Spatio-Temporal Change of Land Use in a Coastal Reclamation Area: a Complex Network Approach

sustainability

Article Spatio-Temporal Change of Land Use in a Coastal Reclamation Area: A Complex Network Approach

Caiyao Xu 1,2 , Lijie Pu 3,*, Fanbin Kong 1,2,* and Bowei Li 1

1 College of Economics and Management, Zhejiang A&F University, Hangzhou 311300, China; [email protected] (C.X.); [email protected] (B.L.) 2 Research Academy for Rural Revitalization of Zhejiang Province, Zhejiang A&F University, Hangzhou 311300, China 3 School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China * Correspondence: [email protected] (L.P.); [email protected] (F.K.)

Abstract: Coastal ecological protection and restoration projects aimed to restore and recover the ecological environment of coastal wetland with high-intensity human reclamation activity, while the integrity of the coastal wetland system with human reclamation activity and the ability of individual land use types to control the overall system were not fully considered. In this study, a six-stage land use conversion network was constructed by using a complex network model to analyze coastal land use dynamic changes in the coastal reclamation area located in eastern China from 1977 to 2016. The results showed that land use types had gradually transformed from being dominated by natural types to artiﬁcial types, and the speed of transformation was accelerating. The proportion of un-reclaimed area decreased from 93% in 1977 to 46% in 2007, and ﬁnally fell to 8% in 2014 and

2016. Tidal ﬂat and halophytic vegetation were the main output land use types, while cropland, woodland and aquaculture pond were the main input land use types. Cropland had the highest value

Citation: Xu, C.; Pu, L.; Kong, F.; of betweenness centrality, which played a key role in land use change from 1992 to 2014. The land use Li, B. Spatio-Temporal Change of system of the coastal reclamation area was the most stable in 2002–2007, followed by 1984–1992, and Land Use in a Coastal Reclamation the most unstable in 2007–2014. The Chinese and local government should carry out some measures Area: A Complex Network Approach. to improve the land use in coastal wetland ecosystems, including the allocation and integration of land Sustainability 2021, 13, 8690. https:// use for production space, living space, and ecological space, and develop multi-functionality of land doi.org/10.3390/su13168690 use to realize the coastal high-quality development and coastal ecological protection and restoration.

Academic Editors: Neil Ravenscroft, Keywords: coastal wetland; human reclamation activity; land use change; complex network model; Pingyang Liu and Ely Jose de Mattos Jiangsu; China

Received: 18 June 2021 Accepted: 26 July 2021 Published: 4 August 2021 1. Introduction

Publisher’s Note: MDPI stays neutral Land is an essential and increasingly scarce resource, both for the survival and pros- with regard to jurisdictional claims in perity of humanity, and for the maintenance of all terrestrial ecosystems [1,2]. Land cover published maps and institutional afﬁl- addresses the observed layer of soils and biomass that cover the earth’s surface [3], which iations. can be thus directly acquired in the ﬁeld as well as from remote sensing images [4]. Land use refers to all activities (e.g., grazing) of purposeful development and utilization of land resources and includes the land management practices (e.g., the presence of logging roads) [5], which cannot be always easily observable. Land use and land cover change can markedly impact the climate and the ecosystem at regional and global levels [6]. As Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. urbanization, resources and environmental issues become increasingly prominent, Land This article is an open access article Use and Cover Chang (LUCC) was launched in 1994 to address the problem of land use distributed under the terms and and land cover dynamics. Future Earth was launched in 2014 and continues to focus on conditions of the Creative Commons the issues of sustainability science worldwide [7]. Therefore, LUCC and its driving force Attribution (CC BY) license (https:// have been hot topics of global change research and sustainability science [8]. creativecommons.org/licenses/by/ Coastal wetlands, which have high ecological value and environmental function 4.0/). and provide various direct and indirect ecosystem services [9], play a key role in human

Sustainability 2021, 13, 8690. https://doi.org/10.3390/su13168690 https://www.mdpi.com/journal/sustainability Sustainability 2021, 13, 8690 2 of 16

development and face intense ecological stress from human activities. Socio-economic development with increasing of urbanization and industrialization is an important and critical cause of the degradation of coastal wetland ecosystems. In the past decades, coastal wetland reclamation for artificial land use (e.g., agriculture and construction land) has been a common practice around the world [10–13]. In recent decades, it has become an important way to meet the increasing demand for population growth and socio- economic development in China [14,15]. China reclaimed 2976.1 km2 of coastal wetland, and 910.8 km2 was developed for urbanization in the period of 2002–2018 [15]. High- intensity reclamation activities on coastal wetland ecosystems were studied from the perspective of soil properties [16,17], pollutions [18,19], and land use change [20]. Land use change is the direct result of interactions between humans and nature. Land use patterns can record the evolution of coastal wetlands with the influence of human development as well as the coastal ecological protection and restoration projects. Researchers focused on the characteristics of land use change, specifically from the perspectives of land use types, area of land use type [20], land use intensity [21], and rate of land use change [18], etc. However, little research has focused on the integrity of the coastal wetland system with human reclamation activity, and the ability of individual land use types to control the overall system were not fully considered. All of these traditional indicators can describe the features of land use change, but cannot fully describe the status and role of each land use type in the process of land use change. They also cannot reveal the relationship and influence among land use types in the coastal reclamation activities. Thus, a more scientific and effective method to analyze coastal wetland dynamic changes should be determined. In this aspect, the complex network theory is an appropriate tool that can be employed to analyze such dynamic changes holistically. As an important method of sociological research, the complex network model can better solve these problems. It analyzes the behavior of individuals in the system and the connections between individuals from the perspective of the system as a whole. This method had been widely used in the study of energy trade patterns [21], waste management [22], carbon dioxide emission [23], ecosystem management [24], transportation [25], and urban planning [15], etc. Many scholars have used complex network models to study land use change as well [15,21,26,27], from the perspective of the system as a whole, to identify the key land use types and evaluate the stability of the land use system. The coastal wetlands of Jiangsu Province are typical silty tidal flats, which are rich in resources, accounting for about 25% of the total coastal wetlands in China. Due to the input of sediment from the Yellow River and the Yangtze River and the special seabed geomorphic environment, the coastal wetlands in Jiangsu are characterized by dynamic growth. The “Outline of Jiangsu Coastal Reclamation Development Plan” was released by the Chinese government in 2009, which proclaimed Jiangsu Province’s intention to accomplish a coastal reclamation area of ~1800 km2 from 2010 to 2020, and to build ports, industrial zones and coastal towns [14,15]. The reclaimed areas were mainly concentrated in Yancheng City and Nantong City. Dongtai County is one of the most densely reclamation areas along the coast of Jiangsu. In the planning, the scale of coastal reclamation in Dongtai County went up to 667 km2 [28], which is more than 33% of Jiangsu Province’s reclamation plan. Therefore, Dongtai County had the largest reclamation scale in the coastal development of Jiangsu. High-intensity human reclamation activities are bound to cause drastic land use/cover changes in the coastal wetland ecosystem. Coastal ecological protection and restoration projects have been promoted in China nowadays with the release of a comprehensive 15-year plan (Master plan for major projects of national important ecosystem protection and restoration) since the year of 2020. Therefore, the whole land use change process should be systematically studied to understand the evolution and driving force of coastal wetland ecosystems with the effect of reclamation, which can effectively guide the formulation of ecological protection and restoration measures. With the implementation of coastal ecological protection and restoration project since 2020, a comprehensive and systematic understanding of the evolution process of coastal reclamation is significant to promote Sustainability 2021, 13, x FOR PEER REVIEW 3 of 17

