Northeast Federal Fishery Dependent Data Visioning Project Industry Workshop Final Workshop Report September 10, 2014 June 30th -­‐ July 1st, 2014 Waypoint Event Center New Bedford, Massachusetts Hosted in partnership by the Gulf of Maine Research Institute, UMass Dartmouth’s School for Marine Science and Technology, and NOAA’s National Marine Fisheries Service Interested parties can find additional details about the workshop on GMRI’s project webpage. To view presentations from the two days, click here or visit gmri.org/fishdependentdata. 1 Project Background: Fishery dependent data include information characterizing fishing operations (fishing location, gear type used, area fished, landings, bycatch, operational costs) that can come from a variety of sources, including from the fishermen themselves, dealers, onboard observers, and from automated technology such as vessel monitoring systems. Fishery dependent data are essential to the sound management and sustainability of fisheries, and are 100% dependent on industry participation. Such data are used to estimate fish populations, monitor fish catch and fishery interactions with protected species, evaluate compliance with existing regulations, and assess the impact of changes to proposed management measures. Evolving management needs and industry uses throughout New England and the Mid-­‐
Atlantic, including proliferation of quota-­‐based management regimes at the vessel/sector level, have taxed existing data collection methods and infrastructure, and the industry. This has resulted in a patchwork of systems that struggle to meet the current and expected needs of fisheries science and management. NOAA leadership in the Greater Atlantic Region has prioritized modernizing fishery dependent data systems as an opportunity to create efficiencies and improve catch accounting, stock assessments, and fine-­‐scale management approaches through timely and accurate data collection and processing. Initiated in 2013, the Northeast Federal Fishery Dependent Data Visioning Project (FDDVP) represents a formal effort by NOAA’s National Marine Fisheries Service (NMFS) Greater Atlantic Fisheries Office (GARFO) and the Northeast Fisheries Science Center (NEFSC) to modernize data systems throughout the Greater Atlantic Region in order to meet the needs of fisheries science and management now, and into the future. The project is holistically reviewing fishery dependent data collection methods and systems in all Greater Atlantic fisheries, with the ultimate goal of implementing a modernized data collection system and associated infrastructure that supports the varying needs and uses of all fisheries dependent data within the Greater Atlantic region. The expected benefits of NOAA’s data modernization effort include: • more accurate and timely data; • consistent data products for analysis and reports; • reduced reporting burden for industry; • more efficient utilization of NOAA staff resources; • increased communication and coordination of data by NOAA and its partners; and • quicker and easier access to data by all users. The goal of NMFS is to begin implementing a modern data system in the Greater Atlantic Region by 2017. The projected NMFS implementation plan timeline is as follows: • Develop data system requirements document (December 2014) 2 •
•
•
•
Create project plan and appropriate business rules to implement idealized fishery dependent data system (Spring/Summer/Fall 2015) Identify and prioritize system implementation modules (Spring/Summer 2016) Program and test updates to fishery dependent data system (Fall 2016/Spring 2017) Implement improved fishery dependent data system (Summer 2017) Through support from a federal grant, the Gulf of Maine Research Institute (GMRI) sub-­‐contracted with the UMass Dartmouth’s School for Marine Science and Technology (SMAST) and others knowledgeable about the fishing industry to conduct surveys and interviews with stakeholders from the commercial fishing industry, including harvesters, dealers, and industry-­‐representative organizations. These surveys/interviews focused on identifying current data needs/uses, evaluating the current data collection systems, and identifying characteristics of an ideal data system. Similarly, NMFS staff conducted surveys and interviews focused on the same topics with agency staff (GARFO, NEFSC, and the Southeast Fisheries Science Center and Regional Office), state agencies, Atlantic States Marine Fisheries Commission (ASMFC), Atlantic Coastal Cooperative Statistics Program (ACCSP) and its counterpart in the Gulf of Mexico (GulfFIN), the New England and Mid-­‐Atlantic Fishery Management Councils, and non-­‐governmental organizations. The results of these interviews formed the basis for further exploration of key topics as part of this industry workshop, and helped gather additional industry input that will be used to improve data collections and associated data management systems. Additional work focused on exploring standards for fishery dependent data will be conducted later in 2014 to supplement the results of both the surveys/interviews and the workshop. FDDVP Industry Workshop Summary: An industry workshop for the FDDVP was held in New Bedford, Massachusetts over June 30th and July 1st. The workshop was organized by GMRI, SMAST, GARFO and NEFSC. The purpose of the workshop was to further explore the current and future fishery dependent data needs of industry, science, and management in the Greater Atlantic Region. The workshop goals included: Goal #1: Provide context for the current data collection and storage systems, and identify benefits and challenges associated with fisheries dependent data collections and outputs. Goal #2: Characterize current and future data needs of industry, science, management, and enforcement. Goal #3: Identify desired characteristics of data collections and systems. 3 Goal #4: Identify tools and approaches that would help meet fishery dependent data needs most effectively. The workshop brought together over 60 fisheries stakeholders from the Greater Atlantic Region, including harvesters, seafood dealers, representatives from fishing and seafood businesses, industry associations, state agencies, academic and research institutions, environmental organizations, as well as groundfish sector managers, ACCSP staff, software developers, New England and Mid-­‐Atlantic Fishery Management Council staff, and NMFS staff. The workshop began with an introduction to the FDDVP and other initiatives to improve fishery dependent data collections such as the exploration of electronic monitoring in certain fisheries and discussions held at the Massachusetts Fisheries Institute (MFI) workshops. NMFS staff and the GMRI/SMAST project team followed this with presentations that summarized the existing fisheries dependent data systems, current uses of federal fisheries dependent data in the Greater Atlantic Region, current and anticipated data needs and desired characteristics of an ideal fishery dependent data system identified during stakeholder interviews. The format then pivoted to focus on current and future data needs to set the stage for breakout groups to discuss data needs and industry operations surrounding data collection. The second day focused on identifying the causes of data errors, gaps, and deficiencies, with breakout groups tasked with identifying ways to fill those gaps and reduce data errors, including industry suggestions for new ways to more efficiently collect fishery dependent data. Identified Themes: Over the two-­‐day workshop, several themes frequently came up in the presentations and discussions. The following statements aim to capture the collective conversation, though they may not represent the views of all workshop participants. • Fisheries throughout the Greater Atlantic Region vary considerably. A modernized system will need to be flexible to accommodate a wide range of operations, fishery-­‐specific management needs and uses, and the capacity of particular fisheries to collect and submit such data. • The data modernization initiative is about identifying the core set of data to address existing or anticipated data needs. Collection tools will need to ensure that the data collected and the associated outputs are consistent with system requirements identified by the data modernization project. For example, the methods for data collection could vary by tool and fishery as long as they meet the minimum needs identified for that fishery. • NOAA Fisheries is receptive to third party software developers designing tools to capture and submit the specified data streams based on the data needs and uses identified by stakeholders. 4 •
•
•
•
•
•
•
•
