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1.
黄河口及邻近海域底栖群落健康及生境适宜性评价 总被引：1，自引：0，他引：1
《中国海洋大学学报(自然科学版)》2015,(12)
根据2013年10月黄河口及邻近海域大型底栖动物、水和沉积环境数据,应用Multivariate AMBI(M-AMBI)指数评价了该海域的底栖群落健康和生境状况,通过分析底栖群落健康和生境质量的环境限制因子,本文对研究水域底栖生境的适宜性进行了评价。结果表明,本航次在研究海域共采集到45种大型底栖动物,分属于5个类群,其中多毛类占明显优势,底栖动物以生态组EGI和EGII为主。36.4%的站位底栖群落健康处于良好等级,18.2%的站位处于差的等级,其余各站位处于中等。主成分和相关分析结果显示,M-AMBI指数能敏感地响应底栖生境环境受扰动和污染的状况,水体水深、盐度和溶解无机氮,以及沉积物石油烃和硫化物等是限制底栖群落健康和生境质量的主要因子。根据限制性环境因子,本文对黄河口及邻近海域底栖生境的适宜性进行了划分。在水深较浅、盐度较低和污染相对较重的河口及近岸区域不适宜底栖动物的栖息;在水深较深、盐度较高和无明显污染的近海区域较适宜大型底栖群落的栖息和健康。 相似文献
2.
海州湾鹰爪虾栖息地适宜性研究 总被引：1，自引：0，他引：1
根据2011年及2013?2017年春季和秋季在海州湾进行的底拖网调查数据,结合同步测定的底层水温、底层盐度、水深和资源量等数据,开展鹰爪虾(Trachypenaeus curvirostris)栖息地适宜性的研究,先利用广义加性模型对环境因子进行筛选,再应用提升回归树模型确定各环境因子的权重,然后分别采用算术平均法和几何平均法建立栖息地适宜性指数模型,并通过交叉验证选择最优模型。结果表明:春季鹰爪虾的栖息地适宜性指数模型采用算术平均法构建,选择水深和底层盐度作为变量,具有最小的拟合;秋季鹰爪虾的栖息地适宜性指数模型采用几何平均法构建,选择底层水温和底层盐度作为变量,具有最小的拟合。对春季栖息地适宜性指数模型总偏差贡献率最大的是水深(76.23%),其次是底层盐度(23.77%);对秋季栖息地适宜性指数模型总偏差贡献率最大的是底层水温(82.56%),其次是底层盐度(17.44%)。海州湾春季鹰爪虾的最适栖息水深为24 m以内,底层盐度为29.7～31.8;秋季的最适栖息底层水温为18～24℃,底层盐度为29.2～31.5。本研究表明,环境因子的优化有助于改进栖息地适宜性指数模型,并提升其预测能力。 相似文献
3.
本研究于2020年1月（冬季）、3月（春季）、8月（夏季）和11月（秋季）对大亚湾西部海域的海地瓜（Acaudina molpadioides）空间分布和环境特征进行了调查研究,并结合室内养殖实验,分析了海地瓜的空间分布规律和栖息特性。结果表明：①海地瓜最高生物量达到170 g/m2,其栖息生境为粘土质粉砂和砂质粉砂,低温季节具有较高生物量。②主成分分析（principal component analysis, PCA）发现,有海地瓜分布的站位环境特征表现为较大的水深、盐度和溶解氧浓度,以及较低的水温、叶绿素a含量和较细的底质。③海地瓜的埋栖特征表现为口部向下、尾部朝上,以粘土质粉砂层下的黑色胶泥为食。④经组织切片观察,海地瓜体壁表层无管足,口部有15个触手。海地瓜体表运动器官缺乏,附着能力较弱。⑤主成分分析结果表明,大亚湾西部海域适宜海地瓜栖息的底质为粘土质粉砂,常出现在盐度较高、温度较低的深水区域。冬季和春季的调查数量高于其他季节,这需要进一步研究其生活史以明确其在不同时期内的生活习性。 相似文献
4.
