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1.
Generalized linear models (GLM) and generalized additive models (GAM) were used to standardize catch per unit fishing effort (CPUE) of Ommastrephes bartramii for Chinese squid-jigging fishery in Northwest Pacific Ocean. Three groups of variables were considered in the standardization: spatial variables (longitude and latitude), temporal variables (year and month) and environmental variables, including sea surface temperature (SST), sea surface salinity (SSS) and sea level height (SLH). CPUE was treated as the dependent variable and its error distribution was assumed to be log-normal in each model. The model selections of GLM and GAM were based on the finite sample-corrected Akaike information criterion (AICC) and pseudo-coefficient (Pcf) combined P-value, respectively. Both GAM and GLM analysis showed that the month was the most important variable affecting CPUE and could explain 21.3% of variability in CPUE while other variables only explained 8.66%. The interaction of spatial and temporal variables weakly influenced the CPUE. Moreover, spatio-temporal factors may be more important in influencing the CPUE of this squid than environmental variables. The standardized and nominal CPUEs were similar and had the same trends in spatio-temporal distribution, but the standardized CPUE values tended to be smaller than the nominal CPUE. The CPUE tended to have much higher monthly variation than annual variations and their values increased with month. The CPUE became higher with increasing latitude-high CPUE usually occurred in 145°E–148°E and 149°E–162°E. The CPUE was higher when SST was 14–21°C and the SLH from −22 cm to −18 cm. In this study, GAM tended to be more suitable than GLM in analysis of CPUE.  相似文献   

2.
Weighting values for different habitat variables used in multi-factor habitat suitability index (HSI) modeling reflect the relative influences of different variables on distribution of fish species. Using the winter-spring cohort of neon flying squid (Ommastrephes bartramii) in the Northwestern Pacific Ocean as an example, we evaluated the impact of different weighting schemes on the HSI models based on sea surface temperature, gradient of sea surface temperature and sea surface height. We compared differences in predicted fishing effort and HSI values resulting from different weighting. The weighting for different habitat variables could greatly influence HSI modeling and should be carefully done based on their relative importance in influencing the resource spatial distribution. Weighting in a multi-factor HSI model should be further studied and optimization methods should be developed to improve forecasting squid spatial distributions.  相似文献   

3.
Temporal and spatial scales play important roles in fishery ecology, and an inappropriate spatio-temporal scale may result in large errors in modeling fish distribution. The objective of this study is to evaluate the roles of spatio-temporal scales in habitat suitability modeling, with the western stock of winter-spring cohort of neon flying squid(Ommastrephes bartramii) in the northwest Pacific Ocean as an example. In this study, the fishery-dependent data from the Chinese Mainland Squid Jigging Technical Group and sea surface temperature(SST) from remote sensing during August to October of 2003–2008 were used. We evaluated the differences in a habitat suitability index model resulting from aggregating data with 36 different spatial scales with a combination of three latitude scales(0.5°, 1° and 2°), four longitude scales(0.5°, 1°, 2° and 4°), and three temporal scales(week, fortnight, and month). The coefficients of variation(CV) of the weekly, biweekly and monthly suitability index(SI) were compared to determine which temporal and spatial scales of SI model are more precise. This study shows that the optimal temporal and spatial scales with the lowest CV are month, and 0.5° latitude and 0.5° longitude for O. bartramii in the northwest Pacific Ocean. This suitability index model developed with an optimal scale can be cost-effective in improving forecasting fishing ground and requires no excessive sampling efforts. We suggest that the uncertainty associated with spatial and temporal scales used in data aggregations needs to be considered in habitat suitability modeling.  相似文献   

4.
利用2004~2010年北太平洋鱿钓船队生产数据和海洋环境数据,以海表温度(SST)1℃、海面高度(SSH)为1 cm、叶绿素a浓度(CHL-a)为0.1 mg/m3的间距,分析作业产量、CPUE与SST、SSH、CHL-a的关系,得到柔鱼渔场适宜环境因子范围,并将生产数据和环境数据匹配组成样本集,建立北太平洋柔鱼空间分布BP神经网络模型;利用2011年环境数据预报柔鱼渔场,并与2011年实际生产数据进行对比。结果表明,6~10月各月实际作业位置落入基于频度统计方法预报渔场的概率达90%以上;而BP模型预报的平均精度为79.2%,最低精度为52.5%。基于多环境因子的频度统计柔鱼渔场预报模型优于神经网络模型。  相似文献   