Care must be taken to avoid or minimize increased reporting costs to industry for data collection. Once data is collected, sound data infrastructure is needed to accept, integrate, and process the information that is submitted by industry. Minimize redundant data reporting. Future systems should include data collected from the best source and have the means to link to other data sets together to reduce redundancy and provide more accurate data. Where possible, data collection should be integrated to reduce time lags in access to data and reduce errors. Lessons learned from other data collection modernization initiatives, including those conducted by ACCSP, should be considered. Data collection requirements should prioritize need and use, while considering trade-­‐offs of cost and burden. Clear explanations about why data is needed and how it is used would help to build industry-­‐agency trust and may encourage more accurate data reporting. Workshop Outcomes: Outcomes for the workshop were intended to support overall workshop goals noted above. The following section includes a summary of workshop presentations and discussions related to desired workshop outcomes, as developed by NMFS staff and the GMRI/SMAST project team. The four outcomes are listed in the order they were addressed during the workshop. For a summary of the results of breakout sessions and plenary discussions, please see the appendices of this report. 1. Identify data needs and uses, and the level at which data elements could be collected and disseminated in a future system (Appendix 1). NMFS staff identified five fundamental uses for fisheries dependent data, including population estimation, management and regulation evaluations, quota monitoring, compliance monitoring, and bycatch and discard monitoring. A flow chart for each of these uses is included in Appendix 1. They reviewed the current data needs, including 42 data elements1 (e.g., total catch, fishing location, gear used, date 1 NMFS’s final table contained 48 data elements, although only 42 of these elements were discussed by the breakout groups. The other six elements are noted in Appendix 1. 5 sailed/landed, etc.), and described future data needs, such as finer resolution spatial data and oceanographic information. Workshop participants were asked to weigh in on the level/resolution that fundamental data elements could be collected (e.g., per haul, daily, per offload, monthly, etc.). The plenary and breakout discussions on this topic provided industry feedback on consideration of data needs and uses versus the feasibility of collecting data at the desired resolution. One theme among industry members centered on the importance and feasibility of collecting data elements at a finer scale. Some attendees felt fine-­‐scale data collection may be useful for various scientific and management needs, but may not be relevant to all needs and uses, and could be an additional burden to the industry. For several of the data elements, there were a range of responses regarding the resolution in which data can be collected. Factors affecting the resolution for particular data elements that were discussed included how the data would be used, how each fishery is managed, what benefits could be derived from the submission of particular data elements (for various users), and the logistics of various fishing operations. It was noted that there are policy trade-­‐offs for more refined resolution of data, which can be addressed by each fishery. For example, more precise data collected in the groundfish fishery allows for more refined management measures, but that comes at a cost in terms of reporting scale and complexity, extra data quality validation, and potentially additional operational costs to industry. The outcome of this session was a populated matrix of the resolution at which data could be feasibly collected (Appendix 1). Not all groups agreed on the level/resolution of data collection for each element, as this was a brainstorming exercise and was not designed to build consensus. Some of the general questions and comments brought back to the larger group of attendees focused on: identifying benefits to fishermen of all listed data elements; the need to analyze tradeoffs of reporting at various levels based on each data need; the need to reduce reporting redundancies; inclusion of state reporting requirements; how to reconcile multiple licenses or state registration numbers; how to resolve issues between the vessel trip report (VTR) and the dealer report; and how to report trips with multiple FMP fisheries, e.g. trip with bluefish, groundfish, black sea bass. NMFS staff will consider these issues, and further evaluate necessary data resolution based on the dual objectives of more effectively and accurately collected data without compromising the data needs of various user groups. Recommendations on these issues will be incorporated into the requirements document mentioned above. 2. Identify data errors, reasons for errors, and suggestions on how to address them in a modern data system (Appendix 2). NMFS staff presented data fields that contain errors on a regular basis, and explained that errors include blank fields, typographical errors, incorrect values, or missing an entire VTR or dealer report. The project team showed several examples of common data errors on VTRs and dealer reports. Presentations highlighted the 6 amount of time that is required for data entry and data correction from members of the fishing industry and the associated costs to industry and NMFS, including resources used in finding and correcting errors, the cost of physically returning (mailing) VTRs to the industry, and unusable data. Ramifications of data errors include delays in the delivery of data, inconsistent results, incorrect catch accounting, or data that is not used due to quality issues. NMFS Most Common VTR Data Errors (in ranked order)2: 1. Fishing Location 2. Dealer Name/Permit Number 3. Number of Gear Set/Deployed 4. Species ID 5. Gear Size 6. Fishing Time (average and tow/set) 7. Trip Start/End Date and Time 8. Landing Port 9. Vessel Name/Permit Number 10. Dealer Purchase Date 11. Gear Type 12. Landings Amount 13. Number of Hauls/Sets 14. Depth 15. Fishery Management Plan (FMP) 16. Fishery Management Plan Exemption 17. Fishery Management Plan Sub-­‐Program (access areas, Special Access Programs [SAPs]) 18. Operator Name/Permit Number 19. Discards Amount 20. Protected Species Interactions NMFS Most Common Dealer Errors3: 1. VTR number 2. Vessel name/permit # 3. Species ID 4. Product type 5. Combined trips (vessels that sell more than one trip to a dealer) Workshop participants were asked to provide feedback about where and why errors occur, to minimize errors in the design of a future system. Attendees provided several reasons for errors in reported fishing location, including use of 2 The list of VTR errors was provided by the GARFO, Analysis Program Support Division. The errors were aligned and grouped with the data needs that appear in Appendix 1. 3 The list of dealer errors was provided by the GARFO, Analysis Program Support Division. The errors were aligned and grouped with the data needs that appear in Appendix 1. This list was anecdotal and not ranked in any specific order. 7 LORAN, crossing reporting area boundaries in a single fishing tow, format of the VTR with only a single space for location information, and complications with using statistical area as the basis for location reporting. Attendees suggested overlaying statistical area grids on vessel chart plotting software programs, including more than one field for recording fishing location on VTRs, promoting electronic reporting to automate location information collection, and matching the resolution of data to the data need as possible solutions to fixing location reporting errors. Participants also commented on errors in the number of gear set fields on the VTRs. These errors appear to stem from possible misunderstandings of what is supposed to be recorded and confusion of fishery specific differences in gear. Simple solutions offered by attendees were provision of clear instructions with outreach to industry members and making the data collection system more suitable and compatible for all fishing gears. Attendees noted that there may be confusion between state and federal dealer reporting requirements, and that dealers/processing businesses have different needs for reporting than required by NMFS. To reduce errors in dealer reports, participants suggested consistency in state and federal reporting requirements and flexibility to design individual data collection systems. In addition to identifying reasons for specific data reporting errors, the workshop identified some general reasons associated with incorrect reports and missing data fields. General fatigue by vessel operators, short tow durations, wet hands and gloves, several simultaneous responsibilities, and weather were given as reasons for possible inaccurate reporting. Similarly, NMFS explained that data errors can occur while transcribing or entering data, combining data sets, and querying databases. The outcome of this session was a populated matrix of data errors, reasons for errors and suggestions of how to address the errors (Appendix 2). 3. Identification of data gaps and deficiencies, and suggestions on how to address deficiencies while considering trade-­‐offs of additional data collection (Appendix 3). Presentations from NMFS and the GMRI/SMAST project team covered four areas of data gaps and deficiencies from an industry and agency perspective: gear characteristics, spatial data, environmental data, and discards. For gear characteristics, it was noted that there is currently no way to distinguish between different gear configurations used to prosecute the fishery from data submitted on VTRs. For example, a diamond mesh codend has different selectivity properties than a square mesh codend of equal mesh size. Equally, the gear code ‘GNS’ does not distinguish between tiedown gillnet gear and standup gillnet gear. The presentations were designed to stimulate discussion on what additional data could be useful to include when designing a future data system. The point was made that filling data gaps and addressing deficiencies should yield improvements for both fishermen and science/management. 