Sustainability 2021, 13, 8690 implementation of coastal ecological protection and restoration project since 2020, a 3com- of 16 prehensive and systematic understanding of the evolution process of coastal reclamation is significant to promote the protection and restoration of coastal wetland ecosystems. The objectives of this study were to (i) build complex network models of the dynamic land use the protection and restoration of coastal wetland ecosystems. The objectives of this study conversion of coastal reclamation areas, (ii) depict the dynamic change processes of were to (i) build complex network models of the dynamic land use conversion of coastal reclamationcoastal reclamation areas, (ii) areas depict by thecalculating dynamic indicators change processes of complex of coastal networks, reclamation and (iii) areasanalyze by calculatingthe driving indicatorsforces of land of complex use change networks, in coastal and reclamation (iii) analyze areas. the driving forces of land use change in coastal reclamation areas. 2. Data and Methodology 2.2.1. Data Study and Area Methodology 2.1. StudyThe study Area area is located at Dongtai County, Jiangsu Province (32°33′N–32°57′N, 120°07The′E–120°53 study area′E), which is located is an at Dongtaiextremely County, fragile Jiangsu ecological Province environment (32◦330 N–32 (Figure◦570 1).N, ◦ 0 ◦ 0 120Dongtai07 E–120County53 hasE), a whichtotal area is anof 3175.67 extremely km fragile2, a coastline ecological of 85 environmentkm, and a tidal (Figure flat area1). Dongtaiof 156 km County2. It faces has the a Yellow total area Sea,of which 3175.67 is on km the2, edge a coastline of the Pacific of 85 km, Ocean and to athe tidal east. flat It areabelongs of 156 to the km 2subtropical. It faces the and Yellow warm–temperate Sea, which is transition on the edge zone, of thewhich Pacific is a Oceantypical tomon- the east.soon Itclimate belongs with to an the annual subtropical average and temperature warm–temperate of 14.6 transition °C, annual zone, precipitation which is aof typical 1051.0 ◦ monsoonmm, and annual climate average with an sunshine annual averageduration temperature of 2169.9 h. The of 14.6 terrainC, annualin Dongtai precipitation County is offlat 1051.0 with a mm, ground and elevation annual average of 1.4–5.1 sunshine m, most duration of which of is 2169.9 2.6–4.6 h. m. The The terrain coastal in Dongtaitidal flat Countyin Jiangsu is is flat currently with a groundexpanding elevation seaward, of 1.4–5.1which could m, most provide of which new island 2.6–4.6 resources m. The for coastaldevelopment tidal flat [18]. in JiangsuThe study is currentlyarea covers expanding the main seaward, part of the which reclamation could provide area in new Dongtai land resourcesCounty, including for development all typical [18 land]. The use studytypes areaalong covers with the the entire main process part of theof coastal reclamation recla- areamation in Dongtaiactivity (Figure County, 2). including all typical land use types along with the entire process of coastal reclamation activity (Figure2).

90°0'0"E 135°0'0"E 45°0'0"N µ Yellow Sea Jiangsu Province

Jiangsu Dongtai County Province 30°0'0"N Legend

Study area

1,000 100 km km 15°0'0"N

120°50'0"E Reclamation area Reclamation year Reclamation time Tidal flat - 0a Tidal flat Tiaozini 2013 3a Liangnan 2009 7a Cangdong 2005 11a Wumingchuan 2005 11a Sancangpian 1997 19a 1972 32°52'0"N Xinsanjiao 1982 34a Xindong 1980 36a Changsanjiao 1972 44a Note:Reclamation time was calculated based on 2016. 1982 2013 32°50'0"N

2005 1997 2009 1980 32°48'0"N

Legend

Reclamation area

km 32°46'0"N

Figure 1. The location of the study area. Sustainability 2021, 13, x FOR PEER REVIEW 4 of 17

Sustainability 2021, 13, 8690 4 of 16

Figure 1. The location of the study area.

Figure 2. TypicalTypical land use types in Dongtai coastal reclamation areas: ( A) tidal flat ﬂat after tide, ( B) newly newly built built dike dike and and bare bare land, (C) halophytic vegetation, (D) cropland in newly reclaimed area, (E) aquaculture pond, (F) integrated “wind-solar- land, (C) halophytic vegetation, (D) cropland in newly reclaimed area, (E) aquaculture pond, (F) integrated “wind-solar- fishing” power station, (G) cropland in earlier reclaimed area, (H) woodland, and (I) built-up area. All the photos were ﬁshing” power station, (G) cropland in earlier reclaimed area, (H) woodland, and (I) built-up area. All the photos were taken by Caiyao Xu in 2016. taken by Caiyao Xu in 2016.

2.2.2.2. Data Data Sources Sources and and Processing Processing SevenSeven remote remote sensing sensing images images (e.g., (e.g., 1977, 1977, 1984, 1984, 1992, 1992, 2002, 2002, 2007, 2007, 2014 2014 and and 2016) 2016) of the of Dongtaithe Dongtai coastal coastal reclamation reclamation area area were were used used in inthis this study. study. Table Table 11 showed thethe detaileddetailed informationinformation of of the the images. images. The The dates dates of of the the imag imageses were were selected in the growth period of plants.plants. The geometricgeometric correction, correction, spatial spatial registration registration technology technology and and other other operations operations were wereprocessed processed with with ENVI ENVI 5.3 software. 5.3 software. Then, Then, the imagesthe images were were clipped clipped and and resampled resampled to the to thesame same boundary boundary and and the samethe same resolution resolution (30 m)(30 by m) using by using ArcGIS ArcGIS 10.5 software.10.5 software. Supervised Super- visedclassification classification and visual and visual interpretation interpretation were combinedwere combined to interpret to interpret the seven the remote seven sensingremote sensingimages, images, with a classificationwith a classification precision precision of over of 85%. over The85%. accuracy The accuracy of classification of classification was waschecked checked through through field field work. work. Thus, Thus, seven seven shapefiles shapefiles of land of use land maps use inmaps Dongtai in Dongtai coastal coastalreclamation reclamation area (Figure area 3(Figure) were 3) obtained were obtained to further to analyze.further analyze.

TableTable 1. The parameters of remote sensing images.

DateDate Satellite Satellite Sensor Sensor Spatial Spatial Resolution/m Resolution/m 2016/7/272016/7/27 GF2 GF2 PMS2 PMS2 3.24 3.24 2014/4/232014/4/23 HJ-1B HJ-1B CCD CCD 30 30 2007/6/172007/6/17 Landsat Landsat 5 5TM TM 30 30 2002/8/202002/8/20 Landsat Landsat 7 7ETM ETM 30 30 1992/6/7 Landsat 5 TM 30 1992/6/7 Landsat 5 TM 30 1984/8/4 Landsat 5 TM 30 1984/8/41977/4/20 Landsat Landsat 5 2TM TM 30 79 Note:1977/4/20 the GF2 and HJ-1B remoteLandsat sensing 2 image wasTM from the China Centre for Resources 79 Satellite Data and Note:Application the GF2 (http://www.cresda.com/CN/ and HJ-1B remote sensing, accessed image was on 28 from July 2021);the China the Landsat Centre 2–7 for remote Resources sensing Satellite images Datawere fromand theApplication Geospatial (http://www.cresda.com/CN/, Data Cloud (http://www.gscloud.cn/ accessed, accessed on 28 on July 28 July 2021); 2021). the Landsat 2–7 remote sensing images were from the Geospatial Data Cloud (http://www.gscloud.cn/, accessed on 28 July 2021). SustainabilitySustainability2021 2021, 13, 13, 8690, x FOR PEER REVIEW 55 of of 16 17

1977 1984 1992

2002 2007

Legend µ Tidal creek Tidal flat Cropland Woodland Aquaculture pond 2014 2016 Bare land Build-up area River Halophytic vegetation Grassland Road 0105 km

