the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 03 Nov 2021
Sensitivity of plankton assemblages to hydroclimate variability in the Barents Sea
Abstract. Warming, loss of sea icea and changes in ocean currents in the Arctic has led to biochemical changes in pelagic systems that propagate into, and disrupt the Arctic food web. The responses of plankton to environmental variability is critical in understanding how climate change may shape the structure of pelagic ecosystems in the Arctic. To further this understanding, we used a partial canonical correspondence analysis on remotely sensed and modelled hydroclimate together with plankton abundance data from the Continuous Plankton Recorder Survey from the Barents Sea in the European Arctic – one of the fastest warming regions globally – to assess the spatial and interannual variability of plankton community assemblages. The hydroclimate explained ~50 % of interannual variability in species assemblage of plankton communities. Calanus spp. copepod abundances were particularly sensitive to changes in the hydroclimate, which were strongly associated with the mixed layer depth and nutrient concentrations. In warmer years, where SST exceeded those predicted under various future climate scenarios, we saw evidence of thermal stratification of the water column that supported populations of appendicularians, and the potentially toxin-producing diatom Pseudo-nitzschia. Spatial variability of the assemblage was strongly associated SST and salinity gradients that reflect different water masses. Such changes to plankton assemblages in response to hydroclimatic variability are likely to impact trophic interactions with associated organisms, many with ecological and economic significance in Barents Sea food webs.
This preprint has been withdrawn.
-
Withdrawal notice
This preprint has been withdrawn.
-
Preprint
(2365 KB)
-
Supplement
(1879 KB)
-
This preprint has been withdrawn.
- Preprint
(2365 KB) - Metadata XML
-
Supplement
(1879 KB) - BibTeX
- EndNote
Interactive discussion
Status: closed
-
RC1: 'Comment on bg-2021-279', Anonymous Referee #1, 15 Dec 2021
Review https://bg.copernicus.org/preprints/bg-2021-279/
Price et al., Sensitivity of plankton assemblages …
In this ms the authors present material „to further our understanding how climate change may shape the stucture of the pelagic ecosystem in the Arctic“ (lines 13/14), by studying the sensitivity of plankton assemblages to hydroclimate variability in the Barents Sea (title) and use, among others, data from a CPR line from northen Norway to the south of Spitsbergen.
However, this CPR line runs along the south-western edge of the Barents Sea – or, seen from another direction – at the north-western edge of the Norwegian Sea. In any way, this is not „in the Barents Sea“, and even less in the „Arctic“ Barents Sea, which to my knowledge is defined by the winter ice edge and/or the Polarfront, the front between Polar and Atlantic water. The position of the CPR line and the apparently exclusive presence of the Atlantic copepod Calanus finmarchicus clearly define the working area as „Atlantic“. Therefore, all considerations on consequences of climate change and Atlantification on the polar food web, which occupy a large room in the ms, are out of place here.
In conclusion I do not recommend this ms for publication in Biogeosciences. Instead, I suggest to look for another motivation to make the study attractive. Also, I was surprised that the study of O´Dwyer et al. (2001) reporting 13 transects across the BS Opening is not mentioned
Further comments:
Introduction and Discussion are lengthy and too general.
There are many typos etc.
11: the study area is not affected by sea ice
12: The responses … is critical
21/22: no surprise that plankton is strongly associated with water masses!!!
22: water masses were never defined
75 Climate change induced collapse!!!
98: tha(t)
198 Corethron
254: across a time series
262: both of which???
267:”is has a higher energy denisty”???
279: appendiularians
279: Lopez-urrutia
324: such hydroclimates
371: phenological ? changes
Citation: https://doi.org/10.5194/bg-2021-279-RC1 -
CC1: 'Reply on RC1', Pearse Buchanan, 18 Dec 2021
This is honestly one of the laziest reviews I've seen and does not reflect the quality of this paper. In no way does an esoteric argument about "whether the Barents Sea Opening is actually in the Arctic or not" take away from the fact that the authors saw interesting phytoplankton community changes that were likley driven by hydrographic variability. This study could be picked up and placed in the tropics so long as their methods were valid and their reporting of results unbiased. Perhaps the authors should alter some of strength of their language regarding the connection between Arctic warming and their results, but that does not invalidate the study, and to say so is absurd.
Normally, I would not be drawn into the public review system at Copernicus, but on reading this review I felt the need to.
Citation: https://doi.org/10.5194/bg-2021-279-CC1 -
AC1: 'Reply on RC1', Elliott Price, 22 Feb 2022
Thank you for your response. We do not fully agree with your statement that all considerations on consequences on the polar food web are invalid based on the presence of north Atlantic water masses and organisms. We agree that there is considerable influence of the North Atlantic in this region, but it is also exposed to polar conditions, such as the polar night and 24-hr day light in the summer, meaning that organisms that are advected into the system from the north Atlantic are still influenced by these primarily polar phenomenon. We believe defining this region as Atlantic, as you suggested, when it is subject to the polar night and polar summer is misleading. We will, however, adjust the language throughout the MS to state that the region is a subarctic region, and that the impacts we identify do not correspond to high and central arctic systems.
Citation: https://doi.org/10.5194/bg-2021-279-AC1
-
CC1: 'Reply on RC1', Pearse Buchanan, 18 Dec 2021
-
RC2: 'Comment on bg-2021-279', Anonymous Referee #2, 31 Dec 2021
Manuscript number: bg-2021-279
Review of manuscript entitled "Sensitivity of plankton assemblages to hydroclimate variability in the Barents Sea” by Price et al.
General comments
This study described plankton variability associated with satellite and modelled data in the Barents Sea during June from 2010 to 2016. I acknowledge this study include valuable information and manuscript is well written. However, new scientifical findings (except new data) found by authors were ambiguous. Also, I suggest some points for improving readability as below. Therefore, I can recommend publication of this manuscript after minor revision.
Specific comments
L21-22 I could find any information of water masses. This sentence should be removed.
L122 Show the URL of Continuous Plankton Recorder (CPR) Survey.
L131-132 Please add suitable references for choosing the environmental parameters. Why authors used oxygen concentration? The parameters is easily changed at surface. Also, O2 and pH were not explained in this manuscript.
L134 chlorophyll a. “a” should be italic through the manuscript.
L141-151 Did authors checked day-night effect on the zooplankton data? Even the CPR can collect the zooplankton at about 10 m depth, the DVM by zooplankton could influence their abundance data. I recommend authors include the sampling time in pCCA, or no significant effect should be checked before the pCCA.
