the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 03 Apr 2024
Including the invisible: Deep depth-integrated chlorophyll estimates from remote sensing may assist in identifying biologically important areas in oligotrophic coastal margins
Abstract. Deep chlorophyll maxima (DCM) are common in stratified water columns and may support higher trophic levels. Yet, it is challenging to include DCM contributions in studies aiming to identify marine animal foraging habitats and hotspots, because these studies often rely on satellite remote sensing data restricted to the surface. Previously established quantitative relationships between surface and depth-integrated chlorophyll within the euphotic zone of the open ocean and a eutrophic coastal margin encouraged us to assess whether such relationships are also present within the Western Australian intermittent-oligotrophic coastal margin. We also assessed whether the relationships could be extended to greater depths to capture DCMs below the euphotic zone. Based on ~9600 ocean glider profiles, our analyses demonstrate that such a relationship similarly exists off Western Australia and can be extended to twice the euphotic zone depth. Regression parameters were fine-tuned for three different conditions: 1) stratified waters in summer-transition months (September–April), characterised by relatively deep biomass maxima; 2) stratified waters in mid-winter (May–August) in which DCMs were less common and more likely a photo-acclimation maximum; and 3) mixed waters. While mean absolute errors increased in relationships over twice the euphotic zone depth (i.e., for estimates of deep depth-integrated chlorophyll), they remained low (i.e., max 16.5 %). These results and an observed chlorophyll increase in summer, unique to deep depth-integrated values, highlight the necessity to include deep depth-integrated chlorophyll estimates from satellite remote sensing in studies that aim to identify biologically important areas and productivity anomalies in (intermittent) oligotrophic environments.
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Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Preprint
(5760 KB)
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
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- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2024-859', Anonymous Referee #1, 23 Jun 2024
Brief Summary of the manuscript:
Schoeman and co-authors present evidence on the importance of monitoring deep-depth integrated chlorophyll-a (chla) and phytoplankton biomass based on over 9,000 glider chla fluorescence profiles collected from 2002 to 2022. They compare surface chla concentrations to chla integrated to the euphotic depth (depth-integrated) and chla concentrations integrated to twice the euphotic depth (deep depth-integrated). The authors derive relationships between surface and the two integrated chla concentrations for three different water column conditions: stratified summer, stratified winter, and mixed conditions. They describe the temporal patterns of deep chlorophyll maximum (DCM) occurrence and, within these DCMs, the patterns of deep biomass maximums (DBMs) versus deep acclimation maximums (DAMs). They also provide details on satellite matchups to surface HPLC chla samples and validation. The authors demonstrate that there are increases within the seasonal cycle of deep-depth integrated chla that are not recorded in the seasonal cycle of standard depth-integrated chla. These local deeper increases are biologically important for krill productivity and subsequent whale foraging times.Overall impression:
The results presented in this manuscript are compelling and highlight the increasing importance of including the variability of chla with depth in studies. The study shows how the vertical structure of chla changes seasonally and provides further insight into the potential for monitoring depth-integrated chla using satellite remote sensing data. It suggests that parameters for relationships used should be updated for certain regions. If published, this work could stimulate further discussion about improving satellite-based estimates of depth-integrated chla where DCMs are present. Overall, this manuscript is well-written and well-reasoned. However, there is a need for improved clarity within the method sections, such as the inclusion of a study region map. Additionally, figures could be improved, along with other minor suggestions detailed below.Introduction:
Line 35: Perhaps provide a range or average of the depth to which satellites observe. A good reference here might be Zaneveld et al. 2005 - https://doi.org/10.1364/OPEX.13.009052.
Line 68: This sentence is a bit unclear to what depths was included in these other studies. Did they include deep oceanic samples? the "but" in the sentence makes it unclear and sound unfinished.Methods:
In general, I'm missing some sort of map in the paper. For readers unfamiliar with the region, it would be helpful to have some sort of map showing the study area, some features mentioned in the text such as the Perth Canyon, and perhaps the locations of glider profiles included in the study (if not too crowded) and locations of HPLC samples that could be satellite matched.
Section 2.1: Here the authors state that both the HPLC and glider datasets used are restricted to "between 04 July 2002 and 21 June 2022", please clarify the date ranges of each dataset. Perhaps I have misunderstood the data download process, but according to the AODN delayed mode glider data via the link provided, this online dataset only contains glider data from 2008? If I am mistaken please clarify and/or provide more details on how to download the appropriate glider data.