Figure 3. Land use maps of Dongtai coastal reclamation area from 1977 to 2016. Figure 3. Land use maps of Dongtai coastal reclamation area from 1977 to 2016. 2.3. Methodology 2.3.1.2.3. Methodology Complex Network Model 2.3.1.The Complex man-land Network system Model is a complex system consisting of nature, society and economy. ComplexThe networksman-land aresystem the is backbone a complex of system complex consisting systems, of whichnature, can society quantify and economy. system characteristicsComplex networks and analyze are the the backbone characteristics of complex of the systems, entire network which can system quantify to determine system char- the interactionacteristics of and various analyze factors the andcharacteristics the state of theof the influencing entire network factors [system29]. Therefore, to determine complex the networkinteraction models of various help to factors understand and the the state complex of the dynamic influencing change factors of land [29]. use Therefore, systems [com-30]. Complexplex network networks models were help constructed to understand based the on complex the land dynamic use transfer change matrix, of land to analyze use systems the land[30]. use Complex change networks process, using were the constructed igraph package based [on15] the of Rland software use transfer (R core matrix, team, version to ana- 4.0.5)lyze the in this land study. use change Land process, use types using were the the igraph nodes package of the network,[15] of R software and the (R conversion core team, betweenversion different4.0.5) in landthis study. use types Land was use the type connections were the of thenodes network of the edge.network, The keyand indicesthe con- ofversion the network, between including different theland output/input use types was degree the connection of nodes, of betweenness the network centralityedge. The ofkey nodes,indices average of the shortestnetwork, path including and clustering the output coefficient,/input degree were of calculated nodes, betweenness respectively bycentral- the functionsity of nodes, of degree, average betweenness, shortest path mean and distance,clustering and coefficient, transitivity were in calculated the igraph respectively package. by the functions of degree, betweenness, mean distance, and transitivity in the igraph 2.3.2. Shannon Entropy Method package. Entropy can generally be defined as a measure of chaos or the disorder of a system. Claude2.3.2. Shannon E. Shannon Entropy (1948) Method introduced this concept to describe the uncertainty of an information source; therefore, it is usually called the Shannon Entropy Index [31]. The entropy Entropy can generally be defined as a measure of chaos or the disorder of a system. concept is a quantitative measure of the disorder of thermodynamic systems, which is Claude E. Shannon (1948) introduced this concept to describe the uncertainty of an infor- employed to identify the most probable spatial structure of a system capable of adapting to numerousmation source; uncertain therefore, spatial it states. is usually In this call study,ed the the Shannon characteristics Entropy ofIndex land [31]. use conversionThe entropy concept is a quantitative measure of the disorder of thermodynamic systems, which is Sustainability 2021, 13, 8690 6 of 16

were quantitatively analyzed through the Shannon Entropy Index and Equilibrium Degree. The Shannon Entropy Index (H) is a measure of the degree of the order of land use conversion. The value of H reﬂects the number of land use types and the uniformity of the area distribution of each land use type. The larger the value of H, the more land use types, the smaller the area difference between each land use type, and the more mature the land use system. The calculation formula of H is as follows [32]:

N Ai Pi = = Ai/ ∑ Ai (1) A i

N H = − ∑ Pi log Pi (2) i=1

where Pi is the ratio of the area of land use type i to the total area; Ai is the area of land use type i; N is the total number of land use types; A is the total area of the study area. Constructing the Equilibrium Degree (ED) of a land use system based on the concept of Shannon entropy, ED refers to the ratio of the actual value H to the maximum value Hmax, which is used to describe the difference of area size between land use types and the structural pattern of each land use type. The greater the value of ED, the stronger the homogeneity of the land use system. The calculation formula of ED is as follows [33]:

H ∑N P log P ED = = − i=1 i i (3) Hmax log N

2.3.3. Stability Analysis of Land Use System The Shannon Entropy Index could also be applied into the evaluation of the stability of land use systems. For land use systems, the sum of the largest change area in a certain period is equal to the total area of the study area. The proportion of the transformation area of land use type i to the total area of land use type i in a certain period can be regarded as the probability of event occurrence (Qi). Therefore, in the process of land use change within a certain period (T), the formula of land use system Shannon Entropy Index (H’) could be built as follows: F + F Q = in out (4) i T × A N 0 H = − ∑ Qi log Qi (5) i=1 where, the amount of change (area) from a certain type of land to another type of land is called “transfer-out flow” (Fin), and the amount of change (area) from other types of land to that type of land is called “Fout”. The sum of the transfer flow is the “land use transfer flow” of the land use type in a specific period of time (T), which represents the total amount of all participating land use changes in the land use type. A is the total area of the study area.

3. Results 3.1. Spatial Distribution Characteristics of Land Use Change in Coastal Reclamation Area Coastal land use types changed obviously with the influence of human activity and reclamation projects (Figure3). Figure4 shows the area of each land use type in a study area from 1977 to 2016. The total area of the study area is about 16,031.5 hm2. Tidal flat and halophytic vegetation constituted the key land use types of an unreclaimed area, and other land use types mainly appeared in reclamation areas. The proportion of unreclaimed area decreased from 93% in 1977 to 46% in 2007, and finally fell to 8% in 2014 and 2016, of which the area ratio of halophytic vegetation was only about 0.8%. The land use types after reclamation were mainly aquaculture pond, cropland, woodland, and grassland. The area of aquaculture pond increased gradually from 1977 to 2007, which was from 10.13% to 30.12% and 33.16%, respectively, in 2014 and 2016, and the rate of growth also Sustainability 2021, 13, x FOR PEER REVIEW 7 of 17

Sustainability 2021, 13, 8690 7 of 16

from 10.13% to 30.12% and 33.16%, respectively, in 2014 and 2016, and the rate of growth alsoaccelerated. accelerated. The The proportion proportion of cropland of cropland also also increased increased to 17.31% to 17.31% and and 18.75% 18.75% in 2014 in 2014 and and2016, 2016, respectively. respectively.

Land use types

Aquaculture pond Bare land Built-up area

2 Cropland hm

Grassland

Halophytic vegetation

Area / River Road Tidal creek Tidal flat Woodland 0 5000 10,000 15,000

1977 1984 1992 2002 2007 2014 2016 Year

Figure 4. Figure 4. AreaArea of of each each land land use use type type in in the the Dongta Dongtaii coastal coastal reclamation reclamation area area from from 1977 to 2016. 3.2. Land Use Change Characteristics Based on Complex Network Model 3.2. Land Use Change Characteristics Based on Complex Network Model Six complex network models from 1977 to 2016 are shown in Figure5. In different periods,Six complex the land network use transitions models between from 1977 different to 2016 land are use shown types in were Figure frequent, 5. In different and the periods,network the was land correspondingly use transitions complicated, between diff especiallyerent land in use 2007–2014. types were However, frequent, due and to the the networkshort time was span, correspondingly the land use complicated, transition network especially was in relatively 2007–2014. simple However, in the due period to the of short2014–2016. time span, Table 2the shows land theuse output transition and netw inputork degree was ofrelatively nodes in simple transition in the networks period inof 2014–2016.each period Table in the 2 studyshows area.the output Tidal flatand and input halophytic degree of vegetation nodes in transition were the mainnetworks output in eachland period use types. in the The study output/input area. Tidal ratio flat ofand the halophytic tidal flat was vegetation 3, 1, 3, 2.5, were and the 7 inmain the periodsoutput landof 1977–1984, use types. 1984–1992, The output/input 1992–2002, ratio 2002–2007 of the tidal and flat 2007–2014, was 3, 1, 3, respectively. 2.5, and 7 in Thethe periods ratio of ofoutput/input 1977–1984, 1984–1992, of the tidal 1992–2002, flat gradually 2002–2007 increased and over2007–2014, time, and respectively. reached its The maximum ratio of output/inputduring the period of the of tidal 2007–2014, flat gradually indicating increased that the over intensity time, of and reclamation reached its activities maximum had duringbeen increasing. the period The of 2007–2014, output/input indicating ratio of that halophytic the intensity vegetation of reclamation was 6, 1.5, activities 3.5, 1.67, had and been9 in 1977–1984,increasing. 1984–1992,The output/input 1992–2002, ratio 2002–2007 of halophytic and vegetation 2007–2014, was respectively. 6, 1.5, 3.5, Cropland,1.67, and 9woodland in 1977–1984, and aquaculture1984–1992, 1992–2002, ponds were 2002–2007 the main and input 2007–2014, land use respectively. types, and their Cropland, ratio of woodlandoutput/input and was aquaculture mainly between ponds 0were and the 1. Overall, main input tidal land flat was use antypes, important and their transfer-out ratio of output/inputland use type, was and mainly its area between decreased 0 and from 1. Overall, 10,485.87 tidal to 1127.62 flat was hm an2 importantduring the transfer- years of out1977–2016, land use mainly type, and being its transferred area decreased to grassland, from 10,485.87 woodland to 1127.62 and aquaculture hm2 during land. the years of 1977–2016, mainly being transferred to grassland, woodland and aquaculture land. 3.3. The Recognition of Key Land Use Types The values of betweenness centrality of nodes are presented in Figure6. Cropland had the highest value of betweenness centrality in the transition network in the period of 1992–2014 (Figure6), which indicated that cropland had the most vital status and role in land use change processes in the Dongtai coastal reclamation land use system. Halophytic vegetation was also found to have a high betweenness centrality, which was second only to that of cropland in the period of 2002–2007. Large areas of halophytic vegetation were converted to woodland, grassland, and bare land from 1990 to 2018. Overall, it could be seen that in the six periods from 1977 to 2016, the key land use types in the study area varied significantly, the track of which was tidal flat (1977–1984, with the value of 7) → river and halophytic vegetation (1984–1992, with the value of 13 and 12 respectively) → cropland (1992–2002, with the value of 9) → cropland (2002–2007, with the value of 20) → cropland (2007–2014, with the value of 6) → aquaculture pond (2014–2016, with the value of 5). Sustainability 2021, 13, 8690 8 of 16 Sustainability 2021, 13, x FOR PEER REVIEW 8 of 17

