Open AccessThe dynamic system analysis of lemuru fishery in Bali strait by using biological parameter yield of some surplus production models
Author(s) -
Georgina Maria Tinungki,
Nasrah Sirajang
Publication year - 2019
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/279/1/012054
Subject(s) - maximum sustainable yield , fishing , stock (firearms) , productivity , stock assessment , biomass (ecology) , fishery , fisheries management , production (economics) , yield (engineering) , marine fisheries , fish stock , environmental science , ecology , biology , economics , geography , microeconomics , materials science , macroeconomics , archaeology , metallurgy
Stock assessment in any fisheries scientific study is an effort to determine the productivity of fishery resource, the effect of catch on resources and changes in catch patterns, for example due to implementation of management and development policies. It involves 3 (three) main aspects: the first, determine total biomass by using surplus production model; the second, determine recruitment (the number of fish that has reached the age during one recruitment season) can use Ricker model; the third, determine the equation of growth in the fishery can use Von Bertalanffy model. Mathematical models are mostly used to describe the dynamics of fish populations. In the use of appropriate models in stock assessment will result in a more appropriate basis in selecting fishing methods and advanced analysis of catches, hence required a plan in the sustainable management and utilization of fish resources. The study of sustainable dynamic of lemuru fisheries management in Bali strait is the dynamics of biomass of lemuru fishery by using the biological parameters yield of some surplus production models. By obtain the biological parameter values r, q and K, we obtain the dynamic trajectory between biomass and time, indicates that at the first year of observation, the biomass level is relatively high, but when several years later the biomass tends to decrease until it reaches the stable of biomass obtained for about 30 years and so on (t > 30).