ECONOMIC AND ECOLOGICAL ANALYSIS OF THE CAPE HATTERAS AREA
CLOSURE IN THE ATLANTIC BLUEFIN TUNA FISHERY
by
Megan Ware
Dr. Pat Halpin, Advisor
Dr. Andre Boustany, Advisor
April 21, 2015
Masters project submitted in partial fulfillment of the requirements for the Master of
Environmental Management degree in the Nicholas School of the Environment of Duke
University
EXECUTIVE SUMMARY
Fisheries are a common property resource and, as a result, are often overexploited
because short-term economic gains are considered over long-term societal costs. An archetypical
example of this depletion is in the Atlantic bluefin tuna fishery.
Atlantic bluefin tuna are a highly migratory species whose quality meat and large size
make them a valuable economic resource. In the 1960’s, the catch of Atlantic bluefin tuna
increased dramatically, with 30,000 tons caught in the Eastern Atlantic and 18,000 tons caught in
the Western Atlantic. This rapid growth in the fishery was made possible by improvements in
fishing methodology and technology as well as increased demand from the Japanese sushi
market. However, this high level of fishing was unsustainable and, by 1980, populations
declined.
In response to these depleted populations, quotas were established for the stock. In the
US, the current annual Atlantic bluefin tuna quota is 1018 tons and is apportioned among
different gear types. However, enforcement of this quota is difficult. The longline sector is
continually exceeding its allotment and the number of dead discards is often greater than the
allocation of catch.
Amendment 7 to the 2006 Consolidated Atlantic Highly Migratory Species Fishery
Management Plan represents an effort by NOAA Fisheries to address the management
deficiencies in the Atlantic bluefin tuna fishery. One aspect of the Amendment is to create a
seasonal area closure in the longline fishery off the coast of Cape Hatteras, NC. This
management measure is expected to produce ecological benefits for the species but also
economic costs for fishermen. Therefore, the objective of this Master’s Project was to: 1)
identify the ecological impact of the closure on bluefin tuna and associated species including
yellowfin tuna, bigeye tuna, and swordfish; 2) model the redistribution of displaced fishing
effort; and 3) understand if the area closure is in an effective and equitable location.
Data on the Atlantic bluefin tuna longline fishery were obtained from Dr. Andre
Boustany. Information in the dataset included the date, location, number of sets, number of
hooks, and the number of fish caught per species. Data were imported into ArcGIS and catch per
unit effort (CPUE) was calculated by dividing the number of interactions by the number of
hooks. The redistribution of displaced fishing effort was mapped by assuming fishermen want to
maximize returns and minimize costs. Expected revenue for each set was calculated by
multiplying the monthly average price per species by the number of individuals caught. The
travel costs from four major ports in North Carolina (Hatteras, Morehead City, Ocracoke, and
Wanchese) were calculated by plotting the Euclidean distance and multiplying this by $1.02, a
pelagic longline travel cost estimate from Strand (2004). Expected profit was then calculated by
subtracting travel costs from revenue. The ecological benefits of the area closure were
determined by calculating the number of bluefin tuna, yellowfin tuna, bigeye tuna, and swordfish
impacted by the area closure and comparing this to the proportion and magnitude of catch in the
location where effort is expected to redistribute.
Results showed that while the area closure is in a location with a high number of bluefin
tuna interactions, it does not have a high CPUE. Instead, areas of high CPUE migrate up and
down the coast mimicking the migration patterns of the species. This means the area closure does
not maximize ecological benefits and the burden of conservation is not equally distributed
among fishermen.
Based on profit calculations, displaced fishermen are expected to redistribute their fishing
effort south to waters off of the North Carolina/South Carolina border. This southern region was
1
predicted for all fishermen regardless of their port of origin. Profit in this southern region was
slightly higher than in the area closure; however, the standard deviation of revenue was also
higher. Regression analysis confirmed fishermen prefer areas with both large and stable returns.
Moderate ecological benefits in the bluefin tuna pelagic longline fishery are expected as a
result of the area closure. The annual number of bluefin tuna protected by the area closure is
predicted to be roughly 600 individuals. While this represents less than 1% of total yields for the
species, it accounts for 74% of dead discards. As a result, the area closure will move the fishery
towards quota compliance but it will not ensure complete observance will quota regulations.
Furthermore, the area closure is not expected to rebuild stocks of bluefin tuna.
In total, the area closure is not expected to ensure quota compliance. The short-coming of
this initiative is in large part due to the fact that a stationary area closure does not account for the
complexities associated with managing a highly migratory species. Instead, dynamic
management measures should be considered as a way to mirror the broad-scale movement of the
species. While this type of management requires enhanced levels of education and enforcement,
it would mean protection is provided to the stock at the time and location it is most needed,
ensuring the largest ecological benefit to the species.
2
TABLE OF CONTENTS
Executive Summary……………………………………………………………………………...1
List of Acronyms ………………………………………………………………………………...4
Introduction………………………………………………………………………………………5
I.
II.
III.
IV.
V.
The Atlantic Bluefin Tuna Fishery……………………………………………………5
Current Management of the Fishery…………………………………………………..6
Problems with the Recovery of the Species………………………………………..….8
The Area Closure………………….………………………………………………......9
Objectives of Project…………………………………………………………………12
Methods………………………………………………………………………………………….12
I.
II.
III.
IV.
V.
Data…………………………………………………………………………………..12
CPUE………………………………………………………………………………...13
Cost, Revenue, and Profit……………………………………………………...…….13
Effort Redistribution………………………………………………………………....14
Ecology………………………………………………………………………………15
Results…………………………………………………………………………………………...16
I.
II.
III.
CPUE………………………………………………………………………………...16
Redistribution of Fishing Effort……………………………………………………...18
Ecological Benefits…………………………………………………………………..22
Discussion……………………………………………………………………………………….24
I.
II.
III.
IV.
V.
Economic and Ecological Implications……………………………………………...24
Significant Difference Between the Area Closure and Patch 11………………….....26
Comparison to Amendment 7………………………………………………………..27
Discussion of No-Take Zones………………………………………………………..27
Limitations of Project………………………………………………………………..28
Recommendations…………………………………………..……………………………….….29
Acknowledgements……………………………………………………………………………..33
References…………………………………..…………………………………………………...34
Appendix..………………..……………………………………………………………………...37
3
LIST OF ACCRONYMS
ABFT – Atlantic Bluefin Tuna
ICCAT – International Commission for the Conservation of Atlantic Tuna
TAC – Total Allowable Catch
MSA – Magnuson-Stevens Act
ATCA – Atlantic Tunas Convention Act
CPUE – Catch Per Unit Effort
YFT – Yellowfin Tuna
BET – Bigeye Tuna
SWO – Swordfish
MPA – Marine Protected Area
DMA – Dynamic Management Area
4
INTRODUCTION
I.
The Atlantic Bluefin Tuna Fishery
Fisheries are a common-property resource; without regulations, anyone is permitted to
access and use the stocks. As a result, fish populations are often over-exploited because
individuals consider personal gains rather than costs to society. Specifically, individuals consider
the personal benefit of catching one more fish rather than the consequences of extracting a
resource at a higher rate than it can be replenished. This depletion of a common pool resource,
termed the ‘Tragedy of the Commons’1, is shown to occur in fisheries worldwide.