8 Each breakout group was asked to address data gaps and deficiencies in gear characteristics, spatial data, environmental data, and discards. Attendees commented that VTR forms are too general, and gear codes are not specific enough to capture gear configurations that can reduce bycatch or habitat impacts. Suggestions to address this data gap included modifying the fields on VTRs and associated gear codes, as well as using electronic reporting with gear configurations included in automated pull down menus. Participants noted, however, that those additional gear configurations could increase the need for monitoring and increase operational costs of a fishery. Identified deficiencies in spatial data collection included mismatch between reporting areas and fishing areas or resource location, lack of fine-­‐scale information across reporting areas, poor characterization of fishing locations by the small boat fleet, and lack of information for marine spatial planning purposes. Suggestions to address the deficiencies in spatial data included use of electronic reporting with automated location reporting, use of latitude and longitude position in place of statistical area, and using vessel monitoring system (VMS) logs to determine vessel fishing locations. Some attendees commented on the trade-­‐offs between higher resolution information and the burdens of additional reporting. Much discussion focused on improving discard information. Attendees noted that fishermen do not report discards accurately on VTRs for several reasons. Some industry members noted that VTR-­‐reported discards are not used by scientists or managers, thereby eliminating any incentive to report accurately. Others voiced concern that accurate reports could be used for enforcement purposes. Suggestions to address the data gaps on discards included expanded study fleets, inclusion of incentive-­‐based reporting for bycatch avoidance, reporting discards as proportion of total catch, increased observer coverage and smaller reporting strata. Participants noted that increased collection and use of environmental data could better inform stock assessments and managers on the effects of climate change and could be useful indicators for bycatch avoidance. Attendees suggested use of personal fishing log data to inform assessments and using study fleets to collect temperature, depth and other environmental information. Some participants voiced concern that there needs to be a proven method to incorporate additional environmental data before mandating collection by industry. As time allowed, some breakout groups identified other areas where data gaps and deficiencies exist. Topics of data deficiencies included social and economic information, biological elements, observer data collections, and reporting timeliness. A general comment was that outreach and communication is needed to address industry assumptions about how data will be used. Appendix 3 provides tables for each of the four topic areas, and lists the data gap or deficiency and potential solutions. 9 4. Pros and cons of industry suggested data systems, including collections, outputs, and tools (Appendix 4). The GMRI/SMAST project team presented a range of ideal data systems that were suggested during the Phase I industry interviews. The presentation noted that the majority of suggested systems included some form of electronic reporting. Industry interviews revealed that some dealers are collecting information on paper before entering it into the web-­‐based dealer reporting system, SAFIS. Dealers are also using a range of electronic collection devices to capture data from harvesters. The industry interviews found that although the majority of harvesters submitted paper VTRs, 81% of the fishermen interviewed indicated that they would be willing to submit the report electronically if changes to the existing system and tools were available. Data flow maps were used to depict the range of data collections that interview respondents deemed either redundant or unnecessary (Appendix 4, Figures 1 and 2, respectively). After the interviews, industry suggestions were compiled into three components: 1) Data Systems, 2) Hardware, Software, and Collections, 3) Data Access. Figures depicting these three components of industry suggested systems are included in the presentation, “Industry Interviews: Ideal Data System Suggestions” available on GMRI’s website. During the plenary session, input was sought on the feasibility of the industry suggested data systems. The discussion was centered around overcoming barriers in the current system surrounding issues with its flexibility, accessibility and confidentiality. This was followed up with integrating possible solutions to these barriers in an ideal system such as the use of electronic reporting and the collection of finer scale data while acknowledging that these solutions may not be appropriate for all fisheries or individuals within a given fishery. Russ Brown, NEFSC Deputy Director, expressed the willingness of GARFO and NEFSC to be flexible moving forward, and to work alongside the New England and Mid-­‐Atlantic Fishery Management Councils to improve data collection and management systems. This could entail the specification of standardized data streams through which 3rd party software or tools could be designed to collect data and provide it to NMFS in a standardized format. He noted the need to be cautious in looking for solutions that have wide application to the region’s fisheries, and that we should be ready to eliminate some aspects of the current system, as appropriate. Regardless of the changes the receiving end of the fishery dependent data system has to be ready and equipped to accept this new data before a new system can be fully integrated or operational. Although there was support for new data systems, such as swipe cards or tablets, there was also some concern as to whether these alternatives would work in all states or scenarios. This led into a discussion around the need to maintain the choice of multiple methods of data reporting for fishermen, along with the use of incentive and proper training to encourage and help fishermen with the transition to electronic reporting. Many scenarios surrounding electronic reporting may require reporting at a haul-­‐by-­‐haul level to gain finer scale data and some are 10 skeptical as to whether industry would buy into this. There was also concern that alternatives discussed were too fundamental of a change from the current system and the importance of having a plan going forward and ensuring that the data will be used was emphasized. FDDVP Next Steps Input offered during this workshop, including both comments and questions presented during plenary and breakout sessions, will be merged with input derived from stakeholder interviews and surveys conducted before this workshop. Together, these contributions will be directly incorporated into a data systems requirements document to be developed by NMFS staff by December 2014. This document will likely include a summary of the fundamental data needs and uses of all stakeholder groups throughout the Greater Atlantic Region, along with a list of desired system characteristics and data products/outputs. In addition, recommendations to address special circumstances in particular fisheries or other unique situations, including policy and procedural recommendations, will be developed to help ensure that the improved system is capable of maximizing the utility of fishery-­‐dependent data collected, while minimizing the burden to industry and other data users. The requirements document will be used to generate business rules and system requirements for NMFS or third party software developers to improve the existing, or create a new regional fishery dependent data system. Such business rules should be finalized by the spring/summer of 2015. A project plan and work breakdown structure will then be developed later that summer and fall, which will identify how and when various components of the improved fishery dependent data system will be built. Programming and testing of the new system is scheduled for the fall of 2016 and spring of 2017, with the final system expected to be ready for implementation by May 2017. NMFS will continue to provide updates on the development of the new system, including informing the New England and Mid-­‐Atlantic Fishery Management Councils, ASMFC, ACCSP, and states of system progress and any regulatory changes that may be necessary to revise data collections or other management measures. Once the system is implemented, NMFS will seek further input on system performance and future data needs as management measures and approaches continue to adapt to fishery and resource conditions. 11 Many thanks to the workshop steering committee and project team: Dr. Steve Cadrin, SMAST Douglas Christel, NMFS – GARFO Patricia Collins, GMRI Jessica Joyce, GMRI Rachel Long, GMRI Holly McBride, NMFS -­‐ NEFSC Peter Moore, Contractor Dr. Cate O’Keefe, SMAST Jonathon Peros, GMRI Daniel Salerno, Contractor For questions on the overall project, please contact either Doug Christel: [email protected], Holly Mcbride: [email protected] For questions about the workshop or industry interviews, please contact Jessica Joyce: [email protected] or Cate O’Keefe: [email protected] 12 APPENDIX1–DataNeeds/Uses&DataElementsTable
ThisappendixcontainsfiguresdetailingthefivefundamentalNMFS’needsandusesoffishery‐dependentdata,includingwho
usesthedata,whensuchdataareused,andwhatresolutionofdataisneeded,andatablesummarizingtheresultsofbreak‐
outgroupsdiscussingtheresolutionofindividualdataelements.
Figure1.DataUse:PopulationEstimation
Figure2.DataUse:By‐catchandDiscardMonitoring
Figure3.DataUse:Quota/EffortMonitoring
Figure4.DataUse:Compliance/Enforcement
Figure5:ManagementEvaluation
Thefollowingtablerepresentsthecollectiveresponsesofallsixbreakoutgroups(Outcome#1:Apopulatedtableofdata
needsanduses,andanassociatedlistofdesignapproachesforafuturesystem).Itisworthnotingthatnotallgroupsagreed
onthelevel/resolutionofdatacollectionforeachelementasthiswasabrainstormingexerciseandwasnotdesignedtobuild
consensus.Thistablecontainsthe42dataelementsdiscussedduringtheworkshop;howeverNMFS’finaltablecontainedsix
additionalelements:1)salinity,2)waterPh,3)gearsize,4)DASallocation,5)quotaallocation,and6)quota
balance/availability(inplaceofonlyquota).Thefinaltablealsoclarifiedbetweensurfaceorbottomwatertemperature.
