Sciences in Cold and Arid Regions ›› 2020, Vol. 12 ›› Issue (1): 22-33.doi: 10.3724/SP.J.1226.2020.00022.

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A case study on Landscape Component Niche based on Landscape Pattern Indices: Yanchi, Ningxia Province, China

XiaoNing Zhang1,XueLu Liu1(),Ghanney Philip1,XiaoDan Li2,QuanXi Wang2,YaNan Xu1,TingTing Hui1   

  1. 1.College of Resources and Environmental Sciences, Gansu Agricultural University, Lanzhou, Gansu 730070, China
    2.College of Management, Gansu Agricultural University, Lanzhou, Gansu 730070, China
  • Received:2019-06-10 Accepted:2019-09-29 Online:2020-02-29 Published:2020-03-17
  • Contact: XueLu Liu E-mail:liuxl@gsau.edu.cn

Abstract:

Yanchi County is located in the agro-pastoral ecotone and belongs to the ecologically fragile area of Northwest China. It is important to study the evolution of landscape pattern to curb its environmental degradation. In order to intuitively show how the landscape pattern of the study area changes over time, Landsat Thematic Mappers (TM) and Landsat Operational Land Imager (OLI) data of 1991, 2000, 2010 and 2017 were used. This paper attempts to apply niche theories and methods into landscape ecology, and constructs a niche model of landscape components by using "n-dimentional hypervolume niche theory" and landscape pattern indices. By evaluating the spatial and temporal evolution of niche from the perspective of two-dimensional space to reflect the changes of landscape pattern in the study area over the past 26 years, new theories and methods were introduced for the characterization of landscape pattern. The results indicate that: 1) The larger the attribute and dominance value of landscape components, the higher the ecological niche and the stronger the control effect on the overall landscape. 2) The ecological niche of each landscape component was significantly different, just as its control effect on the overall landscape. 3) The dynamic change of the ecological niche of each landscape component was different, with grassland, unused land and arable land always in a high dominant position, although the ecological niche of construction land and water area was always low. In general, the introduction of niche theory into the landscape ecology provided a new method to study the changes in regional landscape pattern.

Key words: landscape pattern, landscape component niche, landscape stability, landscape dominance

Figure 1

The location of Yanchi County, Northeast China"

Figure 2

The landscape type maps of Yanchi County from 1991 to 2017"

Table 1

Landscape pattern indices and its significance"

IndexFormulaeNote and brief description of index

Stability

indices

Landscape shape index (LSI)LSI=0.25Ei/AiEi, total length of all patch boundaries; Ai, area of landscape component type i. LSI is a brief description of the aggregation of landscape component types
Edge density (ED)ED=k=1meikA×10000eik, total edge length of the landscape component type; A, total landscape area. A greater ED indicates that the higher the exchange of patches with the energy of the external matter and the more stable the interior of the patch
Fractal dimension (FRAC)FRAC=2ln0.25pijln(aij)Pij, the circumference of the patch ij; aij, the area of the patch ij. FRAC is a measure of shape complexity. The smaller the value, the simpler the pattern of patch shape and the worse the stability
Cluster index (CLUMPY)Gi=gikk=1mgik-minei????????????????????????????CLUMPY=Gi-pipiGi<pipi<0.5Gi-pi1-pigii, the number of nodes between the landscape component type i and the landscape component type i; gik, the number of nodes between the landscape component type i and the landscape component type k; minei, the minimum perimeter when the landscape component type i. is maximally brought together. CLUMPY reflects the spatial distribution of patches
Dominance indicesPatch proportion of landscape area (PLAND)PLAND=pij=j=1naijA×100aij, the area of patch ij; A, total landscape area; n, number of landscape component types. PLAND measures the area of a landscape component as a percentage of the total landscape area and is one of the basis for helping to determine the dominant landscape.
Maximum patch index (LPI)LPI=max(aij)j=1nA×100aij, A, n, the same as above. LPI is a simple measure of dominance.

Aggregation

index (AI)

AI=gijmaxgij×100gii, the number of nodes between the landscape component type i pixels; maxgii, the maximum number of nodes between landscape component types i pixels. AI represents the type of patches consisting of patches with regular shape, continuous distribution or aggregation. The larger the value, the higher the connectivity within the patches.

Patch density

(PD)

PD=NiA×10000×100A, the same as above; Ni, number of patch type i; The larger the value of PD, the more patches per unit area, the higher the heterogeneity of landscape, which indicates the integrity and fragmentation of landscape

Figure 3

Geometric indication of the ecological niche of landscape components"

Table 2

Index value of the niche of each landscape component"

TypeYearIndex value of niche factor of stabilityIndex value of niche factor of dominance
LSIEDFRAC_AMCLUMPYPLANDLPIAIPD
Arable land199174.089.041.120.9319.460.3493.950.29
200070.449.151.130.9422.080.5194.610.23
201051.804.951.140.9411.950.5394.630.32
201767.786.571.120.9312.270.3593.040.26
Forest land199124.811.471.150.964.590.7195.940.07
200025.651.141.120.942.590.1394.400.04
201043.265.141.220.9618.431.6996.400.09
201756.236.461.180.9517.280.9995.150.16
Grassland199179.6617.711.380.9464.6136.1396.430.17
200078.8316.891.370.9460.0432.5596.330.28
201063.6113.531.310.9659.1320.6897.030.28
201788.4818.211.330.9455.3815.9695.710.28
Water area199119.630.491.120.920.810.1192.400.02
200016.850.381.130.930.660.1092.810.01
201016.290.341.120.930.570.0892.560.01
201719.620.531.100.930.970.1193.050.02
Construction land199117.720.201.060.850.170.0385.190.08
200021.350.371.070.880.390.0588.020.09
201028.390.701.160.890.800.0988.740.10
201735.331.491.110.922.330.1591.770.13
Unused land199195.598.511.140.8910.360.3689.260.52
200080.938.451.180.9214.250.8192.270.38
201079.996.691.160.909.130.6990.450.40
201786.738.241.150.9011.780.3490.880.49
Weight0.3340.6010.0470.0170.3040.5020.0070.187

Table 3

The attribute value of the stability of each landscape component from 1991 to 2017"

YearArable landForest landGrasslandWater areaConstruction landUnused land
199131.509.5938.877.176.3338.66
200029.119.3336.585.937.4232.19
201020.3617.6229.465.729.9830.82
201726.6722.7540.596.9512.7734.00

Table 4

The attribute value of dominance of each landscape component from 1991 to 2017"

YearArable landForest landGrasslandWater areaConstruction landUnused land
19916.842.4838.510.990.724.09
20007.711.5635.340.940.815.49
20104.667.1829.110.900.963.87
20174.646.4825.591.041.494.52

Figure 4

Scattered distribution of landscape niche of each landscape component for Yanchi County from 1991 to 2017. (a, Arable land; b, Forest land; c, Grassland; d, Water area; e, Construction land; f, Unused land; , Landscape component niche in 1991;▲, Landscape component niche in 2000; ?, Landscape component niche in 2010; , Landscape component niche in 2017 )"

Figure 5

Ecological niche change map of each landscape component in different years"

Figure 6

Ecological niche of each landscape component"

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[1] HuaLi Tong, PeiJi Shi, XueBin Zhang, ZaiYan Li. Characterization of landscape pattern based on land economic niche change: A case study in Ganzhou, Gansu Province, China [J]. Sciences in Cold and Arid Regions, 2018, 10(3): 261-270.
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