Does Climate Change Bolster the Case - Recherche en IA spécialisée au MIT

Does Climate Change Bolster the Case
for Fishery Reform in Asia?
Christopher Costello∗

I examine the estimated economic, ecological, and food security effects of
future ﬁshery management reform in Asia. Without climate change, most
Asian ﬁsheries stand to gain substantially from reforms. Optimizing ﬁshery
management could increase catch by 24% and proﬁt by 34% over business-
as-usual management. These beneﬁts arise from ﬁshing some stocks more
conservatively and others more aggressively. Although climate change is
expected to reduce carrying capacity in 55% of Asian ﬁsheries, I ﬁnd that under
climate change large beneﬁts from ﬁshery management reform are maintained,
though these beneﬁts are heterogeneous. The case for reform remains strong
for both catch and proﬁt, though these numbers are slightly lower than in the
no-climate change case. These results suggest that, to maximize economic
output and food security, Asian ﬁsheries will beneﬁt substantially from the
transition to catch shares or other economically rational ﬁshery management
institutions, despite the looming effects of climate change.

Mots clés: Asia, climate change, ﬁsheries, rights-based management
Codes JEL: Q22, Q28

je. Introduction

Global ﬁsheries have diverged sharply over recent decades. High governance,
wealthy economies have largely adopted output controls or various forms of catch
shares, which has helped ﬁsheries in these economies overcome inefﬁciencies
arising from overﬁshing (Worm et al. 2009) and capital stufﬁng (Homans and
Wilen 1997), and allowed them to turn the corner toward sustainability (Costello,
Gaines, and Lynham 2008) and proﬁtability (Costello et al. 2016). But the world’s
largest ﬁshing region, Asia, has instead largely pursued open access and input
controls, achieving less long-run ﬁshery management success (World Bank 2017).
Recent estimates show that many Asian ﬁsheries continue to languish under
outdated management regimes and could beneﬁt from economically optimized
ﬁshery management systems such as catch shares. World Bank (2017) estimates that

∗Christopher Costello: Professeur, Bren School, University of California Santa Barbara and Research Associate,
National Bureau of Economic Research. E-mail: costello@bren.ucsb.edu. I would like to thank Tracey Mangin for
help in assembling the data for this analysis. I would also like to thank the participants at the Asian Development
Review Conference in Seoul in August 2017, le rédacteur en chef, and two anonymous referees for helpful comments
and suggestions. ADB recognizes “Bombay” as Mumbai and “China” as the People’s Republic of China. The usual
disclaimer applies.

Revue du développement en Asie, vol. 35, Non. 2, pp. 31–57
https://doi.org/10.1162/adev_a_00113

© 2018 Asian Development Bank and
Asian Development Bank Institute.
Publié sous Creative Commons
Attribution 3.0 International (CC PAR 3.0) Licence.

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32 Revue du développement en Asie

Chiffre 1. Hypothetical Beneﬁts of Economically Optimal Fishery Reforms for
Select Economies

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MSY = maximum sustainable yield, NPV = net present value, PRC = People’s Republic of China.
Note: The ﬁgure shows the nine economies with the greatest gains in proﬁt, which all happen to be in Asia.
Source: Calculated from data in Costello, Christophe, Daniel Ovando, Tyler Clavelle, C. Kent Strauss, Ray
Hilborn, Michael C. Melnychuk, Trevor A. Branch, Steven D. Gaines, Cody S. Szuwalski, Reniel B. Cabral, Douglas
N. Rader, and Amanda Leland. 2016. “Global Fishery Prospects Under Contrasting Management Regimes.”
Actes de l'Académie nationale des sciences 113 (18): 5125–29.

Asian ﬁsheries lose $55 billion per year in inefﬁcient management, which accounts for 65% of the estimated global loss of $85 milliard. Chiffre 1 shows the potential
gains from catch shares in the nine economies with the largest economic surplus,
all of which are in Asia.

All of the aforementioned beneﬁts of ﬁshery reform were calculated
assuming a stationary environment. Encore, climate change promises to dramatically
alter the productivity and spatial distribution of most Asian ﬁsh stocks (Molinos
et autres. 2016). These climate-induced changes are expected to play out over the next
100 years or more, but are already starting to take hold. Par exemple, range shifts
have been noted in several of the world’s oceans, coral bleaching appears to be
accelerating, and the productivity of many stocks has sharply changed in recent
années. These ﬁndings raise an important dilemma for Asian economies interested in
the long-run sustainability, food security, and proﬁtability of their ﬁsheries: Should
they aggressively pursue ﬁshery management reforms in advance of the most

Does Climate Change Bolster the Case for Fishery Reform in Asia? 33

serious predicted effects of climate change? Or does the prospect of climate change
weaken the case for reforms such that aggressive reform is no longer necessary?

To shed light on this dilemma, I join newly available data on Asian ﬁshery
status with state-of-the-art climate forecasts and bioeconomic models. I largely
draw on data and methods in Gaines et al. (2018), though that paper does not single
out any results for Asian ﬁsheries, nor does it ask whether the case for reform
is strengthened or weakened under climate change. This allows me to conduct a
species-by-species analysis for 193 species of the most widely harvested ﬁsh in
Asia, representing about 29 million metric tons in ﬁsh catch.1

I begin by estimating biological status and trends for each of these species;
this is accomplished by combining retrospective regression approaches (Costello
et autres. 2012) with dynamic structural models (Martell and Froese 2013). I then
use these data as inputs into a bioeconomic model that estimates the potential
beneﬁts—in terms of ﬁsh conservation, ﬁshery proﬁt, and ﬁsh catch—from
adopting economically efﬁcient ﬁshery management practices in Asia in the
absence of climate change. Essentially, this involves comparing projected ﬁshery
performance under business-as-usual (BAU) management with ﬁshery performance
under economically optimized management.2 Results of that analysis largely
corroborate previous ﬁndings. But because I am primarily interested in how climate
change affects these calculations, I then couple to this analysis projections of
climate effects on each of the species in my data set from Molinos et al. (2016).
These climate models suggest that about 55% of Asian ﬁsheries will experience
reductions from climate change, et 29% will experience signiﬁcant range shifts in
the coming decades. By combining the ﬁshery status, models, and climate effects, je
can then estimate the potential beneﬁts from adopting ﬁshery management reforms
in the face of climate change. Naturellement, this involves solving for the economically
optimal feedback control rule in each ﬁshery. The ﬁnal step is to ask whether
the strong case for ﬁshery reform is maintained, or undermined, in a future with
signiﬁcant climate change.

Dans l'ensemble, the strong case for ﬁshery management reform is maintained in a
world with signiﬁcant climate change.3 For the median ﬁshery, both the economic
and food provision cases for reform are slightly strengthened by climate change
(though by less than 1 percentage point). Cependant, because the effects are not
symmetric, the aggregate case is somewhat weakened (by about 3 percentage points
for harvest and 4 percentage points for value). While these results suggest that
Asian ﬁsheries would still do well to hasten the transition to economically optimized
ﬁshery management, they also point to substantial heterogeneity across ﬁsheries due

1The species list (shown in the Appendix) is the set of species for which ﬁsh catch is reported to the Food

and Agriculture Organization (FAO) in at least one of FAO regions 61, 71, ou 57 (FAO 2014).

