Seagrass meadows are declining at alarming rates globally due to both anthropogenic activities and natural threats. Seagrasses play key ecological roles in coastal ecosystems as primary producers and providers of habitat and environmental structure. Therefore, mapping seagrass beds is indispensable for the effective monitoring and management of coastal vegetated habitats. In contrast to direct sampling techniques and optical remote sensing, active hydroacoustic techniques are relatively inexpensive and efficient for the detection of seagrass. We used a single beam echosounder to detect the spatial and temporal distribution characteristics of the eelgrass Zostera marina L. in an important overwintering habitat for the whooper swan Cygnus cygnus (Swan-Lake lagoon), northern China. We also distinguished echograms of the macroalgae Chaetomorpha linum K. and outlined its threat to seagrass. We also propose a method for calculating the accuracy of interpolation analyses. Results showed that: (1) 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; (2) C. linum is a growing threat for seagrass beds of Swan-lake, with distribution area as high as 129.28 ha in May 2018. The invasion and competition by C. linum against seagrass beds could be one of the reasons for the decline in seagrass beds in Swan-Lake; (3) Topo to Raster has the highest interpolation accuracy and is the most conservative among three interpolation methods. Topo to Raster was the most suitable interpolation method for the sonar detection of seagrass beds. The findings may facilitate the application of sonar technology in seagrass monitoring and provide data for the formulation of appropriate seagrass bed management and restoration strategies and policies.

Shengjin Lake is a typical lake wetland in the lower reaches of the Yangtze River. It is one of the most important wetlands in the world. It is also an important habitat for wintering cranes in China. Environmental factors play an important role in habitat selection of cranes of wetland ecosystem. In this paper, we analyzed land-use types and the four kinds of winter cranes in the Shengjin Lake from the years 1986 to 2015. Also, we adopted grey relational analysis and power function model to analyze the relevance between crane population and land-use types, and the main habitat types of cranes were obtained. We used principal component analysis method to analyze the main influence factor for habitat selection of crane. The results indicated that the main habitat type of four species of overwintering crane was reed-flat; the main factors affecting the habitat selection of cranes were water level, planktonic biomass, and distance to settlement. Among them, the weight of water level factor was the highest, which showed that water level was the most important factor affecting the habitat selection of cranes, followed by planktonic biomass, and the third was the weight of distance to settlement. The average values of them were 0.37 m, 9.47 mg L⁻¹, and 1.25 km, respectively.

The correct corresponding Author of this paper is Bin Dong.

Shengjin Lake wetland is located in the middle and lower reaches of the Yangtze River in China. It is a typical lake-type wetland and is also an ideal place for rare cranes to overwintering. The changes of wetland landscape are closely related to the habitat quality of wintering cranes. It is of great significance to study the habitat change of wintering cranes in wetland for wetland ecological restoration and restoration. In this paper, we analyze four kinds of winter cranes and wetland landscape pattern types from the years 1986 to 2015. Also, we adopted the Pearson correlation analysis method to analyze the relationship between wetland landscape types and crane population, and the main landscape types of cranes habitat were obtained. We selected disturbance degree, food richness, vegetation cover, and hydrological condition as the main factors affecting wintering habitat of cranes. We established a habitat suitability index model for wintering cranes and generated habitat suitability assessment maps by ArcGIS. The results show that the change of landscape pattern in Shengjin Lake protected area was obvious, the number of wetland patches increased, the fragmentation degree of landscape increased, the landscape patch difference became smaller, and the diversity index and evenness index increased gradually. From 1986 to 2015, the number of wintering cranes decreased and the habitat suitability index of wintering cranes decreased from 0.845 to 0.465, and the habitat suitability of wintering cranes fell from 13,577.11 to 7424.42 ha, which showed the overall habitat deteriorated significantly and had a positive correlation between the crane population and habitat suitability.