-144)

 

point (15): regarding the deviations given by the model: are the lines added to the figures those indicating the observations where a significant removal or input of nutrients can be found? If so (add in the caption) the number of actual deviations is quite low. Can the authors comment it?

 Response: The authors agreed with the reviewer. The added lines in the Figure 7 indicated the deviation limits at a significant level 0.05. the values outside this range could be identified as extreme values. The authors have provided the related information in the text, shown as:

The levels of nutrient deviation also showed the degree of nutrient activities. The limit of each deviation was calculated using the 95% confidence interval (α=0.05), mean value (μ), and standard deviation (σ): lower limit= μ-n*σ; upper limit= μ+n*σ (n=1.96 when α=0.05). The deviations of nutrients beside the limit lines might indicated the extreme values. (Page 11: Line 278-281)

 

point (21): were the LEs useful? Why the authors did not use these evaluations in the text? The LE can be very useful in the 3.1.1 paragraph.

Response: The authors agreed with the reviewer. The layering efficiency (LE; ) was a useful tool for describing the degree of water mixing. The authors have provided the information in the text, shown as:

The layering efficiency (LE; LE=ΔS/S0) was a useful tool for describing the degree of water mixing. In which, ΔS indicated the salinity difference between the surface layer and the bottom layer and S0 was the vertically averaged salinity. The LE ranged at 0.0005-1.46 in this study. Most of LE values fluctuated between 0.01 and 1, suggesting a partial mixing in this case, and when the LE values larger than 1 indicated a high mixing. (Page 6: Line 152-156)

point (22): the question remains, the Authors transported the same paragraph to new line 329, indicating that positive correlation between SPM and nutrients means desorption of nutrients from particles (if “desorption of sediment on nutrients” means this). Actually, due to the number of nutrient sources, I don’t think that this process can be demonstrated by simple correlations. In addition, SPM is not strictly sediment, but organic and inorganic particles that can have also a pelagic origin, not entirely benthonic.

 Response: The authors agreed with the reviewer. The SPM tended to suspended particulate matter (e.g., sediment, organic matter, microorganisms) in this study. Our present data were not enough to discuss the P process and its reactivity with sediment. The discussion of the correlation between SPM and nutrients were referred to previous studies (Lai and Lam, 2008; Wang et al., 2010; Nguyen et al., 2019). The authors will improve this kind of study in future. The authors have adjusted the sentences in the text, shown as:

In particular, DIP was potentially absorbed onto the iron oxide and then consolidated. SPM thus played a fundamental ecological role as a result of its adsorption and desorption onto the nutrients in the estuarine ecosystems [46, 47]. Generally, P adsorption capacity increased when SPM concentrations increased. (Page 11: Line 261-264)

References:

Lai, D.Y.F., Lam, K.C., 2008. Phosphorus retention and release by sediments in the eutrophic Mai Po Marshes, Hong Kong. Marine Pollution Bulletin 57, 349-356. https://0-doi-org.brum.beds.ac.uk/10.1016/j.marpolbul.2008.01.038.

Nguyen T.T.N., Némery J., Gratiot N., Garnier G., Strady E., Tran V.Q., Nguyen A.T., Nguyen T.N.T., Golliet C., Aimé J., 2019. Phosphorus adsorption/desorption processes in the tropical Saigon River estuary (Southern Vietnam) impacted by a megacity. Estuarine, Coastal and Shelf Science 227, 106321. https://0-doi-org.brum.beds.ac.uk/10.1016/j.ecss.2019.106321

Wang, Q., Li, Y., 2010. Phosphorus adsorption and desorption behavior on sediments of different origins. Journal of Soils and Sediments 10, 1159-1173. https://0-doi-org.brum.beds.ac.uk/10.1007/s11368-010-0211-9.

point (25): the sentence was quite clear, but the observation needs a little reference.

Response: The authors agreed with the reviewer and have provided the related information and reference in the text, shown as:

The influence of SPM on silicate was stronger than that on nitrogen and phosphorus because its strong adsorption capacity onto the SPM [46]. (Page 11: Line 260-261)

point (26): the paragraph mixes literature data with Author observations, that can be useful, but then the Authors need a reference also for the summer re-suspension of sediment. Or this must be supported by the data.

Response: The authors agreed with the reviewer. The authors did not get these kinds of meteorological data, which would moderately or significantly influence the nutrient distributions in estuary (Li et al., 2017). The authors will improve these kinds of investigations in future. The authors have added the related discussion in the text, shown as:

No meteorological data were considered in this study, which would would moderately or significantly influence the nutrient distributions and phytoplankton chlorophyll [53]. (Page 14: Line 357-358)

Reference:

Li Y., Zhang Y., Shi K., Zhu G., Zhou Y., Zhang Y., Guo Y., 2017. Monitoring spatiotemporal variations in nutrients in a large drinking water reservoir and their relationships with hydrological and meteorological conditions based on Landsat 8 imagery. Science of The Total Environment, 599–600, 1705-1717.

point (29): add the information in the text

 Response: The authors agreed with the reviewer and have added the related information in the text, shown as:

The plot of nutrient deviation against salinity identified the physical mixing and other biological response (Figure 7). The levels of nutrient deviation also showed the degree of nutrient activities. The limit of each deviation was calculated using the 95% confidence interval (α=0.05), mean value (μ), and standard deviation (σ): lower limit= μ-n*σ; upper limit= μ+n*σ (n=1.96 when α=0.05). (Page 11: Line 275-280)

 

point (30): I think that the residence time data and interpretation should be added to the text, given that they are “a convenient parameter representing the time scale of physical transport processes, and often used for comparison with time scales of biogeochemical processes (Wang et al., 2004; Delhez and Deleersnijder, 2010).”. However, in the text I did not find the answer to my question: I’m sure it is explained by the references 47 and 48, but a simple explanatory sentence would help the reader.

