Evolution forms of land systems based on ascendency and overhead: A case study of Shaanxi Province, China

Ecological Modelling 419 (2020) 108960

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Ecological Modelling journal homepage: www.elsevier.com/locate/ecolmodel

Evolution forms of land systems based on ascendency and overhead: A case study of Shaanxi Province, China

T

Li Feia,b,*, Zhou Meijuna, Shao Jiaqia, Qin Zhangxuana a b

College of Urban and Environmental Science, Northwest University, Xi’an, 710127, China Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, Xi’an, 710127, China

A R T I C LE I N FO

A B S T R A C T

Keywords: Land systems Evolution form Ascendency Overhead Sustainability

There were three basic forms of land system evolution: fluctuation, degradation and optimization. Based on the basic principles of system analysis, this study established a framework for analyzing the evolution form of land systems according to the sustainability and the relationship between ascendency and overhead, and then identified the evolution froms of land systems in Shaanxi Province. The results showed that the evolution of land systems in Shaanxi Province was in a fluctuation form and its sustainability showed a trend of increasing first and then decreasing between 1980 and 2015. The sustainability of land system evolution in Loess Plateau and Guanzhong Basin also increased first and then decreased, the changes in Loess Plateau were particularly significant and reached an optimization form during 1990–2000 and 2005–2010. The land system evolution in Guanzhong Basin in a less sustainable form of fluctuation after 2000. Land systems in Qinba Mountain were in an optimization form except for during 1980–1990 and 2005–2010. All three geographic units evolved in an optimization form between 1990 and 2000, and the sustainability of land system evolution in Shaanxi Province has increased from north to south both in 2000–2005 and 2010–2015; however, its sustainability weakened from north to south in 2005–2010. The verification of the results based on the information entropy change of the land systems showed that it was feasible and credible to distinguish the evolution form of land systems based on ascendency and overhead.

1. Introduction The movement of matter is eternal. For thousands of years, land systems have been formed and evolved in the process of human use, transformation and adaptation to the natural environment (Turner II et al., 2003; Hurtt et al., 2006; Pongratz et al., 2008; Bauch et al., 2016; Castro et al., 2016). There are three basic forms of land system evolution: (i) Fluctuation, refers to changes in land systems within a certain threshold range when it is interfered internally or externally, and land systems can still return to the normal state after the disturbance disappears; (ii) Degradation, refers to the structural imbalance and functional attenuation of land systems under the influence of internal and external forces; (iii) Optimization, refers to the enhanced vitality and functional stability of land systems under the influence of self-organization and external interference. Accurately judging the evolution form of land systems is of great significance for regulating land use for sustainable development (Turner II et al., 2007). Land system change is one of the important contents of global change research (GLP, 2005; Rounsevell et al., 2012; Turner II et al.,

⁎

2013; Verburg et al., 2013). Many scholars have conducted detailed and in-depth research on land system change patterns, processes, mechanisms, and impacts on the global (Goldewijk, 2001; Lambin and Meyfroidt, 2011; Václavík et al., 2013; Bruckner et al., 2015), continental (Boillat et al., 2017), national (Liu and Tian, 2010; Niedertscheider and Erb, 2014), regional (Spera et al., 2016; Peng et al., 2017), and local scales (Moore et al., 2012; Johansson and Isgren, 2017). These studies provide a range of models and analytical frameworks for analyzing changes in land systems (Dai and Liang, 2018). Such as, the comprehensive index model of land use change for measuring macroscopic changes in regional land systems (Wang et al., 2001), the land use dynamics model for gathering land system change hotspots (Liu et al., 2003), the land use relative change model for highlighting regional differences in land system changes (Li et al., 2015) and the gravity migration model that characterizes the spatial pattern change of land systems (Wang et al., 2002). However, the existing models and analytical frameworks are difficult to objectively and rationally distinguish the evolution forms of the land system. With the development of system science, the study of land

Corresponding author at: College of Urban and Environmental Science, Northwest University, Xi’an, 710127, China. E-mail address: [email protected] (F. Li).

https://doi.org/10.1016/j.ecolmodel.2020.108960 Received 11 November 2019; Received in revised form 18 January 2020; Accepted 23 January 2020 Available online 31 January 2020 0304-3800/ © 2020 Elsevier B.V. All rights reserved.