2To keep values comparable, I assume that price and cost parameters are the same under BAU and optimized

ﬁshery management, and that these parameters are unaffected by climate change.

3All results in this paper use the representative concentration pathway 6.0 scénario.

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34 Revue du développement en Asie

to differences in (je) current status of ﬁsh populations, (ii) BAU management, (iii)
the biological effects of climate change, et (iv) anticipated geographic movement
under climate projections. Taken together, these results suggest that for many Asian
ﬁsheries, climate change will strengthen the case for management reforms. But in
some cases, I ﬁnd that the case gets substantially weaker; in these places, motivating
governments to undertake costly reforms will have to rely on other arguments or
sources of reform capital.

The rest of this paper is organized as follows. Section II discusses the
status and trends of major Asian ﬁsheries, and their management. Section III
provides theoretical guidance about the conditions under which climate change
might strengthen, or weaken, the case for ﬁshery management reform. Section IV
then focuses on the empirical estimates of the effects of climate change on Asian
ﬁsheries. The estimates of reform with and without climate change are presented in
section V. Enfin, section VI concludes.

II. Status of and Trends in Asian Fisheries

Ofﬁcial data from the Food and Agriculture Organization (FAO) show a
surprising and underrecognized trend in Asian versus non-Asian ﬁsh catch. While
global catch has been relatively constant over the past few decades (at approximately
80 million metric tons per year), the fraction of global catch produced in Asia has
steadily increased (Chiffre 2). Over the past 5 années, Asian catch has surpassed
the rest of the world combined, which represents a dramatic feat for a region
focused intently on increasing protein production from the sea (Cao et al. 2017).
Encore, questions remain about the underlying reasons for this dramatic divergence in
trends between Asia and non-Asian regions. The most common explanation is that
Asia’s catch is being propped up by increasingly aggressive ﬁshing efforts. Under
this explanation, ﬁsheries are progressively being overﬁshed and will eventually
collapse. The second possibility is that many large Asian ﬁsheries are thought to
have ﬁshed-down their immense stocks of predatory ﬁsh and that this allows for
a “predatory release” (Szuwalski et al. 2016). Under this explanation, catches of
smaller-bodied ﬁsh can be sustained at a much higher level than was previously
thought because their predator numbers have been reduced. But owing to the
immense diversity in Asian ﬁsh species, ﬁshery management institutions, et
economic conditions, the truth is almost certainly somewhere in between.4 The
model I use here will not allow us to distinguish between these underlying causes,
but it will allow us to track the likely species-by-species consequences of climate
change on Asia’s ﬁsheries.

Drawing concrete conclusions about Asian ﬁsheries is signiﬁcantly
hampered by the paucity of evidence on the biological status and trends for species

4See Cao et al. (2017) and Costello (2017) for further discussion of Asian ﬁshery objectives and trends.

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Does Climate Change Bolster the Case for Fishery Reform in Asia? 35

Chiffre 2. Fish Catch over Time—Asia versus the Rest of the World

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MMT = million metric tons.
Source: Food and Agriculture Organization (FAO). 2014. “The State of World Fisheries and Aquaculture.” Technical
Report of the Food and Agriculture Organization of the United Nations.

of ﬁsh harvested in Asia. While individual economies conduct some scientiﬁc
surveys (Melnychuk et al. 2017), almost no Asian ﬁsheries conduct or report
stock assessments. While Asian ﬁsheries supply over half of the global ﬁsh catch,
among the more than 500 ﬁsh stocks represented in the global Ram Legacy Stock
Assessment Database (Ricard et al. 2012), only about 1% are from Asia. À
overcome these extreme data gaps, recent contributions have provided data-poor
methods for estimating stock status and backing out the ﬁshing mortality rate that
is implied by reported ﬁsh catches. Costello et al. (2016) merge methods from
Costello et al. (2012) and Martell and Froese (2013) to estimate current biological
status (biomass of a ﬁsh stock relative to its biomass under maximum sustainable
yield (MSY), denoted as B/BMSY ) and current ﬁshing mortality rate (as a fraction
of ﬁshing mortality under MSY, denoted as F/FMSY ).

For an estimate of the current status of Asian stocks, we follow Gaines et al.
(2018) and aggregate ﬁsheries from Costello et al. (2016) at the species level, et
extract species whose geographic range extends into Asian waters. Here I make
some brief comments about the data underlying this analysis. Biomass and ﬁshing
mortality estimates are derived using a panel regression model (Costello et al. 2012)

36 Revue du développement en Asie

as priors for a structural model from ﬁshery science called the Catch–MSY method
(Martell and Froese 2013). This model also provides estimates of the biological
parameters for each individual stock, which are then aggregated at the species level
for species known to exist in Asian waters. Catch data are from FAO (2014) et
the Ram Legacy Stock Assessment Database (Ricard et al. 2012). Price and cost
parameters are species-level aggregations from Costello et al. (2016); the resulting
database of global ﬁsh prices has been published in Melnychuk et al. (2016) and cost
parameters are derived to rationalize the level of ﬁshing observed as formalized in
Costello et al. (2016). The relevant climate data, which describe the spatial footprint
of ﬁsh species now and in the future under alternative climate scenarios, are from
Molinos et al. (2016), who estimate the change in ocean temperatures over time
and associate that with species’ temperature preferences to estimate the geographic
range of a species in the future. After ﬁltering for the species that reside in Asian
waters, this leaves us with 193 species-level bioeconomic models with biological
parameters, spatial distributions, and changes in each over time under different
climate scenarios.5

The resulting 193 Asian ﬁsh species are displayed in Figure 3, where bubble
size indicates the potential size of the species’ ﬁsh catch (MSY) and shading
foretells the future climate effects estimated from the climate model that will be
described later (lighter shade for positive effects on carrying capacity and darker
shade for negative effects on carrying capacity).6 Using this approach, the median
values for B/BMSY and F/FMSY are both near 1; this may initially suggest that Asian
ﬁsheries are in reasonable condition. But a closer inspection of Figure 3 reveals a
stark contrast between two classes of ﬁsheries. Those in the top left of Figure 3 sont
in poor condition. According to this model, these ﬁsheries have been overﬁshed,
driving their biomass below levels that which would maximize food provision, et
they continue to be ﬁshed at an excessive rate.7 Many of the medium-sized and
large Asian ﬁsheries (bubble size), and the ﬁsheries that will be negatively impacted
by climate change (darker shade), are in this region of the ﬁgure. The second
major group consists of ﬁsheries in the bottom right of Figure 3. These ﬁsheries
appear to be underﬁshed, at least so far as food production is concerned. Many
of these biologically abundant species are expected to be positively affected by
climate change. When combined, these features suggest that there may be important
possibilities for future growth in some of these ﬁsheries.

5I will not repeat here all of the data caveats from these previous papers. But it sufﬁces to say that these
estimates are subject to many qualiﬁcations, therefore all of these results should be viewed with some degree of
caution.

