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The Status of World Fisheries
by
Daniel Pauly
Fisheries Centre,
University of British Columbia
Vancouver, Canada
United Nations University
Fisheries Training Programme
Institute of Marine Research
Reykjavik, December 16, 2002
Everywhere one looks, fisheries are in trouble…
Bluefin tuna in the Atlantic …
Martell (1999)
Lingcod in British
Columbia …
…and I could go
on with hundreds
of those…
We can generalize this by using simple definitions of
stock status:
Status of fishery
Criteria applied to 932 species (groups) in FAO’s global catch
statistics
Undeveloped
Year before maximum year and value less than 10% of maximum value.
Developing
Year before maximum year and value 10-50% of maximum value.
Fully exploited
Value larger than 50% of maximum value.
Overfished
Year after maximum year and value 10-50% of maximum value.
Collapsed
Year after maximum year and value less than 10% of maximum value.
Definitions by R. Froese, IfM, Kiel, Germany
...and applying these to FAO’s marine catch data (1951-1998).
This shows a steady erosion of fisheries worldwide. Thus,
fisheries are in crisis, and the problem is growing rapidly.
100%
80%
60%
40%
20%
0%
1951
1956
1961
Undeveloped
1966
1971
Developing
1976
Fully exploited
1981
1986
Overfished
1991
1996
Collapsed
Analysis by R. Froese, IfM, Kiel, Germany
And yet, the global catch statistics assembled
by FAO so far did not seem to add up to a
globally declining catch …
Indeed, global
catches appeared
to increase in the
1990s.
Based on the FAO FISHSTAT database (with
approximations for discards and unreported catches).
To deal with anomalies of this sort, we usually
plot things on a graph, and look for patterns, and
deviations from the patterns. However:
• Except for tuna, fisheries data are usually not
presented in spatially disaggregated form;
• Data on who caught ‘what and where’ usually
exist only for fisheries with on-board observers,
tend to be confidential, and cover only a small part
of the world fisheries;
• Hence, to place fisheries catches on maps, we
must use other things we know.
Thus, we used a ruled-based algorithm…
Taxon (what)
Taxon distribution
database
NO
Country (who)
FAO Area (where)
Fishing access
database
Spatial reference
database
Common spatial
cells?
Improve
databases
YES
Assign catch rate to common cells
This algorithm now
assigns over 99 % of
FAO global marine
catches to ½ degree
spatial cells, and we
are still improving
the underlying
databases …
The global map we got was not very exciting,
except for the anomalies (red)….
0
We had no problem with Peru and Chile. But China?
So we used a statistical model to try to
reproduce the catch map, using depth, primary
production, etc., to predict catches...
It worked
everywhere,
except for
Chinese waters,
where the
discrepancies
were huge….
This allowed us to identify and quantify overreporting of marine catches by China
throughout the 1990s …
(b)
18
16
Constant catch
mandated
6
Chinese catch (t · 10 )
14
12
Overall marine
10
EEZ uncorrected
EEZ corrected
8
6
4
2
0
1970
1975
1980
1985
1990
1995
2000
(Watson and Pauly, Nature, Nov. 29, 2001).
Correcting for this resolved the global conundrum:
(a)
90
El Niño events
85
6
Global catch (t ·10 )
80
75
70
65
El Niño
event
Uncorrected
Corrected
60
Corrected, no anchoveta
55
50
45
40
1970
1975
1980
1985
1990
1995
2000
… in reality, global marine fisheries catches have been decreasing since the
late 1980s (Watson and Pauly, Nature, 2001).
Now to the ecological processes underlying
overfishing.
Fisheries exploit resources embedded within
ecosystems …
wherein each organism has its own trophic level …
Now consider that ecosystem fluxes move up ‘trophic
pyramids’ …
4

10%
3
2
1
 10%
..
. . . . . . . 10%
. *. .*. .
*. . . *. . . . .
*
*. *. *.. *.
.
...
Turning this around, we can use global catches to estimate how much
primary production is required to support the fisheries …
And we can estimate the percentage of total marine
primary production that is appropriated by humans…
Non-tropical
shelves: 35%
Open ocean: 2%
Tropical
shelves: 35%
Terrestrial average:
35-40%
Rivers/
lakes: 24%
Upwelling: 25%
Pauly and Christensen, Nature 1995
Similarly, we can estimate (from catch data and the
trophic level of all species caught) the mean trophic
level of global fisheries landings. This is declining…
TL of landings
3.4
3.3
3.2
Marine
3.1
3.0
2.9
2.8
Freshwater
2.7
1970
1975
1980
1985
1990
Pauly et al. Science March 1998
In a critique, Caddy et al. (1998. Science
282:183a.) wrote we overlooked several
sources of bias, notably:
1. The composition of landings does not
necessarily reflect relative abundance on
underlying ecosystem;
2. Trophic levels change with size or age;
3. Over-aggregated catch statistics may bias
results.
Ad (1) - landing trends vs. ecosystem trends.