DATA ELEMENT Vessel name/permit # LEVEL OF DATA COLLECTION Yearly; reported by source at trip level; per offload. NOTES/COMMENTS Should apply only when there are landings to report. Vessel registration is more important than vessel name. Operator name/permit # Trip; reported by source at trip level; per offload
Prefill by captain one time Dealer name/permit # Per offload; daily; reported by source at trip level.
Prefill by captain one time; for harvesters, the group thought that this might vary by operation and that it was important to account for multiple offloads. Vessel characteristics (size, HP, tonnage) Yearly; with permit change (initial, transfer, or change, e.g. horsepower. Yearly; with permit change (initial, transfer, or change, e.g. horsepower. Owner name Who controls fishing operations? Sector participation (rosters) Moratorium right ID (MRI) Allocation ID (surfclam/quahog, scallop) Unless upgrades occur; prefill by captain one time. Unless changes; prefill by captain one time. Vessel operator by trip, Information not needed. (When reviewing the level column, please note there was confusion over the definition of this data element.) Yearly (with sector operations plan); or when changed. Yearly; permit change. Prefill by captain one time. Yearly; per offload, per trip. DATA ELEMENT LEVEL OF DATA COLLECTION NOTES/COMMENTS Number of crew Trip, when available; by trip by captain; per offload. If always taking same number of crew, no need to report on trip level Observer status Trip or haul observed (per effort event); when available; by trip, trip ID in report; Not needed; per offload. Recorded by observer program; look at observation of specific haul, not just presence or absence on a vessel; observers indicate whether they have observed each haul. FMP Sub‐trip / trip; yearly; by haul; not needed; per offload. Depends on target/gear, should this be activity code to allow switching catch, e.g. groundfish to monkfish, rather than FMP? Fishery and permit dependent; is the question what fishery? Sub‐trip / trip; by haul; per offload. Depends on target/gear; if there were flexibility to enter sub‐
programs within a trip then reporting on a tow by tow. Sub‐trip / trip; by haul; per offload.
Depends on target/gear
Target species Per effort event / trip level in some fisheries; per species targeted; by haul; not needed. Note changes target species as it changes on the trip ‐ not necessarily on the haul by haul level, but at a higher resolution than at the trip level. Too much information for industry to collect.
Species Per effort event when possible or sub‐trip when per effort event is not practical; per haul or set; per area fished.
This level will depend on the volume of catch. Landing amount Per offload; by haul; per week; per trip; per area fished. Depends on FMP reporting needs; report by dealer, should this be sold amount because that's what a dealer would record. FMP Sub‐program (access areas, Special Access Programs, etc.) FMP Exemption Landing disposition Depends on FMP reporting needs; no way of recording with (sold, disposed, donated, Per offload; by haul; per week; per trip. current system. etc.) Kept catch amount not Per offload; by haul, by captain and observer; per sold (personal use, Depends on FMP reporting needs. week; per trip. seizure, etc.) DATA ELEMENT Discarded amount Protected species interactions Product type (market/grade) Size (length and other measurements) LEVEL OF DATA COLLECTION NOTES/COMMENTS Per effort event when possible or sub‐trip when per effort event is not practical; per haul or set; by haul, by captain and observer; per week; per trip; not needed; per area fished.
Needs to be willingness to use self‐reported data; VTR discards not used; possibly use EM to record discards. Per event; per haul; per target species; gear. Per offload; per trip Per offload; by trip / area by observer & port sampler; trip ‐ unobserved, haul – observed. Study fleet information or dockside monitoring. The focus of the discussion of this element was mostly from the dealer perspective. Per offload; by trip / area, by observer, port sampler; trip ‐ unobserved, haul ‐ observed; monthly. Trip start/end date/time When Available; per trip; per offload.
Dealer purchase date Per trip; per offload.
Days‐at‐sea (DAS) used Per trip; per offload
Fishing time (average Per haul or set; per offload (depending on the and tow/set) fishery). Sailing Port Per trip; per offload.
Landing port Per trip; per offload.
Age (samples) Fishing location (area and detailed) Per haul or set; per area Fished. Vessel position Per haul or set; collected by Study Fleet. Depth Per haul or set; not needed; collected by Study Fleet. Study fleet information or dockside monitoring. Suited for port sampling. By captain per trip
By captain per trip
Not always possible at haul level, what position: begin, end, trackline; if electronic or automated could be done on finer scale. Not always possible at haul level, what position: begin, end, trackline. Match with position data; not something captains are likely to record, but with precise lat/long, depth could be back calculated. Also, could be automated using depth/temp probes on the gear. DATA ELEMENT LEVEL OF DATA COLLECTION Dissolved oxygen Per haul or set; collected by Study Fleet. Temperature Per haul or set; collected by Study Fleet. Number of hauls/sets Per trip; per area fished Per haul or set; yearly; when changed; per area fished. Gear type Detailed gear (modifications) NOTES/COMMENTS Collection method dependent; could be passively collected. Collection method dependent; automated data collection devices; could be passively collected. Fine scale if gear changes significantly during trips. This drew a lot of conversation. Some folks thought that gear should be recorded on a haul level, others said it should be Per effort event when possible or sub‐trip when recorded when the target species changes, others thought per effort event is not practical; per haul or set; per species targeted; per event; per trip; per area that it should be recorded when the "event" of the changing/modifying the gear occurred. One fisherman noted fished. that he tinkers with the gear on a haul by haul basis, and that "modifications" could use a standard definition. Number of gear set/deployed Per haul or set; per trip; per area fished. Price/value of landings Per trip: per offload
Cost Per trip: per offload Quota Depends on who needs to know and by when; per haul or set; per area fished; per offload. Better description of what is requested for gillnet: # of nets or # of panels/net. Industry may not benefit from additional cost reporting; owners have this information. APPENDIX 2 – Data Errors Table The following table of data errors, reasons, and suggestions for addressing the error reflects the collective’s input during the plenary session (Outcome #2: A matrix of data errors, reasons for errors, and suggestions on how to address these in a modern data system). Comments are not attributed to individuals. Error Fishing Location Reasons Suggestions of how to address/fix Still reporting in LORAN (unacceptable format): being calculated into coordinates Skymate has inaccuracies in location VTR Format (only has space for one location) Industry not interested in sharing their fishing location. Reporting grids are too big The time lag inherent in reporting Typical vs. actual tow (complacency) Complications for high volume trips (recording location start/end) With 5‐6 hour tows, crossing areas (and/or turning within tows), how do you calculate bottom time, etc. Statistical area gridlines aren’t in the GPS Technology is our friend (GPS integrated in most boat hardware/software), e.g., push button – start location & end Don’t have to ask for location on tow‐by‐tow basis, but can evaluate mean location by statistical area. Technology as a back‐up for QA/QC and environmental data. Need standard definitions for bottom time. Tune to operation (fishery, gear). Have photos or video of the haul (for busy operations where unfeasible to push buttons, etc.) to enable backfilling information. (Implications for mixed‐spp. Fisheries). Overlay statistical areas within GPS systems/software (e.g., “you are here, 512”). FLNDRS assigns a statistical area based on haul back. Can we use lat/long of start and end vs. stat area for some fisheries? Match resolution of data collection to what it’s being used for. For environmental data, matching to VTRs is difficult using Statistical Area  match where fishermen start haul back (standardized: Error Reasons Suggestions of how to address/fix softwares. Statistical area isn’t the best resolution for other uses of data (e.g., climate change); we need finer scale. observers, VTRs). Ask fishermen when ideal time would be to record position data. Haul end might not be ideal, but the beginning might be better. Define for all gear types. Ocean planning – needs higher resolution for various uses. Fishermen’s ability to recall data is beneficial (design timing that is of value to harvester). For example, drop‐down box and audit. Automated, electronic is what the industry wants; provide data needs to 3rd party and let them address how to collect these data. Error Reasons Suggestions of how to address/fix Number of Gear Set If you set 6 strings at the same time, those 6 pieces of gear cover a depth range of 10 fathoms, which is very fine scale. Potential misunderstanding of what’s being asked of vessels (e.g., lobster – pots in water/being fished). Also confusion in hook and line industry (e.g., # hooks). VTR gear overestimation (over observer report); misunderstanding. Availability of observer data in real‐
