共查询到18条相似文献，搜索用时 46 毫秒
1.
本文利用1998-2016年西北太平洋柔鱼渔业数据及其渔场（35°~45°N,140°~165°E）的海洋遥感环境数据,包括海表温度、海面高度异常和叶绿素浓度,采用基于渔场环境的方法标准化西北太平洋柔鱼单位捕捞努力量渔获量（catch per unit effort,CPUE）。结果表明:柔鱼高频次作业的海表温度范围为10.2~22.2℃（96.05%）,海面高度异常范围为-15.9~28.2 cm（97.91%）,叶绿素浓度范围为0.0~1.0 mg/m3（96.69%）。名义CPUE和基于环境因子的标准化CPUE年际变化趋势基本一致。但由于柔鱼作业方式高度集中,有效捕捞努力量远低于名义捕捞努力量,以及考虑环境因子影响效应,名义CPUE均低于标准化CPUE。在深入理解鱿钓渔业和其生物学特性的基础上,基于渔场环境因子准化后的CPUE更具代表性,建议在以后的柔鱼资源评估与管理中使用基于渔场环境因子的标准化CPUE。 相似文献
2.
基于Voronoi图与空间自相关的西北太平洋柔鱼资源空间聚集特征分析 总被引：3，自引：1，他引：2
以西北太平洋柔鱼Ommastrephes bartramii为例,基于2007—2010年中国鱿钓船的生产统计原始点位数据,利用Voronoi图和空间自相关方法,评估柔鱼资源的全局空间模式、局部空间聚集特征,并以空间可视化方式呈现。在渔业资源及空间分析中,高产值聚集的海域称为空间热点,而低产值聚集的海域称为空间冷点。研究表明,全局自相关统计量Morans I和General G均指示了西北太平洋柔鱼资源的聚集分布状态。局部空间自相关显示,2007和2009年均具有2个热点和1个冷点区域,2008年具有1个热点和1个冷点区域,2010年具有1个热点和2个冷点区域,这些热冷点呈南北向或东西向分布态势。热冷点格局的叠加图显示,研究区内存在1个强热点、1个弱热点和1个强冷点,其中弱热点覆盖的区域在4年间表现为热点和冷点的交互变动。对7—11月平均海表温度和叶绿素a浓度的分析显示,热点和冷点均为中心渔场,热冷点形成的温度条件无显著差异;热冷点形成的叶绿素a浓度范围为0.2~1.1mg/m3,其中冷点区域的浓度相对较高。 相似文献
3.
本文利用2003-2011年西南大西洋阿根廷滑柔鱼渔业数据和海洋环境数据,包括海表温度（sea surface temperature, SST）,海面高度（sea surface height, SSH）和叶绿素浓度（chlorophyll a, Chl a）,开发基于广义加性模型（GAM）和神经网络模型（NNM）的复合模型研究滑柔鱼资源时空分布。GAM用于选择关键影响因子,并分析与单位捕捞努力量渔获量（catch per unit effort, CPUE）的关系,NNM用于建立关键影响因子与CPUE之间的预报模型。结果表明：GAM选择的影响因子的偏差解释率为53.8%,空间变量（经度和纬度）,环境变量（SST、SSH、Chl a）均匀CPUE之间存在显著相关性。CPUE与SST和SSH之间为非线性关系,与Chl a之间为线性关系。NNM模型的MSE和ARV较低,其精度高且稳定。此复合模型也能够解释解释西南大西洋阿根廷滑柔鱼时空变化趋势和迁徙模式。 相似文献
4.
