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1.
Evaluating the impact of spatio-temporal scale on CPUE standardization   总被引:1,自引:0,他引:1  
This study focused on the quantitative evaluation of the impact of the spatio-temporal scale used in data collection and grouping on the standardization of CPUE(catch per unit effort).We used the Chinese squid-jigging fishery in the northwestern Pacific Ocean as an example to evaluate 24 scenarios at different spatio-temporal scales,with a combination of four levels of temporal scale(weekly,biweekly,monthly,and bimonthly)and six levels of spatial scale(longitude×latitude:0.5°×0.5°,0.5°×1°,0.5°×2°,1°×0.5°,1°×1°,and 1°×2°).We applied generalized additive models and generalized linear models to analyze the24 scenarios for CPUE standardization,and then the differences in the standardized CPUE among these scenarios were quantified.This study shows that combinations of different spatial and temporal scales could have different impacts on the standardization of CPUE.However,at a fine temporal scale(weekly)different spatial scales yielded similar results for standardized CPUE.The choice of spatio-temporal scale used in data collection and analysis may create added uncertainty in fisheries stock assessment and management.To identify a cost-effective spatio-temporal scale for data collection,we recommend a similar study be undertaken to facilitate the design of effective monitoring programs.  相似文献   

2.
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   

3.
The eastern fall cohort of the neon flying squid, Ommastrephes bartramii, has been commercially exploited by the Chinese squid jigging fleet in the central North Pacific Ocean since the late 1990s. To understand and identify their optimal habitat, we have developed a habitat suitability index (HSI) model using two potential important environmental variables - sea surface temperature (SST) and sea surface height anomaly (SSHA) - and fishery data from the main fishing ground (165°-180°E) during June and July of 1999-2003. A geometric mean model (GMM), minimum model (MM) and arithmetic weighted model (AWM) with different weights were compared and the best HSI model was selected using Akaike’s information criterion (AIC). The performance of the developed HSI model was evaluated using fishery data for 2004. This study suggests that the highest catch per unit effort (CPUE) and fishing effort are closely related to SST and SSHA. The best SST- and SSHA-based suitability index (SI) regression models were SISST-based = 0.7SIeffort-SST + 0.3 SICPUE-SST, and SISSHA-based = 0.5SIeffort-SSHA + 0.5SICPUE-SSHA, respectively, showing that fishing effort is more important than CPUE in the estimation of SI. The best HSI model was the AWM, defined as HSI=0.3SISST-based+ 0.7SISSHA-based, indicating that SSHA is more important than SST in estimating the HSI of squid. In 2004, monthly HSI values greater than 0.6 coincided with the distribution of productive fishing ground and high CPUE in June and July, suggesting that the models perform well. The proposed model provides an important tool in our efforts to develop forecasting capacity of squid spatial dynamics.  相似文献   

4.
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   

5.
The neon flying squid (Ommastrephes bartramii) is a short-lived opportunistic species widely distributed in subtropical and temperate waters in the North Pacific Ocean. The life cycle of O. bartramii from planktonic eggs to nektonic adults is closely linked to oceanographic conditions. The fluctuations in O. bartramii abundance and distribution tend to increase and widen continuously due to the heavy influences of ocean-climate events on various spatio-temporal scales. In this study, we reviewed the interaction between O. bartramii and oceanography variability in the North Pacific with respect to large-scale climatic-oceanic phenomena including El Niño, La Niña, Kuroshio, Oyashio and Pacific Decadal Oscillation (PDO), as well as regional environmental variables such as sea surface temperature (SST), sea surface height (SSH), sea surface salinity (SSS), chlorophyll-a (Chl-a) concentration, and plankton density. The population dynamics of O. bartramii is mediated mainly by meso- and large-scale climatic-oceanic events (e.g., Kuroshio and Oyashio Currents) rather than other local environmental conditions (e.g., SST and Chl-a concentration), because all of the oceanographic influences are imposed on the context of large-scale climate changes (e.g., PDO). An unstructured-grid finite-volume coastal ocean model coupled with an individual-based model is proposed to simulate relevant physical-biological oceanographic processes for identifying ocean-climate influence and predicting O. bartramii distribution and abundance in the North Pacific. Future research needs to be focused on improving the knowledge about early life history of O. bartramii and evaluating the relationship between marine physical environment and two separate passive drifting life stages of O. bartramii including free-floating eggs and planktonic paralarvae.  相似文献   

