# Presentation: 009419

## Spatial Management  in Fisheries

**Lessons from Empirical Bioeconomics**

**Martin D. Smith**
- Nicholas School of the Environment and Earth Sciences
- Duke University
- Prepared for
-  NMFS/NOAA Spatial Modeling Fisheries Economics Workshop
- October 22, 2002

## Four Key Phrases

- Spatial Closure
- Marine Reserve
- Marine Protected Area (MPA)
- No-take (harvest) Zones

## Key Questions

- Are marine reserves a good idea for fisheries management?
- If so, under what conditions?
- What are the implications of ignoring fisher behavior?

## Biological Justifications

- Rebuild overexploited areas
- Take advantage of dispersal mechanisms (e.g. sink/source patterns)
- Returns to scale in organism size and population density
- Preserve natural life cycle
- Hedge against stock collapse

## Economic Skepticism

- Reserves do not  necessarily address the fundamental driving force of overexploitation - open access
- Could be more costly than other forms of management
- Whatever happened to equimarginality?

## A Realistic Synthesis

- 	Biological arguments throw a wrench into our typical economic modeling efforts (e.g. convex production sets). Predicting the ultimate consequences of reserves requires empirical bioeconomic modeling.

## Catch Improvement Conjecture

- 	Marine reserves may generate aggregate harvest increases

## Preview of Findings

- Marine reserves are unlikely to increase harvest in the fishery described below
- Most biological modeling of reserves has resulted in overly optimistic predictions about their performance
- The magnitude and spatial distribution of fishing effort before and after reserve formation are key

## Empirical SettingNorthern California Red Sea Urchin Fishery

- Uni
- Daily diving trips
- Uniform harvest technology
- About 135 owner-operators
- Data combine logbooks and landings tickets (and weather buoy data) from 1988-97
- Marine reserves under consideration

## California Sea Urchins:Ideal for Spatial Management?

- The resource is “patchy” – has potential for sinks and sources
- Subpopulations connected via larval dispersal, sedentary adults
- Density-dependent reproduction
- Fecundity returns to scale (in organism size)
- CPUE has shown dramatic declines

## Structure of the Economic Model: 3 Decision Layers

- Daily discrete participation choice
- Fish or not

## Daily Participation

- Do Not Go

- Go

**Daily Participation**

- Diver i
- at time t

## Structure of the Economic Model:3 Decision Layers

- Daily discrete participation choice
- Fish or not
- Location choice
- If fish, choose a patch or fishing ground

## Daily Participation and Location Choice

- Do Not Go

- Go

- Patch 0

- Patch 1

- Patch 2

- Patch 3

- Patch 4

- Patch 5

- Patch 6

- Patch 7

- Patch 8

- Patch 9

- Patch 10

**Daily Participation and Location Choice**

- Diver i
- at time t

## Empirical Strategy

- Repeated Nested Logit for Participation and Location Choice Branches

## Participation and Location Results 

- Spatial pattern of exploitation is not uniform and is responsive to economic conditions
- Higher revenues and shorter travel distances increase fishing in a patch
- Higher revenues increase participation
- Participation also driven by institutional characteristics and weather conditions

## Structure of the Economic Model:3 Decision Layers

- Daily discrete participation choice
- Fish or not
- Location choice
- If fish, choose a patch or fishing ground
- Port switching
- Within Northern California
- Between Northern and Southern California

## Northern  California Ports

- 3

- 6

- °

- 3

- 7

- °

- 3

- 8

- °

- 3

- 9

- °

- 4

- 0

- °

- 4

- 1

- °

- 4

- 2

- °

- Ft. Bragg

- Albion

- Pt. Arena

- Bodega

- Half Moon Bay

- Crescent

- City

## Empirical Strategy

- SUR share models

## Port Switching Results

- Port shares respond to revenue differences across space
- Shares respond sluggishly; there are time lags involved
- The speed of adjustment differs across share models
- more immediate across ports within northern California
- slower for switches between northern and southern California

## The Sea Urchin Life Cycle

- Broadcast
- Spawn

- Larvae Transported
- in Ocean Currents

**Juveniles Settle**
**in Patches**

**Growth**

**Natural**
**Mortality**

**Fishing**
**Mortality**

**The Sea Urchin Life Cycle**

## Structure of the Biological Model

- Age- and size-structured metapopulation.
- Fecundity as a function of urchin size is increasing at an increasing rate
- Discrete subpopulations linked through larval dispersal
- The size limit combined with growth and allometric parameters convert number of organisms in each age/size class into patch-specific harvestable biomass

## The Bioeconomic Link

- Catch in each patch as a function of fishing effort and harvestable biomass
- Biomass dynamics evolve according to the metapopulation model and catch
- Resource abundance feeds back into expected revenues
- Spatially explicit fishing effort predictions feed back into catch in the next period

