Growth Patterns of Small Pelagic Fish in West Africa

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Dear authors,

Please find enclosed your manuscript with my comments, which I believe will contribute to the quality of the manuscript.

Best regards,

Reviewer

Comments for author File: Comments.pdf

Author Response

• Comments 1: “pelagic”

Response (Gomes et al.): Many Thanks. The word “pelagics” has been corrected by “pelagic”.

• Comments 2: Close this parenthesis at the end of the statement.

Response (Gomes et al.): Thank you, the parenthesis has been closed.

• Comments 3: Have you accidentally given a reference with the same number twice, or should a different reference be given here?

Response (Gomes et al.): Yes, We have corrected.

• Comments 4: Place the percent sign next to the number without a space.

Response (Gomes et al.): Many Thanks. “Fishing is an essential economic, social, and cultural activity in West Africa. In 2017, the total catch of small pelagic fish in West Africa was around 1,300,000 tons (t), with 65% in Mauritania, 28% in Senegal, and 7% in Gambia and Guinea Bissau, re-spectively [13].”

• Comments 5: Write the kilogram as an abbreviation.

Response (Gomes et al.): Thanks. “In Guinea Bissau, the annual availability fluctuates between 25,000 and 2,000 t of small pelagic for a per capita consumption of between 16 and 18 kg [13].”

• Comments 6: Please reformulate this paragraph and clearly define the aims of the work.

Response (Gomes et al.): Thanks. "This study analyzes and compares the growth of E. fimbriata and S. maderensis, integrating data from existing literature with findings specific to the African tropical Atlantic Ocean. By focusing on growth parameters within the same geographical area, we aim to highlight the environmental factors influencing these species. Our discussion emphasizes the implications for stock management of E. fimbriata and S. maderensis in Guinea-Bissau waters, providing insights into sustainable practices that can help maintain healthy populations in the face of environmental changes. Through this analysis, we hope to contribute to effective fisheries management strategies that consider both ecological dynamics and the socioeconomic importance of these species."

• Comments 7:?

Response (Gomes et al.): It is the unit of measurement of salinity (practical salinity unit)

• Comments 8: Part of the manuscript (lines 120-135) is too long. Please leave only a few pieces of information that are important for the work.

Response (Gomes et al.): Thanks for the recommendation. This part has been summarized. "Guinea Bissau has also important rivers, such as the Geba, Cacheu, Buba, and Cacine, and an island part that forms the Bijagós archipelago [16,35]. The Cacheu River is located in the extreme northwest of Guinea-Bissau, in the administrative re-gion of Cacheu, in the area of Cacheu and São Domingos. It is bounded to the north by the Suzana / S. Domingos area and the Antoninho and Djopa Rivers, to the south by the Cobiana River, and to the west by the Bolol and Defename rivers [40,41]. The Buba River covers an area of 271 km², with a width of about 4 km from the mouth to Farancunda and a length of 52 km from the source to the mouth [42].  The Cacine River is located in the Tombali region, Quitafine sector, and consists of about 18 river branches [43]."

• Comments 9: Write the full name and abbreviations or only abbreviations for all.

Response (Gomes et al.): Thank you, full name has been given. “Remotely-sensed environmental data were analysed to test the effects of Sea Sur-face Salinity (SSS), Sea Surface Temperature (SST), and coastal upwelling index (CUI) on the growth of S. maderensis and E. fimbriata.”

• Comments 10: Please do not start a sentence with an abbreviation.

Response (Gomes et al.): Thanks for the note, the correction has been made. “The Sea Surface Salinity, derived from SMOS (Soil Moisture and Ocean Salinity satellite, https://earth.esa.int/eogateway/missions/smos, last visited: 22/02/2024) were averaged in the first 100 km of the Guinea Bissau coast.”

• Comments 11: There is a big difference in the number of specimens examined. Does this affect the validity of the results?

Response (Gomes et al.): Thanks for the comment. However, in the case of countries with poor fisheries data, this does not affect the results. On the contrary, it provides a starting point to help fisheries managers in the assessment and management of resources.

• Comments 12: Delete

Response (Gomes et al.): Thanks, this has been deleted. “To compare the monthly length variations, the data were analyzed either using one-way parametric analysis of variance (ANOVA) or the nonparametric mehod of Tukey’s honest significant difference (HSD) post hoc test or the Kruskal-Wallis test depending on whether the data was normally distributed.”