An archetypal example of a depleted common pool resource is the Atlantic bluefin tuna
(ABFT). Inhabiting the entire North Atlantic and adjoining waters such as the Mediterranean
Sea, ABFT have one of the widest geographical distributions of any species.2 This large
distribution is made possible by their fast swimming speed and the fact that ABFT can maintain
their body temperature in both cold (3o C) and warm (30o C) ocean temperatures.3 Tagging data
show ABFT follow an extensive migration pattern throughout the year. Along the East Coast of
the United States, ABFT winter off of the coast of the Carolinas; however, during the summer,
the species migrates to waters near New England and Canada4. Due to this extensive seasonal
movement, ABFT are characterized as a highly migratory species.
Tagging data have also revealed there are two separate populations of ABFT: the eastern
stock and the western stock. 5 The eastern stock is estimated to have a spawning stock biomass
(the population capable of reproducing) between 439,000- 647,000 tons and originates in the
Mediterranean Sea.6 The western stock is much smaller, with a spawning stock biomass between
22,000 - 33,000 tons, and originates in the Gulf of Mexico.7 While an individual returns to its
spawning site to reproduce, ABFT migrate and forage throughout the entire Atlantic Ocean.8 In
fact, the ranges of the eastern and western stocks overlap up to 47%.9 This means a fisherman
who catches an ABFT off the US coast has up to a 50% chance of catching a fish which was
spawned on the opposite side of the Atlantic.
The impressive size and high quality meat of ABFT makes them a valuable economic
resource. Dating back to the Phoenicians in 1200 BC, ABFT captured the attention of fishermen
due to their impressive length (>3m) and weight (up to 670kg).10 While ABFT were historically
caught with beach seines and hand lines, during the 1950s and 1960s fishing technology
5
transitioned to purse seines and longlines.11 This change in methodology increased the number of
hooks in the water, the number of ABFT caught as bycatch, and mortality in the fishery.12 Other
technological changes included improvements in sonar which made fishermen more effective at
locating tuna, and improved on-board storage, which allowed fishermen to extend their number
of days at sea.13 At the same time demand for bluefin tuna increased largely as the result of the
immense growth in the Japanese sushi market and the ability to quickly fly tuna from the
Atlantic to Tokyo.14 This escalation in demand raised the prices of bluefin tuna, increasing the
profitability of the fishery and providing fishermen the incentive to invest in larger and more
powerful boats.15 Together, these changes expanded the area of the ocean which was
economically viable for tuna exploitation.16 As a result, landings of ABFT increased dramatically
in the early 1960’s, with roughly 30,000 tons caught annually in the East Atlantic.17 In the West
Atlantic, 18,000 tons of ABFT were caught in 1964, 18 times the catch reported four years
previous.18
High landings continued until the late 1960s when the capacity of the fleet exceeded the
productivity of the fishery.19 By 1980, the spawning stock biomass of the western ABFT dropped
to just 15% of its pre-exploitation level.20 A similar collapse was seen in the spawning stock
biomass of the eastern population during the 1970s.21 These low population levels continue today
as the West Atlantic stock is at just 36% of its already overfished 1970 levels.22
II.
Current Management of the Fishery
ABFT are currently managed by the International Commission for the Conservation of
Atlantic Tuna (ICCAT). Established in 1969, this intergovernmental organization was created in
recognition of the fact that tuna are highly migratory and do not obey national or international
boundaries23. The mission of ICCAT is to promote “the conservation of tuna and tuna-like
species in the Atlantic and its adjacent seas”.24 To achieve this goal, member nations of ICCAT
provide annual catch and effort data from their national tuna fisheries.25 This information serves
as the basis of ICCAT’s scientific reports and is used to facilitate management schemes among
member nations.26 Currently, ICCAT oversees the broad geographic range of ABFT by dividing
the stock into two management zones: the western stock and the eastern stock.27 The
management boundary separating these two populations is the 45o W meridian in the North
Atlantic Ocean.28 While this method may provide a simplified management system, it does not
6
match the ecological nature of ABFT since the species migrates between both sides of the
Atlantic Ocean.29 This has significant implications for the validity of stock assessments and
projections on the recovery of the two populations.30 The ineffectiveness of ICAAT’s
management scheme is amplified by the fact that ICAAT has no legitimate enforcement power
over the member nations.31 As a result, issues with over-capitalization of the fishery and illegal,
unintended, and unreported fishing are continuing to plague the ABFT fishery.32
In response to the continued depletion of the ABFT, ICCAT imposed catch quotas in
1982.33 The theory behind quotas is that, by limiting effort in the fishery, scientific data can be
used to direct the optimal harvest of a species. Specifically, data can be used to determine a
sustainable total allowable catch (TAC) and this amount can be divided into shares, or quotas,
among participants in the fishery. In the West Atlantic, TACs have remained relatively stable,
ranging between 1750 and 2700 tons.34 Contrastingly, in the East Atlantic, TACs have been
appreciably high even in the face of scientific data which challenges their long-term
sustainability.35 This discrepancy between the management of the two populations continues
today as the 2014 West Atlantic quota was set at 1750 metric tons while the East Atlantic quota
was 13,500 tons.36 The implications of this mismanagement are severe given there is significant
mixing between the two populations and large yields in the East Atlantic can negatively impact
the western stock.
The United States is a major participant in the West Atlantic bluefin tuna fishery.
Between 2011 and 2014, the annual US baseline quota for ABFT was 1018 tons, roughly 53% of
the TAC for the West Atlantic catch.37 This quota is managed by NOAA Fisheries and is broken
down by gear type as seen in Table 1. The “Reserve” category is set aside for scientific research
and can be used to account for dead discards, thereby providing flexibility in the management of
the fishery.38
7
Table 1: Distribution of US ABFT quota among gear types.39
Gear Type
Percentage of US
ABFT Quota
47.1%
General (Commercial
fishermen who use rodand-reel)
Harpoon
Purse Seine
Longline
Trap
Angling (includes
recreational fishermen)
Reserve
III.
3.9%
18.6%
8.1%
0.1%
19.7%
2.5%
Problems with the Recovery of the Species
Recently, the distribution of ABFT quota among gear types in the US received significant
criticism. The longline category is repeatedly exceeding its subquota, which is 8.1% of the
TAC.40 This is forcing NOAA Fisheries to rely on unharvested quota from other sectors or to
‘borrow’ quota from the Reserve category in order to meet yearly catches.41 Another issue is
that, while yields in the fishery have remained fairly stable due to extensive management
measures, the western stock remains well below its 1960 levels.42 In fact, the stock has been
considered overfished since 1997.43 This means that while the collapse of the fishery may be
halted, the western stock of ABFT has yet to recover.
Several management changes by ICCAT are also precipitating the need for change in the
US ABFT fishery. The first is that, when US quotas were first established in 1999, only landings
were included in this figure; dead discards were accounted for separately.44 However, in 2006,
ICCAT changed its recommendations requiring dead discards to be counted within each
country’s annual quota.45 This issue came to a head in 2011 when the annual quota for the
longline sector was insufficient to cover dead discards and yields. Specifically, the quota from
the longline sector was 82.45 tons and estimates of dead discards exceeded 134.81 tons.46
Secondly, the amount of unharvested quota which can be rolled over each year has been reduced
by ICCAT from 100%, to 50%, to the current 10%.47 This minimizes the flexibility of NOAA
Fisheries to respond to high yields in the longline fishery. Finally, ICCAT recently adopted a
8
more ecologically conservative approach to qualifying and quantifying dead discards, causing
the estimate of dead discards in the fishery to increase.48
The inefficiency in the ABFT fishery is of concern because it means NOAA Fisheries is
failing to meet the standards of the Magnuson-Stevens Act (MSA). The MSA is the foremost
piece of legislation governing the management of fisheries in the US. The law outlines standards
which all fisheries must meet, including minimizing bycatch, managing a species to its optimal
harvest, and rebuilding overfished stocks.49 Furthermore, as a member state of ICCAT, the US
must abide by the Atlantic Tunas Convention Act (ATCA) and enact regulations which carry out
the recommendations of the international organization.50 These regulations include minimizing
dead discards to the extent practicable and supporting the efforts of the stock rebuilding
program.51 Data from the US ABFT fishery show these requirements are not being met.
