Using U i V Vessell Monitoring M it i System (VMS) Data to E ti Estimate t Spatial S ti l Effort Eff t ffor Unobserved Vessels in the B i Bering Sea S Pollock P ll k Fi Fishery h Alan Haynie, NOAA Fisheries Alaska Fisheries Science Center P ti kS Patrick Sullivan, lli C Cornell ll U University i it Overview • VMS and Observer coverage in the Bering Sea pollock fi h fishery • Methodology • Results R l • Conclusions 2 The Bering Sea pollock fishery is conducted by y United States vessels in the B i Bering Sea S 3 4 Pollock Fishery y •1 – 1.5 million MT/ year •Pollock make up approximately 30 percent of the fish and shellfish landed in the US •75% 5% o of Alaska as a g groundfish ou d s fishery s ey in recent years 5 VMS Coverage in Bering Sea Fisheries • All vessels that conduct directed fishing for pollock, Pacific cod, and Atka mackerel in the Bering Sea and Aleutian Islands are required to have VMS (beginning in 2003) • VMS system transmits the following information 2-3 times/hour throughout the season • Data used here are data for 2004 (approximately 100,000 observations used in this analysis) — Vessel identifier — Location — Bearing — Speed 6 Observer Program g Data • On On-board board observers required for 100% of days at sea for vessels >124 feet (~ 38 meters); • On-board observers required for 30% of days at sea for vessels 60-124 feet (18 – 38 meters) • More than 80% of catch is observed 7 Salmon Bycatch Spatial Variation Source: Sea State, Inc. 8 VMS Research Question Can we use th C the VMS d data t ffrom unobserved trips p to better estimate spatial effort and bycatch in the pollock fishery? 9 Generalized Additive Model (Logit Link) ⎧ π ⎫ l ⎨ log ⎬ = α + s ( St ) + s ( St −1 ) + s (ΔB{t − 2,t + 2} ) ⎩1 − π ⎭ where π = Probability of fishing α = Intercept s ( St ) = Smooth function of speed at time t s ( St −1 ) = Smooth h function f i off speedd at time i t −1 s (ΔB{t − 2,t + 2} ) = Smooth function of change in bearing over times t − 2 to t + 2 10 0.2 0.4 Proba ability of fishing 0.4 0.2 0.0 0 0.0 0 Proba ability of fishing 0.6 0.6 0.8 Probability of fishing relative to speed 0 2 4 6 8 Speed at time t 10 12 14 0 2 4 6 8 10 12 14 Speed at time t-1 11 0.4 0.3 0 0.2 0.1 0..0 Probab bility of fishing 0.5 0.6 Probability of fishing relative to mean change in bearing 0 50 100 Mean change in bearing 150 12 Receiver-Operator characteristic (ROC) Curve 0.2 0.4 0.6 •Specificity Prob(Pred=0|Obs=0) Prob(Pred=0|Obs=0). CV Vessels ( 0.94 ) 0.0 senssitivity 0.8 1.0 •Sensitivity Prob(Pred=1|Obs=1)) relative to the specificity of the prediction 0.0 0.1 0.2 0.3 0.4 1 - specificity 13 Map p of Statistical Areas 14 Preliminary Results for Full coverage vessels: VMS vs. Observed % effort by area and squared difference Area VMS100 Observed100 DifSq100 1 16.9 17.9 1.0 2 10 8 10.8 10 1 10.1 05 0.5 3 2.8 2.6 0.0 4 5.9 5.5 0.2 5 4.0 4.5 0.3 6 4.9 5.0 0.0 7 7.3 8.4 1.3 8 5.5 6.1 0.4 9 13 1.3 15 1.5 00 0.0 10 3.5 3.6 0.0 15 Preliminary Results for 30% Coverage Vessels: VMS vs. Observed % effort by area and squared difference Area VMS30 Observed30 DifSq30 1 18.0 21.1 9.7 2 14.3 20.8 42.6 3 7.7 10.4 7.5 4 5.1 5.3 0.0 5 3.9 3.2 0.5 6 3.7 4.2 0.3 7 3.7 4.1 0.2 8 3.4 2.7 0.6 9 2.5 1.6 0.9 10 2.5 1.8 0.6 11 2.4 2.5 0.0 12 2.2 0.0 4.7 13 22 2.2 19 1.9 01 0.1 14 1.6 0.8 0.7 15 1.6 0.0 2.4 16 Conclusions & Next Steps p • Current algorithm allows accurate prediction of Areas fished for fully observed vessels vessels. • Preliminary analysis indicates that there is a significant i ifi diff difference iin spatial i l effort ff ffor observed b d and d unobserved fishing for partially observed vessels. • Current work will estimate the spatial variation in effort between seasons and years; cross-validation is being conducted conducted. • Methods can be used with VMS data in other locations to accurately estimate spatial effort 17 Acknowledgements • Funding support for Dr. Sullivan from NOAA Fisheries Science and Technology and previous support from NOAA Fisheries AK Region • VMS data provided by NOAA Fisheries Enforcement • Brilliant symposium organizers for choosing to have this meeting in Rio • Muito obrigado! 18
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