Halophytic River vegetation Woodland Cropland

Tidal flat Tidal flat Aquaculture Grassland pond

Tidal creek Tidal creek River

Aquaculture Woodland pond Road

Road Halophytic Cropland vegetation Grassland

1977–1984 1984–1992

Aquaculture Woodland Cropland pond Cropland

Tidal flat Tidal flat

Aquaculture pond Build-up area

Tidal creek Tidal creek River River

Woodland Build-up area

Halophytic Halophytic vegetation Grassland vegetation Grassland

1992–2002 2002–2007

Woodland River Cropland Tidal flat Aquaculture pond Woodland Tidal flat Road

River

Bare land Tidal creek Grassland

Halophytic vegetation

Aquaculture Halophytic Build-up area pond vegetation

Grassland Road Build-up area Bare land Cropland

2007–2014 2014–2016

Figure 5. Complex network models of coastal reclamation areas duri duringng different periods. Note Note:: the the arrow arrow represents the direction of landland useuse change,change, and and the the thickness thickness of of the the line line represents represents the the transition transition area area (relative (relative amount) amount) between between two landtwo landuse types. use types.

Sustainability 2021, 13, 8690 9 of 16

Table 2. Output/input degree of nodes in conversion networks during different periods.

Land Use Types Period Indicators TC TF CL WL AP BL BA RV HV GL RD Output 1 6 0 0 0 0 0 1 6 3 0 1977–1984 Input 2 2 1 4 1 0 0 2 1 2 2 Ratio 0.50 3.00 0.00 0.00 0.00 - - 0.50 6.00 1.50 0.00 Output 1 2 2 3 3 0 0 3 3 4 4 1984–1992 Input 2 2 5 5 3 0 0 4 2 3 0 Ratio 0.50 1.00 0.40 0.60 1.00 - - 0.75 1.50 1.33 - Output 3 6 4 2 1 0 0 3 7 3 0 1992–2002 Input 2 2 4 5 4 0 2 5 2 3 0 Ratio 1.50 3.00 1.00 0.40 0.25 - 0.00 0.60 3.50 1.00 - Output 2 5 4 0 2 0 2 5 5 3 0 2002–2007 Input 1 2 5 3 6 0 1 3 3 4 0 Ratio 2.00 2.50 0.80 0.00 0.33 - 2.00 1.67 1.67 0.75 - Output 5 7 6 4 4 0 0 4 9 3 0 2007–2014 Input 2 1 6 6 6 3 3 3 1 5 8 Ratio 2.50 7.00 1.00 0.67 0.67 0.00 0.00 1.33 9.00 0.60 0.00 Output 7 3 0 1 1 4 0 1 0 4 1 2014–2016 Input 0 0 2 3 4 1 2 0 0 2 0 Sustainability 2021, 13, x FOR PEER REVIEW 10 of 17 Ratio - - 0.00 0.33 0.25 4.00 0.00 - 0.00 2.00 - Note: TC-Tidal creek; TF-Tidal ﬂat; CL-Cropland; WL-Woodland; AP-Aquaculture pond; BL-Bare land; BA- Built-up area; RV-River; HV-Halophytic vegetation; GL-Grassland; RD-Road.

Aquaculture pond Grassland Woodland Cropland Halophytic vegetation Tidal creek Tidal flat River 25

Betweenness centrality Betweenness 5

0 1977–1984 1984–1992 1992–2002 2002–2007 2007–2014 2014–2016 Period

FigureFigure 6.6. BetweennessBetweenness centralitycentrality ofof nodesnodes inin conversionconversion networksnetworks duringduring differentdifferent periods.periods. 3.4. Stability Evaluation of Land Use System 3.4. Stability Evaluation of Land Use System The average path length of conversion networks was all less than two in the six periodsThe in average the study path area, length and of theconversion speciﬁc networ value wasks was between all less 1.44 than and two 1.95 in the (Figure six peri-7), indicatingods in the study that the area, network and the had specific poor stability,value was and between land use 1.44 type and conversions 1.95 (Figure were 7), indicat- easily conducteding that the [30 network]. In most had cases, poor two stability, land useand types land coulduse type be connectedconversions as were long aseasily another con- landducted use [30]. type In was most used cases, as a two medium. land use The type averages could path be lengthconnected of the as conversionlong as another networks land showeduse type a was ﬂuctuating used as trenda medium. from 1977 The toaverage 2016. Thepath order length of of the the average conversion path lengthnetworks of networksshowed a influctuating each study trend period from was 1977 2002–2007 to 2016. >The 1984–1992 order of >the 1977–1984 average >path 2014–2016 length of > 1992–2002networks in > 2007–2014.each study Theperiod land was use 2002–2007 system was > the1984–1992 most stable > 1977–1984 in 2002–2007, > 2014–2016 with the > average1992–2002 path > 2007–2014. length value The of land 1.95, use followed system by was 1984–1992 the most with stable the in average 2002–2007, path with length the average path length value of 1.95, followed by 1984–1992 with the average path length value of 1.82; the land use system was the most unstable in 2007–2014, with the average path length value of 1.32. During 2007–2014, two or more reclamation areas were built, and new land use types, such as bare land, also appeared. Therefore, the high intensity of reclamation activity promoted the interaction among land use types, and the new land use types improved the connectivity and accessibility of the network, resulting in the most unstable land system during this period. The clustering coefficient of the networks showed a fluctuating trend that first increased and then decreased (Figure 7). The clustering coefficient was the smallest in 2014–2016, and the largest in 2002–2007. The Shannon entropy method was used to further explore the complexity and balance of land use systems in the study area from 1977 to 2016. At the seven time points from 1977 to 2016 (Figure 8a), the Shannon Entropy Index of the land use system first increased and then turned out to be stable, indicating that the land use system became more and more disorderly during the study period and then reached a new equilibrium. The Shannon Entropy Index was the largest in 2014, and then slightly decreased in 2016. At the same time, the Equilibrium Degree also showed a trend of first increasing and then becoming stable, which showed that the homogeneity of the land use system is increasing. During the process of land use change in the study area (Figure 8b), the disturbance intensity of the land use system by human activities varied greatly in different periods. Among them, the degree of human disturbance to the land use system from 1977 to 1984 was low, so that the intensity of coastal reclamation and development activities in the study area was low. The degree of human disturbance to the land use system from 1984 Sustainability 2021, 13, 8690 10 of 16

