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

doi:10.3724/SP.J.1226.2020.00022.

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

• • 上一篇

收稿日期:2019-06-10 接受日期:2019-09-29 出版日期:2020-02-29 发布日期:2020-03-17

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.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

摘要/Abstract

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

. [J]. Sciences in Cold and Arid Regions, 2020, 12(1): 22–33.

XiaoNing Zhang,XueLu Liu,Ghanney Philip,XiaoDan Li,QuanXi Wang,YaNan Xu,TingTing Hui. A case study on Landscape Component Niche based on Landscape Pattern Indices: Yanchi, Ningxia Province, China[J]. Sciences in Cold and Arid Regions, 2020, 12(1): 22–33.

图/表 10

	Index	Formulae	Note and brief description of index
Stability indices	Landscape shape index (LSI)	$L S I = 0.25 E i / A i$	E_i, total length of all patch boundaries; A_i, area of landscape component type i. LSI is a brief description of the aggregation of landscape component types
	Edge density (ED)	$E D = ∑ k = 1 m e i k A × 10000$	e_ik, 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)	$F R A C = 2 l n 0.25 p i j l n (a i j)$	P_ij, the circumference of the patch ij; a_ij, 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）	$G i = g i k ∑ k = 1 m g i k - m i n e i ???????????????????????????? C L U M P Y = G i - p i p i G i < p i 且 p i < 0.5 G i - p i 1 - p i$	g_ii, the number of nodes between the landscape component type i and the landscape component type i; g_ik, the number of nodes between the landscape component type i and the landscape component type k; mine_i, the minimum perimeter when the landscape component type i. is maximally brought together. CLUMPY reflects the spatial distribution of patches
Dominance indices	Patch proportion of landscape area (PLAND)	$P L A N D = p i j = ∑ j = 1 n a i j A × 100$	a_ij, 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)	$L P I = m a x (a i j) j = 1 n A × 100$	a_ij, A, n, the same as above. LPI is a simple measure of dominance.
	Aggregation index (AI)	$A I = g i j m a x g i j × 100$	g_ii, the number of nodes between the landscape component type i pixels; maxg_ii, 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)	$P D = N i A × 10000 × 100$	A, the same as above; N_i, 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

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Type	Year	Index value of niche factor of stability				Index value of niche factor of dominance
Type	Year	LSI	ED	FRAC_AM	CLUMPY	PLAND	LPI	AI	PD
Arable land	1991	74.08	9.04	1.12	0.93	19.46	0.34	93.95	0.29
	2000	70.44	9.15	1.13	0.94	22.08	0.51	94.61	0.23
	2010	51.80	4.95	1.14	0.94	11.95	0.53	94.63	0.32
	2017	67.78	6.57	1.12	0.93	12.27	0.35	93.04	0.26
Forest land	1991	24.81	1.47	1.15	0.96	4.59	0.71	95.94	0.07
	2000	25.65	1.14	1.12	0.94	2.59	0.13	94.40	0.04
	2010	43.26	5.14	1.22	0.96	18.43	1.69	96.40	0.09
	2017	56.23	6.46	1.18	0.95	17.28	0.99	95.15	0.16
Grassland	1991	79.66	17.71	1.38	0.94	64.61	36.13	96.43	0.17
	2000	78.83	16.89	1.37	0.94	60.04	32.55	96.33	0.28
	2010	63.61	13.53	1.31	0.96	59.13	20.68	97.03	0.28
	2017	88.48	18.21	1.33	0.94	55.38	15.96	95.71	0.28
Water area	1991	19.63	0.49	1.12	0.92	0.81	0.11	92.40	0.02
	2000	16.85	0.38	1.13	0.93	0.66	0.10	92.81	0.01
	2010	16.29	0.34	1.12	0.93	0.57	0.08	92.56	0.01
	2017	19.62	0.53	1.10	0.93	0.97	0.11	93.05	0.02
Construction land	1991	17.72	0.20	1.06	0.85	0.17	0.03	85.19	0.08
	2000	21.35	0.37	1.07	0.88	0.39	0.05	88.02	0.09
	2010	28.39	0.70	1.16	0.89	0.80	0.09	88.74	0.10
	2017	35.33	1.49	1.11	0.92	2.33	0.15	91.77	0.13
Unused land	1991	95.59	8.51	1.14	0.89	10.36	0.36	89.26	0.52
	2000	80.93	8.45	1.18	0.92	14.25	0.81	92.27	0.38
	2010	79.99	6.69	1.16	0.90	9.13	0.69	90.45	0.40
	2017	86.73	8.24	1.15	0.90	11.78	0.34	90.88	0.49
Weight		0.334	0.601	0.047	0.017	0.304	0.502	0.007	0.187

Year	Arable land	Forest land	Grassland	Water area	Construction land	Unused land
1991	31.50	9.59	38.87	7.17	6.33	38.66
2000	29.11	9.33	36.58	5.93	7.42	32.19
2010	20.36	17.62	29.46	5.72	9.98	30.82
2017	26.67	22.75	40.59	6.95	12.77	34.00

Year	Arable land	Forest land	Grassland	Water area	Construction land	Unused land
1991	6.84	2.48	38.51	0.99	0.72	4.09
2000	7.71	1.56	35.34	0.94	0.81	5.49
2010	4.66	7.18	29.11	0.90	0.96	3.87
2017	4.64	6.48	25.59	1.04	1.49	4.52

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

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