ICES Journal of
Marine Science
ICES Journal of Marine Science (2014), 71(7), 1921– 1926. doi:10.1093/icesjms/fsu079
Comment
Comment on: “Managing fisheries from space: Google Earth
improves estimates of distant fish catches” by Al-Abdulrazzak
and Pauly
Luca Garibaldi 1*, Jennifer Gee 1, Sachiko Tsuji 1, Piero Mannini 2, and David Currie3
1
Food and Agriculture Organization of the United Nations, Statistics and Information Branch, Fisheries and Aquaculture Department, Rome, Italy
Food and Agriculture Organization of the United Nations, Regional Office for the Near East and North Africa, Cairo, Egypt
3
Food and Agriculture Organization of the United Nations, Subregional Office for the Gulf Cooperation Council States and Yemen, Abu Dhabi,
United Arab Emirates
2
*Corresponding author: tel: +39 06 57053867; fax: +39 06 57052476; e-mail: [email protected]
Garibaldi, L., Gee, J., Tsuji, S., Mannini, P., and Currie, D. Comment on: “Managing fisheries from space: Google Earth improves
estimates of distant fish catches” by Al-Abdulrazzak and Pauly. – ICES Journal of Marine Science, 71: 1921– 1926.
Received 21 February 2014; revised 20 March 2014; accepted 22 March 2014; advance access publication 11 June 2014.
This Comment was prompted by the substantial difference in weir catch estimates in the Gulf between (i) those reported by Al-Abdulrazzak and
Pauly (2014. Managing fisheries from space: Google Earth improves estimates of distant fish catches. ICES Journal of Marine Science, 71(3),
450 – 454), who used Google Earth to count weir numbers, and (ii) those available from official national statistics provided by two major weir
fishing countries (Bahrain and Iran). Satellite imageries, including Google Earth, are powerful tools for collecting data on visible structures
when verified with adequate ground validation. However, an extension of their contribution to improving overall catch estimates is rather
limited without having solid information on daily catch, which will substantially differ according to time and area, and fishing season lengths. It
was noted that Al-Abdulrazzak and Pauly (2013) introduced positive biases through their interpretation of Google Earth images and data treatment. They included several assumptions, such as removing the impact of poor visibility, correcting grids of low resolutions, estimating number of
unseen weirs, and applying daily catch rates higher than referenced observed values. The overall extent of such potential positive bias could be more
than six times that which we considered reasonable. This Comment also corrects misconceptions about “FAO catch data”, discusses other available
national data, and introduces the existence of the Regional Commission for Fisheries (RECOFI), a mechanism for fisheries management in the Gulf
region, and its recent activities to collect more complete catch and effort data separated by gear.
Keywords: FAO catch statistics, Google Earth images, Gulf weirs, national catch statistics, RECOFI.
Introduction
Al-Abdulrazzak and Pauly (2014), referred to hereafter as A&P,
counted the number of fishing weirs using Google Earth and estimated their annual catch in six countries bordering the Gulf (also
known as the Persian or Arabian Gulf) by multiplying the number
of days by daily catch generated using a Monte Carlo procedure
based on limited available information.
Satellite imageries, including Google Earth, are powerful tools for
providing a snapshot of visible frame information, such as the
number and extent of weirs and aquaculture cages and ponds. The
basic procedure to utilize frame information in overall catch estimates
is straightforward and well established. As an example of using
# International
satellite imageries to obtain structure information, Trujillo et al.
(2012) combined satellite imageries with assumptions about cage
volume, fish density, harvest rates, and seasonal capacity, and they
then estimated mariculture production of 16 Mediterranean countries with final figures quite close to the recent aquaculture statistics
collated by FAO.
However, A&P obtained catch estimates substantially different
from those officially reported as national statistics. This large discrepancy drew our attention and we decided to review carefully the procedures and assumptions utilized by A&P to identify its causes.
This document first describes our concerns on technical issues of
methodologies and analysis in A&P then introduces the national
Council for the Exploration of the Sea 2014. All rights reserved.
For Permissions, please email: [email protected]
1922
and regional information that was available but not taken into
account by A&P to enhance their analysis and better check against
their results.