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2.3. Identification of evolution forms of land system

system sustainability provides a good opportunity to solve this problem (Damien et al., 2017; Bryan et al., 2018). At present, land system sustainability evaluation methods mainly include three types: index synthesis method, energy value analysis method and systematic analysis method (Ness et al., 2007; Singh et al., 2009; Panyam et al., 2019). The basic principle of the indicator synthesis method is to divide land systems into several subsystems; as long as each subsystem is sustainable, land systems are in a sustainable state. This method ignores the integrity of land systems, the selection of indicators is subjective, and the evaluation results are only the relative sustainability of the vertical, it is difficult to carry out horizontal comparison of different regions. Although the energy value analysis method establishes the relationship between the internal components of systems, the determination of the energy value conversion rate is greatly influenced by human factors. In addition, the sustainability of land systems can only be judged from the process of change (Cai and Li, 2003), which is insufficiently considered by the indicator synthesis method and the energy value analysis method. The systematic analysis method that has emerged in recent years evaluates the sustainability of systems mainly based on the balance between land system efficiency and overhead, which provides a new perspective for the sustainable study of land systems (Huang and Xu, 2010; Bodini, 2012; Fath, 2014; Huang, 2015; Kharrazi et al., 2016). Based on thermodynamics, information theory, network analysis, etc., Ulanowicz et al. (2009) quantitatively describe the overall behavior of systems with development capability, ascendency, reserve (overhead) and robustness, etc., and constructe a system evolution sustainability model (Ulanowlcz and Norden, 1990; Ulanowicz et al., 2009). The method is objective and effective, and could evaluate the system change process, which had been applied in the economic system and water resources system sustainability evaluation (Lietaer et al., 2010; Li and Yang, 2011; Kharrazi et al., 2013). Therefore, based on the basic principles of system analysis, this study constructed an analytical framework for identifying the evolution forms of land systems based on the ascendency and overhead of land system evolution, and Shaanxi Province was selected as the research object for empirical analysis, aiming to expand the theory and content of land system research.

The theoretical basis for evaluating the sustainability of land systems based on the perspective of system evolution is that the sustainability of land system evolution is determined by the ascendency (A) and overhead (φ). The ascendency and overhead together constitute the evolutionary capability (C) of systems. That is:

Tij ⎞ C = A + φ = −∑ Tij log ⎛ TST ⎠ ⎝ i, j ⎜

A=

Tij TST ⎞ ⎟ ⎝ Ti Tj ⎠

2 ⎛ Tij ⎞ φ = −∑ Tij log ⎜ ⎟ i, j ⎝ Ti Tj ⎠

TST =

(2)

(3)

∑ Tij i, j

(4)

∑ Tij (5)

j

Tj =

(1)

∑ Tij log ⎛⎜ i, j

Ti =

⎟

∑ Tij i

(6)

Tij refers to the substance, information or energy flowing from the i subsystem to the j subsystem; Ti refers to all substance, information or energy flowing out of the i subsystem; Tj refers to all substance, information or energy flowing into the j subsystem; TST indicates all substance, information or energy that have metastasized in the system (i ≠ j). In this study, Ti, Tj, Tij and TST only involve changes in the area of land use type. Ascendency (A) characterizes system efficiency and refers to systems can fully demonstrate organized and effective behavior to maintain the integrity of systems (Hines et al., 2018). Overhead (φ) characterizes the potential for changes in a system, meaning that the system has potential for recovery and diverse behavior when interfered by internal components or the external environment (Bodini, 2012; Fath, 2014). If a system lacks ascendency, it is difficult to meet the vitality required for the evolution of the system and the system is in a fluctuation form; if the overhead is too small, the system will be prone to collapse when subjected to external disturbances and the system is in a degeneration form (Fig. 2). However, the increase in systems ascendency will inevitably lead to a decline in the overhead, and the increase in overhead will also cause systems to lose some ascendency. Only when the proportions of the two are suitable, it can ensure that systems can effectively deal with the flow of matter, information and energy, and ensure that systems can recover from external disturbances, thus achieving the sustainable development of systems, and systems evolve in a optimization form (Ulanowicz et al., 2009; Huang, 2015). Therefore, sustainability (S) of land system evolution can be defined as follows:

2. Material and methods 2.1. Study area Shaanxi Province (105°29′-111°15′E, 31°42′-39°35′N), with a total area of about 205,700 km2, is located in the eastern part of northwest China; it belongs to the zone of the continental monsoon climate and also stretches into both the North Temperate Zone and the Semi-tropic Zone. According to topography, landform, hydrology, climate, etc., Shaanxi Province can be divided into three geographical units, named from the north to the south as the Loess Plateau, Guanzhong Basin and Qinba Mountain (Fig. 1). In 2015, the Loess Plateau was mainly occupied by grassland (43.7 %) and cultivated land (32.6 %); Farmland and built-up land accounted for 71.5 % and 14.1 % of the total land area of Guanzhong Basin, respectively; the main land use types in Qinba Mountain were grassland (39.8 %), forest land (36.2 %) and cultivated land (22.8 %).

e aβ log (aβ ) log (e )

(7)

α = A/ C = A/(A + φ)

(8)

S=−

α∈(0, 1]; When α tends to 0, the ascendency tends to 0, and the system evolution sustainability also tends to 0; when α = 1, the overhead is 0, S = 0 ; β is the adjustment parameter. The evolution of land systems is sustainable only when S exceeds a certain threshold (St). According to formula (7), it can be known that St corresponds to two values of α (m and n in Fig. 2); that is, the evolution of land systems is sustainable only when m≤α≤n. In this way, the value of α can be divided into three intervals: (0, m), [m, n], (n, 1]. By analyzing the relationship between ascendency and overhead, the three value intervals of α can correspond to the three forms of land system

