Elsevier

Ecological Indicators

Volume 107, December 2019, 105550
Ecological Indicators

Spatial identification of land use functions and their tradeoffs/synergies in China: Implications for sustainable land management

https://doi.org/10.1016/j.ecolind.2019.105550Get rights and content

Highlights

  • Multifunctional land use directly affects regional sustainability.

  • A classification framework for sustainable land use was established.

  • An evaluation index system for identifying and quantifying land use functions at grid scale was established.

  • Tradeoff/synergy analysis was employed to explore the interrelations among land use functions.

  • Policy implications about land use zoning and management were proposed.

Abstract

Land use function (LUF) has sparked widely attention of researchers and policymakers who are focusing on sustainable development. Identifying the interrelations among multiple LUFs is of great significance for land use sustainability. A conceptual classification framework was proposed and a set of spatialization models were employed to assess, identify, quantify and visualize LUFs in spatial grid context. Upon the works aforementioned, Mechanical Equilibrium Model in physics was referenced to explore the tradeoffs/synergies among LUFs. The findings suggest that the indices of economic, social and ecological functions ranged from 0.00 to 0.99, 0.00 to 0.98 and 0.00 to 0.95, respectively and they displayed obvious heterogeneity in spatial distribution. Strong tradeoffs between socio-economic function and ecological function and synergies between economic function and social function mainly occurred in economic prosperous regions, especially in urban agglomerations, whereas areas with high ecological function and low socio-economic function are spatially agglomerated in the west part of China and the periphery of urbanized regions and farming areas. Essentially, spatial incompatibilities of land use caused by different demands are the roots of the land use conflicts. Hence, optimizing management options from the perspective of multifunctional land use based on tradeoff/synergy analysis, which can demonstrate the functional complementation and conflicts, can provide a reference for land use zoning and sustainable land management.

Introduction

The United Nations’ 2030 Agenda for Sustainable Development maps a global sustainability ambition that considers economy, society and environment (Gao and Bryan, 2017, UN, 2015). Numerous countries and regions have witnessed aggravations of unbalanced relationships between urbanization and industrialization processes and their natural resource and environmental bases. Sustainable land management has generally been considered to be a key issue of regional development and is becoming a force of global importance (Gong et al., 2012, Griggs et al., 2013, Long and Qu, 2018, Mirzabaev et al., 2015). The most formal outcomes of socio-economic modernization have imposed profound impacts on eco-environmental conditions all over the world. Rapid urbanization, industrialization and agricultural modernization have resulted in rampant expansions of urban spaces (Long, 2014, Peng et al., 2016b, Seto et al., 2017), serious soil deterioration (Teng et al., 2014), extensive water pollution (Peng et al., 2015), and severe air pollution (Gao and Bryan, 2017) in developing countries, especially China. Conflicts between socio-economic development and eco-environment, which are derived from economic output-oriented land use patterns, have long been prominent in China (Zhou et al., 2017). Therefore, building a harmonious man-land interrelation through scientific and appropriate land development has been on agenda in recent decades (Long et al., 2018). Multifunctional land use, which combines different functions on the same territorial units, has exactly proved to be an effective path for coordinating limited land resources and people’s multiple demands, especially in populated countries and regions (Liu et al., 2011, Mastrangelo et al., 2014, Paracchini et al., 2014).

Land use functions (LUFs) refer to the capacity for providing private and public products or services through diversified land use types and patterns. Multifunctional land use (MLU) is explicitly concerning on creating synergy effects by combining a diversity of LUFs at the same location (Vreeker et al., 2004). As for another similar concept, land use multifunctionality, comprehensively reflecting the status and performance of MLU, is a significant indicator or method for assessing the sustainability of land use (Mander et al., 2007, Zhou et al., 2017). On the contrary, MLU emphasizes the process, while land use multifunctionality is the result and comprehensive presentation of MLU (Liu et al., 2016, Zhen et al., 2009). The goal of MLU, aiming at promoting land use intensity and efficiency and coordinating the conflicts between scarce land and socio-economic development, is similar to the concepts of mixed land use, compact city and smart city (Otte et al., 2007). While, these concepts that widely used in urban planning always focus on tapping the potential of limited existing urban space (Chen et al., 2008). The scope of MLU can be extended to the macro urban-rural territorial system (Du et al., 2016, Peng et al., 2016a). In essence, MLU represents a mixed state of some compatible spaces, as it organically combines residential space, production space, public service space, and leisure space, so that various spaces are harmoniously compatible with each other. The rationale of MLU lies in that it considers social, economic, and environmental effects of any land use action simultaneously and interactively, to include those of commodity outputs (e.g. food, fibre, energy, timber, housing space, infrastructure) and non-commodity outputs (e.g. habitats, biodiversity, cleaning of water and air, greenhouse gas mitigation, buffering of weather extremes, cooling, flood control, cultural assets, recreational and human health assets) (Mander et al., 2007, Piorr et al., 2007).