Interpretation of Google Earth images
We attempted to replicate the counts of weirs through Google Earth
and encountered difficulties while trying to follow the methods
described by A&P. We counted all weirs visible in Google Earth,
using the images of best available resolution regardless of year to
improve our detection of weirs. Full counts were completed for
Kuwait, Qatar, Saudi Arabia, and the United Arab Emirates
(UAE), while partial counts were conducted for Bahrain and Iran
due to the large number of weirs.
Our total count of weirs, combining both complete structures
and partial or fragmented structures, showed good consistency
with the uncorrected count of weirs referred in Table 1 of A&P.
The percentage of partial or fragmented structures varied by
country: Bahrain (10%), Iran (7%), Kuwait (32%), Qatar (78%),
Saudi Arabia (69%), and UAE (46%). Figure 1 shows an example
of a complete weir and a partial weir located ,1 km apart in Kuwait.
A&P applied two upward corrections to obtain the final estimate
of the number of weirs. The first correction was to remove the impact
of poor visibility, assuming that partial weirs are only partially visible
due to poor visibility caused by “physical condition” (e.g. cloud
cover, glare) and are in operational condition. The second one
was applied for “missing imagery” or grids that had poor resolution.
In our search, the numbers of coastal grids (with sides ≤5 km) in
each country with clouds present were: Bahrain (0), Iran (3), Kuwait
(9), Qatar (0), Saudi Arabia (0), and UAE (1). Very few grids had
cloud present, the cloud coverage was never complete, and any
concern over missed weirs could be simply alleviated by referring
to imagery from another year. Contrary to A&P, we consider that
when only a portion of a weir is visible, it is in fact due to the weir
being only partially present through either disrepair or abandonment (again see Figure 1).
L. Garibaldi et al.
Satellite and aerial imagery have some obvious similarities. Past
experience indicates that the inclusion of non-active fishing units is
among the sources of error in the aerial frame surveys (Bazigos,
1974). Particularly for airborne surveys, small-scale ground verification is crucial to estimate the magnitude of the coverage errors such
as the omission and erroneous inclusion of fishing units (Butler
et al., 1988). In that sense, even assuming all complete weirs as
being operational would be subject to overestimation. Figure 2
shows a weir in Qatar that seems complete from the Google Earth
image, but its base is actually broken. In February 2014, our
contact in the field verified the weir’s location using a GPS and
took photographs of the structure. The same coordinates for the
photograph location were recorded as the weir from the Google
Earth image at location 2686′ 43.45′′ N 5189′ 22.57′′ E.
A&P applied a further correction to estimate the number of unseen
weirs in those grids with good visibility by extrapolating a relation
between number of counts and percentage visible of each weir. We
are concerned this is an over-adjustment for poor visibility that
rarely occurs and could be resolved by examining images with better
visibility. Also, we found that the proportion of partially visible weirs
differed substantially according to the countries. A unique relation utilized for adjustment shown in Figure 3 of their paper assumed 54% of
weirs being only partially visible for all countries, which would introduce excess positive adjustment for those countries with low ratios of
partially visible weirs, such as Bahrain and Iran, even accepting the assumption that all partially visible weirs are in operation.
A&P applied the second correction to estimate a number of weirs
in the grids of low resolution. A&P identified most weirs in Iran as
being along the south coast between the mainland and Qushm
Island near the Strait of Hormuz (refer to Figure 2 of A&P where
visible weirs were identified). We found this area contained many
low-resolution grids in the 2005 images as shown in Figure 3.
When limiting the imagery only to 2005 as stated in the methodology, a substantial proportion (probably over 70%) of the weirs
in Iran identified in A&P’s Figure 2 as “visible” were in fact not
visible, due to very low imagery resolution. To obtain higher
Figure 1. A comparison of a complete weir (a) and a fragment of a weir (b) in Kuwait less than one kilometre apart (from Google Earth, 2005
imagery). The visibility and image resolution are the same for both the fragment and complete structure. (Coordinates: complete weir:
28835′ 57.48′′ N 48823′ 47.77′′ E; fragment: 28835′ 25.80′′ N 48823′ 58.58′′ E).
1923
Comment on: “Managing fisheries from space”
Figure 2. Google Earth image of a weir in Qatar (a) and photograph of same structure (b) showing clear breaks in the base of the weir.