2.2. Data sources The data used in this study mainly included land use data (1980/ 1990/2000/2005/2010/2015) and geographic unit boundary data (Fig. 1). The land use data comes from the 1:100,000 land use database of the Resource and Environmental Science Data Center of the Chinese Academy of Sciences (http://www.resdc.cn/Default.aspx). Geographical unit boundary data was obtained from the Shaanxi Provincial Geographical White Paper (2015). 2

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Fig. 1. land use of Shaanxi Province.

ascendency and small overhead, lack of redundant options in times of disturbances and is prone to collapse, which can be defined as a degeneration form. According to calculation results of Ulanowicz et al. (2009), β should be 1.288 and it can be deduced that the system evolution is sustainable when α∈[0.2393, 0.6971]. The specific analysis and derivation process is detailed in the literature of Ulanowicz et al. (2009). According to the above analysis framework, this study analyzed the form and sustainability of land system evolution from the perspective of land use type change. The sustainability of the system evolution can be improved by adjusting the ascendency, which required calculation of the marginal contribution of the first-order path to ascendency: Fig. 2. Land system evolution forms.

Tij TST ⎤ ∂A = log ⎡ + log (e ) ⎢ Ti Tj ⎥ ∂Tij ⎣ ⎦

evolution. If α∈(0, m), it indicates that the overhead of land systems is great and it lcaks of vitality for land system evolution, which can be defined as a fluctuation form; if α∈[m, n], the ratio of ascendency and overhead is appropriate, indicating the land system evolution is in an optimization form; and if α∈(n, 1], land systems, with excessive

(9)

For land systems in a fluctuation form, strengthening the land use conversion path with great marginal contribution for ascendency can effectively improve the sustainability of land system evolution; for land systems in a degeneration form, it is necessary to reduce the land use 3

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to grassland due to increased vegetation coverage, and the forest area increased by about 200 km2, which effectively enhanced ecosystem services and functions and improved the sustainability of land system evolution during 1990–2000. During 2000–2005, the main characteristics of land system changes in Shaanxi Province were the reduction of cultivated land and the increase of forest, construction land and grassland (Table 4); the area of construction land increased by 10.4 %, while the area of forest land and grassland increased by less than 3 % compared with 2000. Small changes in land use lead to less ascendency and insufficient vitality in the evolution of land systems. Therefore, the evolution of land systems in Shaanxi Province was in a fluctuation form between 2000 and 2005. In addition, the marginal contributions of the conversion of water to forest and built-up land, as well as the abandonment of cultivated and construction land for ascendency were negative, which was the main reason for reducing the ascendency of land system evolution. The sustainability of land system evolution in Shaanxi Province during 2005–2010 ha d improved from the previous period, but it was still in a fluctuation form (Table 1). During this period, the construction land in Shaanxi Province expanded from 3510.9 km2 to 4295.2 km2, an increase of 22.3 %, which is the most important change in land systems in Shaanxi Province (Table 5). At the same time, unused land was exploited for grassland, arable land and construction land, reducing its area by 4.4 %. Due to the implementation of the policy of returning farmland to forests and grassland and the occupation of cultivated land by economic development and urban expansion, the area of cultivated land decreased by 2.6 % in 2010 compared with 2005. The conversion of these types of land use had a positive marginal contribution to the ascendency of land system evolution and increased the sustainability. This trend was particularly evident in the Loess Plateau. The construction land in the Loess Plateau increased by 44.5 % between 2005 and 2010, the grassland increased by 3.7 %, and the cultivated land and unused land decreased by 5.3 % and 4.3 %, respectively, resulted in the sustainability of the land system evolution of the Loess Plateau increased from 0.6861 to 0.8137, and the evolution of land systems was in an optimization form (Table 1). In the Guanzhong Basin, the transition from unutilized land to grassland and water had the most prominent marginal contribution to its ascendency, all above 3.2 %, which was the important incentive for the development of land systems to a sustainable direction; however, the evolution of land systems still in a fluctuation form and lack of vitality. Contrary to the Loess Plateau and the Guanzhong Basin, the area of unused land (in 2010) in the Qinba Mountain increased by 17.2 % compared with 2005 due to climate change such as reduced precipitation and raised temperature and unreasonable human activities. In particular, the conversion of cultivated land and water to unused land reached a marginal contribution of −6.2 % and −6.1 % on ascendency, respectively. These changes led to the evolution form of land systems in Qinba Mountain converted from optimization form during 2000–2005 to fluctuation form during 2005–2010 (Table 1).

