Wild & Hatchery Salmon Interactions Model Pete Rand & Bob Lessard
Hatchery Straying in Prince William Sound Brenner et al. 2012
Objectives Develop a tool to explore some of the hypotheses about wild/hatchery interactions Levels of hatchery production Spatial dynamics of straying Effect of fisheries Fitness
Mitigation of Hatchery/Wild interactions Catch all the hatchery fish so they can t stray Adjust the timing and placement of each gear type to avoid by-catch Produce less hatchery fish
Basic Model Description Model simulates life history and productivity of both wild and hatchery populations in a given region, and includes straying. Key metric is phos (proportion of hatchery-origin fish on spawning grounds). The model simulates fishery (up to two gear types in each district). Wild populations have the following intrinsic properties: Ricker a/b parameters (density-dependent population dynamics) Effect on productivity a function of exposure to hatchery salmon Harvest pressure defined by vulnerability/catchability Model can simulate limits to marine carrying capacity. Model simulates 30 years into the future, with variability.
Tracking Seven Natural Populations 3 (AWC #223) 2 (AWC #222) 1 (AWC #221) 4 (AWC #224) 5 (AWC #226) 6 (AWC #227) 7 (AWC #228)
Model Structure Natural Spawning Habitat Fishery Districts f(stray prob, distance) f(bev-holt S-R) W H W H Hatcheries f(halfmax) f(ricker S-R) Ocean W H f(halfmax)
Probablity of Straying Key Assumptions - Straying In model, number of hatchery strays is calculated from number of fish remaining after harvest and distance from release location. Wild fish do not stray. 5.00E-05 4.50E-05 Probability of Straying 4.00E-05 3.50E-05 3.00E-05 2.50E-05 2.00E-05 1.50E-05 1.00E-05 5.00E-06 0.00E+00 PWS SEAK 0 100 200 300 400 Distance (km)
Productivity Effect (Proportion of Maximum) Key Assumptions Fitness Effects Effect of hatchery fish on productivity of wild fish governed by HalfMax parameters (one for freshwater, one for marine). No intergenerational effects (annual reset ) 1 0.9 0.8 0.7 Weak W-H Interaction HalfMax=0.2 HalfMax=0.7 0.6 0.5 0.4 0.3 0.2 Strong W-H Interaction 0.1 0 0 0.2 0.4 0.6 0.8 1 phos
Recruits (fry) Recruits (fry) Millions Millions Wild & Hatchery Pink Salmon Fry 35 200 30 25 20 15 10 5 0 0 200000 400000 600000 800000 Escapement #1 #2 #3 #4 #5 #6 #7 180 160 140 120 100 80 60 40 20 0 Hatchery Fry Production 0 200000 400000 600000 800000 Escapement #1 #2 #3 #4 #5 #6 #7
Adult Returns Millions Key Assumptions Marine Carrying Capacity/Marine Survival Two different scenarios: 1) no limit (large K), or 2) ocean survival a function of density. Marine survival of wild and hatchery fish is equal. 20 18 16 14 No ocean limits 12 10 8 6 4 2 0 0 50 100 150 200 250 Fry Releases Millions B-H Model
Catch/Escapement Pink Salmon Data Prince William Sound 2010 Summary for 2010 PWS Fishing Season (ADF&G Data) Pink Salmon Numbers Districts Category 1 2 3 4 5 6 7 Total SGH 15,878,731 0 94,408 32,781 12,788 16,018,708 CCH 2,664 15,751,774 1,718,934 1,456,415 0 18,929,787 WNH 0 1,640,491 11,281,310 2,558,441 0 15,480,242 AFK 800 56,037 474,207 12,373,316 0 12,904,360 Wild Catch 504,244 468,530 683,702 557,439 3,197 2,217,112 Escapement (X2) 981,903 573,163 670,216 423,418 252,977 289,642 809,723 4,001,042 Harvest Totals 16,386,439 17,916,832 14,252,561 0 16,978,392 15,985 65,550,209 Wild % in Catch 0.03 0.03 0.05 0.03 0.20 0.03
Model Scenarios Ocean Productivity Strength of Hatchery Effect on Wild Productivity WEAK NO LIMIT 1 2 Hatchery Rel: 50-200% Wild Catchability:.1 -.3 LIMIT Hatchery Rel: 50-200% Wild Catchability:.1 -.3 STRONG 3 4 Hatchery Rel: 50-200% Wild Catchability:.1 -.3 Hatchery Rel: 50-200% Wild Catchability:.1 -.3
Eastern PWS Population (#7) no hatchery no fishery Policy Compliance Western PWS Population (#3) hatchery fishery 1. Weak W-H Interaction No Ocean Limits
Eastern PWS Population (#7) no hatchery no fishery Western PWS Population (#3) hatchery fishery 4. Strong W-H Interaction With Ocean Limits
Next Steps A work in progress! Receive some initial input from this meeting. Discuss further development, refinement and application to other systems. Complete a review draft to circulate later this year. Write up manuscript for journal submission later this year.