Response: The authors agreed with the reviewer and have provide more details for the residence time in the text, shown as:

The relatively short residence time of water with extremely high nutrient concentration was thus one of the driving factors that controlled the phytoplankton variability [48, 49]; the residence time was a convenient parameter representing the time scale of physical transport processes, and often used for comparison with time scales of biogeochemical processes.  (Page 12: Line 297-301)

 

point (33) add to the text the information provided in the response (and references).

Response: The authors agreed with the reviewer and have added the related information in the text, shown as:

The major P species were derived from land-based sources, accounting for ~99%, and the sources of atmospheric deposition and marine currents were only contributed 1%; among the land-based sources, sewage discharge was the first contributor to P sources [46, 50]. (Page 13: Line 309-311)

 

new line 362 (marked manuscript): please explain the buffer mechanism.

Response: The phosphorus buffer mechanism described the ability of sediment to regulate the concentrations of DIP in the water and kept them at almost constant levels over prolonged time periods. During the dry season, the physical mixing largely influenced the nutrient activities, and during the flood season the biological uptake was the main dominant.

point (40): please let me understand why the threshold “10” for N and P limitation and the “22” for Si limitation were used instead of 16.

Response: The authors agreed with the reviewer. The authors have adjusted the nutrient limitation according to the Redfield ratios (N:P:Si=16:1:16), shown as:

 

Figure 5. Scatter diagrams of atomic Redfield ratios in the Pearl River estuary

point (41): in fact the authors don’t need an explanation for Si, the third point of explanation (lines 448-449 marked manuscript).

Response: The authors agreed with the reviewer and have deleted this sentence.

point (43): OK, except for ammonia. Was it the results of the eutrophication of the system? I mean: higher chlorophyll due to higher DIP, higher organic matter production that leads to higher degradation confirmed by lower DO and higher ammonia concentrations. This is quite trivial, but maybe the literature about the eutrophication of the area can confirm it. The authors have detailed some parts of these processes in the new lines 491-501(marked manuscript) but I think that some improvements can be done. For instance, DO doesn’t contribute to eutrophication, but at least to the E value (subtle but significant difference). Can the authors explain: “Higher E  values   tended  to the  more active  activities  of marine organisms”? How can DO be influenced by rainfall?

Response: The authors agreed with the reviewer. The phytoplankton chlorophyll was shown as P-limited in this Pearl River estuary (Yin et al., 2004; Zhang et al., 2013; Gan et al., 2014; Li et al., 2017). Compared with the nitrogen, the phosphate level was deficit in this estuary and was considered the key nutrient factor controlling the eutrophication. Eutrophication was caused by the nutrient over-enrichment which would promoted the phytoplankton growth. Rapid phytoplankton growth must accompanied the death, and then microbial decomposition consumed oxygen. There were no direct relationships between rainfall and DO. Actually, atmospheric deposition was one of nutrient sources, particularly the organic nutrients. The authors have improved the sentences, shown as:

Higher E values tended to the more active activities of marine organisms, the phytoplankton growth was thus promoted in the water body, and more oxygen was consumed [55]; the degradation of organic pollutants also required the consumption of DO, which would lead to decreased DO; the non-significant correlation (e.g., in Feb) indicated that the DO distribution was not only related to influences of seawater and temperature, but also related to the DO input.  (Page 15: Line 388-393)

 

References:

Gan J.; Lu Z.; Cheung A.; Dai M.; Liang L.; Harrison P.J.; Zhao X. Assessing ecosystem response to phosphorus and nitrogen limitation in the Pearl River plume using the Regional Ocean Modelling system (ROMS). J. Geophys. Res. Oceans, 2014, 119, 8858-8877.

Li, R.; Xu, J.; Li, X.; Shi, Z.; Harrison, P. Spatiotemporal variability in phosphorus species in the Pearl River estuary: influence of the river discharge. Sci. Rep-UK, 2017, 7, 13649.

Yin K.; Song S.; Sun J.; Wu M.C.S. Potential P limitation leads to excess N in the pearl river estuarine coastal plume. Cont. Shelf Res., 2004, 24, 1895-1907.

Zhang X.; Shi Z.; Liu Q.; Ye F.; Tian L.; Huang X. Spatial and temporal variations of picoplankton in three contrasting periods in the Pearl River estuary, South China. Cont. Shelf Res., 2013, 56, 1-12. 521

point (47): please, add p values for DIN.

Response: The authors agreed with the reviewer and have added the p value for DIN, shown as:

The DIN increased significantly over the past two decades (y = 0.0581x+0.2999, p<0.05, R² = 0.56). (Page 16: Line 408-409)

Author Response File: Author Response.pdf

Round 3

Reviewer 3 Report

Please provide always r, n and p for correlations and p for ANOVA, sometimens they are missing.

Fig. 5. X axes missing.

LEs data are missing, the authors described the method, interpretation and min-max values, but no reference in the discussion is given.

The phosphorus buffer mechanism should be explained also in the text.

Please check the sentences and the use of words, sometimes I couldn't understand exactly the meaning of some statements (lines 388-390, for instance), or also the "activity of nutrients", line 385: this is not a contribution but a relationship, title 3.4.3: is this a contribution?