5.
The generalized linear model (GLM) and generalized additive model (GAM) were applied to the standardization of catch per unit effort (CPUE) for Chilean jack mackerel from Chinese factory trawl fishing fleets in the Southeast Pacific Ocean from 2001 to 2010 by removing the operational, environmental, spatial and temporal impacts. A total of 9 factors were selected to build the GLM and GAM, i.e., Year, Month, Vessel, La Niña and El Niño events (ELE), Latitude, Longitude, Sea surface temperature (SST), SST anomaly (SSTA), Nino3.4 index and an interaction term between Longitude and Latitude. The first 5 factors were significant components in the GLM, which in combination explained 27.34% of the total variance in nominal CPUE. In the stepwise GAM, all factors explained 30.78% of the total variance, with Month, Year and Vessel as the main factors influencing CPUE. The higher CPUE occurred during the period April to July at a SST range of 12–15°C and a SSTA range of 0.2–1.0°C. The CPUE was significantly higher in normal years compared with that in La Niña and El Niño years. The abundance of Chilean jack mackerel declined during 2001 and 2010, with an increase in 2007. This work provided the relative abundance index of Chilean jack mackerel for stock assessment by standardizing catch and effort data of Chinese trawl fisheries and examined the influence of temporal, spatial, environmental and fisheries operational factors on Chilean jack mackerel CPUE.  相似文献   

6.
根据2003~2004年西北太平洋秋刀鱼资源调查结果,对西北太平洋秋刀鱼渔场分布及其与海水表层温度(SST)的关系进行分析。结果表明,7~9月西北太平洋秋刀鱼渔场主要集中在40.5°N~44.5°N、151.5°E~158°E,SST为10℃~19℃,捕捞群体以中大型个体为主;各月最高产量及最大CPUE时的SST各不相同,渔场的形成和丰度与亲潮和黑潮的势力强弱及其分布密切相关。经K-S检验,结果表明,各月SST与产量及样本平均体长、平均体重的差异均不显著。这些渔场可作为我国远洋鱿钓渔业的兼作渔场。  相似文献   

7.
The relationships between the neon flying squid, Ommastrephes bartrami, and the relative ocean environmental factors are analyzed. The environmental factors collected are sea surface temperature (SST), chlorophyll concentration (Chl-a) and sea surface height (SSH) from NASA, as well as the yields of neon flying squid in the North Pacific Ocean. The results show that the favorable temperature for neon flying squid living is 10°C–22°C and the favorite temperature is between 15°C–17°C. The Chl-a concentration is 0.1–0.6 mg/m3. When Chl-a concentration changes to 0.12–0.14 mg/m3, the probability of forming fishing ground becomes very high. In most fishing grounds, the SSH is higher than the mean SSH. The generalized additive model (GAM) was applied to analyze the correlations between neon flying squid and ocean environmental factors. Every year, squids migrate northward from June to August and return southward during October–November, and the characteristics of the both migrations are very different. When squids migrate to the north, most relationships between the yields and SST are positive. The relationships are negative when squids move to southward. The relationships between the yields and Chl-a concentrations are negative from June to October, and insignificant in November. There is no obvious correlation between the catches of squid and longitude, but good with latitude. Supported by the National High Technology Research and Development Program of China (863 Program, No. 2003AA607030); National Key Technology Research and Development Program (No. 2006BAD09A05)  相似文献   