以小黑山岛潮下水生层为研究区域,利用生境适宜性指数（habitat suitability index,HSI）模型,同时结合GIS空间分析,选划出适宜毛蚶的增殖修复区域。综合文献查阅和咨询专家咨询的方式,确定影响毛蚶生存的7个重要影响因子,分别为：底质类型,水温,盐度,溶解氧,水深,pH和氨氮。结合专家赋值法和层次分析法确定每个评价因子的权重,利用GIS空间分析模块将现状调查数据进行插值、重分类和栅格计算,绘制研究区域目标种群生境适宜性地图。结果表明：对于刺参和紫贻贝,研究区域均适宜其生长繁殖,同一物种,相同季节在空间上无站位差异,但各季节的生境适宜性分区变化明显;对于魁蚶来说,东北部海域较适宜增殖,其次为西部海域,四季均以较适宜生境为主,仅冬季出现基本适宜生境。水温是造成季节差异的主要因素,底质类型则是引起生境站位差异的重要原因。可为后续的生物多样性保育和生态修复提供基础资料参考。 相似文献
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对南海北部224个表层沉积物样品的粒度组成和碳酸盐含量进行了测试和分析,探讨了沉积物的运移方式及其沉积环境。结果表明,南海北部表层沉积物可划分为砾砂、粗砂、中砂、细砂、粉砂质砂、砂质粉砂、砂-粉砂-黏土、黏土质粉砂、粉砂质黏土、黏土等类型,其中深海-半深海沉积物又可分为:硅质黏土、钙质黏土、含钙质和硅质黏土、有孔虫砂、钙质黏土质粉砂、钙质砂-粉砂-黏土、硅质黏土质粉砂。粉砂质黏土、黏土质粉砂、砂、砂质粉砂、黏土是分布最广泛的沉积物类,约占该区面积的80%以上。同时对粒度相关参数和碳酸盐含量进行了因子统计分析并作沉积环境分区,结果表明上述参数可分为3类因子,将研究区分为4类区域。因子1作用于Ⅰ、Ⅱ两个区域。Ⅰ区为黏土级沉积区,主要分布在研究区东南部水深较大的海域;Ⅱ区为中、细砂质沉积区,主要分布在粤西外大陆架和华南大陆沿海。因子2作用于Ⅲ区,为粗、中粉砂质沉积区,主要分布在琼东南、珠江口外海大陆坡以及台西南外大陆架。因子3作用于Ⅳ区,为粗砂质沉积区,主要分布在台西南内大陆架海域。 相似文献
6.
长江口中华鲟幼鲟栖息地适宜性评价 总被引：1，自引：0，他引：1
对影响长江口中华鲟幼鲟的各种生态因子进行统计,分析整理出其栖息选择的浮游动物、底栖生物、温度和盐度4个关键指标,确定了其阈值和最适范围,采用栖息地适宜性指数法(HS)I进行定量评价。以2004-2010年长江口崇明东滩插网监测的中华鲟幼鱼数据、水质、生物数据进行了适宜性指数法模型的验证,最后结合2006年夏季上海市近岸水体调查数据,运用GIS空间分析的技术手段,对适宜性指数法评价结果进行了分析。结果表明,最适宜栖息地(0.75≤HSI<1)面积为142 km2,占评价范围的2.2%;适宜(0.5≤HSI<0.75)面积为1 322 km2,占20.5%;一般适宜(0.25≤HSI<0.5)面积为2 098 km2,占32.5%;不适宜(0≤HSI<0.25)面积为2 884 km2,占44.8%。为中华鲟物种保护空缺(GAP)寻找和保护区建设提供参考。 相似文献
7.
对珠江口外CJ14区块250个站位的表层沉积物进行底栖有孔虫分析,共发现底栖有孔虫118种,其中玻璃壳质80种,瓷质壳质21种,胶结壳质17种。有孔虫丰度基本随水深变深而增大。为研究底栖有孔虫分布与沉积环境之间的关系,对底栖有孔虫含量进行Q型因子分析,并选取前4个主因子,分别对应4个有孔虫组合。它们总共解释了总方差的86.2%,基本上反映了沉积物中有孔虫的群落结构。研究表明,水深和盐度是影响珠江口表层沉积物中有孔虫组合分布的控制因素,其他影响因素主要包括沉积物类型、水动力条件和沉积速率。水动力条件主要影响有孔虫的含量;沉积速率主要影响有孔虫的丰度。 相似文献
8.
