2. Ship Island, the Pearl River, and Lake Pontchartrain

2006 ◽  
pp. 56-62
Keyword(s):  
Pearl River ◽  
Lake Pontchartrain ◽  
The Pearl River

EVOLUTION OF SEDIMENTARY FACIES AND PALEOENVIRONMENT DURING THE LATE QUATERNARY IN WANQINGSHA AREA OF THE PEARL RIVER DELTA

2010 ◽  
Vol 29 (6) ◽  
pp. 35-42
Author(s):  
Jianhua WANG ◽  
Linglong CAO ◽  
Xiaojing WANG ◽  
Xiaoqiang YANG ◽  
Jie YANG ◽  
...  
Keyword(s):  
Pearl River Delta ◽  
Late Quaternary ◽  
Sedimentary Facies ◽  
River Delta ◽  
Pearl River ◽  
The Pearl River Delta ◽  
The Pearl River

Effects of climate change and fishing on the Pearl River Estuary ecosystem and fisheries

2019 ◽  
Vol 29 (4) ◽  
pp. 861-875
Author(s):  
Zeyu Zeng ◽  
William W. L. Cheung ◽  
Shiyu Li ◽  
Jiatang Hu ◽  
Ying Wang
Keyword(s):  
Climate Change ◽  
River Estuary ◽  
Pearl River Estuary ◽  
Pearl River ◽  
The Pearl River Estuary ◽  
The Pearl River

scholarly journals The Role of Environmental Factors on the Fishery Catch of the Squid Uroteuthis chinensis in the Pearl River Estuary, China

2021 ◽  
Vol 9 (2) ◽  
pp. 131
Author(s):  
Dongliang Wang ◽  
Lijun Yao ◽  
Jing Yu ◽  
Pimao Chen
Keyword(s):  
River Estuary ◽  
Pearl River Estuary ◽  
Sea Surface ◽  
Spatiotemporal Variability ◽  
Pearl River ◽  
Coastal Current ◽  
Catch Per Unit Effort ◽  
Chl A ◽  
The Pearl River Estuary ◽  
The Pearl River

The Pearl River Estuary (PRE) is one of the major fishing grounds for the squid Uroteuthis chinensis. Taking that into consideration, this study analyzes the environmental effects on the spatiotemporal variability of U. chinensis in the PRE, on the basis of the Generalized Additive Model (GAM) and Clustering Fishing Tactics (CFT), using satellite and in situ observations. Results show that 63.1% of the total variation in U. chinensis Catch Per Unit Effort (CPUE) in the PRE could be explained by looking into outside factors. The most important one was the interaction of sea surface temperature (SST) and month, with a contribution of 26.7%, followed by the interaction effect of depth and month, fishermen’s fishing tactics, sea surface salinity (SSS), chlorophyll a concentration (Chl a), and year, with contributions of 12.8%, 8.5%, 7.7%, 4.0%, and 3.1%, respectively. In summary, U. chinensis in the PRE was mainly distributed over areas with an SST of 22–29 °C, SSS of 32.5–34‰, Chl a of 0–0.3 mg × m−3, and water depth of 40–140 m. The distribution of U. chinensis in the PRE was affected by the western Guangdong coastal current, distribution of marine primary productivity, and variation of habitat conditions. Lower stock of U. chinensis in the PRE was connected with La Niña in 2008.

scholarly journals Spatial-Temporal Evolution and Relationship between Urbanization Level and Ecosystem Service from a Dual-Scale Perspective: A Case Study of the Pearl River Delta Urban Agglomeration

2021 ◽  
Vol 13 (15) ◽  
pp. 8537
Author(s):  
Yuanyuan Mao ◽  
Lingli Hou ◽  
Zhengdong Zhang
Keyword(s):  
Ecosystem Service ◽  
Pearl River Delta ◽  
Temporal Evolution ◽  
Pearl River ◽  
Ecosystem Service Value ◽  
Urbanization Level ◽  
Service Value ◽  
The Pearl River Delta ◽  
The Pearl River ◽  
Dual Scale

Since the beginning of the 21st century, urbanization has brought about dramatic changes in population, life, and economy, while having a significant impact on the distribution of ecosystem service. As research on the relationship between urbanization and ecosystem service has gradually specified, we decided to explore it at different scales. In this paper, we quantified and mapped the spatial–temporal evolution and relationship between urbanization and ecosystem service value in the Pearl River Delta Urban Agglomeration from 2000 to 2019 based on a dual-scale perspective of county and 3 km × 3 km raster. Our results show that the overall trend of urbanization level and ecosystem service value was increasing. Urbanization and ecosystem service value at the county scale showed a negative spatial correlation, while it was not significant at the raster scale. The “high–high” agglomeration was more concentrated, while the other three “low–low”, “low–high” and “high–low” agglomerations were more dispersed. Our findings suggest it is crucial to identify the key factors of small urban areas to grasp the development mechanism in the urbanization process and maintain the balance of the ecosystem.

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