Reply on RC1

Such kind of study is not novel, and it could be argued that the authors chose to perform a study that was doomed to failure since it has been long known that macroalgal d13C is widely variable due to many interplaying factors, and that simply collecting specimens from several different locations, albeit as many as they did, will in the end only once more confirm that this huge variability cannot be easily explained by a single factor alone. Because of that, there is a case to reject this paper.

paper. Also, we removed the letters R, C, and O, the acronymous for Phyla Rhodophyta, Ochrophyta, and Chlorophyta, respectively.
The discussion needs that the figures or tables supporting the interpretations are linked to the text, otherwise it is impossible to evaluate the authors claims.

R.In the revised version, each Figure and Table is linked to the text. Few Figures were improved for a better interpretation of the data.
Statistics are very poorly presented throughout the results. For example, line 296-300; which test was used there to compare different groups? There is nothing. This is the rule through the results.

R.A detailed description of the statistical analysis is provided in the Method section (2.3. Analysis of δ13C-macroalgal variability).
A basic statistical analysis of δ13C values in different macroalgae groups was applied to distribute and calculate the arithmetic mean, standard deviation, minimum and maximum. Kolmogorov-Smirnov normality test was applied for all variables. Comparisons among morphofunctional groups and taxon collected in the same habitat (within-subjects factor) were conducted by multivariate analysis of variance (MANOVA), which is a procedure for comparing multivariate sample means. When differences were noted, a Tukey-Kramer HSD (Honestly Significant Difference) test was performed. Besides, variations of d13C macroalgal in specimens of the same morpho-functional and taxon collected in different habitats were also investigated with a Kruskal-Wallis test.
The relationships between d13C with each independent variable related to the inherent macroalgae properties (morphology and taxon), biogeographical collection zone (GC coastline and coastal sector), habitat features (substrate, hydrodynamic, protection, and emersion level), and environmental conditions (temperature, pH, and salinity) were examined through simple and multiple linear regression analyses. Analyses of simple linear regression were performed to establish the relationships between d13C-macroalgal with each environmental parameter analyzed as possible driving factors (e.g., temperature, salinity, pH). Multiple linear regression analyses were conducted to evaluate the combined effects of those independent variables (macroalgae properties, biogeographical collection zone, habitat features, and environmental conditions) on the d13Cmacroalgal. For all statistical tests, a probability P<0.05 was used to determine statistical significance. The statistical analysis of the results was done using JMP 14.0 software (SAS Institute Inc.).
Many times, the authors make affirmations without any support from literature. For example, line 478, where are the numbers for the conditions in GC waters? Line 485, who said that an efficient CCM helps productivity when the alga is growing under sub-optimal conditions? Line 527, how is that that pCO2 and temperature depend on light?
R.The reviewer is right. In the revised version, all our affirmations were correctly supported by the literature. Many other documents were reviewed and considered for a better interpterion of our data. We appreciate the support of the Reviewer suggesting and providing specialized literature to consult.
In summary, I SUGGEST REJECTION, because the paper is not novel and is very poorly prepared. Comments above are for re-work and maybe resubmission to another journal, but the lack of novelty may render all the effort useless.
R.In our opinion, the revised version was substantially improved. Data were reinterpreted and the Discussion section restructured according to the three study objectives.
On top of all that, the authors need to completely re-interpret their results. It is very clear that their approach is inefficient. All environmental factors influencing d13C are nonsignificant, and, when are, very weakly. The authors need to do a more rational analysis of their results.
R.In agreement with the Reviewer's comments, and to obtain a better interpretation of our results, we revisited our complete dataset and statistical analysis, consulted a lot of specialized literature, and considered the comments of both Reviewers. The most significant modifications of the original version occurred in the Discussion section. We discussed the useful information and knowledge of our large macroalgal d13C database to explain their variations in the function of phylogenetic, morphological, and environmental parameters. We have a substantially improved paper.
Macroalgal d13C is actually two variables in one: DIC d13C plus fractionation. Part of the variability in their results is due to differences in DIC d13C. For example, when salinity changes, DIC d13C changes, and consequently macroalgal d13C changes as well. I believe the authors did not measure DIC d13C (if they did, they should definitely include these data, it would make a mediocre paper become a great paper). But, for most of their samples, DIC d13C will probably be very uniform, so most variation in macroalgal d13C will probably reflect fractionation. Fractionation in macroalgae is largely influenced by photosynthetic rates. So, the authors should reframe their discussion taking photosynthetic rates into consideration, possibly as the main consideration. Therefore, the authors should re-interpret their results using what is currently known about fractionation, and, if they can, about DIC d13C. If they don't have DIC d13C data, they can at least estimate probable values using historical data for the geographical region, taking into consideration seasonal variation, and, importantly, rain parameters, as the main factor here will be seawater and freshwater mixing. R.We appreciate the time and talent of the Reviewer to conduct this careful review of our MS. We appreciate the gem of knowledge shared in the last paragraph.
In this study, composite water samples were collected for a complimentary analysis of nutrients, alkalinity (and their chemical components), and d13C-DIC. However, the dataset was non-included in the old version. In this revised version, the δ13C-DIC values in the Gulf of California surface seawaters were included as Supplementary Information in Fig. S1. In agreement with the preliminary data, the δ13C-DIC in the GC seawater averages 1.4±0.4‰ (-1 to 4.9‰) (Fig. S1).
Because δ13C-macroalgal depends on the isotope discrimination during carbon assimilation in the photosynthesis (Δ13C), we calculated the Δ13C by subtraction of δ13Cmacroalgae to δ13C-DICseawater in the GC. In our concurrent analysis we observed that δ13C-DIC in the GC surface seawater is relatively constant and uniform, thus, the influence of the δ13C-DIC variations to the Δ13C-macroalgal variability was negligible. Based on the integrative discrimination factor against 13C, five groups were identified: one for Chlorophyta (Δ13C=16.0±3.1‰), two for Rhodophyta (16.6±3.8‰ and 34.6±1‰), and two for Ochrophyta (9.1±1.7‰ and 15.7±2.7‰). Values δ13Cmacroalgal reflect mainly the discrimination during carbon assimilation (Δ13C), attributable to the intrinsic properties related to the life form (e.g., taxonomy, morphology) and influenced by environmental conditions controlling the photosynthetic DIC acquisition.
Our research is the first approximation to understand the d13C macroalgal variability in one of the most diverse marine ecosystems in the world, the Gulf of California. We did not pretend to resolve the intricate processes controlling the variations of δ13C or Δ13C-macroalgal during carbon assimilation and respiration and determine the isolated influence of each environmental factor. Controlled experiments in laboratory and mesocosm type in combination with field studies are required to elucidate the complex processes controlling the δ13C-macroalgal.
In our study, the δ13C-macroalgal was a good proxy to identify CO2 or HCO3source in photosynthesis and to infer the presence or absence of CCM's, which is a good indicator of the physiological state of photosynthetic metabolism. Because the ocean acidification in progress and the bloom-forming macroalgae events that increase in México and worldwide, the analysis of δ13C-macroalgal constitute an excellent tool to study acidification and eutrophication, however, the δ13C-macroalgal must be first evaluated.