MLU is featured by its comprehensiveness and diversity (Maier and Shobayashi, 2001, Mander et al., 2007). For this reason, a clear classification of LUFs is the premise of LUF evaluation. The classification methods differ from each other because of the differences among different research objects and disciplines (Groot and Hein, 2007). To balance the various dimensions of sustainable development, LUFs generally are divided into three subcategories including economic function, social function and ecological function (Helming, 2014, Zhou et al., 2017). As for economic function, it is mainly in terms of providing basic production and living materials, as well as industry development with the aim of economic growth (Wiggering et al., 2006). Basically, a sound land use system is capable to guarantee the orderly operation of social activities and maximize human welfare. Social function is embodied in providing living space, creating employment opportunities and guaranteeing residents’ traveling (Defries et al., 2004). With regard to ecological function, it refers to indigenous conditions that sustain production with the effects of soil conservation, water regulation and biodiversity preservation (Liu and Zhang, 2013). Land use system is an open, dynamic and complex one, if altered, it would disturb system coordination and cause deviations from the given targets (Torre et al., 2014). Economic function is constrained by natural resources, the environment, and other regional indigenous factors, and is closely related to regional development direction and strategic positioning. Extensive and inefficient economic development patterns will inevitably impose considerable pressure on eco-environments. Degraded environments will in turn place restraints on socio-economic sustainable development (Paracchini et al., 2011). The eco-environment determines human living conditions and provides the impetus, basis and resource support for the operation of the socio-economic system. Social function is the ultimate goal of land use and embodies the creation of prosperous, harmonious, stable, ecological and livable spaces for urban and rural residents through optimal allocations of land resources.

Current studies about LUFs paid more attention to a certain region, such as the whole nation (Song et al., 2015), a province (Fan et al., 2018) or a prefecture-level city (Liu et al., 2018), but few researches downscaled to a more micro scale. Previous studies mostly applied Multi-factor Comprehensive Appraisal Method to evaluate different LUFs based on the construction of index system and analyzed the spatiotemporal patterns, as well as the influential factors (Du et al., 2016). However, most of these studies merely depend on socio-economic statistics and lack of the comprehensive application of multi-source data (Sun et al., 2017). Meanwhile, only a few papers targeted at the relationships among different functions, such as the trade-off (Liu et al., 2018) and land use conflicts (Zhou et al., 2017). Tradeoff/synergy analysis, in general, sheds light on the conflict between socio-economic benefits and ecological cost from the perspective of ecosystem service provision (Carreño et al., 2012, Deng et al., 2011). Previous studies of tradeoff/synergy analysis primarily have two foci. One focus is investigating the variation of the relationship (conflict or synergy) among different ecosystems services and its spatiotemporal pattern, influential factors and the regional difference (from a historical perspective) (Deng et al., 2016, Jia et al., 2014, Pan et al., 2014). The second focus is examining how the interaction of the ecosystem service bundles respond to future land use options based on the projected land use conditions, which generally takes rapid urbanization, ecological security, and other kinds of projected scenarios into account (Lang and Song, 2019). However, little work has been done to examine how multiple LUFs correlate with each other at a fine scale and to find an ideal “point” to balance multiple functions, despite the quantification and evaluation of LUFs were conducted intensively and thoroughly for specific regions (Jia et al., 2014). Analyzing the inverse or direct relationships of LUFs is conducive to assessing the impact of land use policies or land use zoning on LUFs. Land use zoning is not only a simple process of spatial cluster or categorization, but also a practice that needs to coordinate multi-objectives (Liu et al., 2018). Land use management has transformed from one single production function to maximize the comprehensive benefits of economic growth, social advancement, and ecological protection. Therefore, competing objectives should be highlighted and different land use preference should be assigned to different land use zones to facilitate sustainable land use (Fan et al., 2018). Assessing and identifying LUFs is the necessary prerequisites of revealing their spatial heterogeneity, which is essential for land use zoning. Understanding the corresponding relationships among LUFs is helpful to find out dominant services that the land within specific region deliveries. Although land use type is the direct representation of the explicit property, while the function morphology emphasizes more on the implicit characteristics. Hence, multiple indicators incorporating both natural and socio-economic factors are supposed to be referenced to establish a comprehensive framework for LUF assessment. Additionally, the majority of literature conducted land use zoning at administrative unit scales, whereas the spatial information of index data can be processed and obtained with the advancement of GIS technology and the intensive data provided by remote sensing technology. In spite of the difficulty of collecting multi-source data, land use zoning based on tradeoff/synergy analysis among multiple LUFs at grid-scale ought to be carried out to fill in this research gap.

