SUPPLEMENTARY MATERIAL 1 Data collection and the

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SUPPLEMENTARY MATERIAL 1
Data collection and the vulnerability metrics
We compiled population trajectories of adult biomass (Figure 1) and fishing mortality
rates (Figure 2) for 26 populations of scombrids (Table 1), including 17 tunas, 5
mackerels and 4 Spanish mackerels, from the scombrid fisheries stock assessment data
set [1]. The vulnerability to decline is a function of the exposure of a species to extrinsic
threats such as fishing (exposure) coupled with the species’ intrinsic life history and
ecology (sensitivity). We calculated three population biomass metrics to describe
vulnerability to decline: (1) average annual rate of decline in adult biomass, (2) total
extent of decline in adult biomass, and (3) current exploitation status (Figure 3, Table 2).
In order to calculate the first two metrics, we first calculated the logarithm of the ratio of
population biomasses for successive years to estimate the annual rates of change (ri), ri =
ln(AB i+1/ABi), for each population, where ABi is the adult biomass in year i. We then
estimated the average of the annual rates of change in adult biomass across all the years
for each population using a generalized least-squares model of the form ri = bo + ei. In
this model, ri is the dependent variable, interpreted as the annual (i) rate of change in
adult biomass; bo, the intercept, is interpreted as the average annual rate of change in
adult biomass across all the years; and ei is the residual error (Figure 3A). We used this
method to estimate the average annual rate of change because most of the time series of
adult biomass showed non-linearity and temporal autocorrelation [1]. Secondly, we
calculated the total extent of change in adult biomass over the entire time period of
exploitation for each population as follow: (1 -exp(bo·n))·100, where bo is the model
estimated average annual rate of change for each individual population and n is the length
of the time series of each individual population [1]. The third vulnerability metric
described the current exploitation status of populations using the standard fisheries
reference point Bcurrent/BMSY. Bcurrent/BMSY,is the ratio of the current adult biomass relative
to the adult biomass that would provide the maximum sustainable yield (MSY) and
determines whether a population is currently overfished (Bcurrent<BMSY) or not overfished
(Bcurrent > BMSY) (Figure 3B). The relative fishing mortality rate metric was not available
for all 26 populations of scombrids, it was missing for three populations (North Pacific
Albacore tuna, Northeast Pacific Chub mackerel and Pacific bluefin tuna) and therefore
we were not able to include these populations in our analyses (Figure 2, Table 2).
In this study, we aim to progress our understanding of the intrinsic patterns and processes
of decline and collapse in marine fish species by examining the interaction between life
histories and fishing in determining population declines. Therefore, we selected those
populations that have experienced population declines (on average negative annual rates
of change in adult biomass) during their period of exploitation (Figure 3A).
Consequently, we excluded from the statistical analyses four populations of scombrids
(four populations of Spanish mackerels) with increasing population trajectories (on
average positive annual rates of change in adult biomass, Figure 3A). We explain below
the main reasons why we think it important to exclude the four populations of Spanish
mackerels with their trajectories of recovery from our analysis. First of all, this study is
focused only to investigate the decline paradigm. Our study was designed to test the
relative importance of size- and time-related traits for explaining species vulnerability to
decline while controlling for fishing mortality, and test our hypothesis stating that
temperate tunas would decline more than their similar-sized tropical counterparts, for a
given level of fishing mortality. Our study was not designed on understanding the
patterns and processes of recovery where it has been showed that multiple factors
(magnitude of reductions, temporal trajectory of declines, life histories, allee effects,
species interactions, level of fishing, and implementation of fishing regulations) play a
role and interact in the recovery of species [2-5].
