Back in February, I blogged about a paper on the tracking the global footprint of fisheries, that was quite illustrative of that fact… but I also blogged later on in regards the controversies this paper was causing.
Obviously much smarter than me people had also issues with the paper and the claim that "vessels are now fishing in 55% of the world’s oceans, which is an area four times larger than occupied by onshore agriculture" and put their brains into it. They just publish a comment on that original paper.
Fig. 1 Effect of grid resolution on the perception of fishing footprint. The areas in dark blue show the trawling footprints estimated for 2016 with (A and C) an equal-area grid with 0.5° resolution at the equator; (B and D) an equal-area grid with 0.01° resolution at the equator.
Their reanalyses of their global (all vessels) and regional (trawling) data at higher resolution reduced footprint estimates by factors of >10 and >5, respectively. The fact that they also illustrated their work with the South Atlantic (where I started fishing) was an extra bonus.
Based on this analysis, less than 4% of the global ocean is fished, not 55% as reported in the original paper.
Interestingly, the revision of the data is based on the same questioning I had on a paper on the Rise of the DWFN, where the “definition” of the scale of analysis could provide very different data.
Personally, I don't like to imagine this "comments on papers" as discrediting in between scientist, but as a way to get to more accurate results, in a field that is just being developed with every IAS data-based papers, perhaps a tacit agreement of what resolution to use is the way to go. This is science at work! May not be good for egos, but lead to a better understanding and more transparency... and that can only be good!
Anyway…. below I quote parts of the response… but read the original comment.
Kroodsma et al. (1) used automatic identification system (AIS) data to track vessels they classified as “fishing” and estimated that fishing activities occurred in 55% of the world’s oceans in 2016. We show how strongly their results depend on the spatial scale of analysis. Their method gridded the ocean into large cells of 0.5° at the equator (~3100 km2) and counted every cell with any assumed fishing event of any duration in 2016 as fished, thus contributing its total area to fishing footprint.
We accessed the 0.01° grid fishing data made available by Global Fishing Watch (2) and reanalyzed these data at resolutions of ~3100, ~123, and ~1.23 km2 (corresponding to 0.5°, 0.1°, and 0.01° at the equator), giving footprint estimates of 49%, 27%, and 4% of ocean area, respectively. Thus, higher-resolution analyses reduced their global fishing footprint estimates by a factor of >10. Our estimate of footprint at 0.5° (49%) differs from that reported by Kroodsma et al. (55%) because they improved their algorithm to identify fishing by squid jiggers after publication and updated data in the current release. Also, the method we used to reallocate fishing activity to grids differed slightly from that in Kroodsma et al., leading to small differences in absolute footprint estimates, but these do not affect the relative relationships between footprints across spatial scales.
All human activities have diffuse impacts that extend beyond the area of activity. However, for fishing activities, using a spatial grid of an arbitrary low resolution does not provide an appropriate or consistent quantitative assessment of diffuse impact. For example, some diffuse impacts would be assessed more effectively using catch and bycatch data and population or community analyses that account for the diverse movements and life histories of affected populations and species, as well as the different rates of mortality that result from their varied interactions with fishing activities (4–6).
We also quantified the effects of grid resolution on trawl fishing footprints with the Global Fishing Watch data (2). We focused on trawling because footprint is a consistent and well-defined concept for trawling vessels, which tow a net or nets directly behind the vessel(s) and for which gear dimensions are known or can be estimated more reliably. Further, high-resolution footprints for bottom trawling (although Kroodsma et al. did not distinguish bottom trawls from trawls that do not contact the seabed) have long been used as metrics to assess fishing impacts on seabed habitats [e.g., (7–9)].
To illustrate the effects of grid resolution on trawling footprints, we considered regions of the north Pacific Ocean and off southern South America. For each region, trawling footprint (as proportion of the ocean area) was calculated using equal-area grids of 0.5° and 0.01° at the equator (Fig. 1). At the higher resolution of analysis, the estimated footprints in these regions fell by factors of 5.3 (48% to 9%) and 5.9 (29.5% to 5%), respectively. Further, if we take as an example a region of the north Pacific Ocean where trawling was banned in 2016 (10) (Fig. 1, A and B), then 100% of this area (59,000 km2 of ocean) was incorrectly classified as trawled at 0.5° resolution. For such reasons, many published analyses of trawling footprints are conducted at higher resolution (11–13).
A coarse gridding of the positions of fishing vessels (globally or regionally) that ignores differences in catching power among vessels and gear, or ignores the scale of their direct and diffuse impacts, leads to footprint estimates that are primarily driven by the spatial resolution of analysis. Such analyses are unlikely to be a good proxy for the footprint of fishing or the status of species or ecosystems affected by fishing. The high temporal resolution of AIS data can provide valuable insight into the behavior of individual vessels and allowed Kroodsma et al. to classify different types and patterns of fishing activity. These analyses alone are an interesting achievement, but the footprint estimates and comparisons with agriculture highlighted in their report are misleading.