单位捕捞努力量渔获量(catch per unit effort, CPUE)常被假设与渔业资源量成正比而被应用于渔业资源评估与管理中,不同的环境模态下,所选取的空间分辨率对CPUE的标准化会产生影响,从而影响对该渔业资源丰度的评价。本研究运用广义加性模型(generalized additive model, GAM),对中国在北太平洋鱿钓渔业数据进行CPUE标准化。根据北太平洋环境的差异,以160°E为界将其划分为不同的环境模态。分别对两种模态下3种空间尺度(0.25°×0.25°、0.5°×0.5°、1°×1°)的名义CPUE进行标准化,得到各自的最适GAM模型。比较不同环境模态下,各因素对CPUE标准化产生的影响;相同环境模态下,不同空间尺度对CPUE标准化产生的影响。结果表明:不同环境模态下,对CPUE标准化产生影响的变量差异较大:160°E以西海域分别为年、纬度、SST以及交互项年与纬度、月与纬度;160°E以东海域分别为纬度、年与纬度的交互项、月与纬度的交互项。同一环境模态下,不同的空间尺度最适GAM模型对CPUE标准化结果不同,根据均方误差选取0.5°×0.5°和0.25°×0.25°分别为160°E东、西海域CPUE标准化的最适空间尺度。因此,在对北太平洋柔鱼(Ommastrephes bartramii)商业性渔获数据进行标准化时,需要考虑因不同的环境模态以及不同的空间尺度而导致的CPUE标准化所出现的差异。 相似文献
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太平洋褶柔鱼为大洋性经济鱼种,具有一年生命周期,其资源变动受气候和海洋环境条件的显著影响。本研究根据日本提供的2003-2012年太平洋褶柔鱼冬生群体的渔业统计数据,结合产卵场环境数据以及尼诺指数ONI（定义为Niño 3.4区海表温度距平值）,分析不同气候条件下（厄尔尼诺和拉尼娜）太平洋褶柔鱼冬生群体产卵场海表温度（SST）、叶绿素a（Chl-a）浓度以及适宜产卵面积（SSA）的变动情况及对其资源丰度（CPUE）的影响。结果表明,太平洋褶柔鱼冬生群体产卵场SST、Chl-a浓度和SSA具有明显的季节性变化。相关分析表明,各年CPUE与Chl-a浓度以及SSA具有显著的正相关关系（p<0.05）,但与SST相关性不显著（p>0.05）。此外,厄尔尼诺和拉尼娜事件通过驱动太平洋褶柔鱼冬生群体产卵场SSA和关键海域（25°-29°N,122.5°-130.5°E）内的Chl-a空间分布和大小变化,从而改变其资源丰度,但影响作用随各异常事件的强度不同而变化,具体表现为：发生弱强度厄尔尼诺事件时,产卵场SSA较高,Chl-a浓度处于较低水平,导致资源补充量处于较低水平,CPUE降低;发生中等强度厄尔尼诺事件时,产卵场SSA较低,但Chl-a浓度处于较高水平,导致资源补充量增加,CPUE处于上升水平;发生中等强度拉尼娜事件时,产卵场SSA和Chl-a浓度均处于较高水平,资源补充量显著增加,CPUE显著升高。研究表明,厄尔尼诺和拉尼娜事件对太平洋褶柔鱼冬生群体产卵场摄食孵化环境和资源丰度变动具有显著影响。 相似文献
6.
东南太平洋秘鲁海域光合有效辐射对茎柔鱼资源丰度和空间分布的影响研究 总被引：4，自引：2，他引：2
光合有效辐射（PAR）是海洋初级生产力的重要驱动因素之一,因此对海洋鱼类的资源丰度和空间分布产生潜在影响。本文根据2006-2015年1-12月中国鱿钓科学技术组提供的秘鲁外海茎柔鱼捕捞数据和光合有效辐射卫星遥感数据,以单位捕捞努力量渔获量（CPUE）表征资源丰度,以CPUE的纬度重心表征渔场空间分布,评估了东南太平洋秘鲁海域光合有效辐射对茎柔鱼资源变动的影响。结果发现,茎柔鱼渔场的产量、捕捞努力量、CPUE和PAR呈现明显的月间变化,其中CPUE和PAR月间变化规律表现为1-6月降低,7-12月增加的趋势。相关分析法表明,CPUE与PAR呈正相关关系,7月和8月相关性显著,而其余月份相关性不显著。依据频率分布法估算了各月适宜和最适PAR范围,各月最适PAR范围占渔场总面积比例与CPUE呈显著正相关关系,推测茎柔鱼资源丰度可能由各月适宜PAR面积大小决定;同时,最适PAR纬度与CPUE纬度重心呈显著正相关,说明茎柔鱼渔场的空间分布受最适PAR纬度的显著影响。此外,拉尼娜年份茎柔鱼适宜PAR面积要显著高于厄尔尼诺年份。研究表明,茎柔鱼资源丰度和空间分布受光合有效辐射的显著影响,其调控作用在不同气候条件下呈现不同的变化规律。 相似文献
7.
