Institutional Repository of Key Laboratory of Marine Ecology & Environmental Sciences, CAS
|Place of Conferral||中国科学院海洋研究所|
|Keyword||鳗草 海草床 分布现状 声呐探测技术 种子保存|
鳗草（Zostera marina L.），又名大叶藻，广泛分布在北半球的温带海域，是中国北方温带沿海海草的优势种，主要分布在辽宁、山东、河北沿海地区。人类活动正日益威胁海草床的健康，开展近海重要海草资源及生境调查研究亟需进行。本文运用现场采样调查、声呐探测技术和水下观测系统等手段对我国典型鳗草海草床的分布特征调查，查明鳗草资源退化现状；并结合室内实验控制温度、盐度，探寻鳗草种子长期保存的最适条件，构建鳗草人工种子库，研究结果对鳗草资源的监测、保护和种子法恢复具有指导意义。主要结果如下：
（3）通过对比地形转栅格（Topo to Raster）、反距离权重法（inverse distance weight，IDW）和克里金法（Kriging）这三种插值分析方法发现，相对于其他两种方法，地形转栅格能产生圆滑且更符合真实情况的栅格表面，插值精度高且更加保守，更适合应用于声呐探测海草床数据的分析过程。
（1） 利用声呐探测技术结合现场定点验证，对威海天鹅湖鳗草海草床的时空分布特征进行研究。威海天鹅湖海草床面积在7-9月达到最大值（199.09ha~231.67ha），对应海草的生长高峰期，显著高于过冬后（5月份）的海草床面积（88.46ha）。鳗草在天鹅湖从南到北均有分布，主要分布在天鹅湖中部，在2018年8月的平均海草高度为0.482m。天鹅湖平均水深约为1.6 m，整体水深较浅仅东南部的深沟和航道处水深较深，最深水深约6 m。结合现场验证环节，通过分析声呐的回波图，能分辨出鳗草和硬毛藻(Chaetomorpha linum)。天鹅湖中海草存在的地方常伴有硬毛藻的出现，硬毛藻现已经对天鹅湖海草资源构成严重的威胁。
（2） 利用声呐探测技术结合现场定点验证，在河北唐山曹妃甸沿海报道目前国内面积最大的鳗草海草床，也是面积最大的单种海草床，海草床面积高达2916.81ha，海草床外围面积高达9025.56ha。此处鳗草海草床8月份平均海草高度为0.457m；高度范围在0.2 m~0.6 m之前的海草面积为2644.69 ha，占总海草床面积的90.67%；海草覆盖度高于60%的海草面积为1959.38 ha，占总海草床面积的67.18%。此处鳗草海草床在5-6月份具有一定比例的生殖枝，种子成熟后，生殖枝开始衰落，鳗草营养枝生长高峰期在7月末。
（1） 在研究温度和盐度对鳗草种子长期保存影响实验中，对照组（室温，盐度30psu）保存条件下的种子有大量萌发损失，保存3个月后损失率就高达68.65%； 4℃低盐度（30-50psu）保存条件下，鳗草种子损失也较严重，4℃/30psu处理组保存3个月后的种子损失率为48.36%，4℃/50psu处理组保存12个月后的种子损失率高达60.66%；相比之下，保存温度为0℃的各盐度处理组(30-70psu) 在保存12个月后的种子损失率均不超过20%，0℃/40psu、0℃/50psu和0℃/70psu三个处理组的种子损失率甚至不超过10%，均保持较低水平。此外，与4℃种子保存条件相比，0℃保存条件下的种子因微生物感染而腐烂的可能性也更小。
The eelgrass Zostera marina L. is a dominant seagrass species circumglobally distributed in temperate coastal environments in the North Hemisphere, which mainly occurs in coastal areas of Hebei, Shandong, Liaoning and other provinces in China. Human activities are increasingly threatening the health of seagrass beds, and it is urgent to carry out research on important coastal seagrass resources and habitats. In this paper, we used an in-situ sampling survey, sonar detection technology and underwater observation system to investigate the distribution characteristics and habitats of typical eelgrass meadows in temperate China; and we studied the effects of temperature and salinity on the long-term storage of eelgrass seeds in laboratory conditions. The results may facilitate the monitoring, conservation and restoration of seagrass resources. The main results are summarized as followed:
1. The advantages and analysis process of sonar detection technology in monitoring the distribution characteristics of seagrass beds
(1) In contrast to direct sampling methods and optical remote sensing, active hydroacoustic techniques are relatively inexpensive and efficient for the detection of seagrass meadows. In this paper, we introduced the processes of sonar data acquisition, data processing and data analysis in detail, and obtained the seagrass distribution maps, the seagrass coverage distribution maps, and water depth distribution maps of the target seagrass beds.
