Spatial interpolation is a common tool used in the study of fishery ecology, especially for the construction of ecosystem models. To develop an appropriate interpolation method of determining fishery resources density...Spatial interpolation is a common tool used in the study of fishery ecology, especially for the construction of ecosystem models. To develop an appropriate interpolation method of determining fishery resources density in the Yellow Sea, we tested four frequently used methods, including inverse distance weighted interpolation(IDW), global polynomial interpolation(GPI), local polynomial interpolation(LPI) and ordinary kriging(OK).A cross-validation diagnostic was used to analyze the efficacy of interpolation, and a visual examination was conducted to evaluate the spatial performance of the different methods. The results showed that the original data were not normally distributed. A log transformation was then used to make the data fit a normal distribution. During four survey periods, an exponential model was shown to be the best semivariogram model in August and October 2014, while data from January and May 2015 exhibited the pure nugget effect.Using a paired-samples t test, no significant differences(P>0.05) between predicted and observed data were found in all four of the interpolation methods during the four survey periods. Results of the cross-validation diagnostic demonstrated that OK performed the best in August 2014, while IDW performed better during the other three survey periods. The GPI and LPI methods had relatively poor interpolation results compared to IDW and OK. With respect to the spatial distribution, OK was balanced and was not as disconnected as IDW nor as overly smooth as GPI and LPI, although OK still produced a few 'bull's-eye' patterns in some areas.However, the degree of autocorrelation sometimes limits the application of OK. Thus, OK is highly recommended if data are spatially autocorrelated. With respect to feasibility and accuracy, we recommend IDW to be used as a routine interpolation method. IDW is more accurate than GPI and LPI and has a combination of desirable properties, such as easy accessibility and rapid processing.展开更多
Temporal changes in biological characteristics of small yellow croaker Larimichthys polyactis in the Yellow Sea were examined for the period of 1960–2008. The body size and age of small yellow croaker decreased subst...Temporal changes in biological characteristics of small yellow croaker Larimichthys polyactis in the Yellow Sea were examined for the period of 1960–2008. The body size and age of small yellow croaker decreased substantially, in particular, average length of fish in 2008 was reduced by ~85% than those occurring in 1985, and at that time ~93% of the total catch was dominated by one-year-old individuals. Correspondingly, growth parameters also varied significantly over the years, i.e., k（growth coefficient） and t_0（zero-length age） gradually increased from 0.26 and –0.58 year in 1960 to 0.56 and –0.25 year in 2008, respectively. Although, L∞（body length）sharply decreased from 34.21 cm in 1960 to 24.06 cm in 2008, and t_r（inflexion age） decreased from 3.78 year in1960 to 1.61 year in 2008. There was a great increase both in natural mortality coefficient and fishing mortality coefficient. However, according to the gray correlation analysis, changes in the biological characteristics of small yellow croaker were induced by different stressors ranked as： fishing vessel power〉feeding grade〉sea surface temperature. This study suggests that the active fishery management measures for biological characters of fish populations should be considered.展开更多
基金The National Basic Research Program of China under contract No.2015CB453303the National Natural Science Foundation of China under contract No.U1405234+1 种基金the Aoshan Science&Technology Innovation Program under contract No.2015ASKJ02-05the Special Fund of the Taishan Scholar Project
文摘Spatial interpolation is a common tool used in the study of fishery ecology, especially for the construction of ecosystem models. To develop an appropriate interpolation method of determining fishery resources density in the Yellow Sea, we tested four frequently used methods, including inverse distance weighted interpolation(IDW), global polynomial interpolation(GPI), local polynomial interpolation(LPI) and ordinary kriging(OK).A cross-validation diagnostic was used to analyze the efficacy of interpolation, and a visual examination was conducted to evaluate the spatial performance of the different methods. The results showed that the original data were not normally distributed. A log transformation was then used to make the data fit a normal distribution. During four survey periods, an exponential model was shown to be the best semivariogram model in August and October 2014, while data from January and May 2015 exhibited the pure nugget effect.Using a paired-samples t test, no significant differences(P>0.05) between predicted and observed data were found in all four of the interpolation methods during the four survey periods. Results of the cross-validation diagnostic demonstrated that OK performed the best in August 2014, while IDW performed better during the other three survey periods. The GPI and LPI methods had relatively poor interpolation results compared to IDW and OK. With respect to the spatial distribution, OK was balanced and was not as disconnected as IDW nor as overly smooth as GPI and LPI, although OK still produced a few 'bull's-eye' patterns in some areas.However, the degree of autocorrelation sometimes limits the application of OK. Thus, OK is highly recommended if data are spatially autocorrelated. With respect to feasibility and accuracy, we recommend IDW to be used as a routine interpolation method. IDW is more accurate than GPI and LPI and has a combination of desirable properties, such as easy accessibility and rapid processing.
基金The National Basic Research Program(973 Program)of China under contract No.2015CB453303the Aoshan Scientific and Technical Innovation Program under contract No.2015ASKJ02-05the Taishan Scholar Project Special Fund
文摘Temporal changes in biological characteristics of small yellow croaker Larimichthys polyactis in the Yellow Sea were examined for the period of 1960–2008. The body size and age of small yellow croaker decreased substantially, in particular, average length of fish in 2008 was reduced by ~85% than those occurring in 1985, and at that time ~93% of the total catch was dominated by one-year-old individuals. Correspondingly, growth parameters also varied significantly over the years, i.e., k（growth coefficient） and t_0（zero-length age） gradually increased from 0.26 and –0.58 year in 1960 to 0.56 and –0.25 year in 2008, respectively. Although, L∞（body length）sharply decreased from 34.21 cm in 1960 to 24.06 cm in 2008, and t_r（inflexion age） decreased from 3.78 year in1960 to 1.61 year in 2008. There was a great increase both in natural mortality coefficient and fishing mortality coefficient. However, according to the gray correlation analysis, changes in the biological characteristics of small yellow croaker were induced by different stressors ranked as： fishing vessel power〉feeding grade〉sea surface temperature. This study suggests that the active fishery management measures for biological characters of fish populations should be considered.