6The unit of analysis in this article is technically a species of ﬁsh residing in Asian waters as extracted and

reported from Gaines et al. (2018). For exposition, I also refer to species as either stocks or ﬁsheries.

7As with most bioeconomic models, the one used here ﬁnds that the level of ﬁsh biomass that maximizes

steady state ﬁshery proﬁt exceeds BMSY by about 20%–30%.

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Does Climate Change Bolster the Case for Fishery Reform in Asia? 37

Chiffre 3. Status and Fishing Pressure for Asian Fish Stocks

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MSY = maximum sustainable yield.
Note: Size indicates MSY and shading indicates whether climate change is expected to have a positive (lighter shade)
or negative (darker shade) effect on carrying capacity through 2100.
Source: Author’s analysis of data from Gaines, Steven, Christopher Costello, Brandon Owashi, Tracey Mangin,
Jennifer Bone, Jorge Garcia Molinos, Merrick Burden, Heather Dennis, Ben Halpern, Carrie Kappel, Kristen
Kleisner, and Dan Ovando. 2018. “Fixing Fisheries Management Could Offset Many Negative Effects of Climate
Change.” Science Advances. Forthcoming.

III. Climate Change and Fishery Reforms—Theory

The basic question this paper poses is whether the case for ﬁshery
management reform that has been established in the absence of climate change
will be maintained in a future with aggressive climate change. Dans cette section, je
develop the theory underpinning the empirical analysis that follows. Consider a
single ﬁshery in discrete-time with period-t biomass given by Bt . The fraction of
the ﬁsh stock that is extracted in year t is given by Ft, so the harvest is given
by Ht = FtBt. Price is assumed to be constant, p, and harvesting costs depend on
for some constants c ≥ 0 and β ≥ 1.8
aggregate ﬁshing mortality, so cost is cF B
t

8This nests the canonical bioeconomic model in which β = 1, but allows for the possibility that early

applications of ﬁshing effort are the most efﬁcient; donc, additional units of effort are increasingly costly.

38 Revue du développement en Asie

This implies that period-t proﬁt of the ﬁshery is

πt (Ft, Bt, Kt ) = pHt − cF
t

(1)

where I have made explicit the dependence on ﬁshing mortality (Ft ), biomass of
the stock (Bt ), and carrying capacity (Kt ), which will capture the effects of climate
change on the growth of the ﬁsh stock.

But the ecosystem places natural constraints on an economy’s harvesting

decisions. Let the growth of the ﬁsh stock be given by the following:

Bt+1 = B (t ) +

φ + 1

φ gBt

(cid:5)

(cid:2)

(cid:4)φ

(cid:3)

Bt
Kt

1 −

− Ht

(2)

This biological growth equation (known as the Pella–Tomlinson model)
contains three parameters: (je) g, which is related to the maximum (or “intrinsic”)
growth rate of the stock; (ii) φ, which governs the skewness of the familiar
hump-shape of growth function; et (iii) Kt, which is the carrying capacity of the
stock.9 This functional form is quite general and nests two familiar examples. D'abord,
in equation (2), I have allowed the carrying capacity (Kt ) to vary over time; dans
this paper, Kt reﬂects the climate state in year t. Par exemple, if climate change is
expected to reduce the overall suitable geographic range of a stock by 2% per year,
I follow Gaines et al. (2018) and interpret this as a change in carrying capacity (donc
Kt declines by 2% per year). This interpretation of carrying capacity allows climate
impacts to have year-by-year effects on ﬁsh stock growth. Deuxième, the special case
where φ = 1 delivers the familiar logistic growth equation (with carrying capacity
Kt and intrinsic growth rate 2g).

Naturellement, the consequences of climate change on any given ﬁshery will hinge
not only on the environmental effects, but also on the way in which the ﬁshery is
managed. As a measure of the economic beneﬁt of ﬁshery reform without climate
changement, I calculate the net present value (NPV) under the BAU ﬁshing mortality
rate (again without climate change); denoted as ¯F−CC, these are the “Fishing
Pressure” values in Figure 3 and are compared to the NPV under economically
optimized ﬁshery management, denoted as F ∗
−CC (Bt ). To calculate the optimized
feedback control rule, F ∗
−CC (Bt ), I use a discrete-time dynamic programming
approche, with numerical-value-function iteration and backward induction using
Kt = K0, thus assuming that climate change is not occurring. I work backward
until the value and policy functions converge. I then forward simulate using the
converged policy function from the starting conditions shown in Figure 3 to obtain
¯V−CC (NPV under BAU without climate change), V ∗
−CC (optimized NPV without
climate change), ¯H−CC (cumulative harvest 2012–2100 under BAU without climate
changement), and H ∗
−CC (cumulative harvest 2012–2100 under optimized NPV without
climate change).

9All parameters were extracted from Gaines et al. (2018).

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Does Climate Change Bolster the Case for Fishery Reform in Asia? 39

In a similar manner, when climate change is present, I calculate the NPV and
harvest under a BAU policy and an optimized policy. But which policies to use? Pour
the optimized policy, since Kt can change each year in the climate change scenario,
it could be treated as a state variable, which would give rise to a policy function
that conditioned on Kt (as well as Bt). Under that fully adaptive assumption, le
fully optimal policy function would take the form F ∗
CC (Bt, Kt ), so effectively there
would be a different optimized harvest control policy function every year that fully
anticipated the future effects of climate change. While this may seem farfetched, it
would provide a useful benchmark because it would represent the highest possible
NPV that any ﬁshery could attain under climate change. Mais, I do not conduct this
additional optimization for three reasons. D'abord, doing so would presume that the
ﬁshery manager had perfect foresight about climate effects in all ﬁsheries over the
next 80 years and was able to perfectly reoptimize her policy function every year
in anticipation of those changes. This seems implausible because of information
and policy constraints that often prevent such nimble policy responses. The second
reason is that I have conducted this optimization for three ﬁsheries (representing the
5ème, 50ème, and 95th percentiles of change in K due to climate change) and found that
it makes almost no difference in the ultimate NPV of the ﬁshery. The percentage
increases in value from using the F ∗
CC (Bt ) politique
sont 0.36%, 0.001%, et 0.02%, respectivement, for the 5th, 50ème, and 95th percentile
ﬁsheries; the commensurate differences in aggregate harvest in 2012–2020 are
3.9%, 0.01%, et 0.04%, respectively.10 The ﬁnal reason is that conducting this
optimization for all 193 ﬁsheries is very time consuming.

CC (Bt, Kt ) policy instead of the F ∗

CC (Bt ) = F ∗

For these reasons, I continue to use the same optimized feedback control
rule derived above, so F ∗
−CC (Bt ) from the dynamic programming value
function iteration procedure described above. For the BAU policy under climate
changement, I allow for the possibility raised in Gaines et al. (2018), who argue that
range shifts induced by climate change could lead to institutional failures that
increase ﬁshing pressure. En même temps, it seems irrational to assume that ﬁshing
would extend beyond what is economically viable.

