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Ministero degli Affari Esteri
REGIONE BASILICATA
Ministero dello
Sviluppo Economico
FPA Balkans - Line 2.3 Environment and Sustainable Development
Integrated Project RIVA
Sub Project RIVA
“Environmental requalification of the basin of Skadar (Albania)”
Phase 5 - Transversal supporting activities: sub-activity 5.1
ASSESSMENT AND MANAGEMENT
OF SHARED FISHERY RESOURCES
Manual of the Training Course
Agenzia Regionale per la Prevenzione e Protezione dell’Ambiente - Regione Puglia
Direzione Generale - Corso Trieste, 27 - 70126 Bari
Tel. +39 080 5460.111 - Fax +39 080 5460.150 - www.arpa.puglia.it
Stampato su carta certificata FSC dalla Sagraf srl Capurso (Ba) / Cover photo credits: Annamaria Pastorelli - Nicola Ungaro
Regione Puglia
Regional Cooperation Support ‐ FPA Balkans Line 2.3 Environment and Sustainable Development Integrated Project RIVA Sub Project RIVA “Environmental requalification of the basin of Skadar (Albania)” ASSESSMENT AND MANAGEMENT OF SHARED FISHERY RESOURCES Manual of the Training Course
ARPA PUGLIA Agenzia Regionale per la Prevenzione e Protezione dell’Ambiente REGIONE PUGLIA Direzione Generale Corso Trieste, 27 70126 Bari Tel. +39 080 5460.111 Fax +39 080 5460.150 www.arpa.puglia.it AUTHORS ARPA PUGLIA Nicola Ungaro, Biologist‐Environmental Manager FAO (Food and Agriculture Organization of the United Nations) Luca Ceriola, Biologist UNIVERSITY OF BARI (Faculty of Sciences ‐ Biology Department) Roberto Carlucci, Researcher UNIVERSITY OF SKADAR (Faculty of Natural Sciences) Lindita Bushati, Biologist (Department of Biology) Razim Suma, Biologist (Skadar, Albania) COORDINATION AND EDITING Anna Maria Pastorelli* & Nicola Ungaro, Natural Resources Unit ‐ ARPA Puglia *RIVA Sub‐Project Coordinator SUPERVISION Massimo Blonda, Scientific Manager – ARPA Puglia; Vito Michele Perrino, Chief Manager of Natural Resources Unit – ARPA Puglia 1
PREFACE Puglia, due to its geographical location, has always been involved in trade exchanges with bordering Mediterranean countries, thus bestowing a typical Apulian penchant for dialogue, mutual cultural growth and the opportunity to improve economic development on both shores of the Mediterranean. When it comes to the environment, the Apulian Regional Administration – as is the case of other participating institutions – is well aware of the mutual need we share with neighboring Mediterranean friends: a multidisciplinary approach based on teamwork, so as to enhance cooperation and coordination among national and regional institutions in charge of protecting our lands. Likewise, environmental training programmes and communication synergies may lead to a momentous increase in terms of environmental controls, which represents a key benefit for the entire population. In view of this, synergies and institutional cooperation programmes are essential to instate a proactive process of shared knowledge and joint experiences. The purpose is to establish a consistent set of consolidated methodologies inspired by rigorous technical and scientific procedures. Communicating scientific evidence and best practices is the best approach to achieve and improve a shared cultural enrichment, by way of standardized procedures of proven effectiveness and utility. The Western Balkans Framework Programme Agreement (Apulian Region Action 2.3, Environment and Sustainable Development), has been an essential opportunity for dialogue and exchange, yielding a clear method in order to identify critical issues, thus meeting and exceeding a steady demand for qualified information and training. Markedly, this programme identified intervention strategies apt to pursue the common goal of environmental protection and nature preservation, with the specific goal of the requalification of the basin of Skadar (Albania), identified as one of the most important natural area of the Albanian territory to be managed according to the sustainability principles. This experience has been particularly significant, as this study comprises of two segments: a synthetic and a functional approach. The wide array and knowledge base of participating partners has greatly contributed to ensure a multidisciplinary, integrated approach to complex issues, as is the case with the management of a large water basin such as the Skadar lake, in an effort to protect and optimize the natural resources. Giorgio Assennato ARPA Puglia General Manager 2
INDEX INTRODUCTION THE ACQUATIC BIOLOGICAL RESOURCES THE BIOLOGICAL RESOURCES LIVING IN THE AQUATIC ENVIRONMENTS Dr. Nicola Ungaro (ARPA Puglia) BIOLOGY OF FISH Dr. Nicola Ungaro (ARPA Puglia) THE FISH COMMUNITIES AND THE RELATIONSHIPS WITH THE ABIOTIC FEATURES OF WATER BODIES Dr. Nicola Ungaro (ARPA Puglia) THE EXPLOITATION OF ACQUATIC BIOLOGICAL RESOURCES THE EXPLOITATION OF ACQUATIC BIOLOGICAL RESOURCES Dr. Roberto Carlucci (University of Bari) THE ASSESSMENT OF FISHERY RESOURCES THE ASSESSMENT OF FISH STOCKS: MAIN TOPICS ‐ Dr. Luca Ceriola (FAO) SAMPLING METHODS FOR THE ASSESSMENT OF THE FISHERY STOCKS Dr. Luca Ceriola (FAO) THE ASSESSMENT OF FISH STOCKS: HOLISTIC MODELS ‐ Dr. Luca Ceriola (FAO) THE ASSESSMENT OF FISH STOCKS: ANALYTICAL MODELS Dr. Luca Ceriola (FAO) ECOSYSTEM APPROACH ‐ Dr. Luca Ceriola (FAO) THE MANAGEMENT OF FISHERY THE MANAGEMENT OF FISHERY‐ Dr. Roberto Carlucci (University of Bari) FISH AND FISHERY IN THE SKODAR LAKE FISH SPECIES AND COMMUNITIES IN THE SKADAR LAKE Dr. Lindita Bushati (University of Skadar) THE FISHERY IN THE SKADAR LAKE ‐ Dr. Razim Suma (Region of Skadar) REFERENCES 3
Pag. 4 Pag. 5 Pag. 7 Pag. 14 Pag. 17 Pag. 21 Pag. 25 Pag. 29 Pag. 33 Pag. 37 Pag. 42 Pag. 45 Pag. 51 Pag. 53 INTRODUCTION The present document has been realized in the framework of FPA Western Balkans, intervention line 2.3 “Environment and Sustainable Development”, carrying out the Integrated Project RIVA subproject RIVA ““Environmental requalification of the basin of Skadar (Albania)”. The main objective of the project is to improve knowledge about a proper exploitation of the territory and of the safeguard and rationalization of natural resources management from the local population, the Municipality, the Region of Skadar and from all the stakeholders. The improvement of the territory planning ability can be useful for a more efficient management and protection of the wetland areas next to Skadar Lake, including the adoption of a unique protocol for the best Basin management. The project is primarily addressed to the local administrators (Skadar Region and Municipality), due to their role for the administrative and environmental management of the hydrographic basin. The project interventions and activities are targeted to the following three macro‐areas: ‐ Ecology and Environment; ‐ Territory Governance (Management and Regulations); ‐ Environmental Education (Training on Environmental Protection, Monitoring and Education). RIVA Integrated Project is funded by Italian decentralized cooperation (5 Italian Regions are involved and many partners from those Regions), under the coordination of the Italian Ministry of Foreign Affaires and Italian Ministry for Economic Development. The Italian Partnership includes: Basilicata Region, as RUP Coordinating Region for RIVA Project implementation; Puglia Region, which identifies ARPA Puglia (coordinator of the working group for the project implementation) and Polytechnic University of Bari as implementing bodies; Calabria Region with its Basin Authority, the Mediterranean University of Reggio Calabria, and ARPA Calabria; Sardegna Region with ENAS (Ente Acque della Sardegna); Sicilia Region with ARPA Sicilia and the Osservatorio delle Acque ‐ DAR (Dipartimento dell’Acqua e dei Rifiuti); Toscana Region with INCS (Istituzione Centro Nord Sud); Basilicata Region with University of Basilicata. The Albanian Partnership includes: the Albanian Ministry of Environment (Institutional Representative); the Ministry of Economic Development (Institutional Representative); the Regional Council of Skadar; the Municipality of Skadar. The technical coordination of the project is in charge of the Apulian Agency for the Environmental Prevention and Protection (ARPA Puglia). The training course on the Assessment and Management of Shared Fishery Resources is one of the activities planned in the framework of the project; the organization of the course was in charge of ARPA Puglia. The course was carried out in Bari (Italy) on April 2011. A training class has been held on the Assessment and Management of Shared Fishery Resources. The training activity included several frontal lessons, as well as in‐the‐field ones. This handbook includes the explanation of topics discussed during the abovementioned course. This handbook may be considered a synopsis for local technical partnership and for stakeholders interested in further studies on discussed subjects. We wish to thank all contributors, whose efforts have proved essential in the completion of this study. Anna Maria Pastorelli RIVA project coordinator 4
THE AQUATIC BIOLOGICAL RESOURCES
NICOLA UNGARO
ARPA Puglia, Scientific Direction. Corso Trieste 27 – 70126 Bari (Italy)
e.mail: [email protected]
THE BIOLOGIC RESOURCES LIVING IN THE AQUATIC ENVIRONMENTS
The aquatic resources are intended as exploitable by the human society.
There are two categories of aquatic resources, the renewable and the not renewable ones.
The not renewable resources are represented i.e. by the minerals and fossil fuels, while the
renewable resources are mostly the biological ones (i.e. the fishes).
The not renewable resources are characterised by scarce or null regenerative capacity, then
they are at exhaustion risk; the renewable resources are characterised by regenerative
capacity, then they are at exhaustion risk only if exploited over the regenerative capacity.
The biological resources are linked each other as a rule. The basic link is the trophic chain
(i.e. diatom species, copepods, anchovies, tunas), but the relationships among the trophic
chains can produce the trophic nets (see at the figure below). Looking at the mentioned
relationships, the biomass distribution by trophic levels is resumed in the trophic pyramid (see
at the figure).
An example of trophic net.
An example of trophic pyramid
Undoubtedly, all the species living in the aquatic ecosystems are strongly related. The
ecological equilibrium is a dynamic ones, thus changes in the population of one species affect
the characteristics of other populations. In example, if the sharks populations decline probably
the squids populations increase.
But, what are the main features of the aquatic biological resources?
- Consistency (stock dimension): Total Biomass, Total Number, Biomass Density,
Numerical Density;
- Quality (intrinsic characteristics): Growth Rates, Reproductive Rates, Mortality Rates.
Both consistency and quality features of the biological resource contribute to the expression
of the “Minimum Population Doubling Time”, or the time period in which the population
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doubles. This time, as well as the consistency and quality of the renewable resource, is
regulated by the carrying capacity of the system also.
The most important aquatic biological resources are the fishery ones. The fishery resources,
intended as fishes, crustaceans and molluscs, are categorised as “demersals” if living close to
the bottoms, while “pelagics” if they live in the water column.
Fishes live everywhere in the waters (fresh, transitional and marine waters); the crustaceans
live mostly in the marine waters, but also in the fresh and transitional waters. The molluscs
live in the marine and transitional waters as a rule, and they are very rare in the fresh waters.
The bony fishes represent the main fraction of the aquatic biological resources. The
zoological classification of bony fishes includes about n. 40 Orders and about n. 20,000
species.