Sustainability 2021, 13, x FOR PEER REVIEW 11 of 17 value of 1.82; the land use system was the most unstable in 2007–2014, with the average path length value of 1.32. During 2007–2014, two or more reclamation areas were built, and new land use types, such as bare land, also appeared. Therefore, the high intensity to of2014 reclamation was relatively activity high. promoted During the this interaction period, around among land92% useof the types, study and area the newhad been land encircled,use types land improved use types the were connectivity diversified, and and accessibility the development of the network,intensity was resulting maintained in the at mosta high unstable level. The land intensity system duringreduced this from period. 2014 Theto 2016, clustering and the coefficient land use of system the networks turned intoshowed a relatively a fluctuating stable state. trend that first increased and then decreased (Figure7). The clustering coefficient was the smallest in 2014–2016, and the largest in 2002–2007. 2.2 0.8 0.68 0.70 0.68 2 0.63 1.95 0.6 1.8 0.53 1.82

1.6 0.41 0.4

1.46 1.43 1.4 1.44 0.2 Average path length Average 1.32 coefficient Clustering 1.2

1 0 1977–19841984–19921992–20022002–20072007–20142014–2016 FigureFigure 7. 7.AverageAverage path path length length and and clustering clustering coefficien coefﬁcientt of of conversion conversion networ networksks during different periods.periods. Note: Note: the the black black polyline polyline indicates indicates the the average average path path length length (left (left Y Y axis), axis), and and the red polyline indicatesindicates the the aggregation aggregation coefficient coefﬁcient (right (right Y Y axis). axis).

The Shannon entropy method was used to further explore the complexity and balance of land(a) use systems in the study area from 1977 to 2016. At the seven time points from 1977 to 2016 (Figure8a), the Shannon Entropy Index of the land use system ﬁrst increased and )

thenH turned out to be stable, indicating that the land use system became more and more disorderly during the study period and then reached a new equilibrium. The Shannon Entropy Index was the largest in 2014, and then slightly decreased in 2016. At the same time, the Equilibrium Degree also showed a trend of ﬁrst increasing and then becoming stable, which showed that the homogeneity of the land use system is increasing. During the process of land use change in the study area (Figure8b), the disturbance intensity of the 0.6 0.7 land use system by human activities varied greatly in different periods. Among them, Equilibrium Degree the degree Index( Shannon Entropy of human disturbance to the land use system from 1977 to 1984 was low, so that the intensity of coastal reclamation and development activities in the study area was low. The degree0.0 of 0.5 human 1.0 disturbance 1.5 to the land use system from 1984 to 2014 was relatively high. 1977 1984 1992 2002 2007 2014 2016 During this period, around 92% of the study area had been encircled, land use types were diversiﬁed,(b) and the development intensity was maintained at a high level. The intensity reduced from 2014 to 2016, and the land use system turned into a relatively stable state. ) H' Equilibrium Degree Equilibrium Shannon Entropy Index( Entropy Shannon 0.72 0.76 0.80 0.0 0.5 1.0 1.5 2.0 1977-19841977–1984 1984–1992 1984-19921992–2002 1992-20022002–2007 2002-20072007–2014 2007-2014 2014-20162014–2016

Figure 8. The Shannon Entropy Index and Equilibrium Degree of the land use system. Note: the gray bar graph represents the Shannon Entropy Index (left Y axis), and the red triangle dot graph represents the Equilibrium Degree (right Y axis). Sustainability 2021, 13, x FOR PEER REVIEW 11 of 17

to 2014 was relatively high. During this period, around 92% of the study area had been encircled, land use types were diversified, and the development intensity was maintained at a high level. The intensity reduced from 2014 to 2016, and the land use system turned into a relatively stable state.

2.2 0.8 0.68 0.70 0.68 2 0.63 1.95 0.6 1.8 0.53 1.82

1.6 0.41 0.4

1.46 1.43 1.4 1.44 0.2 Average path length Average 1.32 coefficient Clustering 1.2

1 0 1977–19841984–19921992–20022002–20072007–20142014–2016 Sustainability 2021, 13, 8690 Figure 7. Average path length and clustering coefficient of conversion networks during different11 of 16 periods. Note: the black polyline indicates the average path length (left Y axis), and the red polyline indicates the aggregation coefficient (right Y axis).

(a) ) H 0.6 0.7 Equilibrium Degree Shannon Entropy Index( Shannon Entropy 0.0 0.5 1.0 1.5 1977 1984 1992 2002 2007 2014 2016

(b) ) H' Equilibrium Degree Equilibrium Shannon Entropy Index( Entropy Shannon 0.72 0.76 0.80 0.0 0.5 1.0 1.5 2.0 1977-19841977–1984 1984–1992 1984-19921992–2002 1992-20022002–2007 2002-20072007–2014 2007-2014 2014-20162014–2016

Figure 8.8. TheThe ShannonShannon EntropyEntropy IndexIndex andand EquilibriumEquilibrium DegreeDegree ofof thethe landland useuse system.system. Note:Note: thethe gray barbar graphgraph representsrepresents thethe ShannonShannon EntropyEntropy IndexIndex (left(left YY axis),axis), andand thethe redred triangletriangle dotdot graphgraph representsrepresents thethe EquilibriumEquilibrium DegreeDegree (right(right YY axis).axis). 4. Discussion 4.1. Driving Factors of Land Use Change in Coastal Reclamation Area Dongtai County is the largest county-level city in Jiangsu Province, with the largest area of coastal wetland. It could also be seen from Figure9 that Dongtai County’s coastal reclamation activity had experienced two high stages since 1970, namely from 1970 to 1985 and 1995 to 2015, with a cumulative reclaimed area of 395.50 km2. The size of the reclaimed area in 1970–1985 accounted for 24.82% of the total reclaimed area, and the speed of coastal reclamation was 6.58 km2/a. During this period, the conflict between man and land gradually appeared. The demand for cropland resources was the main reason for the formation of the first high stage. A new round of coastal reclamation craze set off between 1995 and 2015. During this period, the reclaimed area reached 74.59% of the total reclaimed area, and the speed of coastal reclamation reached 14.84 km2/a. Among them, the speed of confinement in the first five years (1995–2000) of the construction of the “Maritime Eastern Jiangsu” reached 18.56 km2/a, which was the fastest period of Dongtai coastal reclamation activity from 1970 to 2015. In general, the tendency of Dongtai coastal reclamation activity was consistent with the Jiangsu Province, and even China. Sustainability 2021, 13, x FOR PEER REVIEW 12 of 17

4. Discussion 4.1. Driving Factors of Land Use Change in Coastal Reclamation Area Dongtai County is the largest county-level city in Jiangsu Province, with the largest area of coastal wetland. It could also be seen from Figure 9 that Dongtai County’s coastal reclamation activity had experienced two high stages since 1970, namely from 1970 to 1985 and 1995 to 2015, with a cumulative reclaimed area of 395.50 km2. The size of the reclaimed area in 1970–1985 accounted for 24.82% of the total reclaimed area, and the speed of coastal reclamation was 6.58 km2/a. During this period, the conflict between man and land gradually appeared. The demand for cropland resources was the main reason for the formation of the first high stage. A new round of coastal reclamation craze set off between 1995 and 2015. During this period, the reclaimed area reached 74.59% of the total reclaimed area, and the speed of coastal reclamation reached 14.84 km2/a. Among them, the speed of confinement in the first five years (1995–2000) of the construction of the “Mari- time Eastern Jiangsu” reached 18.56 km2/a, which was the fastest period of Dongtai coastal Sustainability 2021, 13, 8690 12 of 16 reclamation activity from 1970 to 2015. In general, the tendency of Dongtai coastal reclamation activity was consistent with the Jiangsu Province, and even China.

Figure 9. DongtaiDongtai coastal reclamation area from 1970 to 2015 (modiﬁed(modified from reference [[34]).34]).