To capture these features, I analyze two different models of BAU ﬁshing
pressure (Tableau 1). In both models, BAU ﬁshing pressure is initially ¯F−CC (as in
the case without climate change). In the ﬁrst model, I assume ﬁshing pressure for
shifting stocks gradually shifts to the open access level of ﬁshing pressure (pour
which economic proﬁt is zero in steady state) over time as range shifts take hold. Dans
the second model, I assume BAU ﬁshing pressure is unaffected by climate change,
so ¯FCC = ¯F−CC forever.

Across these models,

I evaluate two different measures of ﬁshery
performance. The ﬁrst is the NPV of the ﬁshery from 2012 à 2100, and the second

10These ﬁsheries are Paciﬁc rudderﬁsh (dont 2100 K is only 62% of its current K), Bartail ﬂathead (dont

2100 K is 99.7% of its current K), and Akiami paste shrimp (dont 2100 K is 110% of its current K).

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Tableau 1. Fishing Policies with and without Climate Change

Policy

BAU
Optimized

Changement climatique?

Non
¯F−CC
F ∗
−CC (Bt )

Oui
¯F−CC to ¯FOA or ¯F−CC forever
F ∗
CC (Bt )

BAU = business as usual.
Source: Author’s compilation.

is the cumulative harvest over the same time period. For any given ﬁshery, ces
values will depend on the starting conditions (Chiffre 3), policy function (Tableau 1),
and climate change impact on carrying capacity (Chiffre 6).

The NPV of the ﬁshery under any climate trajectory and any policy function

is given by
(cid:3)

T(cid:6)

V =

t=0

(cid:4)
t

1
1 + r

πt (Ft, Bt, Kt )

(3)

where r = 5% is the discount rate and the equation is subject to equation (2). Ce
implies that there are four relevant values to calculate for the NPV and four relevant
values for H:

• NPV calculations

(cid:7)
¯V−CC
– No climate change, BAU management
(cid:7)
V ∗
– No climate change, optimized management
(cid:7)
(cid:8)
−CC
¯VCC
– Climate change, BAU management
(cid:7)
(cid:8)
V ∗
– Climate change, optimized management
CC

(cid:8)

• Cumulative harvest calculations

(cid:7)
¯H−CC
– No climate change, BAU management
(cid:7)
H ∗
– No climate change, optimized management
(cid:8)
−CC
¯HCC
– Climate change, BAU management
(cid:8)
(cid:7)
– Climate change, optimized management

(cid:8)

(cid:7)

H ∗
CC

(cid:8)

This paper seeks to determine the ﬁrst differences:

• percentage loss from failing to optimize management without climate change:

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(cid:5)(cid:6)−CC ≡

(cid:6)∗

−CC

− ¯(cid:6)−CC

(cid:6)∗

−CC

(cid:8)

(cid:7)
H ∗
CC

• percentage loss from failing to optimize management with climate change:

(cid:5)(cid:6)CC ≡

− ¯(cid:6)CC

(cid:6)∗
CC
(cid:6)∗

−CC

(4)

(5)

Does Climate Change Bolster the Case for Fishery Reform in Asia? 41

where the outcome variable (cid:6) can either be NPV (V) or cumulative harvest (H) depuis
2012 à 2100. Par exemple, (cid:5)V−CC provides a measure of what is lost by adhering
to BAU management, rather than optimizing the management of the ﬁshery, dans le
absence of climate change.11 These values are represented in Figure 7 (where BAU
ﬁshing pressure is given by the transition to open access for shifting stocks) et
Chiffre 8 (where BAU ﬁshing pressure is unchanged under climate change).

And our main statistic of interest will be the difference in these differences,

expressed as a percentage point change:

(cid:5)(cid:6) ≡ (cid:5)(cid:6)CC − (cid:5)(cid:6)−CC

(6)

Par exemple, si (cid:5)V = 5 percentage points for a particular ﬁshery, this would
indicate that the case for ﬁshery reform is 5 percentage points stronger in a world
with climate change than it is in a world without climate change. Bien sûr, nous
expect this statistic to be positive for some ﬁsheries and negative for others. These
values are represented in Figures 9 et 10 below.

Theoretical Guidance

Does theory provide any guidance about how we might expect climate
change to affect the value of ﬁshery management optimization? D'abord, whether or
not climate change occurs, we expect that optimizing the management of a ﬁshery
will lead to an increase in economic value. Autrement dit, we expect (cid:5)V−CC > 0
et (cid:5)VCC > 0. And while we generally expect ﬁshery proﬁt and ﬁshery catch to
go hand-in-hand, ﬁshing costs (c in equation 1) imply that it is possible for an
intervention to increase proﬁt but decrease catch.12 But as a general rule, we expect
(cid:5)H−CC > 0 et (cid:5)HCC > 0 for most ﬁsheries; when these values are negative, nous
expect them to be small in absolute value.

But how will (cid:5)V−CC and (cid:5)VCC compare with each other? Autrement dit,
calculating (cid:5)V (cid:2) 0 will determine whether the presence of climate change
increases or decreases the economic case for ﬁshery management reform. De la même manière,
calculating (cid:5)H (cid:2) 0 will determine whether the presence of climate change
increases or decreases the food production case for reform. While the answers
will turn out to depend on current conditions, BAU management, and the dynamic
effects of climate change for any particular ﬁshery, some broad generalizations are
possible. D'abord, for ﬁsheries that will experience a reduction in carrying capacity

11The denominators in equations (4) et (5) are the same. Normalizing both by the no-climate change
scenario facilitates their comparison as percentage point differences later in the paper. Also note that the denominator
is the optimized value (cid:6)∗
−cc rather than the preoptimized value. This is because under some open access scenarios
the preoptimized value can be negative so the percentage would not make sense. The interpretation of these values is
the percentage loss from failing to optimize rather than the percentage gain from optimizing.

12Par exemple, suppose the ﬁshery is already managed to maximize sustainable yield. Then a management

change to optimize NPV will necessarily decrease long-run catch.

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42 Revue du développement en Asie

Chiffre 4. Steady-State Fishery Production with and without Climate Change for a Fishery
with Globally Median Parameters

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Note: The solid line is without climate change and the dashed line is with a hypothetical 60% reduction in carrying
capacity from climate change.
Source: Author’s calculations from globally median parameters extracted from Costello, Christophe, Daniel
Ovando, Tyler Clavelle, C. Kent Strauss, Ray Hilborn, Michael C. Melnychuk, Trevor A. Branch, Steven D.
Gaines, Cody S. Szuwalski, Reniel B. Cabral, Douglas N. Rader, and Amanda Leland. 2016. “Global Fishery
Prospects Under Contrasting Management Regimes.” Proceedings of the National Academy of Sciences 113 (18):
5125–29.

from climate change, it is reasonable to expect a reduction in both the maximum
ﬁsh catch and the maximum value of the ﬁshery. Par exemple, Chiffre 4 shows the
production function for a ﬁshery with the median global parameters, where the solid
line uses current parameters (no climate change) and the dashed line assumes a
60% reduction in carrying capacity resulting from climate change. Production with
climate change is everywhere below production without climate change, reﬂecting
the reduction in carrying capacity. This logic seems to suggest that ﬁsheries that
will suffer reductions in carrying capacity are likely to gain less from management
reform than are ﬁsheries that will experience increases in carrying capacity.