conversion path with great marginal contribution for ascendency. 2.4. Information entropy change of land system The information entropy of land systems reflects the number of land use types and the uniformity of the area distribution of each land use type. It characterizes the disorder degree of the system; the larger the information entropy, the higher the degree of disorder, and vice versa. The structure of a sustainable evolutionary system will tend to be more orderly and the information entropy should not increase. Therefore, the sustainability and evolution form of land systems can be verified according to the change in information entropy. The calculation formula of land system information entropy (H) is as follows (Pourghasemi et al., 2012): k ⎡ M ⎛ Mi ⎞ ⎤ H = −∑ ⎢ k i ln ⎜ ∑k M ⎟ ⎥ M ∑ i=1 ⎢ ⎣ i=1 i ⎝ i=1 i ⎠ ⎥ ⎦

(10)

Mi (i = 1, 2… k) is the area of i-th type of land use in the region, and k is the total number of land use types. The calculation formula of land system information entropy change (ΔH) is k

ΔH = HE − HS =

⎡

⎛ Msi ⎞ ⎤ Msi ln k ⎜ ∑k M ⎟ ⎥ i = 1 ⎢ ∑i = 1 Msi ⎝ i = 1 si ⎠ ⎥ ⎣ ⎦

∑⎢

k

⎡ M ⎛ MEi ⎞ ⎤ −∑ ⎢ k Ei ln ⎜ ∑k M ⎟ ⎥ i = 1 ⎢ ∑i = 1 MEi ⎝ i = 1 Ei ⎠ ⎥ ⎦ ⎣

(11)

HS and HE are the information entropy before and after the land system change, respectively. MSi and MEi are the area of a certain land use type before and after the land system change. For example, the information entropy change in land systems between 2010 and 2015 is (11)

ΔH2010 − 2015 = H2015 − H2010 3. Results

3.1. Temporal variation of land system evolution form in Shaanxi Province From the perspective of land use area structure, the sustainability of land system evolution in Shaanxi Province fluctuated over time, and it was the most sustainable during 1990–2000. The evolution of land systems in Shaanxi Province during 1980–1990 was in a fluctuation form with low sustainability (Table 1). During this period, the lack of ascendancy was the main reason for the fluctuation of land systems; in particular, the conversion of grassland to construction land, which concentrated in the Loess Plateau (Table 2), had the greatest negative contribution to ascendancy. Compared to the period of 1980–1990, the magnitude of change in land systems between 1990 and 2000 increased significantly (Table 3. Nearly 1,300 km2 of unused land was converted Table 1 Sustainability and form of land system evolution in Shaanxi Province. Periods Shaanxi Province

Loess Plateau

Guanzhong Basin

Qinba Mountain

a S Form a S Form a S Form a S Form

1980–1990

1990–2000

2000–2005

2005–2010

2010–2015

0.1603 0.6065 Fluctuation 0.1578 0.5993 Fluctuation 0.2788 0.8631 Optimization 0.2098 0.7316 Fluctuation

0.3204 0.9200 Optimization 0.3419 0.9432 Optimization 0.3085 0.9052 Optimization 0.2953 0.8875 Optimization

0.1775 0.6531 Fluctuation 0.1905 0.6861 Fluctuation 0.2047 0.7199 Fluctuation 0.2392 0.7936 Optimization

0.2032 0.7164 Fluctuation 0.2498 0.8137 Optimization 0.2357 0.7865 Fluctuation 0.1911 0.6875 Fluctuation

0.1015 0.4208 Fluctuation 0.0613 0.2682 Fluctuation 0.2215 0.7574 Fluctuation 0.2694 0.8479 Optimization

4

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Table 2 Land Use Transfer Matrix of Shaanxi Province from 1980 to 1990 (unit: km2). 1980

Shaanxi Province

Loess Plateau

Guanzhong Basin

Qinba Mountain

Farmland Forest Grassland Water Built-up land Unused land Farmland Forest Grassland Water Built-up land Unused land Farmland Forest Grassland Water Built-up land Unused land Farmland Forest Grassland Water Built-up land Unused land

1990 Farmland

Forest

Grassland

Water

Built-up land

Unused land

71562.4 12.9 83.0 125.0 5.7 7.6 35009.1 7.6 22.3 14.3 0.0 7.0 17547.6 1.2 43.1 94.4 5.7 0.6 19005.7 4.0 17.6 16.2 0.0 19005.7

27.6 46059.6 40.7 14.7 0.0 0.4 10.5 15465.7 2.6 0.5 0.0 0.4 0.9 577.2 0.6 13.1 0.0 0.0 16.1 30016.7 37.5 1.1 0.0 16.1

99.2 42.8 76928.4 65.3 2.2 15.5 73.7 4.7 40982.8 8.2 0.0 15.5 3.3 0.5 2103.4 50.1 2.2 0.0 22.2 37.6 33842.2 7.1 0.0 22.2

58.3 4.5 87.4 1661.4 0.0 0.2 8.8 0.5 4.6 773.7 0.0 0.2 41.1 2.6 74.3 585.2 0.0 0.0 8.3 1.4 8.5 302.5 0.0 8.3

59.1 2.0 0.9 1.7 2696.3 0.0 3.1 0.0 0.8 0.2 459.5

13.1 0.0 12.3 6.0 0.0 6037.5 11.5 0.0 12.3 2.8 0.0 5881.6 1.6 0.0 0.0 3.2 0.0 126.0 0.0 0.0 0.0 0.0 0.0 0.0