time/near real‐time (perhaps raw data at the boat?). Attempt to represent gear allocation (e.g. # of traps) because of perceived use of data by enforcement General Captains forgetting to enter certain fields. Clear instructions/documentation & outreach. Get a copy of the raw observer data, review the report (e.g., fishermen would see the frequency/level of data and perform a self‐
audit, increasing QC). Some fisheries can see observer data w/in 48 hours, through SIMM. Even a data summary of observer reports would help, because the level of data collected by captain vs. observer is not equal. For observed trips, a system automatically creates a VTR form based on that info. Observers moving toward a Toughbook, and can perhaps highlight fields across data sets (observer and Captain/VTR log). Technical and analytical data could be lost if you are not collecting data from both captains and observers (e.g., mixed skates vs speciating skates). Distinguish between # in the water and # fished during the trip. Make the system more suitable to ALL gears (e.g. non‐groundfish). More customization by gear, less generalization (e.g. gear number, gear type) High level gear type designation dictates customized data entry platform. Tablets pre‐populate fields (digital database). Error Reasons Species ID: old paper logbooks, where codes haven’t been updated. Species Identification Dealer Name & Permit Number Port Landed Old paper logbooks, where codes haven’t been updated. Species redistribution: for the species coming up from the south, fishermen don’t know what the species are. Mixed species landed together (e.g., red/white hake, juvenile winter skate vs. little skate) Are we doing a disservice from misidentifying species? Do some species that are not landed need to be recorded? Confusion with state/federal dealer numbers. NY; has its own system, they are their own consignment system Different needs for private businesses (dealers) than Federal needs. SAFIS ‘favorite’ defaults for other ports (also occurs for favorites in other fields). Suggestions of how to address/fix One ticket system: vessel operator hand off all data to dealer (could work in small‐scale fisheries). Automation of a unique code. Electronic data collection For common species, there should be a pull‐down list to select from. Photo guides. Do we only need a multispecies code for certain species not being landed? For states: a lot of overlap between state/federal dealers: cross‐
reference back to permits, so the dealer number isn’t as much of an issue. Be flexible for different sales systems. Need to identify what we need at initial offload. One‐ticket scenario: Fishermen upload everything except the price initially and then several days later, dealer includes price. More concrete integration of systems, checks and balances Error Reasons Multiple ports in a single trip re‐coded incorrectly during the audit. Vessel‐dealer integration problems. Difficult to correct recurrent problems because there is no accountability. Suggestions of how to address/fix Timely uploads to ID problems at the time. APPENDIX 3 – Data Gaps & Deficiencies Table The following tables represent the aggregated responses of all breakout groups. Each group was asked to address data gaps and deficiencies, starting with gear modifications, spatial data, environmental data, and discards (Outcome #3: Feedback on how NOAA Fisheries and Industry can work together to fill data gaps). As time allowed, some breakout groups identified other areas where data gaps and deficiencies exist. Individual rows represent the issues and fixes suggested by a single breakout group. One general comment was that outreach and communication is needed to address industry assumptions about how data will be used. Gear Modifications Issues Forms are too general ‐ fisheries are so different (gear types, modifications, number, fishing technique) ‐ current forms make it difficult/impossible to properly describe fishing activity How do we capture gear modifications to the level needed by industry, management, science? Need (gear information) for bycatch, FMP modifications. How to differentiate between modifications and original gear? How to capture gear modifications? Not capturing specific gear configurations; not getting credit for bycatch reduction gears Confusion about gear codes Need to capture what is actually being used for gear How to address/fix & trade‐offs Develop unique forms (customization)/electronic platforms for each fishery. Automation would also be helpful. 

Sweep length important Square vs diamond mesh important Need to be able to distinguish between original gear type and modifications because it would allow more precise accounting "Gear Modifications":  Yes/No field on VTR.  Can have detailed gear descriptions by permit on Fish OnLine account to reference which gear on VTR or barcode gear for observer reports. Pull down menus that have "favorite" gear; new gear codes to include more specific configurations; additional codes could be difficult for dealers to understand; additional gear codes could lead to additional strata and potential to reduce assumed discard rate (groundfish); changing gear configuration during a trip may cause additional reporting requirements; Account for separator mechanisms (in gear); create optional collections and modules; standardize gear codes Issues How to address/fix & trade‐offs Inconsistent gear classification ‐ not enough codes to track changes Speed of gear modification review process discourages gear tweaking to reduce discards Increase # of codes/ potential bias/transition costs; challenging to get statistically significant bycatch sample per strata. Stop assigning assumed discards to unobserved trips. Discards Issues Dealer discards ‐ how can we better record these discards? (Mortality that is unaccounted for.) Misreporting by fishermen Discard estimation Discard mortality not as gear specific / updated as needed Observer bias Estimating discards on unobserved trips How to address/fix & trade‐offs Look at the lobster industry protocols (follow the rules). Also don’t reconcile VTR with dealer data ‐ the difference may be a tool to help quantify dealer discards. Full retention, or more specifically maximum retention of regulated species. Also use logbooks for documentation not necessarily quantification ‐ use them to observe changes, and trends, not as "hard" numbers. Non‐observer based discards? Observer acts as an inspector of an accurate log (essentially changing the role of the observer). For hire client would validate discard estimates. Multi‐prong approach using several techniques to validate/estimate discards. For unobserved trips, use random US Coast Guard boarding and fish counting or full retention / shore side monitoring. Use captain / observer debrief at end of trip before leaving boat and using data from observer tablet to understand and correct data at first read. Get download of observer Toughbook to captain at end of trip (Doug Christel says that NAFO does this w/in one hour of landing). Make the report to the captain an observer contract requirement. Lack of reliable self‐reported estimates:  Discard weights more difficult to gauge as fishermen see dressed fish not round fish Assumed discard strata is not accurate; automatic discarding in conveyer fisheries; not enough detail on discard mortality; VTR discards are not used by scientists or managers; Make assumptions about discards from observed trips to apply to the unobserved trip ‐ not a true count of discards. Current data collections are not capturing the selectivity of fishing gear ‐ gear codes don't account for all modifications and don’t capture avoidance. Inconsistent discard estimation due to several factors  observed vs. unobserved, different gear types etc. Inability to assign discard rates to more narrowly defined strata Slow data processing/checking Fishermen trying to game the system Conduct statistical analysis of unobserved trips to determine bias. [Make self‐reporting discards?] Not required Report only select species (i.e. FMP species) Report level of discards or percentage of catch in total instead of by species. Study fleets could give better resolution on discards, but will need a verification process; expand incentive based discard recording, such as SMAST Bycatch Avoidance; additional discard accounting could impact fishing operations and lead to economic loss; additional studies on discard mortality; electronic monitoring; increased observer coverage; small