L274-275 I suggest authors could add a bit more discussion about how detrimental effect by the harmful species (e.g., reduced their escape responses, Harðardóttir et al., 2018).
L314 high SST?
L371 What “?”.
Figure 6. It was so hard for me to read this figure. I recommend the each panel should be bigger.
Citation: https://doi.org/10.5194/bg-2021-279-RC2 -
AC2: 'Reply on RC2', Elliott Price, 22 Feb 2022
Thank you very much for your response. We agree that the exact scientific findings are ambiguous in the manuscript, and we will adjust the reporting of our findings to reflect a more concise manuscript.
Thank you for your specific comments, we will address them all and below we outline how we will resolve some of your suggestions.
L131-132 – We will remove oxygen concentrations and pH from the analysis.
L141-151 – We did check the effect of day-night on the zooplankton data. We found no significant effect on the analysis. This is likely because the samples were from June CPR tows where, in this region, there is 24-hour daylight. Thank you for bringing this up and we will report this analysis in the manuscript.
L274-275 – We will elaborate on the detrimental effect of this harmful species.
Figure 6 – We will expand this figure and orientate the panels vertically to improve readability.
Citation: https://doi.org/10.5194/bg-2021-279-AC2
-
AC2: 'Reply on RC2', Elliott Price, 22 Feb 2022
-
RC3: 'Comment on bg-2021-279', Anonymous Referee #3, 12 Jan 2022
This paper examines phyto- and zooplankton communities together with their environmental drivers on a large transect across the western Barents Sea. The CPR dataset behind the work is a large and impressive dataset, and the region is of great importance. However, the paper has some very serious flaws and I cannot recommend it for publication in its present state. In my opinion it needs to be re-focused, re-structured and re-written before it can be publishable. I do not list the minor comments here, just major ones.
I agree with Reviewer 1 that the region of study is not “the Arctic”, although it is certainly en-route to the Arctic and will influence the Arctic. Unlike reviewer 1 I do not believe that this alone is enough to warrant rejection, but it does mean that the introduction and parts of the discussion would need to be re-written. This is not an Arctic ecosystem, it is the North Atlantic.
I found it strange to pool phyto- and zooplankton communities into a single community analysis since they are operating on different size, spatial and temporal scales and clearly have different factors driving them. Also one may influence the other (in both directions, as you rightly mention top-down control).
After throughly reading the paper several times I am still not exactly sure what the main finding is here. That plankton are inter-annually variable? That plankton communities are influenced by water masses? Both of those statements are well established facts that do not require proof. To be interesting and scientifically valuable you need to show is (a) the extent of this variability (and how it compares - in absolute numbers - not arbitrary placements along ordination axes - with for example seasonal or spatial variability, and also with other similar studies, (b) exactly which water masses/properties influence the communities and in what way.
The presentation of the results is messy and confusing, and I believe that the statistical methods chosen in the paper are not appropriately applied or interpreted. Moreover, the way most of the model results are presented make them to be an “result in themselves”, whereas ordination models are merely a mostly visual tool to aid scientific interpretation of complex data. Most of the text in the result section, Figures 3-4,7 and especially Tables 1-6 - correlations of species to axes - carry no scientific value on their own (they can be in the supplementary material for transparency, of course), but all of this information should already be visible on the ordination plots (which are, incidentally, not even all shown). An in-depth discussion of the results is missing, the existing discussion is scattered and very superficial.
Some more specific comments on the stats are provided below, but I am certain a statistician would have more to say. I highly suggest to the editor that the authors consult with one prior to re-submitting the paper.
The main (and really only) tool the author apply is a pCCA - a partial canonical correspondence analysis, but to me it is not clear that the authors fully understand what this method is. Line 145: “In brief, pCCA is a cluster analysis that describes variability in the plankton assemblage by producing an artificial ‘axis’ that represents a certain plankton community.” CCA is not a cluster analysis, it is an ordination method! It does not produce artificial axes (pl.!) that represent communities. Ordination methods take multidimensional data and try to reduce the number of dimensions, ideally to a 2- or 3- dimensional space. Then we can look at where the data points are relative to each other on this reduced space, and which original variables influenced their placement to infer “communities”. A CCA compared to other ordination methods additionally places these data points to maximise correlation to a second matrix of variables (environmental drivers), so we can also see which variables are most correlated to those communities. A partial CCA is applied when we have a set of covariates we are not interested in. Here the authors want to look at spatial variability without year, or interannual variability without space - so that part is OK. But still they do not seem to grasp that CCA is primarily a *visual* method, a way to visualise complex data in reduced space - hence the 6 tables, and many pages of text that describe what should already be visible on the ordination diagrams. They also do not even present the diagrams until figure 6, for the “biplots" - which are already part of the CCA, not a separate analysis. The ordination diagram for the spatial data is not presented at all.
Moreover, the way the data was treated is not clear. Line 155: Any taxa that contributed less than 5 % of the total count zooplankton and phytoplankton counts were removed prior to the pCCA analysis. 5% in any one sample or all samples pooled? If the latter, that seems unnecessarily conservative and would result in the removal of a lot of species that could be very important, just in a smaller number of samples. I wonder how many total species were left in the dataset? I would remove singletons, but the rarer species (especially larger ones that are just unlikely to be caught in large numbers) can also be important indicators of communities!
Line 156. “Species counts in both phytoplankton and zooplankton datasets differed by several orders of magnitude and tended towards zero inflation. To mitigate against these effects, species counts were standardized from 0 and 1.” First of all, zero inflation does not necessarily equal “a high percentage of zeros”, we will come back to that later. Species counts were standardised from 0 to 1, what does that mean? That you took the ratio of each species in each sample? Or you took the highest abundance and set it to 1 and adjusted the rest accordingly as a fraction of 1? But how does that mitigate the order of magnitude problem? If you have 10,000 Oithona and 1 Calanus in your sample, then you will have 0.9999 and 0.0001 (or 1 and 0.0001), still same order of magnitude difference. I think what you might mean here is that you were interested in the *relative composition* of the communities, not total species abundances? In this case you should of course use ratios, not absolute abundances. To address the order of magnitude problem I would also do a log- or square/fourth root transformation to de-emphasise the most dominant species and bring up the importance of the rarer ones, but consult with a statistician whether that is appropriate in your case.
You standardised your abundance values (or at least tried to), what about the environmental variables? These should be scaled too.
