Presentation is loading. Please wait.

Presentation is loading. Please wait.

David Sampson Professor of Fisheries OSU Hatfield Marine Science Center Coastal Oregon Marine Experiment Station.

Similar presentations


Presentation on theme: "David Sampson Professor of Fisheries OSU Hatfield Marine Science Center Coastal Oregon Marine Experiment Station."— Presentation transcript:

1 David Sampson Professor of Fisheries OSU Hatfield Marine Science Center Coastal Oregon Marine Experiment Station

2 With the European Commission’s Joint Research Center in Ispra, north of Milan. The JRC provides research based scientific advice to support a wide range of European Union policies. Institute for the Protection and Security of the Citizen. Applied research & development aimed at analyzing, modeling and developing new security applications. Maritime Affairs Unit. Shipping container traffic; vessel surveillance & port security; scientific support to fisheries. FISHREG Action. ~ 25 fisheries scientists. Two Years in Northern Italy

3 At the JRC while building a bioeconomic simulator, David stumbled upon some surprising behavior related to fishery selectivity. Resulting publications: Sampson, D.B. and Scott, R.D A spatial model for fishery age-selection at the population level. Canadian Journal of Fisheries & Aquatic Sciences 68: Scott, R.D. and Sampson, D.B The sensitivity of long-term yield targets to changes in fishery age- selectivity. Marine Policy 35: Sampson, D.B. and Scott, R.D An exploration of the shapes and stability of population-selection curves. Fish and Fisheries (available on line).

4 Talk Outline 1.What is fishery selectivity? 2.Issues related to gear-selectivity. 3.Selection curve shapes and stability. 4.A spatial model for fishery age- selectivity. 5.Conditions that generate domed population-selectivity. 6.Selectivity and MSY reference points.

5 Arona Part 1. What is fishery selectivity ?

6 ? What is Selectivity ? Fish abundance and catch-at-age Fishing mortality-at-age Young fish escape the gear or live elsewhere. Selection is F-at-age scaled so the maximum value is 100%.

7 Factors Influencing Selectivity: Gear selection.  Fish age / size / behavior affect which fish are caught and retained by any type of fishing gear. The mixture of fishing gears.  When there are multiple gear-types with differing gear- selection traits, the relative catches by each gear-type determine the population-level selectivity. Spatial locations of the fish and the fishing.  Fishing gear operates at a local scale and can only catch fish that are near the gear.  The population- level C age depends on the spatial distribution of fishing operations relative to the spatial distribution of the fish.

8 Selectivity Factors: Gear Selection

9 Selectivity Factors: Gear Mixtures Gear 1: 20%Gear 2: 80%Gear 1: 40%Gear 2: 60%Gear 1: 60%Gear 2: 40%Gear 1: 80%Gear 2: 20%

10 Selectivity Factors: Spatial Effects

11 Varese Part 2. Issues related to gear-selection.

12 Selection by the Fishing Gear ? Age-Based or Length-Based ? If selection is by age, then no effect on observed length-at-age. Not so if selection is by length. Length

13 ? What’s Wrong with these Graphs ? Assessment of Lingcod (Ophiodon elongatus) Are such changes in selection plausible?

14 Another Strange Selection Curve Assessment of Longspine Thornyhead (Sebastolobus altivelis)- 2005

15 Selectivity Propositions 1.Fish that are about the same age or size should have the same relative vulnerability (i.e., selection). 2.If estimates of selection by age (or by size) show abrupt changes between adjacent age-classes, there is probably something wrong with the model specifications.

16 Gelati Part 3. Selection Curve Shapes and Stability: An Empirical Analysis.

17 Selection Curve Shape and Stability Virtual Population Analysis (VPA).  Complete catch-at-age data to reconstruct abundance- at-age and F-at-age.  No assumptions about selectivity.  Widely used on both sides of the North Atlantic. F-at-age estimates from 15 published, peer- reviewed stock VPA assessments. F-at-age converted to smoothed selectivity curves estimates using GAMs. Test for Age, Year, and Age x Year effects.

18 Selection Shape and Stability (cont.) Increasing selectivity : American plaice on the Grand Bank Asymptotic selectivity : Atlantic cod on Georges Bank

19 Selection Shape and Stability (cont.) Domed selectivity : Atlantic herring (fall spawners) in the southern Gulf of St Lawrence Saddle selectivity : Atlantic herring in the Gulf of Maine and Georges Bank

20 Part 4. A spatial model for fishery age-selectivity.

21 M is the instantaneous rate of natural mortality. F i is the instantaneous rate of fishing mortality in region i. Coefficient s a is the gear selectivity for age- a fish. Coefficient P i,j is the proportion of fish that move into region i from region j at the end of each year. A Mathematical Model for Selectivity Abundance-at-age ( a ) by region ( i ): Survival of fish that stay in region i Survival of fish that migrate into region i

22 Selectivity Model (continued) F-at-age: Pop. selection-at-age: Abundance-at-age: N.B. This is a cohort (equilibrium) model.

23 Now we will explore an Excel version of the population- selectivity model.

24 Heuristic Explanation for the Dome Consider a stock in two regions, no movement between regions, same logistic gear selection curve in both regions. The population selection curve is the average of the two F age curves. The Region 1 curve (F = 0.4) dominates at young ages; the Region 2 curve (F = 0.1) dominates at old ages. Higher F  fewer old fish Lower F  more old fish

25 Part 5. Conditions that generate domed population-selectivity.

26 Conditions for Domed Selectivity Domed selection if S a+1 < S a. Under what conditions? The general conditions are difficult to discern because the equation for population selection is complicated. The gear-selection coefficients are embedded in the age- and region-specific total mortality coefficients, Z a,i = M + F i ∙ s a.

27 Domed Selectivity (continued) Condition for domed selection can be written Exponentiate and rearrange to get Direct substitution of the general equations for N a, N a+1 and N a+2 into this inequality produces a mess. But, useful results can be obtained from the simpler problem of no movement and constant gear-selection.

28 Domed Selectivity (continued) Consider the case of two regions. Decreasing selectivity implies

29 Domed Selectivity (continued) Similar reasoning leads to the solution for any number of regions. Population-selectivity (given no movement and constant gear-selection) will be decreasing if

30 Venizia Genoa Part 6. Selectivity & MSY reference points.

31 Selectivity and MSY Equilibrium yield is derived from standard equations for yield-per-recruit, spawning biomass-per-recruit, and a Beverton & Holt stock-recruit relationship. Yield-per-recruit: Spawning biomass-per-recruit: N.B. No plus-group. All fish are dead by age A +1.

32 Selectivity and MSY (continued) B&H stock-recruit relationship: Equilibrium Yield: At equilibrium each recruit exactly reproduces the spawning biomass of its parents.

33 Selectivity and MSY (continued) Fishery selection influences DB-SRA results. Maturity Age 50% M = 0.2; k = 0.15

34 Now we will explore an Excel version of the spatial population- selectivity model, extended to include the MSY calculation.

35 Near Como Sunrise from my bedroom Summary and Conclusions

36 Summary of the Lessons Learned VPA results indicate considerable variation in population-selection. We should not be surprised to find that population-selectivity varies through time. (Constant selection is unusual.) We should not be surprised to find that population-selectivity is dome-shaped. MSY and related biological reference points are functions of selectivity and also the spatial distribution of fishing.

37 Grazie per l’Attenzione


Download ppt "David Sampson Professor of Fisheries OSU Hatfield Marine Science Center Coastal Oregon Marine Experiment Station."

Similar presentations


Ads by Google