discard strata. Should we even collect discards if the trip is unobserved? Ask what the total catch is for that tow, not by species. Use the difference between the total catch and landed catch to estimate the total volume of discards from a trip. Process observer data more quickly (and make available to industry). Industry alerts about protected species interactions  hot spot alerts, industry collaboration Expand industry involvement in research  financing for gear technology research (S‐K grants) Environmental Issues Distribution shifts (dealing with new species, shifting fishing grounds, permit issues)  Auditing process may incorrectly change a valid rare event  Need for information (oceanographic) to be collected Current environmental data collected (eMolt, survey, other research projects) not spatially and/or temporally coordinated Minimal data currently collected to inform assessments of environmental change Depth/structure fished on matters, not regularly collected How to address/fix & trade‐offs Use fishermen to help detect change ‐ take better advantage of this knowledge base Pictures of rare events Consolidate information, provide data to fishermen so that they can use it eMOLT Program); cooperative studies may be better suited to collect this type of information; don't mandate collection of this type of data but make the tools available Use study fleet / sampling (not census) to get environmental data, i.e. not a requirement for everybody Use MARACOOS/NERACOOS data for environmental info Can be used to predict bycatch/protected species interactions, need outreach & regular output of information accessible to all, platforms of opportunity with fleet with passive recorders across region as a subset of industry & not gear specific, observers deploy recorders on gear for observed trips Automated data collection devices delivered to and installed on vessels by port agents; study fleets; 3rd party management of data set; additional data needs to be able to integrate with current data collections (buoys, survey samples, satellite); assessment models currently not capable of incorporating environmental data, need to be sure there is a use for the data before adding new data collection requirements; voluntary collection of environmental data Use the data from the composition of non‐target catch to help determine habitat, i.e. sand dollars, sea stars, will help determine habitat structure. Missing other components of bycatch that are indicators of habitat. Climate change changing species distribution, bottom temperature Collect data on catch relative to environment – temperature data from fishing line Environmental data modeling Spatial Issues Confidentiality / security issues / don't want to share data What level of spatial resolution is needed for management and science? Catch of target species versus bycatch Resolution not fine scale enough to capture differences across statistical/stock areas Statistical areas cover very large areas with very How to address/fix & trade‐offs Deal with confidentiality issue and we can get better data. Increase transparency about data use, modify requirements based on specific stock needs, and create data ownership. Better explain current confidentiality regulations. Make the option available so people who want to provide detailed data have a platform to do it. Make it simple / easy to record and access. Align management regime to catch up to ability to determine where activity is taking place, i.e. use the electronic location tools that are available and modernize regulations to match. Eliminate use of statistical area on data reports (statistical area could easily be added electronically from lat/long). Dynamic feedback loop of catch/bycatch in real time Additional data could change assumed discard rate and increase benefits to industry, but tradeoff is effort to collect more data; system to process more data in real‐time currently does not exist; finer scale management may benefit portions of industry, but may increase monitoring requirements or lead to more constraints by area. Automate spatial fishing locations. different habitats and depth, these differences get lost in the current reporting system. Change the reporting areas to reflect a finer resolution. Match the scale of spatial resolution to what the fishery requires. Lack of resolution on where fishing occurs. Use VMS to understand the tow path. Set a common level of resolutions. Develop/utilize inexpensive mapping tools (trade‐off: loss of confidentiality Concerns about marine spatial planning and and secrecy of fishing grounds). confidentiality (all data) Poor characterization of small boat fleets Social/Economic Issues How to address/fix & trade‐offs Catch history not matching current actual catch Collect finer scale catch information  fish catch location versus landing port  current groundfish allocations not reflective of current available species to catch Lack of socioeconomic information Collect trip costs on more fishing trips, not just observed; no benefit to industry from collecting more cost data, owners use this information and already have it; not willing to share fine scale cost information; what gap would be filled by collecting additional socioeconomic data? Who is fishing – Collecting data on operator and crew. Collect socio/economic data when there is a permit change. Ports, purchases For party/charter trips, have a tablet for the boat for crew to fill out there info Variable trip cost surveys Data bias by sampling error Translate surveys for non‐English speakers Language barrier Survey in different/more ports Extreme inaccuracy with fuel estimation Free up observer time to collect socio‐economic data CPUE – fuel use Give option to provide data anonymously Observers Issues Issues with fishermen‐observer interactions: how can we improve this interaction? Also miscommunications about the role of observers related to the perception of enforcement as opposed to data collection. How to address/fix & trade‐offs Education and communication with fishing industry. Improved observer training / retention Biological Elements Issues Stomach contents, maturation, age How to address/fix & trade‐offs Reporting Timeliness Issues Time lags in error corrections impacts the accuracy of report (error corrections are asked 4 weeks to 6 months after a trip, captains have to guess). Linking state and federal data can take months ‐ availability of data (months) Differences in federal vs. state management impacts availability of data How to address/fix & trade‐offs Improved communication between state agencies gathering data and NOAA fisheries to make data available in a timely way for stock assessments. APPENDIX 4 – Industry Suggested Data Flow Maps This appendix presents two data flow maps that reflect feedback from the industry interviews. Figure 1 depicts redundant data collections and Figure 2 depicts unnecessary reports. These maps are part of the presentation, “Industry Interview: Ideal Data System Suggestions,” available at www.gmri.org/fishdependentdata. Figure 1. Redundant Data Collections Figure 2. Unnecessary Reports APPENDIX5–WorkshopPresentations
AllpresentationsareavailableonGMRI’swebsite:
http://www.gmri.org/fishdependentdata.Thisappendixbrieflysummarizeseach
presentationandexplainsthescopeoftheplenarydiscussionsandbreak‐outgroups.
DAY1:
FederalFisheryDependentDataVisioningProjectandProcess
DanMorris,DeputyRegionalAdministrator–GARFO
RussBrown,DeputyScienceandResearchDirector–NEFSC
NortheastFisheryDependentDataVisioningProjectIntroduction
DouglasChristel(GARFO)begantheday’spresentationsbydescribingtheFDDVinitiative
indetail.Heemphasizedthebroadscopeoftheproject–notingthattheagencywill
completeacomprehensivedataneedsandrequirementsanalysis.Dougalsounderscored
thatalloptionsarebeingconsidering–includingsoftwarerevisions,changesto
regulations,andstaffing/resourceadjustments.Thepresentationoutlinedproject
participants,andtheapproachNOAAFisheriesistakinginthisinitiative,andupdatedthe
groupontheinternalinterviewsDougandHollyMcBridecompleted.ForNOAA’snext
steps,Dougdiscussedoptimizingdatacollections,mappinganintegrateddatasystem,and
walkedtheaudiencethroughanimplementationplan.
GMRIandSMASTCINARProjectOverview
JonathonPeros(GMRI)introducedtheGMRI/SMASTprojectteam,andhighlightedthe
industryfocusoftheproject.Hedescribedthemulti‐phasedapproachbeingtakento
understandandcharacterizethedatacollectionandsystemsthatareneededtoeffectively
managefisheriesthroughouttheGreaterAtlanticRegion.Heunderscoredthatthe
approachbeingtakenbyGMRIandSMASTalignswiththeeffortofNOAAFisheries,before
summarizingthethreephasesoftheproject.GMRIandSMASTwillcontinuetheirworkon
theFDDVinitiativeintoearly2015.
DataRecommendationsfromMassachusettsFisheriesInstitute(MFI)End‐to‐End
ReviewofMonitoring
Dr.SteveCadrin(SMAST)beganhisinvitedtalkbyintroducingtheMFI’sEnd‐to‐End
ReviewofNewEnglandGroundfishstockassessments.TheEnd‐to‐Endreviewwas
comprisedofaseriesofthreeworkshops,andworkshopreportscontainingaseriesof
recommendationstoimprovethescientificbasisofmanagementforgroundfishfisheries.