51.8 0.0 0.0 1.1 1862.5 0.0 4.2 2.0 0.0 0.5 374.3 4.2

of land system evolution was only 0.2682 and the ascendency was less than 0.1, indicated land system evolution was in a fluctuation form. This was closely related to the disorderly expansion of construction land in the Loess Plateau. During these five years, the area of construction land in the Loess Plateau increased from 885.3 km2 to 1356.8 km2, with an increase of 53.2 %, which was much greater than the growth rate of construction land in other geographic units during the same period (Guanzhong Basin: 13.5 %; Qinba Mountain: 9.9 %). However, the area change of other land use types in the Loess Plateau was less than 3 %, resulted in a lower ascendency in land system evolution. Judging from its marginal contribution to ascendency,

During 2010–2015, the most obvious features of land system changes in Shaanxi Province were the expansion of construction land (with an increase of 21.2 %) and water (with an increase of 3.6 %) (Table 6). Except for construction land and water, the area change ratios of other land use types were all less than 1 %. Therefore, the evolution of land systems in Shaanxi Province lacked vitality and was in a fluctuation form. In this period, the sustainability of land system evolution in Shaanxi Province was only 0.4208, far less than its sustainability in the previous two periods. The sustainability of land system evolution in the Loess Plateau and the Guanzhong Basin also showed similar trends. Especially in the Loess Plateau, the sustainability

Table 3 Land Use Transfer Matrix of Shaanxi Province from 1990 to 2000 (unit: km2). 1990

Shaanxi Province

Loess Plateau

Guanzhong Basin

Qinba Mountain

Farmland Forest Grassland Water Built-up land Unused land Farmland Forest Grassland Water Built-up land Unused land Farmland Forest Grassland Water Built-up land Unused land Farmland Forest Grassland Water Built-up land Unused land

2000 Farmland

Forest

Grassland

Water

Built-up land

Unused land

71205.1 59.2 555.6 89.2 0.3 35.1 34879.2 24.4 395.0 6.0 0.0 32.6 17322.3 1.1 41.3 80.4 0.2 2.5 19003.5 33.7 119.3 2.8 0.0 0.0

112.5 45908.6 253.0 1.0 0.0 67.8 50.1 15332.9 243.1 0.3 0.0 36.1 59.1 568.3 7.2 0.7 0.0 31.8 3.4 30007.3 2.6 0.0 0.0 0.0

56.3 152.8 76228.8 31.1 0.1 1298.6 33.2 119.6 40360.3 10.5 0.0 1298.6 2.9 3.9 2081.7 20.5 0.0 0.0 20.2 29.3 33786.8 0.1 0.0 0.0

30.4 1.6 29.0 1685.9 0.0 7.9 2.3 0.0 3.3 767.3 0.0 0.1 26.2 1.5 25.4 600.9 0.0 7.7 1.9 0.0 0.3 317.7 0.0 0.0

356.7 18.5 8.7 0.3 2759.7 3.0 60.0 0.7 5.9 0.0 463.5 2.8 282.0 16.6 2.7 0.3 1915.2 0.2 14.6 1.1 0.0 0.0 381.0 0.0

35.5 2.3 78.3 3.9 0.0 4656.5 35.5 2.0 77.1 3.7 0.0 4538.1 0.0 0.4 1.2 0.2 0.0 88.6 0.0 0.0 0.0 0.0 0.0 29.8

5

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Table 4 Land Use Transfer Matrix of Shaanxi Province from 2000 to 2005 (unit: km2). 2000

Shaanxi Province

Loess Plateau

Guanzhong Basin

Qinba Mountain

Farmland Forest Grassland Water Built-up land Unused land Farmland Forest Grassland Water Built-up land Unused land Farmland Forest Grassland Water Built-up land Unused land Farmland Forest Grassland Water Built-up land Unused land

2005 Farmland

Forest

Grassland

Water

Built-up land

Unused land

69239.0 96.8 626.8 51.5 9.1 24.8 33503.5 41.6 384.4 17.6 1.8 15.5 17112.6 3.8 30.9 31.8 5.4 9.3 18622.9 51.4 211.5 2.0 1.9 0.0

927.6 46064.4 505.1 1.4 0.9 5.6 797.9 15560.8 394.3 1.0 0.3 1.4 18.9 645.0 3.1 0.2 0.4 4.0 110.7 29858.6 107.7 0.2 0.2 0.1

1362.6 149.4 76525.9 7.5 3.1 66.6 965.3 46.6 40966.1 3.3 1.2 63.4 24.6 1.2 2052.3 2.8 0.7 3.1 372.7 101.7 33507.5 1.4 1.2 0.1

77.7 4.2 27.2 1693.3 0.6 3.2 4.7 1.0 6.1 750.8 0.1 3.1 65.0 2.9 16.8 626.6 0.3 0.0 8.0 0.3 4.3 316.0 0.2 0.0

