Spatio-temporal Pattern of Multifunction Tradeoffs and Synergies of the Rural Landscape: Evidence from Qingpu District in Shanghai

doi:10.5814/j.issn.1674-764x.2021.02.009

Abstract

Abstract:

The configuration of a multifunctional rural landscape is critical for its protection. Although studies on multifunctional rural landscapes have been conducted, there is a lack of information regarding the spatiotemporal characteristics and tradeoff/synergy relationships of rural landscape functions in the time series on the administrative unit scale. The purposes of this study were to (1) analyze the spatial-temporal distribution characteristics of the tradeoff and synergy from the perspective of multifunctionality for efficient use of rural landscape resources and (2) formulate regional sustainable development policies to minimize the conflict between people and nature. Aiming at the scientific representation of landscape function and the quantification of landscape multifunctional relationships, and by taking Qingpu District of Shanghai as an example, six kinds of rural landscape functions were constructed according to the functional framework of “productive function, living function and ecological function”. Based on the data for 1980 to 2018, the characteristics of variations of multifunctional tradeoff and synergy relationships of the rural landscape in 184 administrative villages were studied by the methods of Spearman rank correlation coefficient analysis and bivariate spatial autocorrelation. The following results were obtained. 1) The fine division of rural landscape function types was realistic and necessary for analyzing the regional multi-function relationships in the regions with rapid development. In the process of rapid urbanization, the rural landscape functions of urban suburban areas changed under the combined action of natural resource endowment, social and economic conditions and other internal and external factors. As a result, the agricultural production function could not replace the economic development function and become the function of rural landscape production. The research results of Qingpu District showed that the agricultural production function was no longer the primary functional form, yet the economic development function became the dominant function in this area. 2) Temporal and spatial analysis methods of rural landscape functions can accurately and comprehensively reflect the evolution of the characteristics of multifunction tradeoffs and synergies. According to the Spearman rank correlation analysis of the multifunction value of the rural landscape in the time dimension, the results masked the differences of resource and environment carrying capacity caused by the differences of regional landscape resource endowment in the spatial dimension. 3) The spatial and temporal differences of the multi-functional tradeoffs and synergies of the rural landscape in Qingpu District from 1980 to 2018 were significant. There was significant heterogeneity of tradeoffs and synergies between functions in the spatial pattern, with clustering characteristics. Meanwhile, as for the temporal pattern, the tradeoffs and synergies of functions changed differently in terms of Moran's I and the correlation coefficient. The results of this study can provide scientific references for urban-suburban-rural space reconstruction and regional sustainable development.

Key words: rural landscape, multifunction, evolution, tradeoff and synergy, Qingpu District

REN Guoping, LIU Liming, LI Hongqing, YIN Gang, ZHAO Xu. Spatio-temporal Pattern of Multifunction Tradeoffs and Synergies of the Rural Landscape: Evidence from Qingpu District in Shanghai[J]. Journal of Resources and Ecology, 2021, 12(2): 225-240.

Figures/Tables 8

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Target	Criterion	Indicators	Direction	Weight
PF	APF	X₁ Annual value of food supply(yuan)	Positive	0.065
		X₂ Annual value of cash crop supply (yuan)	Positive	0.051
		X₃ Per capita cultivated land area (ha person^-1)	Positive	0.039
	EDF	X₄ Per capita GDP (yuan)	Positive	0.059
		X₅ Land urbanization rate (%)	Positive	0.053
		X₆ Contribution of agriculture(%)	Positive	0.044
LF	SCF	X₇ Population density (person km^-2)	Positive	0.061
		X₈ Area of settlement landscape land (ha)	Positive	0.063
		X₉ Per capita road mileage (km person^-1)	Positive	0.044
	LAF	X₁₀ Demand (person)	Positive	0.045
		X₁₁ Level of demand (yuan person^-1)	Positive	0.053
		X₁₂ Radiation range of landscape aesthetics (km)	Positive	0.039
		X₁₃ Plaque agglomeration	Positive	0.041
		X₁₄ Landscape diversity index	Positive	0.034
EF	ERF	X₁₅ Vegetation coverage index (%)	Positive	0.043
		X₁₆ Water network density index (%)	Positive	0.056
		X₁₇ Land degradation index	Negative	0.037
	EMF	X₁₈ Annual fertilizer application (t)	Negative	0.065
		X₁₉ Environmental annual capacity of landscape ecological land (t)	Positive	0.049
		X₂₀ Industrial waste emissions (t)	Negative	0.059