Thethirdworkshop,focusedonfisherymonitoringandsurveyselectivity,hasparticular
relevancetotheFDDVP.Hesharedseveralshort‐andlong‐termrecommendationsthat
cameoutoftheMFIworkshop(workshopreport).Short‐termrecommendationsincluded
moretimelyavailabilityofinformationisneededformanagementofallfisheries,increased
accessibilityofdataforallusers,andamorepreciseapproachisneededtodeterminecatch
locationonunobservedtrips.Long‐termrecommendationsincludeddefiningthecurrent
objectivesofthemonitoringsystemandthecorrespondingsystemrequirements,creating
anintegratedsystemofcollectionprogramstogainefficiencies,streamlinedelectronic
reportingwithefficientdataentryandprocessingwouldbeanimprovementoverpaper
logbooks,andcontractingsoftwaredevelopmenttoprivateindustryshouldbeconsidered.
Heconcludedhistalkbynotingthatthecurrentfisherymonitoringsystemwasdesignedto
domanythings,buthasnotbeenevaluatedforperformanceandcostefficiencyinmeeting
currentandnearfutureneeds.Hewrappedupstatingthatimprovementsareneededto
supporttheincreasedneedsoftimelyfisherymonitoringandmoreeffectivefishery
managementingeneral.
NMFSandExternalPartnerDataUses,Strengths/WeaknessesofExistingSystem,and
FutureCharacteristics
HollyMcBride(NEFSC)spoketotheneedsbasedapproachNOAAFisheriesistaking
throughtheFDDVinitiativeindetailbeforedescribingthefivefundamentaldatausesby
theagency:populationestimation,managementandregulationevaluations,quota
monitoring,compliancemonitoring,andbycatchanddiscardmonitoring.Foreachofthe
fivefundamentaldatauses,Hollyexplainedwhytheyarenecessaryandwhatdatais
neededforeachuse.AllofthefundamentaldatausesaremandatedbytheMagnuson‐
StevensFisheryConservationandManagementAct(MSFCMA),andseveralarerequiredby
otherpiecesoffederallegislationsuchastheEndangeredSpeciesActandMarineMammal
ProtectionAct.Shewentontosaythatadditionaldatausesincludedatarequests,research,
fishingtrends,costrecovery,economicperformanceindicators,IFQtransfers/leases/
allocations,andeligibilitydeterminations.Hollythendescribedthestrengthsand
weaknessesoftheexistingdatasystem.Strengthsincludedthelongtimeseriesforfishery
dependentdata,acomprehensivefour‐sourcedatasystem,andpartnershipswithother
agenciesandorganizations.Weaknessesincludedredundantsystems,lackofintegration
amongexistingsystems,insufficientprecisionofVTRareafished,poorcommunication
amongstaff,andinconsistentdataoutputs.Hollyofferedthatafuturesystemshould
integratefisherydependentdatasystems,collectandtransmitdataelectronically,
automatevalidationprocesses,reducemanualentrywherepossible,makedataavailable
onlocations,becontrolledbyoneentity,andbeflexibletoadapttochanges.Sheconcluded
bynotingthatitisimportanttoonlycollectdatathatisneededandwillbeused.
FisheryDependentDataFlowMap–GroundfishSectorVessels
DanielSalerno(Contractor&GroundfishSectorManager)describedthedata
collectionsandflowsatvarioustimesduringasinglefishingtrip(Figure1).Hefocusedon
groundfishsectorvessels,asreportinginthatcomponentofthefisheryisoneofthemost
complexofallGreaterAtlanticfisheries.Hebeganbydescribingtheentitiesinvolved,
followedbyrequireddatasubmissionspriortoleavingthedock,whileatseaaswellas
uponlanding.HealsodidhighlightadditionalreportingrequirementsinotherGreater
AtlanticRegionfisheries.
before trip
PTNS
during trip
NEFSC
after trip
ACCSP
paper VTR
VTR
IVR
Vessel
arc line, RSA trip,
fishing inside dem
trip declaration
Scal/Mult trip
flex declaration
Trip Start Hail
GARFO
Trip End Hail
catch report
VMS
AM S
&
Deale Complia
nc
r,
HAPO DAS, Ca e, OBS,
tc
Roste , Hails, VT h,
R , PT
r, PS
C &A
N S,
CE
port
/Inj Re
dealer repo
rt
Mort
MMPA
Monk Trip Limit Overage
sector
manager
Protected
Resources HQ
dealer
ho
weig
p
ut sli
Figure1.Dataflowsduringasinglefishingtrip
DataVisioningIndustryInterviewResults
Dr.CateO’Keefe(SMAST)presentedresultsfortheGMRI/SMASTindustryinterview.At
theoutsetofhertalkshenotedthatthedataresponsesbeingpresentedcamedirectlyfrom
interviewswithindustrymembers,andmaynotberepresentativeoftheviewsofall
projectparticipants.Theprojectteamcompletedinterviewswith57individuals
throughouttheGreaterAtlanticregion.Thissamplecoveredawidedemographicof
businesses,fisheries,ports,andgeartypes.Cateexplainedthatinterviewquestionswere
organizedintocategoriesfocusedondatacollectionsandflows,feedbackonthecurrent
system(positive/negative),andinputfordesigningan“ideal”datasystem.Cate’s
presentationincludedanalysesofresponsesfromharvesters,dealers,processors,industry
association,sectormanagers,softwaredevelopers,andfleetmanagers.Formore
informationabouttheresultsoftheindustryinterview,pleaseseetheindustryinterview
reportpreparedbytheGMRI/SMASTprojectteam.
MAFMCVisioningProject:Science/DataThemes&Recommendations
MaryClark(MAFMC)beganherinvitedtalkwithabriefexplanationoftheMAFMC’s
StrategicPlanningandVisioningProcesses.AspartoftheMAFMC’sVisioningProject’sdata
collectionphase,theCouncilreceivedinputthroughsurveys,portmeetings,andposition
letters.Throughthisinput,themecategoriesemerged,whichincludedscienceanddata.
Marypresentedresultsthatshowednearly2/3rdsofstakeholderrespondentswere
seriouslyconcernedaboutthemanagementimplicationsofalackofaccuratebiological
data,alackoftimelydata,andalackofaccuratesocialandculturaldataavailable.The
MAFMC’svisioningprojectrevealedthatstakeholdersbelievethatdatausedbytheCouncil
lackstheaccuracy,precision,anddetailneededtoinformfisherymanagementdecisions,
thereportingprocessisredundantandinefficient,andthatthereistoomuchofatimelag
betweendatacollectionandresultingmanagementdecisions.Maryconcludedhertalkby
sharingdesiredcharacteristicsofcollectionsystemsthatincludedminimizingtimelagin
datacollections,improvingcoordinationbetweenscienceandmanagementprocesses,and
creatingfeedbackloopsamongscientists,managers,andfishermen.
PLENARYANDBREAKOUTSESSION:FisheryDependentDataNeedsandUses
ThisplenaryandbreakoutsessionwasdesignedtoaddressGoals#1and#2ofthe
workshopbycompletingOutcome#1.PresentationsbyJonathonPerosandDouglas
ChristelfocusedoncurrentandfuturedataneedsandusesbyindustryandNOAA
Fisheries,andwerefollowedbyaplenarydiscussion.Forthebreakoutsessions,
participantswereaskedtoweighinonthelevel/resolutionfundamentaldataelements
couldbecollectedat(haul‐by‐haulvs.trip).Handoutsofthefivefundamentaldatauses
withcorrespondingdataelementswereprovidedforreferencebacktotheusesofthat
data.Theoutcomeofthissessionwasapopulatedmatrixoftheresolutionatwhichdata
couldbefeasiblycollected(Appendix1).
