Study of Small Scale Fisheries and Analyzing Catch Lengths Relating to
Minimum Landing Sizes in Eastern Coastal Mediterranean Samos,
Greece
Daniel Golconda1, Jose Ortiz1, Chase Walker1, Ben Goss2, Amy Griffin2,
Dimitrios Kosmopoulos1, Vassilis Athitsos1
1
Computer Science and Engineering Department, University of Texas at Arlington
Arlington, Texas 76019, USA
2
Archipelagos, Institute of Marine Conservation
Ormos Marathokampou, Samos 83102, Greece
Abstract: A study is presented to analyze local, small-scale fisheries
in the eastern Mediterranean, Samos, Greece in partnership with
Archipelagos Institute of Marine Conservation, an NGO based in the
North East Aegean Island chain. Archipelago research scientists with
the acknowledgement of local fishermen perform the collection of data.
Attributes recorded include species composition and fish sizes along
with characteristics regarding the fishermen’s fishing vessel, including
boat name, location fished, fishing gear type implemented, a record of
any damage to fishing gears and the possible causes of this damage.
This data was recorded in multiple data sheets and a final product will
include a database system for easy recording and exporting of data.
Data analysis will be performed to determine what percentage of these
fishermen’s catch is under the “Minimum Landing Size”, which is the
legal minimum size limit of fish that are caught, and to determine if
there is a correlation between gear type and species of fish caught over
time. Computer Science Engineers studying at The University of Texas
at Arlington will present this study in collaboration with Archipelagos
IMC, an NGO based in Samos, Greece.
Key words: Mediterranean Fisheries, Minimum Landing Sizes
I. Introduction
Small-scale fisheries are of high socioeconomic importance within the Mediterranean, this is
especially true within Island communities where many people rely both directly and indirectly on fishing as
a form of income. Since June 2009, members of Archipelagos Institute of Marine Conservation have been
collecting data from a local small fishery in Ormos Marathakampos, Samos (A. Miliou*, 2009). During this
time data has been collected on species composition and individual fish size as well as vessel information
such as, boat number, gear type used and gear characteristics (mesh size, depth, hook number and size) (A.
Miliou*, 2009). From this data, the Archipelagos research team is interested in extracting information
regarding over-fishing, juvenile fish catches and the change in catch size over time. “FAO (2009) reported
that in 2007, 52% of global fish stocks were fully exploited, 28% were overexploited or depleted, 20%
were moderately exploited, and only 1% showed signs of recovery – all a direct consequence of the fishing
effort expansion from the 1970s onwards.” (J.A. Anticamara, 2011) This concern has impacted local
economies of the island and coastal communities, especially due to the importance of artisanal fisheries on
the local community. There are a total of 17,382 recorded fishing vessels currently operating in Greek
waters. About 94% of those vessels (16,322) are small scale boats based along the coastline (Hellenic
Fishermen Confederation, 2008). These coastal areas contribute roughly 55% of the total value of fisheries
in Greece. (Tzantos, 2005)
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One main issue affecting this negative decline is the lack of resources for regulations provided by
the government. As stated by the Fisheries and Aquaculture Department, “The development of aquaculture
in Greece is highly constrained by 1) the lack of capital available; 2) high cost of capital; 3) limited access
to appropriate technology; 4) lack of trained and experienced personnel; 5) difficulty in properly projecting
economic performances; 6) lack of market studies; and 7) administrative complexity and delays.” It is as a
result of this lackadaisical attitude that many fishing practices are not always legal and in turn can be
harmful to the coastal environment. Illegal, Unreported and Unregulated (IUU) fishing practices are a
common occurrence, especially in areas where regulation is lacking, for example, the introduction of
minimum landing sizes for commercially important fish species has been established in Greece for a
significant period of time. However, due to the sheer expanse of coastline, coupled with the “straight to
market” aspect of the fishery, this is not always enforced. Another practice that is having negative impacts
on the marine environment is inshore trawling within restricted areas. This non selective and highly
destructive fishing method, physically alters the composition of the seabed and is a research priority of
Archipelagos Institutes’ in relation to the protection of Posidonia oceanica seagrass beds and Coralligene
reefs, both of which are habitats of high environmental importance. There is a significant lack in the
enforcement of existing legislation with regard to trawling, minimum landing sizes and catch quotas.