Figure 3. Low resolution imagery in Iran for the year 2005 with the lowest resolution areas in green.
resolution imagery where all weirs in this area are visible, we had to use
imagery from 2011. In summary, we suggest that future methods for
utilizing satellite imagery (from sources such as Google Earth) could
be made more robust by assessing the best-available imagery rather
than constraining imagery to past years. Finally, ground-truthing of
structures is a vital step in ensuring that visual counts in Google
Earth are robust and accurate.
Reliability of overall estimates
To obtain overall catch estimates, A&P multiplied the number of
weirs counted from Google Earth (actually measured) by the daily
catch rate and the number of fishing days that were generated with
a Monte Carlo procedure based on only three data points from
Kuwait and one point from Bahrain. The concept was in accordance
1924
L. Garibaldi et al.
with the FAO standard methodology to estimate catch based on
sample-based surveys (FAO, 1999; Stamatopoulos, 2002), i.e. multiplying the amount of a given frame (e.g. number of gear, boats,
fishing days, etc.) by the measured catch per unit effort. When multiple variables are used in estimation, the overall reliability of the
resultant estimate is determined by an extent of uncertainty (or reliability) of the least reliable variables used, which in this case is daily
catch.
Weir-hadrah is a passive fishing gear, harvesting fish that are left
in a pocket area due to tide or that encounter a gear wing and are successfully led to a trap end/pocket (Al-Baz et al., 2007). The daily
catch by weirs can differ substantially according to season, area,
shape of gear, fish migration, ocean current, topography, weather
condition, etc. The Gulf is not a uniform area in terms of oceanographic conditions, with indications that the temperature of nearshore waters may vary between 10 and 398C (Carpenter et al.,
1997). Distances from neighbouring weirs will also affect a weir’s
daily catch. Our quick review of Google Earth images in the
region indicated that the shapes of weirs differ substantially according to the countries and that the type of weir shown in Figure 1 of
A&P was typical in Iran but not in other countries. Obtaining and
applying country-specific and time-specific daily catch rates
would be an essential step towards improve reliability and utility
of such estimates.
A&P cited two catch rate estimates (62.2 and 42.6 kg d21), both
from personal communications and based on a very small number
of measurements, three for Kuwait with more than 50% CV, and no
information for Bahrain. If daily catches used in the overall catch estimation were generated with a Monte Carlo procedure based on those
four points, the expected value of the mean daily catch should be the
same as the mean of the original figures used. The average daily catch of
individual countries, calculated from Table 1 of A&P (dividing estimated annual catch by corrected number of weirs and fishing days)
turned out to be around 64 kg d21, even higher than the original
data from Kuwait (62.2 kg d21), for all countries except Saudi
Arabia to which was applied an unexpected lower rate of 25 kg d21.
No explanation for this was given in the paper. Fishing season
lengths were also obtained from three personal communications.
Estimate of potential bias in A&P results
Table 1 shows the impacts of assumptions and corrections applied
by A&P. For the proportion of fully visible weirs, it was assumed
that A&P’s weir count was based on structures detected in Google
Earth using the best visibility and resolution imagery regardless of
year. The impact according to the assumption that fragmented
weirs were operational was calculated as the inverse of the proportion of complete weirs. The impacts of visibility and low resolution
corrections were derived from the differences between before and
after the corrections shown in Table 1 of A&P, and the baseline
was set on the assumption that all existing structures are visible
and that only fully visible gears are in operational condition. Bias
in Monte Carlo simulation of daily catch was estimated assuming
all four data points were treated equally.
Results indicated a possible positive bias in final catch estimate of
A&P in a range of from 1.37 to more than six times. Considering the
weak rationale on daily catch rate value utilized, we concluded that
the final estimate contains not only a high level of uncertainty but
also the potential for substantial positive bias.
National data
A search of the publicly accessible archive for information on
weirs-hadrah catch by the Gulf countries was conducted. This
revealed that Bahrain had collected and published its catch statistics
separated by six to seven gear types back to 1980. A 30-year-long
dataseries on total catch by weirs (Table 2) is available from three
Bahraini official publications (Directorate of Fisheries, 1997; Al
Radhi et al., 2006, 2011), which for 2004 and 2009 also included
weir catches in kilograms detailed by over 25 species. The two
more recent publications also included number of weirs for a total
of 17 years (Table 3).