InIn this study,study, with with the the dynamic dynamic change change process process in coastalin coastal reclamation reclamation area, area, 9 to 119 to land 11 landuse types use types were were regarded regarded as nodes as nodes in a conversionin a conversion network, network, the conversion the conversion relationships relation- between land use types were regarded as edges, and the area of conversion between the ships between land use types were regarded as edges, and the area of conversion between land use types was used as the weight of edges. Therefore, the land use change process the land use types was used as the weight of edges. Therefore, the land use change process in each period (1977–1984, 1984–1992, 1992–2002, 2002–2007, 2007–2014, 2014–2016) was in each period (1977–1984, 1984–1992, 1992–2002, 2002–2007, 2007–2014, 2014–2016) was regarded as a complex network system composed of nodes and edges. Comprehensively, regarded as a complex network system composed of nodes and edges. Comprehensively, considering the results of the analysis above and other references, the typical and common considering the results of the analysis above and other references, the typical and common land use types were selected to depict the land use change process from sea to land in the land use types were selected to depict the land use change process from sea to land in the coastal reclamation area. The theoretical and actual evolution paths of typical land use coastal reclamation area. The theoretical and actual evolution paths of typical land use conversions in coastal reclamation areas were concluded in Figure 10. Theoretically, a high conversions in coastal reclamation areas were concluded in Figure 10. Theoretically, a salinity of soil limits the rapid expansion of agriculture, with the natural succession of high salinity of soil limits the rapid expansion of agriculture, with the natural succession vegetation instead. In the initial stage, the reclaimed area was developed as an aquaculture ofpond, vegetation which can instead. produce In the economic initial beneﬁtsstage, the and reclaimed also to a certainarea was extent developed promote as soil an desali-aqua- culturenation. pond, With the which maturation can produce of soil, economic reclamation benefits areas and could also be to reclaimed a certain extent for agriculture, promote soilthen desalination. built-up areas With can appearthe maturation and even of form soil, settlements. reclamation Therefore, areas could the theoreticalbe reclaimed evolu- for agriculture,tion path is then sea → built-uptidal ﬂat areas→ halophytic can appear vegetation and even form→ aquaculture settlements. pond Therefore,→ cropland the the-→ oreticalbuilt-up evolution area. With path the wideis sea application→tidal flat of→ newhalophytic salt-tolerant vegetation species → and aquaculture the improvement pond→ croplandof rapid desalination→ built-up area. technology With the [17 wide], the application process and of time new of salt-tolerant the land use species evolution and path the improvementin coastal reclamation of rapid areasdesalination has fundamentally technology shortened.[17], the process Therefore, and time the actual of the evolution land use Sustainability 2021, 13, x FOR PEER REVIEWevolutionpath is different path in from coastal the reclamation theoretical path.areas Forhas example,fundamentally the sea shortened. can be directly Therefore, used13 of the for 17

actualaquaculture, evolution and path tidal ﬂatis different or newly from reclaimed the theoretical areas can bepath. developed For example, for cropland the sea because can be directlyof salt-tolerant used for crops. aquaculture, and tidal flat or newly reclaimed areas can be developed for cropland because of salt-tolerant crops.

Figure 10. The evolution path of typical land use changes in coastal reclamation areas (modiﬁed from [35]).

Figure 10. The evolution path of typical land use changes in coastal reclamation areas (modified from [35]).

The driving factors of land use change can be divided into natural factors (weather, geomorphology, plant succession, etc.) and artificial factors (socio-economic, institutional, policy and technological factors, etc.). In general, with the development of social economy and the growth of populations, the driving force of land use change in coastal reclamation areas has changed accordingly, as shown in Figure 11. China’s coastal reclamation activity has developed rapidly since the 1950s [36]. During this period, there was less pressure from the population and economic development, and coastal area was mainly reclaimed to expand salt fields. Coastal land use change was mostly obviously affected by geology and geomorphology, and ocean dynamics. Then, many big reclamation projects were carried out for agriculture from the mid-1960s to the 1970s, especially in the coastal areas of Zhejiang, Jiangsu and Fujian [14]. In these initial stages, the driving forces of land use change were mainly natural factors, supplemented by human activities. By the 1990s, a new round of coastal reclamation occurred in China with more than 30% of coastal wetlands reclaimed in order to meet the needs of rapid urbanization and industrialization [36]. Because of high salinity land and low levels of desalination technology, most coastal reclamation areas were developed for aquaculture. In 1995, the “Maritime Eastern Jiangsu” cross-century marine economic development project was proposed. Many coastal reclamation projects were carried out to accommodate rapid development of the marine economy. The “Outline of Jiangsu Coastal Reclamation Development Plan” proclaimed Jiangsu Province’s intention to accomplish a coastal reclamation area of ~1800 km2 from 2010 to 2020, and to build ports, industrial zones and coastal towns [14,15]. Since the 21st century, the driving force of coastal land use change has primarily been artificial factors. Sustainability 2021, 13, 8690 13 of 16

The driving factors of land use change can be divided into natural factors (weather, geomorphology, plant succession, etc.) and artificial factors (socio-economic, institutional, policy and technological factors, etc.). In general, with the development of social economy and the growth of populations, the driving force of land use change in coastal reclamation areas has changed accordingly, as shown in Figure 11. China’s coastal reclamation activity has developed rapidly since the 1950s [36]. During this period, there was less pressure from the population and economic development, and coastal area was mainly reclaimed to expand salt fields. Coastal land use change was mostly obviously affected by geology and geomorphology, and ocean dynamics. Then, many big reclamation projects were carried out for agriculture from the mid-1960s to the 1970s, especially in the coastal areas of Zhejiang, Jiangsu and Fujian [14]. In these initial stages, the driving forces of land use change were mainly natural factors, supplemented by human activities. By the 1990s, a new round of coastal reclamation occurred in China with more than 30% of coastal wetlands reclaimed in order to meet the needs of rapid urbanization and industrialization [36]. Because of high salinity land and low levels of desalination technology, most coastal reclamation areas were developed for aquaculture. In 1995, the “Maritime Eastern Jiangsu” cross-century marine economic development project was proposed. Many coastal reclamation projects were carried out to accommodate rapid development of the marine economy. The “Outline of Jiangsu Coastal Reclamation Development Plan” proclaimed Jiangsu Province’s intention 2 Sustainability 2021, 13, x FOR PEER REVIEWto accomplish a coastal reclamation area of ~1800 km from 2010 to 2020, and to14 buildof 17 ports, industrial zones and coastal towns [14,15]. Since the 21st century, the driving force of coastal land use change has primarily been artificial factors.

FigureFigure 11. 11. DrivingDriving factors factors of of land land use use change change in in the the Jiangsu Jiangsu coastal coastal reclamation reclamation area. area.

4.2.4.2. Land Land Use Use Optimization Optimization Measures Measures CoastalCoastal reclamation reclamation activities activities have have resulted resulted in in serious serious ecological ecological and and environmental environmental problemsproblems [9]. [9]. As natural landland useuse types types and and the the original original forms forms of of coastal coastal wetland wetland ecosystem, ecosystem,tidal tidal ﬂat andflat and halophytic halophytic vegetation vegetation had had important important ecosystem ecosystem functions functions and and ecological ecologi- calvalue. value. With With the the increasing increasing development development of of coastal coastal zones, zones, naturalnatural landland use types have beenbeen largely largely reclaimed reclaimed for for the the needs needs of of ec economiconomic growth growth and human populations, the the phenomenonphenomenon ofof which which has has appeared appeared in many in many coastal coastal zones allzones around all the around world [the9,12 ,world36,37]. [9,12,36,37].The expansion The and expansion key role and of cropland key role hasof cr mainlyopland beenhas mainly the outcome been the of theoutcome government of the governmentpolicy, the “ Outlinepolicy, the of Jiangsu “Outline Coastal of Jiangsu Reclamation Coastal DevelopmentReclamation Development Plan”, which Plan determined”, which determinedthe land use the pattern land use of pattern coastal of reclaimed coastal re areasclaimed with areas 60% with of agricultural 60% of agricultural land, 20% land, of 20%construction of construction land and land 20% and of 20% ecological of ecological land. land. Thus,Thus, China China released released a a comprehensive comprehensive 15-year 15-year plan plan ( (NationalNational Master Master Plan Plan for for Major EcosystemEcosystem Protection Protection and and Restoration Restoration Projects Projects)) for for ecological ecological protection protection and and restoration restoration with with ninenine major major ecological ecological conservation conservation projects, projects, setting setting a target a target to improve to improve the thecountry’s country’s environment and achieve the goal of building a Beautiful China by 2035 [21]. Coastal ecological protection and restoration projects are one of the nine special plans, which aim to carry out the ecological protection and restoration of the sea and tidal flats, the shoreline, the estuary bay, typical marine ecosystems (such as mangroves and coral reefs), tropical rainforest protection, and the prevention of invasive species such as Spartina alterniflora. Therefore, the land use change under the coastal ecological protection and restoration project should be further studied in the future and the possible evolution path of land use change is depicted in Figure 10. The main feature is that the artificial land use types would be restored to natural land use types. Natural land use types in coastal zones contained tidal flats, halophytic vegetation and other land use types with high ecological value. Nowadays, the Chinese government highly values the development of a high-quality marine economy [21]. The core content of land use optimization measures for coastal high- quality development should be the allocation and integration of production space, living space, and ecological space. Firstly, considering the limited land resources, fragile ecological environments and increasingly tense relationship between humans and nature, coastal protection should focus on the transformation from single function to multi-functionality of land use in coastal wetland ecosystems [21]. Secondly, with the strategy of “Land-Sea Coordination”, it should promote the coordinated improvement of social, economic and ecological functions of the land and ocean through scientific, systematic coordination of coastal resources, industries, ecologies and environments [38,39]. Thirdly, with the concept of “a community with a shared future for mankind”, the transformation from fragmented management to coordinated governance should be realized. It is an urgent need to establish a whole-scale, all-element, and systematic land use regulated Sustainability 2021, 13, 8690 14 of 16