Each fish species is defined by distinctive “taxonomic” characters: morphological,
morphometric and meristic ones.
The morphological characters include some features as body shape, coloration, fin presence
and position, mouth position, anus position, etc.
The morphometric characters include some features as measures and ratio between body
measurements (head length, eye diameter, fin length, etc.), while the meristic characters
include some features as numerical ones (n° of rays in the fin, n° of scales of the lateral line,
etc.).
Some of taxonomic characters can change in the same species according to the life cycle
(young specimens different from adults), sexual dimorphism, body modification due to the
reproduction, latitudinal distribution of the species and low genetic exchange, environmental
conditions.
Changes of water temperature, of the habitat, of the fish diet and also the generic stress, can
produce anomalies in the vertebrae number, of the fins, in the number of the fins rays and
scales.
Looking at the morphological, morphometric and meristic characters, each fish species can be
identified and classified according to the available taxonomic keys of identification.
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THE AQUATIC BIOLOGICAL RESOURCES
NICOLA UNGARO
ARPA Puglia, Direzione Scientifica. Corso Trieste 27 – 70126 Bari (Italy)
e.mail: [email protected]
BIOLOGY OF FISH (FEEDING, GROWTH, REPRODUCTION)
Each fish species is characterized by specific biological features, the most important related to
the feeding, the growth and the reproduction.
Feeding
According to the feeding behaviour, the fish species are grouped in the main trophic guild:
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Omnivorous;
Herbivorous;
Detritivorous;
Invertivorous;
Piscivorous.
The Omnivorous fishes eat all can contain organic substance (dead organisms, particulate
organic matter, algae, small invertebrates, small fishes).
The Herbivorous fishes eat algae and aquatic plants as a rule.
The Detritivorous fishes eat mainly organic particulate matter and small invertebrates living
on and in the bottom substrates. Some of the species can eat organic materials in the water
also.
The Invertivorous fishes eat mainly invertebrates living in the water and on the bottom; this
trophic guild can be subdivided as Benthivorous, Zooplanktivorous, Insectivorous.
The Piscivorous fishes eat mainly other fishes and/or other swimming preys.
The shape of the mouth and its relative dimension, as well as the presence, dimension and
shape of teeth, can be indicative of the feeding behaviour of the fish species. However, the
fish diet can vary during the life cycle due to the somatic growth and/or habitat changes.
Grey mullet, a detritivorous fish. Sea Bream, an invertivouros fish.
Sea bass, a piscivorous fish.
The distribution of fish species by trophic guilds depends on the environmental characteristics
of the surface waters (rivers, lakes, transitional and marine waters) and it is strongly related to
the local habitats.
The invertivorous fishes represent the main fraction of the fish assemblages as a rule, while
the piscivorous fishes are usually the minority.
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Growth
The growth of fishes is a metabolic affair. In fact, it depends on the balance between food
intake and energy consumption: Food intake Rate minus Energy consumption Rate = Growth
Rate.
The length-weight and age-length (weight) relationships are intrinsic characteristics of the
single fish species, due to the specific genetic features.
Nevertheless, the growth is also affected by the environmental (hydrology, water quality,
temperature, etc..) and local situations (food availability, stress, etc.).
The length-weight relationships fit as a rule the equation:
- Weight = a*Length^3
The age-length relationships fit the von Bertalanffy equation:
-L(t) = L∞(1-e^-k(t-t0))
Where: L(t) = length at age t; L∞ = maximum length; K = growth rate; T0 = birth time.
An example of length - weight relationship.
An example of age - length relationship.
The age and growth of fishes is estimated by means of otoliths and scales readings or
analyzing the length frequencies from experimental and commercial fishery catches.
An otolith (look at the growth rings).
A scale (look at the growth rings).
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Relationship between otolith/scale rings and growth.
Age cohorts from the analysis of length-frequencies.
Reproduction
The reproduction is one of the most important (and critical) phase in the fish life. The fish
attains the “first” sexual maturity according to the genetics of the species (typical age and
length) and the changing in the environmental factors (light, temperature, etc.).
The reproduction physiology can be affected by some population and community features, in
example an abnormal population density, an unbalanced sex ratio, a stress condition, etc..
Moreover, the development of sexual organs (gonads) and the following spawning phase can
affect other aspects of the fish biology, as the feeding behaviour.
Feeding activity during the gonad development and spawning phase.
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The sexual maturity is highlighted by the changes in the reproductive apparatus (gonads),
depending on cellular modifications in the testis and ovary (see at the figures below).
Fish ovary section at the microscope: cells at different maturity stages.
The study of fish reproduction needs the knowledge of the basic terminology:
-
Oviparous species = eggs laying;
Ovoviviparous species = incubate eggs and liberate young without providing any
maternal source of nourishment other than that in the egg;
Viviparous species = nourish developing embryos;
Gonochoristic (dioecius) species = two different sex;
Hermaphroditic species = individual produces both eggs and sperm;
Sequential hermaphrodites species = first male (protandrous) or first female
(protogynous);
Semelparous (monocyclic) species = spawn only once before they die;
Iteroparous (polycyclic) species = spawn two to several times during a lifetime;
Total (isochronal) spawner = the whole gonad matures and all the eggs or sperm are
spawned in a single breeding period (short period, one week….);
Partial (heterochronal) spawner = the spawning period is protracted and the gonad can
include eggs or sperm at different maturity stages.
The maturity of fish can be investigated looking at the macroscopic features of the gonads.
According to the different developing stages the gonads change general aspect, shape, relative
dimension, position and colour, as it was shown in the example reported in the following
picture.
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Changes in shape and colour of fish ovary during the maturity cycle.
The macroscopic stages of the gonads are classified according to maturity scales. There are
many maturity scales available in the scientific literature, one of the most famous the
historical NIKOLSKI’S SCALE for the bony fishes.
NIKOLSKI’S SCALE (teleosts)
Stage I. Immature: Young individuals which have never spawned yet.
Stage Il. Quiescent: gametes either have not yet started to develop or else have already been
discharged; the swelling process in the cavity of the gonad is complete; gonads are of very
small size; eggs not visible to the naked eye.
Stage III. Ripening: eggs visible to the naked eye; the gonad increases in weight very rapidly;
testes change from transparent to pale rose colour.
Stage IV. Ripeness: gametes ripe; gonads have reached their maximum weight, but the
gametes do not yet run out when light pressure is applied.
Stage V. Reproduction: gametes run out on the application of the lightest pressure to the
thorax; the weight of the gonad rapidly decreases from start to finish of the spawning process.
Stage VI. Spent: gametes extruded, and cavity of gonad swollen; gonad has the appearance of
an empty sac, usually with a few eggs remaining in females, or sperms in males.
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An example of fish at Nikolski’s stage IV.
The observations on the maturity stages are useful both for the estimation of the reproductive
(spawning) period and the estimation of the length-at-maturity.
The spawning period can be identified using the macroscopic observation of gonad
development together with the calculation of the “gonadic-somatic index”.
The gonadic-somatic index is the ratio between the gonads weight and the body weight
(gutted or not); it is variable as a rule according to the fish age (length) and the seasons. When
the fish attains the maturity age (length) we can found the largest ratio values during the
spawning season.
An example of gonadic-somatic index trend during one year time period.
The length at first maturity is conventionally the size at which the 50 % of the population
attains the advanced stages of gonad development (Lm50%).
The data needed for the estimation of the size at first maturity came from the calculation of
the maturity percentage (or ratio) per length class (number of mature individuals/total number
per each length class).
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The length- maturity relationships fit the logistic-like equation:
- Pr.mat = 1 / [1+ exp -b*(Lmat - Lm50)]
Where: Pr.mat = maturity proportion (ratio); Lmat = length corresponding at the maturity
proportion; Lm50 = length at maturity 50%; b = coefficient.
An example of length-maturity curve.
Of course, the knowledge on the reproduction features are useful for the conservation and
management of fish resources; in example, if we know the length at maturity and spawning
period of the species we can decide to use selective gears and/or ban the fishery during the
spawning period.
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THE AQUATIC BIOLOGICAL RESOURCES
NICOLA UNGARO
ARPA Puglia, Direzione Scientifica. Corso Trieste 27 – 70126 Bari (Italy)
e.mail: [email protected]
THE FISH COMMUNITIES AND THE RELATIONSHIP WITH THE ABIOTIC
FEATURES OF WATER BODIES (GEO-MORPHOLOGICAL, PHYSICAL AND
CHEMICAL CHARACTERISTICS)
The presence of the different fish species in the aquatic environment is conditioned by the
physical and chemical characteristics of water bodies.
Each fish species is distributed in the aquatic environment according to the geomorphological, physical and chemical characteristics of the water body, among which the
most important are:
-
Salinity;
Temperature;
Oxygen concentration;
Turbidity;
Water speed and circulation;
Habitat (water body typology, substrate);
Depth.
Some species are more tolerant with respect the changes of the environmental characteristics
(Euriecious), others are less tolerant and sensible to small variation of one or more parameters
(Stenoecious).
According to the salinity, the most sensible species live in the fresh water as a rule, due to the
peculiar physiology (osmoregulation): in example, the Carp, the Black Bullhead, the Northern
Pike, the European Perch, the Tench. There are some species that live in the salt water only, in
example the Tuna fishes.
On the contrary, there are fish species that can live at changing salinity values (non sensible),
both in fresh, transitional and marine waters, sometimes migrating for trophic or reproductive
purposes from salt to fresh water and viceversa: Anguillidae, Salmonidae, Mugilidae and
others.
According to the water temperature, there are some species that live at particular temperature
ranges only. With regard to fresh water, the Trout prefers relatively cold fresh waters (2-16
°C), as well as the Salmons in the marine waters (2-10 °C).
In the marine waters, some tropical fishes live at relatively high temperatures (20-30 °C).
Other species, both in fresh and salt water, are quite tolerant at the large variations of
temperature (i.e. Grey mullets, Cat fishes, Carp, European eel).
According to the oxygen concentration, most of the sensible species to the O2 concentration in
the water are the same sensible to the temperature and living in the coldest waters (Trouts,
Salmons, etc.).
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The fish species not sensible to the O2 values are often the same not sensible to the
temperature and living in the warmest waters (i.e. Grey mullets, Cat fishes, Carp, European
eel).
According to the water turbidity, there are some species that can live in clean water only,
mostly because of the peculiarities in the respiratory physiology (oxygen adsorption by the
gill) and nutrition strategy.
Other species are not sensible, and live in murky waters also (Grey mullet, Black bullhead,
Eel, Carp, Tench, Chub, etc.).
According to the water speed and circulation, there are some species that prefer to live in the
water with high circulation regime (good swimmers), and others prefer calm water, both in
fresh and salt waters.
In example: Trout = high water circulation, fresh waters; Tuna fish = high water circulation,
marine waters; Carp = low water circulation, fresh waters; Grey Mullet = low water
circulation, salt waters.
Moreover, the habitat typology is sometimes a determinant factor. The water turbulence, the
presence of rocky or soft bottoms, as well as the presence or not of plants and macroalgae can
affect the composition of fish communities. According to the habitat preferences and water
typology, the fish communities are categorised as reported below.
Fresh waters:
- Benthic (fish living close the bottom);
- Reophilic (fast-flowing, well-oxygenated stretches of river where the substratum is
characterized by gravel or sand);
- Lithophilic (calm water with aquatic vegetation, substratum characterized by gravel or
sand, good oxygen concentration);
- Phitophilic (calm water with prolific aquatic vegetation, muddy substratum, high
turbidity, relatively high temperature).