Section 2.2: Somewhere in this section the reader should be reminded of the total number of glider profiles used after the filtering steps described here. Before this it is only mentioned in the abstract as "~9600" and then again at the beginning of section 3.1 as "We extracted 6438 and 3234 profiles from", unless I missed it.
Line 104-105: It would be interesting to see the authors speculate/comment somewhere here or in the discussion (see comment below) on the potential use of daytime satellite data to infer depth-integrated chla based on relationships derived from nighttime chla profiles. Could this be a limitation that should be acknowledged in the final paragraph of the discussion?
Section 2.3 Line 115: Perhaps I have missed or misunderstood, please clarify here or elsewhere what is meant by profiles that do not cover the Zeu? Have any steps been taken to ensure that profiles cover to a depth of Zeu x2 for the calculation of Chlzeu2?Results:
Section 3.1: It would be easier for new readers to follow these descriptions and get a better idea of the MLD and Zeu characteristics of the study area if there were a plot somewhere here in the main text or in a supplement. Perhaps seasonal box plots or line plots with depth on the y-axis showing both average MLD and Zeu over the seasonal cycle? This might also provide a better background and link to Figure 1. Adding a panel to Figure 1 could also be an option.
Figure 1: I find the addition of the density plot without a y-axis at the top of the figure a bit out of place. Perhaps this seasonal distribution should be shown as a secondary axis in Figure 1 or in another panel. See also other comments below about the addition of a plot showing the annual number of profiles and HPLC samples satellite matched over 2002-2020.
Section 3.2: This whole section will be clearer to a new reader if it shows visually the proportion of DBMs vs. DAMs over a seasonal cycle. Perhaps a figure similar to Figure 1. Either as a supplementary figure or possibly as an additional first panel to Figure 2.
Line 193: Add reference to Figure 1 at end of sentence.
Line 217: Perhaps remind reader here that surface chla concentrations referred to here is the Chlzpd defined in the methods.
Line 221: Remind reader that it is Chlzeu being describe here and similarly in Line 222 that Chlzeu2 is being described.
Figure 3: Increase size of panels numbers (here and all other multi-panel plots) and reduce the amount of blank space at the top of panel (a). Also revise the width of the multi-panel plots with months on the x-axis, here the month text labels are too close together in my opinion and look better in Figure 2.
Figure 4: I suggest making it clear within the figure panels which is summer and which is mid-winter, perhaps with annotations Stratified: summer; Stratified: mid-winter? I would also find it easier to follow the text and compare relationship visually if Figures 4 and 5 were combined into one figure. Perhaps into a figure with 3 columns and 2 rows; a-c showing the Chlzeu relationship and 2nd row d-f showing the Chlzeu2 relationship, with an annotation "Mixed" added to panels showing the relationship in mixed conditions. Also include the definition of stratified vs. mixed in the caption to remind the reader, e.g. Zeu<Zmld.
In figures with regression lines, I suggest to extend lines to edges of the plots.
Figure 6: Add units to each axis.Discussion:
Line 330: Add the value of the R2 in the parenthesis.
Line 350: Related to an earlier comment, this part of the discussion could be a good place to perhaps discuss or acknowledge the impacts/limitations of using night time relationships of surface with depth integrated values if satellite surface values possibly used in the future are during day time.Citation: https://doi.org/10.5194/egusphere-2024-859-RC1 -
AC3: 'Reply on RC1', Renée P. Schoeman, 16 Aug 2024
Dear reviewer,
Thank you for taking the time to go over our manuscript and for providing valuable feedback that will help us improve the manuscript content. We have taken your feedback into consideration and herewith attach a pdf document with our response to each individual comment/suggestion.
Best wishes on behalf of all authors
-
AC3: 'Reply on RC1', Renée P. Schoeman, 16 Aug 2024
-
RC2: 'Comment on egusphere-2024-859', Anonymous Referee #2, 12 Jul 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-859/egusphere-2024-859-RC2-supplement.pdf
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AC1: 'Reply on RC2', Renée P. Schoeman, 16 Aug 2024
Dear reviewer,
We greatly appreciate your time and effort to read through our manuscript and thank you for indicating your concerns regarding the clarity of the methods section, our unbalanced focus on the regression results, and lack of strength in the discussion. We have carefully considered your suggestions and concerns and provide feedback on each individual comment in the attached pdf.