332.0 14.8 25.9 0.6 3133.0 4.5 60.9 2.5 15.2 0.1 529.6 4.5 226.2 11.1 5.7 0.3 2210.1 0.0 44.8 1.2 5.0 0.2 393.3 0.0

5.1 13.1 56.1 0.3 0.0 4672.0 4.7 9.9 55.9 0.2 0.0 4568.5 0.4 3.1 0.1 0.1 0.0 73.9 0.0 0.1 0.1 0.0 0.0 29.6

a fluctuation form. While, the the land system evolution in the Guanzhong Basin, characterized by the expansion of cultivated land and construction land and the reduction of grassland and water areas, had the greatest sustainability compared to the other two geographic units. All three geographic units evolved in an optimization form between 1990 and 2000. In this period, significant changes that were suitable for regional development took place in land systems in the Loess Plateau (characterized by greening of unused land), the Guanzhong Basin (characterized by the expansion of construction land), and the Qinba Mountains (characterized by the appropriate increase in cultivated land area). These changes in land use generally promoted the

increasing investment in construction land remediation into farmland or grassland can effectively enhance the ascendency of land system evolution in the Loess Plateau and achieve sustainable evolution.

3.2. Spatial differences of land system evolution form in Shaanxi Province Land systems in the Loess Plateau changed little between 1980 and 1990, with less than 1 % change in area of each land use type, resulted in insufficient ascendency and great overhead. Therefore, the sustainability of land system evolution in the Loess Plateau during this period was the lowest of the three geographic units and land systems evoled in Table 5 Land Use Transfer Matrix of Shaanxi Province from 2005 to 2010 (unit: km2). 2005

Shaanxi Province

Loess Plateau

Guanzhong Basin

Qinba Mountain

Farmland Forest Grassland Water Built-up land Unused land Farmland Forest Grassland Water Built-up land Unused land Farmland Forest Grassland Water Built-up land Unused land Farmland Forest Grassland Water Built-up land Unused land

2010 Farmland

Forest

Grassland

Water

Built-up land

Unused land

66161.1 242.1 1522.1 152.7 110.2 62.5 31080.4 130.5 838.7 17.8 33.4 55.1 16552.2 30.1 218.3 105.7 71.2 7.5 18528.5 81.5 465.1 29.2 5.6 0.0

439.7 47014.4 524.8 9.2 22.3 6.2 336.5 16496.9 158.9 1.5 0.9 4.1 33.3 617.2 14.2 6.8 1.7 0.5 69.9 29900.3 351.7 0.9 19.6 1.6

2629.9 172.7 75854.8 81.3 14.1 143.0 2390.9 104.8 40909.4 39.5 6.3 130.9 80.1 2.2 1817.8 37.9 3.1 10.8 158.9 65.7 33127.7 3.9 4.8 1.3

110.7 7.9 48.8 1550.4 7.4 11.6 10.1 1.9 11.4 698.0 1.0 2.2 62.0 3.1 10.2 558.1 4.8 9.5 38.6 2.9 27.2 294.3 1.6 0.0

690.3 49.7 132.8 8.9 3356.9 56.6 136.4 11.3 103.2 6.7 571.1 56.6 461.1 15.2 19.7 1.7 2372.8 0.0 92.9 23.2 9.9 0.5 412.9 0.0

16.2 18.2 32.1 3.9 0.0 4466.7 10.1 10.3 24.4 2.2 0.0 4390.4 5.2 3.9 4.5 1.7 0.0 49.4 0.9 4.0 3.1 0.0 0.0 26.9

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Table 6 Land Use Transfer Matrix of Shaanxi Province from 2010 to 2015 (unit: km2). 2010

Shaanxi Province

Loess Plateau

Guanzhong Basin

Qinba Mountain

Farmland Forest Grassland Water Built-up land Unused land Farmland Forest Grassland Water Built-up land Unused land Farmland Forest Grassland Water Built-up land Unused land Farmland Forest Grassland Water Built-up land Unused land

2015 Farmland

Forest

Grassland

Water

Built-up land

Unused land

67577.4 37.6 144.9 5.5 3.4 79.0 31998.0 24.0 106.1 3.1 3.3 78.9 16568.7 0.1 1.3 1.9 0.0 0.0 19010.7 13.5 37.5 0.5 0.0 0.1

4.7 47919.2 0.8 0.9 0.0 1.4 0.5 16930.0 0.5 0.0 0.0 1.4 0.0 664.3 0.0 0.8 0.0 0.0 4.2 30324.9 0.3 0.1 0.0 0.0

45.5 3.6 78385.1 17.7 0.7 2.6 5.1 1.3 43135.9 4.0 0.7 2.5 0.9 0.0 1931.4 13.5 0.0 0.0 39.5 2.3 33317.8 0.2 0.0 0.1

57.8 3.1 27.6 1705.8 0.7 4.3 13.3 1.7 12.8 711.5 0.3 3.9 42.0 1.2 12.9 630.6 0.4 0.4 2.5 0.2 1.9 363.7 0.0 0.0