Second, our data provides a unique opportunity to test for the role of life histories in
explaining population declines in tunas and their relatives while controlling for fishing
mortality, because all the populations (except the four populations that we exclude)
started to be exploited by industrial fisheries in the 1950-60-70s (depending on the
populations) and since then these populations have been declining in biomass. The
biomass trajectories of some populations have now stabilized around their maximum
sustainable yields (MSY), others continue decreasing below those MSY levels. In
contrast, our data does not provide an opportunity to test the role of life histories in
population recoveries, in part because there are only four populations with recovery
trajectories, and second, for these populations we could divide their trajectories in two
fragments, a first face of decline before the 1980s when the fishery was unregulated and
the stocks where overfished, and a second face of recovery in response to a well
implemented fisheries management plan. Before the 1980s, these populations of Spanish
mackerels off the east of coast of the United States were unregulated and overfished, and
after a successful recovery plan they are now fully recovered to healthy biomass levels
[6]. Therefore, our metrics of vulnerabilities (average rate of change and extent of
decline) would be mixing both signals (decline and recovery) and by doing this, we
would be adding noise into the analysis.
We consider that one of the strengths of our analysis is that we geographically match
high quality datasets of half a century of population biomass trajectories of decline and
fishing mortalities with population level life history trait data.
References
1.
Juan-Jordá M.J., Mosqueira I., Cooper A.B., Dulvy N.K. 2011 Global population
trajectories of tunas and their relatives. Proc Natl Acad Sci USA 51, 20650-20655.
2.
885.
Hutchings J.A. 2000 Collapse and recovery of marine fishes. Nature 406, 882-
3.
Hutchings J.A. 2001 Influence of population decline, fishing and spawner
variability on the recovery of marine fishes. J Fish Biol 59 (Supplement A), 306-322.
4.
Hutchings J.A., Butchart S.H.M., Collen B., Schwartz M.K., Waples R.S. 2012
Red flags: correlates of impaired species recovery. Trends in ecology and evolution 27,
542–546.
5.
Kuparinen A., Hutchings J.A. 2014 Increased natural mortality at low abundance
can generate an Allee effect in a marine fish. Royal Society Open Science 1, 140075.
6.
Ortiz M. 2004 Stock assessment analysis on Gulf of Mexico king mackerel.
SEDAR5- 2004 NMFS SEFSC Miami Lab Sustainable Fisheries Division Contribution
2004-004.
Table 1 List of scombrid populations including their type of climate.
Taxonomic
group
Latin name
Population
code
Climate
SKJwp
Tropical
ALBna
Subtropical
ALBsa
Subtropical
ALBnp
Subtropical
Thunnus alalunga
Population common
name
Skipjack tuna, West
Pacific
Albacore tuna, North
Atlantic
Albacore tuna, South
Atlantic
Albacore tuna, North
Pacific
Albacore tuna, South
Pacific
Tunas
Katsuwonus pelamis
Tunas
Thunnus alalunga
Tunas
Thunnus alalunga
Tunas
Thunnus alalunga
Tunas
ALBsp
Subtropical
Tunas
Thunnus albacares
Yellowfin tuna, Atlantic
YFTa
Tropical
Tunas
Thunnus albacares
YFTi
Tropical
Tunas
Thunnus albacares
YFTep
Tropical
Tunas
Thunnus albacares
Yellowfin tuna, Indian
Yellowfin tuna, East
Pacific
Yellowfin tuna, West
Pacific
YFTwp
Tropical
Tunas
Thunnus maccoyii
Southern bluefin tuna
SBF
Temperate
Tunas
Thunnus obesus
Bigeye tuna, Atlantic
BETa
Subtropical
Tunas
Thunnus obesus
Bigeye tuna, Indian
BETi
Subtropical
Tunas
Thunnus obesus
Bigeye tuna, East Pacific
BETep
Subtropical
Tunas
Thunnus obesus
Bigeye tuna, West Pacific
BETwp
Subtropical
Tunas
Thunnus orientalis
Pacific bluefin tuna
PBF
Temperate
Tunas
Thunnus thynnus
Atlantic bluefin tuna, East
BFTea
Temperate
Tunas
Thunnus thynnus
Atlantic bluefin tuna, West
BFTwa
Temperate
Mackerels
Scomber japonicus
Chub mackerel, Chilean
MASch
Subtropical
Mackerels
Scomber japonicus
MASj
Subtropical
Mackerels
Scomber japonicus
MASnep
Subtropical
Mackerels
Scomber japonicus
MAStcj
Subtropical
Mackerels
Spanish
mackerels
Spanish
mackerels
Spanish
mackerels
Spanish
mackerels
Scomber scombrus
Scomberomorus
cavalla
Scomberomorus
cavalla
Scomberomorus
maculatus
Scomberomorus
maculatus
Chub mackerel, Japanese
Chub mackerel, North East
Pacific
Chub mackerel, Tsushima
Current Pacific
Atlantic mackerel, North
east
King mackerel, Gulf of
Mexico
King mackerel, U.S.
