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Frontiers of Earth Science

ISSN 2095-0195

ISSN 2095-0209(Online)

CN 11-5982/P

邮发代号 80-963

2019 Impact Factor: 1.62

Frontiers of Earth Science  2012, Vol. 6 Issue (3): 237-249   https://doi.org/10.1007/s11707-012-0312-4
  RESEARCH ARTICLE 本期目录
Changes of wetland landscape patterns in Dadu River catchment from 1985 to 2000, China
Changes of wetland landscape patterns in Dadu River catchment from 1985 to 2000, China
Laibin HUANG1, Junhong BAI1(), Denghua YAN2, Bin CHEN1, Rong XIAO1, Haifeng GAO1
1. State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China; 2. China Institute of Water Resources and Hydropower Research, Beijing 100044, China
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Abstract

Based on the interpretation and vector processing of remote sensing images in 1985 and 2000, the spatial changes of wetland landscape patterns in Dadu River catchment in the last two decades were studied using spatial analysis method. Supported by Apack software, the indices of wetland landscape pattern were calculated, and the information entropy (IE) was also introduced to show the changes of wetland landscape information. Results showed that wetland landscape in this region was characteristic of patch-corridor-matrix configuration and dominantly consisted of natural wetlands. Landscape patterns changed a little with low fragment and showed concentrated distribution with partial scattered distribution during the period from 1985 to 2000. The values of patch density and convergence index kept stable, and the values of diversity, evenness indices and IE showed a slight decrease, while dominance and fractal dimension indices were increased. All types of wetland landscapes had higher adjacency probabilities with grassland landscape in 1985 and 2000, and there was extremely weak hydrological link and large spatial gap among river, glacier, reservoir and pond wetlands due to low adjacency matrix values. Since their cumulative contribution exceeded 81% through the PCA analysis, the agriculture activities would be the main driving force to the landscape changes during the past 15 years.