海南新村港潟湖表层沉积物粒度特征及其沉积环境 总被引：5，自引：2，他引：3
对2013年8月在海南新村港潟湖采集的表层沉积物样品进行粒度分析,揭示了该区表层沉积物的粒度特征和沉积物类型,结合高空间分辨率的水动力和水深数据,采用系统聚类和主成分相结合的方法划分现代沉积环境。结果表明,研究区表层沉积物主要有4种类型,以粉砂和粉砂质砂为主,分别分布在潟湖中部和近岸浅水区域。沉积物平均粒径变化较大(0~8.0 Ф),均值为4.6 Ф,沉积物随水深增大而逐渐变细;沉积物粒度组分以砂(平均含量43%)和粉砂(平均含量为52%)为主,黏土含量较少,平均含量为5%。聚类结果表明,平均粒径可分为两组:第一组平均粒径均大于5.5 Ф,均值为6.8 Ф;而第二组平均粒径均小于3.5 Ф,均值为2.2 Ф。此外,平均粒径与分选、偏态和峰态系数之间呈现出两种不同的相关关系。研究区大潮和小潮期间的均方根流速(RMSV)均值是7.5和6.9 cm/s,标准偏差分别是15.3和14.9 cm/s。当RMSV大于4 cm/s,RMSV与极细砂(63~125 μm)含量呈明显的正相关关系,这表明RMSV决定了潟湖沉积物中极细砂含量。聚类和主成分分析结果表明,平均粒径、峰态和分选系数是对沉积环境最为敏感的粒度参数组合,同时结合高空间分辨率的水动力和水深数据,将研究区沉积环境划分为3类。这样划分充分考虑了水动力、物源、地形及其相互作用,更能有效地揭示沉积环境的差异,尤其体现了适宜的粒度参数组合和高空间分辨率的水动力数据在沉积环境划分中的重要性。 相似文献
9.
南海东部海域表层沉积物类型的研究 总被引：10，自引：3，他引：7
南海东部海域表层沉积物可被分为11种类型:含岩块砾石黏土质粉砂、贝壳珊瑚砂、黏土质粉砂、钙质黏土、钙质软泥、有孔虫砂、深海黏土、含铁锰微粒粉砂质黏土、硅质黏土、含火山灰硅质黏土、含火山灰粉砂质黏土.这些类型按物源和成因可被分为陆源碎屑、钙质碎屑和硅质碎屑、火山碎屑3大类型,其中陆源碎屑分布面积约占50%,钙质碎屑占20%,硅质碎屑和火山碎屑各占15%.在物质来源、海底地形、火山作用、生物作用、水动力条件等因素影响和控制下,由于沉积环境的差异,故区内褐色类沉积物最多(60.68%),灰色类沉积物次之(38.20%),黄色类沉积物最少(1.12%).台湾省以南到17°N以北海区沉积物以陆源沉积物分布为主;巴士海峡以西海区沉积物较粗,常含砂岩块和砾石;东沙群岛以东海区钙质生物碎屑沉积丰富;中、西部海区以含铁锰微粒沉积物为主;中、南部海区水深大,主要分布硅质沉积物;南部海区、礼乐滩北缘沉积物受礼乐滩珊瑚碎屑影响大,沉积物类型为钙质软泥. 相似文献
10.
黄河口海域盐度变化受黄河入海径流量、气候及海洋动力条件的影响,河口沉积物的沉降、固结及侵蚀等动力学行为与黄河口海域盐度变化有密切关系。为研究不同盐度环境对河口沉积物抗侵蚀性变化的影响,在现代黄河三角洲刁口河路潮滩上进行原位试验,模拟不同盐度的沉积环境,使用黏结力仪（CSM）对细粒沉积物进行抗侵蚀性测试。结果表明细粒沉积物的临界剪应力为0.728～1.581Pa,且随着沉积环境盐度增加,细粒沉积物的临界剪应力呈线性增加。当沉积环境盐度增加1时,其临界剪应力增加约0.02Pa。 相似文献
11.