Thank you for your attention!
All Four Model Scenarios
Eastern PWS Population (#7) no hatchery no fishery Policy Compliance Western PWS Population (#3) hatchery fishery 1. Weak W-H Interaction No Ocean Limits
Eastern PWS Population (#7) no hatchery no fishery Western PWS Population (#3) hatchery fishery 2. Weak W-H Interaction With Ocean Limits
Eastern PWS Population (#7) no hatchery no fishery Western PWS Population (#3) hatchery fishery 3. Strong W-H Interaction No Ocean Limits
Eastern PWS Population (#7) no hatchery no fishery Western PWS Population (#3) hatchery fishery 4. Strong W-H Interaction With Ocean Limits
phos
Model Input - Ricker Parameters for Natural Populations # this contains the Ricker parameters for the natural populations (Fec=800 eggs per adult, egg2frysurv =.115 (Quinn) 1435,.129 for chum) # Ricker a parameters 120, 150, 95, 110, 135, 140, 180 # Ricker b parameters 300000,400000,250000,200000,400000,60000 0,500000 # The proportion of hatchery fish at which the natural population decays to 50% of it's maximum natural production 0.7
Model Input Beverton Holt Parameters # this contains the BH parameters for the natural populations ocean stage # BH a parameters for natural populations.1,.14,.08,.22,.18,.12,.09,.16 # BH b parameters for natural populations 15000000,20000000,12000000,10000000,200 00000,30000000,85000000,25000000 # BH a parameters for hatchery populations.08,.07,.09,.066 # BH b parameters for hatchery populations 15000000,20000000,12000000,10000000 # The proportion of hatchery spawners in natural escapement at which 50% decay in BH productivity has occurred 0.7
Proposal for Collaboration on Model Problem definition Develop and apply model as a tool for: Prince William Sound (pink) Southeast Alaska (chum) Aniva Bay, Sakhalin (pink) Hokkaido, Japan (chum) Use as a risk management tool explore alternative management actions to achieve management objectives (e.g. minimizing phos).
Management Levers in Model Change in hatchery releases (total #s, release locations). Fishery type, fishing effort, season (including selectivity/catchability of different gear)
Key Uncertainties to Evaluate Natural productivity dynamics in freshwater Ocean effect on survival/density-dependence Factors controlling straying, straying variability Selectivity of fishing Magnitude of fitness effect
Some key points Process is important! Transparency, objectivity, and inclusiveness are keys to success. It is one tool to aid in future decision making process.
Steps Continue developing model structure River spatial layer ( distance matrix ) District boundaries, fishery types Data needs Hatchery release numbers Stock-recruitment data or functions to represent natural populations Catch/effort and escapement data W/H ratio in fishery, on spawning grounds Willingness to collaborate on model and writing (draft reviews, co-authorship on report/manuscript)