Research Gap Analysis of Remote Sensing Application in Fisheries: Prospects for Achieving the Sustainable Development Goals

Round 1

Reviewer 1 Report

Remote Sensing has been essential and become quite widely standard for fisheries research. As authors mentioned, “Sustainable development requires effective monitoring and management of marine resources”. Particularly, the former, “the role of RS in monitoring” is the most important at the first stage to achieve sustainable fisheries.

 

Before that, it is essential to understand current status of RS application in fisheries in the world. Therefore, I admit authors’ efforts, value and direction of the present study.

 

However, some points are very concerning; method of data collection and bias included in authors’ analyses, classification of research purpose of selected articles, and contents in the Section 2 & 5.

 

Major comments

 

(1) The meaning of “fisheries” such as in the title is ambiguous; authors frequently mention “RS application in fisheries”. Which does the “fisheries” used in this article mean actual fisheries or fisheries study/research/science/oceanography? The former is limited to practical or operational usage of RS data, the information of which are directly given to fishermen, fishing fleets, or fishing company in real-time. Meanwhile, the latter corresponds to academic/experimental/retrospective usage of RS data. Please strictly discriminate the meaning of “fisheries” throughout this article.

 

(2) The first comment rose, partly because the retrieved 236 articles are not listed in this article. If such a list is given as supplementary material, reproducibility of a series of data analyses in this article will be ensured.

 

(3) The biggest problem is as follows. When the aforementioned “fisheries” means fisheries research/science/oceanography (see question (1)), I’m very concerned about a large underestimation that was caused by authors’ methodology of data collection. Authors used only the two keywords, “Remote Sensing (RS)” and “fisheries” in searching WOS database. The number of 236 articles appears to be too small, compared with published fisheries scientific papers.

 

In my limited experience, when specialists of RS related satellite-derived environmental conditions to fisheries (e.g., fishing ground), they tended to use RS as a keyword of their study. However, when fisheries researchers/scientists/oceanographers used RS data, they did not explicitly use “RS” as a keyword. This is because fisheries researchers have regarded RS data, including “SST”, “Chl-a”, and “altimetry” data, as standard/basic products. In my limited knowledge, they describe product names (e.g., GHRSST, NOAA AVHRR, AVISO, …) or just write other keywords (e.g., satellite, altimetry, image, …) in their articles. Therefore, the two keywords must be insufficient in collecting information. Authors need to modify the data collection method. However, if authors show the validity of the current method, please meticulously discuss representativeness/bias of analyzed results.

 

In addition, there are many secondary products from RS data. For example, weather forecast systems (e.g., ERA, JRA, NCEP/NCAR, …) in the world at least utilize SST and sea ice concentration data at the sea surface mainly by RS. Wind data from such systems are frequently used for fisheries scientific study. This can be regarded as indirect usage of RS data to the fisheries scientific study. Moreover, recent progresses of fisheries scientific study have been brought by operational ocean forecast system mainly resolving mesoscale variability, into which oceanographic and RS data are assimilated to accurately make nowcast and forecast of ocean states. Even when the keyword of “RS” is not explicitly included in articles, RS data are used seamlessly to fisheries scientific study

 

(4) The third comment rose, for example, because “Peru” is not included in authors’ results. Peru faces the eastern boundary current region (i.e., Humboldt Current region) in the South Pacific Ocean, where there is a large amount of landing of anchoveta. IMARPE is a national institute for ocean research in Peru, where many scientists examined the oceanographic and fisheries conditions along the Peruvian coast with collaboration with scientists from IRD (France). However, authors’ results do not reflect these facts.

 

(5) Regarding the third comment, I think that important domestic studies are published with non-English language. For example, important reports from IMARPE are published in Spanish. Also, stock assessment reports from Japanese government are published in Japanese. Hence, domestic studies can have a large international bias, if only English papers/reports are picked up.

 

(6) I think contents in the Section 2 are instructive, but too long description seems to disturb the main focus of this study.