Specifically, while some gear categories are exceeding their subquotas, others are failing to reach
their limit. This shows the fishery is not being optimally managed. Additionally, the large
number of dead discards, especially in the longline sector, illustrates bycatch is not being
minimized in the fishery. Finally, the fact that the species is still considered overfished means
regulations are failing to rebuild the stock.
IV.
The Area Closure
In an effort to address these deficiencies within the fishery, NOAA Fisheries undertook a
comprehensive review of ABFT management and the quota system. In 2012, the Highly
Migratory Species Advisory Panel began the scoping process to assess challenges within the
fishery and potential changes which could be made.52 In August 2013, NOAA Fisheries
published the Draft Amendment 7 to the 2006 Consolidated Atlantic Highly Migratory Species
Fishery Management Plan53, a document outlining specific actions which could be taken in the
fishery to meet MSA and ICCAT requirements. The Final Amendment 7 proposal was released
in August 2014 and the Final Rule was issued on December 1, 2014.54 Some of the management
strategies outlined in the Amendment include reallocating quota among gear types, implementing
area closures, enhancing monitoring, and creating individual bluefin quotas in the longline
fishery.55 One management measure of specific relevance to North Carolina fishermen is the
implementation of a seasonal gear restriction off of Cape Hatteras.56 As seen in Figure 1, the area
was chosen because it has a high number of ABFT interactions relative to the surrounding area.57
9
This area closure will prohibit the use of longline gear from December to April; however, select
longline fishermen will be permitted access to the area closure based upon previous compliance
with the Pelagic Observer Program, low historic bluefin tuna interactions, and superior logbook
reporting.58 The overall goal of the area closure is to improve ABFT stocks by reducing the
number of vessels in the fishery, decreasing the number of ABFT caught, and eliminating the
boats which make up a large portion of total bycatch.59
Figure 1: The location of the Cape Hatteras area closure. The closure will be implemented from
December to April and apply to pelagic longline fishing.60
Implementing this type of closure has vast economic and ecological impacts. Therefore, it
is important to analyze the location and timing of the area closure and predict impacts to
fishermen and the stock. In the Amendment, NOAA Fisheries undertook a rudimentary analysis
to understand the ecological and economic impact of the Cape Hatteras area closure. A major
10
assumption in the analysis is fishermen with 75% or more of their hooks in the area closure will
exit the fishery; fishermen who have 40-75% of their hooks in the area closure will redistribute
50% of that displaced fishing effort; and fishermen with less than 40% of their hooks in the area
closure will redistribute all of their effort in the fishery.61 Based on this assumption, NOAA
estimates that, of the thirty-four vessels fishing in the Cape Hatteras area closure, fourteen will
be proscribed from fishing in the region based on performance metrics.62 Four of these fourteen
vessels will exit the fishery since greater than 75% of their effort is concentrated in the area
closure.63 Three vessels will distribute 50% of their effort outside of the area closure.64 This
downsize of the fishery will result in 25 fewer ABFT landed each year and 379 fewer ABFT
discarded each year.65 Since ABFT are part of a multi-species fishery, other species impacted
include swordfish (1344 fewer fish caught/year), bigeye tuna (310 fewer fish caught/year), and
yellowfin tuna (862 fewer fish caught/year).66 Economically, the revenue lost in the fishery after
accounting for the partial redistributed of effort is estimated at $211,000 per year.67
While NOAA Fisheries estimates the ecological and economic impacts of the closure,
there are several methodological concerns. The first is the assumption that fishermen with greater
than 50% of their hooks in the gear restricted area will, in part or in total, exit the fishery. Since
the ABFT fishery is a lucrative industry with large sunk costs, it is unlikely fishermen will
simply leave the fishery. This is especially true considering fishing is often an immense source of
pride and community, making many fishermen unwilling to leave their profession even when it
is economically rational to do so.68 Secondly, the analysis in the Amendment assumes displaced
fishermen will evenly distribute their effort outside of the area closure. However, this is unlikely
since fishermen, hoping to maximize profit, will go to the location which has the highest
potential revenue and the lowest fuel costs. As a result, redistributed effort will be
heterogeneous.69 Finally, the location of the gear restricted area was chosen due to a high
concentration of ABFT interactions. However, it can be argued the most effective location for an
area closure is one with a high catch per unit effort (CPUE). CPUE is a measure of fish yields
relative to fishing effort. Accounting for effort is important because, unlike the number of
interactions, it results in an accurate estimate of fish density; the greater the effort spent catching
a fish, the smaller the stock in a given area.70 Furthermore, the calculation of CPUE over time
can reflect trends in the population size.71 As a result, CPUE is an important indicator to use
when locating a potential area closure. Since interactions, not CPUE, were used as the basis of
11
NOAA’s analysis, it is unclear if the area chosen for the seasonal closure is the most effective
location to promote the conservation of ABFT.
V.
Objectives of Project
The objective of this Masters Project was threefold. The first was to map CPUE in order
to determine if the location of the Cape Hatteras area closure is an effective and equitable
location for the conservation of ABFT. Since Figure 1 shows there are high levels of ABFT
interactions in the area, a high CPUE would confirm this location has a high stock density and is
ideal for increased management. The second objective of this Master’s Project was to analyze the
potential environmental benefits of the area closure to ABFT as well as the other species in the
fishery. These include swordfish (SWO), bigeye tuna (BET), and yellowfin tuna (YFT). Finally,
the third goal of the Project was to predict where displaced fishermen will go given that they are
looking to maximize potential revenue and minimize fuel costs. This relocation could have
important economic impacts to fishermen and ecological impacts to the multi-species fishery.
An overarching objective of this Master’s Project is to inform future decision-making concerning
the location and impact of area closures by using this paper as a methodological case study.
METHODS
I.
Data
Data from the ABFT longline fishery were obtained from Dr. Andre Boustany. The
dataset included the location (latitude and longitude) of 194,288 sets in the fishery between 1992
and 2008. Additional information included the number of hooks per set, the date, and the number
of ABFT, YFT, BET and SWO caught per set.
The data were imported into ArcGIS 10.2 as a shapefile using the “NAD 1983 StatePlane
North Carolina FIPS 3200” projection. The location of the area closure near Cape Hatteras was
mapped in ArcGIS using the coordinates provided in Figure 2.8 of the NOAA Amendment (see
Figure 1).
12
II.
CPUE
CPUE was calculated and mapped in ArcGIS by dividing the total number of interactions
for a given species by the total number of hooks in the water for all data between 1992 and 2008.
First, data on the number of hooks and the number of interactions per species were converted
into raster files (cell size 72000, 72000). If multiple fishing sets occurred in the same raster cell,
the sum of the number of hooks and interactions was taken. The Raster Calculator was then used
to divide the number of interactions per species by 10,000 hooks. The number of hooks used in
the calculation was large so the resulting values of CPUE would not be small decimal numbers.
This same procedure was used to calculate CPUE for each of the twelve months.
III.
