Globalizing localization of data-limited approaches for sustainable resource management

Transcription

1 NWFSC, Seattle Globalizing localization of data-limited approaches for sustainable resource management Jason M. Cope Collaborators: Jim Berkson, Jim Thorson, Chantel Wetzel, SNAP working group on Data-limited Fisheries Management 2015 Lowell Wakefield Symposium: Tools and Strategies for Assessment and Management of Data-Limited Fish Stocks

2 Common terms Globalization: Large scale collaboration to develop data-limited methods Localization: Adaptation to and respect for local conditions/needs Sustainable use the objective? See Natalie Dowling s talk Friday morning! See Kendra Karr s talk after that! U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 2

3 Common terms Data -limited methods Data availability Resources Quantity Quality Coverage Temporal Spatial Time Funding Analysts # stocks Management needs U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 3

4 Common terms Data -limited methods Data availability Resources Quantity Quality Coverage Temporal Spatial Uncertainty Time Funding Analysts # stocks Management needs U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 4

5 Common terms Data -limited methods Data availability Resources Quantity Quality Coverage Temporal Spatial Uncertainty Time Funding Analysts # stocks Management needs Varies locally U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 5

6 Common terms Data -limited methods Data availability Resources Quantity Quality Coverage Temporal Spatial Uncertainty Time Funding Analysts # stocks Management needs Globalization Varies locally Localization U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 6

7 Globalization: Method development Creativity/Research Performance Improvement Thorson et al U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 7

8 Globalization: Basic Research Removals Abundance indices* Size & Age compositions Scale Status Productivity M A&G L-W Sel Mat. h U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 8

9 Globalization: Method development Life-history based Vulnerability/Risk Catch-only Length-based Model based MPA-based U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 9

10 Long-term yield Globalization: Simulation testing Avg. C DCAC DB-SRA S.A. Performance relative to operating model Based on performance metrics; can be global or local Yield, risk of overfishing, stock status Avg. Biomass / B MSY Findings: No one method wins. Data matters! Performance sensitive to stock status, life history, key assumptions. Probability of overfishing Carruthers et al. 2014, Fish. Res. U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 10

11 Globalization: BASI testing Performance relative to benchmark assessment ( best available science ) Also uses performance metrics. Used when aspects cannot be simulated (e.g. expert opinion) or want direct comps. to current approaches Promotes common framework development & testing. Can learn about both datalimited & rich approaches. Cope et al U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 11

12 Index? Globalization: Using a common framework Stock status prior? Y N Y N NA XSSS NA SSS SS SRA CC-SRA Borel s Paradox Y N Y N comps? Bio. SSS: Simple Stock Synthesis CC-SRA: Catch curve stock reduction analysis XSSS: Extended Stock Synthesis SRA: Stock reduction analysis SS: Stock Synthesis (normal application) U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 12

13 Globalization: Improving inputs Thorson et al SB MSY /SB 0 Zhou et al F MSY /M Hamel 2015 Cope et al M U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 13

14 Localization: Expert elicitation Anna Chrysafi, U. Helsinki U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 14

15 Localization: Expert elicitation Accessible Easy submission Expert calibration Anna Chrysafi, U. Helsinki U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 15

16 Localization: Expert elicitation Natural mortality Growth Selectivity Anna Chrysafi, U. Helsinki U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 16

17 Localization: Accessibility & Specificity Method availability R resources GitHub Local application Management (e.g., harvest) control rules Broad application Multiple models Application to data-rich assessments Feedback to globalization U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 17

18 Localization: Accessibility R Cross platform open source statistical software User-friendly graphical interface Sharing code via packages Code supports replication, standardization Don t have to have constant internet connection U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 18

19 Localization: Toolboxes Anyone with R can get it. Allows users to Add new stock types Add new methods Use OM to test new methods against other methods Can() and Cant() functions tells method availability Other packages (Ex: U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 19

20 Localization: Accessibility GitHub Version control software Easily share code & examples U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 20

21 Localization: Application Grouping methods Input/Data types Static vs dynamic Baseline vs nonbaseline Effort vs catch (management units) Method organization Increases accessibility Direct data-collection planning U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 21

22 Localization: Harvest control rules (HCRs) Decision rule that modifies catch. Can modify other measures. Makes methods operational Uses references points Incorporates uncertainty Oft needed connection between D-L method and management Dowling et al May improve poorly performing D-L method U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 22

23 Localization: Broad applications Multiple application Conduct DL methods EVEN when complex models available Broad application feedbacks to globalization U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 23

24 Globilization-localization interface Localization feedback Improve inputs Performance testing Method sharing Toolboxes (e.g. DLM) D-L methods Decision rules (e.g., HCRs) Application U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 24

25 Summary Data-limited approaches are Rapidly developing Showing promising results Increasingly & sorely needed DLM Globilization requires Creativity to develop methods Performance testing Continued development via input improvement DLM Localization requires Method availability Method organization Method application (via management control rules) Broad application = Localized knowledge transfer to global users U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 25

26 Recommendations Take DLM tools across the world Computers more portable and affordable Batteries are better Resource sharing quick & easy When applying DL models: Apply multiple methods Apply to data-rich models Make your DL method(s) available Make your results available U.S. Department of Commerce National Oceanic and Atmospheric Administration NOAA Fisheries Page 26