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Peer-Review Record

The Structure and Composition of Puerto Rico’s Urban Mangroves

Forests 2020, 11(10), 1119; https://doi.org/10.3390/f11101119

by Benjamin L. Branoff^1,*

and Sebastián Martinuzzi²

Reviewer 1: Anonymous

Reviewer 2: Anonymous

Forests 2020, 11(10), 1119; https://doi.org/10.3390/f11101119

Submission received: 8 September 2020 / Revised: 2 October 2020 / Accepted: 5 October 2020 / Published: 21 October 2020

(This article belongs to the Special Issue Forest Stand Management and Biomass Growth)

Round 1

Reviewer 1 Report

Most of the reviewers' comments have been addressed very well. Thank you.

Author Response

Most of the reviewers' comments have been addressed very well. Thank you.

We appreciate the reviewer’s time and consideration in reviewing our manuscript.

Reviewer 2 Report

Dear author and co-authors,

Thanks for taking into consideration most of the comments highlighted by the reviewers. The clarity of the manuscript has increased significantly and this work is of interest for both the academic community and a wider readership, specially for those concerned with conservation in urban environments. This work sheds light into anthropic-induced changes in mangrove ecosystems for which the consequences in relation to ecosystem function remain little understood.

Despite the statement in the response to reviewers (and considerable efforts to improve the MS), there are still some writing habits that need to be improved. For instance, there still a failure to describe the direction of changes in the results section regarding regressions.. for example sentences such as "stand density decreased with ammonium concentrations"..what about ammonium concentrations decreases stand density?. This is obvious when looking at the figures, but it would be certainly optimal that readers don't have to keep juggling between text and figures to understand the results. These and further comments should be addressed.

Also please consider having a native english editor proof read the final document, using expressions like "biomass percentage as A. germinans" extremely common along the MS to be perceived as a typing mistake. I am not a native english speaker, but sill never saw this expression in academic papers and would be very surprised if this would be considered proper grammar.

further minor details:

L111 change “placed” for “selected” or “located”

350 The stress value represents the disagreement between the model's N-dimensional configuration and the predicted values from the regression between the configuration and the observed distances (Oksanen, 2019. “Vegan: an introduction to ordination"). Thus, to understand how well the model can represent the community in Fig. 4, the authors must specify the number of dimensions of the NMDS, as more than 2 are possible, and the higher the number of dimensions, the lower the stress value will be. Either metaMDS() returns the optimal number of dimensions or the user defines the number of dimensions in the k argument of the function. Please report on methods section or results depending on what the author’s approach was.

353… strange use of “as -species-”, do the authors mean of?

356 – 366. Although this reviewer is in an irrelevant position to point towards a correct English grammar, something seems wired about the way “as” is being used followed by scientific names. Please consider changing “as” for “of”

L358-361 “(Figure 5). For instance, while the biomass percent of A. germinans decreased with increasing urban index values, the biomass percent of L. racemose increased. Further, R. mangle percent biomass increased with salinity, whereas the biomass percent of L. racemose was negatively correlated to salinity.

L367-371…

Increased with higher total K….” or “ were positively correlated with total …

370 change “the stem density…” for “stem density decreased with increasing surface water ammonium concentrations”

And so on with the direction of change in the regression results

Discussion

404 do the authors refer to “true mangrove species” when using the term “mangrove diversity” clarify the first time mentioned in the MS adding a statement such as “(further referred as “mangrove diversity”)

Figures

2,3, and 5 change “denote statistically different sites(groups)” for “denote significant differences”

Fig. 5. Please add in the caption a brief description of symbols for the first and last charts (total K.N vs Height) and (Sp. Diversity vs Population density)… “in tree height as a response to total Kjeldahl N open circles, filled circles, and triangles correspond to: 90^th height percentile, mean height and SD of height, respectively. Whereas in species density as a response to population density open circles and file circles denote (overall tree sp. and true mangroves, respectively)

Author Response

Reviewer 2

These are all good suggestions/comments and we appreciate the reviewer’s thoughtful consideration. Please see our response to these issues below.

further minor details:

L111 change “placed” for “selected” or “located”

done

Excellent point. We used the default, k=2 dimensions and have reported so in the methods:
- Line 256: “NMDS was first performed through the metaMDS function with the default of two dimensions.”