Line 111 onwards - you said you use SST separate into 3 regions based on water masses, but it looks like you just use latitude. Otherwise, you need to show this somewhere. Moreover, I am not sure you can separate water masses based on SST alone.
Line 132 We selected a suite of environmental variables that have previously been known to influence arctic plankton community assemblages.
I think you need to justify this statement with some specific citations. Again, here I have to question your decision to pool the phyto- and zooplankton community together for all your analyses, since they will clearly have different parameters influencing them.
Line 135 we included the average seasonal SST for the spring and summer prior to sampling to capture any lagged effects of SST
Plankton are not stationary, they do not hang out in one spot for one year, by their very definition they are flowing with the currents, and this is a highly advective area. SST *in that location* will certainly not influence the plankton community a year later. It is possible that it may be proxy of what is going on upstream, but why not just use data from upstream if you are using remote sensed data anyway? I would also be very cautious adding such data, for precisely the reason that it might generate “false positives” - you rightfully conclude that last year’s summer temperature is unlikely to be driving Calanus abundance, but yet it showed up as a prominent “predictor” in your analysis.
Line 158 “For each axis produced, each species, each hydroclimate variable and each sample was scored to describe how each component relates to that axis. A species and hydroclimate variable with a similar score for an axis were positively correlated, and a sample with a similar axis score for the corresponding species and hydroclimate axes indicated that species was in higher abundance in that sample.”
Yes, that is how an ordination works, and this information should be well visible on the plot, not presented in 6 tables.
Line 161-166 What is the purpose of all these additional tests? What do you gain that you cannot see just by looking at the ordination? In my opinion, it adds very little and adds a lot of clutter
Line 180. To determine the impact of phenology on the results of the pCCA, we estimated seasonal abundances by comparing the monthly mean abundance of those taxa. To account for the heavily skewed, zero-inflated distribution of the data, as is common for spatially heterogenous plankton communities, we conducted a zero-inflated negative binomial regression using the ‘pscl’ package in R. The percentage of zeros in the count data was > 50 % for all species, and so zero inflated models were chosen.
I don’t understand this. What did you use a zero-inflated negative binomial regression for? Abundance against … ?
Additionally: like I said before, zero inflated data does not equal data with a lot of zeroes. If you apply a zero-inflated model, you need to have a reasoning behind it. For example, if you are looking at euphausiid abundance, they are known to escape nets, so a lot of zeros in such a dataset will be false zeros. Or if your data includes stations outside of the geographic range/season of the species occurrence. If they are “real” zeros, the model should not ignore them, and it is likely that the negative binomial model alone can account for them!
Results
Section 3.1
For all the plethora of tables and figures and text, some basic information is missing (or hidden). How much of the total inertia was captured by the CCA vs the unconstrained ordination? How much by each axis? Were all the explanatory variables significant - you have a lot, and probably lots of them are junk and some others that may be correlated among each other, some preliminary analysis and step-wise model selection might be very useful here! Why did you chose Axes 1 and 3 for ST1 when usually the first 2 axes describe most of the variability? I see on Fig. 6 that it says that Axis 3 accounts for 15.1% but I honestly find that a bit hard to believe. But if that is indeed true, it is a very large %, but it means that Axis 2 is even higher, and then you can’t just choose to ignore it!! In that case you need to show the model as a 3-d box with 3 axes. Like I said, would be nice to see the stats tables for these models. Figure 6 is actually your main result, it should be much larger and come first. Statements like line 194 “consistently negative values for axis 1 across all regions for C. finmarchicus and the low 2014 sample scores” are unnecessary - you can see this in the plot! The fact that they are negative/low is meaningless - this is an arbitrary axis, its values don’t carry meaning on its own. You can actually see a lot of nice information in the plots that you don’t articulate well. For example, in ST1 there is very clear interannual variability (most ellipses are non overlapping), in ST2 a bit less so, and in ST3 I would argue that there is almost no (or very little) separation. That has some real implications that should be discussed!
I don’t really understand how you infer “variability” of species from axes scores - for example, Calanus is the species that is most significantly driving the ordination (i.e. separation of communities), but that doesn’t say much about the variability in its abundance, especially since you standardized(??) the abundance and just looked at relative community composition. Why not just show some box plots/run an ANOVA of the abundances of the different species across the years? Isn’t that what variability is??
Section 3.2
Here instead of Table 4 and Figure 7 you should present (and discuss) an ordination diagram with all appropriate biplots, plus a stats table of the CCA (or describe them in words).
Section 3.3
The word “phenology” is inappropriately used here and throughout the text. You do not look at phenology, just at seasonal variations in abundance (which can be influenced by a hundred different things). These terms do not mean the same thing and cannot be used interchangeably.
This section also feels a bit out of place, since the rest of the paper just focuses on one season.
Discussion
I am missing here a discussion - and comparison - with the large number of zooplankton/ecosystem papers from the Barents Sea. This is the best studied region in the Arctic/sub-Arctic!
Line 261. I would hardly qualify a “high interannual variation of C. finmarchicus abundance” a standout finding. Especially since you don’t really quantify this variability anywhere.
Line 265-268. This is an overly simplistic view. See for example paper by Paul Renaud et al., 2018 from your reference list
Line 285- . SST the year before at this location would not be influencing the community, since it would be a different community
For all the talk of Atlantification in the introduction, one very important aspect is not touched upon at all - advection! This is a highly advective region yet you treat your regions like they are self-contained boxes. The whole transect exists because it is an "Arctic gateway"- it is influenced by several different currents from upstream, and is very important for the Arctic downstream. How are your 3 regions impacted by advection, and by each other?
Citation: https://doi.org/10.5194/bg-2021-279-RC3 -
AC3: 'Reply on RC3', Elliott Price, 22 Feb 2022
Thank you very much for this in-depth review and we appreciate the time taken to analyse our manuscript to this extent. Below you will find our responses to each of your comments.
In response to “I agree with Reviewer 1 that the region of study is not “the Arctic”…”. We concede that the language we have used throughout is misleading and that the study region is not primarily an Arctic region. We do, however, believe that, due to its exposure to the polar night and the subsequent impact this has on the base of the food web, this area could be defined as sub-arctic. As we responded to RC1, we will revise the wording throughout our manuscript to reflect the region’s definitions as sub-arctic.