Transitional and Marine waters:
- Nektonic (fish species living in the water column);
- Benthic (fish species living close to the bottom):
Rocky bottoms
1 – Macroalgae coverage
2 – Phanerogams coverage
3 – No vegetation
Soft bottoms (sandy, muddy)
2 – Phanerogams coverage
3 – No vegetation
Mixed (rocky/sandy, look at the previous classifications)
- Nekto-benthic (fish species living both in the water column and close to the bottom).
The depth can be an important factor for the distribution of fishes mostly in the marine waters
and sometimes in the deep lakes (deeper than 100-200 m). The different distribution of fish
species by bathymetry is a common rule in the Oceans and Seas, being the species living at
different depth ranges characterized by typical adaptations (coloration, shape, etc.) to the
changing environment (strong difference of the hydrostatics pressure, light intensity, etc.).
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If we look at the pristine conditions of water bodies (“natural” physical and chemical
characteristics), the quali-quantitative composition of fish communities are regulated by the
ecological relationships among species and populations living in the same habitat.
The antrophic pressures (fishery, pollution, introduction of allochtonous species, etc.) can
impact the communities, causing sometimes the depletion of more sensible species and the
modification of the ecosystem equilibrium.
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THE EXPLOITATION OF ACQUATIC BIOLOGICAL RESOURCES
ROBERTO CARLUCCI
Department of Biology - University of Bari. Via Orabona, 4 - 70125 Bari (Italy)
e-mail: [email protected]
THE EXPLOITATION OF ACQUATIC BIOLOGICAL RESOURCES
Generally, stock assessment synthesizes information on the life history-traits of the target
species using mathematical models typical of the population dynamics to produce an
evaluation of the stock conditions in function of fishing effort. In fact, outputs from stock
assessments are used to determine stocks size, the sustainability of the fishery throughout the
definition of biological reference points and are stressed to forecast possible consequences of
alternative fishery management actions even tough with a degree of uncertainty.
Bottom trawling and the small scale fishery are the main fisheries in the Mediterranean basin.
Fishing gears such as trawl-net, long-line, purse seine, nets and traps are commonly used. The
fisheries are targeted to the catch of many species (Selachians, Teleosts, Crustaceans and
Cephalopods) .
Assessment of fishery resources
Biological marine resources represent a fundamental contribution of food for humankind.
However, up to date marine resources were globally exploited at increasing rates close to
fishing collapse. In fact, about 25% of global marine resources is exploited more than
Maximum Sustainable Yield (the figure below) and up to 50% resulted fully exploited.
Maximum Sustainable Yield (MSY) and fishing effort.
Fish Population Dynamic
Generally, the term population dynamic applied to a fish stock intuitively means the change
(negative or positive) in number of individuals through birth and recruitment, death (e.g.
natural or fishing mortality) and dispersal (e.g. migration) (see at the next figure).
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For a fish ecologist, the perception of growth is more multifaceted as growth in fish
populations can be discussed at two levels: the growth of individuals in the populations and
the growth of populations consisting of these individuals. Therefore, to understand the
production and dynamics of fish populations and their response to harvesting it is necessary to
consider not only changes in numbers but also changes in size distributions. The variation in
individual growth with density in fish populations comes about because growth is strongly
dependent upon food availability.
Fish population dynamic.
Mortality rates, Recruitment, Spawning Stock Biomass
The status of the stocks in many commercial fish species is assessed and for these species
biological reference points are available that are based on reliable estimates of the age
composition of the catches, allowing an evaluation of the historic development of fishing
mortality (F) and stock numbers by age group up to the present day.
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To obtain the best possible estimates, a variety of statistical methods were developed that use
additional information on catch per unit of effort (CPUE) derived from commercial and/or
research vessel data to improve estimates of fishing mortality and stock numbers.
Essentially, the methods reconstruct population size on the basis of an exponential decay in
numbers surviving as governed by removals by the fishing (F) and natural mortality rates (M).
For the latter component no direct information is available and therefore a common
assumption has to be made that natural mortality rate (M) is constant from year to year at
some average level that may be age group specific. In reality, natural mortality rate may vary
from year to year and the uncertainty introduced by the assumption of constant M depends
critically on the fraction of the total mortality rates (Z) represented by fishing mortality (F).
Although F or Z are output from the assessment process and delivered as an indicator of stock
status from the perspective of the stock and ecosystem they are essentially pressure indicators.
In particular, F0.1 is the fishing mortality rate at which the slope of the yield per recruit curve
as a function of fishing mortality is 10 % of its value near the origin. (see at the figure below).
F0.1
Fmax
Fishing mortality as biological reference points.
Generally, F0.1 is a conservative reference point for yield optimization because it results in
almost as such yield per recruit as F max does, but at lower levels of fishing mortality.
Fishing mortality rate which corresponds to the maximum yield per recruit as a function of
fishing mortality. Fmax is the F level that defines growth overfishing.
In general, Fmax is different than FMSY (the F that maximizes sustainable yield), and is usually
higher than FMSY, depending on the stock-recruitment relationship. By definition, Fmax is
always higher than F0.1.
Recruitment (R)
The number of juveniles fish (recruits) produced each year, which survive from spawning to
enter into the parental fish stock or into the harvesting phase of fishery.
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Spawning Stock Biomass (SSB)
The spawning stock biomass (SSB) is identified as the total weight of the fish in a stock that
are old enough to spawn or as the biomass of all fish beyond the age or size class in which
50% of the individuals are mature.
The spawning stock biomass provide a typical example of harvest control rule, incorporating
limit and target (and possibly threshold ) reference points into a simple schematic that shows
the action to be taken in terms of defining and setting fishing mortality rates or yields
depending on the estimated biomass level (see at the next figure).
Example of implementation of harvest control rules (from ICES, 1997).
Size/Age at maturity
Size above which 50 % of the population is mature, when combined with age at length keys,
can also be used to calculate the age at which 50% of the sampled population are mature.
The von Bertalanffy growth parameters
The von Bertalanffy growth function (VBGF) formulated on physiological considerations
assumes that a fish grows towards some theoretical maximum length or weight, and the closer
the length gets to the maximum, the slower the rate of size change will be (von Bertalanffy,
1938). Thus, in the model, Lt is the length at time t, L∞ is the asymptotic length of a given
stock would reach if they were to grow indefinitely, k is the growth rate parameter, and t0 the
age of the fish at zero length if it had always grown in a manner described by the equation
(figure below).
The von Bertalanffy Growth Function.
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THE ASSESSMENT OF FISHERY RESOURCES
LUCA CERIOLA
Food and Agriculture Organization of the United Nations. Viale delle Terme di Caracalla - 00153 Rome (Italy)
e-mail: [email protected]
THE ASSESSMENT OF FISH STOCKS: MAIN TOPICS
According to Saetersdal (1985) a general principle of fisheries management is “to obtain the
best possible use of the resource for the benefit of the community. According to such
concept, three main interconnected words or elements can be highlighted when fisheries
management planning and implementation is concerned: “best”, which is related to the
objective of management; “possible”, which refers to the time dimension of management and
thus to the sustainability of fishing through time; and community, which gives the spatial
dimension of the intervention. It is necessary to identify, in each particular case, the meaning
of these three words (Cadima, 2003) .
In general,
• Best, the first word or element refers to the objective of the management and can vary
depending on local specific needs. Possible options or objective to be achieved for a
management intervention are e.g. the largest catch, the highest economic value, the
maximum profit for fishermen, the highest income of hard currency; the highest
number of employees involved in fishing.
• Possible, the second word or element relevant in fisheries management refers to the
use of the resources through time. Fisheries management should be finalised to ensure
sustainability to fisheries by maintaining the resources above a critical level.
• Community, the third word or element relevant in fisheries management refers to the
area of intervention, could be a Country, a region or a group of stakeholders such as,
e.g., fishers, vessel owners, political parties.
These concepts can be visualised and best understood when the evolution of a fishery and of
the fishery studies are considered (see at the figure below).
Development of a fishery (G. Kesteven, 1973 modified).
21
In particular, four main phases can be identified in the development of a commercial fishery:
i) beginning of experimental or exploratory fishing trips, when the first boats initiate to
exploit natural resources in a specific area – during this period fishing effort and catch
increase, while the abundance of natural resources initiate to decline; ii) development, when a
fishing fleet increases its number and capacity – during this period the fishing effort increases
and the catches after a peak initiate to decline together with the natural resources; iii)
stabilisation, when owing to the decrease of abundance of natural resources and of total catch,
managers adopt measures to reduce the exploitation pattern and fishing capacity/effort is
reduced; iv) maintenance, when after the management intervention, natural resources, total
catch and fishing exploitation reach an equilibrium.
As described for fisheries, also the scientific research evolves or should evolve during the
above mentioned same phases: i) experimental surveys are carried out; ii) based on the results
of the surveys the assessment of the state of natural stocks are performed; iii) and iv) technical
advice on the level of exploitation (current, optimal and to be achieved to ensure
sustainability) to managers are formulated.
For these reasons, responsibilities for managers and scientific researchers can be identified as
follow:
•
•
Managers - setting of goals and/or objectives in the short and long term, the definition
of the management measures to consider;
Researchers - determination of current state of stocks and fisheries; definition of
possible range for exploitation; analysis of likely consequences of different/alternative
management measures.
Based on such responsibilities, the main objective of researchers involved in stock assessment
is: to advice management on likely consequences of different possible management measures.
In particular a stock assessment researcher should provide managers with information on how
much fish there is in a basin where fisheries take place, how much these fish produce, how
much catch can be taken from the stock, what is the effect of the fishery on the dynamics of
the stock (and vice-versa), and what is the effect of different management measures on the
dynamics of the stock and the fishery.
Purpose of Fish Stock Assessment
The main purposes of fish stock assessment are to provide managers with technical advice on
the optimum exploitation of aquatic living resources and on likely consequences of different
possible management measures. Living resources are limited but renewable and fish stock
assessment may be described as the search for the exploitation level which in the long run
gives the maximum yield in weight from the fishery. Basically with stock assessment,
scientists try to answer to the main questions on fish and on fisheries management: how much
fish is there in the basin? How much do they produce? How much catch can we take from the
stock? What is the effect of the fishery on the dynamics of the stock? (and vice-versa) What is
the effect of different management measures on the dynamics of the stock and the fishery?
22
Steps in Fish Stock Assessment
The assessment of fish stock involves the following steps: collection of data (which is a theme
in itself and is treated in a different context); decide the best model; assess the quality of data;
estimate the parameters of the model; calculate Biological Reference Points (BRP’s); assess
the current status and the historical trends of the stock and the fishery; evaluate the likely
consequences of alternative management options. All models, being a simplification of
reality, are based on assumptions (conditions for their application) and require input data to
provide outputs.
Decide the best model Science builds models or theories to explain and/or describe natural
phenomena. A model is a simplified description of the links between elements and/or
phenomena that are observed in nature. The decision on the best model to represent the
dynamics of the stock and the fisheries should be based on the characteristics of the stock and
the fishery, the management measures considered, and the type and quantity of data available
on the fishery and the stock.
Models for stock assessment can be divided into three main categories: i) holistic / global /
production models; ii) analytical / structural models; iii) individual based models.