基于灰色系统西南大西洋阿根廷滑柔鱼资源丰度预测模型的构建 总被引：3，自引：0，他引：3
阿根廷滑柔鱼（Illex argentinus）是西南大西洋鱿钓渔业的主要作业鱼种,对资源丰度进行准确的预测可指导企业合理安排渔业生产。因此,本研究根据2000-2016年我国西南大西洋阿根廷滑柔鱼的生产数据,以单位捕捞努力量的渔获量（Catch per unit effort, CPUE）为阿根廷滑柔鱼资源丰度的指标,利用灰色绝对关联分析和灰色预测建模的方法（GM（0, N））,计算2001-2015年CPUE的时间序列值与产卵期（6-8月）产卵场海表面温度（Sea surface temperature, SST）时间序列值的灰色绝对关联度,选取产卵场海域中灰色绝对关联度大于0.90的海区SST建立资源丰度预测模型,并用2016年实际CPUE进行验证。灰色绝对关联分析表明,6-8月,30°~40°S,45°~60°W海域内存在若干海区的SST与次年对数CPUE时间序列呈现较强的关联度,可作为预报因子。GM（0, N）模型结果表明,以6-8月产卵场SST作为环境因子建立的模型4能较好地拟合出阿根廷滑柔鱼资源丰度变动趋势,与2016年真实值相比,相对误差为7%,该模型可较好地作为阿根廷滑柔鱼资源丰度的预测模型。相反,包含6月和7月SST的模型1效果优于不包含6月SST的模型2或不包含7月SST的模型3,拟合得到的2016年的数据与真实值相比,相对误差分别为128%和289%,这说明6月和7月是西南大西洋阿根廷滑柔鱼的主要产卵月份。 相似文献
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茎柔鱼(Dosidicus gigas)是我国远洋渔业的重要捕捞对象。当前针对茎柔鱼渔场分布及其与环境关系的研究多集中于秘鲁海域,针对赤道海域茎柔鱼特定种群小型群体资源分布及其渔场环境特征研究较少。根据2019年12月至2020年2月茎柔鱼生物学数据,2019年12月至2020年4月生产和环境数据,运用胴长-体重关系拟合、地统计插值、广义可加模型(GAM)探究其资源分布及渔场环境状况。结果表明：东太平洋赤道海域茎柔鱼胴长范围为136~407 mm,体重范围为117~1557 g；2019年12月至2020年4月各月渔获量呈先增加后减小趋势,2月渔获量最高；CPUE曲线除2月增加外,总体呈下降趋势；渔场集中分布于0°~3°S、105°W~114°W海域,不同月份渔场重心经向变化明显；渔场最适SST范围是24.5~25.5 °C,最适Chl-a范围是0.16~0.20 mg/m3,月份是影响茎柔鱼CPUE的主要因子。研究表明：该海域茎柔鱼渔获主要为小型群体；小型群体生长发育期(2–3月)对渔场分布有重要影响,生长发育期前茎柔鱼集群度高,生长发育期后逐渐分散活动；单一影响因子与茎柔鱼CPUE相关性不显著,综合考虑其他环境因素及其交互影响是今后的研究方向。 相似文献
9.