In response to “I found it strange to pool phyto- and zooplankton communities…”. We grouped these phytoplankton and zooplankton communities together in the same analysis for the reason that you stated - that one group may influence the other. Because of the potential top-down control of phytoplankton by zooplankton, and the potential bottom-up control of zooplankton by phytoplankton, the pCCA, to our knowledge, should reveal the relationships between phytoplankton and zooplankton species by assigning them on opposite ends of each axis.
In response to “After throughly reading the paper several times…” We acknowledge your point that the findings of plankton being interannually vulnerable and related to water masses are not novel and therefore not the main finding, and we will revise the manuscript to provide a measure of variability based on the abundance of the plankton species, rather than, as you state, the ordination axes. We tried to definitively state which water mass properties were impacting the plankton communities, however we agree that this is perhaps not clear enough in our analysis so we will revise the analysis and the conclusions of our paper to make the environmental associations clearer. To accomplish this, we will carry out a PERMANOVA on the underlying distance matrices produced from the ordination analyses to understand whether the distance to the centroids are different between groups (between year and region).
In response to “The presentation of the results is messy and confusing…”. We will move tables displaying model output from the main text and into supplementary as you correctly state the displayed information is already visualized in the ordination plots. We will also display all the pCCA axes in ordination plots regardless of whether there was apparent variability between groups for each axis. We acknowledge that the pCCA outputs are not scientific findings in themselves, and, as stated in the previous response paragraph, we will use PERMANOVA to assess differences in the ordination outputs between groups. Furthermore, we will clarify the questions we are asking and the hypotheses we are testing in the introduction to help sharpen the conclusions and improve the understanding of the results to the reader.
In response to “The main (and really only) tool the author apply is a pCCA…” We will amend our description, use and interpretation of the pCCA analysis throughout as to represent the technical aspects of the analysis more accurately.
In response to “Moreover, the way the data was treated is not clear.” We removed species that represented less than 5 % of the total zooplankton count and 5 % of the total phytoplankton count per sample, not the entire dataset. We will make this point clearer in the text.
In response to “Line 156. “Species counts in both phytoplankton and zooplankton datasets…” We took the highest abundance for each species and set it to 1, then adjusted the other counts for that species accordingly. So we standardised the data matrix by column (species) rather than row (sample), the latter method would, as you stated, conserve the ratio between species and be not be a relevant method. Whereas standardising by individual species should mitigate the problem that arises in the example that you provided with Oithona and Calanus. Thank you for shedding light on this uncertainty and we will alter our wording accordingly.
In response to “You standardised your abundance values…” The environmental matrix is automatically standardised when running the pCCA from the ‘cca’ function in the R package ‘ade4’. We will make this clear in the text.
In response to “Line 111 onwards - you said you use SST separate into 3 regions based on water masses…” The regions were separated based on both SST and Sea Surface Salinity values averaged over the time series which is stated on Line 113. These groupings are consistent with water masses identified from CTD depth profiles observed in that region – please see Tuerena et al., 2020 Biogeosciences.
In response to “Line 132 We selected a suite of environmental variables that have previously…” Thank you for your suggestion and we will include citations back up our selection of environmental variables.
In response to “Plankton are not stationary, they do not hang out in one spot for one year…” We agree that the consideration of SST in previous summer and previous autumn were not valid predictors given the strong role of advection in the system. Whilst we could add in upstream data, we agree and believe that this would introduce too much uncertainty and increase the likelihood of generating false positives. We will therefore remove this variable from the dataset and re-run the analysis. However, we will leave in the SST from the spring as this provides information on the conditioning of the bloom at the start of the season and will have influenced the ecology at the time of CPR sampling in June.
In response to “Line 161-166 What is the purpose of all these additional tests?” On further reflection we see that examining the correlation between the species and hydroclimate axes is redundant given that multiple regressions are intrinsically used in the pCCA model itself to associate the hydroclimate variables with the plankton species. We will also replace the ANOVA’s to assess differences between years and regions with a PERMANOVA that is a more robust analysis when dealing with between group differences on the back of ordination techniques.
In response to “I don’t understand this. What did you use a zero-inflated negative binomial regression for?” It is apparent that our understanding of zero-inflated datasets was inaccurate and therefore the application of zero-inflated negative binomial regressions to assess seasonal abundance was unwarranted. As you state later in your review, this section seems misplaced and isolated - since the results of this section only inform a few minor discussion points, we will remove this analysis from the manuscript. We will, however, show the raw abundance data across the seasons in a supplementary figure to support the minor discussion points.
In response to “For all the plethora of tables and figures and text, some basic information is missing…” We will remove the tables displaying much of the pCCA output, and shift this into a data file in the supplementary information. This will be replaced by tables showing the inertia of the axes and the significance of these. We chose axis 1 and 3 for ST1 as these were the axes that described a community that were interannually variable. In our revision we will present the first three ordination plots for each pCCA carried out, remove much of the results texts that is describing the patterns that can be seen in the plots, and provide greater detail on the technical outputs of the pCCA that describe its performance.
In response to “I don’t really understand how you infer “variability” of species from axes scores…” We inferred variability of species by assessing which species most strongly contributed to the pCCA axes that showed interannual variability in the ANOVA. However, now we see that the pCCA doesn’t produce scientific findings in itself, we will assess variability of the species contributing highly to the pCCA axes by running ANOVA’s on the abundance of the species of interest identified from the pCCA. We will conclude levels variability based on the summary statistics produced from the ANOVA’s, this also has the added benefit of being able to relate the variability to actual abundances and not arbitrary axes scores so thank you for the suggestion.
In response to Section 3.2 comments. We will include ordination plots and the statistical outputs from the pCCA.
In response to Section 3.3 comments. Since the results of this section only inform a few minor discussion points, we will remove this analysis from the manuscript. We will, however, show the raw abundance data across the seasons in a supplementary figure to support the minor discussion points. We will also revise our use of the term phenology and use seasonal variation instead.
In response to “I am missing here a discussion - and comparison” We will provide a more in depth comparison with studies other plankton community composition studies from the Barents Sea region.
In response to “Line 261. I would hardly qualify a “high interannual variation” We will amend the standout finding of the paper once the changes to the analysis are complete and make sure that any quantifiable findings are reported in the main text. For example, showing the high level of variability in C. finmarchicus using boxplots and ANOVA’s as you suggested in your review.
In response to “Line 265-268. This is an overly simplistic view.” We will elaborate on the implications of C. finmarchicus replacing C. glacialis to reflect the complexity of mechanisms relating to lipids in marine food webs.