Atlantic
Spanish mackerel, Gulf of
Mexico
Spanish mackerel, U.S.
Atlantic
MACnea
Temperate
KGMgm
Tropical
KGMwa
Tropical
SSMgm
Subtropical
SSMwa
Subtropical
Table 2. Data set including vulnerability metrics and relative fishing mortality metric for 26
populations of scombrids.
Stock name
Chub mackerel, North East
Pacific
Stock
acronym
Average
rate of
change
Extent
of
change
Exploitation
status
Relative fishing
mortality
MASnep
-0.0917
-99.92
Chub mackerel, Chilean
MASch
-0.0696
-62.26
Not_overfished
Atlantic bluefin tuna, West
BFTwa
-0.0573
-85.74
Overfished
2.09
Chub mackerel, Japanese
MASj
-0.0566
-87.69
Overfished
1.33
Albacore tuna, North Atlantic
ALBna
-0.0505
-97.73
Overfished
1.73
Albacore tuna, South Pacific
ALBsp
-0.0365
-82.64
Not_overfished
0.32
Bigeye tuna, West Pacific
BETwp
-0.0356
-85.86
Not_overfished
0.64
Atlantic mackerel, North East
MACnea
-0.0353
-69.86
Overfished
0.78
Yellowfin tuna, Indian
YFTi
-0.0314
-67.70
Not_overfished
0.69
Yellowfin tuna, Atlantic
YFTa
-0.0304
-66.48
Not_overfished
0.41
Southern bluefin tuna
SBF
-0.0291
-89.38
Overfished
1.95
Albacore tuna, South Atlantic
ALBsa
-0.0276
-74.80
Overfished
0.37
Bigeye tuna, Atlantic
BETa
-0.0270
-55.57
Overfished
0.43
Atlantic bluefin tuna, East
BFTea
-0.0239
-55.64
Overfished
1.52
Bigeye tuna, East Pacific
BETep
-0.0202
-47.66
Overfished
0.97
Chub mackerel, Tsushima
Current Pacific
MAStcj
-0.0173
-44.55
Overfished
1.9
Yellowfin tuna, West Pacific
YFTwp
-0.0150
-55.42
Not_overfished
0.37
Bigeye tuna, Indian
BETi
-0.0125
-51.70
Not_overfished
0.17
Skipjack tuna, West Pacific
SKJwp
-0.0112
-33.94
Not_overfished
0.25
Pacific bluefin tuna
PBF
-0.0083
-35.71
Yellowfin tuna, East Pacific
YFTep
-0.0066
-19.01
Not_overfished
0.68
King mackerel, Gulf of Mexico
KGMgm
0.0103
22.99
Not_overfished
0.86
Albacore tuna, North Pacific
ALBnp
0.0146
77.00
King mackerel, U.S. Atlantic
KGMwa
0.0180
43.34
Not_overfished
0.92
0.4306
Spanish mackerel, U.S. Atlantic
Spanish mackerel, Gulf of
Mexico
SSMwa
0.0474
123.88
Not_overfished
1.06
SSMgm
0.0722
241.39
Not_overfished
0.9
Figure 1 Trajectories of adult biomass (thousand tonnes) for 26 populations of scombrids (11
species).