Holistic models, also defined as global or production models, consider the stock globally as a
unit (do not take into consideration its structure). For such models the total biomass of a non
exploited stock cannot growth beyond a certain limit or Carrying Capacity, K.
Analytical models, or structural models, recognise that the stock is composed of different
groups individuals (cohorts) by different age and size. They consider the evolution of the
groups of over time to reconstruct the stock. Analytical models analyse and project the stock
and the catches for the coming years, by following the evolution of its different groups/cohort.
Individual based models recognise that the stock is composed of single individuals. Such
models consider and analyse the evolution of each individual (individual growth) over time to
reconstruct the stock.
Assessing the quality of data in stock assessment basically means to check if they are
adequate to the assumptions of the model to be used.
Estimating the parameters of a model is the process of fitting the model to the data available.
Such operation provides values for the parameters which characterise the model and allow to
obtain the numerical results of the analysis. Once the running of a model provides outputs on
the phenomenon to be described, the quality of the fit (of model to the data) should be
assessed. This step is based on statistical methods and provides information on how good the
model describes the data. It is the model that should fit to the data and NON vice versa.
Calculating the Biological Reference Points (BRP’s). To set objectives in fisheries
management, the values of fishing level which allow bigger catches while ensuring the
conservation of the natural resources (stocks) have to be considered. Likewise, the extreme
values of the biomass or the fishery exploitation level which can dramatically hamper the self
renovation of the resources (stocks) have to be considered. Such values of biomass or of
fishing level are defined as biological reference points (BRP).
The identification and definition of BRPs for stock assessment is still matter of active debate
worldwide. However three groups of BRPs are generally considered: Limit Reference Points
(LRP, e.g. fishery at maximum sustainable yield, FMSY); Target Reference Points (TRP, e.g.
fishing mortality which correspond to a specific level, of the maximum sustainable, generally
10% F0.1); Precautionary Reference Points (PRP, e.g. fishing mortality at a level lower than
the TRP which is identified according to a precautionary approach, Fpa).
LRPs are the maximum values of fishing mortality or minimum values of stock biomass,
which not to be exceeded. If such values are exceeded, it is considered that it might endanger
the capacity to self-renewal of the stock.
23
TRPs correspond to the level of fishing mortality or of the stock biomass which permit the
long-term sustainable exploitation of the stocks with the best possible catch. For practical
purposes, TRPs are converted, directly or indirectly, into values of fishing effort.
The precautionary principle proposed by FAO in the Code of Conduct for Responsible
Fisheries (FAO, 1995), states that limitations, uncertainties or lack of data for the stock
assessment cannot be justification for not applying regulation measures. Such uncertainties
therefore lead the scientific community to determine new reference points called
Precautionary Reference Points (PRPs). PRPs impose conditions more restrictive with respect
to TRP.
The evaluation of BRP should be periodic and values updated taking into account possible
changes in biological parameters or any possible changes in exploitation pattern.
To assess the current status and the historical trends of the stock and the fishery, different
indicators can be used. The classic model-based approach consider as indicators of stock
status, e.g., the stock biomass; fishing mortality; yield, total catch. Using such indicators, their
current value (or the most recently estimated) has to be compared to the BRPs. The choice of
such indicators can be relative to the BRP’s identified to manage the stock. In recent years the
use of time series of new groups of empirical indicators to assess the status of fish stocks was
proposed. Such indicators are generally linked to fishery independent (survey) data but they
can also be calculated, to some extent, using fishery dependent (catch) data. They describe
several aspects of a species considering the characteristics of both the entire stock and single
individuals pointing out their variation over time. Such empirical indicators comprise, e.g.,
the overall abundance of the stock (both in weight and number), the individual average size,
the size at first maturity, the occurrence, the number of recruits or of spawners. Specific
reference values can also be identified for such indicators when their time series is considered.
To evaluate the likely consequences of alternative management options for the stock and/or
for the fishery, projections regarding the development of the stock and of the catches to the
short and long term period should be carried out. To this extent, different options for
management and/or future scenarios should be verified.
The basic concept when projections in stock assessment are concerned is: knowing the
structure of the stock at the beginning of a certain time interval, it is possible to estimate the
characteristics of the stock during that period and project the structure of the stock for the
beginning of the next period (and in specific conditions for the following time interval as
well), for different values of fishing mortality. For fish, the time interval usually considered is
the year. For completing such projections several assumptions should be satisfied and the
biological parameters of the species considered such as growth, natural mortality and
maturity, should be known.
24
THE ASSESSMENT OF FISHERY RESOURCES
LUCA CERIOLA
Food and Agriculture Organization of the United Nations. Viale delle Terme di Caracalla - 00153 Rome (Italy)
e-mail: [email protected]
SAMPLING METHODS FOR THE ASSESSMENT OF THE FISHERY STOCKS
Objectives of sampling
Sampling to study aquatic living resources and fish in particular is planned and carried out to
achieve general or specific objectives. General objectives are mostly associated to questions
of scientific interest such us a better knowledge on the biology and ecology of a species to
understand natural processes and dynamics. Specific objectives are usually associated to the
need to ensure sustainability and conservation over time of natural resources (e.g. protection
of species or habitat of high ecologic importance) and/or to manage human activities related
to them (e.g. fisheries management,). In particular, specific objectives are related to the basic
managers’ questions: how much fish is there in a basin? How much do they produce? How
much catch can we take from natural stocks? What is the effect of the fishery on the dynamics
of the stock? What is the effect of different management measures on dynamics of the stock
and fisheries?
To answer to such questions, data on single species (e.g. classification, occurrence,
abundance, body size, age, sex, sexual maturity stage), community (e.g. total number of
species, biodiversity level, type of biocenoses) and/or environmental parameters (bottom type,
temperature, pH, O2, strength and direction of wind, water mass movements) in a specific area
can be collected through scientific studies.
In particular, depending on the aim of the study and on the type of analysis to be carried out,
different kind of sampling methods can be adopted. When working at single species level the
objectives of the studies could be a better understanding of population dynamic, stock
assessment, productivity, risk for stock integrity. When studies target the community
characterizing a specific area, investigation focuses on the risk of loosing species and of a
reduction of biodiversity. In studies on environmental factors, the variations in parameters and
the loss of sensitive habitats (not only for fish) are generally investigated.
To study species’ population dynamic and stock assessment, two types of sampling methods
can be used: direct and indirect methods. The choice of the sampling method for stock
assessment is generally based on the characteristics of the basin to be studies, on the type of
fishing activities carried out and on the resources (human and economic) available. It can be
very useful before planning a survey in the field to interview local fishermen for collecting
preliminary information on the main characteristics of the study area.
Direct methods
The direct methods involve the observation of natural resources through direct sampling and
comprise inter alia:
- Experimental surveys using different sampling gears (bottom and pelagic trawling,
traps, nets and long lines);
25
-
Visual census (periodic observation and record of species composition in the water by
an operator or using ROV (Remote Operating Vehicle). Visual census are generally
implemented when relatively small or very homogeneous areas are considered.
When planning experimental surveys several aspects should be preliminary considered on the
sampling are and gear and on the sampling scheme to be adopted for allocating the sampling
stations.
To identify the sampling area, its main characteristics in terms of bottom profile and type
(including biocenoses), water mass movement and overall surface should be defined.
The sampling gear should be defined to match with the main area characteristics and with the
bio-ecology of the species or group of species to be studied (e.g. pelagic, demersal,
benthonic). Information on the fishing activities traditionally carried out in the basin to be
investigated can concur to identify the best sampling gear.
The definition of the sampling scheme for a scientific survey generally depends on the
amount of information already available on the resources abundance and distribution.
Sampling schemes can be random (the sampling station are allocated randomly within a
specific area) or systematic (the sampling stations are allocated according to a fixed grid). The
adoption of random sampling ensures the best results for estimation of stock size, whereas
systematic sampling ensures the maximum information on the distribution through area, but
not necessarily the most precise estimate of biomass. Whatever sampling scheme is adopted,
the allocation of sampling stations generally follows a stratification which is related to the
bottom profile and to the density distribution of fish. When exploratory surveys are
considered, a random sampling scheme should be applied.
Indirect methods
The indirect methods involve observation of the natural resources by studying and sampling
the commercial catch/landing. Such methods assume that the abundance of fisheries resources
is reflected in their abundance in the catch. Indirect methods for studying fisheries resources
involves inter alia:
- Fishery observer on board of fishing vessels/boat, an operator embark on fishing unit
and record the type and quantity of the catch during the entire fishing trip);
- Sampling at the landing site directly from vessels/boat, total catch is recorded at the
landing site and samples are collected for detailed investigation);
- Sampling at fish market (if any), as for the sampling at landing site, but at the fish
market.
When sampling of the catch is concerned (both on board, at landing site or at the fish market),
the type of sampling, sampling periodicity (daily, weekly, monthly, quarterly) and quantity
have to be planned a priory best possible information on fisheries, ant type and quantity of the
catch.
For planning a sampling at landing sites an overall distinction between three worlds should
betaken into account: population, which is entirely or partially unknown, its elements can be
of various types with known characteristics; sample, which is completely known, from the
sample data the characteristics of the population will be estimated; sampling, that is the set of
samples of the same size that could be selected with the same criterion from the population; it
can be simple random (for homogeneous population), stratified random (for non
homogeneous population), cluster (the population is partitioned into groups or clusters which
do not have necessary the same size).
26
In general, stratification and sampling allow to reconstruct the population size without
measuring it entirely every time. In this document, some details on stratified random sampling
are provided only.
In stratified random sampling, stratification is generally by geographical area (port or landing
site), fishing gear (net, lines, traps, etc.), fishing boat characteristics, main fishing area (wind
sheltered/exposed area, deepest part, etc.) and target species (migratory or local fish,
crustaceans, etc). The sampling should cover all the population according to the categories
(strata) identified. Therefore the proper identification of sampling strata is crucial to obtain
reliable results from the final analysis of the data.
An example of selection of sampling strata by area or landing site, boat type and fishery target
species is provided below.
- Area: landing site or fish selling point SP 1.
- Type of boats: with or without engine, length overall, LOA (< 4 m LOA; 4-6 m LOA;
> 6 m LOA).
- Target species: none, all species to be considered.
Strata 1 all the boats landing at SP 1 < 4 m LOA without engine;
strata 2 all the boats landing at SP 1 < 4m LOA with engine;
strata 3 all the boats landing at SP 1 4-6m LOA without engine; etc.…
Main pros and cons of direct and indirect sampling methods for stock assessment
Direct methods - main pros
- Area coverage, depending on resources the sampling could be potentially extended to entire
basin of interest;
- According to the sampling gear, a large fraction of the population (potentially the entire
population) can be sampled and investigated;
- Allow to study all the species (and biodiversity) characterising the study area, including
species assemblages and biocenoses;
- Some models to perform stock assessment using survey data have been developed and
successfully tested/applied;
- Provided that standardised protocols are used, the survey is repeatable over time and in
different areas and the results comparable to obtain time series or comparison between distant
areas;
Direct methods - main Cons
- Costs of surveys are generally high (in many cases it is not possible to perform more than 1
or 2 surveys per year);
- A properly equipped vessel/boat is necessary;
- Most of the classic stock assessment methods cannot be successfully applied to survey data
and/or time series;
- Do not allow to obtain absolute abundance values (only relative estimations can be
produced);
- If the sampling period does not cover the reproduction peak of a species only incomplete
information on its biology can be obtained.
