Yahe Wang
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Yahe Wang has a total of 6 co-authors. Here are the top co-authors by number of shared publications:
- Jun Song
Operational Oceanography Institute (OOI), Dalian Ocean University, Dalian 116023, China
1 shared publication - Jun Yang
College of Marine Science and Environment, Dalian Ocean University, Dalian 116023, China
1 shared publication - Junru Guo
Operational Oceanography Institution (OOI), Dalian Ocean University, Dalian 116023, China
1 shared publication - Wei Hu
Operational Oceanography Institution (OOI), Dalian Ocean University, Dalian 116023, China
1 shared publication - Yanzhao Fu
School of Marine Science and Environment Engineering, Dalian Ocean University, Dalian 116023, China
1 shared publication - Yanzhen Song
Operational Oceanography Institution (OOI), Dalian Ocean University, Dalian 116023, China
1 shared publication
Latest Publications
- Open Access
- 19 May 2025
- Published by MDPI AG in Sustainability
- Vol. 17 (10) , 4645
Suitability Evaluation of the Water Environment for Seagrass Growth Areas in the Changshan Archipelago
Seagrass beds provide essential ecosystem services, such as habitat for marine life, water quality purification, carbon sequestration, and climate regulation. For the Changshan Archipelago, which relies heavily on marine resources, the growth and development of seagrass beds are key factors affecting aquaculture. This study is based on data collected from a survey conducted in the nearshore waters of the Changshan Archipelago in August 2022, encompassing seagrass distribution and water sample data. The water samples were analyzed for various parameters, including salinity, suspended solids, pH, dissolved oxygen, sea temperature, nitrite-nitrogen, nitrate-nitrogen, and ammonia-nitrogen concentrations. A habitat suitability assessment of the seagrass beds in the Changshan Archipelago was conducted. The study calculated the suitability index for each environmental variable based on the abundance index, and then established a Habitat Suitability Index model using a weighted allocation method. The results indicate that the seagrass bed area in the study region is primarily composed of excellent and suitable habitats. The concentration of inorganic nutrients is a key factor influencing seagrass growth. The HSI model not only identifies the hierarchical distribution of habitats in seagrass areas, but also detects potential suitable habitats for seagrass. This provides scientific reference for future seagrass bed resource protection and artificial cultivation efforts.
- 19 May 2025
- Published by MDPI AG in Sustainability
- Vol. 17 (10) , 4645
Open AccessSuitability Evaluation of the Water Environment for Seagrass Growth Areas in the Changshan Archipelago
Seagrass beds provide essential ecosystem services, such as habitat for marine life, water quality purification, carbon sequestration, and climate regulation. For the Changshan Archipelago, which relies heavily on marine resources, the growth and development of seagrass beds are key factors affecting aquaculture. This study is based on data collected from a survey conducted in the nearshore waters of the Changshan Archipelago in August 2022, encompassing seagrass distribution and water sample data. The water samples were analyzed for various parameters, including salinity, suspended solids, pH, dissolved oxygen, sea temperature, nitrite-nitrogen, nitrate-nitrogen, and ammonia-nitrogen concentrations. A habitat suitability assessment of the seagrass beds in the Changshan Archipelago was conducted. The study calculated the suitability index for each environmental variable based on the abundance index, and then established a Habitat Suitability Index model using a weighted allocation method. The results indicate that the seagrass bed area in the study region is primarily composed of excellent and suitable habitats. The concentration of inorganic nutrients is a key factor influencing seagrass growth. The HSI model not only identifies the hierarchical distribution of habitats in seagrass areas, but also detects potential suitable habitats for seagrass. This provides scientific reference for future seagrass bed resource protection and artificial cultivation efforts.