• Comments 13: Unless I've missed something, it seems to me that you're using this abbreviation (chlorophile) for the first time in the text. It should be added to the environmental parameters.

Response (Gomes et al.): Thanks, that was a mistake, it has been corrected. It was rather the SSS. “The Pearson test was used to study the correlation between the annual value mean length of E. fimbriata and S. maderensis with the mean annual of each environmental parameter, SST, SSS, and CUI [57].”

• Comments 14: Please use capital letters when writing the months of the year.

Response (Gomes et al.): Thanks for the comments. it has been corrected. “Kruskal-Wallis's pairwise comparison test showed that the length did not vary be-tween the months of January-February, January-July, February-July, February-November, March-May, March-June, March-December, May-June, May-July, May-December, and June-December.”

• Comments 15: Please use capital letters when writing the months of the year.

Response (Gomes et al.): Thanks for the comments. it has been corrected. “Kruskal-Wallis's pairwise comparison test showed that the length did not vary except for January-march, January-august, February-March, February-August, March-April, March-June and March-September.”

• Comments 16: In July of which year?

Response (Gomes et al.): Many thanks for the remark, it's in July 2021. “Based on the length frequency data of E. fimbriata, L_∞, K, and φ' for August 2020 to July 2021 caught off the Bissau Guinean coast were estimated to be 36.2 cm, 0.61 year^-1, and 2.91 respectively.”

• Comments 17:?

Response (Gomes et al.): Thanks, it was an exponent. "year^-1". “Based on the length frequency data of E. fimbriata, L_∞, K, and φ' for August 2020 to July 2021 caught off the Bissau Guinean coast were estimated to be 36.2 cm, 0.61 year^-1, and 2.91 respectively.”

• Comments 18: Do the results of this work only refer to the sampling in Guinea-Bissau (Fig. 2)? Why do you mention Côte d'Ivoire, Nigeria, Sierra Leone, Congo and Senegal? Are these also your results? If yes, then change Fig. 2, and if not, then move this part to the discussion.

Response (Gomes et al.): Thanks for the recommendations. Corrections have been taken into account.

• Comments 19: "a" and "b" are not visible in the diagram. And again the same question for the study area?

Response (Gomes et al.): Thank you, we have specified a and b in the figures.

• Comments 20: "a" and "b" are not visible in the diagram.

Response (Gomes et al.): Thank you, we have specified a and b in the figures.

• Comments 21: Delete

Response (Gomes et al.): Thanks for suggestion. “For instance, adverse environmental conditions and limited food availability early during the stages of life may lead to slower growth, decreased energy reserves and subsequently diminished fitness throughout lifespan [62].”

• Comments 22: Latin name?

Response (Gomes et al.): Thanks, we added the Latin name "Engraulis encrasicolus". “In the case of European anchovy (Engraulis encrasicolus) larvae, growth has been linked to higher phytoplankton values [69].”

• Comments 23: fimbriata

Response (Gomes et al.): Thanks. “This phenomenon may lead to a decrease in size at maturity and an increase in fecun-dity of E. fimbriata under high salinity conditions [23,84].”

• Comments 24: Close the bracket.

Response (Gomes et al.): Many Thanks. “Thus, a high removal of older and larger individuals can lead to a change in species growth dynamics (e.g. population age structure and reproductive capacity [7,19,92]).”

• Comments 25: In general, use Latin species names throughout the text, except at this point in the text and for key words. Please decide what you think is better and make it consistent throughout the text.

Response (Gomes et al.): thanks. We use the latin name. “Better information on the population biology of E. fimbriata and S. maderensis in variable environments with complex interactions will help fisheries managers to plan and adapt to environmental change.”

• Comments 26: I advise you not to start and end the discussion with "climate change". The research for the purposes of this paper takes 12 months, and in the discussion you mainly address the effect of temperature on growth parameters. Climate is not just temperature, and claiming that something is a consequence of climate change requires a much longer follow-up than 12 months. Try replacing the term "climate change" with another term or terms. It is very likely that everything you cite in your paper is a consequence of climate change, among other influences, but you have no concrete evidence of this in your paper.

Response (Gomes et al.): Thank you for your suggestion. We have taken into account and modified by environmental change.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

 

General points:

Interesting paper, although it is difficult to draw any meaningful conclusions from the way the data are presented.

To help this I would replace the auximetric plots with some maps of the region, showing how these variables change in space.

