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The Proof of Concept of Aerial Catch Estimation

December 12, 2013

Weir

A Google Earth image of a fishing weir along the Persian Gulf coast.

We are slowly beginning to see attempts at testing new technologies to assess illegal fishing.  Point in fact is the “Short Communication” article published by the ICES Journal of Marine Science just a couple weeks ago: “Managing Fisheries from Space: Google Earth improves estimates of distant fish catches.

(For a shorter read, check out this World Fishing article. And for a primer on remote sensing for ocean management, read here.)

This article was both very good and, well, frustratingly mum on how wildly inaccurate its predictions could well be.  Sure, it’s not an official article, but rather a short communication…but I would have thought there would be some tighter screening.

So let’s start with what was good: proof of concept.

All in all, the article shows that aerial photos can be used to estimate the catches of coastal fisheries.  How so?  The assessment methodology relies on Google Earth, a visual count of fishing traps, and some best educated guesswork to determine how many fish would be caught by a special type of fish trap – a weir – in the Persian Gulf each year. Call it a sort of fisheries spectrometer in beta version.  Here I quote:

We surveyed the coast of all Gulf countries (inward of the Strait of Hormuz) three times and marked each weir with the Google marker tool…and solved for the total (seen and unseen) weirs…We then raised the total number of weirs corrected for poor resolution by the percentages of missing imagery.

To estimate total annual catch, we combined the number of estimated weirs with daily catch rates and fishing season lengths (and the confidence intervals associated with all these parameters) in a Monte Carlo procedure (Uhler, 1980) for each country and for the entire region.

Pretty cool, right?  In my view, this tech and our ability to remotely estimate actual fishing effort and catches will only expand as Google Earth gets more imagery from aircraft and more powerful satellites at its suppliers’ disposal.  Of course, that assumes we also continue to improve associated methods to estimate catch rates and seasons in data poor fisheries.  And this gets me to my second point…

What this article gets wrong is how little it discusses its catch estimation methods, and how it established confidence intervals around the estimates that resulted.

For example, consider how the catch rates were estimated:

The mean catch rates used to calculate total catch were 62.2 kg d-1 (n=3; s.d.=32.4 kg) for Kuwait (A. Al-Baz, Kuwait Institute for Scientific  Research,  pers.  comm.) and 42.6 kg kg d-1 for  Bahrain (A. H. AlRadhi, Directorate of Fisheries Resources, pers. comm.).

And now consider how the seasons, species composition ratios, and regional rates were estimated:

Estimates for fishing season lengths and species composition ratios were also obtained from the same sources, as well as for the UAE (S.  A.  Hartmann, Environmental  Agency  –  Abu  Dhabi,  pers. comm.), while regional averages were applied for countries without these data (Iran, Saudi Arabia and Qatar).

Frankly, I don’t even know what a lot of this means.  Catch estimates from a personal communication, and one estimate was based on the sampling of just three fishing weirs?  And these two personal communications formed the basis for estimates for the other three countries that were assessed?  I can’t believe at this moment that these numbers approached anything more than a wild guess. I mean…this is the Persian Gulf we’re talking about.

Ultimately, I wonder if maybe this article wasn’t meant to elicit some ideas or collaboration to better refine the concept.  Or was this the UBC Fisheries Centre upholding its reputation of occasionally playing too fast with the numbers?   (Or in a more real politik view, was someone else about to beat the author to the proof-of-concept finish line?)

I’m going to assume the former and humbly offer my own thoughts here.

First, I think we need to be far more open about the data limitations of each analysis. Until we have developed complementary catch, composition, and season length assessment methodologies for data poor fisheries, we just can’t be throwing around so many numbers as come later in the article.  I mean, really, was the following not just a slight overstep?

Species composition varies between Gulf countries. Kuwait’s catch is  dominated  by  mackerel  (Scombridae;  30%),  bream (Sparidae; 19%) and morraja (Gerreidae; 15%), while Bahrain’s catch is dominated by rabbitfish  (Siganidae;  26%), swimming crab  (Portunidae;  26%), and  sardines  (Clupeidae; 15%).  Over 96% of the UAE’s catch is reported as snapper (Lutjanidae). The regional average species  composition is dominated by Siganidae (22%), Portunidae (22%) and Clupeidae (13%).

Second, why not develop a methodology where you rapidly assess these parameters. For example, field surveys of the fishermen of the fishermen could be conducted. UAVs could be used to evaluate if fishing effort is uniformly distributed across a fishing area (as the article assumed), or if it follows some predictable pattern to take advantage of variable fish distributions. You could also work with a national fisheries agency to get authorization from the fisheries ministry to deploy some experimental traps to estimate these variables. Anyway, food for thought.

So in closing, I’m quite excited by this demo’ing of the technology. I believe it shows some tremendous potential for helping us one day truly manage the majority of the world’s fisheries for sustainability. I hope we can now find the tools to help it fulfil its promise. On the opportunity for this more expansive management, the authors and I absolutely agree:

[O]ur results speak to the potential for satellite imagery and remote sensing to expose illegal fishing practices. In the same way that industrial fisheries rely on technology to target catches (i.e. Fishfinders, GPS Chartplotters etc.), technological advances in satellite imagery can be used to monitor fisheries remotely, particularly in areas that were once considered too remote or expensive to enforce. In the case of Qatar, our methods revealed 17 operating weirs (14 visible directly and 3 added to compensate for poor resolution and imagery availability), despite their ban in 1994 (M.S. Al-Muhindi, Ministry of Fisheries, pers. comm.). Beyond other large semi-permanent structures, such as fish ponds in Hawaii and Japan, vywers in South Africa, or sakkar in the UAE, satellite imagery can be used to expose other illegal marine practices, such as verifying the magnitude of oil spills (Amos, 2013), assessing the use of illegal fishing gears, and monitoring activities in Marine Protected Areas (MPAs), among others. This is particularly useful for improving data collection in countries with known data inaccuracies, or in developing countries where resources allocated toward conservation and/or management are scarce.

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