Key wordswetland landscape    spatial pattern    landscape indices    wetland management    Dadu River catchment
收稿日期: 2011-08-01      出版日期: 2012-09-05
Corresponding Author(s): BAI Junhong,Email:junhongbai@163.com   
 引用本文:   
. Changes of wetland landscape patterns in Dadu River catchment from 1985 to 2000, China[J]. Frontiers of Earth Science, 2012, 6(3): 237-249.
Laibin HUANG, Junhong BAI, Denghua YAN, Bin CHEN, Rong XIAO, Haifeng GAO. Changes of wetland landscape patterns in Dadu River catchment from 1985 to 2000, China. Front Earth Sci, 2012, 6(3): 237-249.
 链接本文:  
https://academic.hep.com.cn/fesci/CN/10.1007/s11707-012-0312-4
https://academic.hep.com.cn/fesci/CN/Y2012/V6/I3/237
LandscapeFirst-order classificationSecond-order classificationThird-order classification
Local landscapeWetlandNatural wetlandRiver wetland
Lake wetland
Marsh wetland
Glacier wetland
Constructed wetlandReservoir and pond wetland
Non-wetlandWoodlands-
Grasslands-
Dry land-
Human habitat-
Other lands-
Tab.1  
Fig.1  
Fig.2  
Landscape typesSub-landscape typesAreas/hm2PTA*19852000
1985200019852000N*AAP*MAP*N*AAP*MAP*
Natural landscapeRiver wetland1880.162036.112.2212.3512156.68841.2913156.62841.29
Lake wetland1110.471022.357.226.208812.62155.978412.17155.97
Marsh wetland11475.6212503.5974.5975.8793123.391410.2291137.401410.22
Glacier wetland408.51408.512.662.482204.26360.682204.26360.68
Sub-total14874.7615970.5596.6896.9019576.281410.2219084.061410.22
Constructed landscapeReservoir and pond wetland510.12510.123.323.103215.94118.743215.941187.38
Total15384.8816480.67100.00100.00227222
Tab.2  
YearDiversity (H)Dominance (D)Evenness (E)Patch density (PD)Convergence (RC)Fractal dimension (FD)IE
19850.8570.7530.5320.0140.9941.4262.08
20000.8430.7660.5240.0140.9941.4282.06
Tab.3  
TypesLakeRiverMarshGlacierReservoirand pondWoodlandGrasslandHuman habitatDry landOther landscapes
Lake60.4600.33008.3827.050.213.220.35
River080.450001.8217.73000
Marsh0.06083.29001.2913.880.050.281.15
Glacier00092.63007.37000
Reservoir and pond000078.801.4619.74000
Woodland0.0100.010090.309.3400.250.08
Grassland0.020.010.06004.4495.030.010.160.26
HumanHabitat0.4200001.9512.4877.187.920.05
Dry land0.1500.07006.738.940.3583.760.01
Other landscapes0.0100.13000.996.9300.0191.93
Tab.4  
LakeRiverMarshGlacierReservoir and pondWoodlandGrasslandHumanhabitatDry landOther landscapes
Lake61.3100.29008.8625.320.193.710.31
River080.030001.4918.48000
Marsh0.06083.68001.1913.810.050.260.95
Glacier00092.63007.37000
Reservoir and pond000078.801.4619.74000
Woodland0.0200.010090.439.2200.250.06
Grassland0.020.010.07004.3795.120.010.150.25
Human habitat0.2100.28001.9912.5077.267.710.05
Dry land0.1900.07006.878.840.3683.650.01
Other landscapes0.0100.14000.887.9200.0191.04
Tab.5  
Fig.3  
LandscapeLake wetlandRiver wetlandMarsh wetlandGlacier wetlandReservoir and pond wetland
Lake wetland1022.350.000.000.000.00
River wetland0.001880.160.000.000.00
Marsh wetland0.000.0011475.620.000.00
Glacier wetland0.000.000.00408.510.00
Reservoir and pond wetland0.000.000.000.00510.12
Tab.6  
Landscape conversionWetland → wetlandWetland → non-wetlandNon-wetland → wetlandIncreased area
Changes in area/hm215296.7588.161183.911095.79
Area/total wetland area in 198599.43%0.57%7.70%7.12%
Area/total wetland area in 200092.82%0.54%7.18%6.65%
Tab.7  
Landscape typesSub-landscape typesAreas/hm2N*piAjqiAj
19852000198520001985200019852000
Natural landscapeRiver wetland1880.162036.1121312.22%12.35%5.29%5.86%
Lake wetland1110.471022.3588847.22%6.20%38.77%37.84%
Marsh wetland11475.6212503.59939174.59%75.87%40.97%40.99%
Glacier wetland408.51408.51222.66%2.48%0.88%0.90%
Constructed landscapeReservoir and pond wetland510.12510.1232323.32%3.10%14.10%14.41%
Tab.8  
Fig.4  
YearSocio-economic factorsNatural factors
TP/104AP/104AP:TP/%FOP/109 CNYAHP/109 CNYFIP/109 CNYNLS/104ACL/104hm2AI/104hm2GDP/104CNYAMP/mmAMT/°C
1989862.2734.885.20%2.7318.910.97225.96874.4490.17655065872.510.49
1990868.9744.385.70%3.0720.761.08237.8579.66479.954308551088.111.24
1992879.3746.984.90%3.4625.351.3235.44573.88309.15885835911.2710.62
1994892.4738.382.70%4.3742.031.96242.71570.67324.2211750084311.55
1996901748.982.10%5.2154.052.9256.46403328.32820800895.1710.83
1998901.3750.782.50%5.8132.020.92254.13400.02143.512486458990.3312.11
1999918.8757.782.50%6.5333.171.06260.12399.2143.3315801001043.9711.82
Tab.9  
ComponentInitial eigenvaluesExtraction sums of squared loadingsRotation sums of squared loadings
Total% of varianceCumulative/%Total% of varianceCumulative/%Total% of varianceCumulative/%
17.11559.29659.2967.11559.29659.2966.63255.26555.265
22.60621.71381.0092.60621.71381.0092.75222.93478.199
31.50612.54793.5561.50612.54793.5561.84315.35893.556
40.6015.00798.564
50.1451.21199.774
60.0270.226100.000
74.229E–163.524E–15100.000
82.520E–162.100E–15100.000
91.147E–169.557E–16100.000
10-1.292E–17-1.077E–16100.000
11-4.185E–17-3.488E–16100.000
12-1.397E–16-1.164E–15100.000
Tab.10  
PC1PC2PC3
TP(x1)0.9720.187-0.034
AP(x2)-0.9600.0400.206
AP/TP(x3)0.9470.275-0.064
AHP(x4)0.9120.3400.193
FOP(x5)0.868-0.0680.239
FIP (x6)-0.856-0.312-0.328
NLS (x7)0.793-0.1750.232
ACL (x8)-0.778-0.5530.198
AI (x9)-0.0200.9910.018
GDP(x10)0.4220.905-0.041
AMP(x11)-0.0540.1040.974
AMT(x12)0.368-0.4230.742
Tab.11  
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