• Korean Journal of Fisheries and Aquatic Sciences
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• v.8 no.2
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• pp.47-60
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• 1975

For the calculation of population parameter and estimation of recruitment of a fish population, an application of multiple regression method was used with some statistical inferences. Then, the differences between the calculated values and the true parameters were discussed. In addition, this method criticized by applying it to the statistical data of a population of bigeye tuna, Thunnus obesus of the Indian Ocean. The method was also applied to the available data of a population of Pacific saury, Cololabis saira, to estimate its recuitments. A stock at t year and t+1 year is, $N_{0,\;t+1}=N_{0,\;t}(1-m_t)-C_t+R_{t+1}$ where $N_0$ is the initial number of fish in a given year; C, number o: fish caught; R, number of recruitment; and M, rate of natural mortality. The foregoing equation is $$\phi_{t+1}=\frac{(1-\varrho^{-z}{t+1})Z_t}{(1-\varrho^{-z}t)Z_{t+1}}-\frac{1-\varrho^{-z}t+1}{Z_{t+1}}\phi_t-a'\frac{1-\varrho^{-z}t+1}{Z_{t+1}}C_t+a'\frac{1-\varrho^{-z}t+1}{Z_{t+1}}R_{t+1}......(1)$$ where $\phi$ is CPUE; a', CPUE $(\phi)$ to average stock $(\bar{N})$ in number; Z, total mortality coefficient; and M, natural mortality coefficient. In the equation (1) , the term $(1-\varrho^{-z}t+1)/Z_{t+1}$s almost constant to the variation of effort (X) there fore coefficients $\phi$ and $C_t$, can be calculated, when R is a constant, by applying the method of multiple regression, where $\phi_{t+1}$ is a dependent variable; $\phi_t$ and $C_t$ are independent variables. The values of Mand a' are calculated from the coefficients of $\phi_t$ and $C_t$; and total mortality coefficient (Z), where Z is a'X+M. By substituting M, a', $Z_t$, and $Z_{t+1}$ to the equation (1) recruitment $(R_{t+1})$ can be calculated. In this precess $\phi$ can be substituted by index of stock in number (N'). This operational procedures of the method of multiple regression can be applicable to the data which satisfy the above assumptions, even though the data were collected from any chosen year with similar recruitments, though it were not collected from the consecutive years. Under the condition of varying effort the data with such variation can be treated effectively by this method. The calculated values of M and a' include some deviation from the population parameters. Therefore, the estimated recruitment (R) is a relative value instead of all absolute one. This method of multiple regression is also applicable to the stock density and yield in weight instead of in number. For the data of the bigeye tuna of the Indian Ocean, the values of estimated recruitment (R) calculated from the parameter which is obtained by the present multiple regression method is proportional with an identical fluctuation pattern to the values of those derived from the parameters M and a', which were calculated by Suda (1970) for the same data. Estimated recruitments of Pacific saury of the eastern coast of Korea were calculated by the present multiple regression method. Not only spring recruitment $(1965\~1974)$ but also fall recruitment $(1964\~1973)$ was found to fluctuate in accordance with the fluctuations of stock densities (CPUE) of the same spring and fall, respectively.

• Journal of Korean Society of Forest Science
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• v.53 no.1
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• pp.1-26
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• 1981