根据2011年和2013?2018年秋季在海州湾及邻近海域进行的底拖网调查数据,结合同步采集的底层水温、底层盐度、水深、资源密度、饵料生物等生物和非生物因子数据,开展长蛇鲻(Saurida elongata)栖息地适宜性的相关研究。利用提升回归树(Boosted Regression Tree, BRT)模型确定各环境因子的权重,分别采用算术平均法和几何平均法建立栖息地适宜性指数(Habitat Suitability Index, HSI)模型,并通过交叉验证确定最优模型。结果表明:海州湾长蛇鲻在秋季最适宜栖息的底层水温范围为17.5～18℃,最适底层盐度范围为31.3～32.0,最适水深范围为24～37 m;选择其3种主要饵料生物作为生物因子,即枪乌贼(Loligo spp.)、戴氏赤虾(Metapenaeopsis dalei)和六丝钝尾鰕虎鱼(Amblychaeturichthys hexanema),与底层水温、底层盐度和水深共同作为影响因子建立HSI模型。结果显示,对长蛇鲻空间分布总偏差贡献率最高的是饵料因子,其次是水深和底层水温。通过交叉验证发现,运用算术平均算法,且赋予权重的HSI模型具有较低的赤池信息准则值(Akaike Information Criterion, AIC)。研究发现,海州湾秋季长蛇鲻的最适栖息地(HSI≥0.7)主要分布在34.5°～36°N,119°～121°E之间,其中35°～36°N海域的最适栖息地分布范围大,而且从近岸至远海,HSI指数有增加的趋势。 相似文献
12.
剑鱼（Xiphias gladius）是一种高度洄游性鱼类,其迁徙和栖息地利用受海洋环境影响明显,理解其空间分布格局形成的机制对于资源的养护和管理具有重要意义。本研究利用2017-2019年中国印度洋延绳钓渔业观察员数据中剑鱼的渔获物信息作为物种出现数据,结合西印度洋海域的海表温度、海面高度、叶绿素a浓度、混合层深度、海表盐度等环境数据,采用最大熵模型对剑鱼的栖息地适宜性分布进行了模拟。结果表明：（1）模型对印度洋西部剑鱼栖息地适宜性分布的模拟精度非常高,各个季节受试者工作特征曲线的曲线下面积都大于0.9,可用于模拟剑鱼潜在的栖息地适宜性分布;（2）研究区域内剑鱼适宜栖息地分布变化与实际作业位置变动基本一致,干季和湿季剑鱼栖息地高适宜性的区域分布都较为集中,但湿季分布范围要大于干季;（3）海表温度、海表盐度和混合层深度是影响西印度洋剑鱼栖息地适宜性分布的重要环境因子,在干季和湿季的最适范围分别为25.8～31.6℃、34.4～35.9、0.1～24.9 m和25.6～30.5℃、34.8～36.4、13.1～54.1 m。研究结果可为西印度洋海域剑鱼种群的可持续利用和科学管理提供必要参... 相似文献
13.
Yunlong Chen Xiujuan Shan Dingyong Zeng Harry Gorfine Yinfeng Xu Qiang Wu Tao Yang Xianshi Jin 《海洋学报(英文版)》2022,41(6):22-30
Acquiring a comprehensive and accurate understanding of habitat preference is essential for species conservation and fishery management, especially for mobile species that migrate seasonally. Presence and absence data from field surveys are recommended when available due to their high reliability. Using field survey data, we investigated seasonal habitat suitability requirements for Tanaka’s snailfish (Liparis tanakae) in the Bohai Sea and Yellow Sea (BSYS) via a machine-learning method, random forests (RFs). Five environmental and biologically relevant variables (bottom temperature, bottom salinity, current velocity, depth and distance to shore) were used to build the ecological niches between the presence/absence data and suitable habitat. In addition, the degree to which false absence data might impact model performance was evaluated. Our results indicated that RFs provided accurate predictions, with seasonal habitat suitability maps of L. tanakae differing substantially. Bottom temperature and salinity were identified as important factors influencing the distribution of L. tanakae. False absence data were found to have negative effects on model performance and the decrease in evaluation metrics was usually significant (P<0.05) after 30% or more errors were added to the absence data. Through identifying highly suitable areas within its geographic range, our study provides a baseline for L. tanakae that can be further applied in ecosystem modelling and fishery management in the BSYS. 相似文献
14.