353… strange use of “as -species-”, do the authors mean of?

This is an interesting point. As a native English speaker, it seems ok to us, but we do understand the confusion and want to avoid this for future readers. Therefore, throughout the document we have changed all instances to: “percent stand biomass composition of species”.

L367-371…

Increased with higher total K….” or “ were positively correlated with total …

370 change “the stem density…” for “stem density decreased with increasing surface water ammonium concentrations”

And so on with the direction of change in the regression results

A good point. All of our regressions are reported with increasing the predictor variable but we have clarified this throughout the document.

Discussion

This is defined in Table 2.

Figures

2,3, and 5 change “denote statistically different sites(groups)” for “denote significant differences”

done

Good suggestion, done.

This manuscript is a resubmission of an earlier submission. The following is a list of the peer review reports and author responses from that submission.

Round 1

Reviewer 1 Report

The link of mangrove-urbanisation is an interesting issue but there is a missing parameter that is important to assess in this study. Instead of the urban index, my attention is on how the hydrology of mangrove forests is controlled by the 'urbanisation'. Figure 1 clearly shows the hydrology modification by canals. The authors should explain the definition of 'partially restricted to tidal flow' (line 128) and partially restricted canals (135-136) with water level data that has been published somewhere (line 196-197). Water regime has significant control on vegetation community, especially mangroves, and this evidence should be deeply discussed in this manuscript (see line 401). The species dominance might be not related to urban/rural population or cover but is likely due to geomorphology and hydrology of the sites. The 'hidden' main driver is possibly the hydrology modification in urban area.

I'd suggest to sub-section the result into three assessed parameters (forest structure, hydrology and water chemistry) instead of the methods.

For further references, please see Friess et al in Biological Reviews (2012), Perez et al in Hydrobiologia (2017), Zhang et al in Ecological Informatics (2012), Van Loon in Aquatic Botany (2007), Alongi and Brinkman (2011)...etc

Some specific comments:

line 104: the classification for the urban index is quite confusing and not consistent. For example: 34 is the max for LEV but the greater value (42) is the min for SUA.

Table 1: you can make the ratio of urban cover : mangrove cover to assess site characteristics.

line 160-170: please explain why is LIDAR used in this study and only in San Juan and LEVMID? Did you interpolate it to other sites?

line 191-203: methodology of sampling/data collection for hydrology and water chemistry should be described.

line 211: what does hydro-geomorphology refer to ? Is it based on water level ? geomorphology classification ?

line 258: how many true and associate mangroves (out of 30 species) ?

line 350: what are the three methods ?

line 355-358: the statement is quite confusing.

line 376: please explain 'periodically flooded' in terms of tidal regime with the data.

line 374: this statement might be correct, but you need to support it with how much waste delivered to mangrove forests.

line 409-410: please provide reference for the statement misanthrope and synanthrope.

Conclusion need to be improved. The first paragraph is not relevant to the study and findings, but you can move it to the Introduction.

Author Response

Editor(s) and reviewers,

Thank you very much for your interest in our manuscript. Please find our revised manuscript and our response to the reviewers’ comments following the initial review. We found the reviewers’ comments very helpful and we have made the appropriate changes in the manuscript. In addition to their specific requests, we have made some additional changes to the manuscript, including the addition of a new predictor variable (soil porewater salinity) and conducting one of the ANOVA tests at the plot level instead of site level, as outlined here:

We added predictor variables of soil porewater salinity to the regression analyses. These data recently became available and were found to be important in the analysis, so we felt it pertinent to include them. They contribute to the discussion on the role of tidal connectivity and the potential influence of urbanization on restricted tidal flow. Changes resulting from these additional variables are:
- Lines 171-178, description of the methods for measuring porewater salinity
- Table2, addition of porewater salinity in the variable description table
- Figure 5, inclusion of porewater salinity as the best single predictor of the percent contribution of both racemosa and R. mangle to stand biomass.
- Lines 362-365, description of the effect of porewater salinity on the composition metrics.
- Table 5, inclusion of porewater salinity as an important predictor for canopy density, % biomass as R. mangle.
- Line 471, inclusion of porewater salinity in the discussion
- Lines 23-24, included this finding in the abstract
Clarified the maximum LiDAR height terminology throughout. We were using different terms to describe this forest height metric and we have now made sure to be consistent in this throughout.
- Max height is the 90^th percentile of LiDAR return heights. This has been changed in table 2, described in lines 200-202, and changed in all figures and tables.
Lines 312-318, for watershed comparisons, performed ANOVAs at the plot level, as intended, instead of at the site level as originally reported. This changed the results from no-statistical differences to some statistical differences in metrics between watersheds.