Best wishes on behalf of all authors
-
AC1: 'Reply on RC2', Renée P. Schoeman, 16 Aug 2024
-
AC2: 'Reply on RC1', Renée P. Schoeman, 16 Aug 2024
Dear reviewer,
Thank you for taking the time to go over our manuscript and for providing valuable feedback that will help us improve the manuscript content. We have taken your feedback into consideration and herewith attach a pdf document with our response to each individual comment/suggestion.
Best wishes on behalf of all authors
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2024-859', Anonymous Referee #1, 23 Jun 2024
Brief Summary of the manuscript:
Schoeman and co-authors present evidence on the importance of monitoring deep-depth integrated chlorophyll-a (chla) and phytoplankton biomass based on over 9,000 glider chla fluorescence profiles collected from 2002 to 2022. They compare surface chla concentrations to chla integrated to the euphotic depth (depth-integrated) and chla concentrations integrated to twice the euphotic depth (deep depth-integrated). The authors derive relationships between surface and the two integrated chla concentrations for three different water column conditions: stratified summer, stratified winter, and mixed conditions. They describe the temporal patterns of deep chlorophyll maximum (DCM) occurrence and, within these DCMs, the patterns of deep biomass maximums (DBMs) versus deep acclimation maximums (DAMs). They also provide details on satellite matchups to surface HPLC chla samples and validation. The authors demonstrate that there are increases within the seasonal cycle of deep-depth integrated chla that are not recorded in the seasonal cycle of standard depth-integrated chla. These local deeper increases are biologically important for krill productivity and subsequent whale foraging times.Overall impression:
The results presented in this manuscript are compelling and highlight the increasing importance of including the variability of chla with depth in studies. The study shows how the vertical structure of chla changes seasonally and provides further insight into the potential for monitoring depth-integrated chla using satellite remote sensing data. It suggests that parameters for relationships used should be updated for certain regions. If published, this work could stimulate further discussion about improving satellite-based estimates of depth-integrated chla where DCMs are present. Overall, this manuscript is well-written and well-reasoned. However, there is a need for improved clarity within the method sections, such as the inclusion of a study region map. Additionally, figures could be improved, along with other minor suggestions detailed below.Introduction:
Line 35: Perhaps provide a range or average of the depth to which satellites observe. A good reference here might be Zaneveld et al. 2005 - https://doi.org/10.1364/OPEX.13.009052.
Line 68: This sentence is a bit unclear to what depths was included in these other studies. Did they include deep oceanic samples? the "but" in the sentence makes it unclear and sound unfinished.Methods:
In general, I'm missing some sort of map in the paper. For readers unfamiliar with the region, it would be helpful to have some sort of map showing the study area, some features mentioned in the text such as the Perth Canyon, and perhaps the locations of glider profiles included in the study (if not too crowded) and locations of HPLC samples that could be satellite matched.
Section 2.1: Here the authors state that both the HPLC and glider datasets used are restricted to "between 04 July 2002 and 21 June 2022", please clarify the date ranges of each dataset. Perhaps I have misunderstood the data download process, but according to the AODN delayed mode glider data via the link provided, this online dataset only contains glider data from 2008? If I am mistaken please clarify and/or provide more details on how to download the appropriate glider data.
Section 2.2: Somewhere in this section the reader should be reminded of the total number of glider profiles used after the filtering steps described here. Before this it is only mentioned in the abstract as "~9600" and then again at the beginning of section 3.1 as "We extracted 6438 and 3234 profiles from", unless I missed it.
Line 104-105: It would be interesting to see the authors speculate/comment somewhere here or in the discussion (see comment below) on the potential use of daytime satellite data to infer depth-integrated chla based on relationships derived from nighttime chla profiles. Could this be a limitation that should be acknowledged in the final paragraph of the discussion?
Section 2.3 Line 115: Perhaps I have missed or misunderstood, please clarify here or elsewhere what is meant by profiles that do not cover the Zeu? Have any steps been taken to ensure that profiles cover to a depth of Zeu x2 for the calculation of Chlzeu2?Results:
Section 3.1: It would be easier for new readers to follow these descriptions and get a better idea of the MLD and Zeu characteristics of the study area if there were a plot somewhere here in the main text or in a supplement. Perhaps seasonal box plots or line plots with depth on the y-axis showing both average MLD and Zeu over the seasonal cycle? This might also provide a better background and link to Figure 1. Adding a panel to Figure 1 could also be an option.