《African Journal of Marine Science》2013,35(2):487-499
The spawning habitats of anchovy Engraulis encrasicolus and sardine Sardinops sagax in the southern Benguela upwelling ecosystem were characterised by comparing their egg abundances with environmental variables measured concomitantly during two different survey programmes: the South African Sardine and Anchovy Recruitment Programme (SARP), which comprised monthly surveys conducted during the austral summers of 1993/94 and 1994/95; and annual pelagic spawner biomass surveys conducted in early summer (November/December) from 1984 to 1999. Eggs were collected using a CalVET net. Physical variables measured included sea surface temperature (SST), surface salinity, water depth, mixed-layer depth, and current and wind speeds; biological variables measured included phytoplankton biomass, and zooplankton biomass and production. Spawning habitat was identified by construction of quotient curves derived from egg abundance data and individual environmental variables, and relationships between these variables were determined using multivariate co-inertia analysis. SARP data showed that anchovy spawning was associated with cool water and moderate wind and current speeds, whereas sardine spawning was related to warmer water and more turbulent and unstable conditions (i.e. high wind speeds and strong currents) than for anchovy. SARP data also showed significant differences in selection of spawning habitat of the two species for all environmental variables. The relationship between anchovy egg abundance and salinity was strongly positive, but strongly negative with water depth, phytoplankton biomass and zooplankton production. Sardine egg abundance was strongly positively related to current speed. The spawner biomass survey data demonstrated that the spawning habitat of anchovy was characterised by warm water and high salinity, whereas sardine spawning was associated with cool water and low salinity. The survey data showed significant differences in spawning habitat selection by anchovy and sardine for SST, salinity and zooplankton biomass, but not for the other environmental variables. There was a positive relationship between anchovy egg abundance and SST, salinity and mixed-layer depth, and a negative relationship with water depth, phytoplankton biomass and zooplankton production. For sardine there was a strong positive relationship between egg abundance and current speed and wind speed. Differences in the results between the two survey programmes could be attributable to differences in their spatio-temporal coverage. Spawning habitats of anchovy and sardine appear to be substantially different, with anchovy being more specific than sardine in their preference of various environmental conditions. 相似文献
15.
三疣梭子蟹(Portunus trituberculatus)是莱州湾最重要的经济蟹类,其资源丰度受栖息环境影响显著,为了解不同的环境因子对其栖息地分布的影响,根据2010~2020年夏季底拖网调查数据,研究莱州湾三疣梭子蟹栖息地适宜性及其影响因子。利用广义可加模型(generalized additive models,GAM)选取变量因子,通过提升回归树模型(boosting regression tree,BRT)对因子进行权重分析,构建了4种栖息地适宜性指数(habitat suitability index,HSI)模型,并通过实测值和预测值的Pearson检验,对模型比较和验证。结果表明,GAM和BRT优化的HSI模型好于其他3种模型(未优化模型,GAM优化HSI模型,BRT优化HSI模型),以生物量表征资源丰度的模型好于尾数表征资源丰度的模型,算术平均法构建的HSI模型的整体预测准确率和相关系数高于几何平均法,对莱州湾三疣梭子蟹栖息地有较强的预测能力。底层水温、底层盐度和水深对三疣梭子蟹栖息地影响较大,夏季栖息地适宜性较高的海域(HSI>0.7)主要分布在莱州湾南部、东南部和东北部海域,中部和西南部海域分布较少。研究结果为莱州湾三疣梭子蟹增殖放流工作提供了科学依据。 相似文献
16.