Original reviewer comments are provided below, followed by our response. The original reviewer page numbers refer to the original line numbers, but our response line numbers refer to the NEW UPDATED document. These changes are also marked within the new document along with the original reviewer comments pertaining to the changes made.

Reviewer 1

We appreciate your recognition of the importance of hydrology and the potential influence urbanization may impart on it. Because we recognize it as well, we have explicitly tested for some connection to hydrology and inundation, but our results found little evidence for a direct connection. However, we recognize as you point out that a discussion on the indirect influence of urbanization on hydrology via isolated infrastructure projects, is warranted. A previous publication has examined this in more detail, and we cited this publication in the original line 124 (now line 136). However, given your suggestion, we have elaborated on the urban-hydrology link in the following ways:
- To clarify the hydro-geomorphic classifications (e.g. partial tidal restriction):
  - Lines 138 to 160: Clarifying that the previous study (Branoff, 2020, Hydrological Sciences Journal) shows a significant difference in the rainfall response between partially restricted and open hydro-geomorphologies. Also stating the mean diurnal ranges of water levels at all sites and comparing them to open ocean ranges at nearby buoys.
- To expand on the potential influence of hydrology modifications:
  - Added the second to last paragraph of the discussion (lines 463-487), as follows:
    - Previous studies have largely hypothesized that observed patterns in urban mangrove species composition are primarily due to changes in hydrology from the urban environment [32, 34]. Indeed tidal influence and connectivity are critical to mangrove zonation and competition with non-halophytes [85, 86]. Thus, it was hypothesized in the present study that changes in the mangrove community along the urban gradient could be tied to changes in tidal connectivity and hydrology. A previous study at these sites did find evidence of reduced tidal amplitudes along the urban gradient as well as immediately upstream of canal restrictions or dredging projects [45]. The present study, however, found mixed evidence in support of this hypothesis. While mangrove composition did change along the urban gradient and a connection to porewater salinity was also observed, these changes were not consistently tied to changes in hydrology or to infrastructure projects. For instance, there was no significant difference in the number of species per plot or the percent composition of A. germinans or L. racemosa between the dredged portion of the Caño Martín Peña at MPDMAX and the un-dredged portion roughly 500 m away at MPNMIN, which exhibits a near 50% (20 cm) reduction in the diurnal tide range. The same is true for SUAMAX and SUAMIN, the two sites on either side of the Suárez canal restriction at the Baldorioty expressway, which also exhibit a 14 cm difference in diurnal tide ranges between the two. Thus, changes in hydrology as a result of infrastructural projects alone cannot account for the observed change in compositional metrics along the urban gradient. Further, while inundation parameters and soil porewater salinity were important in describing variability in forest composition under multiple regression, this importance was shared with and often shadowed by that attributed to surrounding urban metrics. As a result, it cannot be definitively concluded that hydrology or infrastructure projects are the most important drivers of urban mangrove floral community composition. Instead there may be an alternative selection pressure in urban environments (e.g. residential and municipal landscaping) that drives the observed patterns, which may have implications for the suitability of urban mangroves to provide habitat to a wide variety of taxa that often seek specific floral species [87].

I'd suggest to sub-section the result into three assessed parameters (forest structure, hydrology and water chemistry) instead of the methods.

We appreciate this suggestion, however, our approach does not follow this sectioning and it would be confusing to try and split up the multiple regression results into these categories. We therefore argue that the current organization should remain as it keeps the consistency throughout the manuscript

We have added them. Thank you!