6.
<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   

7.
In this paper, we use the optimum interpolation sea surface temperature (OISST) provided by the National Center for Environmental Prediction (NCEP) to replace the temperature in the top three layers in the ISHII data, and make use of the modified ISHII temperature data to calculate the thermosteric sea level (called modified steric sea level (SSL) hereafter). We subtract the modified SSL and the steric sea level (called ordinary SSL hereafter) derived from the ISHII temperature and salinity from the steric sea level (SSL) provided by the Gravity Recovery and Climate Experiment (GRACE), respectively, and find that the rms error of the difference of the former is obviously smaller than that of the latter. Therefore we reach the conclusion that under the assumption that the GRACE SSL is accurate, the modified SSL can reflect the true steric sea level more accurately. Making use of the modified SSL, we can find that the modified SSL in sea areas of different spatial scales shows an obvious rising trend in the upper 0-700 m layer for the period 1982-2006. The global mean SSL rises with a rate of 0.6 mm year-1 .The modified SSLs in sea areas of different spatial scales all show obvious oscillations with period of one year. There are oscillations with periods of 4-8 years in global oceans and with periods of 2-7 years in the Pacific. The Empirical Orthogonal Function method is applied to the sea areas of different spatial scales and we find that the first modes all have obvious 1-year period oscillations, the first mode of the global ocean has 4-8 year period oscillations, and that of the Pacific has 2-6 year period oscillations. The spatial distribution of the linear rising trend of the global modified SSL in the upper 0-700 m layer is inhomogeneous with intense regional characteristics. The modified SSL linear trend indicates a zonal dipole in the tropical Pacific, rising in the west and descending in the east. In the North Atlantic, the modified SSL indicates a meridional dipole, rising in the latitude band of 20°N-40°N and 45°N-65.5°N and descending obviously in the latitude band of 40°N-45°N.  相似文献   

8.
Seasonal and annual with stress fields over the Bohai Sea, the Yellow Sea and the East China Sea were computed from the wind rose data compiled in the Climatic Atlas of Chinese Offshore Areas and North-west Pacific and published by the Ocean Press in 1982. 684 wind roses in 2° latitude by 2° longitude boxes constructed from 278,815 wind reports are involved in the present study. The computations are principally intended as a data source for further research. Some oceanographic consequences are expounded on.  相似文献   

9.
Heat center of the western Pacific warm pool   总被引:1,自引:0,他引:1  
A heat center (HC) of the western Pacific warm pool (WPWP) is defined, its variability is examined, and a possible mechanism is discussed. Analysis and calculation of a temperature dataset from 1945-2006 show that the mean position of the HC during this period was near 0.4°S/169.0°E, at 38.0 m depth. From a time series of the HC, remarkable seasonal variability was found, mainly in the meridional and vertical directions. Interannual variabilities were dominant in the zonal and vertical directions. In addition, semiannual variation in the HC depth was discovered. The longitude of the HC varies with ENSO events, and its latitude is weakly related to ENSO on time scales shorter than a decade. The variation of the HC longitude leads the Nio-3 index by about 3-4 months, and its depth lags the index for approximately 3 months. It is concluded that the HC depth results from a combination of its longitudinal and latitudinal variations. Low-pass-filtered time series reveal that the HC has moved eastward since the mid 1980s.  相似文献   

10.
多变量分位数回归构建印度洋大眼金枪鱼栖息地指数   总被引:1,自引:0,他引:1  
以0~300m水层加权平均水温、50~150m水层的温差和氧差及其交互变量为影响因子,运用分位数回归法,寻找出环境变量与大眼金枪鱼(Thunnus obesus)延绳钓钓获率的最佳上界分位数回归方程,计算出栖息地指数(HSI),并应用地理信息系统(GIS)软件绘制各月HSI空间分布图。研究表明:大眼金枪鱼延绳钓钓获率(HR)依加权平均水温(x)、温差(y)、氧差(z)与的最佳上界分位数回归方程为HR0.70=-15.596+2.124x-0.003x3+0.033xyz-0.036y2z+0.107yz2-0.337z3;HSI空间分布为:16°S—10°N印度洋海域HSI高于0.7,HSI>0.8的海域随季节发生显著变化,马达加斯加外海至100°E、16°S—26°S海域常年存在一片HSI<0.4的区域,26°S—40°S海域的HSI介于0.4~0.5,40°S以南海域HSI<0.4,东非外海季节性地出现一片HSI<0.6的海域。利用多个环境变量的栖息地指数模型来预测分析大洋金枪鱼资源分布效果较好。  相似文献   