In response to “Line 285- . SST the year before at this location would not be influencing the community…” We agree and we will remove the SST of the previous seasons from the analysis.
In response to “For all the talk of Atlantification in the introduction, one very important…” We will revise the discussion of the manuscript to reflect the strength that advective processes play across the Barents Sea Opening, and were appropriate, try to avoid discussion points that treat our regions as self-contained boxes rather than interacting regions. Specifically, we will add a section addressing how advection could have impacted the results and the implications of this on the wider ecosystem.
Citation: https://doi.org/10.5194/bg-2021-279-AC3
-
AC3: 'Reply on RC3', Elliott Price, 22 Feb 2022
Interactive discussion
Status: closed
-
RC1: 'Comment on bg-2021-279', Anonymous Referee #1, 15 Dec 2021
Review https://bg.copernicus.org/preprints/bg-2021-279/
Price et al., Sensitivity of plankton assemblages …
In this ms the authors present material „to further our understanding how climate change may shape the stucture of the pelagic ecosystem in the Arctic“ (lines 13/14), by studying the sensitivity of plankton assemblages to hydroclimate variability in the Barents Sea (title) and use, among others, data from a CPR line from northen Norway to the south of Spitsbergen.
However, this CPR line runs along the south-western edge of the Barents Sea – or, seen from another direction – at the north-western edge of the Norwegian Sea. In any way, this is not „in the Barents Sea“, and even less in the „Arctic“ Barents Sea, which to my knowledge is defined by the winter ice edge and/or the Polarfront, the front between Polar and Atlantic water. The position of the CPR line and the apparently exclusive presence of the Atlantic copepod Calanus finmarchicus clearly define the working area as „Atlantic“. Therefore, all considerations on consequences of climate change and Atlantification on the polar food web, which occupy a large room in the ms, are out of place here.
In conclusion I do not recommend this ms for publication in Biogeosciences. Instead, I suggest to look for another motivation to make the study attractive. Also, I was surprised that the study of O´Dwyer et al. (2001) reporting 13 transects across the BS Opening is not mentioned
Further comments:
Introduction and Discussion are lengthy and too general.
There are many typos etc.
11: the study area is not affected by sea ice
12: The responses … is critical
21/22: no surprise that plankton is strongly associated with water masses!!!
22: water masses were never defined
75 Climate change induced collapse!!!
98: tha(t)
198 Corethron
254: across a time series
262: both of which???
267:”is has a higher energy denisty”???
279: appendiularians
279: Lopez-urrutia
324: such hydroclimates
371: phenological ? changes
Citation: https://doi.org/10.5194/bg-2021-279-RC1 -
CC1: 'Reply on RC1', Pearse Buchanan, 18 Dec 2021
This is honestly one of the laziest reviews I've seen and does not reflect the quality of this paper. In no way does an esoteric argument about "whether the Barents Sea Opening is actually in the Arctic or not" take away from the fact that the authors saw interesting phytoplankton community changes that were likley driven by hydrographic variability. This study could be picked up and placed in the tropics so long as their methods were valid and their reporting of results unbiased. Perhaps the authors should alter some of strength of their language regarding the connection between Arctic warming and their results, but that does not invalidate the study, and to say so is absurd.
Normally, I would not be drawn into the public review system at Copernicus, but on reading this review I felt the need to.
Citation: https://doi.org/10.5194/bg-2021-279-CC1 -
AC1: 'Reply on RC1', Elliott Price, 22 Feb 2022
Thank you for your response. We do not fully agree with your statement that all considerations on consequences on the polar food web are invalid based on the presence of north Atlantic water masses and organisms. We agree that there is considerable influence of the North Atlantic in this region, but it is also exposed to polar conditions, such as the polar night and 24-hr day light in the summer, meaning that organisms that are advected into the system from the north Atlantic are still influenced by these primarily polar phenomenon. We believe defining this region as Atlantic, as you suggested, when it is subject to the polar night and polar summer is misleading. We will, however, adjust the language throughout the MS to state that the region is a subarctic region, and that the impacts we identify do not correspond to high and central arctic systems.
Citation: https://doi.org/10.5194/bg-2021-279-AC1
-
CC1: 'Reply on RC1', Pearse Buchanan, 18 Dec 2021
-
RC2: 'Comment on bg-2021-279', Anonymous Referee #2, 31 Dec 2021
Manuscript number: bg-2021-279
Review of manuscript entitled "Sensitivity of plankton assemblages to hydroclimate variability in the Barents Sea” by Price et al.
General comments
This study described plankton variability associated with satellite and modelled data in the Barents Sea during June from 2010 to 2016. I acknowledge this study include valuable information and manuscript is well written. However, new scientifical findings (except new data) found by authors were ambiguous. Also, I suggest some points for improving readability as below. Therefore, I can recommend publication of this manuscript after minor revision.
Specific comments
L21-22 I could find any information of water masses. This sentence should be removed.
L122 Show the URL of Continuous Plankton Recorder (CPR) Survey.
L131-132 Please add suitable references for choosing the environmental parameters. Why authors used oxygen concentration? The parameters is easily changed at surface. Also, O2 and pH were not explained in this manuscript.
L134 chlorophyll a. “a” should be italic through the manuscript.
L141-151 Did authors checked day-night effect on the zooplankton data? Even the CPR can collect the zooplankton at about 10 m depth, the DVM by zooplankton could influence their abundance data. I recommend authors include the sampling time in pCCA, or no significant effect should be checked before the pCCA.
L274-275 I suggest authors could add a bit more discussion about how detrimental effect by the harmful species (e.g., reduced their escape responses, Harðardóttir et al., 2018).
L314 high SST?
L371 What “?”.
Figure 6. It was so hard for me to read this figure. I recommend the each panel should be bigger.
Citation: https://doi.org/10.5194/bg-2021-279-RC2 -
AC2: 'Reply on RC2', Elliott Price, 22 Feb 2022
Thank you very much for your response. We agree that the exact scientific findings are ambiguous in the manuscript, and we will adjust the reporting of our findings to reflect a more concise manuscript.
Thank you for your specific comments, we will address them all and below we outline how we will resolve some of your suggestions.
L131-132 – We will remove oxygen concentrations and pH from the analysis.
L141-151 – We did check the effect of day-night on the zooplankton data. We found no significant effect on the analysis. This is likely because the samples were from June CPR tows where, in this region, there is 24-hour daylight. Thank you for bringing this up and we will report this analysis in the manuscript.
L274-275 – We will elaborate on the detrimental effect of this harmful species.