中国近海鲐鱼资源时空分布与海洋净初级生产力的关系研究 总被引：2，自引：0，他引：2
海洋净初级生产力影响了浮游动植物的空间分布和丰度,因此决定了海洋渔业的潜在产量。本文根据2006-2015年7-9月中国远洋渔业数据中心提供的中国近海鲐鱼捕捞数据和海洋净初级生产力遥感数据,以单位捕捞努力量渔获量（CPUE）表征资源丰度,以经度和纬度重心表征空间分布,分析研究了鲐鱼资源丰度和空间分布与海洋净初级生产力的关系。研究结果表明,2006-2015年鲐鱼产量、CPUE、经度和纬度重心呈现明显的月份和年际变化,7-9月渔场内净初级生产力空间分布模式不同。频率分布结果表明7-9月鲐鱼对应的适宜净初级生产力浓度范围分别为300~500 mg/（m2·d）（以碳计,下同）,300~400 mg/（m2·d）,300~400 mg/（m2·d）。相关分析结果表明,鲐鱼资源丰度与适宜净初级生产力海域范围比例呈显著正相关,且鲐鱼纬度重心与适宜净初级生产力海域平均纬度呈显著正相关关系,这表明渔场内的净初级生产力大小和分布模式显著影响鲐鱼的资源丰度和渔场重心位置。在鲐鱼主要分布海域25°~30°N,120°~130°E范围内,鲐鱼资源丰度与净初级生产力大小呈显著负相关关系。此外,不同气候条件下鲐鱼渔场净初级生产力大小变化不同,2007年和2010年强拉尼娜年份以及2009年中强厄尔尼诺年份鲐鱼渔场范围海洋净初级生产力降低,但适宜的海洋净初级生产力范围增大,导致鲐鱼资源丰度上升;而2015年超强厄尔尼诺年份鲐鱼渔场范围内海洋净初级生产力上升,但适宜的海洋净初级生产力范围显著减小,因此鲐鱼资源丰度相对降低。研究表明,中国近海鲐鱼资源时空分布与海洋净初级生产力具有显著关联。 相似文献
10.
基于GAM和GWR模型分析环境因子对南极磷虾资源分布的非线性和非静态性影响 总被引：1，自引：0，他引：1
分析南极磷虾分布与环境因子的非线性和空间非静态性关系,对南极磷虾的高效捕捞和管理具有重要意义。本研究基于“龙腾”船2015、2016年在南设得兰群岛捕捞作业的渔捞日志数据,应用广义加模型(Generalized additive model,GAM)和地理权重回归模型(Geographical weighted regression,GWR)探究南极磷虾(Euphausia superba)渔场分布与环境因子的非线性和空间非静态性关系,并比较这2种模型的模拟性能,为南极磷虾的渔场渔情预报、资源评估和渔业管理提供基础数据。GAM模型结果显示,2015、2016年单位捕捞努力量渔获量(Catch per unit effort,CPUE)与作业水深均呈显著负相关关系(P<0.01),表明在作业水深范围内,南极磷虾在较浅水域集群密度较高;2015年CPUE与表层水温呈显著正相关关系(P<0.01),但在2016年呈显著负相关关系(P<0.01),推测是由于2年调查作业位置不同所致;CPUE与离岸距离关系不显著(P≥0.05)。GWR模型结果显示,作业水深对CPUE的影响无显著的空间变化(P>0.05);海水表温和离岸距离对CPUE的影响具显著的空间变化(P<0.01),表明这2个因子对南极磷虾渔场分布的影响在空间上不连续,存在显著空间非静态性。GAM模型可用于研究资源分布与驱动因子的一般规律;GWR模型作为全局回归模型的有效补充,可用于探究一般规律不适合的特殊区域,便于发现资源分布的“热点”区域,未来在海洋生物资源分布研究中将有广阔的应用前景。 相似文献
11.
The spatial scale(?shing grid) of ?sheries research af fects the observed spatial patterns of?sheries resources such as catch-per-unit-ef fort(CPUE) and ?shing ef fort. We examined the scale impact of high value(HH) clusters of the annual ?shing ef fort for Dosidicus gigas of fshore Peru from 2009 to 2012.For a multi-scale analysis, the original commercial ?shery data were tessellated to twelve spatial scales from 6′ to 72′ with an interval of 6′. Under these spatial scales, D. gigas clusters were identi?ed using the Anselin Local Moran's I. Statistics including the number of points, mean CPUE, standard deviation(SD),skewness, kurtosis, area and centroid were calculated for these HH clusters. We found that the z-score of global Moran's I and the number of points for HH clusters follow a power law scaling relationship from2009 to 2012. The mean ef fort and its SD also follow a power law scaling relationship from 2009 to 2012.The skewness follows a linear scaling relationship in 2010 and 2011 but ?uctuates with spatial scale in2009 and 2012; kurtosis follows a logarithmic scale relationship in 2009, 2011 and 2012 but a linear scale relationship in 2010. Cluster area follows a power law scaling relationship in 2010 and 2012, a linear scaling relationship in 2009, and a quadratic scaling relationship in 2011. Based on the peaks of Moran's I indices and the multi-scale analysis, we conclude that the optimum scales are 12′ in 2009 ? 2011 and 6′ in 2012, while the coarsest allowable scales are 48′ in 2009, 2010 and 2012, and 60′ in 2011. Our research provides the best spatial scales for conducting spatial analysis of this pelagic species, and provides a better understanding of scaling behavior for the ?shing ef fort of D. gigas in the of fshore Peruvian waters. 相似文献
12.