539.7 29.8 249.6 6.2 4289.7 92.0 116.6 20.8 241.7 5.4 880.3 92.0 373.1 8.0 5.6 0.8 2870.0 0.0 50.0 0.9 2.3 0.1 539.4 0.0

25.7 23.5 88.0 0.6 0.7 4357.8 22.5 21.1 84.8 0.6 0.7 4258.8 0.2 0.1 0.6 0.0 0.0 64.1 3.0 2.3 2.5 0.0 0.0 34.8

respectively) was the main change characteristic. Due to the abundant precipitation and humid climate in Qinba Mountain, rational utilization of unused land through afforestation played an important role in enhancing the sustainability of land system evolution. In 2005–2010, the sustainability of land system evolution in Shaanxi Province increased from south to north (Table 1). Similar to 2000–2005, the sustainability of land system evolution in Shaanxi Province increased from north to south in 2010–2015, and the Qinba Mountain had the greatest sustainability and achieved optimization form (Table 1).

3.3. Results verification based on information entropy change of land systems By calculating the information entropy change and sustainability of the land system evolution, it can be found that, except the Guanzhong Basin, the sustainability based on the ascendency and overhead had a significant linear correlation with the information entropy change of land systems at the 0.01 level, with a correlation coefficient of -0.749 (Fig. 3). Interestingly, the information entropy of land system evolution in an optimization form was no more than 0.003. The unused land in the Loess Plateau decreased by 21.2 %, and the construction land increased by 15 % between 1990 and 2000; the area change ratio of forest, grassland and water was also about 2 %. However, these dramatic land-use changes not only did not increase the information entropy, but made land systems developed in a more orderly direction. Therefore, it can be considered that the evolution of land systems was sustainable and in an optimization form, which was consistent with the results calculated based on ascendency and overhead. During 2000–2005, the area of construction land, water and farmland in Qinba Mountain increased by 12 %, 2.8 % and 1.4 %, respectively. However, this obvious land system changes only increased the information entropy by 0.001. That is, the obvious land system changes did not increase the information entropy, indicating that the land system evolution had a higher sustainability, which was consistent with the judgment results in Table 1. Therefore, it was credible that the land system evolution in Qinba Mountain was in an optimization form during 2000–2005.

Fig. 3. Relationship between information entropy change sustainability.

ecosystems maintenance and economic and social development, so the land system evolution in three geographic units was highly sustainable. In 2000–2005, the sustainability of land system evolution in Shaanxi Province decreased from south to north; i.e., Qinba Mountain had the highest sustainability, followed by Guanzhong Plain, and Loess Plateau had the lowest sustainability (Table 1). The main characteristics of the land system changes in the Loess Plateau were that the construction land and forest increased by 13 % and 6.5 % respectively, the cultivated land decreased by 4 %, and the evolution of land systems was in a fluctuation form. The precipitation on the Loess Plateau was sparse and the climate was dry; unreasonable afforestation on the unused land would aggravate its aridification, which was an important reason for the unsustainable land system evolution in the Loess Plateau during 2000–2005. The land system changes in the Guanzhong Basin were dominated by the development and utilization of unused land (reduced by 14.2 %) and the expansion of construction land (increased by 10.7 %). Although the ascendency of land systems in the Guanzhong Basin was higher than that in the Loess Plateau, it was still in the evolution form of fluctuation. During 2000–2005, the land system evolution in Qinba Mountain was in an optimization form and the increase in construction land and water (with an increase of 12 % and 2.8 % 7

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entropy that characterize their degree of disorder should not increase rapidly, but the results of these studies all indicated it increased. This is mainly because the expansion of urban construction land led to the massive and rapid conversion of suburban arable land into construction land, which resulted in an increase in the information entropy in fast urbanized areas (Wang and Wang, 2018). Although the information entropy change of land systems in the rapidly urbanized area was greater than its due level, it was not inconsistent with the unsustainable fluctuation form of the land system evolution. That is, it did not affect the identification of the evolution form of land systems in fast urbanized areas. Moreover, it demonstrated that the identification of the evolution form based on ascendency and overhead was reasonable and feasible, and there was a deeper connotation to be explored. Although there may be a mathematical relationship between the information entropy change and the sustainability calculated based on ascendency and overhead, the thinking and data foundation of the two calculations were completely opposite. The calculation of information entropy change was to first calculate the information entropy of each year according to the land use data (static data) in different years, and then compare the changes of the information entropy between the two years, which can be summarized as calculating the information entropy first, then calculating change. However, the sustainability was calculated based on the data on the changes in land use between two different years (dynamic data), which can be summarized as changing first and then calculating sustainability. Therefore, it was feasible to verify the sustainability with changes in information entropy. There were some limitations in this study. The evolution of land systems was only seen from the conversion of land use types, and the results were relatively one-sided. A land system was a generated human-environment system, and the transformation of land use types was difficult to reflect the overall evolution of the system (Rounsevell et al., 2012; Turner II et al., 2016). In the future, we will explore the ascendency and overhead of land system evolution from the aspects of energy flow and ecosystem service flow, and provide decision-making suggestions for land system management. In addition, the value range of α was mainly calculated from the results of research based on ecosystems by Ulanowicz et al. (2009). However, the value range of α for different systems such as ecosystems, economic systems, water resources systems, and land systems were different (Goerner et al., 2009; Morris et al., 2009; Huang and Xu, 2010; Li and Yang, 2011).The exact value range of α for land systems should be explored in conjunction with relevant research results, in order to make the research more scientific and reasonable, and to provide decision-making suggestions for the realization of regional sustainable development.