(2) We proposed a method for determining the accuracy of interpolation analyses. Though fully use the tools in ArcGIS and the principle of interpolation analysis, we may design the sonar detection route and verification line in advance, and randomly extract the verification points from the verification line. According to the real values and the prediction values of the verification points, the accuracy of the interpolation analysis can be calculated.
(3) We used three interpolation analysis methods to analyze the same sonar data in August 2018. These methods include Topo to Raster, Kriging, and IDW. The raster surface obtained from Topo to Raster is considerably smoother compared to those from the other two methods. Topo to Raster has the highest interpolation accuracy and is the most conservative among three interpolation methods. Thus, we concluded that Topo to Raster was the most suitable interpolation method for sonar detection of seagrass beds.
2. Sonar detection of seagrass beds
(1) In the present study, we used a single beam echosounder to investigate the spatial and temporal distribution characteristics of Swan Lake seagrass beds. The distribution of seagrass in Swan Lake varies with seasons, with maximum distribution area in summer. The maximum distribution area of seagrass beds in Swan Lake was 199.09 ha-231.67 ha, accounting for 41.48%-48.26% of the area of Swan Lake. The area of seagrass beds in Swan Lake was significantly reduced in winter (88.46ha). The distribution of seagrass in Swan Lake was concentrated in the central area of the lake and got patchy around the lagoon. The average canopy height of seagrass in August 2018 was 0.482 m. The average water depth in Swan Lake was approximately 1.6 m, and deep gullies existed only in the southeast. We could distinguish the echogram of the bloom-forming macroalgae Chaetomorpha linum K. and the eelgrass Z. marina. We observed that C. linum was increasingly threatening seagrass beds in Swan Lake, which might lead to a decrease in seagrass bed area and biomass in Swan Lake.
(2) Based on the sonar detection technology, the largest Z. marina seagrass beds in China was discovered in the coastal waters of Tangshan in Bohai sea with a seagrass bed area of 2916.81ha. The average canopy height in this eelgrass beds was 0.457m; the area of seagrass meadow whose canopy height in the range from 0.2 m~0.6 m was 2644.69 ha, accounting for 90.67% of the total seagrass beds; the area of seagrass meadow with seagrass coverage higher than 60% was 1959.38 ha, accounting for 67.18% of the total seagrass beds. A certain proportion of reproductive branches appeared in May-June. After the seeds matured, the numbers of reproductive branches began to decline, and the peak growth period of the vegetative branches was the late July.
3. In-situ sampling survey and underwater observation system research results
In the coastal areas of Xingcheng city and Changhai city, Liaoning Province, we found a large area of seagrass distribution. The seagrass bed area in Xingcheng was ca. 800ha, which had important research value. The underwater observation system had great potential for in-situ observing the biodiversity, animal habits and behavioral characteristics of the seagrass bed ecosystems.
4. Results of long - term eelgrass seed storage experiment
(1) During the long-term eelgrass seed storage experiment, the seeds stored in the control group germinated rapidly at a salinity of 30 psu and under variable room temperature (5–20 oC) conditions, where the percentage seed loss was 68.65% after three months of storage. There was a high seed loss percentage at 4oC with a salinity of less than 60 psu, and the highest seed loss was observed in the 30 psu salinity and 4oC treatment, with 12% after 1 month, 37% after 2 months, and 48.36% after 3 months. Conversely, after storage for 12 months, all of the treatments at 0oC kept lower seed loss percentages, which were not more than 20%, and some treatments (0oC/40psu, 0oC/50psu and 0oC/70psu) were even not exceed 10%. In addition, compared with the seeds stored at 4oC, the seeds stored at 0oC were less likely to be infected by bacteria.
(2) After storage for 12 months, both salinity and temperature had significant effects on seed value. There was high seed loss and lower seed vigor in the 4 oC treatment groups, therefore, 4 °C is not suitable for the long-term storage of eelgrass seeds. Although the seed loss rate during storage under high salinity conditions (60psu and 70psu) was very low, the seed vigor after storage was also low, which was also not suitable for the long-term storage of eelgrass seeds. Seeds stored in conditions of 0°C/30psu, 0°C/40psu and 0°/C50psu maintained high seed vigor (>60%) after 12 months of storage, but a higher seed loss rate (17.67%) at 0°C/30psu. Considering the seed loss rate and the seed vigor after storage, a salinity of 40-50 psu and a temperature of 0°C were the optimal conditions for long-term wet storage of Z. marina seeds.
|Subject Area||生物学 ; 生物工程(亦称生物技术)|
|MOST Discipline Catalogue||工学 ; 工学::生物工程|
|许帅. 黄渤海典型鳗草海草床声呐探测及种子保存研究[D]. 中国科学院海洋研究所. 中国科学院大学,2019.|
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