1. Aiming at supply of basic informations on tree species siting and forest fertilization by understanding of soil properties that are demanded by each tree species through studies of forest soil's morphological, physical and chemical properties in relation to tree growth in our country, the necessary data have been collected in the last 10 years, are quantified according to quantification theory and are analyzed in sccordance with multi-variate analysis. 2. Test species, japanese larch (Larix leptolepis Gord) and the Korean white pine, (pinus koraiensis S et Z.) are plantable in extensive areas from mid to north in the temperate forest zone and are the two most recommended reforestation tree species in Korea. However, their respective site demands are little known and they have been in confusion or considered demanding the same site during reforestation. When the Korean white pine is planted in larch sites, it has shown relatively good growth, but, when Japanese larch is planted in Korean white pine site it can be hardly said that the Japanese Larch growth is good. To understand on such a difference soil factors have been studied so as to see how th soil's morphological, physical and chemical factors affect tree growth helped with the electronic computer. 3. All the stands examined are man-made mature forests. From 294 Japanese larch plots and 259 Korean white pine plots dominant trees are cut as samples and through stem analysis site index is determined. For each site index soil profiles are made in the related forest-land for analysis. Soil samples are taken from each profile horizon and forest-land productivity classification tables are worked out through physical and chemical analyses of the soil samples for each tree species for the study of relationships between physical, chemical and the combined physical/properties of soil and tree growth. 4. In the study of relationships between physical properties of soil and tree growth it is found out that Japanese larch growth is influenced by the following factors in the decreasing order of weight deposit form, soil depth, soil moisture, altitude, relief, soil type, depth a A-horizon, soil consistency, content of organic matter, soil texture, bed rock, gravel content, aspect and slope. For the Korean white pine the influencing factors' order is soil type, soil consistency, bed rock, aspect, depth of A-horizon, soil moisture, altitude, relief, deposit form, soil depth, soil texture, gravel content and slope. 5. In the study of relationships between chemical properties of soil and tree growth it is found out that Japanese larch growth is influenced by the following factors in the order of base saturation, organic matter, CaO, C/N ratio, effective $P_2O_5$, PH, exchangeable, $K_2O$, T-N, MgO, CEC, Total Base and Na. For the Korean white pine the influencing factors' order is effective $P_2O_5$, Total Base, T-N, Na, C/N ratio, PH, CaO, base saturation, organic matter, exchangeable $K_2O$, CEC and MgO. 6. In the study of relationships between the combined physical and chemical properties of soil and tree growth it is found out that Japanese larch growth is influenced by the following factors in the order of soil depth, deposit form, soil moisture, PH, relief, soil type altitude, T-N, soil consistency, effective $P_2O_5$, soil texture, depth of A-horizon, Total Base, exchangeable $K_2O$ and base saturation. For the Korean white pine the influencing factors' order is soil type, soil consistency, aspect, effective $P_2O_5$, depth of A-horizon, exchangeable $K_2O$, soil moisture, Total Base, altitude, soil depth, base saturation, relief, T-N, C/N ratio and deposit form. 7. In the multiple correlation of forest soil's physical properties larch's correlation coefficient for Japanese Larch is 0.9272 and for Korean white pine, 0.8996. With chemical properties larch has 0.7474 and Korean white pine has 0.7365. So, the soil's physical properties are found out more closely related with tree growth than chemical properties. However, this seems due to inadequate expression of soil's chemical factors and it is proved that the chemical properities are not less important than the physical properties. In the multiple correlation of the combined physical and chemical properties consisting of important morphological and physical factors as well as chemical factors of forest soils larch's multiple correlation coefficient is found out to be 0.9434 and for Korean white pine it is 0.9103 leading to the highest correlation. 8. As shown in the partial correlation coefficients Japanese larch needs deeper soil depth than Korean white pine and in the deposit form of colluvial and creeping soils are demanded by the larch. Moderately moist to not moist should be soil moisture and PH should be from 5.5 to 6.1 for the larch. Demands of T-N, soil texture and soil nutrients are higher for the larch than the Korean white pine. Thus, soil depth, deposit form, relief, soil moisture, PH, N, altitude and soil texture are good indicators for species sitings with larch and the Korean white pine while soil type and soil consistency are indicative only limitedly of species sitings due to their wide variations as plantation environments. For the larch siting soil depth, deposit form, relief, soil moisture, pH, soil type, N and soil texture are indicators of good growth and for the Korean white pine they are soil type, soil consistency, effective $P_2O_5$ and exchangeable $K_2O$. In soil nutrients larch has been found out demanding more than the Korean white pine except $K_2O$, which is demanded more by the Korean white pine than Japanese larch generally. 9. Physical properties of soil has been known as affecting tree growth to the greatest extent so far. However, as a result of this study it is proved through computer analysis that chemical properties of soil are not less important factors for tree growth than chemical properties and site demands for the Japanese larch and the Korean white pine that have been uncertain so far could be clarified.