the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Underwater light environment in Arctic fjords
Abstract. Most inhabitants of the Arctic live near the coastline, including fjord systems where socio-ecological coupling with coastal communities is dominant. It is therefore critically important that the key aspects of Arctic fjords be measured as well as possible. Much work has been done to monitor temperature and salinity, but an in-depth knowledge of the light environment throughout Arctic fjords is lacking. This is particularly problematic knowing the importance of light for benthic ecosystem engineers such as macroalgae, which also play a major role in ecosystem function. Here we document the creation and implementation of a high resolution (~50–150 m) gridded dataset for surface photosynthetically available radiation (PAR), diffuse attenuation of PAR through the water column (KPAR), and PAR available at the seafloor (bottom PAR) for seven Arctic fjords distributed throughout Svalbard, Greenland, and Norway, during the period 2003–2022. In addition to bottom PAR being available at a monthly resolution over this time period, all variables are available as a global average, annual averages, and monthly climatologies. Throughout most Arctic fjords, the interannual variability of monthly bottom PAR is too large to determine any long term trends. However, in some fjords, bottom PAR has increased in spring and autumn, and decreased in summer. While a full investigation into these causes is beyond the scope of the description of the dataset presented here, it is hypothesised that this shift is due to a decrease in seasonal ice cover (i.e. enhanced surface PAR) in the shoulder seasons, and an increase in coastal runoff (i.e. increased turbidity/decreased surface PAR) in summer. A demonstration of the usability of the dataset is given by showing how it can be combined with known PAR requirements of macroalgae to track the change in time of the potential distribution area for macroalgal habitats within fjords.
The dataset (Gentili et al., 2023a) is available on PANGAEA at: https://doi.org/10.1594/PANGAEA.962895. A toolbox for download and working with this dataset is available in the form of the FjordLight R package, which is available via CRAN (Gentili et al., 2023b), or may be installed via GitHub: https://face-it-project.github.io/FjordLight (last access: 8 December 2023).
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Status: final response (author comments only)
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RC1: 'Comment on essd-2023-462', Anonymous Referee #1, 30 Jan 2024
The comment was uploaded in the form of a supplement: https://essd.copernicus.org/preprints/essd-2023-462/essd-2023-462-RC1-supplement.pdf
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AC1: 'Reply on RC1', Robert Schlegel, 05 Feb 2024
We would like to thank the reviewer for their constructive comments on this manuscript. While we disagree that PAR data are 'qualitative' because they are related to other environmental variables, perhaps there is a language barrier issue interfering with our understanding of the reviewers criticism and their motivation for a major revision. Particularly considering how few specific comments there are.
That being said, when revising the manuscript we aim to address all issues that the reviewer has raised. Specifically:
- Figure 1 will be completely overhauled. All horizontal scales of the fjords will be added, as well as isobath lines and a table will be added showing how many shallow and coastal pixels are available per site. In this figure and all others, the colour palette for the sites will be changed to a new one that shows much clearer contrast.
- A new table will be added containing the metadata for the optics sensors used. E.g. name, period of coverage, spatial and temporal completeness, etc.
- A new table will be provided that shows the statistics of the good vs. bad pixels and exactly how many days were available per month.
- The colour palette for the sites will be changed for all relevant figures.
- The method of downscaling from 1 km to ~50 - 200 m will be more clearly explained. Accompanied by an appropriate note of caution to users.
- We will revisit all of the climatological average values and provide standard deviations where appropriate.
- Median values are preferable to mean when describing the seasonal cycle due to the kurtosis (right skew) of the PAR variables. These statistics will be made more clear in the text.
- We respectfully disagree that this PAR dataset is 'semi-qualitative'. Perhaps we have a miscommunication issue. We do however agree that the extrapolation of a 20 year time series to a long-term trend should be done with caution, and that the inter-annual variability is likely more related to the physical phenomenon mentioned in your comment. When editing the discussion we will take this point into consideration and comment on it accordingly.
Citation: https://doi.org/10.5194/essd-2023-462-AC1
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AC1: 'Reply on RC1', Robert Schlegel, 05 Feb 2024
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RC2: 'Comment on essd-2023-462', Anonymous Referee #2, 22 Apr 2024
General comment: the paper described a gridded dataset covering 2003-2022 of PAR in a selected number of Artic Fjords. The paper is well written and the information well organised even if it’s not clear what are the complementary information/data/observation required by this methodology. A key point is missing, the uncertainty associated to the explained methodology and the accuracy of the information of this dataset. There is no comparison with any other methodology that can be used in this field, is this the only way for estimating gridded PAR in Arctic areas? A critical description of the chosen methodology, its limitations and how it performs compare to others is missing.
An interesting point would be to explain the sustainability of this methodology for updating the existing this timeserie.
Specific comment:
Page 7 line 154: The fjords of Northen Norway …. Looking at figure 1 and Table 1 there is only 1 fjord in Norway.
Page 15 , 3.2 Bottom values…. The description of table 3 and figure 4 has no additional information than describing the values. Is there a way to provide a clear message to the reader on the meaning of these values?
Pag. 17 line 364: which is figure S1?
Pag. 17 line 372: same for figure S2
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AC2: 'Reply on RC2', Robert Schlegel, 26 Apr 2024
We would like to thank the reviewer for their constructive comments on this manuscript. While we do not think that it is within the scope of this manuscript to provide comparisons between the methodology used to generate the dataset discussed within this paper and any other methodology that may exist, we have looked through the literature and do not find any other alternatives. As for the uncertainty that may exist around values generated with the methodology, this is all very well documented within Singh et al. (2022) and we also do not think it is within the scope of an ESSD dataset paper to go into this level of detail. We rather focus here on the dataset and its potential use cases.
We agree with the reviewer that it would be interesting to comment on how readily this dataset could be updated, year-on-year, so we will add a couple of sentences to the conclusion section.
Specific comment:
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While true that there is only one Northern Norwegian fjord in the study area, we state early on in the manuscript that this one site is representative of Northern Norwegian fjords generally. We will endeavour to remove any ambiguity about this throughout the text.
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Because Section 3.2 is meant to report on the results, and their context is discussed in detail in Section 5 P2, we do not want to repeat to much text here. We will however add a sentence to the end of Section 3.2 P1 giving the reader the context of why the numbers are important.
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We regret that the reviewer was not able to find Figures S1 and S2. We will ensure that they are available in the material upon the following submission.
Citation: https://doi.org/10.5194/essd-2023-462-AC2 -
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AC2: 'Reply on RC2', Robert Schlegel, 26 Apr 2024
Data sets
FjordLight: PAR data for Arctic fjords Bernard Gentili, Rakesh Singh, Simon Bélanger, Robert Schlegel, Jean-Pierre Gattuso https://doi.org/10.1594/PANGAEA.962895
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