Environmental problems of both countryside and urban areas were considered to be associated with the segregation of production function from other functions (Vreeker et al., 2004). There exist differences among the sub-functions (economic function, social function, and ecological function) in expression form and action intensity. In other words, maybe a certain function is particularly prominent, and another function is weak (Fan et al., 2018). This is always attributed to unscientific land use planning that separated functions in order to maximize scale and efficiency (Peng et al., 2015). Some land use managers and users just pursue the economic benefit, but ignore that land also provides social and ecological functions. Therefore, conducting an assessment of LUFs and identifying the functional bias are of significance in adjusting regional land use policies and implementing MLU. Improved understandings of spatial patterns and tradeoff/synergy relations for the whole nation, especially in developing countries, are of extreme theoretical and practical significance. So, this paper aims to (1) apply a classification framework for sustainable land use and establish an evaluation index system in order to identify and quantify LUFs at grid-scale; (2) analyze the spatial pattern of LUFs in China based on qualifying the sub-functions and measuring the status of LUFs; and (3) investigate the tradeoff/synergy relations among multiple LUFs, and based on which to explore the reasons that contributing to this spatial pattern and propose policy implications for land use zoning.

Section snippets

Study area

There exists huge spatial differentiation of topography and climatic conditions in China. The southeast part of the HU line is more suitable for survival so that it carries nearly 96% of the total population in China (Qi et al., 2016). Only a small proportion of population scattered in the wide range of plateau areas. China’s arable land mainly distributes in Heilongjiang, Jilin, Liaoning, Shandong, Hebei, Inner Mongolia, Jiangxi, Hunan, Sichuan, Henan, Hubei, Anhui, and Jiangsu. In particular,

Spatial characteristics of land use sub-functions

The sub-functions calculated by the aforementioned method show obvious spatial heterogeneity. (1) High grain production function regions mainly located in the main grain-producing areas for agricultural products including the Northeast Plain, Huang-Huai-Hai Plain, Middle-Lower Reaches of Yangtze River Plain and Sichuan Basin. As is clearly presented in Fig. 5a, a large number of low-value areas are embedded in a wide range of continuous high-value regions, which is due to the occupation of

Insights into the spatial heterogeneity and the interaction of LUFs

In essence, the uncoordinated development of economic, social and ecological functions is a complex process of trade-off influenced by physical and socio-economic factors, which can occur through many possible mechanisms (Raudsepp-Hearne et al., 2010). Regional indigenous factors (e.g., topography, climate, resource endowments, and economic location) constitute the prerequisites of the variation in LUFs. Moreover, external drivers (e.g., urbanization, industrialization and agricultural

Conclusions

To investigate the spatial patterns and tradeoff/synergy relationships among LUFs in China, this paper establishes an index system to assess different LUFs and explore their interactions at grid scale by referring to Mechanical Equilibrium Model to propose pertinent suggestions for China’s sustainable land management. The results suggest that the function indices of economic, social and ecological functions, and their conflict level varied from 0.00 to 0.99, 0.00 to 0.98, 0.00 to 0.95, and 0.00

Acknowledgments

This work was supported by the Key Program of National Natural Science Foundation of China (Grant No. 41731286), the Bagui Scholars Program of Guangxi Zhuang Autonomous Region, Program of Science and Technology Plan of Guangxi Zhuang Autonomous Region (Grant No. 2018AD18001), and Natural Science Foundation of Guangxi Zhuang Autonomous Region (Grant Nos. 2018GXNSFAA138055 and 2018GXNSFDA281032).

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