During 2005–2010, the land system structure of the Loess Plateau changed drastically, with the area of construction land, grassland and forest increased by 44.5 %, 3.7 % and 1.5 % respectively, and the area of water, cultivated land and unused land respectively decreased by 5.4 %, 5.3 % and 4.3 %. The dramatic structural changes in land systems only led to an increase in information entropy of 0.002, indicating that the evolution of land systems in this period was highly sustainable and in an optimization form. This was also consistent with the results in Table 1. During 2010–2015, the main characteristics of land system changes in Qinba Mountain were the increase in unused land and construction land, which increased by 22 % and 9.9 % respectively. The change in information entropy caused by these land system changes was little (only 0.003). It can be judged that the land system evolution of the Qinba Mountain during 2010–2015 was reasonable and sustainable, and was in an optimization form. In addition, the land system information entropy changes caused by the land system evolution in the form of fluctuation were all greater than 0.006. For example, during 2010–2015, the information entropy change of land systems was 0.017 in the Loess Plateau, which was greater than the information entropy change in other periods; however, the sustainability (only 0.268) of land system evolution was the smallest of the three periods and it was in a fluctuation form. In summary, it was feasible and credible to identify the evolution form of land systems based on ascendency and overhead. 4. Discussion The identification of the evolution forms of land systems was a prerequisite for the regulation of land systems. According to the ascendency and overhead, the evolution forms of land systems can be objectively and accurately identified. If a land system was in an optimization form, it was not necessary to adjust the land system; if in the degradation form, its overhead should be improved; if in a fluctuation form, increase the ascendency would improve the sustainability of land system evolution. In particular, land systems can be effectively and accurately regulated by analyzing the marginal contribution of the conversion path. The three geographic units in Shaanxi Province represented three different climatic regions, semi-arid area (Loess Plateau), semi-humid area (Guanzhong Basin), and humid area (Qinba Mountain). In general, the more humid the region, the more sustainable the evolution of land systems. That is, the sustainability of land system evolution in the humid area was the greatest, followed by semi-humid area, and the evolution of land systems in semi-arid regions was the least sustainable. In semi-arid regions, the average sustainability of land system evolution was not only the lowest, but also has the largest fluctuations in different periods. The evolution of land systems in a region was not static. As long as master the evolution laws of land systems and explore the evolution direction that is suitable for the local climate conditions, land systems could evolve in the form of optimization. The sustainability of land system evolution based on the ascendency and overhead had a positive correlation with the information entropy change. That is, the smaller the information entropy increases, the greater the sustainability of land system evolution. However, in the rapidly urbanized areas, the information entropy change obvious greater than that it should be under its sustainability state. As a typical rapid urbanization area in China, the evolution sustainability of land systems in the Guanzhong Basin in the last three periods was 0.720, 0.786 and 0.757, respectively; however, their information entropy changes were 0.023, 0.009 and 0.032, respectively, which much larger than the information entropy it should be. A number of case studies have also supported this (Chen and Liu, 2001a; 2001b; Tan and Wu, 2003; Zhao et al., 2004). Urbanized areas were ordered dissipative structural systems, which should be more and more orderly in the process of urban development. The information

5. Conclusion From the perspective of system evolution, this study established a framework for the analysis of land system evolution forms based on the relationship between ascendency and overhead. Shaanxi Province was selected as a research case to evaluate the sustainability of land systems and analyze the changes in the land system evolution form of various geographic units in different periods. In general, the evolution of land systems in Shaanxi Province was in a fluctuation form, and its sustainability increased first and then decreased. Among them, the changes in the Loess Plateau were particularly dramatic, and its evolution during 1990–2000 and 2005–2010 reached an optimization form, while its sustainability was only 0.2682 in 2010–2015. The evolution of land systems in the Guanzhong Basin had been in a less sustainable form of fluctuation. The land system evolution in Qinba Mountain was highly sustainable; except for the fluctuation forms during 1980–1990 and 2005–2010, the rest of the period was in optimized forms. All three geographic units evolved in an optimization form between 1990 and 2000. During 2000–2005 and 2010–2015, the sustainability of land system evolution in Shaanxi Province increased from north to south; it decreased from north to south during 2005–2010. By analyzing the 8

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changes of land system information entropy, it was known that it was feasible to identify the evolution form of land systems based on ascendency and overhead, and the research conclusions were credible.

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