Albacore tuna, North Atlantic
Albacore tuna, North Pacific
100
50
250
200
150
100
50
1940
1960
1980
2000
Albacore tuna, South Pacific
1970
1980
1990
2000
Atlantic mackerel, North East
4000
3500
3000
2500
2000
400
300
200
100
1960
1970 1980 1990 2000
Bigeye tuna, East Pacific
1960
1970 1980 1990
Bigeye tuna, Atlantic
2000
1000
900
800
700
600
500
400
2010
1980
1990
2000
Bigeye tuna, Indian
1975 1980 1985 1990 1995 2000 2005
Bigeye tuna, West Pacific
1200
600
500
400
800
300
600
200
100
400
1950 1960 1970 1980 1990 2000 2010
1950 1960 1970 1980 1990 2000
Bluefin tuna, West Atlantic
Chub mackerel Northeast Pacific
1200
50
1000
800
40
600
30
400
20
200
10
0
1970
1980
1990
2000
1940
1960
1980
2000
Chub mackerel, Japanese
Chub mackerel, Tsushima current
140
120
100
80
60
40
1000
1980
1990
2000
Bluefin tuna, East Atlantic
200
Adult biomass (thousand tonnes)
Albacore tuna, South Atlantic
180
160
140
120
100
80
150
150
100
1970
1980
1990
2000
Chub mackerel, Chilean
3000
2500
500
400
300
200
100
1000
2000
500
1500
1000
0
1990
1995
2000
King mackerel, Gulf of Mexico
1970
26
24
22
20
18
16
1980
1990
2000
King mackerel, U.S. Atlantic
1980
1990
2000
Pacific bluefin tuna
5
60
50
40
30
20
10
4
3
2
1980
1985
1990
1995
2000
Skipjack tuna, West Pacific
4000
3500
3000
2500
1980
1990
2000
Spanish mackerel, West Atlantic
1980
1000
800
600
400
200
0
2010
7
6
5
4
3
1985
1990
1995
Southern bluefin tuna
2000
1940
1960
1980
Yellowfin tuna, Atlantic
2000
300
200
2000
1970
1980
1990
2000
Yellowfin tuna, West Pacific
3500
3000
2500
2000
1500
1000
2500
2000
1500
1000
500
1980
1990
2000
1985
1990
1995
2000
Yellowfin tuna, East Pacific
350
300
250
200
150
100
400
1990
1995
Yellowfin tuna, Indian
1960 1970 1980 1990 2000
Spanish mackerel, Gulf of Mexico
8
7
6
5
4
500
1985
1950
1950
1960
1970
1980
1990
Time (years)
2000
1980
1990
2000
Figure 2 Trajectories of relative fishing mortality rates for 26 populations of scombrids
(11 species). The metric of relative fishing mortality rate was calculated as the ratio
between the average fishing mortality rate across all years and the fishing mortality
predicted to produce maximum sustainable yield (Faverage/FMSY). Broken horizontal line
shows when Faverage/FMSY is one. FMSY was not available for the North Pacific Albacore
tuna, Northeast Pacific Chub mackerel and Pacific bluefin tuna, therefore, we were not
able to include these populations in our analyses.
