A system simulation model for exploring the population dynamics of Indian mackerel (Rastrelliger kanagurta) in the fisheries off peninsular Malaysia

Abstract

One of the ways to monitor fishing productivity and abundance over time is to use catch per unit effort (CPUE). For instance, declines over time of overall productivity, as measured by changes in catch per unit effort (CPUE), may be an indicator of declining fish stocks, or abundance as it implies that an increasing amount of effort is required to catch the same amount as in the past (Van Hoof & Salz, 2001; Grafton & Kirkley, 2006; Almeida et al., 2009). In this study, Indian mackerel is chosen as the case study. This species scientifically known as Rastrelliger kanagurta (Cuvier, 1817). It is a pelagic shoaling fish of the scombridae family which is widely distributed in the Indo-West Pacific region (FAO, 2014). According to Annual Fisheries Statistics Reports Malaysia, the amount of catch is increasing year to year (since 2003), however, the remaining stock of the species remain unknown. The lack of biological data were one of the limitations preventing identification of the Indian mackerel stock status in previous research studies. This was because of limited modelling tools. The assessments of the stock were totally dependent on survey sampling (tagging system) or the maximum sustainable yield (MSY) obtained from the trend landings of catch and effort data. And one of the methods to estimate the number of the Indian mackerel stock is through a simulation approach known as System Dynamics. System dynamics provides a degree of flexibility as it can integrate biological data with fisheries data available to estimate the stock status (Dudley, 2008; Garrity, 2011). In this study, there are three policies that are used to simulate the behaviour of the stock. Based on the open-access simulation results of Indian mackerel, the alternative policy implication is aimed to reduce the number of fishing boats and this will directly reduce the number of fishing days. However, the policy simulation results suggested that by reducing number of boats did not provide a big impact or change on the stock. The causes can be explained as; Indian mackerel is a In this study, Indian mackerel is chosen as the case study. This species scientifically known as Rastrelliger kanagurta (Cuvier, 1817). It is a pelagic shoaling fish of the scombridae family which is widely distributed in the Indo-West Pacific region (FAO, 2014). According to Annual Fisheries Statistics Reports Malaysia, the amount of catch is increasing year to year (since 2003), however, the remaining stock of the species remain unknown. The lack of biological data were one of the limitations preventing identification of the Indian mackerel stock status in previous research studies. This was because of limited modelling tools. The assessments of the stock were totally dependent on survey sampling (tagging system) or the maximum sustainable yield (MSY) obtained from the trend landings of catch and effort data. And one of the methods to estimate the number of the Indian mackerel stock is through a simulation approach known as System Dynamics. System dynamics provides a degree of flexibility as it can integrate biological data with fisheries data available to estimate the stock status (Dudley, 2008; Garrity, 2011). In this study, there are three policies that are used to simulate the behaviour of the stock. Based on the open-access simulation results of Indian mackerel, the alternative policy implication is aimed to reduce the number of fishing boats and this will directly reduce the number of fishing days. However, the policy simulation results suggested that by reducing number of boats did not provide a big impact or change on the stock. The causes can be explained as; Indian mackerel is aIn this study, Indian mackerel is chosen as the case study. This species scientifically known as Rastrelliger kanagurta (Cuvier, 1817). It is a pelagic shoaling fish of the scombridae family which is widely distributed in the Indo-West Pacific region (FAO, 2014). According to Annual Fisheries Statistics Reports Malaysia, the amount of catch is increasing year to year (since 2003), however, the remaining stock of the species remain unknown. The lack of biological data were one of the limitations preventing identification of the Indian mackerel stock status in previous research studies. This was because of limited modelling tools. The assessments of the stock were totally dependent on survey sampling (tagging system) or the maximum sustainable yield (MSY) obtained from the trend landings of catch and effort data. And one of the methods to estimate the number of the Indian mackerel stock is through a simulation approach known as System Dynamics. System dynamics provides a degree of flexibility as it can integrate biological data with fisheries data available to estimate the stock status (Dudley, 2008; Garrity, 2011). In this study, there are three policies that are used to simulate the behaviour of the stock. Based on the open-access simulation results of Indian mackerel, the alternative policy implication is aimed to reduce the number of fishing boats and this will directly reduce the number of fishing days. However, the policy simulation results suggested that by reducing number of boats did not provide a big impact or change on the stock. The causes can be explained as; Indian mackerel is a type of species that has a high growth rate and they spawn at minimum 3-4 times a year and produces 650,000 eggs per batch. Therefore, even with the high amount of catch, the stock may not be affected unless if there is a high rate of climate change impact.

Date of Award	Aug 2017
Original language	English
Awarding Institution	University of Portsmouth
Supervisor	Pierre Failler (Supervisor) & Andy Thorpe (Supervisor)