Overview of computer simulations- Winter School on Towards Ecosystem Based Management of Marine Fisheries – 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 – relative yield per recruit- Winter School on Towards Ecosystem Based Management of Marine Fisheries – 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 – 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 – Building Mass Balance Trophic and Simulation Models

Surplus production models are an important approach to the study of harvested populations’ 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