Some specific comments:

line 104: the classification for the urban index is quite confusing and not consistent. For example: 34 is the max for LEV but the greater value (42) is the min for SUA.

Good point. The min/max labels are local only and refer only to the waterbody in question, they do not apply to the other sites. We briefly explained this in Table 1 but we have now moved it to the main text and expanded as follows:
- Line 103-115: Sites in the San Juan Bay Estuary are named for their waterbodies (BAH is the San Juan Bay, MPN is the Caño Martín Peña, SAN is the San José lagoon, SUA is the Suárez canal, TOR is the Torrecilla lagoon, and PIN is the Piñones lagoon. In Ponce and Levittown, mangrove area is comparatively smaller and so sites are named for their watershed only: LEV is Levittown and PON is Ponce. To ensure that we captured the most and least urban forests in a given area, two sites per waterbody in the San Juan Bay Estuary and three sites each in Ponce and Levittown were selected, each representing the relative minimum, mid, or maximum urbanness levels for that area. In the San Juan Bay Estuary, two sites were placed in the minimum and maximum levels of urbanness in each waterbody, as denoted by “MIN” and “MAX” following waterbody abbreviations in site names. In Levittown and Ponce, three sites were placed at the minimum, median, and maximum urbanness levels of each watershed, as denoted by “MIN”, “MID” and “MAX” following watershed (“PON” and “LEV”) abbreviations. Thus, “MIN”, “MID” and “MAX” in site names are relative to local urbanness levels only, not island wide.

Table 1: you can make the ratio of urban cover : mangrove cover to assess site characteristics.

A good suggestion, we have added this in table 1 as well as clarified the variables in the table legend.

line 160-170: please explain why is LIDAR used in this study and only in San Juan and LEVMID? Did you interpolate it to other sites?

We clarified that we used available LiDAR data that were collected as part of another project for parts of Puerto Rico, and those areas included San Juan and LEVMID. Interpolating the LiDAR data (or metrics) outside of the areas of acquisition is out of the scope of this paper. The text now reads:
- Line 189: Airborne LiDAR data were collected over parts of Puerto Rico in March of 2017 using the NASA G-LiHT (Goddard's LiDAR, Hyperspectral & Thermal) imaging system [57], as part of the US Department of Energy, Next-Generation Ecosystem Experiments–Tropics project (https://ngee-tropics.lbl.gov) (Figure 1). LiDAR data provide detailed information on forest 3D structure and therefore can be used to quantify forest structure across urban gradients. Among our sites, LiDAR data from the GLiHT camplaign were only available for the San Juan Bay Estuary sites and the LEVMID site

line 191-203: methodology of sampling/data collection for hydrology and water chemistry should be described.

These are described in detail in the cited publication, but we agree we need to provide more information, and have expanded our description as follows:
- Line 224-29: Water level models were constructed from water level observations recorded by data loggers at each site and precipitation observations at nearby weather stations. Tidal harmonics models were used to extract tidal constituents and moving sums were used to model precipitation contributions to observed water levels. These were then used to reconstruct water levels over a five-year period in which flooding conditions were assessed every hour by comparing the predicted water level to the elevation of the forest as determined from digital elevation models.
- Line 234-241: These measurements were only available for the fourteen sites in San Juan. Monthly measurements are obtained in-situ by a handheld sonde and are dissolved oxygen (mg/L), pH, salinity (PSS), specific conductivity (ms/cm), and temperature (^oC). Bi-annual measurements are obtained by water samples from surface waters and laboratory chemical analyses. These include Ammonium (mg/L), total Kjeldahl nitrogen (mg/L), nitrate & nitrite (mg/L), and phosphorus (mg/L). A detailed description of this process is given in Branoff [45] and scripts and results for this analysis can be found at the url: github.com/BBranoff/Urban-Mangrove-Hydrology.

line 211: what does hydro-geomorphology refer to ? Is it based on water level ? geomorphology classification ?

This refers to the previously described tidal connectivities. We have elaborated as follows:
- Line 250:…hydro-geomorphologies (i.e. open embayment, restricted embayment, open canal, restricted canal)…

line 258: how many true and associate mangroves (out of 30 species) ?