In 2005, catches by weir in Bahrain were 592 t according to the
national data collection system, whereas for the same year, A&P estimated 17 125 t, a figure almost 29 times greater. It could be argued
that 2005 was a year of low weir catches, but also the average annual
catch (1134 t) in the 30-year period is still 15 times lower than the
A&P estimate for Bahrain.
In addition, Tooraj Valinassab, Head of Marine Resource
Management Division, Iranian Fisheries Research Organization,
stated that the official “Catch Statistics Yearbook” for the year 2006
by the Iran Fishery Organization (an unpublished document for
domestic inter-organizational purposes) reported 608 moshtas
(the name of weir-hadrah in Farsi) and 2737 t as total weir catches
in the Gulf, a value 4.5 times lower than the 12 240 t estimated by
A&P. The latest figure available on weir catches is 329 t for 2012.
National authorities have been aiming for a complete ban on
moshtas operating in Iran through a progressive reduction of
them (Tooraj Valinassab, pers. comm.).
For both Bahrain and Iran, the difference between the numbers
of weirs available from official sources and those from A&P (880
for Bahrain and 726 for Iran) is much lower than that between the
official and estimated catches.
Inappropriate referencing of FAO data
A&P compared their estimate with supposed “FAO catch data”
derived from an FAO Technical Paper (De Young, 2006).
However, this is a compilation of country profiles prepared by
Table 1. Estimate of impacts of various assumptions and corrections applied by A&P.
Bahrain
Iran
Kuwait
Qatar
Saudi Arabia
UAE
Proportion of
fully visible
weirs
0.90
0.93
0.68
0.22
0.31
0.54
Impact of assuming
fragmented weirs as
operational
1.11
1.08
1.47
4.55
3.23
1.85
Impact of
visibility
correction
1.10
1.06
1.02
1.14
1.07
1.03
Impact of correction
of low resolution
grids
1.00
1.11
1.12
1.06
1.00
1.19
Bias in Monte Carlo
simulation of daily
catch rate
1.12
1.12
1.11
1.12
0.44
1.11
Potential positive bias calculated by multiplying the three impacts and the bias in Monte Carlo simulation by country.
Potential
positive bias
1.37
1.41
1.87
6.16
1.51
2.51
1925
Comment on: “Managing fisheries from space”
Table 2. Weir-hadrah and total catches by Bahrain from official
publications.
Year
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
Hadrah catches (t)
654
1 086
881
579
832
1 613
1 373
973
763
2 008
1 367
1 933
1 381
1 064
712
1 045
1 527
1 480
1 723
1 767
1 783
1 350
925
1 413
709
592
965
450
556
505
Total catches (t)
5 115
5 746
5 596
4 811
5 598
7 764
8 057
7 842
6 737
9 209
8 106
7 554
7 984
8 959
7 630
9 388
12 940
10 050
9 849
10 662
11 718
11 230
11 204
13 639
14 489
11 853
15 595
15 011
14 175
16 356
Share of hadrah
catches in total (%)
12.8
18.9
15.7
12.0
14.9
20.8
17.0
12.4
11.3
21.8
16.9
25.6
17.3
11.9
9.3
11.1
11.8
14.7
17.5
16.6
15.2
12.0
8.3
10.4
4.9
5.0
6.2
3.0
3.9
3.1
Table 3. Number of weir-hadrah in Bahrain from official
publications.
Year
1983
1988
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
Number of hadrah
535
667
671
617
587
515
593
607
581
608
377
617
613
610
537
644
644
different authors mostly addressing fisheries management issues
rather than catch statistics. FAO does not request countries to
provide catch statistics separated by fishing gear such as weirs or
others. Reference to “FAO catch data” should be limited to information extracted from the FAO global capture database (FAO, 2013a),
which is mostly composed of official statistics reported by national
correspondents and by definition does not include illegal, unreported, and unregulated catches and discards (Garibaldi, 2012).