But this logic turns out to depend on the current level of ﬁshing pressure. If
BAU ﬁshing pressure is very high (par exemple., if the ﬁshery is in open access equilibrium),
then the logic holds ﬁrmly because the ﬁshery is currently experiencing low (ou
zero) proﬁt and low catch. Optimizing such a ﬁshery eventually brings about
positive increases whether or not climate change occurs, but climate change
increases the case for reform only if it will increase carrying capacity. Alternativement,

Does Climate Change Bolster the Case for Fishery Reform in Asia? 43

Chiffre 5. Steady-State Economic Upside from Reform for a Fishery with Globally
Median Parameters

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BAU = business as usual.
Note: The solid line is without climate change and the dashed line is with a hypothetical 60% reduction in carrying
capacity from climate change.
Source: Author’s calculations from globally median parameters extracted from Costello, Christophe, Daniel Ovando,
Tyler Clavelle, C. Kent Strauss, Ray Hilborn, Michael C. Melnychuk, Trevor A. Branch, Steven D. Gaines, Cody
S. Szuwalski, Reniel B. Cabral, Douglas N. Rader, and Amanda Leland. 2016. “Global Fishery Prospects Under
Contrasting Management Regimes.” Proceedings of the National Academy of Sciences 113 (18): 5125–29.

if BAU ﬁshing pressure is very low (take the extreme case when it is zero), then the
logic also holds because under BAU both proﬁt and catch are low (or zero). But for
intermediate levels of ﬁshing pressure, it turns out that the logic can break down.
Chiffre 5 shows the increase in steady-state proﬁt (again for a ﬁshery with globally
median parameters) that arises from ﬁshery management reform as a function of
BAU ﬁshing pressure. The solid line depicts the upside from reform without climate
change and the dashed line depicts it with a 60% drop in carrying capacity resulting
from climate change. To see how a deleterious climate shock could actually increase
the beneﬁts from reform, consider the following example. Suppose BAU ﬁshing
pressure is about 0.9, which is near the proﬁt-maximizing ﬁshing pressure in the
absence of climate change (solid line in Figure 5). In that case, the economic
upside from reform (in the absence of climate change) is near zero. But how
does the economic upside from reform change after a deleterious climate shock
(dashed line)? After climate change, the optimal level of ﬁshing pressure declines
(to about 0.75) and the upside from reform, given that BAU ﬁshing pressure is

44 Revue du développement en Asie

0.9, is nonnegligible. This example is simply meant to illustrate the possibility that
a negative climate shock does not necessarily imply a lower beneﬁt from ﬁshery
management reform.

The bioeconomic models I apply to Asian ﬁsheries are substantially more
complicated than the simple illustrative examples from Figures 4 à 5. The effects
of climate change play out over time, starting conditions differ across ﬁsheries,
BAU and optimized policies have effects that evolve over time, and optimal policies
are dynamically (not statically) optimized. While the intuition provided above can
provide some guidance, it is ultimately an empirical question whether the presence
of climate change will strengthen or weaken the case for management reform in any
given Asian ﬁshery.

IV. The Effects of Climate Change on Asian Fisheries

Following Gaines et al. (2018), the myriad effects of climate change on
global ﬁsheries can be distilled into two categories. The ﬁrst, and most widely
studied, is that climate change may alter the stock growth of a ﬁshery, which is
often interpreted as a change in carrying capacity. This can occur through changes
in prey abundance, ocean temperatures, acidiﬁcation, or via other mechanisms. Le
second consequence of climate change is that it can alter the spatial range of a
species in the ocean. Even in the absence of carrying capacity changes, range shifts
can have signiﬁcant consequences to ﬁshery sustainability because as a ﬁsh stock
crosses international boundaries, institutional failures can lead to overexploitation.
I thus assume that the major effects of climate change can be captured by
changes in carrying capacity and shifts in geographic range over time. Changes in
the total geographic area suitable for a species correspond to changes in carrying
capacity over time. Chiffre 6 shows the individual trajectories of carrying capacity
for each of the 193 species in this analysis under a representative concentration
pathway 6.0 climate change scenario; among these species, 55% will decline in
carrying capacity and 45% will increase. The line thickness in Figure 6 corresponds
to MSY (so it varies over time for each stock, in accordance with changes in Kt)
and the shading corresponds to scaled Kt; all values are relative to the 2012 valeur.
Among the species studied, 61% will experience a reduction in carrying capacity
and/or signiﬁcant range shifts as a result of climate change; the other 39% will
experience positive effects.

To capture these effects of climate change on a species’ carrying capacity
and range, we must somehow translate them into the bioeconomic model presented
au-dessus de. D'abord, we keep track of the carrying capacity in each year for each species
(Chiffre 6), and this becomes an input into the model itself (see equation 2). À
capture range shifts, we make no changes to the model when a stock is a stationary
stock (c'est, when it stays within a country’s waters). But for the 29% of species

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Does Climate Change Bolster the Case for Fishery Reform in Asia? 45

Chiffre 6. Effects of Climate Change on Carrying Capacity of Asian Fish Stocks

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Remarques: Each line represents an Asian ﬁsh species. Shading indicates carrying capacity (relative to 2012 valeur) et
thickness indicates maximum sustainable yield (MSY) of the stock.
Source: Author’s analysis of data from Gaines, Steven, Christopher Costello, Brandon Owashi, Tracey Mangin,
Jennifer Bone, Jorge Garcia Molinos, Merrick Burden, Heather Dennis, Ben Halpern, Carrie Kappel, Kristen
Kleisner, and Dan Ovando. 2018. “Fixing Fisheries Management Could Offset Many Negative Effects of Climate
Change.” Science Advances. Forthcoming.

that are shifting stocks, I run two scenarios. In the ﬁrst scenario, the BAU ﬁshery
policy gets progressively worse as these transboundary shifts start to take hold. Dans
the second scenario, ﬁshing pressure for shifting stocks is unaffected by climate
changement. All of these assumptions are summarized as follows:

• Changes in ﬁsh stock growth

– Changes in carrying capacity, K, au fil du temps: Kt (Chiffre 6) is an input to the

biological model (equation 2) and thus to the forward simulations.

– BAU policy under climate change: ﬁsh at the current ﬁshing mortality rate

(except for shifting stocks, see below)

– Optimized policy under climate change: use the dynamically optimized

harvest control rule under current conditions.

• Range shifts

– “Stationary stocks” have policy functions as indicated above.
– “Shifting stocks,” or those that are expected to cross signiﬁcantly into multiple

jurisdictions (Gaines et al. 2018), are treated as follows:

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· Under BAU, the initial ﬁshing mortality rate is the current ﬁshing mortality
rate. It either gradually transitions to the ﬁshing mortality rate under open
access according to when the shifts are expected to occur, or it is maintained
at the current ﬁshing mortality rate; both scenarios are examined below.
· Under optimized management, the harvest policy is optimized (sous

current conditions), so range shifts are internalized into the policy.