More information is needed on how you calculated growth parameters. Referencing a package it not enough detail. You can present figures from this analysis so we can assess how robust it is.

The figures need editing and there is a disconnect between the data presented in figure 4, 5 and table 1 – it reads as though these are all the same data. The sample sizes used are also small, so some justification for using the statistical approach is needed (i.e. how robust is Pearson's correlation to small datasets?). Also, were all datasets in this plot normally distributed?

Lots of the text detailing comparisons to growth parameters from other studies could be moved to discussion, rather than results.

Fundamentally, I don't think the conclusions you have drawn can be supported by the results you have presented. 

 

Please see below for line-by line comments. 

Line specific comments.

Line 19: These species appear?

Line 22: Not sure what ‘size-dependent patterns of the two growth mechanisms’ means – needs explanation

Line 24: Remove contents of brackets. it's not referred to in the sentence. You can just say - in upwelling environments.

Line 25: change to ‘areas’

Line 29: other species, or the same species?

Line 42: close brackets after ‘]’

Line 67: ‘It breeds throughout the year in Senegal.’ just in senegal? or is this the only place it has been studied? Also, combine this sentence with the next and add a reference (I assume [18]?)

Line 68: what does ‘with continuous reproduction’ mean? if it is a discrete season from Jan-Feb, how can it be continuous reproduction?

Line 74: ‘Their’ – Whose? And is this a stock assessment?

Line 76: ‘on the estuary’ dependent on estuarine environments for certain parts of its life cycle?

Line 77: delete ‘the’

Line 77: add ‘salinity’ before ‘between’

Line 78: remove ‘Coastal’

Lines 79 – 80: ‘…season in the estuary and the hot season at sea [23]. ‘ where? and what estuary? or all estuaries in the area?

Line 84: ‘(peak in 2016…)’ it does not look like you have a peak in 2016. If the plot is stacked data, possibly 2008 or 2013 were the largest catches in this time period? Revisit this to make sure the values are correct.

Line 86: change ‘Key parameters study of ‘ to ‘studies exploring key parameters of’

Line 90: remove ‘the’

Line 94: change ‘as elsewhere help fisheries’ to ‘will help’

Figure 1/Line100: how are these catches reconstructed? Needs some explanation

Lines 110 & 111: How do the Canary Currebt and Guinea current interact? are they flowing in different directions? If it was possible to add these to the a context map in Figure 2, that would be helpful

Line 113: ‘36 to 30 psu’ you refer to ppt on line 77 – be consistent

Lines 115 & 116: ‘With a coastline of 274 km and a continental shelf of 45,000 km, the coastal zone of Guinea-Bissau is mainly covered by mangroves [16,34,35]. ‘  these three statements don’t logically follow - why does the coastal zone being dominate by mangroves relate to  the size of the continental shelf?

Line 117: change to ‘ecosystem’ and ‘protecting’

Lines 120 – 134: way too much information on the study area - no need for information on the bed topography of different river systems - cut back to one paragraph of relevant info for the study. None of this comes up again or is relevant to the findings.

Figure 2: map needs to be improved - at a minimum with a grid of lat-long values along each edge. A second panel or inset area in a broader geographical context would also be useful, you could add the current locations mentioned in lines 110-112 on top of this as well.

Line 165: ‘Data on the growth’ this implies these fish were aged or the individual growth was analyzed somehow. I would change this to reflect that length measurements were obtained in order to deduce growth at a population level.

Line 160: capitalize ‘To’

Line 161: change to ‘caught in encircling…’

Line 167: explain what K and Linf are n detail. These are fundamental values used throughout the paper. Anyone not familiar with growth studies will not know what these are/represent.

Line 168: TropfishR is a large package with many different functions. What did you use specifically? This needs more description as it is a fundamental part of the paper.

Did you use the ELEFAN functions? If so, this results in figures that can be included in the manuscript to help the reader assess the robustness of the analysis.

Line 183: the section on statistical analyses covers lots of tests in a single paragraph. These would be better suited in the same sections as the methods you are describing.

Line 190: add ‘value’ after ‘annual’

Line 192: this is different to the symbol used in the equation on line 173. You have used a lower case Phi here but upper case in the equation

Line 194: ‘These populations represent the entire geographical range of E. fimbriata and S. maderensis’s distribution’

You say in the introduction that S. madrensis is also fished heavily in Mauritania, so this statement is incorrect without knowledge of stock boundaries etc. There are also presence records in GBIF of this species as far north as the Mediterranean.