environment and achieve the goal of building a Beautiful China by 2035 [21]. Coastal ecological protection and restoration projects are one of the nine special plans, which aim to carry out the ecological protection and restoration of the sea and tidal flats, the shoreline, the estuary bay, typical marine ecosystems (such as mangroves and coral reefs), tropical rainforest protection, and the prevention of invasive species such as Spartina alterniflora. Therefore, the land use change under the coastal ecological protection and restoration project should be further studied in the future and the possible evolution path of land use change is depicted in Figure 10. The main feature is that the artificial land use types would be restored to natural land use types. Natural land use types in coastal zones contained tidal flats, halophytic vegetation and other land use types with high ecological value. Nowadays, the Chinese government highly values the development of a high-quality marine economy [21]. The core content of land use optimization measures for coastal high- quality development should be the allocation and integration of production space, living space, and ecological space. Firstly, considering the limited land resources, fragile ecological environments and increasingly tense relationship between humans and nature, coastal protection should focus on the transformation from single function to multi-functionality of land use in coastal wetland ecosystems [21]. Secondly, with the strategy of “Land-Sea Coordination”, it should promote the coordinated improvement of social, economic and ecological functions of the land and ocean through scientific, systematic coordination of coastal resources, industries, ecologies and environments [38,39]. Thirdly, with the concept of “a community with a shared future for mankind”, the transformation from fragmented management to coordinated governance should be realized. It is an urgent need to establish a whole-scale, all-element, and systematic land use regulated system for the “mountains– rivers–forests–farmlands–lakes–grasslands” of coastal ecosystem. Finally, with the strategy of “ecology first, green development”, it requires us to optimize the construction logic and practical path of the bottom line of the development, to regulate the time and space order of the development and protection of coastal ecosystem, and to form the security and resilience of coastal ecosystems.

4.3. Limitations and Future Directions of the Study This study constructed complex network models of the Jiangsu coastal reclamation area and analyzed the integrity of the coastal wetland system with human reclamation activity and the ability of individual land use types to control the overall system. The data used in this study was limited in understanding the latest evolutionary features, which should be further studied in the future. Although the results provide insight into the spatial and temporal changes and the driving forces of land use in coastal reclamation areas, mainly by using a complex network approaches, further research is needed to tackle future challenges from new policy (e.g., high-quality marine economy and coastal ecological protection and restoration project) and to support the understanding of mechanisms that shape the land use patterns of coastal wetland ecosystems. It is necessary for future studies to consider the predictions of changes in man–land interactions under future land use development scenarios and management actions, such as coastal ecological protection and restoration projects, which aim to determine how to affect the supply capacity of coastal wetland ecosystems and to seek a win–win management policy for the government’s ecological planning. What’s more, the land use pattern of coastal wetlands to support the carbon neutrality should also be further studied. Future management policy should ensure the safety of ecological environments and achieve coastal high-quality development under future land use scenarios.

5. Conclusions This study introduced the complex network method to identify the key land use types, land use processes, and system stability of land use systems from 1977 to 2016 in the Dongtai coastal reclamation area, Eastern China. The following conclusions were made: Sustainability 2021, 13, 8690 15 of 16

(1) The land use types under the influence of coastal reclamation activities had gradually transformed from being dominated by natural types (tidal flat, halophytic vegetation, etc.) to artificial types (cropland, aquaculture pond, construction land, etc.), and the speed of transformation was accelerating. During the period of 1977 to 2016, the proportion of unreclaimed area decreased from 93% in 1977 to 46% in 2007, and finally fell to 8% in 2014 and 2016, of which the area ratio of halophytic vegetation was only about 0.8%. (2) Tidal flat and halophytic vegetation were the main output land use types, while cropland, woodland and aquaculture ponds were the main input land use types. Cropland had the highest value of betweenness centrality in the transition network in the period of 1992–2014. The key land use types during the six periods from 1977 to 2016 were tidal flat (1977–1984) → river and halophytic vegetation (1984–1992) → cropland (1992–2002) → cropland (2002–2007) → cropland (2007–2014) → aquaculture pond (2014–2016). (3) The average path length of conversion networks fluctuated between 1.44 and 1.96. Frequent conversions between different land use types led to poor stability of land use systems in coastal reclamation areas. The land use system was the most stable in 2002–2007, followed by 1984–1992; the land use system was the most unstable in 2007–2014. (4) Artificial factors were the main driving forces in the land use change of coastal reclamation areas. The core content of land use optimization measures for coastal high- quality development could be the allocation and integration of production space, living space, and ecological space, and could develop multi-functionality of land used in coastal wetland ecosystems.

Author Contributions: Data collection and analysis, C.X.; writing—original draft, C.X.; writing— review & editing, C.X., L.P., F.K. and B.L.; research design and methodology, C.X., L.P. and F.K.; constructive suggestions, B.L. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by the National Natural Science Foundation of China (No. 41230751), the Special Project of Cultivating Leading Talents in Philosophy and Social Science of Zhejiang Province (21YJRC12-2YB, 21YJRC2ZD), the Major Research Project of Humanities and Social Sciences in Colleges and Universities of Zhejiang Province (2021QN062), Research Development Fund of Zhejiang Agriculture and Forestry University (2020FR066). Acknowledgments: The authors thank the anonymous reviewers for their helpful and constructive comments that have greatly improved this paper. Conﬂicts of Interest: The authors declare no conﬂict of interest.