Facilitator:Dr.CateO’Keefe
DataVisioningIndustryInterview:DataNeedsandUses
JonathonPeros’(GMRI)presentationofindustryneedsandusesbuiltontheinterview
resultspresentedbyCateO’Keefe.Inhistalk,Jonathonhighlightedfive
themes/characteristicsthatindustryspoketowhenaskedtodescribeanidealdatasystem:
accessibility,accuracy,efficiency,flexibility,andresponsiveness.DuringthePhase1
interviews,industrymemberswereaskedtoidentifyanyfutureneedsorusesoffishery
dependentdata.Responsesincludedreal‐timeandfine‐scalemanagement,betterdiscard
estimates,traceability,marinespatialplanning,andcharacterizingecosystemandclimate
change.Industryalsoidentifiedgearconfigurations,environmentaldata,economic
information,discardinformation,andmorepreciselocationinformationasdatathat
shouldbecollected;aspartoftheinterviewindustrydescribeddatacollectionchallenges,
whichincludedfatigue,weather,shorttows,largevolumecatches,severalsimultaneous
responsibilities,andchallengingworkconditions.Industrywasclearthatanewsystem
shouldreducereportingburdens,andthataone‐sizefitsallapproachwillnotworkacross
allGreaterAtlanticfisheries.
CurrentandExpectedDataNeeds:NMFSandExternalUsers
TheafternoontalkondataneedsbyDouglasChristel(GARFO)teedupthesubsequent
plenarydiscussion,whichwasfollowedbybreakoutgroupdiscussions.Dougdescribedthe
currentdataneedsforfisheriesmanagement,whichhebrokedownintofundamental
elements.Hethenreviewedthecurrentdataneeds(totalcatch,fishinglocation,gearused),
andwentontodescribefuturedataneedssuchasfinerresolutionspatialdataand
oceanographicinformation.Thetalkthenpivotedtoconsiderthedataneedsanduses
versusthefeasibilityandresolutionofthedatacollection.Hepointedoutthatfine‐scaled
datacollectionisnotrelevanttoallneedsanduses,andcouldbeanadditionalburdenon
industry.DougthenwentontodescribethefivefundamentaldatausesthatHollyMcBride
spoketoearlierinthedayingreaterdetail.Heconcludedhistalkwithaseriesofquestions
relatedtothebreakoutexercisefocusedonunderstandingthelevel(resolution)ofdata
collectionthatisfeasibleforcollectionbyindustry.
DAY2
JohnBullard,RegionalAdministrator(GARFO)beganDay2withremarksemphasizing
theimportanceoffisherydependentdatainfisheriesmanagement.
PLENARYSESSION:DataErrors
ThisplenarysessionwasdesignedtoaddressGoals#1and#2oftheworkshopby
completingOutcome#2.Thedataerrorssessionbeganwithback‐to‐backpresentationsby
DanielSalernoandHollyMcBride,followedbyaplenarydiscussionledbyDr.SteveCadrin.
Thediscussionfocusedonreasonsfordataerrors,aswellassuggestionsforhowtofix
them.
Facilitator:Dr.SteveCardin
DataCollectionandEntryErrors(IndustryPerspective)
DanielSalerno(Contractor&GroundfishSectorManager)presentedresultsfromthe
Phase1industryinterviewondataerrors,andshowedexamplesofentryerrorsofthe
VesselTripReportserialnumberindealerreports,triphails,catchreports,observerdata,
etc.Dannotesthatthedatacollectionandentryprocesseswhetheritishandwrittenor
electronic,cantakeaconsiderableamountoftimeforharvestersanddealers,andthat
errorsonlyincreasetheamountoftimetheyspendenteringdata.Heshoweddifferences
betweenthepaperVTRandelectronicvesseltripreport,suchasthenumberofdigitsused
toformtheserialnumber(8vs.14).Danalsowalkedthegroupthrougharangeof
scenarioswhereinformationfrommultipletripsiscombinedintoasingleeventandvice
versa.
DataCollectionsandEntryErrors(NOAAFisheriesPerspective)
HollyMcBride(NEFSC)beganhertalkbynotingthatalldatahaserrors.Shewentonto
describethetypesoferrorsthatNOAAFisheriesstaffseeintherequireddatasubmissions
(suchasVTRs),whichincludeblankfields,typographicalerrors,incorrectvalues,and
missingdata.Shepointedouttheassociatedcosts(resources)thatgointoaddressing
errors,whichincludes,butisnotlimitedto:resourcesusedinfindingandcorrecting
errors,thecostofphysicallyreturning(mailing)backVTRstotheindustry,andunusable
data.Ramificationofdataerrorsincludesdelaysinthedeliveryofdata,inconsistent
results,incorrectcatchaccounting,ordataisnotusedbecauseitisofquestionablequality.
Hollyconcludedherpresentationbyreiteratingthatitiscrucialtounderstandwhyerrors
areoccurringsothattheycanbeminimizedinthedesignofafuturesystem,andeveryone
canavoidtheconsequences.
BREAKOUTSESSION:DataGapsandDeficiencies
ThedatagapsanddeficienciesbreakoutsessionfocusedoncompletingOutcome#3.Holly
McBrideandDanielSalernogaveashortjointpresentationthatfocusedondatagapsand
deficiencies.FollowingthesameformatastheDataErrorsplenarysession,sixbreakout
groupsworkedtoidentifythereasonsfordatagapsanddeficiencies,andtosuggestways
toaddressthem.
AddressingDataGapsandDeficiencies
Beforeworkshopparticipantssplitintobreakoutgroups,DanielSalerno(Contractor&
GroundfishSectorManager)andHollyMcBride(NEFSC)deliveredajointtalkondata
gapsanddeficiencies.DanandHollycoveredfourareasofdatagapsanddeficienciesfrom
anindustryandagencyperspective:gearcharacteristics,spatialdata,environmentaldata,
anddiscards.Forgearcharacteristics,DanandHollypointedoutthatthereiscurrentlyno
waytodistinguishbetweendifferentgearconfigurationsusedtoprosecutethefishery
fromVTRs.Forexample,adiamondmeshcodendhasverydifferentselectivityproperties
thanasquaremeshcodendofequalmeshsize.Equally,thegearcode‘GNS’doesnot
distinguishbetweentiedowngillnetgearandstandupgillnetgear.Thepointwasmade
thatfillingdatagapsandaddressingdeficienciesshouldyieldimprovementsforboth
fishermenandmanagement.
PLENARYSESSION:CharacteristicsofanIdealDataSystem
ThisplenarysessionwasdesignedtoaddressGoals#3and#4oftheworkshopby
completingOutcome#4.
Facilitator:JonathonPeros
IndustryInterviews:IdealDataSystemSuggestions
JonathonPeros(GMRI)presentedarangeofidealdatasystemsthathadbeensuggested
duringthePhaseIindustryinterviews.Henotedthatthesuggestedsystemsincluded
electronicreporting,andrecappedseveralkeypointsmadebyCateO’KeefeonDay1.First,
intheindustryinterviews,dealersreportedcollectinginformationonpaperbefore
enteringitintoSAFIS.Dealersalsoreportedusingarangeofelectroniccollectiondevicesto
capturedatafromharvesters.Second,whilethemajorityofharvestersinterviewed
submittedpaperVTRs,81%ofthefishermeninterviewedindicatedthattheywouldbe
willingtosubmitthereportelectronicallyifchangestotheexistingsystemandtoolswere
made.AmodifiedversionofthedataflowmappresentedbyDanielSalernoonDay1was
usedtodepicttherangeofdatacollectionsthatinterviewrespondentsdeemedeither
redundantorunnecessary.Beforesharingthesuggestedsystemdesigns,the
characteristicsofanidealsystemwerereintroduced.Industrysuggestionswerebrokenout
intothreeparts:1)DataSystems,2)Hardware,Software,andCollections,3)DataAccess.
Eachsuggestionwasstatedintheindustry’sownwordsandaschematicofwhatthe
systemmightlooklikeandhowthedatawouldflowwaspresentedonthesameslide.
Duringtheplenarysession,inputwassoughtonthefeasibilityoftheindustrysuggested
datasystems.