Albacore tuna, North Atlantic
Albacore tuna, North Pacific
6
5
4
3
2
1
0
1940
1960
1980
2000
Albacore tuna, South Pacific
1.0
0.8
0.6
0.4
0.2
0.0
1960
1970
1980
1990
2000
Bigeye tuna, East Pacific
1970
1980
1990
2000
Atlantic mackerel, North East
1980
1990
2000
Bigeye tuna, Indian
1.0
0.5
1980
1990
2000
Bluefin tuna, East Atlantic
5
3.0
2.5
2.0
1.5
1.0
4
3
2
1
1970
1980
1990
2000
Chub mackerel, Chilean
1.5
0.5
0.0
1990
1995
2000
King mackerel, Gulf of Mexico
1.0
0.5
1950 1960 1970 1980 1990 2000 2010 1950
Bluefin tuna, West Atlantic
1.4
1.2
1.0
0.8
0.6
1960 1970 1980 1990 2000
Chub mackerel Northeast Pacific
1970
1940
1960
1980
2000
Chub mackerel, Tsushima current
1980
1990
2000
Chub mackerel, Japanese
3.0
2.5
2.0
1.5
1.0
1970
1.6
1.4
1.2
1.0
0.8
0.6
1980
1990
2000
King mackerel, U.S. Atlantic
1980
1.5
1.0
1985
1990
1995
Skipjack tuna, West Pacific
2000
1980
1.0
0.8
0.6
0.4
0.2
0.0
1985
1990
1995
Southern bluefin tuna
2000
2010
1940
1960
1980
Yellowfin tuna, Atlantic
2000
1.0
0.8
0.6
0.4
0.2
1.5
1.0
1985
1990
1995
Yellowfin tuna, Indian
2.0
1.5
1.0
0.5
0.0
1980
1990
2000
2000
1950
1960 1970 1980 1990 2000
Spanish mackerel, Gulf of Mexico
1.6
1.4
1.2
1.0
0.8
0.6
0.4
5
4
3
2
1
0
1980
1990
2000
Spanish mackerel, West Atlantic
1990
2000
Pacific bluefin tuna
1.4
1.2
1.0
0.8
0.6
2.0
1980
2000
1.5
2.5
2.0
1.5
1.0
0.5
1.0
1970 1980 1990
Bigeye tuna, Atlantic
1975 1980 1985 1990 1995 2000 2005
Bigeye tuna, West Pacific
1.0
0.8
0.6
0.4
0.2
0.0
1.5
1960
1.0
0.8
0.6
0.4
0.2
1.2
1.0
0.8
0.6
0.4
0.2
0.0
2010
2.0
Relative fishing mortality (Faverage/Fmsy)
Albacore tuna, South Atlantic
1.0
0.8
0.6
0.4
0.2
0.0
1.4
1.2
1.0
0.8
0.6
1985
1990
1995
Yellowfin tuna, East Pacific
1.2
1.0
0.8
0.6
1970
1.0
0.8
0.6
0.4
0.2
0.0
1950
1980
1990
2000
Yellowfin tuna, West Pacific
1960
1970
1980
1990
Time (years)
2000
1980
1990
2000
2000
Figure 3 Vulnerability to decline metrics for the 26 populations of scombrids (11
species). (A) Average annual rate of change in adult biomass (mean ± 95% CIs) for each
population across the entire period of available biomass data. (B) Overall extent of
decline or recovery in adult biomass for each population from the first year to the last
year of available biomass data. Population are colored according to their exploitation
status according to the fisheries reference point, Bcurrent/BMSY. Red populations are
overfished (B < BMSY) and green populations are not overfished (B > BMSY). Populations
for which fisheries reference points were unavailable are shown in grey.
A
B
Chub mackerel, North East Pacific
Chub mackerel, Chilean
Atlantic bluefin tuna, West
Chub mackerel, Japanese
Albacore tuna, North Atlantic
Albacore tuna, South Pacific
Bigeye tuna, West Pacific
Atlantic mackerel, North East
Yellowfin tuna, Indian
Yellowfin tuna, Atlantic
Southern bluefin tuna
Albacore tuna, South Atlantic
Bigeye tuna, Atlantic
Atlantic bluefin tuna, East
Bigeye tuna, East Pacific
Chub mackerel, Tsushima Current Pacific
Yellowfin tuna, West Pacific
Bigeye tuna, Indian
Skipjack tuna, West Pacific
Pacific bluefin tuna
Yellowfin tuna, East Pacific
King mackerel, Gulf of Mexico
Albacore tuna, North Pacific
King mackerel, U.S. Atlantic
Spanish mackerel, U.S. Atlantic
Spanish mackerel, Gulf of Mexico
-30
-20
-10
0
10
Rate of change
(% per year)
20
30
-100
0
50 100 150 200 250
Extent of change
(% over time)
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