Through this research, we hope to begin the process to establish maritime procedures which will not only
try to restore areas on the verge of ecological collapse, but also ensure legal fishing practices to provide a
better future for marine biodiversity.
There has been a specific study, which took place in the Patraikos Gulf in Greece, in 2006
(Tzanatosa, Somarakisa, Tserpesb, & Koutsikopoulosa, Identifying and classifying small-scale fisheries
m´etiers in the Mediterranean: A case study in the Patraikos Gulf, Greece, 2006) and in 2008 (Tzanatosa,
Somarakisa, Tserpesb, & Koutsikopoulosa, Catch length analysis, relation to minimum landing sizes and
management implications from a Mediterranean, 2008). Both publications studied the relationships
between the fish being caught and indirectly correlating their results with the fishermen’s practices. One
way to monitor these practices is to compare an attribute labeled “minimum landing size”, (MLS), which
states the minimum size a fish should be legally caught based on individual species’ characteristics, such as
its length when it is first able to reproduce. Fishermen are required to abide by certain size restrictions but
as can be seen from the data used in this report, this is not always the case.
This study will cover data collected on a continuous basis within a small scale artisanal fishery
located in Samos, Greece. Our objective is to create a working database system with an easy graphical user
interface (GUI) that will facilitate the collection of fishery data and by using that data collected to obtain
knowledge regarding fisheries using various data mining techniques.
Area of Study
Figure 1: Map of Samos, Greece http://www.diavlos.gr/properties/samosmaps/samosmaps.html
II. Problem
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There have been five major environmental problems defined by Archipelagos IMC with regards to
fishing practices in Greece, including; the lack of conservation of protected habitats, a negligible number of
areas where fishing is minimized or restricted, lack of security for protected species and an absence in the
enforcement of legislation, fishing and selling of undersized marine organisms (fish, invertebrates, etc.),
and also the inefficient operation of the Fishing Monitoring Centre (Archipelagos Research Institute, 2011).
While our work will help and influence the majority of these issues based on our data analysis and
data mining techniques, our time here will be very focused and constricted. There are many research
opportunities regarding these issues and our input will be implemented within proposals and possible future
scientific papers to be published.
Specifically, our work will be concerned with the data collection practices, data analysis, and data
mining. Research information is continuously being collected, including the daily recordings of fisheries
information each morning. Attributes being collected include boat number, gear type and gear
characteristics, species of fish being caught and their individual sizes, as well as the location from which
they were fished. One of the main challenges includes the fact that many of these attributes have not been
continuously collected as a result of sampling problems faced by members of the Archipelagos research
team. This poses a problem to our team due to the fact that since our team is not heavily involved with the
subject of marine conservation, sifting through the data determining which is relevant, especially since
many data fields are not filled, will complicate our data analysis and introductory phases. About twenty
percent of our project was spent formulating more efficient data sheets.
There are other data analysis problems that have been presented to our team including specific
population trends over time, fish sizes over time, and minimum landing sizes. These specific problems will
help with data collection as well as a good introduction into our data mining stages.
Project Questions
 Create a manageable database along with simple user interface.
 Using the database, determine the percentage of juvenile catches based on length at first maturity
categorized by species.
 Determine the percentage of illegal catches categorized by species determined by minimum
landing size.
 Determine if a correlation exists between gear type and species caught under the minimum landing
size.
