Wild & Hatchery Salmon Interactions Model. Pete Rand & Bob Lessard
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1 Wild & Hatchery Salmon Interactions Model Pete Rand & Bob Lessard
2 Hatchery Straying in Prince William Sound Brenner et al. 2012
3 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
4 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
5 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.
6 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)
7 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)
8 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 E-05 Probability of Straying 4.00E E E E E E E E E+00 PWS SEAK Distance (km)
9 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 ) Weak W-H Interaction HalfMax=0.2 HalfMax= Strong W-H Interaction phos
10 Recruits (fry) Recruits (fry) Millions Millions Wild & Hatchery Pink Salmon Fry Escapement #1 #2 #3 #4 #5 #6 # Hatchery Fry Production Escapement #1 #2 #3 #4 #5 #6 #7
11 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 No ocean limits Fry Releases Millions B-H Model
12 Catch/Escapement Pink Salmon Data Prince William Sound 2010 Summary for 2010 PWS Fishing Season (ADF&G Data) Pink Salmon Numbers Districts Category Total SGH 15,878, ,408 32,781 12,788 16,018,708 CCH 2,664 15,751,774 1,718,934 1,456, ,929,787 WNH 0 1,640,491 11,281,310 2,558, ,480,242 AFK , ,207 12,373, ,904,360 Wild Catch 504, , , ,439 3,197 2,217,112 Escapement (X2) 981, , , , , , ,723 4,001,042 Harvest Totals 16,386,439 17,916,832 14,252, ,978,392 15,985 65,550,209 Wild % in Catch
13 Model Scenarios Ocean Productivity Strength of Hatchery Effect on Wild Productivity WEAK NO LIMIT 1 2 Hatchery Rel: % Wild Catchability: LIMIT Hatchery Rel: % Wild Catchability: STRONG 3 4 Hatchery Rel: % Wild Catchability: Hatchery Rel: % Wild Catchability:.1 -.3
14 Eastern PWS Population (#7) no hatchery no fishery Policy Compliance Western PWS Population (#3) hatchery fishery 1. Weak W-H Interaction No Ocean Limits
15 Eastern PWS Population (#7) no hatchery no fishery Western PWS Population (#3) hatchery fishery 4. Strong W-H Interaction With Ocean Limits
16 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.
17 Thank you for your attention!
18
19 All Four Model Scenarios
20 Eastern PWS Population (#7) no hatchery no fishery Policy Compliance Western PWS Population (#3) hatchery fishery 1. Weak W-H Interaction No Ocean Limits
21 Eastern PWS Population (#7) no hatchery no fishery Western PWS Population (#3) hatchery fishery 2. Weak W-H Interaction With Ocean Limits
22 Eastern PWS Population (#7) no hatchery no fishery Western PWS Population (#3) hatchery fishery 3. Strong W-H Interaction No Ocean Limits
23 Eastern PWS Population (#7) no hatchery no fishery Western PWS Population (#3) hatchery fishery 4. Strong W-H Interaction With Ocean Limits
24 phos
25 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 ,400000,250000,200000,400000, , # The proportion of hatchery fish at which the natural population decays to 50% of it's maximum natural production 0.7
26 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 , , , , , , , # BH a parameters for hatchery populations.08,.07,.09,.066 # BH b parameters for hatchery populations , , , # The proportion of hatchery spawners in natural escapement at which 50% decay in BH productivity has occurred 0.7
27 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).
28 Management Levers in Model Change in hatchery releases (total #s, release locations). Fishery type, fishing effort, season (including selectivity/catchability of different gear)
29 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
30 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.
31 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)
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