8.
Catch per unit of eff ort(CPUE) data can display spatial autocorrelation. However, most of the CPUE standardization methods developed so far assumes independency of observations for the dependent variable, which is often invalid. In this study, we collected data of two fisheries, squid jigging fishery and mackerel trawl fishery. We used standard generalized linear model(GLM) and spatial GLMs to compare the impact of spatial autocorrelation on CPUE standardization for different fisheries. We found that spatialGLMs perform better than standard-GLM for both fisheries. The overestimation of precision of CPUE estimates was observed in both fisheries. Moran's I was used to quantify the level of autocorrelation for the two fisheries. The results show that autocorrelation in mackerel trawl fishery was much stronger than that in squid jigging fishery. According to the results of this paper, we highly recommend to account for spatial autocorrelation when using GLM to standardize CPUE data derived from commercial fisheries.  相似文献   

9.
西北太平洋柔鱼资源与海洋环境的GIS空间分析   总被引:12,自引:0,他引:12  
本文根据1995~2001年的西北太平洋地区(35°N~45°N,140°E~170°W)巴特柔鱼资源调查与生产的实际情况对柔鱼渔获量进行了研究,并利用同期遥感反演的海洋表层温度数据(SST)和近表层叶绿素a数据(Chlorophylla),拓展了GIS的空间分析功能,定量地研究了我国远洋柔鱼产量与水温、叶绿素等海洋要素场之间的关系,揭示西北太平洋柔鱼中心渔场的环境特征,以期为我国西北太平洋海区的鱿鱼生产服务。  相似文献   

10.
<正>柔鱼(Ommastrephes bartramii)广泛分布在北太平洋,20世纪70年代初首先由日本鱿钓船开发,我国大陆于1993年开始利用该资源,1994年进行较大规模地商业性生产。目前北太平洋鱿钓渔业已成为我国远洋渔业的支柱[1]。据估计,历史上北太平洋柔  相似文献   

11.
Using surplus production model packages of ASPIC(a stock-production model incorporating covariates) and CEDA(Catch effort data analysis),we analyzed the catch and effort data of Sillago sihama fishery in Pakistan.ASPIC estimates the pa-rameters of MSY(maximum sustainable yield),Fmsy(fishing mortality),q(catchability coefficient),K(carrying capacity or unexploited biomass) and B1/K(maximum sustainable yield over initial biomass).The estimated non-bootstrapped value of MSY based on logistic was 598 t and that based on the Fox model was 415 t,which showed that the Fox model estimation was more conservative than that with the logistic model.The R2 with the logistic model(0.702) is larger than that with the Fox model(0.541),which indicates a better fit.The coefficient of variation(cv) of the estimated MSY was about 0.3,except for a larger value 88.87 and a smaller value of 0.173.In contrast to the ASPIC results,the R2 with the Fox model(0.651-0.692) was larger than that with the Schaefer model(0.435-0.567),indicating a better fit.The key parameters of CEDA are:MSY,K,q,and r(intrinsic growth),and the three error assumptions in using the models are normal,log normal and gamma.Parameter estimates from the Schaefer and Pella-Tomlinson models were similar.The MSY estimations from the above two models were 398 t,549 t and 398 t for normal,log-normal and gamma error distributions,re-spectively.The MSY estimates from the Fox model were 381 t,366 t and 366 t for the above three error assumptions,respectively.The Fox model estimates were smaller than those for the Schaefer and the Pella-Tomlinson models.In the light of the MSY estimations of 415 t from ASPIC for the Fox model and 381 t from CEDA for the Fox model,MSY for S.sihama is about 400 t.As the catch in 2003 was 401 t,we would suggest the fishery should be kept at the current level.Production models used here depend on the assumption that CPUE(catch per unit effort) data used in the study can reliably quantify temporal variability in population abundance,hence the mod-eling results would be wrong if such an assumption is not met.Because the reliability of this CPUE data in indexing fish population abundance is unknown,we should be cautious with the interpretation and use of the derived population and management parameters.  相似文献   