Line 196: same comment as above about Phi notation

Line 201: ‘respectively’ not needed as you only refer to one value.

Lines 203 – 204: too many results in a single sentence, it is difficult to make sense of this. Also inconsistent capitalization. This data would be better presented in a different format, perhaps a table?

Line 208 &  209: same comment as above.

Figure 3: Given the details in the above paragraph about between month differences, this would be better as a multi-panel figure (full page) showing the individual monthly data. You can then highlight the months of highest average size and the reader can visually see any cohort progression through time.

Lines 218 – 221: This is discussion text - contextualizing the results you are presenting.  

Table 1: what is your t value in this table? is it a t-test statistic value?

At a minimum you should use a sample size of 25 or more for Pearson’s correlations (ideally 30 to fit with the central limit theorem for normality), your size is only 12.

I took a look at your figure and can't easily see which dataset is CUI (see comment below), however extracting values for S. maderensis (grey solid line) and CUI (long dashed with cross) the correlation between these and S. maderensis is 0.4.

Using a t-test, this relationship is not significant due to the small sample size. The critical t-value is 1.8 and the t-test statistic is 1.3.

However, doing the same thing for data in figure 5, it matched what you have here - which one is correct?

Figure 4: much easier to interpret with a figure legend rather than textual descriptions of each dataset.

I cannot see a black solid line with triangle - with diamond?

Your left hand y-axis is confusing, do all these values just conveniently fall in this range?

The secondary y-axis is even more confusing. Your legend says that the CUI is represented by long dashed line with cross, the max value of this dataset is less then 5, so why is the max axis value 40? Is this the CUI dataset? or is it the solid black with diamond, which would explain the large axis? If not, change this to something more appropriate (0-5).

I also don't see what '(black line)' on line 235 is referring to.

Lastly, if the fish length values are means, there should be confidence intervals on the plot

Lines 241 – 244: How were these estimated - see methods. You do not give enough info here. You can present ELEFAN outputs to let the reader look at your analysis.

Line 246: gradient or just a difference between two values? No obvious gradient is presented.

Line 253: we can't visualize a gradient without knowing geographically where each dataset is from. Is there a way of visualizing this on a map?

Line 259: ‘asymptotic length (L∞)’ of which species?

Figure 5: is far away from its section in the text. I don't understand where these data have come from. The CUI values are not those presented in figure 4. The CUI range is only 0.2 - 0.28, the data in Figure 4 ranges from ~0.4 - 4.7.

It matches the statistical values in Table 1 and makes it clear that the t values are t-test statistics, but there is a disconnect between this and fig 4.

The fact still stands that this is a low number of values to perform parametric statistics on.

Figure 6: von-bertalanffy growth curves?

Add a & b to figure panels and make into one single figure.

add figure legend for colours

Figure 7: These plots are hard to interpret - add legends to describe point shape.

Add a & b, make a true 2-panel plot, not 2 separate images. they are currently different sizes with different formatting.

This is difficult to interpret and it's not clear what the significance of it is without geopraphical context. Could you represent growth performance index values on a map (e.g. heat map or proportional spot size)?

Line 287: remove first ‘adaptive’

Line 292: remove first ‘early

Line 296: change ‘to enhance their life success’ to ‘to increase their fitness’

 

Line 306: remove ‘in’

Line 356: add ‘conditions’ after ‘environmental’

Line 370: ‘The biological characteristics of E. fimbriata and S. maderensis (e.g. growth), are significantly influenced by environmental conditions (e.g. intensity of CUI and SST).’

Where is the significant result for this? I didn't see this anywhere.

Lines 371 – 372:  ‘Both species respond dramatically and rapidly to changes in ocean climate and have biological 372 characteristics that make them highly sensitive to environmental fluctuations.’ Needs citation

Line 374: ‘we observed that recruitment of small pelagics’ I didn't see any recruitment analyses or discussion or recruitment in this paper.

Line 375 – 377: ‘Environmental changes appear to have a significant positive effect on the growth of E. fimbriata and S. maderensis in Guinea-Bissau, confirming a more general trait of their high phenotypic plasticity’ 

how have you concluded this? you only present one significant relationship for one of these species.

You even say:

'No statistical differences between the 254 growth performance index (φ’) of historical data collected off the West African coast of E. 255 fimbriata and S. maderensis'

Line 378: Change ‘tactics’ to ‘patterns’, tactics suggest the fish are in control of this.