Cost Distance, Revenue, and Profit
Four major longline fishing ports in North Carolina (Hatteras, Morehead City, Ocracoke,
and Wanchese) were identified and their location mapped in ArcGIS.72 Using the Euclidean
Distance tool, seaward distances were calculated in miles. Since all four points were located on
the coast and the Atlantic Ocean was the focus on the study, there was no concern about avoiding
land in this calculation. This prevented the need to use the Cost Distance tool. Distances were
then transformed into costs by multiplying the Euclidean Distance raster files by $1.02. This
estimate for the cost of fishing per boat mile in North Carolina was obtained from Strand
(2004).73
Revenue for each set of hooks was estimated by multiplying the monthly average price
per pound of the species by the average weight of the species caught and then multiplying this
value by the number of fish caught per set. Monthly data on the total revenue and total poundage
caught for each species in the South Atlantic were obtained from NOAA Commercial Fisheries
Statistics.74 This allowed for the calculation of the monthly average price per pound for each
species. If data were not available for a specific month, then the average price per pound of the
previous month served as a proxy.
Data on the average weights of ABFT, BET, YFT, and SWO caught in the longline
fishery were obtained from catch-at-size data in ICCAT stock assessments.75 These values were
then multiplied by the monthly average revenue per pound to get the average revenue per fish
caught. The revenue for each species in a single fishing set was calculated by multiplying the
monthly average revenue per fish by the number of individuals caught of that species. The
13
revenue values for the four species were then added together to get the total revenue per set. The
number of ABFT landed per set (and thus sold for revenue) was limited to two fish to reflect
retention limits in the fishery.76 This revenue data were imported into ArcGIS and converted to a
raster file. If multiple data points occurred in the same raster cell, the mean of these values was
taken.
The expected profit for each fishing set was calculated by subtracting the cost-distance
for each port from the expected revenue. Therefore, four profits were estimated from a single
fishing set to account for different travel costs from each port. These calculations were done in
ArcGIS using the Raster Calculator tool.
IV.
Effort Redistribution
In order to compare areas of equal size, locate regions of high profit, and better predict
the redistribution of displaced fishing effort, the Southeast Atlantic coast was divided into 18
rectangles similar in size to that of the area closure. This method was based on models developed
by Smith & Wilen (2003) in which fishermen choose between an array of locations, or patches,
based on expected revenues and travel costs.77 Figure 2 shows the location and size of these
patches. Average profits for each patch per port of origin were calculated in ArcGIS by
converting profit raster files into shapefiles and using the Statistics tool in the attribute table to
calculate the mean. The standard deviation of the average profit was also calculated for each
patch. Only data from December to April were used to calculate these average profits since this
is when the area closure is to be implemented. This same procedure was repeated to calculate
monthly average profits for each patch.
14
Figure 2: An array of 18 patches along the SE Atlantic Coast. This replicated the method used in Smith & Wilen
(2003) in which fishermen choose between regions based upon travel costs and expected profit. The blue box is the
area closure.
A series of regressions were run in STATA to ascertain the respective importance of
revenue, economic risk, and travel costs in the fishing location decisions made by fishermen.
These regressions analyzed the number of sets in each patch relative to average revenue, the
standard deviation of that revenue, and travel costs to the center of the patch. The centroid of
each patch was determined using the Calculate Geometry function in the attribute table. All data
were used in these regressions.
V.
Ecology
The ecological impacts of the Amendment were assessed by first calculating the average
number of ABFT, YFT, BET, and SWO caught within the area closure from December to April.
Only data from 2006 to 2008 were used to calculate these averages in order to account for recent
population trends. Additionally, the number of ABFT caught within the closure was divided in
15
half to account for the fact that this represents fish from both the western and eastern stocks. The
number of individuals caught for each species was then compared to total yield estimates and
longline catch data in ICCAT stock assessments.78 ABFT catches impacted by the area closure
were also compared to dead discards to assess the potential for quota compliance in the longline
fishery.
The same methodology was used to assess the number and type of fish caught in patch
11, the area to which most fishing effort is expected to redistribute. Additionally, the relative
proportion of each species caught in the fishery was calculated for the area closure and patch 11
to determine if catch in one location is dominated by a specific species. This analysis used data
between December and April from all available years.
RESULTS
I.
CPUE
Figure 3 maps the CPUE for ABFT caught off the Southeast coast. While CPUE ranges
from 0-244 ABFT caught per 10,000 hooks, no clear patterns emerges from the map. Most
importantly, CPUE is not appreciably higher in the area closure, denoted by the blue box. This
means that although there are a high number of interactions in the area closure, this is largely the
result of high fishing effort.
16
Figure 3: The CPUE of ABFT in the South Atlantic for all data between 1992 and 2008. The blue box represents
the area closure, illustrating CPUE is not considerably higher in this region.
To determine the magnitude and extent of seasonal patterns in the fishery, CPUE was
calculated for each month. Figure 4 shows a selection of 8 months which illustrate clear trends in
the data. During January and February, CPUE is highest just south of the area closure. This
region of high CPUE migrates north into the area closure during March and April. Extensive
regions of high CPUE are found in the Mid-Atlantic and New England regions during the month
of June and then this area begins to migrate south in the early winter months. These seasonal
changes are not surprising given the migration patterns of ABFT up and down the East Coast.
17
Figure 4: Seasonal changes in the location of high CPUE areas. In the late winter, CPUE is highest in the South
Atlantic while in the summer and early winter, CPUE is highest in the Mid-Atlantic.
II.
Redistribution of Fishing Effort
The distribution of profits among the 18 patches for fishermen from the four North
Carolina ports is shown in Figure 5. The yellow box is the location of the area closure while the
green box is the patch with the highest profit and the region to which displaced fishermen are
expected to relocate. Profits range from a loss of roughly $400 dollars (fuels costs if nothing is
caught) to a gain of $29,000. Importantly, regardless of the port of origin, all fishermen are
predicted to relocate to the same patch and this patch is not adjacent to the area closure.
18
Figure 5: Predicted profits of fishermen from the four major fishing ports in North Carolina. The yellow box is
the patch with the area closure while the green box is the patch with the highest profit. The star is the location of the
port. Profits range from a loss of roughly $400 to a gain of $29,000.
Analysis was also undertaken to determine if the relocation of displaced fishermen varied
by month. Figure 6 shows the results for fishermen from Wanchese; however, the results were
uniform among the four ports. During January, February and April displaced fishermen are
predicted to go to patch 11. In December and March, fishermen are predicted to go slightly
further south to patch 16. While there is modest seasonal change in the relocation of displaced
fishing effort, the overall pattern remains the same: regardless of their port of origin, fishermen
will relocate their effort to waters near the North Carolina/South Carolina border. Maps of this
monthly analysis for Hatteras, Ocracoke, and Morehead City fishermen can be found in Figures
1-3 of the Appendix.
19
Figure 6: The predicted profit for fishermen from Wanchese for each month of the area closure. The yellow box
represents the location of the closure while the green box is the patch with the highest profit. The winter profit is an
average of profits between December and April.
The winter average profit and associated standard deviation for each patch and port of
origin is shown in Tables 2-5. The red highlighted row (patch 4) is the location of the area
closure and the green highlighted row (patch 11) is where displaced fishermen are predicted to
relocate. Interestingly, patch 11 has a higher average profit than patch 4 for all ports. This begs
the question why fishermen are not already relocating to this area. Importantly, Tables 2-5 also
show that patch 11 has one of the highest standard deviations meaning profit in this location
varies considerably. It may be fishermen are considering economic risk when deciding where to
fish.