Indirect methods - main pros
- Costs are generally lower than surveys (monthly sampling are generally foreseen and carried
out)
27
- Almost all the classic stock assessment methods can be successfully applied to commercial
catch data and/or time series;
- Allow to estimate absolute values of abundance and reference points;
Indirect methods – main Cons
- They are based on the assumption not verified that the total abundance of wild stocks can be
properly described by commercial catch
- Depending on the selectivity of the fishing gear, only a portion of the population (generally
the fraction of adults) can be sampled and investigated;
- They allow to study only commercial species and not all the species (and biodiversity)
characterising a specific area;
- Comparability between different areas is not always appropriate.
Which method should be used for stock assessment studies?
In many cases a choice is not possible and scientists and manager must use the most suitable
system to obtain the necessary information for fishery management. However, when
economic and human resources are not limiting factors, both direct and indirect methods
should be used for stock assessment studies.
28
THE ASSESSMENT OF FISHERY RESOURCES
LUCA CERIOLA
Food and Agriculture Organization of the United Nations. Viale delle Terme di Caracalla - 00153 Rome (Italy)
e-mail: [email protected]
THE ASSESSMENT OF FISH STOCKS: HOLISTIC MODELS
Holistic models, also defined as global or surplus production models, consider the stock
globally as a big unit of biomass without taking into consideration its structure. Therefore,
surplus production models deal with the entire stock, the entire fishing effort and the total
yield obtained from the stock, without entering into any details such as the growth and
mortality parameters, or the effect of fishing gears on the catch.
More in details, basic assumptions for global or surplus production models are:
• The models deal with the entire stock and the entire fishing effort;
• Stock can be described solely by its biomass;
• “Natural” Rate of change in biomass depends on current biomass only;
• There is a maximum biomass that the system can support defined as carrying capacity
(K);
• The relative rate of increase of biomass is maximum when the biomass is close to
zero, and zero when the biomass is at the maximum level;
• The objective of the application is to determine the optimum level of effort, that is the
effort that produces the maximum sustainable yield;
• They are much simpler and the data requirements are less demanding than the other
models;
• They can be applied when data are available on the yield (by species) and of the effort
over a certain number of years
• The fishing effort must have undergone substantial changes over the period covered.
The objective of applying surplus production models is to obtain an estimation of the stock
biomass, the Maximum Sustainable Yields (MSY), and to determine at which level of fishing
effort MSY has been or will be reached. Some biological reference points (BRPs) can be
estimated using the surplus production models including, inter alia, the already mentioned
MSY, the current value of stock biomass (Bcurr), the biomass of the virgin population (without
fishery exploitation, B0); the value of fishing effort corresponding to the MSY (FMSY). More
detailed description of BRPs that can be estimated using Surplus Production Models is
reported in a further section.
Shaffer and Fox models
The most common and simplest surplus production models are the Shaffer and the Fox
models. Both models conform to the assumption that the biomass in a virgin population and
without fishing can growth up to a maximum called carrying capacity of the system (K)
according to an asymptotic function (logistic or similar). However, they differ on the form of
the relative and absolute biomass growth rate in function of the total biomass.
The main charts describing the variation of the stock biomass in the Shaffer and Fox models
over time are reported below.
29
Biomass vs Time
Relative Biomass Growth Rate vs Biomass
K
Biomass
Rel G. rate
r
0
0
Biomass
K
r
Abs G. Rate
0
Relative Biomass Growth Rate vs Biomass
R el G. rate
Absolute Biomass Growth Rate vs Biomass
Time
0
Biomass
Biomass
K
K
Absolute Biomass Growth Rate vs Biomass
Biomassa vs Tempo
Biomass
A bs G. R ate
K
0
0
Biomass
Time
Shaffer models.
K
Fox models.
The variation of the stock biomass over time according to surplus production models vary
significantly when fishing start. In particular for such models, and in general, the stock
biomass can growth, remain stable or decline depending on the level of fishing exploitation
which is applied to the system.
In particular, the evolution of a population depends on relative values of catch and natural
growth. Three cases can be easily identified: i) Catches > Natural growth; ii) Catches <
Natural growth; iii) Catches = Natural growth.
i)
Catches < Production: the capacity of renewal of the sock compensates the loss
due to fishing and the stock growths over time.
30
Biomass
Evolution of Biomass with fishing
Catches<Production
Time
Dot line = variation of biomass without fishing
Vertical line = fraction of stock removed by fishing
Red line = variation of biomass without fishing
ii) Catches > Production: the capacity of renewal of the sock is not enough to compensate the
loss due to fishing, the stock decline over time.
Biomass
Evolution of Biomass with fishing
Catches>Production
Tim e
Dot line = variation of biomass without fishing
Vertical line = fraction of stock removed by fishing
Red line = variation of biomass without fishing
iii) Catches = Production: the capacity of renewal of the sock is equal to the loss due to
fishing, the stock remain stable over time.
Biomass
Evolution of Biomass with fishing
Catches=Production
Tim e
Dot line = variation of biomass without fishing
Vertical line = fraction of stock removed by fishing
Red line = variation of biomass without fishing
31
Biological Reference Points
The BRPs that can be estimated applying production models are:
MSY – Maximum Sustainable Yield
BMSY – Biomass producing MSY
FMSY – Fishing mortality which, if applied for a long period, will lead the stock to BMSY
F0.1 – Fishing mortality level at which the increase in Yield with F is 10% of Virgin Biomass
B0.1 – Biomass at which the stock natural relative rate of increase is F0.1
Some diagnostic charts and BRPs that can be obtained using surplus production models are
reported below.
SY0.1Bvirgin
MSY
SY0.1Bvirgin
MSY
Fox Model
Schaefer Model
Yield
Biomass
Yield
Biomass
F0.1 FMSY
F0.1 FMSY
Variation of yield as a function of fishing effort and position of biological reference points according to the
Shaffer (left) and Fox (right) models.
200%
Trends in diagnostic ratios
"B/BMSY"
150%
100%
50%
0%
Variation of the ratio between current biomass and biomass at MSY (Bcur/BMSY). Current Biomass is expressed
as % of BMSY. This chart describes the current situation responding to the question: where are we now with
respect to the optimum?
300%
Trends in diagnostic ratios
"Fi/FSYi"
200%
100%
0%
Variation of the ratio between current fishing effort and the fishing effort at a sustainable level (FCur/FSYCur).
Current Fishing Mortality is expressed as % of F that produces the sustainable catch. This chart describes how is
evolving fishing effort with respect to a sustainable level responding to the questions: Where are we going? How
Fast?
32
THE ASSESSMENT OF FISHERY RESOURCES
LUCA CERIOLA
Food and Agriculture Organization of the United Nations. Viale delle Terme di Caracalla - 00153 Rome (Italy)
e-mail: [email protected]
THE ASSESSMENT OF FISH STOCKS: ANALYTICAL MODELS
Deterministic models, also defined as analytical or structural production models, recognise
that the stock is composed of different groups individuals (cohorts) characterised by different
age and/or size. Such models consider the evolution of the groups of individuals or cohort
over time to reconstruct the stock. They analyze and project the stock and the catches for the
coming years by following the evolution of its different groups/cohort.
More in details, according to such models to study its evolution over time:
• A population is split into categories or classes of individuals similar among them, e.g.
with the same age, size, sex;
• The evolution of the number and average characteristics of each class is modelled;
• Trends of Population or Total Catch obtained by summing/averaging the
characteristics of each class;
• Fishing is modeled as the removal of a part of the Numbers (and Biomass) from one or
more classes separately per each class.
The structural models are conceptually linked to the processes that affect the evolution of the
stock: recruitment (which gives a measure of the capability of a stock to rebuild itself),
mortality (the rate at which the stock decline, it can be natural or due to fishery); individual
growth (the time necessary to single of individual or cohort to increase its size and/or age, to
mature etc.). Accordingly, to obtain a description of the evolution of stocks there is the need
of models for each of these processes.
The objective of applying surplus production models is to obtain an estimation of the stock
biomass, of the Maximum Sustainable Yields (MSY), and to determine at which level of
fishing effort MSY has been or will be reached. Biological reference points (BRPs) can be
estimated using the structural models including, inter alia, the already mentioned MSY; the
value of fishing effort corresponding to the MSY (FMSY), the current value of fishing
mortality (F). Structural models also allow to carry out projection to the medium and long
term, among others, of the stock size and status, of the possible consequences of variation of
fishing mortality on both yield and stock size.
Evolution of a cohort during life
To apply structural models means to study the evolution of cohorts during the life cycle.
According to the biological cycle of each individual, the evolution of a cohort can be divided
into two main phases:
• Pre-exploitable phase, the life before recruitment –cannot be studied using fishery
dependent data (only hypotheses can be formulated on what occur to the cohort during
this phase);
33
•
Exploitable phase, the period of life during which a cohort may (potentially) be
exploited (fished) –can be studied using fishery dependent data (fish stock assessment
focus specifically on this phase).
A graphic description of the evolution of a cohort over time is reported in the next figure.
From the biological point of view, since when a cohort is born, two phenomena happen to the
fish: death or growth. This means that from the first moment in a cohort we observe a
numbers decrease due to individual mortality and an increase of the mean weight of survivors
(growth).
Survivors growth: mean size increases with the passage of time.
As a result of the decrease in number and increase of individual weight, the total biomass of
the cohort increases to a point. A description of the evolution of the total biomass of a cohort
and of the two main factors which contribute to such evolution (number decrease due to
mortality and individual growth) is reported below.
Evolution of a cohort during its life
Abundance in Biomass
Individual Mean Weight
Abundance in number
Age
34
A further factor affecting the evolution of a cohort is the reduction in number due to
exploitation or to fisheries (fishing mortality), which has to be added to the natural mortality.
More in particular, as far as exploitation and fish stock assessment is concerned, cohort's life
should be divided into 3 phases: unexplored phase, explored phase and exploitable phase (see
figure below).
The unexplored phase extends from hatching to the age or time of first capture, tc, which
depend on the selectivity of the fishing gear used; this phase cannot be explored using the
standard sampling methods for stock assessment.
The explored phase starts from tc and generally continue for the entire life span of the
individual; this phase can generally be explored using the standard sampling methods for
stock assessment (in some cases adults or large individuals become inaccessible to fishery,
thus preventing sampling and accurate studies on this phase).
The exploitable phase extends from the age or time at recruitment (tr), the age at which the
fish is potentially catchable, and generally continue for the entire life span of the individual;
this phase is the target of fish stock assessment using structural models.
Cohort during whole life - Modelling
Basic concepts for structural or analytical models are: the life of cohort can be considered as
divided into time intervals Ti; during each interval, it is assumed that the instantaneous
relative mortality rates are constant; validity depends on duration of intervals, consider
average characteristics of cohort during each interval.
More in particular, from a model point of view, the evolution of a cohort during whole
exploitable life start at age of recruitment tr, is explored according to Time Intervals Ti and
evolves from first to last interval (i) covering the whole exploitable phase. The time interval
usually considered is 1 year. During this time interval the structural models for stock
assessment investigate and describe the evolution of cohort and of catch in number.
Modelling life of cohort - Approach
The approach used to model life cohort when applying structural models for stock assessment
considers the following steps:
• To split life into several consecutive time (age)-intervals
35
•
•
•
Assumes that processes are constant within each of the time/age-intervals;
Model evolution of cohort abundance and average characteristics within each interval;
Obtain characteristics over life by adding and/or averaging the abundance and/or
characteristics at all time intervals.