 

 

 

Comments on the Quality of English Language

Only minor editing required. 

Author Response

Interesting paper, although it is difficult to draw any meaningful conclusions from the way the data are presented.

To help this I would replace the auximetric plots with some maps of the region, showing how these variables change in space.

More information is needed on how you calculated growth parameters. Referencing a package it not enough detail. You can present figures from this analysis so we can assess how robust it is.

The figures need editing and there is a disconnect between the data presented in figure 4, 5 and table 1 – it reads as though these are all the same data. The sample sizes used are also small, so some justification for using the statistical approach is needed (i.e. how robust is Pearson's correlation to small datasets?). Also, were all datasets in this plot normally distributed?

Lots of the text detailing comparisons to growth parameters from other studies could be moved to discussion, rather than results.

Fundamentally, I don't think the conclusions you have drawn can be supported by the results you have presented.

Please see below for line-by line comments.

Line specific comments.

Response (Gomes et al.): Thank you for your comments which have greatly contributed to improving the document. Indeed, fisheries management is difficult, especially in developing countries where data available for stock identification and assessment are scarce or non-existent. However, given often inappropriate and ineffective fisheries management policies and increasing demand for fisheries resources, they have been facing for several decades the effects of overfishing and the collapse of fisheries in terms of local consumption, food security and economic value. Therefore, management guidelines and controls need to be simple, but also robust to uncertainties, and proportionate to the information available. In this way, generic management procedures can be applied, which are not necessarily the best for a given fishery, but may be better than inaction. This study demonstrates the applicability and use of results from countries where data collection and availability is difficult or even scarce; size frequencies to data-poor artisanal fisheries. It is hoped that these results can help assess many stocks currently considered too data poor to assess, particularly in developing countries.

Line 19: These species appear?

Response (Gomes et al.): Thanks for the suggestion, the correction has been added. “Often living in upwelling regions, these species appear to have developed mechanisms to cope with environmental variability, such as opportunistic reproductive tactics, enhancing their growth performance, or increasing their egg production by following the more predictable sys-tem attributes of seasonal cycles.”

Line 22: Not sure what ‘size-dependent patterns of the two growth mechanisms’ means – needs explanation

Response (Gomes et al.): To test this hypothesis, we investigated size-dependent patterns of the two growth mechanisms (i.e. growth rate) of two West African small pelagic populations (Ethmalosa fimbriata and Sardinella maderensis) in upwelling environments (sea surface temperature (SST), Sea Surface Salinity (SSS) and coastal upwelling index (CUI)). We examined growth rates of Ethmalosa fimbriata and Sardinella maderensis off Senegal and other coastal areas to determine how they relate to variations in environmental characteristics of coastal waters.  Indeed, the rate at which fish grow, which is a parameter that influences how individuals respond to various physiological stressors. Growth parameters vary in time and space, depending on parental condition (e.g., weight and condition), food availability (abundance and quality), environmental parameters (temperature and salinity), and evolutionary stressors (e.g., density, fishing pressure) (Baldé et al. 2019; Baldé et al. 2019; Puerta et al. 2015). Thus, information obtained from growth parameters could help identify the adaptation strategies and environmental conditions of a given species (Baldé et al. 2019), facilitating the modeling of population dynamics and impacts of anthropogenic factors for many fisheries considered poor in data (Froese et al. 2019).

Line 24: Remove contents of brackets. it's not referred to in the sentence. You can just say - in upwelling environments.

Response (Gomes et al.): Thanks for the comments, this part has been deleted.

Line 25: change to ‘areas’

Response (Gomes et al.): Thanks for the suggestion. “These results were discussed with other areas in African tropical Atlantic waters.”

Line 29: other species, or the same species?

Response (Gomes et al.): Thanks for the feedback, we have corrected this part. “It demonstrates how the geographical distribution of the same species, together with location-specific variation in temperature and food, can combine to determine local and regional growth responses in pelagic fish.”

Line 42: close brackets after ‘]’

Response (Gomes et al.): Thank you, the parentheses have been closed. “Adult fish size is often an important factor in fitness (e.g., distribution, fecundity, re-cruitment, and offspring survival [4–6]).”

Line 67: ‘It breeds throughout the year in Senegal.’ just in senegal? or is this the only place it has been studied? Also, combine this sentence with the next and add a reference (I assume [18]?)