Data Collection & Dataset
The data was collected beginning in the summer of 2009. “Within the preliminary fishery data
collection, the fish recorded were measured individually in centimeters (cm) using a ruler, however, in the
long term this proved to be an impractical and inefficient way of collecting catch data and interfered too
greatly with the fishermen’s daily routines. For this reason it was decided in early May 2010 that the
handling of catch should be minimal, in order to prevent damage to the fish which may jeopardize its
economic value. As a result of this, it was decided that fish sizes were to be estimated to the nearest cm by
using known references to previously memorized material on species size and identification. However, in
late May 2010 it was decided that measuring fish in this way introduced too much error and so length bins
were introduced (e.g. 0-5 cm, 5-10 cm, 10-15 cm etc.). This not only increased the efficiency of data
collection but also allowed room for small error in fish size approximations. ” (Archipelagos Research
Institute, 2010)
The data was presented as a Microsoft Excel file database. Some of the major attributes include
species of fish, boat type/gear, date, size of fish. Other attributes recorded, some of which are incomplete,
include net length, mesh size, habitat and location. Our dataset includes 11,073 tuples and is continuously
growing. Some data analysis has been performed to better understand our data including approximately the
percentage of incomplete data, filled in data, and statistics about our dataset. Issues with the data include
gaps in information, irrelevant data which may impede data collection, insufficient data entries, etc. Table 1
shows the percentage of data not recorded for each attribute observed.
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Attribute
Percentage
Not Recorded
Hook Number
KG
Hook Size
Net Length
Mesh Size
Gear Type
Depth
Location
93%
92%
92%
54%
54%
40%
38%
17%
Table 1: Percentage of Data Not Recorded
Figure 2, Figure 3, and Figure 4 are charts that display percentage of data recorded but not complete in
regards to certain attributes. The blue represents data filled in and the red represents data not filled in.
Figure 2: Trammel & Gill Net vs. Mesh Size
Data needed in formula for
length/weight ratio
Figure 3: Longline vs. Hook Number
Data for length/weight
ratio
20%
Data
available
Data
available
Data
Unavilable
80%
Data
unavailable
Figure 4: Length/Weight Ratio – Before & After Data Analysis
III. Data Analysis
A main priority for this project was to analyze the current data so that some knowledge and trends
may be noticed. As shown in Figure 5: Count of Recorded Species, the highest recorded species of fish
caught is the Boops boops by an overwhelming margin. Figure 6: Count of Gear Type describes how many
times each gear type was recorded. The most popular is the trammel net and the second most recorded was
no recording. With the introduction of a database, we will be able to see which species of fish is caught
with each specific gear type. (See Figure13)
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Count of Recorded Species
20000
18000
16000
14000
12000
10000
8000
6000
4000
2000
0
Figure 5: Count of Recorded Species
Figure 6: Count of Gear Type
5
Figure 7: Count of Species Over Time
Figure 8: Number of Recorded Trips Over Time
Figure 7: Count of Species Over Time shows that the majority numbers of fish catches are during
summer time and usually trends downward as the year progresses. Figure 8 highlights Figure 7 and
perpetrates the previously defined figure by showing the amount of trips performed during that period of
time. Figures 9 provides some analysis regarding the gear types used to catch fish.
Figure 9: Data Analysis Concerning Specific Gear Types
Figure 10 provides some insight on which gear types are used thoughout the years. There is a
flucuation in usage of the longline gear type in late 2009. It is interesting to see how the most used gear
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type, the trammel net, is used mostly durin the summer times of the year and then very easily becomes less
popular. This information could be used in the process of proposing minor regulations.
Gear Type vs. Time
700
600
500
400
300
200
100
Jan
Oct
Dec
Jul
Sep
May
Jul
Sep
Nov
Nov
Jun
Aug
Oct
Dec
Jul
Sep
Nov
Feb
Jun
Aug
Oct
Dec
Jun
Aug
Oct
Dec
Mar
May
0
2009
Boat Seine
2009
2010 2011
2009 2009
Gill net
Kalami
2010 2011 2009
Longline
2010
2011
Trammel net
Figure 10: Gear Types Used Over Time
IV. Database & GUI Application
One of the challenges presented was to create a database system to ease the process of data
collection and analysis. Once the data acquisition and data cleanup, creation of the database was performed
using PHPmyAdmin software. The datasheets, which were given in multiple sheets in the original
Microsoft Excel file, were merged into one sheet using SQL queries and then translated into one database
table. The primary key for the table was the “ID” attribute, which is associated with every data collection
entry and recorded when the sampling occurred.