12.
2004年北太平洋柔鱼钓产量分析及作业渔场与表温的关系   总被引:1,自引:0,他引:1  
根据2004年5~11月我国鱿钓船在北太平洋生产数据,结合表温资料,按经纬度1°×1°的格式,利用Marineexplorer 4.0软件作图进行柔鱼钓产量及渔场与表温的关系分析。结果表明,5~7月在160°E以东海域作业,产量较低;8~10月在150°~160°E海域作业,为生产作业的产量高峰期,占总产量的62.5%;11月在150°E以西海域作业,产量也较低。在150°E以西海域CPUE最高,150°~160°E中部海域次之,160°E以东海域最低。作业渔场的适宜表温呈现出季节性变化。各月适宜表温分别为:5月12~14℃;6月15~16℃;7月14~16℃;8月18~19℃;9月16~17℃;10月15~16℃;11月12~13℃。  相似文献   

13.
南太平洋长鳍金枪鱼渔场预报模型研究   总被引:4,自引:0,他引:4  
长鳍金枪鱼资源是南太平洋金枪鱼渔业的重要目标种类,也是我国金枪鱼延绳钓的主要捕捞对象之一。根据2008-2009年我国海洋渔业公司在南太平洋海域的生产数据,结合表层、105 m和205 m水层温度,以及海面高度、叶绿素a浓度等海洋环境数据,运用一元非线性回归方法,按季度建立基于各环境因子的长鳍金枪鱼栖息地适应性指数,采用算术平均法获得基于多环境因子的栖息地指数综合模型,并用于中心渔场的预报。通过与实际作业渔场的比较与验证,结果表明:模型预报准确性达到70%以上,具较高渔情预报准确度。  相似文献   

14.
Wang  Xuehui  Qiu  Yongsong  Zhang  Peng  Du  Feiyan 《中国海洋湖沼学报》2017,35(4):902-911
Based on the biological data of purpleback flying squid(Sthenoteuthis oualaniensis)collected by light falling-net in the southern South China Sea(SCS) during September to October 2012 and March to April 2013,growth and mortality of 'Medium' and 'Dwarf' forms of squid are derived using the Powell-Wetherall,ELEFAN methods and length-converted catch curves(FiSAT package).Given a lack of commercial exploitation,we assume total mortality to be due entirely to natural mortality.We estimate these squid have fast growth,with growth coefficients(k) ranging from 1.42 to 2.39,and high natural mortality(M),with estimates ranging from 1.61 to 2.92.To sustainably exploit these squid stocks,yield per recruitment based on growth and natural mortality was determined using the Beverton-Holt dynamic pool model.We demonstrate squid stocks could sustain high fishing mortality and low ages at first capture,with an optimal fishing mortality 3.0,with the optimal age at first capture increased to 0.4-0.6 years when fishing mortality approached optimal levels.On the basis of our analyses and estimates of stock biomass,we believe considerable potential exists to expand the squid fishery into the open SCS,relieving fishing pressure on coastal waters.  相似文献   

15.
The relationships between the neon flying squid, Ommastrephes bartrami, and the relative ocean environmental factors are analyzed. The environmental factors collected are sea surface temperature (SST), chlorophyll concentration (Chl-a) and sea surface height (SSH) from NASA, as well as the yields of neon flying squid in the North Pacific Ocean. The results show that the favorable temperature for neon flying squid living is 10℃-22℃ and the favorite temperature is between 15℃-17℃. The Chl-a concentration is 0.1-0.6 mg/m3. When Chl-a concentration changes to 0.12-0.14 mg/m3, the probability of forming fishing ground becomes very high. In most fishing grounds,the SSH is higher than the mean SSH. The generalized additive model (GAM) was applied to analyze the correlations between neon flying squid and ocean environmental factors. Every year, squids migrate northward from June to August and return southward during October-November, and the characteristics of the both migrations are very different. When squids migrate to the north, most relationships between the yields and SST are positive. The relationships are negative when squids move to southward. The relationships between the yields and Chl-a concentrations are negative from June to October, and insignificant in November. There is no obvious correlation between the catches of squid and longitude, but good with latitude.  相似文献   