Response (Gomes et al.): Thanks for the suggestion. “The first breeding season extends from April to October while the second breeding season, with continuous reproduction (more intense than during the first period), takes place from January to the end of February [18].”

Line 68: what does ‘with continuous reproduction’ mean? if it is a discrete season from Jan-Feb, how can it be continuous reproduction?

Response (Gomes et al.): Thanks for the comment. Indeed, It is a continuous reproduction throughout the year with peaks of reproduction in January and February (intense period of reproduction).

Line 74: ‘Their’ – Whose? And is this a stock assessment?

Response (Gomes et al.): We are talking about the evaluation of the stocks of Ethmalosa fimbriata and Sardinella maderensis. We have given details to the sentence.

Line 76: ‘on the estuary’ dependent on estuarine environments for certain parts of its life cycle?

Response (Gomes et al.): Thank you, we corrected the sentence.

Line 77: delete ‘the’

Response (Gomes et al.): Thank you for the suggestion. The word has been deleted.

Line 77: add ‘salinity’ before ‘between’

Response (Gomes et al.): Thank you for the suggestion.

Line 78: remove ‘Coastal’

Response (Gomes et al.): Thank you for the suggestion.

Lines 79 – 80: ‘…season in the estuary and the hot season at sea [23]. ‘ where? and what estuary? or all estuaries in the area?

Response (Gomes et al.): Thanks for comments. “In Sine Saloum (Senegal), Tthe reproduction of E. fimbriata is possible throughout the year and the main breeding periods are during the cold season in the estuary and the hot season at sea [23].”

Line 84: ‘(peak in 2016…)’ it does not look like you have a peak in 2016. If the plot is stacked data, possibly 2008 or 2013 were the largest catches in this time period? Revisit this to make sure the values are correct.

Response (Gomes et al.): Thank you for your comment. Indeed, during the period 2008 to 2019, the peaks were observed in 2010 (11,927 tons) and in 2013 (11,808 tons). Corrections have been made.” Catches of E. fimbriata in Guinea Bissau increased between 1970-1985 (peak in 1972 with 10500 t) and 1987-2005 (peak 1999 with 29000 t), with a slight decrease between 2008-2019 (peak in 20106 with 11,927 t; Figure 1).”

Line 86: change ‘Key parameters study of ‘ to ‘studies exploring key parameters of’

Response (Gomes et al.): Thanks for the suggestions. “Despite the importance of these small pelagic species, studies exploring key parameters (e.g., growth parameters) and size structure of E. fimbriata and S. maderensis have never been estimated in Guinea-Bissau.”

Line 90: remove ‘the’

Response (Gomes et al.): Thanks for the suggestions. the word has been removed. “Despite the importance of these small pelagic species, studies exploring key parameters (e.g., growth parameters) and size structure of E. fimbriata and S. maderensis have never been estimated in Guinea-Bissau.”

Line 94: change ‘as elsewhere help fisheries’ to ‘will help’

Response (Gomes et al.): Thanks. “Thus, knowledge on growth and reproduction in Guinea Bissau will help managers to sustainably manage these resources.”

Figure 1/Line100: how are these catches reconstructed? Needs some explanation

Response (Gomes et al.): Thanks, the data we present ('reconstructed data') combine official reported data and reconstructed estimates of unreported data (including major discards), with reference to individual EEZs. Official reported data are mainly extracted from the Food and Agriculture Organization of the United Nations (FAO) FishStat database. The "Reported catch" represent all catches deemed reported (including foreign) and allocated to this spatial entity. (see for methods https://www.seaaroundus.org/catch-reconstruction-and-allocation-methods/, consulted 11/10/2024)

Lines 110 & 111: How do the Canary Currebt and Guinea current interact? are they flowing in different directions? If it was possible to add these to the context map in Figure 2, that would be helpful

Response (Gomes et al.): During the cold season, the southward shift of the ITCZ ​​causes the descent of tropical influences. Off the coast of Guinea and Senegal, the currents are then generally parallel to the coast and flow south-southeast with speeds of around 0.5 knots. During the warm season, the Azores High strengthens and the ITCZ ​​rises, causing tropical influences to flow northward as far as Cape Blanc (Mauritania). This change in influences is at the origin of the advection of the Cape Verde circuit and the formation of the equatorial counter-current, which flows northward near the coast and strengthens the Guinea Current.