V. The Value of Fishery Management Reform for Asian Species

Detailed information on ﬁshery management in Asia is extremely hard to
come by. Most available evidence suggests that ﬁshery management institutions are
somewhat outdated and rely heavily on input controls such as season length; gear
restrictions; et, in some cases, limited licenses. But there seem to be very few cases
of feedback control rules, such as harvest control rules, that are now the backbone
of ﬁshery policy in Australia, Canada, the United States, and much of Europe and
Latin America. I use the model described above to estimate the economic and food
provision beneﬁts of adopting ﬁshery management reforms in Asian ﬁsheries.

In the absence of climate change, the beneﬁts of management reforms
vary by ﬁshery, but adopting economically rational ﬁshery management generally
increases both cumulative harvest (horizontal axis of Figure 7) and economic value
(vertical axis of Figure 7) relative to BAU. The average effect of implementing
optimized ﬁshery management is expected to increase catch by about 24% et
economic value by 34%, though these values range widely across ﬁsheries. Le
comparable results in a world with climate change are shown in Figure 8, où
the shading refers to whether climate change is expected to have a positive (lighter
shade) or negative (darker shade) effect on ﬁsh stock growth. With climate change,
the beneﬁts of reform are still large (visuellement, there is little difference between
Figures 7 et 8). But the average effects of reform are slightly muted here (reform
increases catch by 21% and economic value by 30%). The next section explicitly
focuses on the difference between these two sets of results.

How Does Climate Change Affect the Value of Fishery Reform in Asia?

The main question this paper seeks to ask is: does climate change undermine
the case for ﬁshery management reform in Asia? I conclude with an emphatic “no.”
Perhaps the best evidence is from Figure 8, which shows that there remains a large
beneﬁt of ﬁshery management reform in nearly all Asian ﬁsheries despite the onset
of climate change. A more nuanced question is: does climate change strengthen
or weaken the case for ﬁshery management reform? Essentially, this amounts to
the difference between Figure 8 and Figure 7, which is depicted in Figure 9 comme
percentage point changes for each individual ﬁshery.

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Does Climate Change Bolster the Case for Fishery Reform in Asia? 47

Chiffre 7. The Value of Reforming Asian Fisheries without Climate Change as a Fraction
of Optimized Value without Climate Change

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MSY = maximum sustainable yield, NPV = net present value.
Source: Author’s analysis of data from Gaines, Steven, Christopher Costello, Brandon Owashi, Tracey Mangin,
Jennifer Bone, Jorge Garcia Molinos, Merrick Burden, Heather Dennis, Ben Halpern, Carrie Kappel, Kristen
Kleisner, and Dan Ovando. 2018. “Fixing Fisheries Management Could Offset Many Negative Effects of Climate
Change.” Science Advances. Forthcoming.

For stationary stocks (triangles in Figure 9), climate change only affects
carrying capacity (it does not affect BAU management). For these stocks, le
intuition provided in section III was that carrying capacity increases and the
case for reform typically go hand-in-hand. En effet, this seems to be the case
for Asian ﬁsheries: those for which carrying capacity shocks will be positive
(lighter triangles) tend to have a stronger case for reform (in both harvest and
economic value), and those for which carrying capacity shocks will be negative
(darker triangles) tend to have a weaker case for reform. For stationary stocks, le
overall conclusion is that climate change will generally bolster the case for ﬁshery
management reform in Asia.

But the story can be considerably different for Asian stocks for which we
anticipate future range shifts resulting from climate change (circles in Figure 9,
which reﬂect the assumption that BAU ﬁshing pressure gradually shifts to open
access for shifting stocks). For those stocks, climate change induces potentially
devastating institutional failure, which drives a possibly large wedge between the

48 Revue du développement en Asie

Chiffre 8. The Value of Reforming Asian Fisheries under Climate Change as a Fraction of
Optimized Value without Climate Change

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MSY = maximum sustainable yield, NPV = net present value.
Note: Shading indicates whether climate change is expected to have a positive (lighter shade) or negative (darker
shade) effect on carrying capacity through 2100.
Source: Author’s analysis of data from Gaines, Steven, Christopher Costello, Brandon Owashi, Tracey Mangin,
Jennifer Bone, Jorge Garcia Molinos, Merrick Burden, Heather Dennis, Ben Halpern, Carrie Kappel, Kristen
Kleisner, and Dan Ovando. 2018. “Fixing Fisheries Management Could Offset Many Negative Effects of Climate
Change.” Science Advances. Forthcoming.

value of the ﬁshery with and without reform. This complicates the calculus. While
many shifting stocks are also negatively affected by climate change, the case for
reform can either be strengthened (circles in upper right of Figure 9) or weakened
(circles in lower left of Figure 9) by the onset of climate change. Taken together,
these results suggest that despite climate change, the case for ﬁshery reform remains
strong in Asia, though the case can be weakened for some stocks.

To test the importance of the BAU assumption for shifting stocks, I repeat the
same analysis for the alternative BAU scenario. In the results depicted in Figure 9,
the BAU policy under climate change was for stationary stocks to continue at their
current ﬁshing mortality rate and for shifting stocks to transition to open access
ﬁshing pressure. The alternative is to treat shifting stocks in the same manner
as stationary stocks (so they maintain the current ﬁshing mortality rate). In that
case, the basic story stands but the case for reform is even stronger. In both the

Does Climate Change Bolster the Case for Fishery Reform in Asia? 49

Chiffre 9. Does Climate Change Strengthen the Case for Fishery Reform in Asia? BAU
Fishing Pressure Gradually Shifts to Open Access for Shifting Stocks

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no-climate change and the climate change scenarios, the beneﬁts of reform are
21%–24% (increase in harvest from reform) and 30%–34% (increase in economic
value from reform), suggesting that climate change does not dramatically alter the
case for reform. The ﬁshery-by-ﬁshery results for this scenario are depicted in
Chiffre 10, which conform to the theoretical expectation that the case for reform
will generally be strengthened for stocks that experience a positive climate shock
(lighter shade) and weakened for stocks that experience a negative climate shock
(darker shade).

Returning to the original BAU assumption, we can aggregate the data
underlying Figure 9 to the FAO ﬁsh category level to provide a glimpse into the
types of ﬁsh for which climate change is likely to strengthen or weaken the case
for ﬁshery reforms (recognizing that the case for reform remains strong in nearly
all cases). Tableau 2 reports (cid:5)H and (cid:5)V for the seven ﬁsh categories with MSY > 1
million metric tons (reported as percentage point gains as a consequence of climate
changement). These data suggest that the case for reform is strengthened for the large
class of cods, hakes, and haddocks, but weakened (sometimes substantially) pour

50 Revue du développement en Asie

Chiffre 10. Does Climate Change Strengthen the Case for Fishery Reform in Asia?

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MSY = maximum sustainable yield, NPV = net present value.
Note: Plotted for all stocks under the alternative business-as-usual assumption (with climate change, all stocks are
ﬁshed at their current ﬁshing mortality rate).
Source: Author’s analysis of data from Gaines, Steven, Christopher Costello, Brandon Owashi, Tracey Mangin,
Jennifer Bone, Jorge Garcia Molinos, Merrick Burden, Heather Dennis, Ben Halpern, Carrie Kappel, Kristen
Kleisner, and Dan Ovando. 2018. “Fixing Fisheries Management Could Offset Many Negative Effects of Climate
Change.” Science Advances. Forthcoming.

