globalizing localization of data-limited approaches for...

Globalizing localization of data-limited approaches for sustainable resource

management NWFSC,

Seattle

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

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 |

Common terms


“Data”-limited methods

Data availability Resources

• Quantity

• Quality

• Coverage

• Temporal

• Spatial

• Time

• Funding

• Analysts

• # stocks

• Management

needs

Common terms




• Quantity

• Quality

• Coverage

• Temporal

• Spatial

• Time

• Funding

• Analysts

• # stocks

• Management

needs

Uncertainty

Common terms




• Quantity

• Quality

• Coverage

• Temporal

• Spatial

• Time

• Funding

• Analysts

• # stocks

• Management

needs

Uncertainty

Varies locally

Common terms




• Quantity

• Quality

• Coverage

• Temporal

• Spatial

• Time

• Funding

• Analysts

• # stocks

• Management

needs

Varies locally

Uncertainty

Localization Globalization


Globalization: Method development

• Creativity/Research

• Performance

• Improvement

Thorson et al. 2012

Scale Status Productivity

Removals Abundance

indices* Size & Age

compositions

M h A&G Mat. L-W Sel

Globalization: Basic Research



Globalization: Method development

• Life-history based

• Vulnerability/Risk

• Catch-only

• Length-based

• Model based

• MPA-based

• Performance relative to

operating model

• Based on performance

metrics; can be global

or local

• Yield, risk of overfishing,

stock status

• Findings:

• No one method “wins”.

• Data matters!

• Performance sensitive to

stock status, life history,

key assumptions.

Long-t

erm

yie

ld

Avg. B

iom

ass

/ B

MSY

DCAC DB-SRA S.A. Avg. C

Probability of overfishing Carruthers et al. 2014, Fish. Res.

Globalization: Simulation testing


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 data-

limited & “rich” approaches.

Cope et al. 2015

Globalization: Using a common framework


NA SS

XSSS SRA

NA CC-SRA

SSS Borel’s Paradox Index?

Y

N

Stock status prior? B

io.

com

ps?

Y

N

Y

N

Y N

SSS: Simple Stock Synthesis

CC-SRA: Catch curve stock reduction analysis

XSSS: Extended Stock Synthesis

SRA: Stock reduction analysis

SS: Stock Synthesis (normal application)

Globalization: Improving inputs

Cope et al. 2015


M

0.0 0.2 0.4 0.6 0.8 1.0

0.0

0.5

1.0

1.5

Hamel 2015

FMSY/M

Zhou et al. 2012 Thorson et al. 2012

SBMSY/SB0


Localization: Expert elicitation

Anna Chrysafi, U. Helsinki




• Accessible

• Easy submission

• Expert calibration




• Natural mortality

• Growth

• Selectivity


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


Localization: Accessibility

• 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

R

http://r-pkgs.had.co.nz/

http://cran.r-project.org/

http://www.rstudio.com/


Localization: Toolboxes

• http://cran.r-project.org/web/packages/DLMtool/index.html

• 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: http://www.flr-project.org/)

http://cran.r-project.org/web/packages/DLMtool/index.html




Localization: Accessibility

GitHub • Version control software

• Easily share code & examples


Localization: Application

• Input/Data types

• Static vs dynamic

• Baseline vs non-

baseline

• Effort vs catch

(management units)

Grouping methods

• Increases accessibility

• Direct data-collection

planning

Method organization

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

• May improve poorly performing

D-L method Dowling et al. 2008


Localization: Broad applications

• Multiple application

• Conduct DL methods

EVEN when complex

models available

• Broad application

feedbacks to

globalization

Globilization-localization interface


D-L

methods

Improve

inputs

Performance

testing

Application

Decision rules

(e.g., HCRs) • Method sharing

• Toolboxes (e.g. DLM)

“Localization f

eedback”


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

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


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