The existence of coastal upwelling on the west coast of Africa is due to the action of the trade winds that push surface waters towards the west, associated with the Coriolis force that carries the waters towards the open sea. There are two permanent upwelling zones: Cap Blanc and the small Senegalese coast. The waters of Guinea-Bissau benefit from the influence of the Senegalese upwelling because of their location downstream from the Canary Current. The biological contributions associated with the presence of upwelling are one of the factors that explain the fishery richness of the waters of the archipelago.

Fig. 1: The West African Ocean System (extract from J. R. Vanney, 1998 (VANNEY J.R. (1998)- L'Atlantique un regard géographique. Historiens et Géographes, n°363, p. 75-128)).

Line 113: ‘36 to 30 psu’ you refer to ppt on line 77 – be consistent

Response (Gomes et al.): Thank you, we have made corrections. We have harmonized everything in psu.

Lines 115 & 116: ‘With a coastline of 274 km and a continental shelf of 45,000 km, the coastal zone of Guinea-Bissau is mainly covered by mangroves [16,34,35]. ‘  these three statements don’t logically follow - why does the coastal zone being dominate by mangroves relate to  the size of the continental shelf?

Response (Gomes et al.): Corrections have been made. “The coastline is 274 km with a continental shelf of 45,000 km. The coastal area of ​​Guinea-Bissau is mainly covered by mangroves [16,34,35].”

Line 117: change to ‘ecosystem’ and ‘protecting’

Response (Gomes et al.): Many thanks. “These mangrove areas play a regulating role in the ecosystem, protecting the coast-line, and, among other things, provide nutrients for the surrounding fauna [36–38].”

Lines 120 – 134: way too much information on the study area - no need for information on the bed topography of different river systems - cut back to one paragraph of relevant info for the study. None of this comes up again or is relevant to the findings.

Response (Gomes et al.): Thank you very much for the suggestions. The paragraph has been summarized and only the relevant information has been kept. “Guinea Bissau has also important rivers, such as the Geba, Cacheu, Buba, and Cacine, and an island part that forms the Bijagós archipelago [16,35]. The Cacheu River is located in the extreme northwest of Guinea-Bissau, in the administrative re-gion of Cacheu, in the area of Cacheu and São Domingos. It is bounded to the north by the Suzana / S. Domingos area and the Antoninho and Djopa Rivers, to the south by the Cobiana River, and to the west by the Bolol and Defename rivers [40,41]. The Buba River covers an area of 271 km², with a width of about 4 km from the mouth to Farancunda and a length of 52 km from the source to the mouth [42].  The Cacine River is located in the Tombali region, Quitafine sector, and consists of about 18 river branches [43].”

Line 165: ‘Data on the growth’ this implies these fish were aged or the individual growth was analyzed somehow. I would change this to reflect that length measurements were obtained in order to deduce growth at a population level.

Response (Gomes et al.): Thanks, we appreciate.

Line 160: capitalize ‘To’

Response (Gomes et al.): Thanks.

Line 161: change to ‘caught in encircling…’

Response (Gomes et al.): Thanks for suggestion. “To have the same fishing gear selectivity for monthly comparisons of the length distribution only specimens caught in encircling gillnets (EGNs; [47]) were used.”

Line 167: explain what K and Linf are n detail. These are fundamental values used throughout the paper. Anyone not familiar with growth studies will not know what these are/represent.

Response (Gomes et al.): Many thanks L_∞: L_t value when the growth rate is zero; K: coefficient of growth rate.

Line 168: TropfishR is a large package with many different functions. What did you use specifically? This needs more description as it is a fundamental part of the paper.

Response (Gomes et al.): Thanks, we add more information. “The von Bertalanffy [48] growth parameters (K, L∞) were estimated from monthly length-frequency data using the ‘TropFishR’ (Tropical Fisheries Analysis with R) package [49]. These software packages contain many promising new features, but still include the Powell-Wetherall (P–W) method [49] as a central component of the proposed analyses [38]. The P—W method allows to estimate L∞ from a linearized transformation of the annual length frequency data (LFD) (i.e., the "catch curve"). To do this, the mean lengths (Lmean) of all fish larger than the catch length (Lc) are calculated.”

Did you use the ELEFAN functions? If so, this results in figures that can be included in the manuscript to help the reader assess the robustness of the analysis.

Response (Gomes et al.): Thanks we use the Powell-Wetherall (P–W) method. The P—W method allows to estimate L∞ from a linearized transformation of the annual length frequency data (LFD) (i.e., the "catch curve").