Figure 6 – We will expand this figure and orientate the panels vertically to improve readability.
Citation: https://doi.org/10.5194/bg-2021-279-AC2
-
AC2: 'Reply on RC2', Elliott Price, 22 Feb 2022
-
RC3: 'Comment on bg-2021-279', Anonymous Referee #3, 12 Jan 2022
This paper examines phyto- and zooplankton communities together with their environmental drivers on a large transect across the western Barents Sea. The CPR dataset behind the work is a large and impressive dataset, and the region is of great importance. However, the paper has some very serious flaws and I cannot recommend it for publication in its present state. In my opinion it needs to be re-focused, re-structured and re-written before it can be publishable. I do not list the minor comments here, just major ones.
I agree with Reviewer 1 that the region of study is not “the Arctic”, although it is certainly en-route to the Arctic and will influence the Arctic. Unlike reviewer 1 I do not believe that this alone is enough to warrant rejection, but it does mean that the introduction and parts of the discussion would need to be re-written. This is not an Arctic ecosystem, it is the North Atlantic.
I found it strange to pool phyto- and zooplankton communities into a single community analysis since they are operating on different size, spatial and temporal scales and clearly have different factors driving them. Also one may influence the other (in both directions, as you rightly mention top-down control).
After throughly reading the paper several times I am still not exactly sure what the main finding is here. That plankton are inter-annually variable? That plankton communities are influenced by water masses? Both of those statements are well established facts that do not require proof. To be interesting and scientifically valuable you need to show is (a) the extent of this variability (and how it compares - in absolute numbers - not arbitrary placements along ordination axes - with for example seasonal or spatial variability, and also with other similar studies, (b) exactly which water masses/properties influence the communities and in what way.
The presentation of the results is messy and confusing, and I believe that the statistical methods chosen in the paper are not appropriately applied or interpreted. Moreover, the way most of the model results are presented make them to be an “result in themselves”, whereas ordination models are merely a mostly visual tool to aid scientific interpretation of complex data. Most of the text in the result section, Figures 3-4,7 and especially Tables 1-6 - correlations of species to axes - carry no scientific value on their own (they can be in the supplementary material for transparency, of course), but all of this information should already be visible on the ordination plots (which are, incidentally, not even all shown). An in-depth discussion of the results is missing, the existing discussion is scattered and very superficial.
Some more specific comments on the stats are provided below, but I am certain a statistician would have more to say. I highly suggest to the editor that the authors consult with one prior to re-submitting the paper.
The main (and really only) tool the author apply is a pCCA - a partial canonical correspondence analysis, but to me it is not clear that the authors fully understand what this method is. Line 145: “In brief, pCCA is a cluster analysis that describes variability in the plankton assemblage by producing an artificial ‘axis’ that represents a certain plankton community.” CCA is not a cluster analysis, it is an ordination method! It does not produce artificial axes (pl.!) that represent communities. Ordination methods take multidimensional data and try to reduce the number of dimensions, ideally to a 2- or 3- dimensional space. Then we can look at where the data points are relative to each other on this reduced space, and which original variables influenced their placement to infer “communities”. A CCA compared to other ordination methods additionally places these data points to maximise correlation to a second matrix of variables (environmental drivers), so we can also see which variables are most correlated to those communities. A partial CCA is applied when we have a set of covariates we are not interested in. Here the authors want to look at spatial variability without year, or interannual variability without space - so that part is OK. But still they do not seem to grasp that CCA is primarily a *visual* method, a way to visualise complex data in reduced space - hence the 6 tables, and many pages of text that describe what should already be visible on the ordination diagrams. They also do not even present the diagrams until figure 6, for the “biplots" - which are already part of the CCA, not a separate analysis. The ordination diagram for the spatial data is not presented at all.
Moreover, the way the data was treated is not clear. Line 155: Any taxa that contributed less than 5 % of the total count zooplankton and phytoplankton counts were removed prior to the pCCA analysis. 5% in any one sample or all samples pooled? If the latter, that seems unnecessarily conservative and would result in the removal of a lot of species that could be very important, just in a smaller number of samples. I wonder how many total species were left in the dataset? I would remove singletons, but the rarer species (especially larger ones that are just unlikely to be caught in large numbers) can also be important indicators of communities!
Line 156. “Species counts in both phytoplankton and zooplankton datasets differed by several orders of magnitude and tended towards zero inflation. To mitigate against these effects, species counts were standardized from 0 and 1.” First of all, zero inflation does not necessarily equal “a high percentage of zeros”, we will come back to that later. Species counts were standardised from 0 to 1, what does that mean? That you took the ratio of each species in each sample? Or you took the highest abundance and set it to 1 and adjusted the rest accordingly as a fraction of 1? But how does that mitigate the order of magnitude problem? If you have 10,000 Oithona and 1 Calanus in your sample, then you will have 0.9999 and 0.0001 (or 1 and 0.0001), still same order of magnitude difference. I think what you might mean here is that you were interested in the *relative composition* of the communities, not total species abundances? In this case you should of course use ratios, not absolute abundances. To address the order of magnitude problem I would also do a log- or square/fourth root transformation to de-emphasise the most dominant species and bring up the importance of the rarer ones, but consult with a statistician whether that is appropriate in your case.
You standardised your abundance values (or at least tried to), what about the environmental variables? These should be scaled too.
Line 111 onwards - you said you use SST separate into 3 regions based on water masses, but it looks like you just use latitude. Otherwise, you need to show this somewhere. Moreover, I am not sure you can separate water masses based on SST alone.
Line 132 We selected a suite of environmental variables that have previously been known to influence arctic plankton community assemblages.
I think you need to justify this statement with some specific citations. Again, here I have to question your decision to pool the phyto- and zooplankton community together for all your analyses, since they will clearly have different parameters influencing them.
Line 135 we included the average seasonal SST for the spring and summer prior to sampling to capture any lagged effects of SST
Plankton are not stationary, they do not hang out in one spot for one year, by their very definition they are flowing with the currents, and this is a highly advective area. SST *in that location* will certainly not influence the plankton community a year later. It is possible that it may be proxy of what is going on upstream, but why not just use data from upstream if you are using remote sensed data anyway? I would also be very cautious adding such data, for precisely the reason that it might generate “false positives” - you rightfully conclude that last year’s summer temperature is unlikely to be driving Calanus abundance, but yet it showed up as a prominent “predictor” in your analysis.