## Two Issues to Explore

- Best prediction for performance of a marine reserve
- Implications for ignoring behavioral responses
- ECON versus NOECON

## Economics of Marine Reserves with Macroeconomic Shocks

**Steady-State**

**Trips**

**Steady-State**

**Steady-State**

**Discounted***

**N. California**

**Per Diver**

**Partic**

**Harvest**

**Egg Production**

**Revenues**

**Divers**

**Per Year**

**Rate**

**(1,000 pounds)**

**(Billions)**

**($1000)**

- Discrete Choice Only

- No Closure

- 131

- 29.9

- 13%

- 830

- 1,316

- 17,440

- Close Patch 8

- 131

- 25.3

- 11%

- 752

- 1,441

- 15,074

- Port Choice and Discrete Choice

- No Closure

- 33

- 57.8

- 25%

- 638

- 1,627

- 13,400

- Close Patch 8

- 36

- 47.2

- 20%

- 576

- 1,692

- 11,660

- Port Choice and Discrete Choice  - 50% Decrease in S. Cal. Revenues

- No Closure

- 83

- 37.9

- 16%

- 802

- 1,399

- 16,846

- Close Patch 8

- 89

- 31.2

- 13%

- 728

- 1,495

- 14,683

- Discrete Choice Only

*Double prices and exogenous increase in participation rate*

- No Closure

- 131

- 107.1

- 46%

- 883

- 720

- 18,548

- Close Patch 8

- 131

- 96.5

- 41%

- 921

- 879

- 17,362

- Port Choice and Discrete Choice

*75% Decrease in S. Cal. Revenues, double prices, and exogenous increase in participation rate*

- No Closure

- 56

- 174.5

- 75%

- 972

- 796

- 20,402

- Close Patch 8

- 68

- 143.1

- 61%

- 952

- 910

- 18,865

- * Uses a 5% constant discount rate and assumes $1 per pound of sea urchin.

## Conclusions

- Both **magnitude** and the **spatial pattern** of fishing effort influence the performance of reserves
- Fixed effort assumption at high levels of exploitation on the approach path drives marine reserve optimism
- Assumption of uniformly distributed effort at high levels of exploitation also drives marine reserve optimism
- A realistic depiction of reserves that includes behavioral responses along the approach path to the steady-state leads to far more pessimism
- It is essential to distinguish between two types of externalities - excess fishing effort and an inefficient spatial allocation

## Discussion

- As a policy instrument for controlling fishing effort, a marine reserve is an extreme policy.

## Appendix A

- Statistical Models and Results

## Statistical Model of Partic. And Loc.

## Statistical Model of Port SwitchingAn SUR Partial Adjustment Approach

- Restrictions:

- _Estimating Equation_

## South/North Switching OLS Model of Port Shares 

**South/North Switching OLS Model of Port Shares**

## The Metapopulation Model

*Size *

*j,a*

-  =

*e *

*j*

-  =

*A *

*j,a*

-          where

** **

** **

** **

** **

## The Bioeconomic Link

## Slide 38

## Appendix B

- Biological Parameter Values

## Parameter Values for Biological ModelFrom Botsford et al. (1993, 1994, 1999); Morgan (1997) and Morgan et al. (2000)

## Appendix C

- Details on the economic and biological literature

## Summary of Key Biological Articles

**Summary of Key Biological Articles**

**Article**

**Year**

**Citation**

**Count**

**Modeling or**

**Empirical**

**Pre- and Post-Reserve**

**Effort Assumptions**

- Dugan and Davis

- 1993

- 74

- Discussion

- none

- Polacheck

- 1990

- 49

- Modeling

- fixed total effort and uniform

- redistribution

- Carr and Reed

- 1993

- 48

- Modeling

- constant harvest - no behavior

- DeMartini

- 1993

- 45

- Modeling

- fixed total effort and uniform

- redistribution

- Lauck et al.

- 1998

- 41

- Modeling

- random harvest fraction.

- Russ and Alcala

- 1996

- 39

- Empirical

- N/A

- Quinn et al.

- 1993

- 38

- Modeling

- fixed total effort and uniform

- redistribution, fishers give up at

- very low densities

- Man et al.

- 1995

- 34

- Modeling

- fixed total effort and uniform

- redistribution

- Bohnsack

- 1993

- 30

- Discussion

- N/A

- Hastings and Botsford

- 1999

- 14

- Modeling

- fixed harvest fraction

## Economics Articles on Reserves

- Holland and Brazee (1996)
- Brown and Roughgarden (1997)
- Hanesson (1998)
- Sanchirico and Wilen (1999, 2001)
- Wilen, Smith, Lockwood and Botsford (2002)
- Smith (2002a, 2002b)
- Smith and Wilen (2002a, 2002b)