2025 Bangor University Bycatch in Welsh Static Net Fisheries Observer Data
Monitoring bycatch in Welsh static net fisheries through onboard observer data collection
2023 - 2025 Bycatch in static nets Wales
This Fisheries Industry Science Partnership project was a collaboration between Bangor University, Natural Resources Wales and the Welsh Fisherman's Association, to assess bycatch in static net fisheries in Wales from 2023 - 2025. An onboard observer program was conducted during netting operations on small scale commercial vessels and during commercial shore netting in Welsh inshore waters. Observers collected data on species catch (target and bycatch) with associated length, weight, vitality and sex data (when possible), fishing effort (duration of fishing activities), GPS locations of fishing activities, and gear characteristics (gear type, net length, mesh size). For data collection reasons only relevant available metadata is published.
dataset
BU_FISP_BSN
eng
biota
economy
oceans
revision
2025-03-06
revision
2025-03-06
revision
2021-09-28
revision
2021-09-28
-3.197021484375
-3.109130859375
51.641672200851
51.395564180331
creation
2021-01-06
creation
2021-01-06
Irish Sea
creation
2021-01-06
VIIa
creation
2021-01-06
VIIg
0
43
urn:ogc:def:crs:EPSG::5701
2023-10-13
2025-01-21
publication
2025-03-06
revision
2025-01-21
notPlanned
Observer data was collected as part of a FISP funded research project on bycatch in Welsh static net fisheries. Additional fisher self-reported data were used to supplement the observer data and enhance coverage. An ethical review process was performed prior to data collection and all fishers involved were MCA certified. Data were collected on 116 days from 13th October 2023 until 21st January 2025. A total of 7 commercial fishing vessels participated on a voluntary basis in both the observer programme and in providing self-reported data. Data collection was conducted in North Wales (ICES subdivision 7a) and South Wales (ICES subdivision 7g). Bycatch of all species including marine mammals, seabirds, elasmobranchs and diadromous fish were recorded across inshore areas of Wales where small commercial net fisheries operate. Count data was collected on all species captured, including target catch and bycatch. Catch data were recorded for each set, individuals were recorded at species level and biometric measurements (length and weight) were taken where possible, as well as the condition (dead or alive) and outcome (retained or discarded) recorded for each individual Species were weighed using motion compensating scales or digital scales and a sling for larger species. Individual length measurements were recorded using either a measuring board or a tape measure (depending on the size of the individual). Measurements were recorded differently for each taxonomic group: marine mammals: total length; seabirds: wingspan (left wingtip to right wingtip) and total length (bill tip to tail feather tip); elasmobranchs: total length for sharks or disc width for rays/skates; teleost: total length; crustaceans: carapace width for crabs or carapace length for lobsters. Sex of the animal was identified when possible. Metadata (site, haul and set dates and times, vessel characteristics, soak time, net characteristics etc.) were recorded for every net hauled even in the absence of target catch or bycatch to account for all effort. A Garmin handheld GPS was used to collect vessel tracks and gather coordinates when hauling for the start and end of fishing nets, with associated time data. GPS data was used to create maps of observer effort and fishing effort in QGIS. Catch data was used to calculate estimates of bycatch per unit effort (BPUE) across different taxonomic groups, species and net types. All data were manipulated and prepared for analysis in R Studio. Calculations of mean BPUE rates (and associated bootstrapped 95%CI’s), analysis of catch composition, outcome and condition proportions were all conducted in R. Generalised linear mixed models were conducted using the glmmTMB package to model BPUE rates against various predictor variables. Multivariate analysis comparing patterns in species composition across factors (net type and season) and identifying environmental variables and particular bycatch species which best explain the variation in species composition were conducted in PRIMER 7.
publication
2010-12-08
true
The metadata complies with MEDIN Discovery Metadata Standard 3.1.2.
publication
2011-01-28
true
The metadata conforms with the MEDIN data guideline for static net, pot and trap data.
Restricted access and use. No conditions apply, the data cannot be used by the public.
Metadata contact
Bangor University School of Ocean Sciences
owner
Metadata contact
Bangor University School of Ocean Sciences
custodian
Metadata contact
Bangor University School of Ocean Sciences
originator
Metadata contact
Bangor University School of Ocean Sciences
distributor
Bangor University School of Ocean Sciences
pointOfContact
2025-03-06