Figure 1: I find the addition of the density plot without a y-axis at the top of the figure a bit out of place. Perhaps this seasonal distribution should be shown as a secondary axis in Figure 1 or in another panel. See also other comments below about the addition of a plot showing the annual number of profiles and HPLC samples satellite matched over 2002-2020.
Section 3.2: This whole section will be clearer to a new reader if it shows visually the proportion of DBMs vs. DAMs over a seasonal cycle. Perhaps a figure similar to Figure 1. Either as a supplementary figure or possibly as an additional first panel to Figure 2.
Line 193: Add reference to Figure 1 at end of sentence.
Line 217: Perhaps remind reader here that surface chla concentrations referred to here is the Chlzpd defined in the methods.
Line 221: Remind reader that it is Chlzeu being describe here and similarly in Line 222 that Chlzeu2 is being described.
Figure 3: Increase size of panels numbers (here and all other multi-panel plots) and reduce the amount of blank space at the top of panel (a). Also revise the width of the multi-panel plots with months on the x-axis, here the month text labels are too close together in my opinion and look better in Figure 2.
Figure 4: I suggest making it clear within the figure panels which is summer and which is mid-winter, perhaps with annotations Stratified: summer; Stratified: mid-winter? I would also find it easier to follow the text and compare relationship visually if Figures 4 and 5 were combined into one figure. Perhaps into a figure with 3 columns and 2 rows; a-c showing the Chlzeu relationship and 2nd row d-f showing the Chlzeu2 relationship, with an annotation "Mixed" added to panels showing the relationship in mixed conditions. Also include the definition of stratified vs. mixed in the caption to remind the reader, e.g. Zeu<Zmld.
In figures with regression lines, I suggest to extend lines to edges of the plots.
Figure 6: Add units to each axis.Discussion:
Line 330: Add the value of the R2 in the parenthesis.
Line 350: Related to an earlier comment, this part of the discussion could be a good place to perhaps discuss or acknowledge the impacts/limitations of using night time relationships of surface with depth integrated values if satellite surface values possibly used in the future are during day time.Citation: https://doi.org/10.5194/egusphere-2024-859-RC1 -
AC3: 'Reply on RC1', Renée P. Schoeman, 16 Aug 2024
Dear reviewer,
Thank you for taking the time to go over our manuscript and for providing valuable feedback that will help us improve the manuscript content. We have taken your feedback into consideration and herewith attach a pdf document with our response to each individual comment/suggestion.
Best wishes on behalf of all authors
-
AC3: 'Reply on RC1', Renée P. Schoeman, 16 Aug 2024
-
RC2: 'Comment on egusphere-2024-859', Anonymous Referee #2, 12 Jul 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-859/egusphere-2024-859-RC2-supplement.pdf
-
AC1: 'Reply on RC2', Renée P. Schoeman, 16 Aug 2024
Dear reviewer,
We greatly appreciate your time and effort to read through our manuscript and thank you for indicating your concerns regarding the clarity of the methods section, our unbalanced focus on the regression results, and lack of strength in the discussion. We have carefully considered your suggestions and concerns and provide feedback on each individual comment in the attached pdf.
Best wishes on behalf of all authors
-
AC1: 'Reply on RC2', Renée P. Schoeman, 16 Aug 2024
-
AC2: 'Reply on RC1', Renée P. Schoeman, 16 Aug 2024
Dear reviewer,
Thank you for taking the time to go over our manuscript and for providing valuable feedback that will help us improve the manuscript content. We have taken your feedback into consideration and herewith attach a pdf document with our response to each individual comment/suggestion.
Best wishes on behalf of all authors
Peer review completion
Journal article(s) based on this preprint
Data sets
IMOS – Australian National Facility for Ocean Gliders (ANFOG) – delayed mode glider deployments Ocean Gliders Facility, Integrated Marine Observing System (IMOS) https://portal.aodn.org.au/
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Renée P. Schoeman
Christine Erbe
Robert D. McCauley
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(5760 KB) - Metadata XML