11.
The process of habitat degradation varies in habitat type and driving force which shows certain spatial and temporal heterogeneity on regional scales. In the present study, a new diagnostic model for enclosed bay habitat degradation was established, with which the spatial and temporal variation patterns of habitat degradation during 1991–2012 in Sansha Bay, Fujian, China was investigated. The results show that anthropogenic disturbance is the major controlling factor for the habitat degradation in large temporal heterogeneity in the bay. On the other hand, the habitat degradation experienced signifi cant spatial variations among six sub-bays. Under the joint action of temporal and spatial heterogeneity, the degradation trend in growing scale shows a more signifi cant correlation with the distribution of local leading industries along shorelines. Therefore, we quantifi ed the main characters of habitat degradation in Sansha Bay, and have understood the relationship between the status of habitats spatio-temporal variation value and the main controlling factor leading to the changes. However, a defi ciency of this research is the lack of or inaccessible to the detailed data, which shall be better solved in the future study for accessing more data from more sources.  相似文献   

12.
Comparing fat content with physiological status can throw light on the reproduction and feeding behavior of the fish. The biological data of 586 bigeye tuna were collected from the longline fishery in the waters of Western Central Indian Ocean from November, 2012 to March, 2013. The spatial or temporal distribution of the fat content, and the relationships of fat content with gender, round weight, gonadal maturity and fork length were analyzed. A generalized additive model (GAM) was used to analyze the relationships between fat content and fork length (FL), gonadosomatic index (GSI), condition factor (K), and somatic index (SI). Results showed that: 1) the fat content of bigeye tuna was in the range of 3.1%–27.1% with the average 12.8%; 2) there were no significant geographical differences of average fat content (P > 0.05) among 1° squares in general; 3) there were no significant differences (P > 0.05) of the fat content for different genders, months, or gonad maturity stages; 4) there was an extremely significant correlation (P = 0.000) between fat content and FL and GSI. There was no significant correlation (P = 0.051) between fat content and K. There was a significant correlation (P = 0.003) between fat content and SI. The results of this study suggest that the fat content of the matured fish was relatively stable. The survey area was in a spawning region, and the survey period was the spawning season for bigeye tuna.  相似文献   

13.
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   

14.
使用FY-3C气象卫星GNSS掩星数据反演得到2017-03-01~2018-02-28大气温度廓线,并估计对流层顶高度变化;然后利用探空气球数据和ERA5模型数据进行验证;最后以2°×2°的空间分辨率将中国区域划分为608个网格,针对每一个单元格,分别计算对流层顶参数,建立格网模型,分析中国区域对流层顶参数的时空分布...  相似文献   

15.
Climate change will affect the geographic distribution and richness of species at different spatial and temporal scales. We applied Maximum entropy(MaxEnt) modeling to predict the potential influence of climatic change on the current and future distribution of the important mountainous tree species Moringa peregrina(Forssk.) Fiori. The Maxent model performed better than random models for the species with the training and test AUC(Area Under the receiver-operating characteristic Curve) values of 0.96 and 0.90, respectively. Jackknife test and response curves showed that the distribution of the species negatively correlates with higher altitudes and precipitation in October and November. Moreover, it positively correlates with the total annual precipitation and precipitation in January. Under current and future climatic conditions, our model predicted habitat gains for M. peregrina towards the coastal northern and southern limits of its distribution. The potentially suitable habitats, under future climate projections, are currently characterized by elevations of 1000 m a.s.l. and total annual precipitation of 80-225 mm/year. Moderate and high potential habitat suitability will increase by 5.6%-6% and 2.1%-2.3%, under RCP2.6 and RCP4.5 scenario, respectively. The results indicated that the habitat suitability of M. peregrina would increase with increasing climate warming, particularly under RCP2.6 scenario. We recommend sustainable conservation and cultivation of Moringa peregrina in its current habitats along the Red Sea mountains.  相似文献   

