Systematic assessments of tidal wetlands loss and degradation in Shanghai, China: From the perspectives of area, composition and quality

Shu, Lin; Li, Xiuzhen; Yang, Bin; Ma, Yuxi; Jiang, Can; Xue, Liming; Wang, Jiangjing; Yan, Zhongzheng

doi:10.1016/j.gecco.2020.e01450

Cited by 11 publications

(4 citation statements)

References 48 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For these reasons, relevant regulations should be formulated to strictly control reclamation projects and waste discharge. Also, the government should invest financial funds and human resources to strengthen ecological restoration and monitoring, allowing natural habitats to perform their roles to the fullest [130].…”

Section: Intervention Suggestions 421 Maintenance and Development Of ...mentioning

confidence: 99%

Assessing Coastal Vulnerability and Evaluating the Effectiveness of Natural Habitats in Enhancing Coastal Resilience: A Case Study in Shanghai, China

Lin,

Singh

2024

Sustainability

View full text Add to dashboard Cite

This research evaluates the coastal vulnerability of Shanghai, evaluates the effectiveness of existing natural habitats in reducing that vulnerability, and, finally, provides recommendations to improve the resilience of the coastal areas. Shanghai is an important economic center that is home to a large population. However, the combination of ground subsidence, rising sea levels, and more frequent coastal flooding due to tropical cyclones poses escalating climate risks for Shanghai, demanding urgent mitigation measures. The InVEST Coastal Vulnerability Model was used in this study to assess Shanghai’s coastal vulnerability under the current situation and various scenarios that simulated the absence of natural habitats. The assessment results were analyzed through a comparison between different scenarios and spatial aggregation analysis. This study pinpointed highly vulnerable areas, primarily located on the east coast of Chongming Island, the east and northeast coasts of Hengsha Island, and the east coast of the mainland of Shanghai. These areas need to be prioritized for intervention. Also, it demonstrated the effectiveness of existing natural habitats in reducing coastal vulnerability, with large green spaces and salt marshes playing a greater role compared to small green spaces. This is the first study applying the InVEST Coastal Vulnerability Model to Shanghai, demonstrating the model’s potential in providing valuable information regarding coastal protection against the impacts of climate change in Shanghai. Insights from the findings of this study are useful in crafting sustainable land-use policies and plans for Shanghai.

show abstract

Section: Intervention Suggestions 421 Maintenance and Development Of ...mentioning

confidence: 99%

Assessing Coastal Vulnerability and Evaluating the Effectiveness of Natural Habitats in Enhancing Coastal Resilience: A Case Study in Shanghai, China

Lin,

Singh

2024

Sustainability

View full text Add to dashboard Cite

show abstract

“…Previous studies often focused on the influence of one kind of driving process in the study area, such as reclamation [13,22,26], and often ignored the influence of multiple coupled natural and human driving processes. In this study, we found that CBCS increased from 1990 to 2015, though the coastal carbon sequestration continuously decreased, due to the interactions between the natural driving processes (e.g., accretion) and human-driven processes (e.g., reclamation).…”

Section: Spatiotemporal Change and Driving Processes Of Cbcsmentioning

confidence: 99%

Spatiotemporal Change and the Natural–Human Driving Processes of a Megacity’s Coastal Blue Carbon Storage

Cai

Zhu

Chen

et al. 2021

IJERPH

View full text Add to dashboard Cite

Coastal blue carbon storage (CBCS) plays a key role in addressing global climate change and realizing regional carbon neutrality. Although blue carbon has been studied for some years, there is little understanding of the influence of a megacity’s complex natural and human-driven processes on CBCS. Taking the Shanghai coastal area as an example, this study investigated the spatiotemporal change in CBCS using the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) model during 1990–2015, and analyzed the response of the CBCS to a megacity’s complex natural- and human-driven processes through a land use/land cover transition matrix and hierarchical clustering. The results were as follows: (1) Thirty-three driving processes were identified in the study area, including four natural processes (e.g., accretion, succession, erosion, etc.), two human processes (reclamation and restoration) and twenty-seven natural–human coupled processes; they were further combined into single and multiple processes with positive and negative influences on the CBCS into four types (Mono+, Mono−, Multiple+ and Multiple− driving processes). (2) Shanghai’s CBCS increased from 1659.44 × 104 Mg to 1789.78 ×104 Mg, though the amount of Shanghai’s coastal carbon sequestration showed a decreasing trend in three periods: 51.28 × 104 Mg in 1990–2000, 42.90 × 104 Mg in 2000–2009 and 36.15 × 104 Mg in 2009–2015, respectively. (3) There were three kinds of spatiotemporal patterns in the CBCS of this study area: high adjacent to the territorial land, low adjacent to the offshore waters in 1990; high in the central part, low in the peripheral areas in 2009 and 2015; and a mixed pattern in 2000. These patterns resulted from the different driving processes present in the different years. This study could serve as a blueprint for restoring and maintaining the CBCS of a megacity, to help mitigate the conflicts between socioeconomic development and the conservation of the CBCS, especially in the Shanghai coastal area.

