Gathering Fishery-Dependent Data in the Digital Age A guide for managers & scientists March 2019
Review your management
1 objectives and data needs 2 Make a data collection list
Do an initial prioritization – Must Have, Nice to Have, Dream Big Get feedback Get specific about what you need and when Separate by fishery dependent v. independent What could improve accuracy?
3
Examine your fishery dependent data list
What could improve efficiency? How will you handle location?
4 Map tools to data needs 5 Write up & evaluate options
Survey fishers
Why this guide
The Only Rule
Every day, more people are bringing digital data collection tools onboard fishing boats, from personal mobile phones to systems of integrated cameras and gear sensors. For managers, scientists, fishers, and anyone involved in ocean conservation, this presents opportunities to bring faster, more accurate data into management. This guide is to help you think through which tools might make sense for your fishery, and what questions to ask before adopting them.
Regardless of what you decide to recommend for the fisheries you manage, keep in mind that the technology landscape is always shifting. This guide walks through five steps which all boil down to one core guideline:
Before you start We recommend setting aside an hour for your first run through of this guide. Before you start, make sure you have the following resources available: ● Any existing monitoring or research plans ● Relevant laws and guidelines We also recommend identifying colleagues who can be thought partners as you work through the guide. Even if you prefer to start with a solo review, reviewing your thinking in teams can surface new considerations that benefit everyone’s review. There are also specific steps where we recommend getting outside feedback.
Objectives before tools Moving from paper to electronic reporting is an excellent time to revisit what data you need and why, which defines the objectives for your data collection tools. Technology can automate data collection, avoid errors from self-reported data, and improve the resolution of time and location data. Technology can also collect large amounts of data that don’t feed into stock assessments and are prohibitively expensive to analyze and store. Clearly defined data objectives, including data formats and collection frequency, will help you choose the most appropriate digital tool without being distracted by the latest gadget. Paper may still be the best choice based on the needs and characteristics of the fishery.
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1.
Review your management objectives and data needs
An objective here is something that’s in between a high level statutory requirement (e.g. minimize and reduce bycatch”) and a detailed experimental protocol (e.g. “oocycte samples collected from 25% of landed females”). Objectives should include a what and a why - do x in order to achieve y - but not focus on the how. We’ll get to how in steps 3 & 4. Example Objective: Capture size and sex of a subsample of commercial and recreationally caught fish every month of the fishing season, in order to understand population dynamics and set appropriate size limits If you don’t have a fishery management plan, or a set of monitoring objectives, we encourage you to look at FishPath or the DataLimited Fisheries Toolkit. Both of these frameworks can help you think through management options and the data needed to support each measure; in the case of the DataLimited Fisheries Toolkit, you can see what additional data elements would allow to you compare additional management strategies. Another good resource is the article “Guiding Principles for Development of 1 Effective Commercial Fishery Monitoring Programs.”
We strongly encourage you to invest time in this step before making any investments in digital monitoring, even if your initial reason for considering new technology is outside of the strict scope of managing the fishery, such as responding to a government mandate, receiving donated equipment, or switching from paper to electronic logbooks when your current supply runs out. Having clear objectives can help you pick tools that could serve multiple purposes. Even if it’s digital, data isn’t free. It costs time to collect and analyze, server space to store, and development capacity to build software and setup data structures. If you can’t match data to a monitoring objective – why are you collecting it?
Zollett, E.A., R.J. Trumble, J.H. Swasey and S.B. Stebbins. 2015. Guiding Principles for Development of Effective Commercial Fishery Monitoring Programs. Abstract. Fisheries. Vol. 40 (1): 20-25. (contact erika.zollett@mragamericas.com for reprints) 1
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Do an initial prioritization – Must Have, Nice to Have, Dream Big Before you get into the details of data collection, do a quick sort into one of three groups: Must Have, Nice to Have, and Dream Big. Must Have
Nice to Have
Dream Big
Clear, direct line to your management needs E.g. Number of participants, total catch, gear type, abundance indices, discard rate, protected species interactions
Improves confidence, reduces bias, allows better projections E.g. Size at age, growth parameters, discard mortality
Collection may be unlikely, but it helps to imagine ideal scenarios E.g. What would you do with a week of free ship time? What about $50,000? What didn't you put in the official monitoring plan that you really wish you had?
You should have something in each of the three categories. If all data ends up in the “Must Have” column, think about what’s the bare minimum you need to manage and try putting everything else into “Nice to Have.” If you don't have anything in “Dream Big,” take a look at a non-fisheries technology website and think about repurposing one of those innovations for fish.