16.
Water vapor in the earth′s upper atmosphere plays a crucial role in the radiative balance, hydrological process, and climate change. Based on the latest moderate-resolution imaging spectroradiometer(MODIS) data, this study probes the spatio-temporal variations of global water vapor content in the past decade. It is found that overall the global water vapor content declined from 2003 to 2012(slope b = –0.0149, R = 0.893, P = 0.0005). The decreasing trend over the ocean surface(b = –0.0170, R = 0.908, P = 0.0003) is more explicit than that over terrestrial surface(b = –0.0100, R = 0.782, P = 0.0070), more significant over the Northern Hemisphere(b = –0.0175, R = 0.923, P = 0.0001) than that over the Southern Hemisphere(b = –0.0123, R = 0.826, P = 0.0030). In addition, the analytical results indicate that water vapor content are decreasing obviously between latitude of 36°N and 36°S(b = 0.0224, R = 0.892, P = 0.0005), especially between latitude of 0°N and 36°N(b = 0.0263, R = 0.931, P = 0.0001), while the water vapor concentrations are increasing slightly in the Arctic regions(b = 0.0028, R = 0.612, P = 0.0590). The decreasing and spatial variation of water vapor content regulates the effects of carbon dioxide which is the main reason of the trend in global surface temperatures becoming nearly flat since the late 1990 s. The spatio-temporal variations of water vapor content also affect the growth and spatial distribution of global vegetation which also regulates the global surface temperature change, and the climate change is mainly caused by the earth's orbit position in the solar and galaxy system. A big data model based on gravitational-magmatic change with the solar or the galactic system is proposed to be built for analyzing how the earth's orbit position in the solar and galaxy system affects spatio-temporal variations of global water vapor content, vegetation and temperature at large spatio-temporal scale. This comprehensive examination of water vapor changes promises a holistic understanding of the global climate change and potential underlying mechanisms.  相似文献   

17.
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   

18.
气象变量常作为重要的影响因子出现在环境污染、疾病健康和农业等领域,而高分辨率的气象资料可作为众多研究的基础数据,对推进相关研究的发展意义重大。本文以中国大陆为研究区域,利用2015年824个气象站点的气温、相对湿度和风速3套数据,结合不同的解释变量组合,分别构建了各自的GAM和残差自编码器神经网络(简称残差网络)模型,以10倍交叉验证判断模型是否过拟合。研究结果表明:① GAM和残差网络方法都不存在过拟合问题,同GAM相比,残差网络显著提高了模型预测的精度(3个气象因素的交叉验证CV R2平均提高了0.21,CV RMSE平均降低了37%),其中相对湿度模型的提升幅度最大(CV R2:0.85 vs. 0.52,CV RMSE:7.53% vs. 13.59%);② 残差模型的结果较普通克里格插值结果和再分析资料更接近站点观测数据,表明残差网络可作为高分辨率气象数据研制的可靠方法。此外,研究还发现在相对湿度模型中加入臭氧浓度和气温、在风速模型中加入GLDAS风速再分析资料,可提升模型的性能。  相似文献   

19.
Version 4(v4) of the Extended Reconstructed Sea Surface Temperature(ERSST) dataset is compared with its precedent, the widely used version 3b(v3b). The essential upgrades applied to v4 lead to remarkable differences in the characteristics of the sea surface temperature(SST) anomaly(SSTa) in both the temporal and spatial domains. First, the largest discrepancy of the global mean SSTa values around the 1940 s is due to ship-observation corrections made to reconcile observations from buckets and engine intake thermometers. Second, differences in global and regional mean SSTa values between v4 and v3b exhibit a downward trend(around-0.032℃ per decade) before the 1940s, an upward trend(around 0.014℃ per decade) during the period of 1950–2015, interdecadal oscillation with one peak around the 1980s, and two troughs during the 1960s and 2000s, respectively. This does not derive from treatments of the polar or the other data-void regions, since the difference of the SSTa does not share the common features. Third, the spatial pattern of the ENSO-related variability of v4 exhibits a wider but weaker cold tongue in the tropical region of the Pacific Ocean compared with that of v3b, which could be attributed to differences in gap-filling assumptions since the latter features satellite observations whereas the former features in situ ones. This intercomparison confirms that the structural uncertainty arising from underlying assumptions on the treatment of diverse SST observations even in the same SST product family is the main source of significant SST differences in the temporal domain. Why this uncertainty introduces artificial decadal oscillations remains unknown.  相似文献   

20.
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