海州湾春季皮氏叫姑鱼栖息地适宜性研究 总被引：4，自引：0，他引：4
根据2011年及2013-2015年春季在海州湾及其邻近海域进行的底拖网调查数据,结合同步采集的底层水温、底层盐度、水深以及资源密度等数据,开展皮氏叫姑鱼（Johnius belangerii）栖息地适宜性的相关研究。利用提升回归树（boosted regression tree,BRT）模型确定各环境因子的权重,分别采用算术平均法（AMM）和几何平均法（GMM）建立栖息地适宜性指数（habitat suitability index,HSI）模型,并通过交叉验证确定最优模型。结果表明,皮氏叫姑鱼幼体最适栖息的底层水温为17.4~18.0℃,底层盐度为29.2~30.8,水深为7 m以浅;成体最适栖息的底层水温为17.3~18.0℃,底层盐度为28.8~30.8,水深为12 m以浅。根据BRT模型的输出结果显示,对皮氏叫姑鱼幼体总偏差贡献率最大的是水深,其次是底层盐度和底层水温;对成体总偏差贡献率最大的是底层水温,其次是水深和底层盐度。通过交叉验证发现,无论幼体还是成体,运用GMM算法,且赋予权重的HSI模型具有较低的赤池信息准则值（akaike information criterion,AIC）。海州湾春季皮氏叫姑鱼的最适栖息地随生长阶段而变化,幼体的最适栖息地（HSI ≥ 0.7）主要分布在7 m等深线以浅的山东、江苏沿岸海域;成体的最适栖息主要分布于12 m等深线以浅的海域。海州湾春季皮氏叫姑鱼幼体和成体最适栖息地的空间分布与其自身的生态习性、外界环境因子以及黄海冷水团、近岸沿岸流等因素密切相关。 相似文献
17.
《Estuarine, Coastal and Shelf Science》2003,56(3-4):749-764
A challenge for marine ecologists is to explain distinct and recurrent patterns in the distribution of marine faunas by developing new methods that identify and link environmental processes responsible for these patterns. Methods that describe and predict the distribution of benthic faunas using single factors such as sediment type or water depth are generally inadequate, particularly when applied on a broad scale. When a combination of factors such as near-bed tidal velocity, surface seawater temperature and salinity are evaluated in conjunction with sediment type and depth, however, they more clearly characterise benthic habitats. Using principal component analysis (PCA) patterns in the distribution and abundance of different echinoderm and crustacean species were shown to be predictable and characterised by a suite of physical factors. Characterising benthic habitats using factors from the environment provided a potential mechanism for predicting patterns in their spatial distribution. A new analytical method for characterising a species habitat was constructed using a combination of PCA and a generalised additive model. The method is able to predict the habitat preferences of individual species based on their association with physical factors characterising their habitat. These preferences were then used to describe the probability of a species occurring across a range of different habitats, which is referred to as the habitat-envelope. This method enables one species habitat range to be compared directly to another. The strong correlation between species patchiness and its habitat-envelope was used to develop an index to identify species that are potentially more sensitive to habitat change. Distinct patterns in the habitat preferences of echinoderms were generally stronger than those identified for crustaceans. Thus, crustaceans were found more likely to exploit a wider range of habitats than echinoderms, suggesting that they may be less sensitive to habitat change. 相似文献
18.
Lakes Waihola and Waipori are shallow, coastal, tidal lakes that experience wind‐induced sediment resuspension, saline intrusions, and high inputs of nutrients. To determine the influence of externally‐driven, physical factors on spatial and temporal patterns of water quality in the two lakes, meteorological, hydrological, and water quality data were collected over 1 year. Multivariate analyses indicated that wind energy was driving the main water quality gradient in the lakes, which was primarily related to wind‐induced resuspension of lake sediments. The major, seasonally regulated, non‐tidal freshwater inflow was important in determining nutrient and salinity gradients in the lakes. The main nutrient inputs to the system were identified as the regulated, non‐tidal inflow (the upper Waipori River) and the tidal inflow (lower Waipori River). The impact of water quality gradients on zooplankton community structure in the lakes was assessed by canonical multivariate methods. Salinity gradients, caused by seasonal saltwater intrusions, were strongly related to zooplankton community structure in the lakes. Nutrient gradients (indicative of trophic state) were also related to zooplankton community structure. Although wind‐induced sediment resuspension had the largest impact on water quality in the lakes, it had little impact on the zooplankton community structure in either lake. The relationships between water quality and zooplankton community structure were confounded in Lake Waipori because of its very short hydraulic residence time (annual mean =1.9 days). Zooplankton community structure was resilient to short‐term changes in suspended particulate matter concentrations but not to seasonal changes in salinity. The results of this study support others which have shown impacts of even relatively small variations in salinity on the structure of zooplankton communities. This highlights the vulnerability of zooplankton communities in coastal lakes and wetlands to increasing salinity resulting from sea level rise and global climate change. 相似文献