20
Tables 2 & 3: Average profit and standard deviation for Wanchese and Hatteras fishermen. The patch 4 is the
location of the area closure while patch 11 is the region with the highest profit. Patch 11 also has a high standard
deviation, a measure of economic risk.
Tables 4 & 5: Average profit and standard deviation for Ocracoke and Morehead City fishermen. The patch 4 is
the location of the area closure while patch 11 is the region with the highest profit . Patch 11 also has a high standard
deviation, a measure of economic risk.
21
Results from regressions run to ascertain the respective importance of revenue, economic
risk, and travels costs in the location choices of fishermen are shown in Table 6. Revenue had a
positive coefficient and was significant at the 0.05 level for the ports of Wanchese and Hatteras.
Standard deviation had a negative coefficient and was significant at the 0.05 level for all ports,
with p-values ranging from 0.009 to 0.024. Travel costs had negative coefficients and were not
significant. R-Squared values for the four ports ranged between 0.426 and 0.3578.
Table 6: Regression results for each port when number of sets is a function of revenue, standard deviation of that
revenue, and travel costs. Standard deviation was significant at the 0.05 level for all of the ports, revenue was
significant for half of the ports and travel costs were not significant for any of the ports.
Port
Wanchese
Ocracoke
Morehead City
Hatteras
III.
Variable
Revenue
SD
Travel Cost
Revenue
SD
Travel Cost
Revenue
SD
Travel Cost
Revenue
SD
Travel Cost
Coefficient
3.26
-0.31
-10.42
3.42
-0.32
-11.11
3.12
-0.28
-6.35
3.49
-0.33
-11.39
P-Value
0.025
0.009
0.338
0.057
0.024
0.43
0.061
0.017
0.604
0.047
0.021
0.374
R-Squared
0.426
0.3998
0.3578
0.4145
Ecological Benefits
The annual number of ABFT caught in the area closure averaged over the three most
recent years of data is shown in Table 7. In total, the annual catch of ABFT is expected to be
reduced by roughly 600 individuals. Using an average catch- at-size of 150kg, this is equal to
roughly 99 tons of ABFT. The percentage of total ABFT yields impacted by the proposal is
shown in the fourth and fifth columns of Table 7. These percentages are all less than 1% of
current catches for the eastern and western stocks. Table 7 also shows the percentage of longline
catch impacted by the area closure. While the closure accounts for less than 1% of longline
catches in the eastern stock, the impact to the western stock ranges up to 3%. Importantly, since
some fishermen will be able to fish in the area closure due to high levels of logbook compliance,
the reduction in catch and the percentages are likely smaller than those shown in Table 7.
22
Table 7: Number of ABFT affected by the area closure and the relative proportion of this number to total yields
and current longline catches. The total number of ABFT per month is divided in half to account for the presence of
eastern and western stocks.
Month
December
January
February
March
April
#
ABFT
96
31
93
165
217
Eastern Western
ABFT
ABFT
48
48
15
15
46
46
83
83
109
109
% Eastern
Yields
0.0488%
0.0156%
0.0473%
0.0844%
0.1107%
% Western
Yields
0.4386%
0.1406%
0.4249%
0.7580%
0.9949%
% Eastern
Longline
0.356%
0.114%
0.345%
0.616%
0.809%
% Western
Longline
1.352%
0.433%
1.309%
2.336%
3.066%
Since ABFT are a part of a multispecies fishery, the area closure may also have
ecological ramifications for SWO, YFT, and BET. Table 8 shows the annual number of SWO,
YFT, and BET caught in the area closure, averaged over the three most recent years of data.
SWO are the most common species caught in this region; however, catch in the area closure
accounts for less than 1% of their total yields. Similar trends exist for the YFT and the BET. The
impacts of the area closure on longline catches of each species are also shown in Table 8. Again,
these values are all less than 1%.
Table 8: The catch of YFT, BET, and SWO which will be impacted by the area closure. The relative proportions
of these numbers to total yields and current longline catches for each species are also shown.
Month
# YFT
December
January
February
March
April
652
617
204
92
221
% YFT
Yields
0.0105%
0.0100%
0.0033%
0.0015%
0.0036%
% YFT
# BET
Longline
0.0588% 260
0.0556% 226
0.0184%
44
0.0083%
32
0.0199%
65
% BET
Yields
0.0243%
0.0211%
0.0041%
0.0030%
0.0060%
% BET
Longline
0.0476%
0.0413%
0.0081%
0.0058%
0.0253%
# SWO
906
552
602
280
297
% SWO
Yields
0.3396%
0.1958%
0.2324%
0.1048%
0.1112%
% SWO
Longline
0.355%
0.204%
0.243%
0.109%
0.116%
It is expected that much of the fishing effort displaced by the area closure will
redistribute to patch 11. Figure 7 compares the fishing patterns in the two regions. From the
graphs it is clear SWO make up a much larger portion of the catch in patch 11 than in the area
closure (70% vs. 54%). Additionally, ABFT do not make up a measurable portion of catch in
patch 11 whereas they account for 4% of catches in the area closure. Another observation is that
the magnitude of catch in the area closure is much higher than in patch 11. This does not mean
profit should be necessarily higher in the area closure since revenue is largely dependent on the
23
density of the catches. Instead it means the amount of fishing in patch 11 is significantly less
than in the area closure.
Patch 11 Catch
Dec.-Apr.
Area Closure Catch
Dec.-Apr.
4%
0%
13%
0%
BFT (12)
BFT (2481)
30%
BET (21)
BET (7920)
54%
29%
70%
YFT (17843)
YFT (5934)
SWO (14095)
SWO (32404)
Figure 7: Proportion and number of catch for the four species in the area closure and patch 11.
DISCUSSION
I.
Economic and Ecological Implications
As seen in Figure 3, the area closure is not in a region with a high CPUE. This calls into
question the effectiveness of the area closure since high amounts of effort may be causing the
large number of interactions seen in Figure 1 rather than a high population density. Monthly
analysis of CPUE shows areas of high CPUE migrate up and down the coast, following the
migration patterns of ABFT. Figure 4 shows that during March and April, the areas of highest
CPUE are, in fact, in the area closure. This suggests there could be large ecological value to the
management measure during these two months. However, as the summer progresses, the highest
CPUE is found in the Mid-Atlantic and New England regions. By January, ABFT CPUE is
highest just south of the area closure.
The observation that regions of high CPUE seasonally migrate is important for two
reasons. The first is that while an area closure may prove effective for a month or two, there is no
single location which is optimal for a long-term closure. This suggests stationary area closures
are not ideal to protect non-spawning grounds in the fishery. Secondly, given the fact that CPUE
can be just as high off New England as it can be off of Cape Hatteras, the implementation of an
area closure in just one of these locations means the burden of conservation is not equally
distributed among fishermen. Moreover, while North Carolina fishermen are faced with a closure
24
during critical fishing months, no such management restriction is proposed for New England
fishermen. This calls into question the equitable nature of the area closure.
The estimated profits shown in Figure 5 suggest displaced fishermen, who are looking to
maximize returns and minimize costs, will likely redistribute their fishing effort south of the area
closure to patch 11. This pattern slightly varies by month as fishermen either move to patch 11 or
patch 16. Therefore, contrary to the assumptions made in the NOAA Amendment, effort
redistribution is not homogenous but rather congregates around an area of high profit.
Furthermore, this redistribution is not adjacent to the area closure meaning fishermen are not
expected to merely move to the borders of the closure. Profits between the area closure and patch
11 are comparable, with profits being slightly higher in patch 11. Notably, the standard deviation
of revenue is also higher in patch 11. This begs the question whether revenue, economic risk in
the form of standard deviation, or travel cost is the most important factor fishermen consider
when choosing where to fish.