show abstract

“…Multiband, multispectral, and high-resolution remote sensing technology and GIS have been widely used in monitoring wetland dynamics and to research the patterns and causes of wetland degradation (Held et al, 2003;Lhermitte et al, 2011;Houborg et al, 2015;Zhu et al, 2022). Some scholars have extracted the Land-Use/Land-Cover (LULC) databases based on remote sensing data and constructed remote sensing models to quantitatively and qualitatively explore and evaluate the spatial and temporal patterns of regional wetland shrinkage and degradation (Jiang et al, 2017;Lin et al, 2021;Cui et al, 2022). Cui et al (2015) established a comprehensive model of wetland ecological degradation based on regional habitat succession and, combined with remote sensing images, proved that human disturbance and species invasion were the main causes of coastal wetland degradation in Jiangsu Province, China.…”

Section: Introductionmentioning

confidence: 99%

Remote sensing and environmental assessment of wetland ecological degradation in the Small Sanjiang Plain, Northeast China

Sun

Mao

et al. 2023

Front. Ecol. Evol.

View full text Add to dashboard Cite

IntroductionThe plain marsh wetland ecosystems are sensitive to changes in the natural environment and the intensity of human activities. The Sanjiang Plain is China’s largest area of concentrated marsh wetland, the Small Sanjiang Plain is the most important component of the Sanjiang Plain. However, with the acceleration of the urbanization and development of large-scale agricultural reclamation activities in the Small Sanjiang Plain in Northeast China, the wetland has been seriously damaged. In light of this degradation this study examines the Small Sanjiang Plain.MethodsFrom the four aspects of area, structure, function, and human activities, we try to construct a wetland degradation comprehensive index (WDCI) in cold region with expert scoring methods and analytic hierarchy process (AHP), coupled with network and administrative unit. The objective was to reveal the degradation of wetlands in Northeast China over three decades at a regional scale.ResultsThe results showed that (1) the overall wetland area decreased between 1990 and 2020 by 39.26×103 hm2. Within this period a significant decrease of 336.56×103 hm2 occurred between 1990 and 200 and a significant increase of 214.62×103 hm2 occurred between 2010 and 2020. (2) In terms of structural changes, the fractal dimension (FRAC) has the same trend as the Landscape Fragmentation Index (LFI) with little change. (3) In terms of functional changes, the average above-ground biomass (AGB) increased from 1029.73 kg/hm2 to 1405.38 kg/hm2 between 1990 and 2020 in the study area. (4) In terms of human activities, the average human disturbance was 0.52, 0.46, 0.57 and 0.53 in 1990, 2000, 2010 and 2020, with the highest in 2010. (5) The composite wetland degradation index shows that the most severe wetland degradation was 49.61% in 2010 occurred between 1990 and 2020. (6) Among the severely deteriorated trajectory types in 2010–2020, mild degradation → serious degradation accounted for the largest area of 240.23×103 hm2, and the significant improvement trajectory type in 1990–2000 accounted for the largest area of 238.50×103 hm2.DiscussionIn brief, we conclude that the degradation of the Small Sanjiang Plain wetland was caused mainly by construction, overgrazing, deforestation, and farmland reclamation. This study can also provide new views for monitoring and managing wetland degradation by remote sensing in cold regions.

show abstract

Systematic assessments of tidal wetlands loss and degradation in Shanghai, China: From the perspectives of area, composition and quality

Cited by 11 publications

References 48 publications

Assessing Coastal Vulnerability and Evaluating the Effectiveness of Natural Habitats in Enhancing Coastal Resilience: A Case Study in Shanghai, China

Assessing Coastal Vulnerability and Evaluating the Effectiveness of Natural Habitats in Enhancing Coastal Resilience: A Case Study in Shanghai, China

Spatiotemporal Change and the Natural–Human Driving Processes of a Megacity’s Coastal Blue Carbon Storage

Remote sensing and environmental assessment of wetland ecological degradation in the Small Sanjiang Plain, Northeast China

Contact Info

Product

Resources

About