Line 183: the section on statistical analyses covers lots of tests in a single paragraph. These would be better suited in the same sections as the methods you are describing.

Response (Gomes et al.): Thanks for the suggestion. These explanations have been put in this section to help the reader understand it better.

Line 190: add ‘value’ after ‘annual’

Response (Gomes et al.): Many thanks. “The Pearson test was used to study the correlation between the annual value mean length of E. fimbriata and S. maderensis with the mean annual of each environmental parameter, SST, SSS, and CUI [57].”

Line 192: this is different to the symbol used in the equation on line 173. You have used a lower case Phi her

Response (Gomes et al.): Thanks, we have made corrections

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

The main addressed question by the research is the growth patterns of small pelagic fish in West Africa, but it really addressed only two species in one zone (the Gambian).

This work tries to investigate if some mechanisms cope with environmental variability, such as opportunistic breeding tactics, improving growth performance or increasing egg production evolved bay small pelagic species.

In this work, authors had investigated the size-dependent patterns of the two growth mechanisms (i.e. growth rate) of two populations of small pelagic from West Africa (Ethmalosa fimbriata and Sardinella maderensis) in upwelling environments (sea surface temperature (SST), sea surface salinity (SSS), and coastal upwelling index (CUI)). 

The datasets used in this study are obtained from: Sea Around Us 98 (https://www.seaaroundus.org/. These data represent reconstructed catch data, in addition the landing data from artisanal fisheries used outside of being reconstructed, do not give a good appreciation of the growth of the species caught, because fishermen generally target large sizes.

To better appreciate growth, it is wise to use scientific sampling data (scientific prospecting campaigns) that do not target particular sizes as in the case of commercial fisheries which target large individuals, which biases the sampling. 

Drawing conclusions solely on the analysis of reconstructed landing data for two species in an area that is not the most representative for small pelagic can be improved. This improvement can be done by updating the data series that are a little old (2018), especially in a context of increasingly rapid climate change, by integrating data from campaigns scientists and analyzing the situation in other areas of the sub-region where small pelagic are more 

Author Response

The main addressed question by the research is the growth patterns of small pelagic fish in West Africa, but it really addressed only two species in one zone (the Gambian).

This work tries to investigate if some mechanisms cope with environmental variability, such as opportunistic breeding tactics, improving growth performance or increasing egg production evolved bay small pelagic species.

In this work, authors had investigated the size-dependent patterns of the two growth mechanisms (i.e. growth rate) of two populations of small pelagic from West Africa (Ethmalosa fimbriata and Sardinella maderensis) in upwelling environments (sea surface temperature (SST), sea surface salinity (SSS), and coastal upwelling index (CUI)). 

The datasets used in this study are obtained from: Sea Around Us 98 (https://www.seaaroundus.org/. These data represent reconstructed catch data, in addition the landing data from artisanal fisheries used outside of being reconstructed, do not give a good appreciation of the growth of the species caught, because fishermen generally target large sizes.

To better appreciate growth, it is wise to use scientific sampling data (scientific prospecting campaigns) that do not target particular sizes as in the case of commercial fisheries which target large individuals, which biases the sampling. 

Drawing conclusions solely on the analysis of reconstructed landing data for two species in an area that is not the most representative for small pelagic can be improved. This improvement can be done by updating the data series that are a little old (2018), especially in a context of increasingly rapid climate change, by integrating data from campaigns scientists and analyzing the situation in other areas of the sub-region where small pelagic are more 

Responses Gomez et al.: Thank you for your comments which have greatly contributed to improving the document. Indeed, fisheries management is difficult, especially in developing countries where data available for stock identification and assessment are scarce or non-existent. However, given often inappropriate and ineffective fisheries management policies and increasing demand for fisheries resources, they have been facing for several decades the effects of overfishing and the collapse of fisheries in terms of local consumption, food security and economic value. Therefore, management guidelines and controls need to be simple, but also robust to uncertainties, and proportionate to the information available. In this way, generic management procedures can be applied, which are not necessarily the best for a given fishery, but may be better than inaction. This study demonstrates the applicability and use of results from countries where data collection and availability is difficult or even scarce; size frequencies to data-poor artisanal fisheries. It is hoped that these results can help assess many stocks currently considered too data poor to assess, particularly in developing countries.

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors Dear authors, Thank you for considering my suggestions. I wish you all the best. Best regards,
Reviewer