The regression analysis shown in Table 6 shows revenue and the standard deviation of
revenue are important factors fishermen consider when choosing where to fish. The coefficients
on the regression outputs show that ideally, fishermen prefer areas with high and stable revenue.
This is not surprising given that fishermen want to maximize returns and minimize economic
risks. Travel costs were never significant in the regression output and do not appear to be a
significant factor in choosing where to set hooks. However, only a small fraction of the range of
the fishery was analyzed and travel to far away areas may be limited. Other variables which also
influence where fishermen decide to set could include proximity to other fishing grounds, typical
ocean conditions, and family tradition. This highlights the complexity of predicting the
redistribution of displaced fishing effort.
Ecologically, the area closure provides moderate benefits to the ABFT pelagic longline
fishery. Table 7 shows that the catch of ABFT will be reduced by roughly 600 individuals, or 99
tons. While this represents only a small percentage of total longline catch, it does equal 74% of
longline dead discards, which were 134.81 tons in 2011. Importantly, this does not account for
all dead discards and means that the area closure will not ensure quota compliance in the longline
sector. Moreover, the area closure will not reduce dead discards to within current catch limits
and the fishery will not be in strict compliance with NOAA Fisheries or ICCAT. Table 7 also
shows the area closure will impact less than 1% of total ABFT yields. Therefore, the closure will
25
not serve to rebuild or improve current stocks in the fishery. Notably, the percentages calculated
are likely higher than the ecological benefits which will be accrued for ABFT since select
longline fishermen will be allowed to fish in the area closure due to historic compliance with
observers and superior logbook compliance.
Impacts to BET, YFT, and SWO are expected to be minimal in the multi-species fishery.
Table 8 shows affected portions of these species are all less than 1% of longline catches and total
yields. Therefore, the ecological benefits accrued by the area closure for these species are not
expected to be significant.
II.
Significant Differences Between the Area Closure and Patch 11
Displaced fishing effort from the area closure is expected to redistribute to patch 11;
however, there are significant differences in the fishing patterns of these two locations which
could have important ecological and economic impacts. The first difference is that, while
average profits in the two regions are similar, the range of profits in patch 11 is much greater.
This means there is greater economic risk when fishing in patch 11. Another important disparity
is that, as seen in Figure 7, the proportion of species caught in patch 11 is markedly different
than those caught in the area closure. Specifically, fishing in patch 11 is characterized by high
catches of SWO, with almost no ABFT and BET caught in this region. Finally, the current
magnitude of catch in patch 11 is far less than that occurring in the area closure. This means that,
when the area closure is implemented, fishing effort in patch 11 will dramatically increase.
These differences between the area closure and the location of effort redistribution have
important economic and ecological consequences. With large amounts of effort being transferred
to a location which currently supports far less fishing, it is unclear what level of catch can be
supported. If displaced fishermen are unable to meet their quotas in patch 11, CPUE will drop
prompting fishermen to invest in more advanced gear and technology. This effect will be
amplified since the economic risk of fishing in patch 11 is greater and fishermen will seek out
improved technology to increase the reliability of their catch. While overall catch is
hypothetically limited by quotas, overcapitalization in the fishery will likely result in greater
levels of bycatch.79
This transfer of fishing effort south of the area closure will also have implications for the
species in the fishery. The fact that hardly any ABFT and BET are caught in patch 11 suggests
26
the redistribution of fishing effort may not negate the mild benefits accrued to these species in
the area closure. Moreover, the minimal impacts to ABFT and BET populations may be
preserved even after the redistribution of fishing effort. Contrastingly, fishing pressure on SWO
will likely increase since they make up 70% of catch in patch 11, compared to 54% in the area
closure. While this does not pose a current concern since SWO catches are below quota limits, it
is an indirect effect of the area closure that should be monitored. 80 It does not appear YFT
populations will be significantly impacted by the area closure. Roughly the same percentage
(29% vs. 30%) of YFT is caught in both regions and it is likely the relocation of fishing effort
further south will nullify any minimal benefits to the stock.
III.
Comparison to Amendment 7
Rough calculations in Amendment 7 state the economic loss to the fishery will be
roughly $211,000.81 This number is largely based on expected exits in the fishery. Contrary to
the assumption that fishermen with a majority of sets in the area closure will reduce their fishing
effort or completely exit the fishery, Figure 5 suggests patch 11 presents a potentially profitable
alternative. Furthermore, given the large sunk cost of a boat, the occupational pride felt by many
fishermen, and the lucrative tuna business, it is unlikely many fishermen, if any at all, will leave
the fishery. Therefore, economic loss from the consolidation of the fishery is unlikely; however,
fishermen’s profits could decrease if patch 11 is unable to sustain the increase in fishing effort.
Additionally, overcapitalization of the fishery could increase the costs associated with fishing.
The NOAA Amendment also estimates the ecological impact to the four species will be
1344 fewer SWO, 310 fewer BET, 862 fewer YFT, and 401 fewer ABFT caught each year.82
These values all represent impacts to less than 1% of the respective total landings and roughly
2% of ABFT pelagic longline landings. Importantly, NOAA’s estimates are based on effort
consolidation since they assume some fishermen will exit fishery.83 As previously stated, this is a
flawed assumption so the validity of the specific values must be questioned.
IV.
Discussion of No-Take Zones
The establishment of area closures, no take zones, and marine reserves is a popular
management scheme to conserve and preserve fish stocks. It is believed that these protected
zones increase fish biodiversity and abundance by eliminating fishing pressure, diminishing
27
bycatch, and removing habitat disturbances.84 Furthermore, these positive impacts are thought to
spill-over to adjacent areas as fish move out of the area closure.85 Some studies have found
success with this management option. Research at the Mona Island Marine Protected Area
(MPA) in the Caribbean found the implementation of a no-take zone resulted in a greater
abundance of early life-stage fish within and outside of the MPA.86 Another study at De Hoop
Reserve in South Africa found that within 2.5 years of establishing a no-take zone, the CPUE of
six species increased.87
While the above research points to tangible benefits of no-take zones, some economists
are beginning to question their effectiveness. A review on the methodological approach to
evaluating marine reserves found that, while many papers report higher abundances of fish as the
result of an area closure, there is no counterfactual to judge the effectiveness of the management
plan; there is no comparison to determine what would have happened to the species if a marine
reserve had not been implemented.88 Another issue with the evaluation of marine reserves is the
simplification of fishermen’s responses to these closures.89 Specifically, many studies assume
displaced fishing effort will evenly distribute over the available area.90 However, this assumption
can cloud estimates of harvest and egg production, resulting in overly optimist predictions of
marine reserves.91
Recent studies are revealing the ecological benefits of no-take zones may be minimal. A
study of a marine reserve in the Great Barrier Reef found that 9 years after establishing a marine
reserve, there was no increase in total catch levels or catch-rates outside the area closure.92 This
refutes the theory that spillovers of adult and juvenile fish will create economic benefits in the
fishery.93 Another investigation into the seasonal closure of the Californian sea urchin fishery
found that, when changes in the amount and location of effort were accounted for in harvest and
recruitment models, the biological effects of the marine reserve were significantly minimized.94
These results support the finding that an area closure off of Cape Hatteras will only produce
moderate benefits to ABFT and will not serve to rebuild currently depleted stocks.
V.
