The range expansion patterns of Spartina alterniflora on salt marshes in the Yangtze Estuary, China

2010 ◽  
Vol 88 (1) ◽  
pp. 99-104 ◽  
Author(s):  
Derong Xiao ◽  
Liquan Zhang ◽  
Zhenchang Zhu
Keyword(s):  
Spartina Alterniflora ◽  
Range Expansion ◽  
Salt Marshes ◽  
Yangtze Estuary ◽  
The Yangtze Estuary

scholarly journals The Effect of Artificial Mowing on the Competition of Phragmites australis and Spartina alterniflora in the Yangtze Estuary

Scientifica ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Yue Yuan ◽  
Chao Zhang ◽  
Dezhi Li
Keyword(s):  
Spartina Alterniflora ◽  
Phragmites Australis ◽  
Native Species ◽  
Interspecific Interactions ◽  
Interaction Strength ◽  
Yangtze Estuary ◽  
The Yangtze Estuary ◽  
Neighbor Effect ◽  
Index Effect

Spartina alterniflora Loisel. is one of the most invasive species in the world. However, little is known about the role of artificial mowing in its invasiveness and competiveness. In this work, we studied the effect of mowing on its interspecific interactions with native species Phragmites australis (Cav.) Trin ex Steud of the Yangtze Estuary, China. We calculated their relative neighbor effect (RNE) index, effect of relative crowding (Dr) index, and interaction strength (I) index. The results showed that the RNE of Phragmites australis and Spartina alterniflora was 0.354 and 0.619, respectively, and they have competitive interactions. The mowing treatments can significantly influence the RNE of Phragmites australis and Spartina alterniflora on each other. Concretely, the RNE of Spartina alterniflora in the removal treatments was significantly higher than the value in the controls. But the RNE of Phragmites australis in the removal treatments was significantly lower than the value in the controls. Meanwhile, Dr of the two species on the targets was higher in the removal treatments than that in the controls, and the opposite was for I. We concluded that artificial mowing could promote the invasion of Spartina alterniflora by increasing its competitive performance compared with native species.

The impact of the change in vegetation structure on the ecological functions of salt marshes: the example of the Yangtze estuary

2013 ◽  
Vol 14 (2) ◽  
pp. 623-632 ◽  
Author(s):  
Xiuzhen Li ◽  
Linjing Ren ◽  
Yu Liu ◽  
Christopher Craft ◽  
Ülo Mander ◽  
...  
Keyword(s):  
Salt Marshes ◽  
Vegetation Structure ◽  
Yangtze Estuary ◽  
Ecological Functions ◽  
The Yangtze Estuary ◽  
The Impact

Seed dispersal capacity and post-dispersal fate of the invasive Spartina alterniflora in saltmarshes of the Yangtze Estuary

2016 ◽  
Vol 169 ◽  
pp. 158-163 ◽  
Author(s):  
Derong Xiao ◽  
Chao Zhang ◽  
Liquan Zhang ◽  
Zhenchang Zhu ◽  
Kun Tian ◽  
...  
Keyword(s):  
Seed Dispersal ◽  
Spartina Alterniflora ◽  
Yangtze Estuary ◽  
The Yangtze Estuary ◽  
Dispersal Capacity

scholarly journals Simulating the Range Expansion ofSpartina alterniflorain Ecological Engineering through Constrained Cellular Automata Model and GIS

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Zongsheng Zheng ◽  
Bo Tian ◽  
L. W. Zhang ◽  
Guoliang Zou
Keyword(s):  
Environmental Factors ◽  
Spartina Alterniflora ◽  
Range Expansion ◽  
Salt Marshes ◽  
Ecological Engineering ◽  
Vegetation Density ◽  
Tidal Elevation ◽  
Remote Sensing Classification ◽  
Ca Model ◽  
Neighbor Effect

Environmental factors play an important role in the range expansion ofSpartina alterniflorain estuarine salt marshes. CA models focusing on neighbor effect often failed to account for the influence of environmental factors. This paper proposed a CCA model that enhanced CA model by integrating constrain factors of tidal elevation, vegetation density, vegetation classification, and tidal channels in Chongming Dongtan wetland, China. Meanwhile, a positive feedback loop between vegetation and sedimentation was also considered in CCA model through altering the tidal accretion rate in different vegetation communities. After being validated and calibrated, the CCA model is more accurate than the CA model only taking account of neighbor effect. By overlaying remote sensing classification and the simulation results, the average accuracy increases to 80.75% comparing with the previous CA model. Through the scenarios simulation, the future ofSpartina alternifloraexpansion was analyzed. CCA model provides a new technical idea and method for salt marsh species expansion and control strategies research.

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