1. Fisheries 101: Modeling and assessments to achieve sustainability Training Module July 2013

2. Outline Small Scale Unassessed Fisheries Fishery assessments – – How they can be used – – What are we trying to assess and why? Projection Modeling Overview – – What are projection models and why should we use them? – – Inputs and outputs 2

3. The problem is most acute in small scale, coastal fisheries Global Fisheries Costello et al., 2012, Science 3

4. Small Scale Unassessed Fisheries Small scale, but collectively responsible for 40% of global catch Account for 90% of all fishermen Millions of jobs in fish processing, marketing, etc. Many appear to be overfished and not producing as much food/money as possible So what do we do? 4

5. Fishery Dependent Information (logbook data, discards, etc.) Landings by Gear Type 1. commercial 2. recreational Fishery Independent Surveys (e.g., trawl surveys) Life History Information growth, maturity, etc. Stock Assessment (statistical model) Biomass + Fishing Mortality Management Decision Catch Demographic Data 1. age composition 2. length composition Stock Assessments: The Foundation of Fisheries Management Courtesy of S. Ralston 5

6. Fishery Dependent Information (logbook data, discards, etc.) Landings by Gear Type 1. commercial 2. recreational Fishery Independent Surveys (e.g., trawl surveys) Life History Information growth, maturity, etc. Stock Assessment (statistical model) Biomass + Fishing Mortality Management Decision Catch Demographic Data 1. age composition 2. length composition Stock Assessments: The Foundation of Fisheries Management > 80% of fisheries are unassessed Courtesy of S. Ralston 6

7. Data Poor Assessments Methods are less costly and data intensive than traditional assessments Goal of the assessment is to make management decisions using only readily available information A variety of approaches – we will highlight three of them 7

8. Length Young Prime Old Length Frequency Wilson et al. 2010 1. Marine Reserve-Based Decision Tree This tool examines the length frequency and density of scientifically sampled fish inside and outside of marine reserves as well as trends in the catch The model can then be used to adjust last years total allowable catch in order to achieve a target reference point 8

9. Compare CPUE of prime sized fish inside and outside of reserves Level 1 Compare CPUE and proportion of old fish in catch to SPR40 levels Level 3 Evaluate CPUE of young fish over past 5 years Level 4 Compare CPUE of young fish to SPR50 levels 1. Marine Reserve-Based Decision Tree Output: Adjustment to Total Allowable Catch (TAC) Evaluate CPUE of prime sized fish in fished area over previous 3-5 years rising stable falling Level 2 9

10. Spawning Potential Ratio Fishing Mortality 2. Spawning Potential Ratio (SPR) methods SPR = A measure of current egg production relative to unfished levels Lightly Fished Spawning = 50% of unfished levels Spawning = 10% of unfished levels Heavily Fished No Fishing target 10

11. 3. Catch Curve Analysis: using No-take Zones as Reference Areas Total Mortality (Z) = Natural (M) + Fishing (F) Mortality F = Z - M Reserve Non-Reserve M = natural mortality Z = M + F Wilson et al. in review 11

12. Outline Small Scale Unassessed Fisheries Fishery assessments How they can be used What are we trying to assess and why? Projection Modeling Overview What are projection models and why should we use them? Inputs and outputs 12

13. What is a “projection model”? A way to combine essential elements of a system to answer specific questions about management outcomes Critical concepts Level of detail required depends on question General principles don’t answer specific questions Assumptions must be clear, can be challenged No model is exact to reality 13

14. Why use projection models? Models can include more information than any individual can consider Models can include more information than any individual can consider Helps to organize thinking Helps to organize thinking Often reveal counterintuitive results Often reveal counterintuitive results Models move from simple to complex based on the type of question you are addressing Models move from simple to complex based on the type of question you are addressing 14

15. Population Dynamics One species Few parameters One area Bioeconomic simulation models: Example of a simple simulation model Courtesy of S. Valencia and J. WilsonFish Icon courtesy of L. Allen 15

16. Population Dynamics Age Recruitment Growth Movement (larval and adult) Mortality (natural and fishing) Bioeconomic simulation modeling: Moving toward more complex models Courtesy of S. Valencia and J. WilsonFish Icon courtesy of L. Allen 16

17. Incorporate into the model: Fishing effort – fleet dynamics Habitat quality Adult emigration Larval spillover Bioeconomic simulation modeling Moving toward more complex models (cont.) Courtesy of S. Valencia and J. WilsonFish Icon courtesy of L. Allen 17

18. Complex Model inputs Combines Habitat (where are productive reefs) Life history (reproduction, growth, migration) Human behavior (where/how much they fish) Community objectives (profit, sustainability, ecological outcomes, local employment) Used for: Scenario evaluation (what happens if …?) Optimization (what’s the best place for ….?) 18

19. Example Outcomes Decision Table- Compared with long term status quo % Change Yield % Change BiomassP<0.1B0P>0.4B0 Scenario 1 2014.37.44 Scenario 2 15 17.25.63 Scenario 3 10 12.14.79 Scenario 4 12 22.28.72 Scenario 5 18 4.21.68 Biomass Profits Time 19

20. Summary Stock assessments are costly and data intensive Data poor stock assessments and projection models are ways to make predictions using basic/incomplete/imperfect data No tool is perfect, but if you manage adaptively you can reconsider decisions over time 20

21. Thank you!