A schematic representation of such approach and a simulation of a cohort evolution during the
whole exploitable life is reported in the figures below (during the evolution of a cohort the
total number decrease, the individual weight increase, the total biomass increase up to a
certain value).
Evolution of a cohort through life
-Modelling approach-
Age
Cohort “moves” one age-class in every year, abundance diminishes with time (see below).
Nº Survivors
Age
0
1
2
3
4
5
6
7
8
9
10
Evolution of abundance in nº of cohort during life
Year
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005
2000
1341
899
602
404
271
181
122
82
55
37
Age
For describing the evolution of cohort, models for the following characteristics at each age
through whole life of cohort are needed: Numbers in cohort; Numbers in catch; Mean weight
of survivors; Cohort Biomass; Catch in Weight. Modeling such characteristics is the main
subject of Structural or analytical models from stock assessment.
36
THE ASSESSMENT OF FISHERY RESOURCES
LUCA CERIOLA
Food and Agriculture Organization of the United Nations. Viale delle Terme di Caracalla - 00153 Rome (Italy)
e-mail: [email protected]
ECOSYSTEM APPROACH
Background
Ecosystems are complex and dynamic natural units that produce goods and services beyond
those of benefit to fisheries. Because fisheries have a direct impact on the ecosystem, which is
also impacted by other human activities, they need to be managed in an ecosystem context.
The meaning of the terms “ecosystem management”, “ecosystem based management”,
“ecosystem approach to fisheries” (EAF), etc., are still not universally defined and
progressively evolving. Nevertheless, the justification of the EAF is evident in the
characteristics of an exploited ecosystem and the impacts resulting from fisheries and other
activities.
In the expression “Ecosystem Approach to Fisheries (EAF)” the terms ecosystem, approach,
and fisheries are defined in dictionaries and in the scientific literature. Used together,
however, they imply a process using specific means to achieve selected objectives.
The broad principles and approach for effective and responsible fisheries management are
contained in the FAO Code of Conduct for Responsible Fisheries, many of which relate to an
ecosystem approach to fisheries (EAF). EAF is, in effect, a means of implementing many of
the provisions of the Code and provides a way to achieve sustainable development in a
fisheries context.
The main elements that will be considered in this contribution describe why the EAF is
necessary, the key features of the EAF; and a brief comparison of the EAF with respect to
other traditional approaches.
Why EAF?
Several elements leaded to the identification and development of principles and basic
concepts of the EAF. Among them a key role played the degradation of fishery resources and
the marine environment, the poor performance of current management practices, the
increasing awareness of the importance of addressing issues in a systemic way, the
recognition of a wide range of societal interests in marine ecosystems and the need to
reconcile these. For what concern the degradation of fisheries resources, the overexploitation
of several stocks is a problem widely acknowledged worldwide (see at the figure below).
Recovering
1%
7%
Depleted
17%
Overexploited
52%
Fully exploited
21%
Moderately exploited
Underexploited
According to FAO (Garcia and
De Leiva, 2004) about 75% of
natural stocks are depleted or
overexploited and only 24% is
moderately or under exploited.
3%
0%
10%
20%
30%
40%
50%
Exploitation level of wild stocks in the oceanic region of the world.
37
In addition, changes in ecosystem structure and functioning are recorded and a dramatic
decline of abundance and distribution of top predators in favor of species at lower level in the
trophic chain has been foreseen in the future if changes in management approaches do not
become effective (see below).
Schematic representation of the shift foreseen in the structure of the ecosystem in the oceanic region highly
exploited by fisheries.
In highly exploited regions like several areas in the Mediterranean basins, a dramatic biomass
decline of the main fishery target species was observed in 50-year time. A clear example is
provided in the next figure, where the abundance of the main fishery target species in the
Adriatic sea is described using the survey data collected during the Hvar expedition (19481949) and the MEDITS surveys (1997-1998).
HVAR expedition 1948-49
MEDITS programme 1997-98
Abundance of main fishery target species in a 50-year time period using bottom trawl surveys. The name and
year of the surveys considered is reported.
38
Key features of the EAF
The Ecosystem Approach to Fisheries strives to balance diverse societal objectives, by taking
account of the knowledge and uncertainties about biotic, abiotic and human components of
ecosystems and their interactions and applying an integrated approach to fisheries within
ecologically meaningful boundaries (FAO guidelines, FAO, 2003). It is important to note that
none of the principles that underlie the EAF are new. They can all be traced in earlier
instruments, agreements, declarations which were first developed at the beginning of 1970ies
and were collected under the EAF framework in very recent years. As a result, the EAF
highlights and reorganizes the principles of sustainable development making their application
more imperative.
From the “normative” point of view, the EAF principles point to maintaining ecosystem
integrity and improving human well-being and equity. To this extent, a large part of the EAF
is devoted to increasing awareness on the development of the human dimension of fishery
management.
The “operational” implementation of the EAF principles involves the application of the
precautionary approach, the broadening of stakeholder participation in decision making
process, the use incentives and the promotion of sectoral collaboration (collaboration between
categories involved in fisheries at all level) (see at the next figure).
Schematic representation of the elements which are part of the fisheries ecosystem: the marine environment and
the human dimension.
Based on such principles, some of the EAF key features can be summarized as follow:
•
•
it is participatory, promoting the consultation of all the stakeholders in decision
making process;
it is comprehensive, it ensures that all key components of the fishery system
(institutional, ecological and human) are taken into consideration, while also taking
into account external drivers;
39
•
•
•
it encourages use of the ‘best available knowledge’ in decision-making (improving
scientific understanding of ecosystems, of human and institutional systems is
fundamental for the application of EAF) and according to a precautionary principle,
fisheries management is explicitly required to take decisions also in the lack of
complete scientific knowledge;
it promotes the adoption of an adaptive management system (i.e. a system that
responds to signals from a monitoring process covering biological, social and
economic aspects) and should lead to more resilient and adaptive socio-ecological
systems;
it evolves from existing fisheries management institutions and practices.
The EAF is an extension of the traditional approaches to fisheries management. It foresees in
its logical framework: the setting of multiple objectives; the interaction with other sectors;
considering biodiversity and environment not only fish; adaptive strategy; extended
knowledge (not only scientific and including all the dimension of fisheries such as the natural
environment, the social and the economic aspects); interactive and/or participatory approach
in the decision making process; the development of public and/or transparent processes.
Comparison of approaches
In the last 20 years many approaches have been proposed for a sustainable use of aquatic
ecosystems and fisheries development, each emphasizing and giving relevance to specific
elements in fisheries and fisheries management depending on the context, e.g.: Ecosystembased fisheries management (EBFM); Ecosystem-based management (EBM); Ecosystem
approach to fisheries (EAF); Integrated coastal zone (or area) management (ICZM, ICAM);
Community-based fisheries management (co-management): Territorial user rights for
fisheries (TURFS).
In particular, sectoral and cross-sectoral approaches have been developed through time for
addressing fisheries management issues and needs. Sectoral approaches deal with goals and
intentions for sustainable development within the fisheries sector and makes sure that there is
consistency with the framework provided by the global strategy. In the sectoral approaches,
each sector is managed in a way that is consistent with overall principles and broad objectives
set for the given region. Sectoral approaches converge into wider approaches which consider
all the sectors integrating their needs and potentials. Cross-sectoral (integrated) approaches
expand the sectoral approach dealing with goals for sustainable development in a given region
and/or ecosystem including all sectors (e.g. fisheries, mining, shipping, tourism etc.), and
allocating rights to different user groups and reconcile conflicts. Cross-sectoral approaches
develop integrated plans for a given region/ecosystem, set common conservation and
development objectives, and allocate rights across sectors. Examples of cross-sectoral
approaches are the Ecosystem Based Fisheries Management, the Integrated Coastal Zone
Management and the Ecosystem Approach to Fisheries.
In particular the EAF try to balance the requirements and potential of the three main aspects
of the fisheries ecosystem: ecological, human and institutional. Considerable emphasis is
therefore given to promoting participation of stakeholders at all the levels of the management
decision process and to the implications that management decisions have on natural
ecosystem and human communities.
40
Being a wider and integrated approach, several challenges shall be faced to fully implement
the EAF:
• Existing governance systems (transparency and a vision of fairness, equity and
sustainability objectives shared among the various stakeholders and within society);
• Lack of coherence between economic, social and environmental policies;
• Globalization and international trade;
• Developing appropriate institutional frameworks across sectors and stakeholders;
• Climate change.
Conclusions
The process of evolution from conventional management has started and is gaining
momentum. Valuable experience is already available and valuable action can be readily taken.
The implementation of the EAF can only be incremental and adaptive. Guidance is provided,
by FAO and other institutions, on who to initiate the process of applying the EAF, but its
actual application can only take place with the main actors on the ground taking responsibility
for the needed changes and in a way relevant to a given context.
To facilitate the process of implementing the EAF, the FAO is develop a specific toolbox, is
progressing in the identification of appropriate indicators for EAF, continuing the work
initiated with consolidating best practices, working on the human dimensions (social,
economic and institutional considerations), directly assisting member countries with
implementation.
In particular several guidelines have been produced and are now available in electronic and
printed versions (e.g. Models for an ecosystem approach to fisheries; FAO Technical
guidelines for responsible fisheries, Fisheries Management Suppl. 2 and Suppl. 2 Add. 1; Put
into practice the Ecosystem Approach to Fisheries; Human dimensions of the ecosystem
approach to fisheries: an overview of contexts, concepts, tools and methods; The Ecosystem
Approach to Fisheries.
Finally a specific field work to promote the EAF is being implemented by FAO worldwide
including in the Mediterranean region (next figure).
Areas of FAO field activities for the implementation of the ecosystem approach to fisheries. Red dots areas of
specific actions; geometric shapes, region where work was initiated or is in progress.
41
THE MANAGEMENT OF FISHERY
ROBERTO CARLUCCI
Department of Biology - University of Bari. Via Orabona, 4 - 70125 Bari (Italy)
e-mail: [email protected]
THE MANAGEMENT OF FISHERY
The management of fishery needs a standardized approach, based on technical-scientific
information according to the fish species biological features (life history traits, genetics, etc.;
see below) and the stock assessment results (see at the previous lectures).
Other issues are related to the studies addressed to the definition of the Essential Fish Habitats
as nursery, spawning and feeding areas, or targeted to the identification and delimitation of
the Biological Protection Zones (BPZ). In the last times, the BPZs were showed to be useful
for the conservation of the nurseries and the spawning grounds of some commercial species,
allowing the spread of the specimens in the close areas (the spill-over effect) and the
replenishing of the exploited stocks.
Concerning the management of the fishery in the Mediterranean basin, the Italian and EU
regulations can represent a possible road map available for the non EU Countries, mostly
when shared fishery stocks occurred and for the future inclusion in the European Community.
Life history composition
There is extensive theoretical literature that distinguishes k-strategists from r-strategists
species, that is, species whose life history characteristics adapt them to living in undisturbed,
stable environments versus those adapted to living in frequently disturbed, variable
environments. Particular life history characteristics can be used to place species somewhere
along this continuum, and thus provide an indication of vulnerability to disturbance by
additional fishing mortality. Correspondingly, the life history character composition of
communities may provide a metric of the past impact of fisheries on that community.
Values for one or more of the parameters are available for many species from the literature.