 

If this section is needed, authors had better to mention only essence about (i) what kinds of RS are available, (ii) gaps between developed and developing countries, (iii) necessity to fill the gaps to achieve sustainable development of fisheries, and (iv) the role of RS.

 

(7) The Section 5, “Discussion” must be greatly revised. Now, authors focus on several current gaps between developed and developing countries and discuss the international corporation/collaboration. I agree with the authors’ direction. However, this is not discussion but just like a review.

 

Rather, authors need to discuss interpretation of obtained results. For example, illegal fishing is discussed. However, this is not based on the authors’ results. If the retrieved articles are mostly related to illegal fisheries, this discussion is preferable. Please deeply reconsider what authors should discuss in the Section 5.

 

(8) I think RS data are not necessarily essential data in fisheries scientific studies. For instance, around Japan, stock assessment of fisheries resources is evaluated mostly without RS data. Instead, they used not only net sampling data and in situ hydrographic data by research vessels but also catch data by fishing fleets. Nevertheless, this fact doesn’t mean that fisheries scientific studies without RS data cannot contribute to sustainable development of fisheries. Hence, RS data are not necessarily essential but supportive for fisheries scientific studies connected to the sustainable development. Please discuss the above point in terms of bias of authors’ analysis.

 

Minor comments

(9) Line 94, “RS Model”: RS model is correct.

(10) Line 125, sea surface height, sea level anomaly: “sea surface height” should be deleted, because altimeters have not precisely measured absolute dynamic topography (i.e., sea surface height).

(11) Line 125, polypropylene: What kinds of RS can detect polypropylene? I  have never heard about such sensors and satellites, except for balloon camera.

(12) Line 195 front line & Line 442 frontline victim: The frontline of climate change impact is not restricted to “tropics”. For example, polar areas are suffering from drastic decline of sea ice or permafrost melting.

(13) Line 222-228: Please follow journal rule with respect to equation format.

(14) Lower panel of Figure 3 is not necessary, because most of the information is included in the upper panel of Figure 3.

(15) Figure 5: Figure 5 shows only the range of 28 to 47. However, I wonder spatial differences within the areas less than 28. This comment rose, because authors afterward focus merely on tropical countries, rather than polar areas.

 

These are all of my comments.

Author Response

 

 

Author Response File: Author Response.docx

Reviewer 2 Report

This study applies the WoS database and geographic information systems to analyse the gaps in fisheries science in various countries over the past ten years. The results reveal that most studies have been conducted in the offshore marine areas of the north-eastern United States of America. In addition, all research hotspots were situated in the Northern Hemisphere, indicating a lack of relevant studies from the Southern Hemisphere. For the three major oceans indicated that in terms of remote sensing applications in fisheries, the Atlantic Ocean was the most-studied, followed by the Indian Ocean, while the Pacific Ocean was less studied than the other two regions. On other hand, all research hotspots were situated in the northern hemisphere, which indicates a lack of relevant studies from the southern hemisphere. The authors conclude that the collaboration and partnership can constitute an efficient approach for transferring skills and technology across countries, and research networks can be expanded to mitigate the research gaps and improve the sustainability of marine fisheries resources in order to achieve the SDGs. The study is very interesting and could be useful for developing countries if effectively research networks can be implemented.

 

Some issues need further clarification:

• When you try to measure the international cooperation (using the HHI) of the partners of the primary research sponsors, how did you obtain that information for estimating the HHI? From the papers, may be collaboration among authors from different institutions/countries signing the same paper and funds for their research?
• Although you aren’t analysing correlations, probably the progress of RS applications in fisheries is related to the policymakers’ and technicians’ concerns about the marine habitat situation and decrease in spawning biomass of key species, in particular in the North Hemisphere. You may include some references about the scientific recommendations or comment about this in Discussion section.

 

 

Some minor issues:

- P.4, lines 158-160, please include the discards as one of the challenges for fisheries.

- P.4, lines 160-163, in the same way, please include the risk of escaping of farmed species on marine habitats for the aquaculture case.

Author Response

Please see the attachment.

 

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

I praise great efforts of authors during very short time. I agree with all the points to which authors replied.