Attributes recorded during data collection include the ID, species of fish, boat, gear type, location,
and if or when applicable, weight, length (range or exact), depth, net length, mesh size, hook number, hook
size, and habitat.
Once the database was completed, a Graphical User Interface (GUI) was completed to simplify
and provide visualization for data entry. This GUI is connected to the main database and updates after each
entry. The GUI also has the capability to export the data into an Excel spreadsheet so that specific data
analysis can continue. Figure 14 provides an image of this GUI program. One important feature includes
the ability to provide comments about the recording and data collection.
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Figure 11: Archipelagos Fisheries Database GUI Application
Equations & Formulas
An important part in creating the database and ensuring the data was relevant included a specific
formula to find the weight given the length of the fish. This task was difficult as there is not enough
research in this particular subject area. The formula consisted of multiple parts:
𝑾 = 𝒂 ∗ 𝑳𝒃
W = Weight
L = Length
a,b = known constants dependent on species of fish
Both constants in the equation are specific to each species of fish. Based on the weight found, after
inputting the equation, the amount of fish could be determined. This information was vital to the database
and any analysis that will come from it.
V. Conclusions
The database designed for data collection will prove to be a vital tool for Archipelagos Research
Institute. Most of the data fields have been placed with drop down boxes as to help ease the entering of data
and will restrict the number of errors. With the ability to add new options to these data fields, the database
is an all-inclusive package and ready to be utilized in the field.
Preliminary results and data analysis, with the help of the newly created database, was performed
to recognize the percentage of fish caught which were classed as juveniles according to previous scientific
studies. Figure 12 shows the results of this, the left, black box represents the percentage of fish recorded as
juveniles and the right, grey box represents the percentage of fish recorded as adults. Ideally, this data
could be used to provide information on the catch composition in relation to gear type as well as each
vessel catch with respect to juvenile landings. However, due to the lack of precise length at first maturity
measurements for fish in the eastern Mediterranean/Aegean Sea, this study will utilize MLS characteristics
which are defined for the economically important species contained within Greek and EU legislation. As a
result of this, Figure 13, depicts the outstanding percentage of fish (per species) being caught under the
MLS. The left, black box represents the percentage of fish recorded under the MLS and the right, grey box
represents the percentage of fish recorded above the legal MLS limit. This information can provide some
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insight on the fish populations within the area. As previously mentioned, MLS is defined with respect to
length at first maturity and therefore fish under the MLS can, be assumed to be juvenile or small adults.
The plots show that from the 15 commercially important species where a MLS has been defined by either
Greek or EU legislation, 8 species have catch recordings of more than 50% which are under the MLS and
10 species have catch recordings of more than 25% which are under the MLS. This high percentage of
individuals which were smaller than the MLS highlights two points. The first is that the catch recordings
show a large proportion of juveniles contained within them showing indications of a collapsing fishery. The
second point to note is that as the fishing activity in the area consumes such a large proportion of the
juveniles, the potential spawning stock biomass is reduced. As a result of this, an insufficient number of
mature individuals remain in the region to ensure the continuation of future populations and endurance of
the fishery.
Figure 14 relates the percentages of types of gears used to catch certain species of fish under the
MLS. This shows that the largest percentage of fish observed as being under the relevant MLS were
recorded when no gear information was obtained (37%). Trammel nets recorded the second highest
percentage of fish smaller than the MLS (36.7%) whilst Kalami recorded the lowest percentage (0.05%).