Tableau 2. Effect of Climate Change on the Case for Reform by Major
Fish Category

Category

Stocks
(No.)

MSY
(MMT)

BMSY
(MMT)

(cid:2)H

(cid:2)V

5
23
36
11
18
21
5

4.83
4.86
1.48
3.98
6.06
4.45
1.02

72.22
48.31
21.58
82.49
35.74
36.87
17.75

Cod, hake, haddock
Misc. pelagic ﬁshes
Misc. coastal ﬁshes
Herring, sardines, anchovy
Tuna, bonito, billﬁsh
Misc. demersal ﬁshes
Salmon, trout, smelt

9.66
6.03
2.25
1.75
−6.50
1.46
−0.62
1.44
−0.30
0.19
−2.74
−5.59
−31.48 −23.18
BMSY = biomass under maximum sustainable yield, MMT = million metric tons, MSY =
maximum sustainable yield.
Source: Author’s analysis of data from Gaines, Steven, Christopher Costello, Brandon Owashi,
Tracey Mangin, Jennifer Bone, Jorge Garcia Molinos, Merrick Burden, Heather Dennis,
Ben Halpern, Carrie Kappel, Kristen Kleisner, and Dan Ovando. 2018. “Fixing Fisheries
Management Could Offset Many Negative Effects of Climate Change.” Science Advances.
Forthcoming.

Does Climate Change Bolster the Case for Fishery Reform in Asia? 51

other groups such as salmon and smelts. Some groups show the interesting pattern
that the case for harvest is weakened but the case for economic value is strengthened
(par exemple., herrings, sardines, and anchovies). The table also provides the number of
species composing each category and measures of ﬁshery size (MSY) and overall
biomass (BMSY). Four of the ﬁve largest classes of ﬁsh are expected to have a
stronger economic rationale for reform with climate change than without climate
changement.

VI. Conclusions

The focus of this paper has been on whether climate change undermines
the case for ﬁshery management reform in Asia. While the Asia-wide answer is
“no,” the answer for any given species turns out to hinge on the exact manner in
which climate change will inﬂuence the species. For sedentary stocks, the main
effect of climate change is on the carrying capacity, and thus the overall growth
of the ﬁsh stock. If the carrying capacity of a stock is expected to decline under
climate change, then the case for ﬁshery reform is generally weakened; the opposite
holds for cases when the carrying capacity will increase in the future. While the
model results support this prediction, the weakening of the case for reform is quite
petit (less than 5 percentage point changes), even when climate change will have
deleterious effects. The other signiﬁcant implication of climate change, which has
largely gone unnoticed by the previous literature, is that the ranges of some stocks
will change. When ﬁsh stocks move into new jurisdictions, this can cause a race
to ﬁsh and may result in worse outcomes than if the same stock had not crossed
a jurisdictional boundary. Fisheries for which this second effect is present see a
much wider range of outcomes, which largely hinge on how aggressively they are
currently managed.

Dans l'ensemble, these results suggest that the vast majority of Asian ﬁsheries,
including its largest ones, would beneﬁt economically and in terms of food security
by engaging in ﬁshery management reforms. Across Asia, I ﬁnd that such reforms
could lead to increases of 30% in the present value of ﬁsheries and 21% dans
food provision, even under impending climate change. This implies that Asian
ﬁsheries should hasten the transition to sensible, economically rational ﬁshery
management under current climate conditions; this will simultaneously secure food
and livelihoods across Asia’s diverse ﬁsheries, even in the face of climate change.

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Does Climate Change Bolster the Case for Fishery Reform in Asia? 53

Appendix

This table contains the scientiﬁc and common names for each of the 193
species in the Asia data set used in this paper. Among these are several names
of economies, which represent aggregated species according to the Food and
Agriculture Organization’s not elsewhere included (nei) catégorie (par exemple., Singapore
nei 110).

Table A1. Scientiﬁc and Common Names of Fisheries Used in this Analysis

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38

Scientiﬁc Name

Argyrosomus hololepidotus
Stephanolepis cirrhifer
Tenualosa toli
Atrobucca nibe
Konosirus punctatus
Genypterus blacodes
Scomberomorus lineolatus
Ruditapes philippinarum
Oncorhynchus gorbuscha
Nemipterus virgatus
Ilisha elongata
Portunus trituberculatus
Scomberomorus niphonius
Todarodes paciﬁcus
Oncorhynchus tshawytscha
Muraenesox cinereus
Psenopsis anomala
Tenualosa ilisha
Conger myriaster
Clupanodon thrissa
Mene maculata
Seriolella punctata
Erimacrus isenbeckii
Pennahia argentata
Berryteuthis magister
Paralichthys olivaceus
Sardinella longiceps
Pterygotrigla polyommata
Atheresthes evermanni
Nemadactylus macropterus
Lactarius lactarius
Crassostrea gigas
Trochus niloticus
Miichthys miiuy
Sardinella lemuru
Psettodes erumei
Chelidonichthys kumu
Jasus edwardsii

Common Name
Southern meagre (=Mulloway)
Threadsail ﬁleﬁsh
Toli shad
Blackmouth croaker
Dotted gizzard shad
Pink cusk-eel
Streaked seerﬁsh
Japanese carpet shell
Pink (=Humpback) salmon
Golden threadﬁn bream
Elongate ilisha
Gazami crab
Japanese Spanish mackerel
Japanese ﬂying squid
Chinook (=Spring=King) salmon
Daggertooth pike conger
Paciﬁc rudderﬁsh
Hilsa shad
Whitespotted conger
Chinese gizzard shad
Moonﬁsh
Silver warehou
Hair crab
Silver croaker
Schoolmaster gonate squid
Bastard halibut
Indian oil sardine
Latchet(=Sharpbeak gurnard)
Kamchatka ﬂounder
Tarakihi
False trevally
Paciﬁc cupped oyster
Commercial top
Mi-iuy (brown) croaker
Bali sardinella
Indian halibut
Blueﬁn gurnard
Red rock lobster

Continued.

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Table A1. Continued.

Scientiﬁc Name

Common Name

39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87

Rastrelliger brachysoma
Rexea solandri
Ammodytes personatus
Singapore
Seriolella brama
Sillago ﬂindersi
Arctoscopus japonicus
Callorhinchus milii
Makaira nigricans
Chanos chanos
Cromileptes altivelis
Thaïlande
Palau
Haliotis rubra
Megalops cyprinoides
Oncorhynchus nerka
Cololabis saira
Plectropomus leopardus
Acanthocybium solandri
Amblygaster sirm
Arripis trutta
People’s Republic of China
Pagrus auratus
Sillago sihama
Cambodia
Isurus oxyrinchus
Lates calcarifer
Trachysalambria curvirostris
Taipei,Chine
Ruvettus pretiosus
Scylla serrata
Mugil cephalus
Selaroides leptolepis
Euthynnus afﬁnis
Republic of Korea
Prionace glauca
Tonga
Epinephelus merra
Oncorhynchus keta
Portunus pelagicus
Decapterus russelli
Rastrelliger kanagurta
Eleutheronema tetradactylum
Pomadasys argenteus
Thunnus obesus
Melicertus latisulcatus
Pseudopleuronectes herzensteini
Vanuatu
Platycephalus conatus