16.
根据2007~2009年7~9月渔汛期间我国鲐鱼灯光围网在东海的生产数据,利用海表温、叶绿素浓度、悬浮物浓度和透明度等遥感水质数据,分别将作业网次比例和单网次产量(CPUE)作为适应性指数,利用算术平均数(AM)和几何平均数(GM)分别建立基于海表温、叶绿素浓度、悬浮物浓度和透明度的综合栖息地指数模型。结果表明,AM栖息地指数模型和GM栖息地指数模型拟合效果较好(P<0.01),在HSI大于0.5的海域,2007~2009年7~9月平均作业网次比例在65%以上,各月平均CPUE均高于19.82 t/net。研究认为,AM模型稍优于GM模型。利用2010年7~9月生产数据及遥感水质数据对AM模型进行验证,分析认为,87%以上的作业网次和产量分布在HSI高于0.5的海域,CPUE为14~17 t/net,且较稳定,波动较小。研究认为,基于遥感水质数据的AM栖息地指数模型能较好地预测东海鲐鱼渔场。  相似文献   

17.
We examined spatially clustered distribution of jumbo flying squid (Dosidicus gigas) in the offshore waters of Peru bounded by 78°–86°W and 8°–20°S under 0.5°×0.5° fishing grid. The study is based on the catch-per-unit-effort (CPUE) and fishing effort from Chinese mainland squid jigging fleet in 2003–2004 and 2006–2013. The data for all years as well as the eight years (excluding El Niño events) were studied to examine the effect of climate variation on the spatial distribution of D. gigas. Five spatial clusters reflecting the spatial distribution were computed using K-means and Getis-Ord Gi* for a detailed comparative study. Our results showed that clusters identified by the two methods were quite different in terms of their spatial patterns, and K-means was not as accurate as Getis-Ord Gi*, as inferred from the agreement degree and receiver operating characteristic. There were more areas of hot and cold spots in years without the impact of El Niño, suggesting that such large-scale climate variations could reduce the clustering level of D. gigas. The catches also showed that warm El Niño conditions and high water temperature were less favorable for D. gigas offshore Peru. The results suggested that the use of K-means is preferable if the aim is to discover the spatial distribution of each sub-region (cluster) of the study area, while Getis-Ord Gi* is preferable if the aim is to identify statistically significant hot spots that may indicate the central fishing ground.  相似文献   

18.
根据2000年中国鱿钓船在西南大西洋的生产统计和表温资料,按经纬度1°×1°进行统计,并用渔业地理信息软件MarineExplorer4 .0进行叠加分析。结果表明, 1~5月阿根廷滑柔鱼分布中心集中在45°S、60°W附近海域。各月产量和平均日产量有较大的变动,其中以2~3月为最高。1~5月作业渔场的适宜表温范围为7~14℃,并经过K S检验。但各月的适宜表温有所不同, 2月为11 ~12℃, 3月为10 ~12℃, 4月为8 ~9℃, 5月为7 ~8℃。在表温比往年稍偏高的作业海域,有利于渔场的形成和产量提高。  相似文献   

19.
1 Introduction TheKuroshioflowsthroughtheEastTaiwanChan nel (ETC)betweenthenortheastcoastofTaiwanandtheJapaneseRyukyuIslandbeforeenteringintotheEastChinaSea (ECS)astheextendingflowoftheNorthEquatorialCurrent (NEC)whichbifurcatestotheeastofthePhilippines…  相似文献   

20.
In this paper, the morphological characters of eggs and larvae ofSardinella aurita (Cuvier & Valenciennes), its spawning ground, spawning seasons and spawning conditions have been studied. Sardinella aurita likes to breed in the upwelling area and selects the Waixie fishing ground as its main spawning ground. The months from February to September are its spawning seasons, reaching its peak in April. In the main spawning ground, the temperature of the surface layer was found to be 24.4–25.2°C, the salinity 33.87–34.07%. and the depth of water between 34–60m. The distribution of the larvae is closely related to the distribution of plankton, the path of migration of adult fish, and the current direction of the water system. In order to protect fishery resources, it is necessary to prohibit catching the spawning fish in the Waixie fishing ground in April, and the catching of immatures from March to June. This paper was published in Chinese inOcean. Limn. Sinica 14(3): 240–248, 1983.  相似文献   

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