Target	Criterion	Indicators	Direction	Weight
PF	APF	X₁ Annual value of food supply(yuan)	Positive	0.065
		X₂ Annual value of cash crop supply (yuan)	Positive	0.051
		X₃ Per capita cultivated land area (ha person^-1)	Positive	0.039
	EDF	X₄ Per capita GDP (yuan)	Positive	0.059
		X₅ Land urbanization rate (%)	Positive	0.053
		X₆ Contribution of agriculture(%)	Positive	0.044
LF	SCF	X₇ Population density (person km^-2)	Positive	0.061
		X₈ Area of settlement landscape land (ha)	Positive	0.063
		X₉ Per capita road mileage (km person^-1)	Positive	0.044
	LAF	X₁₀ Demand (person)	Positive	0.045
		X₁₁ Level of demand (yuan person^-1)	Positive	0.053
		X₁₂ Radiation range of landscape aesthetics (km)	Positive	0.039
		X₁₃ Plaque agglomeration	Positive	0.041
		X₁₄ Landscape diversity index	Positive	0.034
EF	ERF	X₁₅ Vegetation coverage index (%)	Positive	0.043
		X₁₆ Water network density index (%)	Positive	0.056
		X₁₇ Land degradation index	Negative	0.037
	EMF	X₁₈ Annual fertilizer application (t)	Negative	0.065
		X₁₉ Environmental annual capacity of landscape ecological land (t)	Positive	0.049
		X₂₀ Industrial waste emissions (t)	Negative	0.059

Function	1980	1995	2007	2018
PF	0.545	0.641	0.662	0.675
LF	0.527	0.546	0.587	0.593
EF	0.605	0.505	0.334	0.396
APF	0.657	0.606	0.453	0.348
EDF	0.540	0.725	0.890	0.949
SCF	0.426	0.549	0.649	0.707
LAF	0.613	0.515	0.326	0.389
ERF	0.658	0.419	0.309	0.314
EMF	0.569	0.349	0.256	0.311

Function	1980	1995	2007	2018
PF	0.545	0.641	0.662	0.675
LF	0.527	0.546	0.587	0.593
EF	0.605	0.505	0.334	0.396
APF	0.657	0.606	0.453	0.348
EDF	0.540	0.725	0.890	0.949
SCF	0.426	0.549	0.649	0.707
LAF	0.613	0.515	0.326	0.389
ERF	0.658	0.419	0.309	0.314
EMF	0.569	0.349	0.256	0.311

Pairs of rural landscape functions	1980		1995		2007		2018
Pairs of rural landscape functions	I value	Z value	I value	Z value	I value	Z value	I value	Z value
PF-LF	0.334	6.255	0.318	5.856	0.217	8.542	0.243	9.885
PF-EF	0.159	1.995	-0.102	6.523	-0.293	5.575	-0.185	2.688
LF-EF	0.272	9.523	0.138	5.445	-0.131	5.742	-0.109	6.635
APF-EDF	-0.559	-6.859	-0.455	-5.778	-0.382	-4.524	-0.314	-3.524
APF-SCF	0.248	7.885	-0.332	-0.758	-0.459	-0.789	-0.547	-0.851
APF-LAF	0.353	7.851	-0.244	-6.855	-0.217	-4.874	0.142	3.448
APF-ERF	-0.142	9.985	-0.311	-8.667	-0.564	-8.228	-0.337	5.668
APF-EMF	-0.037	2.776	-0.119	-6.867	-0.325	-5.567	-0.217	2.888
EDF-SCF	0.256	7.567	0.356	9.861	0.467	10.232	0.633	11.745
EDF-LAF	0.138	2.664	-0.143	-3.752	-0.365	-4.578	-0.243	-8.347
EDF-ERF	-0.251	-6.752	-0.316	-7.664	-0.542	-9.001	-0.424	-5.664
EDF-EMF	-0.332	-3.341	-0.452	-4.584	-0.621	-6.854	-0.522	-7.330
SCF-LAF	-0.213	-0.856	-0.311	-5.856	-0.322	-0.741	-0.362	-1.775
SCF-ERF	0.182	2.452	-0.051	-5.521	-0.242	-7.634	-0.328	-6.853
SCF-EMF	0.212	1.885	-0.101	-5.752	-0.225	-8.532	-0.362	-9.774
LAF-ERF	0.241	2.521	0.312	8.442	0.422	12.841	0.637	18.772
LAF-EMF	0.332	5.321	0.411	8.854	0.492	5.334	0.591	10.654
ERF-EMF	0.451	6.854	0.462	2.885	0.511	13.772	0.542	9.524