This list, however, is far from comprehensive and for several of the parameters, values are
available for only a few species. Therefore, unless we have much better tabulations of life
history traits for large numbers of species, establishing the relationship with fishing impact
may suffer from circularity. Community metrics based on these parameters are calculated per
year by weighting the community species biomasses with the value of that particular life
history parameter.
Genetic diversity
Genetic diversity is a fundamental component of biodiversity and is as critical to
sustainability of our natural resources as are diversity of species and ecosystems.
Virtually all species are composed of populations that exist somewhat independently of each
other, and thus genetic diversity exists both within and among populations of one species.
Levels of genetic diversity in any one population are determined primarily by four forces:
mutation (the ultimate source of all genetic diversity); migration (the exchange of individuals
between populations); natural selection (the removal of ‘unfit’ individuals from the
42
population); and genetic drift (random changes in gene frequency of each generation due to
limited numbers of breeding adults).
Mathematical tools have been developed that allow diagnosis of the relative strengths of the
four genetic forces and, indirectly, properties of populations, such as population size, breeding
structure, and dispersal abilities.
Measurement of genetic diversity with molecular markers can add value to assessments of
ecological condition derived from other ecological indicators, such as landscape and species
assemblage indicators.
Population parameters can be effectively estimated with molecular markers and used to
characterize the geographic structure and connectivity of populations critical to interpreting
data for ecological assessments.
Genetic diversity also serves as independent indicator of environmental condition as
environmental stressors typically reduce genetic diversity, primarily through the forces of
selection and genetic drift. A reduction of genetic diversity reduces long-term sustainability of
the population.
Indicators of Habitat size and quality
The quality value of a marine ecosystem may be determined by the occurrence of specific
habitats (e.g. essential fish habitats as nursery, spawning and feeding areas), their size and
contribution to the maintenance of functional processes.
The impact of fishing activity on these habitats may be quantified observing the changes of
their effectiveness in providing ecosystem services (e.g. renewal of stock fractions in
exploited populations, maintenance of trophic web, etc.).
Indicators at the Ecosystem level
The ecosystem represents the highest hierarchical level of complexity of natural systems,
which summarizes interactions among all different components, both biotic and abiotic,
expressing them in terms of functional processes.
All this could have important implications in a management context, since the lower
hierarchical levels appear to be more sensitive to external disturbance/stress than ecosystem
processes; the ecosystem under stress apparently keeps much of its functions even though
species composition changes.
Moreover, from the combination between structures and processes can also emerge different
features, or emergent properties, not present before in the different components individually,
contributing to further increase the system complexity.
This complexity, characterized by high variability and unpredictability, represents one of the
main difficulties in identifying the ecosystem indicators.
Since main processes that occur in marine ecosystem are production, consumption, respiration
and cycling and transfer of energy, one useful way to better understand relationships among
different ecosystem components is the food web analysis.
Indeed, trophic interactions result to be the most important interactions between ecosystem
components, and a large number of studies have been dedicated to this issue during the past
two decades, including the development of trophic flow models.
In spite of this, many ecosystem indicators (e.g. tropho-dynamic indicators) resulted to be still
descriptive, and reference points have not yet been clearly identified.
43
Although models only tentatively could define the real world, they represent a valid tool for
capturing, in a coherent manner, ecosystem processes as a whole and giving answers to
management questions even in fishery.
The mean Trophic Level
The mean Trophic Level (TL) identifies the position of a species within the food web. It is
defined as the number of food interactions (food item passages) that allow a transfer of energy
from the primary producers and detritus to the given species throughout its diet.
Originally defined as integer values (TL = 1 primary producers and detritus; TL = 2
herbivores; TL = 3 carnivores), it was extended to fractional values for accounting the
omnivorous behaviour that characterize most of the living organisms.
Therefore, the trophic level of a species is defined as one for the primary producers and
detritus, and estimated for consumers, as the average trophic level of its preys weighted by
their fractional contribution in the diet (Stergiou and Karpouzi, 2002).
In accordance with this definition, the trophic level of the species is a real number ranging
from 2 (detritivorous or herbivorous) up to 5 (large top predators as tuna and sharks).
This value is calculated by means of the following formula:
TLi = 1 + Σj(TLj * DCij)
where the trophic level of the predator i (TLi), is calculated as a function of the fraction of the
preys j in its diet (DCij), and their trophic levels (TLj).
Likewise the mean trophic level can be determined at the community or ecosystem level
where the latter is a measure of the average number of passages, and gives an idea of the
development and complexity of the trophic web.
The Mean Trophic level can then be calculated as:
TLy = Σj(TLi * Yiy)/ Σj Yiy
where where Yiy is the catch of species (group) i in year y, and TLi is defined as in above.
The mean Trophic level of the landings is often used as a proxy of the mean trophic level at
the communities or ecosystem level.
Since fishing activities target large individuals (with high trophic level) thereby decreasing
the mean trophic level resulting in an effect known as “Fishing Down the Food Web” (Pauly
et al., 1998).
Therefore the mean trophic level of the catches is widely and efficiently used as an indicator
of fishing impact.
44
FISH AND FISHERY IN THE SKADAR LAKE
LINDITA BUSHATI
University of Skadar. Rruga 13 dhjetori - Skadar (Albania)
FISH SPECIES AND COMMUNITIES IN THE SKADAR LAKE
The Lake Skadar is considered as one of the 40 most famous lakes in the world. It is the
largest Lake in the Balkan Area under protection: 900 km2 protected in Montenegro and
Albania. The lake is included in the basin system of Adriatic Sea, is close to it and is
connected to the Adriatic marine waters by the Buna River (called Bojana in Montenegro)
and divided by the Countries border.
Actually, 495 km on the Albanian side are being protected as "Skadar Lake Natural Reserve”;
Lake Skadar, the Buna river, a beach stretching for miles, lagoons, marshlands and wide
pastureland are part of the new protected area. The lake is extended on the biggest part of
Zeta-Skadar lowland.
The lake of Skadar.
During the recent decades big changes have occurred in the Lake Skadar:
- Some new fish species were spontaneously introduced, while millions individuals of
other unknown species for this lake have been seeded for about 2-3 decades;
- The daily water regimen has changed because of the hydrologic changes in the course
of rivers Buna and Drini;
- Fishing has increased and has gone out of control;
- Pollutants in the lake have increased too.
These occurrences have brought changes in the fish populations of the lake, influencing the
quantitative and qualitative fishery catches also.
The structure of fish communities and the ranking of species importance highlights strong
variation with respect the past times. In example, the population of the high quality species
like Lime, Turbot, Mullet, and Eel too, has been reduced.
45
After the 70’s some exotic species, mainly imported from Asia, have been introduced in the
lake through fish restocking operations. The restocking of these introduced species was
almost completely interrupted during the 90’s and the populations significantly decreased due
to the unsuccessful reproduction in nature for some of them. Only the Prussian Carp
(Carassius gibelio) was adapted to the conditions of the lake.
The Perch (Perca fluviatilis) has entered the lake through Drini river. This fish found in the
lake favorable conditions and breeds successfully.
Perca fluviatilis.
The list of fishes of the Lake Shkoder included 55 species. N. 18 are allochthonous, nine of
them introduced through restocking operations. Nine fish species living in the lake migrate to
the sea, among them: Agone (Alosa fallax), Sea bass (Dicentrarchus labrax), Eel (Auguilla
auguilla), Mullet (Mugil spp., Liza spp.), Flounder (Platichthys flesus). Other migrant species
as the Sturgeons (Acipenser naccari, Acipenser sturio) were reported in the lake but actually
they can not be seen anymore.
Moreover, some endemic species for the lake were reported also:
- the Skadar nase (Chondrostoma scodrense);
- the Montenegro trout (Salmo montenegrinus).
However, these species have been never found since the time they were known as endemic
species and reported in the list.
The full list of fishes of the Lake Shkoder (see at the table below) was provided by Prof.
Dhimiter Dhora in the year 2009 and it was reported in the Bulletin of Natural Sciences of the
Tirana University “Luigj Gurakuqi”.
y
y
y
y
y
y
y
y
y
AGNATHA
I. Order PETROMYZONTIFORMES
1. Family PETROMYZONTIDAE
Genus Eudontomyzon
- Eudontomyzon stankokaramani KARAMAN 1974 Drini Brook Lamprey
Genus Lethenteron
- Lethenteron zanandreai VLADYKOV 1955 Adriatic Brook Lamprey
Genus Petromyzon
-Petromyzon marinus LINNAEUS 1758 Atlantic sea Lamprey
46
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
OSTEICHTHYES
II. Order ACIPENSERIFORMES
1. Family ACIPENSERIDAE
Genus Acipenser
- Acipenser naccarii BONAPARTE 1836 Drini Sturgeon
- Acipenser sturio LINNAEUS 1758 Sturgeon
III. Order ANGUILLIFORMES
1. Family ANGUILLIDAE
Genus Anguilla
- Anguilla anguilla LINNAEUS 1758 Eel
IV. Order CLUPEIFORMES
1. Family CLUPEIDAE
Genus Alosa
- Alosa agone SCOPOLI 1786 Agone
V. Order CYPRINIFORMES
1. Family BALITORIDAE
Genus Barbatula
- Barbatula zetensis SORIC 2000 Zeta Stone Loach
2. Family COBITIDAE
Genus Cobitis
- Cobitis ohridana KARAMAN 1928 Ohrid Spine Loach
3. Family CYPRINIDAE
Genus Alburnoides
- Alburnoides ohridanus KARAMAN 1928 Ohrid Spirlin
Genus Alburnus
- Alburnus scoranza HECKEL & KNER 1858 Scoranza
Genus Barbus
-Barbus rebeli KÖLLER 1926 Western Balkan Barbel
Genus Carassius
- Carassius gibelio BLOCH 1782 Prussia Carp
Genus Chondrostoma
- Chondrostoma nasus LINNAEUS 1758 Nase
- Chondrostoma scodrense ELVIRA 1987 Shkadar Nase
Genus Ctenopharyngodon
- Ctenopharyngodon idella VALENCIENNES 1844 Grass Carp
Genus Cyprinus
- Cyprinus carpio LINNAEUS 1758 Carp
Genus Gobio
- Gobio skadarensis KARAMAN 1936 Shkadar Gudgeon
GenusHypophthalmichthys
- Hypophthalmichthys molitrix VALENCIENNES 1844 Silver Carp
- Hypophthalmichthys nobilis RICHARDSON 1845 Bighead Carp
Genus Megalobrama
- Megalobrama terminalis RICHARDSON 1845 Black Amur Bream
Genus Mylopharyngodon
- Mylopharyngodon piceus RICHARDSON 1845 Black Carp
Genus Pachychilon
- Pachychilon pictum HECKEL & KNER 1858 Albanian Black Roach
Genus Parabramis
- Parabramis pekinensis BASILEWSKY 1855 White Amur Bream
Genus Pelasgus
47
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
- Pelasgus minutus KARAMAN 1924 Ohrid Minnow
Genus Phoxinus
- Phoxinus lumaireul LINNAEUS 1758 Italian Minnow
Genus Pseudorasbora
-Pseudorasbora parva TEMMINCK & SCHLEGEL 1846 Pseudorasbora
Genus Rhodeus
- Rhodeus amarus BLOCH 1782 Bitter ling
Genus Rutilus
- Rutilus karamani FOWLER 1977 Albanian Roach
- Rutilus ohridanus KARAMAN 1924 Ohrid Roach
Genus Scardinius
- Scardinius knezevici BIANCO & KOTTELAT 2005 Shkadar Rudd
Genus Squalius
- Squalius cephalus LINNAEUS 1758 Chub
Genus Telestes
- Telestes montenegrinus VOKUVIĆ 1963 Montenegro Rifle Dace
Genus Tinca
- Tinca tinca LINNAEUS 1758 Tench
VI. Order CYPRINODONTIFORMES
1. Family POECELIDAE
Genus Gambusia
- Gambusia holbrooki GIRARD 1859 Eastern Mosquito Fish
VII. Order GASTEROSTEIFORMES
1. Family GASTEROSTEIDAE
Genus Gasterosteus
- Gasterosteus gymnurus CUVIER 1929 Western Three Spine Stickleback
VIII. Order PERCIFORMES
1. Family BLENNIDAE
Genus Salaria
- Salaria fluviatilis ASSO 1801 Freshwater Blenny
2. Family GOBIIDAE
Genus Knipowitschia
- Knipowitschia panizzae VERGA 1841 Adriatic Dwarf Goby
Genus Pomatoschistus
- Pomatoschistus montenegrinus MILLER & ŠANDA 2008 Shkadar Goby
3. Family MORONIDAE
Genus Dicentrarchus
- Dicentrarchus labrax LINNAEUS 1758 Sea Bass
4. Family MUGILIDAE
Genus Liza
- Liza ramada RISSO 1810 Thinlip Mullet
Genus Mugil
- Mugil cephalus LINNAEUS 1758 Striped Mullet
5. Family PERCIDAE
Genus Perca
- Perca fluviatilis LINNAEUS 1758 Perch
Genus Sander
- Sander lucioperca LINNAEUS 1756 Pike Perch
IX. Order PLEURONECTIFORMES
1. Family Bathoidae
Genus Citharus
48
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
y
- Citharus linguatula LINNAEUS 1758 Spotted Flounder
2. Family PLEURONECTIDAE
Genus Platichthys
- Platichtys flesus LINNAEUS 1758 Flounder
X. Order SALMONIFORMES
1. Family SALMONIDAE
Genus Onchoryncus
- Onchoryncus mykiss WALBAURN 1792 Rainbow Trout
Genus Salmo
- Salmo dentex HECKEL 1851 Zubatac
- Salmo farioides KARAMAN 1938 Balkan Brook Trout
- Salmo marmoratus CUVIER 1829 Marble Trout
- Salmo obtusirostris HECKEL 1851 Soft Muzzled Trout
- Salmo montenegrinus KARAMAN 1933 Montenegro Trout
Genus Salvelinus
- Salvenilus fontinalis MITCHILL 1814 Brook Charr
Genus Thymallus
- Thymallus thymallus LINNAEUS 1758 European Grayling
XI. Order SILURIFORMES
1. Family ICTALURIDAE
Genus Ameiurus
- Ameiurus nebulosus LESUEUR 1819 Brown Bullhead
Information on the biology of some fish species recorded in the Skadar Lake.