The catch data shown in De Young for Bahrain, Kuwait, and the
UAE were obtained from some national sources by the author (Gary
Morgan) of the country profiles. Furthermore, the data in the publication refer to 2001 (Bahrain and Kuwait) and 2002 (UAE),
whereas A&P estimated weir catches for 2005. Hence, the comparison is made between catches of different years, although A&P’s estimate is not sensitive to the reference year, as indicated above. For the
UAE, catches reported by Morgan are very different from those officially submitted to FAO. He stated that it was very probable that
catches officially submitted to FAO were overestimated as they
were based on a market-sampling programme that probably also
records quantities of fish caught by other countries and imported
into the UAE.
By assuming that weir catches in three countries (Iran, Qatar, and
Saudi Arabia) not included in De Young were zero, A&P erroneously
exaggerated the difference between “existing data” and their new estimate. It is very probable that catches from weirs are included in the
catch statistics reported to FAO, but they cannot be separated from
others as FAO does not request catches by gear.
A&P state that Saudi Arabia and Iran do not separate their catches
between their coastlines. This misconception could have been
avoided as Saudi Arabia and Iran provide FAO with catch statistics
that are separated, respectively, by the Red Sea and the Gulf, and by
the Gulf and the Arabian Sea, and the Gulf catches are made available
in the Regional Commission for Fisheries (RECOFI) capture database
(RECOFI, 2013).
Work done by the RECOFI
We fully support the view that reliable fishery data disaggregated by
gear are needed for stock assessment and proper fishery management. The United Nations Convention on the Law of the Sea of
10 December 1982 relating to the Conservation and Management
of Straddling Fish Stocks and Highly Migratory Fish Stocks, Annex
1, Article 7 (United Nations, 1995), defined the primary role of
regional fisheries management organizations or arrangements in
compiling data required for management of shared fish stocks and
fisheries harvesting them. However, A&P totally ignored the existence of, and the work done by, the RECOFI. Established in 2001
within the FAO framework, RECOFI covers the Gulf and part of
the Western Arabian Sea areas, and its membership includes the
six countries (Bahrain, Iran, Kuwait, Qatar, Saudi Arabia, and
UAE) for which A&P estimated the weir catches, plus Iraq and
Oman.
RECOFI agreed a mandatory requirement (effective 1 January
2012) on minimum data reporting that includes catch and effort
data separated by gear (FAO, 2011). Following this recommendation, most member countries have improved or newly established
catch monitoring schemes based on observations at landing sites
and have made substantial improvements in the quality and quantity of data submitted (FAO, 2014a), and the data submitted have
been used as the basis to formulate management advice to the
Commission (FAO, 2013b, 2014b). Preliminary analysis shows
that weir catches are marginal, accounting for at most 10% even
in those countries with relatively active operations of weirs, including Bahrain, Kuwait, and Iran. While it is up to individual regional
fishery management organizations such as RECOFI to decide their
information dissemination policy, a broad sharing of detailed
catch and effort information would be desirable for improving
1926
transparency and credibility on fisheries resource management by
those organizations.
Conclusion
Satellite imageries could be powerful tools in assessing and collecting frame information, such as the number of fixed fishing gear,
when supported with suitable ground validation and proper adjustment procedures. When making adjustments, it must be avoided
introducing biases. Thus, it is necessary to pay balanced attention
to the factors causing both underestimation and overestimation of
final results, though there is a general tendency to emphasize the
factors for underestimation.
To apply the catch estimate methodology proposed by A&P to
fisheries and fish resource management, it is essential to collect
daily catch and fishing season length data regularly, possibly by
“clusters of weirs” distribution. While a one-time assessment of
the situation with best available data would be useful for identifying
potential information gaps, the management and corresponding
decision-making need far more detailed information with adequate
time-series. This requires strong policy commitment and investment in terms of substantial human and financial resources. The
Gulf countries are trying to move in this direction, and their
efforts should be properly recognized.
FAO welcomes any new tool that can help national institutions in
the routine collection and compilation of fishery statistics. The
evaluation of frame information with satellite images would help
to improve the overall credibility of catch estimates not only by simplifying the collection of some frame information but also by providing a basis for developing a better sampling strategy of daily
catch.
Acknowledgements
We thank Richard Grainger, for his constructive advice and suggestions on the manuscript, and Peter Longdill, for conducting a field
verification of weirs in Qatar with photographs and coordinates.
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