204 research outputs found
Overview of computer simulations- Winter School on Towards Ecosystem Based Management of Marine Fisheries тАУ Building Mass Balance Trophic and Simulation Models
Computer simulation is the discipline of designing a model of an actual or theoretical
physical system, executing the model on a digital computer, and analyzing the execution
output. Simulation embodies the principle of ``learning by doing'' - to learn about the
system we must first build a model of some sort and then operate the model. The use of
simulation is an activity that is as natural as a child who role-plays. Children understand the
world around them by simulating (with toys and figurines) most of their interactions with
other people, animals and objects. As adults, we lose some of this childlike behavior but
recapture it later on through computer simulation. To understand reality and all of its
complexity, we must build artificial objects and dynamically act out roles with them.
Computer simulation is the electronic equivalent of this type of role-playing and it serves to
drive synthetic environments and virtual worlds
Marine fisheries sector in India-Resource endowments, infrastructure intensities and stakeholder analysis
World fish production has increased gradually from below 20 million tonnes in 1950 to more than 160 million tonnes in 2009. In a similar fashion the total fish production from India has grown up to around 8 million tonnes in 2010 from below 1 million tonnes in 1950. Marine fish production from India has increased from mere 50,000 tonnes in 1950 to 3.4 million tonnes in 2010. Aquaculture production has reached around 4 million tonnes in 2010 which was almost nil in 1950
Micro-analytical models тАУ relative yield per recruit- Winter School on Towards Ecosystem Based Management of Marine Fisheries тАУ Building Mass Balance Trophic and Simulation Models
Beverton and Holts yield per recruit model is a steady state model. A model that describes
the state of the stock and yield when the fishing pattern has been the same over a long
period so that all recruited fish alive are exposed to fishing is termed as a steady state
model
Estimation of growth parameters
A growth curve is an empirical model of the evolution of a quantity over time. Some
growth curves for certain biological systems display periods of exponential growth. A
Gompertz curve, named after Benjamin Gompertz, is a sigmoid function. It is a type of
mathematical model, where growth is slowest at the start and end of a time period. In
biology, a growth model is a depiction of length or weight of animals as a function of
age. In the case of fish populations, the study of growth is to determine the body size as
a function of its age. The growth model developed by von Bertalanffy (1934) has been
found to be suitable for the observed growth of most of the fish species. This model
expresses length as a function of age of the animal
Gear selectivity
Most of the fishing gears are selective for certain length range of fish thus excluding very
small and very big fish. This property of fishing gears is termed as gear selectivity. Thompson
and Ben-Yami (1984) considered selectivity as the capacity of any method of gear type to
capture certain fractions or sections of the fish population whether grouped by species,
age, size or behaviour and to exclude others. Gear selectivity needs to be considered
when we go for estimation of size composition of fish. The ultimate aim of studies on size
selection is to suggest suitable mesh sizes to catch fish of either economically optimum
size or an optimum size for the judicial exploitation of the stock. It is an important tool for
fisheries managers for regulating the minimum mesh sizes of fishing fleet by determining
the minimum sizes of the target species in certain fisheries. Mesh sizes are regulated to
conserve the spawning stock and to increase the long term sustainable yield. Estimation of
total mortality and prediction of future yield using prediction models etc. will be affected
by selectivity of gear
New methods of fish stock assessment
In the history of fish stock assessment two different approaches dominated. One using
time series of an indicator of stock abundance (standardized catch rate as a proxy for stock
abundance) along with time series of fish catch (Schaefer, 1954). These models provide
inference about current and target fish stock abundance and the maximum sustainable yield.
The second approach depend on a time series of detailed fish catch-at-age data in order to
reconstruct the virtual abundance of each annual cohort that had been fished (Pope, 1972
тАУ Virtual Population Analysis, VPA). In the last two decades there has been development of
a third approach known as Integrated Analysis (IA) that takes a more inclusive approach to
modeling fish population dynamics utilizing a wide range of available data
Marine fish production in India - Present Status
India being a tropical country is blessed with highly diverse nature of marine fishery
resources in its 2.02 million square kilometer Exclusive Economic Zone with an estimated
annual harvestable potential of 4.414 million metric tonnes. The marine fisheries sector
provide livelihood to nearly 4.0 million people of India and meets the food and nutritional
requirements of a significant proportion of the population. Also, it contributes to export
earnings of the country. Sustainable harvest of the marine fishery resources are necessary
as over exploitation of the resources is likely to harm the diversity and cause reduction in
the availability of some of the resources. Monitoring of the harvest of the diverse marine
fishery resources of the country is being carried out regularly by CMFRI since its inception
through a scientific data collection and estimation system from all along the Indian coast
leading to fish stock assessment for deriving management measures to keep the harvest
of the resources at sustainable levels
Macro analytical models - surplus production - Winter School on Towards Ecosystem Based Management of Marine Fisheries тАУ Building Mass Balance Trophic and Simulation Models
Surplus production models are an important approach to the study of harvested
populationsтАЩ dynamics. Such models are based on quite simple equations where both the
state of the population and fishing activity are each described by a single variable. These
models take into account only the interrelationship between observable inputs such as
fishing effort and observable output which is the yield obtained from the fishery. In surplus
production models the stock is considered as a single unit of biomass and modeling is not
based on any age structure, length structure or dynamics of the population in terms of
growth and mortalities. Instead, in these models the entire stock, the fishing effort and the
total yield obtained from the stock are studied and a relationship between these are
established without considering any micro level details such as growth, mortality, age at
first capture, mesh size effect etc. The objective here is to obtain optimum levels of effort,
which gives the maximum yield that can be sustained over a long period
Truss network analysis for fish genetic stock discrimination
Groups of potentially interbreeding natural populations, which are reproductively isolated from other such groups, is referred to as an animal species. Both genotypic and phenotypic homogeneity among groups belonging to the same species are seldom seen due to factors
like environmental differences, isolation by distance and natural selection. These distinctive groups are known as races and referred to as stocks in the case of fish species
Indian marine fishery resources - Present status
India being a tropical country is blessed with highly diverse nature of marine fishery
resources in its 2.02 million square kilometer Exclusive Economic Zone with an estimated
annual harvestable potential of 4.414 million metric tonnes. The marine fisheries sector
provide livelihood to nearly 4.0 million people of India and meets the food and nutritional
requirements of a significant proportion of the population. Also, it contributes to export
earnings of the country. Sustainable harvest of the marine fishery resources are necessary
as over-exploitation of the resources is likely to harm the diversity and cause reduction in
the availability of some of the resources. Monitoring of the harvest of the diverse marine
fishery resources of the country is being carried out regularly by CMFRI since its inception
through a scientific data collection and estimation system from all along the Indian coast
leading to fish stock assessment for deriving management measures to keep the harvest of
the resources at sustainable levels
- тАж