Big Data & Its Impact on Global Fishing
Grant R. McDermott | University of Oregon
@grant_mcdermott
About me
About me (cont.)
Environmental economist interested in energy, climate, water, and fisheries (today's topic of interest).
Assistant Prof. at UO's Dept. of Economics (2017--).
- Before that: Santa Barbara, Norway, Portgual, UK, South Africa...
Accidental academic.
Goals for this evening
Tell you about my fisheries-based research.
Tell you about some of the big data products that I use (and are available to the public).
Answer any question that you might have.
Goals for this evening
Tell you about my fisheries-based research.
Tell you about some of the big data products that I use (and are available to the public).
Answer any question that you might have.
Keep you entertained!
Goals for this evening
Tell you about my fisheries-based research.
Tell you about some of the big data products that I use (and are available to the public).
Answer any question that you might have.
Keep you entertained!
Sound good? Okay, let's look at some actual research...
"Protecting marine mammals, turtles and birds by rebuilding global fisheries"
Burgess, McDermott et al. (2018, Science)
What is bycatch?
What is bycatch?
"Bycatch" = A species accidentally caught in the pursuit of another ("target") species.
Although...
Two problems, one solution?
Many marine species are threatened as fisheries bycatch.
Many parts of the ocean are being fished unsustainably.
Two problems, one solution?
Many marine species are threatened as fisheries bycatch.
Many parts of the ocean are being fished unsustainably.
Research question: Can we solve Problem 1 by addressing Problem 2?
Two problems, one solution?
Many marine species are threatened as fisheries bycatch.
Many parts of the ocean are being fished unsustainably.
Research question: Can we solve Problem 1 by addressing Problem 2?
Answer: Yes! Reduced fishing pressure means better long-term profits and less bycatch.
Two problems, one solution?
Many marine species are threatened as fisheries bycatch.
Many parts of the ocean are being fished unsustainably.
Research question: Can we solve Problem 1 by addressing Problem 2?
Answer: Yes! Reduced fishing pressure means better long-term profits and less bycatch.
We consistently find that \(\geq\) 50% of threatened bycatch populations recover as a collateral benefit of improved fisheries management.
Big picture
Big picture
Big picture
Big picture
Big picture
How do we get our results?
How do we get our results?
Okay, seriously.
All of our bycatch species combined
Summary
Reforming global fisheries (to maximise profit!) goes a long way towards enabling recovery of threatened bycatch species.
- Results are surprisingly robust despite the many uncertainties involved.
At its heart, a classic environmental economics question about externalities.
Part of a growing literature aimed at understanding global fisheries and quantifying the benefits of reform.
"The blue paradox: Preemptive overfishing in marine reserves"
McDermott, Meng, et al. (2018, PNAS)
Motivation
Can you make a problem worse by promising to solve it?
Many examples on land: Gun control, Endangered Species Act, “green paradox”, etc.
But what about the ocean?
Motivation
Can you make a problem worse by promising to solve it?
Many examples on land: Gun control, Endangered Species Act, “green paradox”, etc.
But what about the ocean?
Research questions:
- Do fishers preemptively increase effort in anticipation of a marine reserve (i.e. a "blue paradox")?
- If yes, what are the consequences for science and policy?
Marine reserves are a bit like celebrity health advice
Growing in popularity...
- Celebrity health advice:
- Marine reserves:
Marine reserves are a bit like celebrity health advice
...but not clear that they actually work.
- Celebrity health advice:
- Marine reserves:
To be fair
Marine reserves and protected areas actually have a strong scientific basis.
However, there is still a troubling prevalence of "paper parks".
Could the blue paradox provide another reason?
But where to get data?..
To be fair
Marine reserves and protected areas actually have a strong scientific basis.
However, there is still a troubling prevalence of "paper parks".
Could the blue paradox provide another reason?
But where to get data?..
- Enter Global Fishing Watch.
Global Fishing Watch
GFW is a joint initiative between Google, SkyTruth and Oceana.
Offers unprecented insight into global fishing activity.
- Includes locations that were previously inaccesible to outside observers.
GFW data is available to the public!
Where does GFW get its data?
Ships use AIS (Automatic Identification System) for maritime safety.
- Avoid collisions, etc.
- Raw data contains lots of useful information, but also plenty of mistakes that need to be fixed first.
Satellite and terrestrial systems can receive and record AIS messages too.
AIS is BIG data...
- 22 billion messages from 250k vessels over 2012-2016.
