scholarly journals Spatiotemporal Characteristics of Vegetation Net Primary Productivity on an Intensively-Used Estuarine Alluvial Island

Land ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 130
Author(s):  
Wenxiu Xing ◽  
Yuan Chi ◽  
Xuejian Ma ◽  
Dahai Liu
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Primary Productivity ◽  
Net Primary Productivity ◽  
Spatial Differentiation ◽  
Soil Surface ◽  
Limiting Factors ◽  
Vegetation Growth ◽  
Chongming Island ◽  
Development And Utilization

Net Primary Productivity (NPP) can effectively reflect the characteristics and strength of the response to external disturbances on estuarine alluvial island ecosystems, which can provide evidence for regulating human development and utilization activities and improving blue carbon capacity. However, there are a few studies on NPP of estuarine alluvial islands. We established a model based on a Carnegie–Ames–Stanford Approach (CASA) to estimate NPP on Chongming Island, a typical estuarine alluvial island, by considering the actual ecological characteristics of the island. The NPP of different land-cover types and protected areas in different years and seasons were estimated using Remote Sensing and Geographic Information System as the main tools. Correlations between NPP and Remote Sensing-based spatially heterogeneous factors were then conducted. In the last 30 years, the mean NPP of Chongming Island initially increased and then slowly decreased, while total NPP gradually increased. In 2016–2017, Chongming Island total NPP was 422.32 Gg C·a−1, and mean NPP was 287.84 g C·m−2·a−1, showing significant seasonal differences. NPP showed obvious spatial differentiation in both land-cover and protected area types, resulting from joint influences of natural and human activities. Chongming Island vegetation growth status and cover were the main factors that positively affected NPP. Soil surface humidity increased NPP, while soil salinity, surface temperature, and surface aridity were important NPP limiting factors.

Spatio-temporal variation of net primary productivity in a rapidly expanding artificial woodland area based on remote-sensing data

Erdkunde ◽  
2021 ◽  
Vol 75 (3) ◽  
pp. 191-207
Author(s):  
Qi Yi ◽  
Yuting Gao ◽  
Hongrong Du ◽  
Junxu Chen ◽  
Liang Emlyn Yang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Primary Productivity ◽  
Net Primary Productivity ◽  
Meteorological Data ◽  
Arable Land ◽  
Remote Sensing Data ◽  
Stand Age ◽  
Sensing Data ◽  
Spatio Temporal

The expansion of artificial woodlands in China has contributed significantly to regional land-cover changes and changes in the regional net primary productivity (NPP). This study used Ximeng County in the Yunnan Province as a case study to investigate the overall changes, associated amplitude, and spatio-temporal distribution of NPP from 2000–2015.The Carnegie-Ames-Stanford approach was used in the rapidly expanding artificial woodland area based on MODIS-NDVI data, meteorological data, and Landsat 5 TM data to calculate the NPP. The results show that (1) artificial woodlands experience a 10fold increase and account for 93 % of the land cover transfer, which was mainly from woodland areas. (2) The NPP was 906.2×109 gC·yr-1 in 2000 and 972.0×109 gC·yr-1 in 2015, presenting a total increase of 65.8×109 gC·yr-1 and a mean increase of 52.4 gC·m-2·yr-1 in Ximeng County. (3) The most notable NPP changes take place in the central and the western border regions, with the increasing NPP of artificial woodlands and arable land offsetting the negative effects of the decrease in woodland NPP. (4) The total NPP in the study area kept increasing, primarily due to the growing area of artificial woodlands as well as the stand age of the woods, whereas the mean value change of the NPP is mostly related to the increasing stand age. (5) The artificial woodlands increase the NPP value more than natural woodlands. While protecting and promoting ecologically valuable natural forests at the same time, it seems quite advantageous to establish regional plantations and coordinate their development on a scientific basis with a view to increasing NPP, economic development, but also the ecological stability of this mountain region. Our study reveals the changes in NPP and its distribution in a rapidly expanding area of artificial woodland in southwest China based on remote-sensing data and the CASA model, providing a decision-making basis for rational land-use management, the optimal utilization of land resources, and a county-scale assessment approach.

Assessment on 2000-2010 Ecosystem Function Changes of Yiwulvshan National Nature Scenic Area

2014 ◽  
Vol 1051 ◽  
pp. 489-494
Author(s):  
Xiao Chen Wang ◽  
Jing Hai Zhu ◽  
Yuan Man Hu ◽  
Wei Ling Liu
Keyword(s):  
Remote Sensing ◽  
Ecosystem Function ◽  
Primary Productivity ◽  
Water Conservation ◽  
Net Primary Productivity ◽  
Remote Sensing Data ◽  
Vegetation Coverage ◽  
The Past ◽  
Remote Sensing Technology ◽  
Sensing Technology

Based on the remote-sensing data and ground data, this study is conducted on the ecosystem function of Yiwulvshan National Nature Scenic Area (hereinafter as “Yiwulvshan Scenic Area”) from 2000 to 2010 with the GIS (geographic information system) and RS (remote sensing) technology, so as to provide reference for better environmental protection of the scenic area. It is shown from the results that there is no obvious change of land use in Yiwulvshan Scenic Area; while the capacity for soil and water conservation is slightly improved mainly due to increase of vegetation coverage; the vegetation net primary productivity declines somewhat about 5.27% in past 10 years; and biodiversity is slightly increased. As a whole, the ecosystem function of Yiwulvshan Scenic Area basically kept stable in the past 10 years, which indicated that the existing regulations can effectively protect the ecological function of the Scenic Area.

How does the conversion of land cover to urban use affect net primary productivity? A case study in Shenzhen city, China

2009 ◽  
Vol 149 (11) ◽  
pp. 2054-2060 ◽  
Author(s):  
Yu Deyong ◽  
Shao Hongbo ◽  
Shi Peijun ◽  
Zhu Wenquan ◽  
Pan Yaozhong
Keyword(s):  
Land Cover ◽  
Primary Productivity ◽  
Net Primary Productivity ◽  
Shenzhen City
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