As far as we know there is no definitive list of “associate mangrove” species. However, we understand how similar information may be useful and so we have characterized the species according to their published halophytic characteristics from Santos et al. (2016) plant and cell physiology.
- Line 180-181: Halophytic plant types and salinity tolerances, when available, were provided by Santos, et al. [50]
- Line 304-305: Species include all three true mangrove species of Puerto Rico in addition to five other hydrohalophytic non-true mangrove species, three psammophilic species, and an additional nineteen species with undescribed halophytic characteristics.
- Table 4: added symbols denoting the characteristics of each species

line 350: what are the three methods ?

Good point. We have clarified by adding the following:
- Line 395: Results from three separate statistical methods (i.e. Non-metric multidimensional scaling, simple regression, and multiple regression)…

line 355-358: the statement is quite confusing.

We apologize for that. We have attempted to clarify as follows:
- Line 402-404: Still, simple regression models showed that forest composition was mostly explained by urban variables (i.e. population density and the urban index), and demonstrated increasing tree diversity but decreasing mangrove diversity with greater urbanness.

line 376: please explain 'periodically flooded' in terms of tidal regime with the data.

Good point, we added the range in daily flood frequencies:
- Line 413-414: This may be because the most urban mangroves are permanently or periodically flooded (0.001 – 2.5 times per day) by urban waters…

line 374: this statement might be correct, but you need to support it with how much waste delivered to mangrove forests.

The reviewer is correct, and we have added to the sentence as follows:
- Line 419-423: Although a previous study at these sites found no linear link between the urban index and surface water nitrogen and phosphorus, it did suggest that urban wastewater effluents may be contributing to elevated concentrations of these elements in the most urban mangrove waters, which held three times as much nitrate and nitrite as the least urban waters [45].

line 409-410: please provide reference for the statement misanthrope and synanthrope

Unfortunately, there is no previous study on mangrove floral synanthropy. We are providing a suggestion, based on the results of the study, that they may be classified as such. Therefore, we cannot provide a reference.

Conclusion need to be improved. The first paragraph is not relevant to the study and findings, but you can move it to the Introduction.

We agree and we have substantially redone the conclusion (line 495)

Reviewer 2 Report

The paper entitled “The structure and composition of Puerto Rico’s urban mangroves” presents a well in-depth study of how urbanisation can influence the structure of mangrove communities. The study was able to link not only changes in species composition with increasing urbanisation, but also in forest structure attributes, these changes combined are rightly discussed as elements that have a great potential of changing ecosystem function and their associated ecosystems services.

Below these lines, the authors can find suggestions on minimal edits to the structure of the paper and to improve the clarity of a few sentences that will benefit the quality of the paper.

Introduction

L70 – Typing mistake “empirical little evidence” -> “little empirical evidence”

Methods

The study site description is showing elements that correspond to the results section of the paper (e.g. the urban index is presented in Table1 and figure 1). The reasoning is clear as why the authors made this decision, but it is confusing to the reader.

Please consider reorganizing the description of the methods as to introduce the readers to the urban index (UI) prior to presenting UI values assigned to each study site. As the UI are the result of scoring methodologies applied during the study, these should be better presented in the results section. A suggestion is for this section to move tale 1 to the results section, leaving an overall general description of the study site’s proximity to urban areas, along with Fig1. (removing the boxplots that represent also results of this study).

L223-230 The readability of this section will improve with clear statements of which are considered response and predictor variables. (i.e. "The contribution of environmental variables and different urban elements on forest structure attributes (stand density, canopy cover, diversity, etc.) were analysed by means of simple and multiple regression models. Models were constructed through...."). Please also consider changing sentence structures from “Simple regression was hen performed”-> “Simple regression models were then performed” The same should be considered for multiple regression models.

Results

Figs. 2 and 3

1)Annotations are crowded on the panels and overlap with the violin plots. Consider increasing the height of the final plot to avoid overlaps, alternatively consider leaving only alphabets and removing means .

2)The violin plots are missing a colour scale legend. By intuition one can see it’s related to the study sites, but it’s really not adding information. Consider using no-fill colour or describing briefly on the fig. legend.