-
-
-
Sturgeon (Acipenser sturio): length up to 1,5 m. Eat worms, clams, crabs and little
fishes. It migrates to the sea, coming for reproduction in fresh waters during the period
April-June.
Agone (Alosa fallax): length up to 40 cm. It feeds on different invertebrates especially
crabs but little fishes too. It lives in the sea and migrates in the lake for reproduction
on March-May period.
Albanian Lake Trout (Salmo dentex): length up to 50 cm. It feeds on different species
of invertebrates and fishes.
Scoranza (Alburnus scoranza): length up to 19 cm. It feeds mainly on zooplankton.
The reproduction occurs on gravel bottoms mostly in the spring season.
Carp (Cyprinus carpio): length up to 130 cm. It eat mainly benthic invertebrates, but
also water plants during the summer. The reproduction occurs during the spring
season, in the lake shallower waters colonized by macrophytes.
Lake Ohrid Nase (Chondrostoma nasus ohridanus): length up to 40 cm. It feeds
mostly on worms and fish eggs. The sexual maturity is reached at ages 3-4, and the
reproduction occurs mainly in the February-April. During winter the species
undergoes a crypto depression phase.
Prussia Carp (Carassius gibelio): length up to 45 cm. The reproduction occurs during
April-May months close to the coastline where is high the vegetation coverage. The
99% of the reproducing individuals are females, and the spawn is stimulated by the
sperm of other fishes.
Chub (Squalius cephalus): length up to 50 cm. It feeds mainly on bugs and their
larvae but it eat water plants also. The reproduction occurs at the end of the April on
gravel bottoms.
49
-
-
-
-
Albanian roach (Rutilus karamani): length up to 15 cm. It feeds on algae and other
water plants. The reproduction occurs in March, in the shallow coastal waters rich of
plants.
Shkadar Rudd (Scardinius knezevici): length up to 35 cm. It lives in calm waters and
during winter undergoes a crypto depression phase. The species feeds on water plants
and small invertebrates. The reproduction occurs during April-May months at the
coastline waters, among the underwater plants.
Perch (Perca fluviatilis): length up to 50 cm. It feeds on fishes and other animals. The
first reproduction occurs at 3-4 year age in the lake shallower waters colonized by
water plants.
Sea bass (Dicentrarchus labrax): length usually up to 50 cm, but it can reach 100 cm.
It feeds usually on fishes and crabs. It lives as a rule in the sea waters where spawns
during the December-March months. After the reproduction the young fishes enter the
Buna River and arrive in the lake. The fishes remain in the lake until 2-3 years old as a
rule, and then migrate for reproduction in the Adriatic Sea.
Eel (Anguilla anguilla): length usually up to 80 cm, but it can reach larger sizes. It
feeds on fishes and different invertebrates. During winter season the species remain in
the mud without feeding. In the months of October- November the males and females,
after about six and nine years respectively living in the lake, migrate through the river
Buna to the Adriatic sea for the reproduction that will take place in the Sargasso Sea.
After reproduction, the eel larvae move from the Sargasso Sea with the marine
currents and then they arrive in the Adriatic Sea after 3 years. In November-May
months they get into Buna River and arrive in to the lake.
Striped mullet (Mugil cephalus): length up to 60 cm. It feeds mostly on little
invertebrates. The reproduction occurs in the sea waters on August-September. Young
specimens enter the Shkadar Lake through Buna river.
Thinlip Mullet (Liza ramada): length up to 50 cm. It feeds on small benthonic and
planktonic organisms. The reproduction occurs in the sea waters on OctoberNovember.
Flounder (Platichtys flesus): length up to 50 cm. Eat benthonic macro-invertebrates
and fishes. The reproduction occurs in the sea waters during the January-March
period. After few months the young fishes enter into the lake through the river Buna. 50
FISH AND FISHERY IN THE SKADAR LAKE
RAZIM SUMA
Biologist - Skadar (Albania)
THE FISHERY IN THE SKADAR LAKE
General features
The Skadar lake surface varies from 368 km2 to 542 km2 depending from drought and floods
periods. The average depth of the lake is 8-10 m, reaching the 40 m depths in some specific
zones.
The main affluent is the Moraca River, but many other streams flow in the lake: Shegan,
Vukel, Rrjoll, Kozhnja, etc. Buna river is the only emissary and the relatively low distance
from the Adriatic Sea allows the exchange of marine and fresh water fish species.
The water basin is shared between the Countries of Montenegro and Albania; a surface of 149
km2 is included within the Albanian state border.
The ecological and economic importance of the Skadar lake is high in the geographic region;
it can be estimated an average fish production of 1,200 tons. per year, providing food for the
town and villages, employment and economic wellbeing for the citizens of the community.
Characteristics of the fishery
The fishery tradition in the lake date back to old times. The fishermen of the lake used and use
both fixed and mobile gears. The most utilized are the fixed gears “Lavoriero - Trap”, “Pot
(Stavnik)” and “Bertovello – Fyke net (Pinar)”, while the mobile ones are the trawl nets using
boats. For some species, as the Bleak, the fishing can be carried out by lights surrounding.
Other fishing gears are utilized also, such as gill nets, long-lines (n. 100 hooks each) and
harpoons. Moreover, a particular and unique fishery targeted to the mullets is practiced in
Dajlan.
According to the last two decades, the activity in the Skadar lake can be actually classified as
“artisanal fishery”.
Fishery of the Bleak in the Skadar lake (picture by D. Ulqini).
Unfortunately, some illegal practices, such as electric fishery and fishery with poisoning
substances, have been carried out until recent times in the lake.
51
Time trend of the catches and organization of fishery in the Skadar lake
The development of fishery in the lake has followed a time trend according to the years 1947,
1952, 1992, 1996, 2003.
With regard the catches, a strong increase was highlighted after the 1975, probably due to the
introduced species.
In the last decades, and mostly after the 90’s, some resources decreased; in the table below are
reported the average annual catch (tons.) in the time periods 1980-1990 and 2000-2010 for
some important commercial species.
Fish species
Alosa spp.
Mugilidae spp.
Anguilla anguilla
Dicentrarchus labrax
Platichtys flesus
Years 1980-1990
150
10
25
1
0.5
Years 2000-2010
70
65
15
-
Fishing resources underwent a situation of strong exploitation after the 90’s, and the
intervention of the International Community started after 2000. Italian government approved
the project “Support for the traditional fishing in Skadar lake”, and in the year 2001 a fishery
centre was built for the fishermen of Shiroka and Zogaj. The REC and the World Bank
funded other projects on the fishery, some of them still active.
In the year 2003 the organization for fish management was founded in some cities across
Albania and in Skadar (Shiroka) also, and it is actually operative and based on the approved
statute.
The fishery community of the Skadar consists of 500 fishermen, 70 % of them are full time
employed; the fishermen are not qualified and the salary level is quite low as a rule.
Fishery legislation and options for the future of fishery in the Skadar lake
In 1995 the Parliament of Albania approved the Law 7908, dated 5.4.1995, on Fishing and
Aquaculture. The following year (1996) the fishery inspectorate was established, while the
former law was recently integrated with an amendment dated 21.3.2002.
Due to the shared resources of the lake, the harmonization of the fishing laws between
Montenegro and Albania is needed. A common regulation is fundamental in order to manage
the fishery resources in the right way.
The common regulation will be targeted to:
- identify the zones and periods to be banned for the species conservation;
- repress the illegal fishery activities;
- allow the collaboration between the environmental rangers and the fishing
inspectorate;
- increase the professional level of the fishermen;
- support the fishery sector (financial support, infrastructures, markets, etc.);
- establish a program for the monitoring of the biological resources;
- assess and sustainably manage the fishery resources.
52
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54
Ministero degli Affari Esteri
REGIONE BASILICATA
Ministero dello
Sviluppo Economico
FPA Balkans - Line 2.3 Environment and Sustainable Development
Integrated Project RIVA
Sub Project RIVA
“Environmental requalification of the basin of Skadar (Albania)”
Phase 5 - Transversal supporting activities: sub-activity 5.1
ASSESSMENT AND MANAGEMENT
OF SHARED FISHERY RESOURCES
Manual of the Training Course
Agenzia Regionale per la Prevenzione e Protezione dell’Ambiente - Regione Puglia
Direzione Generale - Corso Trieste, 27 - 70126 Bari
Tel. +39 080 5460.111 - Fax +39 080 5460.150 - www.arpa.puglia.it
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Regione Puglia