- 20 million messages being added per day (and growing).
- AIS is required on all vessels >300 tons on international voyages. Many countries require smaller vessels to use AIS within their EEZs as well.
- A moving vessel broadcasts a position message every 2 to 20 seconds
- An anchored vessel every 3 to 6 minutes.
- GFW average is 50 satellite positions per vessel per day.
Density of AIS
But how get from raw AIS data to fishing activity?
Short answer: Cloud computing and machine learning (Convolutional Neural Network).
- Training data: 240k hours' worth of AIS data from 624 vessels (569k AIS positions) that have been hand-labelled by fisheries experts and/or validated with logbook data.
- There are actually two CNNs:
- One to identify vessel characteristics, including length, engine power, and vessel type. (Training data: 73,994 vessels matched to official fleet registries, including about 13,500 fishing vessels.)
- A second to detect which AIS positions were indicative of fishing activity. (Training data: 240,000 hours’ worth of AIS data, from 624 vessels, with over 569,000 AIS positions labelled by fisheries experts.)
Convo who neural what net?
Don't be intimidated by the terminology
Don't be intimidated by the terminology
The CNN is just replicating what your brain does automatically: Identify and classify patterns. (But, is much easier to scale.)
GFW dataset
The cleaned GFW dataset contains 70k likely fishing vessels.
- AIS-equipped vessels account for 75% of offshore fisheries (>100 nm from land).
Individual vessel tracts.
- Where, when and for how long a vessel was fishing.
- What type of fishing were they doing.
Other covariates of interest: Flag, tonnage, length, speed, etc.
Small fraction of the world's ~2.5 million motorized fishing vessels... but it contains a majority of active vessels over 24 metres.
Back to the blue paradox...
Focus on the Phoenix Island Protected Area (PIPA) as a case study.
- A large and widely celebrated marine reserve in the central Pacific.
Part of the Pacific island nation of Kiribati's exclusive economic zone (EEZ).
- One of the world's largest and most celebrated marine reserves.
Identifying an appropriate counterfactual is key
- Compare fishing effort in PIPA ("treated") versus a neighbouring part of Kiribati EEZ ("control").
NB: Fishers have no incentive to lie about their position pre-enforcement.
Main result (1)
Main result (2)
Main result (3)
Conservation and science implications
BP has implications for both the conservation efficacy of marine reserves and the methods that scientists use to measure this efficacy.
Conservation efficacy
- Impoverished starting point for the affected reserves.
- Possible L-T declines (e.g. breach environmental tipping points).
Scientific measurement
- Simple comparison of fish abundance (e.g. before vs after) will be biased due to preemptive response.
- Maybe we're mismeasuring the true effectiveness of these reserves?
Summary
Anticipation of PIPA causes fishing effort to more than double (↑ 130%).
- Equivalent to 1.5 years of banned fishing.
Extrapolating globally: Temporary ↑ in over-extracted fisheries from 65% to 72%.
Reasons to view our empirical results as a lower bound.
- E.g. Doesn’t account for long-term effects (population thresholds and other tipping points).
BP offers a previously unexplored reason for prevalence of “paper parks”... And also has implications for ways that scientists measure their conservation efficacy.
Future research: Disentangling the exact mechanisms vis-a-vis property rights. Deeper dive into potential long-term ramifications.
Some ongoing and future projects
Several GFW projects
Deep dive into the blue paradox (role of property rights, etc.)
Link between slave labour and overfishing
Etc.
Aquaculture mapping (2)
Despite this incredible aggregate growth, many unknowns remain about aquaculture (mariculture)
We don't even have a good sense of the true spatial footprint; how and where it is growing fastest.
Nor, do we know much about how aquaculture and capture fisheries are interacting.
- Complements? Competitors? Conservation tool? Habitat threat?
Aquaculture mapping (2)
Despite this incredible aggregate growth, many unknowns remain about aquaculture (mariculture)
We don't even have a good sense of the true spatial footprint; how and where it is growing fastest.
Nor, do we know much about how aquaculture and capture fisheries are interacting.
- Complements? Competitors? Conservation tool? Habitat threat?
Idea: Use high-resolution satellite imagery and machine learning to map aquaculture at scale. (Live session.)
Aquaculture mapping (3)
Aquaculture mapping (4)
Thank you!
Questions?
grantmcd@uoregon
@grant_mcdermott
www.grantmcdermott.com
github.com/grantmcdermott