Three counter-arguments:
1. Fish are nowadays exploited everywhere they are
abundant;
2. All trawl survey data so far tested for this (e.g.,
Gulf of Thailand, Cantabrian Shelf, Guinea, etc.)
show TL trends similar to those of the landings;
3. Work by Pinnegar et al. (Lowestoft) for the Irish
Sea shows that decline of TL in landings is less
pronounced than in survey data (i.e., skippers try to
maintain catches of high TL fishes).
Ad (2) – ontogenic changes in TL.
Trophic level tends
to increase with
size/age; as ‘fishing
down’ is associated
with high F, TL
decline is faster
when ontogenic
changes in TL are
considered.
From Pauly et al. (2001; Can. J. Fish and Aquatic Sci.)
Item (3) came up because much of the world’s
catch is reported in very coarse categories…
However, over-aggregating catch statistics has
the effect of masking the fishing down effect.
FAO Area 27 (NE Atlantic)
Indeed, there is another masking effect, overlooked
by Caddy et al. (1998), illustrated by FAO Area 31
(West Central Atlantic). There, fishing down did not
seem to occur, which we first attributed to the crude
statistics from many countries of that region.
However, after separating the USA (‘South
Atlantic’ and Gulf of Mexico) from the rest of
the region (Mexico, Caribbean, NE South
America), we get:
Disaggregating the tuna and billfishes group
from the others in the FAO global database also
shows the fishing down effect to occur in
oceanic areas…
This had so far
been missed
because we had
pooled these fishes
with others in our
analyses by FAO
areas.
The ‘fishing down’
effect is strong and
everywhere.
This is why we now see
increasing emphasis on
products such as this.
(indeed, Western
companies are now
beginning to export
jellyfish to East Asia).
There is also a notion that some parts of the world still have large
fisheries resources, thus making it superfluous to deal with ‘fishing
down marine food webs.’ However, the fish wealth of West Africa
has long attracted distant water fleets from other continents …
Number of ‘country
access years’
by area, 1960-1969
… and these have increased tremendously over the
years …
Number of ‘country
access years’
by area, 1980-1989
… finally reaching the present, staggering
levels.
Number of ‘country
access years’
by area, 1990-1999
What is the impact of all this fishing
on the resource base?
• We quantified this impact for the countries of the
Northwest African sub-region using a
methodology previously applied to the North
Atlantic
• This methodology is based on maps of catch data,
combined with ecosystem models, as documented
at the website of the Sea Around Us Project (see
‘Reports’ at above address).
Fish biomass in 1950
(excluding small pelagics)
Fish biomass in 1975
(excluding small pelagics)
Fish biomass in 1999
(excluding small pelagics)
The reason for this is fishing intensity, which was low in
1950 …
… but increased tremendously over time …
… finally reaching the very high present levels of fishing
intensity.
Thus, we have in summary…
2.5
3.5
Fishing intensity
Biomass
3.0
2.5
Catch
1.5
2.0
1.5
1.0
1.0
0.5
Biomass
0.0
1950
1960
1970
1980
1990
0.5
0.0
2000
Fishing intensity
Biomass and catch (million tonnes)
2.0
Thus, we can assume that globally, caught
seafood per person will continue to go down…
Seafood per person
16
kg per person
14
12
Projection
Less than half the
seafood per person
available at the
peak in 1988
10
8
R. Watson and P. Tyedmers, 2001
060
1970
1975
1980
1985
1990
1995
2000
2005
2010
2015
2020
3.60
3.60
3.40
3.40
3.20
3.20
Trophic Level
Trophic Level
Aquaculture can counter the fisheries trends
only if it is based on organism low in the food
web…
3.00
India
2.80
2.60
Japan
2.40
2.20
3.00
2.80
2.60
2.40
China
2.00
UK
Chile
Canada
France
2.20
2.00
1970 1973 1976 1979 1982 1985 1988 1991 1994 1997
Norway
USA
1970 1973 1976 1979 1982 1985 1988 1991 1994 1997
Trophic level trends of aquaculture production in selected countries:
Left: major Asian producers; right: major non-Asian countries.
Here is an example of a herbivore , which can
add to the global fish supply.
Nile tilapia, Oreochromis niloticus
Other fishes, such as salmon (Salmo salar), do
not add to world fish supply, because they (must)
consume more than they (can) produce….
Our somewhat pessimistic conclusions:
• Fisheries resources, throughout the world, are
under tremendous pressure, as are the ecosystems
within which they are embedded, and we are
losing stocks and increasingly, species;
• There is a strong tendency for these pressures to
increase, i.e., we do not have mechanisms in place
to control the growth of fishing effort. Indeed,
most fisheries work is still devoted to various
forms of ‘development;’
• Aquaculture cannot replace the losses that are due
to overfishing.
The next lectures will address
some of these issues. Thank you.
Acknowledgements…
• Thanks to the Pew Charitable Trusts, Philadelphia;
• Fisheries Centre, Faculty of Graduate Studies, UBC;
• Members of the Sea Around Us project;
and many others.