Line 158 “For each axis produced, each species, each hydroclimate variable and each sample was scored to describe how each component relates to that axis. A species and hydroclimate variable with a similar score for an axis were positively correlated, and a sample with a similar axis score for the corresponding species and hydroclimate axes indicated that species was in higher abundance in that sample.”
Yes, that is how an ordination works, and this information should be well visible on the plot, not presented in 6 tables.
Line 161-166 What is the purpose of all these additional tests? What do you gain that you cannot see just by looking at the ordination? In my opinion, it adds very little and adds a lot of clutter
Line 180. To determine the impact of phenology on the results of the pCCA, we estimated seasonal abundances by comparing the monthly mean abundance of those taxa. To account for the heavily skewed, zero-inflated distribution of the data, as is common for spatially heterogenous plankton communities, we conducted a zero-inflated negative binomial regression using the ‘pscl’ package in R. The percentage of zeros in the count data was > 50 % for all species, and so zero inflated models were chosen.
I don’t understand this. What did you use a zero-inflated negative binomial regression for? Abundance against … ?
Additionally: like I said before, zero inflated data does not equal data with a lot of zeroes. If you apply a zero-inflated model, you need to have a reasoning behind it. For example, if you are looking at euphausiid abundance, they are known to escape nets, so a lot of zeros in such a dataset will be false zeros. Or if your data includes stations outside of the geographic range/season of the species occurrence. If they are “real” zeros, the model should not ignore them, and it is likely that the negative binomial model alone can account for them!
Results
Section 3.1
For all the plethora of tables and figures and text, some basic information is missing (or hidden). How much of the total inertia was captured by the CCA vs the unconstrained ordination? How much by each axis? Were all the explanatory variables significant - you have a lot, and probably lots of them are junk and some others that may be correlated among each other, some preliminary analysis and step-wise model selection might be very useful here! Why did you chose Axes 1 and 3 for ST1 when usually the first 2 axes describe most of the variability? I see on Fig. 6 that it says that Axis 3 accounts for 15.1% but I honestly find that a bit hard to believe. But if that is indeed true, it is a very large %, but it means that Axis 2 is even higher, and then you can’t just choose to ignore it!! In that case you need to show the model as a 3-d box with 3 axes. Like I said, would be nice to see the stats tables for these models. Figure 6 is actually your main result, it should be much larger and come first. Statements like line 194 “consistently negative values for axis 1 across all regions for C. finmarchicus and the low 2014 sample scores” are unnecessary - you can see this in the plot! The fact that they are negative/low is meaningless - this is an arbitrary axis, its values don’t carry meaning on its own. You can actually see a lot of nice information in the plots that you don’t articulate well. For example, in ST1 there is very clear interannual variability (most ellipses are non overlapping), in ST2 a bit less so, and in ST3 I would argue that there is almost no (or very little) separation. That has some real implications that should be discussed!
I don’t really understand how you infer “variability” of species from axes scores - for example, Calanus is the species that is most significantly driving the ordination (i.e. separation of communities), but that doesn’t say much about the variability in its abundance, especially since you standardized(??) the abundance and just looked at relative community composition. Why not just show some box plots/run an ANOVA of the abundances of the different species across the years? Isn’t that what variability is??
Section 3.2
Here instead of Table 4 and Figure 7 you should present (and discuss) an ordination diagram with all appropriate biplots, plus a stats table of the CCA (or describe them in words).
Section 3.3
The word “phenology” is inappropriately used here and throughout the text. You do not look at phenology, just at seasonal variations in abundance (which can be influenced by a hundred different things). These terms do not mean the same thing and cannot be used interchangeably.
This section also feels a bit out of place, since the rest of the paper just focuses on one season.
Discussion
I am missing here a discussion - and comparison - with the large number of zooplankton/ecosystem papers from the Barents Sea. This is the best studied region in the Arctic/sub-Arctic!
Line 261. I would hardly qualify a “high interannual variation of C. finmarchicus abundance” a standout finding. Especially since you don’t really quantify this variability anywhere.
Line 265-268. This is an overly simplistic view. See for example paper by Paul Renaud et al., 2018 from your reference list
Line 285- . SST the year before at this location would not be influencing the community, since it would be a different community
For all the talk of Atlantification in the introduction, one very important aspect is not touched upon at all - advection! This is a highly advective region yet you treat your regions like they are self-contained boxes. The whole transect exists because it is an "Arctic gateway"- it is influenced by several different currents from upstream, and is very important for the Arctic downstream. How are your 3 regions impacted by advection, and by each other?
Citation: https://doi.org/10.5194/bg-2021-279-RC3 -
AC3: 'Reply on RC3', Elliott Price, 22 Feb 2022
Thank you very much for this in-depth review and we appreciate the time taken to analyse our manuscript to this extent. Below you will find our responses to each of your comments.
In response to “I agree with Reviewer 1 that the region of study is not “the Arctic”…”. We concede that the language we have used throughout is misleading and that the study region is not primarily an Arctic region. We do, however, believe that, due to its exposure to the polar night and the subsequent impact this has on the base of the food web, this area could be defined as sub-arctic. As we responded to RC1, we will revise the wording throughout our manuscript to reflect the region’s definitions as sub-arctic.
In response to “I found it strange to pool phyto- and zooplankton communities…”. We grouped these phytoplankton and zooplankton communities together in the same analysis for the reason that you stated - that one group may influence the other. Because of the potential top-down control of phytoplankton by zooplankton, and the potential bottom-up control of zooplankton by phytoplankton, the pCCA, to our knowledge, should reveal the relationships between phytoplankton and zooplankton species by assigning them on opposite ends of each axis.
In response to “After throughly reading the paper several times…” We acknowledge your point that the findings of plankton being interannually vulnerable and related to water masses are not novel and therefore not the main finding, and we will revise the manuscript to provide a measure of variability based on the abundance of the plankton species, rather than, as you state, the ordination axes. We tried to definitively state which water mass properties were impacting the plankton communities, however we agree that this is perhaps not clear enough in our analysis so we will revise the analysis and the conclusions of our paper to make the environmental associations clearer. To accomplish this, we will carry out a PERMANOVA on the underlying distance matrices produced from the ordination analyses to understand whether the distance to the centroids are different between groups (between year and region).