以渤海海域为试验区,对经过时间、空间和波段匹配的 MODIS/Aqua 550 nm 气溶胶光学厚度产品与 CALIOP 532 nm 通道反演得到的气溶胶信息在五种不同空间采样窗口(10 km ×10 km,30 km ×30 km,50 km ×50 km,70 km ×70 km 和90 km ×90 km)、三种不同时间尺度(日、月、季度)下进行了相关性拟合分析.研究发现,较小的空间采样窗口可以更准确地反映气溶胶的局部变化特征,而以季度为时间统计单元能更好地体现气溶胶的季节变化特性.实验结果表明,在10 km ×10 km 采样窗口中,春季的日数据之间相关性较高;春季和秋季的月均值之间高度相关(R 均大于0.950).从而证明,在特定时间和空间尺度下,上述两种数据之间确存在良好的相关性,为利用遥感数据反演渤海海域气溶胶光学厚度信息提供了新的途径. 相似文献
13.
Andrew C. Poje Angelique C. Haza Tamay M. Özgökmen Marcello G. Magaldi Zulema D. Garraffo 《Ocean Modelling》2010,31(1-2):36-50
In order to determine the effect of Eulerian spatial resolution on the two particle statistics of synthetic drifter trajectories, we examine a hierarchy of ocean models, starting from 2D turbulence simulations, progressing to idealized simulations of a buoyant coastal jet with ROMS, and finally to realistic HYCOM simulations of the Gulf Stream. In each case, particle dispersion at large time and space scales is found to be controlled by energetic meso-scale features of the flow that are relatively insensitive to the resolution of finer scale motions. In all cases, time-distance graphs given in terms of computed Finite Scale Lyapunov Exponents show an expected increase in the extent of exponential scaling with increasing spatial smoothing of the velocity field. The limiting value of the FSLE at small separation distances is found to scale remarkably well with the resolution of Eulerian velocity gradients as given by the average of positive Okubo–Weiss parameter values. 相似文献
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J.A. Borg M.J. Attrill A.A. Rowden P.J. Schembri M.B. Jones 《Estuarine, Coastal and Shelf Science》2005,62(4):667-678
Seagrass beds occur in various morphological forms, ranging from small patches to continuous meadows. The endemic Mediterranean seagrass Posidonia oceanica forms dense and extensive stands that occur in several different morphotypes, including reticulate (seagrass interspersed with a different habitat type, such as bare sand) and continuous beds. This study, undertaken in the Maltese Islands, examined whether reticulate and continuous P. oceanica beds, located adjacent to each other and at similar depths, had different within-bed architectural characteristics. Five commonly used architectural measures (shoot density, number of leaves per shoot, mean leaf length, mean leaf width and shoot biomass) were measured from P. oceanica shoots collected from the two bed types at three different spatial scales: (1) tens of metres (‘small’ scale); (2) hundreds of metres (‘medium’ scale); and (3) kilometres (‘large’ scale). Results of 2-factor ANOVA (factor 1=bed type; factor 2=sampling locality) carried out at the three spatial scales indicated significant differences between the two bed types in shoot density (P<0.01) and leaf length (P<0.05) at the small scale, and in leaf number (P<0.05) at the large scale. Significant interactions were also apparent for shoot density (at the large scale) and for shoot biomass (at the medium scale). However, the results obtained did not indicate consistent architectural differences between the two P. oceanica bed types over the spatial scales considered. Spatial variations in within-bed architectural characteristics observed were therefore thought to be attributable mainly to the influence of local environmental factors. The findings are discussed with reference to the conservation and management of P. oceanica habitat. 相似文献
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Schooling behaviour and environmental forcing in relation to anchoveta distribution: An analysis across multiple spatial scales 总被引：7，自引：4，他引：3
Arnaud Bertrand Franois Gerlotto Sophie Bertrand Mariano Gutirrez Luis Alza Andres Chipollini Erich Díaz Pepe Espinoza Jesús Ledesma Roberto Quesqun Salvador Peraltilla Francisco Chavez 《Progress in Oceanography》2008,79(2-4):264