3)The description of what the alphabet letter annotations denote is SO confusing. Perhaps the authors mean to say “different letters indicate statistical differences”?. This means that violins sharing the same letter show non-significant differences, whereas violins with different letters are statistically different, then "a" is significantly different from "b", but not from "ab". Please keep in mind that the term “similar” is not used in statistics. Differences are ether “significant” or “not significant”. Please adhere to this principle throughout the text.

4) maintain consistency with graphics (axis scale labels vary in colour and arrangement – see x-axes on Figs. 2 and 3)

L312 please change to “Forest composition was best described by simple regression models which included urban variables, whereas the different metrics (e.g. basal area, density, etc) were best explained by ....".

L314-316 Unclear description of results, what does surrounding refer to? A. germinans biomass decreased with increasing? urban index?, while the biomass of L. racemosa was positively correlated with increasing population density.

L321-328 The study has a bit more than many response variables, please be kind to the readers and be more specific. Also consider an edition of “mostly structural, were most strongly modelled” to a more readable sentence. Terms such as “Strongly modelled” “best modelled” are not adding clarity to the message. Please consider using simple sentences … “Tree height, stem width, … were positively correlated to total Kjendal nitrogen, whereas height skewness decreased with phosphorus content in water. Sentences as they are don’t give much information other than “water chemistry affects several metrics of forest structure”, and the direction of the influence is missing. Additionally, keep consistency with term use “mean and max. forest height” is earlier defined as mean and max heights? (Tale 2).

L329-330 Delete sentence.

Fig. 5. Figure with legend should be able to stand alone from the text (understandable without referring to main text) please define pertinent abbreviations within the fig. legend (i.e. Height SD (standard deviation of tree height, DBH (stem diameter)…

Discussion

L365 change “larger large” -> “trees with higher maximum stem diameter sizes, which were 27% larger than at the least urban forests”

L379-397 It’s worth discussing self-thinning trajectories. Any forest in development undergoes the same pattern, as trees grow larger, the stand density is reduced by mere displacement through competition. Faster growing trees gain larger canopies, have improved nutrient uptake, eventually shading and suppressing neighbours which will die out (hence reduce density). This is not necessarily solely related to nutrient content or urbanisation and deserves being considered in the arguments presented here. In mangroves stand age is a very difficult matter to track, but there might be the case that the higher density stands are just younger than lower density sites.

Author Response

Editor(s) and reviewers,

Thank you very much for your interest in our manuscript. Please find our revised manuscript and our response to the reviewers’ comments following the initial review. We found the reviewers’ comments very helpful and we have made the appropriate changes in the manuscript. In addition to their specific requests by the reviewers, we have made some additional changes to the manuscript, including the addition of a new predictor variable (soil porewater salinity) and conducting one of the ANOVA tests at the plot level instead of site level, as outlined here:

We added predictor variables of soil porewater salinity to the regression analyses. These data recently became available and were found to be important in the analysis, so we felt it pertinent to include them. They contribute to the discussion on the role of tidal connectivity and the potential influence of urbanization on restricted tidal flow. Changes resulting from these additional variables are:
- Lines 171-178, description of the methods for measuring porewater salinity
- Table2, addition of porewater salinity in the variable description table
- Figure 5, inclusion of porewater salinity as the best single predictor of the percent contribution of both racemosa and R. mangle to stand biomass.
- Lines 362-365, description of the effect of porewater salinity on the composition metrics.
- Table 5, inclusion of porewater salinity as an important predictor for canopy density, % biomass as R. mangle.
- Line 471, inclusion of porewater salinity in the discussion
- Lines 23-24, included this finding in the abstract
Clarified the maximum LiDAR height terminology throughout. We were using different terms to describe this forest height metric and we have now made sure to be consistent in this throughout.
- Max height is the 90^th percentile of LiDAR return heights. This has been changed in table 2, described in lines 200-202, and changed in all figures and tables.
Lines 312-318, for watershed comparisons, performed ANOVAs at the plot level, as intended, instead of at the site level as originally reported. This changed the results from no-statistical differences to some statistical differences in metrics between watersheds.

Reviewer 2

Thank you for your kind comments!

Below these lines, the authors can find suggestions on minimal edits to the structure of the paper and to improve the clarity of a few sentences that will benefit the quality of the paper.