Get feedback This is an important place to get outside feedback. Sharing your objectives and ideas at this higher level (before it looks like a detailed data plan) gives others a chance to offer high level input and novel data collection ideas without getting bogged down in details. Seek input from other colleagues, academic researchers, fishers, and industry associations. Refine what you have in each of your prioritized groups and take that to Step 2.
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2. Make a data collection list Start with what’s in your Must Have group, keeping an eye on the Nice to Have group in case there’s something you discover needs to be pulled over to Must Have as you dive into the details. Get into specifics Pull out fishery-dependent data ● At what increment do you need the data – per trip, per set, We interpret this to mean the data collection is tied to fishing per hook, once a season activity: it can't be collected if there’s no fishing activity, but it can ● At what frequency do you need the data – in real time, and should include data on activities with zero catch, because every trip, once a month fishing activity occurred even if it wasn’t successful. It may not be ● Where do you need data collected from – every port, only collected directly from fishers, as with video monitoring systems certain regions operated by a third-party provider. We recognize there’s a grey ● Are there seasonal issues – e.g. you need spawners, you area including what is most effectively collected from fishers or need population data year round but the fishery only during fishing activity, and what data can be collected by fishers. operates for six months For example, you could gather genetic data with independent research trips or fishers could be trained to collect samples. You These specifics will help you pick tools: monthly sampling could may want to keep more data fields in the fishery-dependent be done by a dock sampler while daily data needs could use category for now, separating them out as you go through the next sensors and easy-to-submit forms. steps of the guide.
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3. Examine the Must Have Fishery-Dependent Data list Digital data collection tools can provide verification, such as GPS coordinates and images, that may increase trust and quality above self-reported records. Looking at your list of fishery-dependent data items, could a change in technology or data management get you: Better Accuracy Adding RFID tags to gear to track deployment and retrieval to get more accurate CPUE data, or video cameras to record catch and discards. Better Efficiency Electronic fish tickets (a web app, by text) for faster access to landings data. If your management objectives require you to get data that’s currently mailed in on a monthly paper log, this is a good field to prioritize for a digital logbook or other reporting device. You may want to consider the efficiency of training fishers to take biological samples as opposed to using dock samplers or on-board observers. There’s also the efficient use of time, both yours and the fleet’s: a camera system could capture data without interrupting fishing, if you’re prepared to set up a video review system. Precise Locations Since most electronic devices automatically collect GPS coordinates, this is one of the simplest fields to autofill into a digital logbook and it’s built into many electronic monitoring and tracking systems. With GPS or lat/long from a boat’s plotter, you can link fisheries data with bathymetry and habitat data; if you also have a timestamp, you can combine weather, temperature, and other data fields. The finer resolution of automatically collected GPS data may be a big improvement to your analyses. It could also generate new privacy concerns for fishers, especially if you’re considering systems that report in real time and the possibility that data may be shared with enforcement. If GPS is important for your objectives, set aside time to think through how the data will be stored and shared so you can ensure you’re meeting legal requirements and communicating what you’ll do with the data to fishers.
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4. Map Tools to Data Needs The table below describes some common digital tools here and maps their suitability against monitoring data fields. A description of each tool follows the table, along with a discussion of algorithmic tools such as image recognition.