Limitations of Project
One of the major limitations of this project was that the dataset did not include ports of
departure and arrival, preventing fishing sets from being identified to a specific boat. These
missing pieces of data impact travel cost calculations since a boat may not return to the same
28
port from which it departed. Additionally, since it was not possible to identify which hooks were
set by the same boat on a single fishing trip, travel between sets was not accounted for in
distance calculations. Instead, travel costs to each set were assumed to be from a port. This is not
realistic because fishermen will place multiple sets in a region, thereby reducing fuel costs for
those subsequent hooks. While travel costs were not found to be significant in the regression
analysis, it is unclear if this outcome might change were the data able to support this high level
of complexity.
Another important limitation is the fact that ecological impact of the area closure on
ABFT was based on ICCAT stock assessments. As mentioned in the beginning of this paper,
ICCAT currently manages the species by dividing the Atlantic stock into two populations along
the 45oW meridian. This simplified management scheme does not account for the intermingling
of the eastern and western stocks and limits the validity of population assessments and recovery
projections. Thus, the predicted ecological impact of the area closure is based on potentially
faulty stock assessments which may obfuscate the true biological effect.
RECOMMENDATIONS
Analysis shows the ecological benefits of the area closure are limited in the multispecies
fishery. While the closure will help the pelagic longline fishery come closer to quota compliance,
the management measure is not enough to cover the current number dead discards in the fishery.
Furthermore, analysis suggests this area closure will not significantly improve the stock of ABFT
or support its recovery. This has important ramifications for NOAA Fisheries since they will
continue to fall short of the requirements outlined in the MSA and ATCA.
The outputs of project highlight the need to incorporate CPUE into the siting of area
closures. The location of the closure in Amendment 7 was chosen because it has a high number
of ABFT interactions; however, analysis shows this area does not have a high CPUE. In fact, the
calculation of CPUE reveals the highest number of fish caught per hooks in the water moves up
and down the coast. This highlights the inequitable nature of the area closure and its
ineffectiveness for three out of the five months it is to be implemented. Therefore, future
decisions concerning the location of area closures should be made after calculating CPUE.
29
Additionally, this project highlights the importance of realistically predicting the
redistribution of displaced fishing effort. The economic and ecological analysis undertaken by
NOAA Fisheries was predicated on the assumption that fishermen would exit the fishery and
effort would evenly distribute over the remaining areas. However, these assumptions do not
accurately reflect the incentives for fishermen to stay in their profession and find the next most
profitable location. By incorporating the heterogeneous redistribution of fishing effort into this
analysis, the ecological benefits of the area closure are more accurately calculated. Furthermore
indirect effects, such as that on SWO, may be identified. This highlights the need to incorporate
realistic economic modeling into the analysis of future area closures.
A primary challenge in the management of the ABFT is the ecological complexity of the
species. Not only is the stock comprised of two distinct populations but ABFT undertake vast
migrations throughout the entire North Atlantic. Since stationary area closures do not reflect this
complexity, they may be ineffective tools for the management of highly migratory species. One
recommendation is that future management schemes reflect the seasonal movement of this
species. Figure 4 shows areas of high CPUE migrate up and down the US coast. Therefore, an
effective area closure would be one which mirrors this pattern. Figure 8 illustrates the basic
concept of a dynamic area closure. In this strategy, the location of the area closure changes
seasonally to follow regions of high CPUE. This dynamic management would not only ensure
the closure focuses on dense population aggregations but it would equally distribute the burden
of conservation among West Atlantic fishermen.
30
Figure 8: A conceptual look at dynamic management in which the location of an area closure moves seasonally to
mirror areas of high CPUE.
Dynamic management has already been implemented in several regions. NOAA Fisheries
implements Dynamic Management Areas (DMAs) in the Northeast to protect right whales from
vessel strikes.95 Specifically, right whale observations are monitored and when a certain
threshold is met, vessel restrictions go into effect.96 These management measures include
reduced vessel speeds and re-routing around the DMA.97 The DMA is an effective management
tool to deal with the rather unpredictable occurrence of right whales. Instead of implementing
year-round closures which could negatively impact the shipping industry, the DMA allows for
management measures to be narrowly tied to the timing and location of right whales.98 This
example shows management measures can be created which are directly linked to the need for
protection.99
31
Like many resource management initiatives, there are difficulties associated with
dynamic fisheries management. First and foremost is the complexity associated with
implementing a moving area closure. Unlike a stationary marine reserve, a dynamic management
area requires a higher level of fishermen education and enforcement.100 The sheer area which
must be covered when implementing this management tool is also greater, especially considering
ABFT are found along the entire US East Coast. This broad range and complex management
scheme translates into higher costs for compliance.101
Despite these challenges, the potential biological benefits of dynamic fisheries
management may be immense, especially for highly migratory species such as ABFT. Further
research is needed to fully understand the magnitude of impact this adaptive management
scheme can have and to determine what guidelines should be established to ensure its successful
implementation. Nonetheless, this project suggests traditional management efforts will not be
enough to rebuild ABFT stocks and dynamic fisheries management may be needed to secure
healthy tuna stocks.
32
ACKOWLEDGEMENTS
I would like to thank my advisors Dr. Andre Boustany and Dr. Pat Halpin for their
guidance throughout this project. A special thanks to Andre Boustany for the supplying the data
for this research. Finally, I would like to thank Dr. Martin Smith for his expertise in modeling the
redistribution of displaced fishing effort.
33
REFERENCES
1
Hardin, G. (1968). The Tragedy of the Commons. Science, 162(3859),1243-1248.
Fromentin, J. M. and Powers, J. E. (2005). Atlantic bluefin tuna: population dynamics, ecology, and fisheries
management. Fish and Fisheries, 6, 281-306.
3
Fromentin and Powers, 2005.
4
Block, B., Teo, S., Walli, A., Boustany, A., Stokebury, M., Farwell, C., Weng, K., Dewar, H., and Williams, T.
(2005). Electronic tagging and population structure of Atlantic bluefin tuna. Nature, 434, 1121-1127.
5
Galuardi, B., Royer, F., Golet, W., Logan, J., Neilson, J., and Lutcavage, M. (2010). Complex migration routes of
Atlantic bluefin tuna (Thunnus thynnus) question current population structure paradigm. Canadian Journal of Fish
Aquatic Science, 67(6), 966-976.
6
ICCAT. (2014). Report of the 2014 Atlantic Bluefin Tuna Stock Assessment Session. Madrid, Spain: September 22
to 27, 2014.
7
ICCAT, 2014.
8
Galuardi et al., 2010.
9
Block et al., 2005.
10
Fromentin and Powers, 2005.
11
Ibid.
12
NOAA Fisheries. (August 2014). Final Amendment 7 to the 2006 Consolidated Atlantic Highly Migratory Species
Fishery Management Plan. Accessed from
http://www.nmfs.noaa.gov/sfa/hms/documents/fmp/am7/final_amendment_7_to_the_2006_consolidated_atlantic_hi
ghly_migratory_species_fishery_management_plan_8_28_2014_for_web.pdf
13
Fromentin and Powers, 2005.
14
Ibid.
15
Ibid.
16
Ibid.
17
Ibid.
18
Bard, Dave. (October 2013). The Story of Atlantic Bluefin Tuna. Pew Environment. Retrieved from
http://www.pewenvironment.org/news-room/fact-sheets/the-story-of-atlantic-bluefin-tuna-85899420680
19
Fromentin and Powers, 2005.