These results are highly affected by the more common use of trammel nets compared to the other gear
types (Figure 6). The largest range of species caught under the MLS was by Trammel nets (15 species)
whereas the other gear types, Longline, Gill nets, Boat Seine and Kalami, were more species specific – 9, 8,
4 and 2 species respectively. Figure 15 shows the normalized data for landings under the MLS with regard
to the number of times each gear type was used. From these two results it can be seen that Trammel nets
are the most non-selective, having caught a large spread of the species with an average catch of individual
fish under the MLS. Similarly, Longline, Gill nets, and Kalami recorded an average catch of fish under the
MLS, however, they can be considered as more species selective due to the smaller range of species that
were recorded. The results concerning the Boat Seine gear show it to be a highly selective method,
although four species were identified in the landings, two of these species had populations of less than 1%
recorded in comparison to the other gears, whilst the other two species had populations of more than 99%
recorded in the Boat Seine catch in comparison to the other gears. In conclusion, the results obtained from
this study agree to a certain extent with those from previous work , i.e. that four of the gears: Trammel nets,
Gill nets, Kalami, and Longlines, can be considered to be more environmentally friendly and have a higher
selectivity with regards to fish size than Boat Seine (Figure 15). (Tzanatosa, Somarakisa, Tserpesb, &
Koutsikopoulosa, Catch length analysis, relation to minimum landing sizes and management implications
from a Mediterranean, 2008) This is further reflected by the higher amount of legislation and restrictions
placed on Boat Seine gear. For example, prior to being made illegal in 2010, the following restrictions
applied:
 It was illegal to use Boat Seine equipment between 1st April and 30th September,
 The ropes used to draw the net together cannot be longer than 700 m on each side of the net.
The database and GUI application were made solely for this project study’s purposes. The
application may be applicable to similar studies, especially for the collection of this kind of data. The
ability to export to Excel will prove to be the most valuable attribute of this database and GUI application
and will be used to create many graphs and charts, based on the data collected, to provide sufficient
evidence to properly conclude some initial regulations as to help this specific community and also the fish
and marine population for decades to come.
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10
Figure 12: Percentage of Fish Caught as Juveniles
11
Figure 13: Percentage of Species Caught Regarding MLS
12
Figure 14: Species of Fish Caught and Type of Gear Used
Normalized Landings under MLS
vs Gear type
3.5%
3.0%
2.5%
2.0%
1.5%
1.0%
0.5%
0.0%
Not
Recorded
Trammel Boat Seine Longline
Nets
Gill Nets
Kalami
Figure 15: Normalized Landings under MLS against Gear Type Used
FUTURE WORK
This study has produced a set of basic results upon which further investigation is required. An
important part of Archipelagos Institutes’ work in the local area is the delineation and implementation of an
area of restricted fishing applied and enforced by the local fishermen’s association. There is, at present, no
such self-contained area within Greece, although the system has been put in place elsewhere with varying
degrees of success. To this end some of the results need to be looked into in the future:
 The characterization of the fishery with regard to gear types utilized; in order to produce the most
effective regional legislation the fishery must be completely understood. This ensures that any
management strategy produced is detailed enough to guarantee that the most destructive aspects of
the fishery are restricted without unnecessarily negatively impacting the fishers’ income.
 The observation of a declining fishery; from the results produced, concerning catch over time, a
decline in fish catch is apparent despite a relatively constant fishing effort. This requires a more
detailed study in order to prove whether this trend is occurring in the long term.
Finally, the focus of this study has been on fish under the MLS. This is only a single aspect of the
problem to the conservation of the marine environment. In order to work toward the conservation of the
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Aegean fish stocks, the larger issues need to be addressed. Despite the short term aspect of this study, it has
shown illegal fishing to be a wide scale problem, with little to no enforcement. This lack of enforcement is
present in nearly all fishing practices in Greece and before the illegal fishing can be stopped, some type of
regulation will be necessary to address these issues.
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