In response to “The presentation of the results is messy and confusing…”. We will move tables displaying model output from the main text and into supplementary as you correctly state the displayed information is already visualized in the ordination plots. We will also display all the pCCA axes in ordination plots regardless of whether there was apparent variability between groups for each axis. We acknowledge that the pCCA outputs are not scientific findings in themselves, and, as stated in the previous response paragraph, we will use PERMANOVA to assess differences in the ordination outputs between groups. Furthermore, we will clarify the questions we are asking and the hypotheses we are testing in the introduction to help sharpen the conclusions and improve the understanding of the results to the reader.
In response to “The main (and really only) tool the author apply is a pCCA…” We will amend our description, use and interpretation of the pCCA analysis throughout as to represent the technical aspects of the analysis more accurately.
In response to “Moreover, the way the data was treated is not clear.” We removed species that represented less than 5 % of the total zooplankton count and 5 % of the total phytoplankton count per sample, not the entire dataset. We will make this point clearer in the text.
In response to “Line 156. “Species counts in both phytoplankton and zooplankton datasets…” We took the highest abundance for each species and set it to 1, then adjusted the other counts for that species accordingly. So we standardised the data matrix by column (species) rather than row (sample), the latter method would, as you stated, conserve the ratio between species and be not be a relevant method. Whereas standardising by individual species should mitigate the problem that arises in the example that you provided with Oithona and Calanus. Thank you for shedding light on this uncertainty and we will alter our wording accordingly.
In response to “You standardised your abundance values…” The environmental matrix is automatically standardised when running the pCCA from the ‘cca’ function in the R package ‘ade4’. We will make this clear in the text.
In response to “Line 111 onwards - you said you use SST separate into 3 regions based on water masses…” The regions were separated based on both SST and Sea Surface Salinity values averaged over the time series which is stated on Line 113. These groupings are consistent with water masses identified from CTD depth profiles observed in that region – please see Tuerena et al., 2020 Biogeosciences.
In response to “Line 132 We selected a suite of environmental variables that have previously…” Thank you for your suggestion and we will include citations back up our selection of environmental variables.
In response to “Plankton are not stationary, they do not hang out in one spot for one year…” We agree that the consideration of SST in previous summer and previous autumn were not valid predictors given the strong role of advection in the system. Whilst we could add in upstream data, we agree and believe that this would introduce too much uncertainty and increase the likelihood of generating false positives. We will therefore remove this variable from the dataset and re-run the analysis. However, we will leave in the SST from the spring as this provides information on the conditioning of the bloom at the start of the season and will have influenced the ecology at the time of CPR sampling in June.
In response to “Line 161-166 What is the purpose of all these additional tests?” On further reflection we see that examining the correlation between the species and hydroclimate axes is redundant given that multiple regressions are intrinsically used in the pCCA model itself to associate the hydroclimate variables with the plankton species. We will also replace the ANOVA’s to assess differences between years and regions with a PERMANOVA that is a more robust analysis when dealing with between group differences on the back of ordination techniques.
In response to “I don’t understand this. What did you use a zero-inflated negative binomial regression for?” It is apparent that our understanding of zero-inflated datasets was inaccurate and therefore the application of zero-inflated negative binomial regressions to assess seasonal abundance was unwarranted. As you state later in your review, this section seems misplaced and isolated - since the results of this section only inform a few minor discussion points, we will remove this analysis from the manuscript. We will, however, show the raw abundance data across the seasons in a supplementary figure to support the minor discussion points.
In response to “For all the plethora of tables and figures and text, some basic information is missing…” We will remove the tables displaying much of the pCCA output, and shift this into a data file in the supplementary information. This will be replaced by tables showing the inertia of the axes and the significance of these. We chose axis 1 and 3 for ST1 as these were the axes that described a community that were interannually variable. In our revision we will present the first three ordination plots for each pCCA carried out, remove much of the results texts that is describing the patterns that can be seen in the plots, and provide greater detail on the technical outputs of the pCCA that describe its performance.
In response to “I don’t really understand how you infer “variability” of species from axes scores…” We inferred variability of species by assessing which species most strongly contributed to the pCCA axes that showed interannual variability in the ANOVA. However, now we see that the pCCA doesn’t produce scientific findings in itself, we will assess variability of the species contributing highly to the pCCA axes by running ANOVA’s on the abundance of the species of interest identified from the pCCA. We will conclude levels variability based on the summary statistics produced from the ANOVA’s, this also has the added benefit of being able to relate the variability to actual abundances and not arbitrary axes scores so thank you for the suggestion.
In response to Section 3.2 comments. We will include ordination plots and the statistical outputs from the pCCA.
In response to Section 3.3 comments. Since the results of this section only inform a few minor discussion points, we will remove this analysis from the manuscript. We will, however, show the raw abundance data across the seasons in a supplementary figure to support the minor discussion points. We will also revise our use of the term phenology and use seasonal variation instead.
In response to “I am missing here a discussion - and comparison” We will provide a more in depth comparison with studies other plankton community composition studies from the Barents Sea region.
In response to “Line 261. I would hardly qualify a “high interannual variation” We will amend the standout finding of the paper once the changes to the analysis are complete and make sure that any quantifiable findings are reported in the main text. For example, showing the high level of variability in C. finmarchicus using boxplots and ANOVA’s as you suggested in your review.
In response to “Line 265-268. This is an overly simplistic view.” We will elaborate on the implications of C. finmarchicus replacing C. glacialis to reflect the complexity of mechanisms relating to lipids in marine food webs.
In response to “Line 285- . SST the year before at this location would not be influencing the community…” We agree and we will remove the SST of the previous seasons from the analysis.
In response to “For all the talk of Atlantification in the introduction, one very important…” We will revise the discussion of the manuscript to reflect the strength that advective processes play across the Barents Sea Opening, and were appropriate, try to avoid discussion points that treat our regions as self-contained boxes rather than interacting regions. Specifically, we will add a section addressing how advection could have impacted the results and the implications of this on the wider ecosystem.
Citation: https://doi.org/10.5194/bg-2021-279-AC3
-
AC3: 'Reply on RC3', Elliott Price, 22 Feb 2022
Viewed
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 876 | 279 | 61 | 1,216 | 106 | 44 | 44 |
- HTML: 876
- PDF: 279
- XML: 61
- Total: 1,216
- Supplement: 106
- BibTeX: 44
- EndNote: 44
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
Elliott L. Price
Rowena F. Stern
Claire Mahaffey
Claudia Castellani
Rachel M. Jeffreys
This preprint has been withdrawn.
- Preprint
(2365 KB) - Metadata XML
-
Supplement
(1879 KB) - BibTeX
- EndNote