20
Center for Biological Diversity. (24 May 2010). Petition to List the Atlantic Bluefin Tuna (Thunnus thynnus) as
Engandered Under the United States Endangered Species Act. Accessed from
http://www.fisheries.noaa.gov/pr/pdfs/species/cbd_bluefintunapetition_5242010.pdf
21
Taylor, N., McAllister, M., Lawson, G., Carruthers, T., and Block, B. (2011). Atlantic Bluefin Tuna: A Novel
Multistock Spatial Model for Assessing Population Biomass. PLOSone, doi: 10.1371/journal.pone.0027693
22
Bard, 2013.
23
ICCAT. Introduction. Accessed from https://www.iccat.int/en/introduction.htm
24
ICCAT. Introduction.
25
Fromentin and Powers, 2005.
26
Ibid.
27
Ibid.
28
Block et al., 2005.
29
Fromentin and Powers, 2005.
30
Ibid.
31
Straker, L. (2009). ICCAT: Managing or Documenting? Marine Technology Society Journal, 43(1), 117-126.
32
Straker, 1009.
33
Fromentin and Powers, 2005.
34
ICCAT, 2014.
35
The Pew Charitable Trusts. (20 November 2014). “ICCAT Ignores Science and Increases Quota for Atlantic
Bluefin Tuna.” The Pew Charitable Trusts News Room. Accessed from http://www.pewtrusts.org/en/about/newsroom/news/2014/11/20/iccat-ignores-science-and-increases-quota-for-atlantic-bluefin-tuna
36
ICCAT, 2014.
37
NOAA Fisheries, 2014.
38
Ibid.
2
34
39
Ibid.
Ibid.
41
Ibid.
42
Fromentin and Powers, 2005.
43
NOAA Fisheries, 2014.
44
Ibid.
45
Ibid.
46
Ibid.
47
Ibid.
48
Ibid.
49
NOAA. (Amended 12 January, 2007). Magnuson-Stevens Fishery Conservation and Management Act. P.L. 94265.
50
Atlantic Tunas Convention Act. (1975). P.L. 94-70.
51
NOAA Fisheries, 2014.
52
Ibid.
53
Ibid.
54
NOAA Fisheries, 2014; 79 FR 71509.
55
NOAA Fisheries, 2014.
56
Ibid.
57
Ibid.
58
Ibid.
59
Ibid.
60
Ibid.
61
Ibid.
62
Ibid.
63
Ibid.
64
Ibid.
65
Ibid.
66
Ibid.
67
Ibid.
68
Daw, T., Cinner, J., McClanahan, T., Brown, K., Stead, S., Graham, N., and Maina, J. (2012). To Fish or Not to
Fish: Factors at Multiple Scales Affecting Artisanal Fishers’ Readiness to Exit a Declining Fishery. PLOSone, doi:
10.1371/journal.pone.0031460.
69
Smith, M. and Wilen, J. (2003). Economic impacts of marine reserves: the importance of spatial behavior. Journal
of Environmental Economics and Management, 46, 183-206.
70
Gulland, J. (1969). Section 4: Effort and Catch Per Unit Effort. In Manual of Methods for Fish Stock Assessment.
Fishery Resources and Exploitation Division, FAO.
71
Musick, J and Bonfil, R. (2005) Management techniques for elasmobranch fisheries. FAO Fisheries Technical
Paper, 474.
72
McCay, B. and Cieri, M. (April 2000). Fishing Ports of the Mid-Atlantic. Report to the Mid-Atlantic Fishery
Management Council. Accessed from http://www.st.nmfs.noaa.gov/st1/econ/cia/McCay_Port_StudyApr2000_Revised.pdf
73
Strand, I. (2004). Spatial Variation in Risk Preferences Among Atlantic and Gulf of Mexico Pelagic Longline
Fishermen. Marine Resources Economics, 19, 145-160.
74
NOAA. Office of Science and Technology. Commercial Fisheries Statistics: Commercial Landings. Accessed
from http://www.st.nmfs.noaa.gov/commercial-fisheries/
75
ICCAT, 2014; ICCAT. (2010). Report of the 2010 ICCAT Bigeye Tuna Stock Assessment Session. Pasaia,
Gipuzkoa, Spain: July 5 to 9, 2010; ICCAT. (2011). Report of the 2011 ICCAT Yellowfin Tuna Stock Assessment
Session. San Sebastian, Spain: September 5 to 12, 2011; ICCAT. (2013). Report of the 2013 Atlantic Swordfish
Stock Assessment Session. Olhao, Portugal: September 2 to 10, 2013.
76
50 CFR 635.23. Retention Limits for BFT.
77
Smith and Wilen, 2003.
78
ICCAT 2014; ICCAT 2010; ICCAT 2011; ICCAT 2013.
79
Alverson, D., Freeberg, M., Murawski, S., and Pope, J. (1994). Part IV: Policy, Solutions, and Conclusions. In A
global assessment of fisheries bycatch and discards. FAO Fisheries Technical Paper. No. 339. Rome, FAO.
40
35
80
ICCAT 2013.
NOAA Fisheries, 2014.
82
Ibid.
83
Ibid.
84
Dugan, J., and Davis, G. (1993). Applications of Marine Refugia to Coastal Fisheries Management. Canadian
Journal of Fisheries and Aquatic Sciences, 50, 2029-2042.
85
Mateos-Molina, D., Scharer-Umpierre, M., Appeldoorn, R., and Garcia-Charton, J. (2014). Measuring the
effectiveness of a Caribbean oceanic island no-take zone with an asymmetrical BACI approach. Fisheries Research,
150, 1-10.
86
Mateos-Molina et al., 2014.
87
Bennett, B. and Attwood, C. (1991). Evidence for recovery of a surf-zone fish assemblage following the
establishment of a marine resource on the southern coast of South Africa. Marine Ecology Progress Series, 52, 173181.
88
Smith, M., Zhang, J., and Coleman, F. (2006). Effectiveness of marine reserves for large-scale fisheries
management. Canadian Journal of Fisheries and Aquatic Science, 63, 153-164.
89
Smith, M., and Wilen, J. (2003). Economic impacts of marine reserves: the importance of spatial behavior.
Journal of Environmental Economics and Management, 46, 183-206.
90
Smith and Wilen, 2003.
91
Ibid.
92
Fletcher, W., Kearney, R., Wise, B., and Nash, W. In press. Large-scale expansion of no-take closures within the
Great Barrier Reef has not enhanced fishery production. Ecological Applications, http://dx.doi.org/10.1890/141427.1
93
Fletcher et al., in press.
94
Smith and Wilen, 2003.
95
NOAA Fisheries. (2004). Dynamic Management Areas. [White paper]. Retrieved from
http://www.greateratlantic.fisheries.noaa.gov/shipstrike/news/DMAs_July_2004.pdf
96
NOAA Fisheries, 2004.
97
Ibid.
98
Ibid.
99
Ibid.
100
Freestone, D., Varmer, O., Bennett, M., Wilhelm, A., Beuttler, T., Ardon, J., Maxwell, S., and Morrison, K.
(2014). Place-based Dynamic Management of Large-Scale Ocean Places: Papahanaumokuakea and the Sargasso
Sea. Stanford Environmental Law Journal, 33(2), 191-248.
101
Freestone et al., 2014.
81
36
APPENDIX
Figure 1A: The predicted profit for fishermen from Hatteras for each month of the closure. The yellow box
represents the location of the area closure while the green box is the patch with the highest profit .
37
Figure 2A: The predicted profit for fishermen from Ocracoke for each month of the closure. The yellow box
represents the location of the area closure while the green box is the patch with the highest profit.
38
Figure 3A: The predicted profit for fishermen from Morehead City for each month of the closure. The yellow box
represents the location of the area closure while the green box is the patch with the highest profit.
39