Introduction

L70 – Typing mistake “empirical little evidence” -> “little empirical evidence”

Great, done! (Line 70)

Methods

The urban index was developed in a separate study and applied here using the same study sites. In our revised manuscript we have attempted to clarify this issue as follows:
- Line 96-98: We focused on twenty mangrove sites (one-hectare each) from Branoff [45] and distributed in the coastal areas of Puerto Rico. These sites were established according to a previously developed urban index [45], such that they fell within the greatest range of urbanness

Again, the urban index was not developed for this study and is presented in a separate study. We hope that the above clarification ameliorates this confusion.

Thank you for these suggestions; we have re-written the paragraph as follows:
- Line 263-276: The contribution of environmental predictor variables (e.g. urban cover, proportion of time flooded, and ammonium concentration etc.) on forest structure and composition (e.g. stem density, biomass, number of species etc.) was analyzed through both simple and multiple regression. To single out the most important environmental influences on forest metrics, simple regression models were constructed through the lm function [57] in the form y~x, y~ln(x), and y~ln(x+1) when environmental predictor variables included values less than or equal to 0. The highest performing models were selected as those with the highest R² value whose p-value was lower than 0.05.

To examine the combined and relative importance of urban, hydrology, and water chemistry variables in explaining variability in forest structure and composition, multiple regression models were constructed by including one variable from each of the three potential influences of land cover, hydrology, and water chemistry. These models took the form of…

Results

Figs. 2 and 3

We feel its important to include the means as there is no other table with this information, but we have stretched the figure and tried to make sure the annotations are clear of the violins.

Thank you. We clarified the color scale in the figure legend.

We have changed these in the figure legends to read: different letters denote statistically different sites

4) maintain consistency with graphics (axis scale labels vary in colour and arrangement – see x-axes on Figs. 2 and 3)

Good point, we changed the axis labels on figure 2 to match that of figure 3. Colors corresponding to sites in Ponce and Levittown are not included in table 3 but all other colors should be consistent between the two tables.

We changed the sentence in question to read:
- Line 358-359: In simple regression, forest composition was best described by models including the urban index and population density, whereas structural metrics were best explained by models involving flooding and water chemistry predictors.

Yes, your interpretation is correct. With the addition of porewater salinity, this has changed to read as follows:
- Line 359 – 365: The percent of mangrove biomass as L. racemosa decreased with increasing porewater salinity while that of R. mangle increased within increasing porewater salinity. Further, while the percentage of biomass as L. racemosa was significantly greater in the most urban sites than the least urban sites, that of R. mangle showed the opposite trend and was greatest in the least urban sites.

These are very useful comments; thank you! We have followed your recommendation in the paragraph by stating only the direction of the relationship, and we agree this results in a clearer description (Line 369 – 375). We also ensured that the use of “height” is consistent without.

L329-330 Delete sentence.

We agree and we have changed the figure abbreviations to read the full word(s).

Discussion

L365 change “larger large” -> “trees with higher maximum stem diameter sizes, which were 27% larger than at the least urban forests”

Line 411-4139: Agreed, done.

We agree, however, in most cases this dynamic of self thinning results in higher biomass and basal area with age, which we did not observe in our study. Thus, we believe there is a confounding factor, temperature, which may be influence the self-thinning dynamic. To clarify this, we adjusted the paragraph as follows:
- Line 428-436: This concomitant reduction in stem density with increasing tree size has also been observed in other forests of the Caribbean [51, 75-77], and can be expected from a self-thinning dynamic in which larger trees outcompete smaller surrounding trees, thus reducing stem density and increasing average tree size as the forest matures [51]. Yet, this theory would also predict an overall increase in forest basal area and biomass as stem density is reduced, a pattern we could not detect in the present study (Biomass ~ Stem Density: p > 0.1, R² < 0.05; Biomass ~ Ammonium: p > 0.3, R²< 0.1). One study in South Florida suggests that this tradeoff between stem density and biomass occurs only in the absence of stress [76]. Thus, the absence of such a pattern in the present study may be indicative of stress that is limiting forest basal area and biomass despite sufficient nutrient conditions.

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