Short mackerel
Silver gemﬁsh
Paciﬁc sandlance
nei_110
Common warehou
Flinders’ sillago
Japanese sandﬁsh
Ghost shark
Blue marlin
Milkﬁsh
Humpback grouper
nei_122
nei_92
Blacklip abalone
Indo-Paciﬁc tarpon
Sockeye (=Red) salmon
Paciﬁc saury
Leopard coralgrouper
Wahoo
Spotted sardinella
Australian salmon
nei_20
Silver seabream
Silver sillago
nei_15
Shortﬁn mako
Barramundi (=Giant seaperch)
Southern rough shrimp
nei_120
Oilﬁsh
Indo-Paciﬁc swamp crab
Flathead grey mullet
Yellowstripe scad
Kawakawa
nei_115
Blue shark
nei_124
Honeycomb grouper
Chum (=Keta=Dog) salmon
Blue swimming crab
Indian scad
Indian mackerel
Fourﬁnger threadﬁn
Silver grunt
Bigeye tuna
Western king prawn
Yellow striped ﬂounder
nei_133
Deep-water ﬂathead

Continued.

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Does Climate Change Bolster the Case for Fishery Reform in Asia? 55

Table A1. Continued.

Scientiﬁc Name

Common Name

88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136

Platycephalus indicus
Indonésie
Saurida tumbil
Selar crumenophthalmus
Fiji
Istiompax indica
Penaeus semisulcatus
Trachurus declivis
Herklotsichthys quadrimaculatus
Scomber australasicus
Chirocentrus dorab
Japan
Timor-Leste
Federated States of Micronesia
Megalaspis cordyla
Zenopsis nebulosa
Beryx decadactylus
Tetrapturus angustirostris
Penaeus monodon
Marsupenaeus japonicus
Thunnus albacares
Oncorhynchus kisutch
Zeus faber
Scomberomorus commerson
Istiophorus platypterus
Katsuwonus pelamis
Sepioteuthis lessoniana
Thyrsites atun
Cephalopholis boenak
Decapterus maruadsi
Kajikia audax
Thunnus alalunga
Harpadon nehereus
Philippines
Pellona ditchela
Mustelus antarcticus
Drepane punctata
Lutjanus argentimaculatus
Carcharhinus longimanus
Hoplostethus atlanticus
Kiribati
Malaisie
Sri Lanka
Solomon Islands
Platycephalus richardsoni
India
Carcharhinus falciformis
Thenus orientalis
Ommastrephes bartramii

Bartail ﬂathead
nei_56
Greater lizardﬁsh
Bigeye scad
nei_39
Black marlin
Green tiger prawn
Greenback horse mackerel
Bluestripe herring
Blue mackerel
Dorab wolf-herring
nei_63
nei_32
nei_78
Torpedo scad
Mirror dory
Alfonsino
Shortbill spearﬁsh
Giant tiger prawn
Kuruma prawn
Yellowﬁn tuna
Coho (=Silver) salmon
John dory
Narrow-barred Spanish mackerel
Indo-Paciﬁc sailﬁsh
Skipjack tuna
Bigﬁn reef squid
Snoek
Chocolate hind
Japanese scad
Striped marlin
Albacore
Bombay-duck
nei_96
Indian pellona
Gummy shark
Spotted sickleﬁsh
Mangrove red snapper
Oceanic whitetip shark
Orange roughy
nei_65
nei_73
nei_117
nei_112
Tiger ﬂathead
nei_55
Silky shark
Flathead lobster
Neon ﬂying squid

Continued.

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56 Revue du développement en Asie

Table A1. Continued.

Scientiﬁc Name

Common Name

137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186

Anoplopoma ﬁmbria
Panulirus longipes
Macruronus novaezelandiae
Elagatis bipinnulata
Eleginus gracilis
Epinephelus tauvina
Seriolina nigrofasciata
Anodontostoma chacunda
Sphyraena barracuda
Xiphias gladius
Tegillarca granosa
Trichiurus lepturus
Centroberyx gerrardi
Arripis georgianus
Sphyraena jello
Sardinella gibbosa
Ariomma indicum
Australia
Papua New Guinea
Rachycentron canadum
Scomberomorus guttatus
Priacanthus macracanthus
Pampus argenteus
Dussumieria elopsoides
Acetes japonicus
Rhynchobatus australiae
Coryphaena hippurus
Cheilinus undulatus
Mallotus villosus
Thunnus orientalis
Fenneropenaeus chinensis
Scomber japonicus
Bregmaceros mcclellandi
Pleurogrammus azonus
Sardinops sagax
Paralithodes camtschaticus
Russian Federation
Metapenaeus joyneri
Democratic People’s Rep. of Korea
Myanmar
Hilsa kelee
Lateolabrax japonicus
Engraulis japonicus
Gadus macrocephalus
Thunnus tonggol
Perna viridis
Sardinella zunasi
Fenneropenaeus penicillatus
Paralithodes platypus
Larimichthys crocea

Sableﬁsh
Longlegged spiny lobster
Blue grenadier
Rainbow runner
Saffron cod
Greasy grouper
Blackbanded trevally
Chacunda gizzard shad
Great barracuda
Swordﬁsh
Blood cockle
Largehead hairtail
Bight redﬁsh
Ruff
Pickhandle barracuda
Goldstripe sardinella
Indian dirtﬁsh
nei_6
nei_94
Cobia
Indo-Paciﬁc king mackerel
Red bigeye
Silver pomfret
Slender rainbow sardine
Akiami paste shrimp
Whitespotted wedgeﬁsh
Common dolphinﬁsh
Humphead wrasse
Capelin
Paciﬁc blueﬁn tuna
Fleshy prawn
Chub mackerel
Unicorn cod
Okhotsk atka mackerel
South American pilchard
Red king crab
nei_101
Shiba shrimp
nei_88
nei_82
Kelee shad
Japanese seabass
Japanese anchovy
Paciﬁc cod
Longtail tuna
Green mussel
Japanese sardinella
Redtail prawn
Blue king crab
Large yellow croaker

Continued.

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Does Climate Change Bolster the Case for Fishery Reform in Asia? 57

Table A1. Continued.

Scientiﬁc Name

Common Name

Larimichthys polyactis
Theragra chalcogramma
Dussumieria acuta
Parastromateus niger
Pseudocaranx dentex
Trachurus japonicus
Pagrus major

Yellow croaker
Alaska pollock (=Walleye poll.)
Rainbow sardine
Black pomfret
White trevally
Japanese jack mackerel
Japanese seabream

187
188
189
190
191
192
193

Source: Author’s analysis of data from Gaines, Steven, Christopher Costello, Brandon Owashi,
Tracey Mangin, Jennifer Bone, Jorge Garcia Molinos, Merrick Burden, Heather Dennis, Ben
Halperne, Carrie Kappel, Kristen Kleisner, and Dan Ovando. 2018. “Fixing Fisheries Management
Could Offset Many Negative Effects of Climate Change.” Science Advances. Forthcoming.

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