Electronic Monitoring Systems
Digital logbooks
Vessel Tracking Systems
Independent cameras
RFID tags
Socioeconomic/ operational info
Yes
No
No
No
No
Gear type/ amount used
Yes
Yes
No
Yes
Yes
Effort
Yes
Yes
Yes
Yes
No
Location
Yes, can be automated
Yes
Yes
Yes, of gear
No
Catch per vessel
Yes
Yes
No
No
No
CPUE
Yes
Yes
Effort only
Effort only
No
Species composition of catch
Yes
Yes
No
No
Yes, likely better for landed catch
Bycatch/discards
Yes
Yes
No
No
Yes, but not comprehensive
Size composition
Yes
Yes
No
No
Yes
Sex composition
Yes
No, unless there are No distinct physical features
No
Yes
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Digital logbooks, or e-logbooks
Software that runs on a government-provided device, device leased form a vendor, or fishers’ own phone, tablet, or console computer. Key Features: ● Open-ended forms that can capture any-self-reported data field ● Can be designed to use GPS from device ● Forced validation and dropdown menus can reduce errors ● Uploads data when device has cellular or wireless service
Electronic monitoring (EM) systems with cameras and hydraulic sensors These include cameras permanently mounted on the boat to record catch and discards, with hydraulic sensors to track gear deployment and retrieval. Data is stored locally on portable hard drives and mailed in for review, or uploaded via satellite or wireless connection. EM is currently only available through a limited number of service providers, who install hardware and charge ongoing fees both to boats and to agencies for data review. Key Features: ● Always on, cannot be adjusted by fishers ● Require on-board power and professional installation
Vessel tracking systems
RFID tags
These are different from traditional Vessel Monitoring Systems in that they capture much more data on boat position and speed, allowing calculations of activity and effort. While VMS may report a boat’s location every hour or more, vessel tracking systems take multiple readings per minute. Key Features: ● Small, can be installed by fishers ● Often solar powered
Radio frequency ID tags are passive transponders that can be a built-in component of both EM and vessel tracking systems. These are not satellite transmitting tags. Tags are attached to gear and read by an on-board sensor that detects when gear is deployed and retrieved, automatically capturing effort. They’re not necessarily part of a basic technology package, so if you see a need for RFID tags make sure to ask about it when talking with potential providers. Key Features: ● Small, cheap, durable, many different designs ● Need an onboard scanner and process to integrate with other data
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Independent cameras This includes cameras that can be attached to nets or sorting areas, separate from an EM system. Fishers could also use smartphones or digital cameras to snap images of individual fish next to a measuring board, or take close-ups of reproductive characteristics or disease. Because the cameras can be turned off and on at the fisher’s discretion, they may not meet compliance requirements but they could be valuable for research. Without a service provider to manage data review and storage, you’ll need to create your own process. Key Features: ● Can use fishers’ own devices or affordable off-the-shelf hardware ● Flexible, can be tailored to short-term research needs
Image recognition and Assisted data review Once you have digital data, you can write a wide variety of algorithms to help you review and analyze that data. You can develop (or hire someone to develop) algorithms that count, identify species, and measure the length of fish in an image. You can also develop data quality protocols that flag unusual data for further review, helping you catch errors and broken hardware. These types of automated tools require you to think about how you’re configuring the systems up front, because they need to be fine-tuned for each data stream. For example, if you’re working with a fishery where a large volume of catch comes on board all at once, you’ll need a setup where fishers sort the fish individually in view of a camera if you want to automate species identification. An EM service provider should help you think through how to optimize their system for eventual automated review, even if you start with human review.
Survey fishers Before exploring what tools you might want to add to your current data collection toolbox, find out what technology your fishery’s participants already carry on their boat. This includes: cell phones with texting capacity, smartphones, tablet computers, laptops, console computers, sonar, plotters, satellite phones, AIS, other satellite connections (like an Inmarsat-C account), NOAA-approved VMS, video monitoring systems, and vessel tracking systems. If possible, visit one or two boats and note or photograph how they’re configured: what’s displayed in the wheelhouse, where catch is sorted and discarded. You could also look at vessel registration data and past logbook reports to get a rough idea of the range of vessel size and capacity in the fleet.
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You may also want to create what developers call ‘personas,’ or slightly generalized descriptions of the type of fishers and fishing boats who will be capturing your fishery-dependent data. Creating these personas can help clarify the mix of technology, both high and low tech, that will get you to your objectives. For example, monitoring cameras could be the easiest solution for the small boats because they require no effort from fishers to record catch and bycatch, but you may still need a written record if you want to get bait type or other data cameras won’t see. On a boat with only one or two fishers, you might want to choose water-resistant paper records, perhaps designed so fishers can photograph them with a smartphone.
Persona: Fisher A Small, single operator (20 boats) No AIS, minimal electronics Hard to enter data while hauling gear & sorting catch Not enough room for an observer Fishes close to shore, state fisheries only Persona: Fisher B Larger, multi-fishery boat (10 boats) Multi-day trips, more electronics already on-board Could accommodate an observer May switch target species on a single trip Fishes federal and state waters, federal and state fisheries
5. Write up & evaluate your options Go back to your objectives in Step 1. Start pulling together packages of monitoring options that meet your objectives, mixing and matching the digital tools likely to improve accuracy and efficiency with the analog options you’ll still need for data like bait and otolith sampling. Discuss your monitoring packages with your team of reviewers and collaborators and make adjustments. When you think about costs, consider both your time and the fishers’ time, and reflect on the amount of time you spend entering and checking data now. You may need to invest more time upfront to set up a new digital data collection program, but in the long run, it should be meeting your management objectives with less effort and better data quality.
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