The Peruvian anchovy or anchoveta (Engraulis ringens) supports the highest worldwide fishery landings and varies in space and time over many scales. Here we present the first comprehensive sub-mesocale study of anchoveta distribution in relation to the environment. During November 2004, we conducted a behavioural ecology survey off central Peru and used a series of observational and sampling tools including SST and CO2 sensors, Niskin bottles, CTD probes, zooplankton sampling, stomach content analysis, echo-sounder, multibeam sonar, and bird observations. The sub-mesoscale survey areas were chosen from mesoscale acoustic surveys. A routine coast-wide (2000 km) acoustic survey performed just after the sub-mesoscale surveys, provided information at an even larger population scale. The availability of nearly concurrent sub-mesoscale, mesoscale and coast-wide information on anchoveta distribution allowed for a unique multi-scale synthesis. At the sub-mesoscale (100s m to km) physical processes (internal waves and frontogenesis) concentrated plankton into patches and determined anchoveta spatial distribution. At the mesoscale (10s km) location relative to the zone of active upwelling (and age of the upwelled water) and the depth of the oxycline had strong impacts on the anchoveta. Finally, over 100s km the size of the productive area, as defined by the upwelled cold coastal waters, was the determining factor. We propose a conceptual view of the relative importance of social behaviour and environmental (biotic and abiotic) processes on the spatial distribution of anchoveta. Our ecological space has two y-axis; one based on self-organization (social behaviour), and the other based on the environmental processes. At scales from the individual (10s cm), to the nucleus (m), social behaviour (e.g. the need to school) drives spatial organization. At scales larger than the school, environmental forces are the main driver of fish distribution. The conceptual ecosystem models presented in this paper may provide the final links needed to develop accurate forecasts of the spatial distribution of anchoveta over multiple scales. 相似文献
18.
D. Jeff Ross Craig R. Johnson Chad L. Hewitt 《Estuarine, Coastal and Shelf Science》2006,67(4):695-707
The northern Pacific seastar, Asterias amurensis, was first collected in southeast Tasmania in 1986. Mistaken for the endemic asteroid Uniophora granifera, its true identity was not realised until 1992. It is now a conspicuous predator in soft sediment habitats in this region, and is considered a major threat to native assemblages and commercial species. We examined the structure of soft sediment assemblages at different spatial scales in southeast Tasmania, and correlated spatial variation in community composition with seastar abundances. We found that the structure of soft sediment assemblages is highly variable at a range of spatial scales from metres to tens of kilometres. Clear differences in the composition of assemblages and abundances of major taxa were detected between areas with and without seastars and between areas with low and high seastar densities. However, the nature of these patterns suggests that they are more likely due to differences in sediment characteristics than due to impacts of the seastar. Thus, spatial differences in soft sediment assemblages might have been erroneously attributed to seastars without detailed information on important physical factors such as sediment characteristics. A second survey, using larger sampling units (1 m2) but across a more limited spatial extent, targeted bivalves and heart urchins that were identified as important prey of the seastar in observations of feeding and in experimental studies. Large-scale patterns of abundance and size structure were consistent with seastar effects anticipated from small-scale experimental and feeding studies for some, but not all, species. While the field survey ultimately provided evidence about the presence or absence of seastar impacts at large-scales, the identification of key ecological variables in experimental and feeding studies proved crucial to both the design and interpretation of patterns observed in the large-scale surveys. Overall, this work highlighted the necessity to consider multiple lines of evidence rather than relying on a single ‘inferential’ test, in the absence of pre-impact data. 相似文献