References 1. Zhou, Y.; Li, X.; Liu, Y. Land use change and driving factors in rural China during the period 1995-2015. Land Use Policy 2020, 99. [CrossRef] 2. Lambin, E.F.; Meyfroidt, P. Global land use change, economic globalization, and the looming land scarcity. Proc. Natl. Acad. Sci. USA 2011, 108, 3465–3472. [CrossRef] 3. Verburg, P.H.; van de Steeg, J.; Veldkamp, A.; Willemen, L. From land cover change to land function dynamics: A major challenge to improve land characterization. J. Environ. Manag. 2009, 90, 1327–1335. [CrossRef] 4. Lambin, E.F.; Linderman, M. Time series of remote sensing data for land change science. IEEE Trans. Geosci. Remote Sens. 2006, 44, 1926–1928. [CrossRef] 5. Lambin, E.F.; Turner, B.L.; Geist, H.J.; Agbola, S.B.; Angelsen, A.; Bruce, J.W.; Coomes, O.T.; Dirzo, R.; Fischer, G.; Folke, C. The causes of land-use and land-cover change: Moving beyond the myths. Glob. Environ. Chang. 2001, 11, 261–269. [CrossRef] 6. Lu, F.; Hu, H.; Sun, W.; Zhu, J.; Liu, G.; Zhou, W.; Zhang, Q.; Shi, P.; Liu, X.; Wu, X.; et al. Effects of national ecological restoration projects on carbon sequestration in China from 2001 to 2010. Proc. Natl. Acad. Sci. USA 2018, 115, 4039–4044. [CrossRef][PubMed] 7. Verburg, P.H.; Crossman, N.; Ellis, E.C.; Heinimann, A.; Hostert, P.; Mertz, O.; Nagendra, H.; Sikor, T.; Erb, K.-H.; Golubiewski, N.; et al. Land system science and sustainable development of the earth system: A global land project perspective. Anthropocene 2015, 12, 29–41. [CrossRef] 8. Lambin, E.F.; Geist, H.J.; Lepers, E. Dynamics of land-use and land-cover change in tropical regions. Annu. Rev. Environ. Resour. 2003, 28, 205–241. [CrossRef] 9. Choi, Y.R. Modernization, Development and Underdevelopment: Reclamation of Korean tidal ﬂats, 1950s–2000s. Ocean. Coast. Manag. 2014, 102 Pt B, 426–436. [CrossRef] 10. Sun, Z.; Sun, W.; Tong, C.; Zeng, C.; Yu, X.; Mou, X. China’s coastal wetlands: Conservation history, implementation efforts, existing issues and strategies for future improvement. Environ. Int. 2015, 79, 25–41. [CrossRef][PubMed] Sustainability 2021, 13, 8690 16 of 16

11. Cho, D.O. The evolution and resolution of conflicts on Saemangeum Reclamation Project. Ocean. Coast. Manag. 2007, 50, 930–944. [CrossRef] 12. Glaser, R.; Haberzettl, P.; Walsh, R.P.D. Land reclamation in Singapore, Hong Kong and Macau. GeoJournal 1991, 24, 365–373. [CrossRef] 13. Hoeksema, R.J. Three stages in the history of land reclamation in the Netherlands. Irrig. Drain. 2007, 56, S113–S126. [CrossRef] 14. Ma, Z.J.; Melville, D.S.; Liu, J.G.; Chen, Y.; Yang, H.Y.; Ren, W.W.; Zhang, Z.W.; Piersma, T.; Li, B. Rethinking China’s new great wall. Science 2014, 346, 912–914. [CrossRef][PubMed] 15. Chuai, X.W.; Huang, X.J.; Wu, C.Y.; Li, J.B.; Lu, Q.L.; Qi, X.X.; Zhang, M.; Zuo, T.H.; Lu, J.Y. Land use and ecosystems services value changes and ecological land management in coastal Jiangsu, China. Habitat Int. 2016, 57, 164–174. [CrossRef] 16. Kim, K.; Samaddar, S.; Chatterjee, P.; Krishnamoorthy, R.; Jeon, S.; Sa, T. Structural and functional responses of microbial community with respect to salinity levels in a coastal reclamation land. Appl. Soil Ecol. 2019, 137, 96–105. [CrossRef] 17. Xie, X.; Pu, L.; Zhu, M.; Meadows, M.; Sun, L.; Wu, T.; Bu, X.; Xu, Y. Differential effects of various reclamation treatments on soil characteristics: An experimental study of newly reclaimed tidal mudflats on the east China coast. Sci. Total Environ. 2021, 768, 144996. [CrossRef] 18. Tian, B.; Wu, W.T.; Yang, Z.Q.; Zhou, Y.X. Drivers, trends, and potential impacts of long-term coastal reclamation in China from 1985 to 2010. Estuar. Coast. Shelf Sci. 2016, 170, 83–90. [CrossRef] 19. Zheng, R.; Zhao, J.; Zhou, X.; Ma, C.; Wang, L.; Gao, X. Land Use Effects on the Distribution and Speciation of Heavy Metals and Arsenic in Coastal Soils on Chongming Island in the Yangtze River Estuary, China. Pedosphere 2016, 26, 74–84. [CrossRef] 20. Yao, H. Characterizing landuse changes in 1990–2010 in the coastal zone of Nantong, Jiangsu province, China. Ocean. Coast. Manag. 2013, 71, 108–115. [CrossRef] 21. Bai, J.; Xiao, R.; Zhang, K.; Gao, H.; Cui, B.; Liu, X. Soil organic carbon as affected by land use in young and old reclaimed regions of a coastal estuary wetland, China. Soil Use Manag. 2013, 29, 57–64. [CrossRef] 22. Cerqueti, R.; Cinelli, M.; Minervini, L.F. Municipal waste management: A complex network approach with an application to Italy. Waste Manag. 2021, 126, 597–607. [CrossRef] 23. Wang, Y.; Lei, Y.; Fan, F.; Li, L.; Liu, L.; Wang, H. Inter-provincial sectoral embodied CO2 net-transfer analysis in China based on hypothetical extraction method and complex network analysis. Sci. Total Environ. 2021, 786.[CrossRef] 24. Joo, H.; Kim, H.S.; Kim, S.; Sivakumar, B. Complex networks and integrated centrality measure to assess the importance of streamflow stations in a River basin. J. Hydrol. 2021, 598.[CrossRef] 25. Dai, L.; Derudder, B.; Liu, X. The evolving structure of the Southeast Asian air transport network through the lens of complex networks, 1979–2012. J. Transport. Geogr. 2018, 68, 67–77. [CrossRef] 26. Zhang, B.; Yin, L.; Zhang, S.; Feng, C. Assessment on characteristics of LUCC process based on complex network in Modern Yellow River Delta, Shandong Province of China. Earth Sci. Inform. 2015, 9, 83–93. [CrossRef] 27. Zhang, M.; Wang, J.; Feng, Y. Temporal and spatial change of land use in a large-scale opencast coal mine area: A complex network approach. Land Use Policy 2019, 86, 375–386. [CrossRef] 28. Jiangsu Coastal Areas Development Office. Outline of Jiangsu Coastal Reclamation Development Plan. Available online: http://www.scio.gov.cn/ztk/xwfb/04/4/Document/542277/542277.htm (accessed on 23 July 2021). (In Chinese) 29. Boccaletti, S.; Latora, V.; Moreno, Y.; Chavez, M.; Hwang, D. Complex networks: Structure and dynamics. Phys. Rep. 2006, 424, 175–308. [CrossRef] 30. Bryan, B.A.; Ye, Y.; Zhang, J.E.; Connor, J.D. Land-use change impacts on ecosystem services value: Incorporating the scarcity effects of supply and demand dynamics. Ecosyst. Serv. 2018, 32, 144–157. [CrossRef] 31. Shannon, C.E. A mathematical theory of communication. Bell Syst. Tech. J. 1948, 27, 623–656. [CrossRef] 32. Fedajev, A.; Stanujkic, D.; Karabašević,D.; Brauers, W.K.M.; Zavadskas, E.K. Assessment of progress towards “Europe 2020” strategy targets by using the MULTIMOORA method and the Shannon Entropy Index. J. Clean. Prod. 2020, 244, 118895. [CrossRef] 33. Ziying, Z.; Jiannan, D.; Chunfeng, L. Temporal-spatial changes analysis of land use structure in Changsha City based on information entropy. Ecnomic Geogr. 2012, 32, 124–129. 34. Meng, Z. Research on the Impact of Tidal Flat Reclamation on Ecosystem Services in Dongtai Coastal Area; Nanjing University: Nanjing, China, 2018. (In Chinese) 35. Jianguo, L. The Impact of Coastal Reclamation on Soil Organic Carbon: A Case Study of Rudong County, Jiangsu Province; Nanjing University: Nanjing, China, 2015. (In Chinese) 36. Jiang, T.-T.; Pan, J.-F.; Pu, X.-M.; Wang, B.; Pan, J.-J. Current status of coastal wetlands in China: Degradation, restoration, and future management. Estuar. Coast. Shelf Sci. 2015, 164, 265–275. [CrossRef] 37. van Roon, M.R. Wetlands in The Netherlands and New Zealand: Optimising biodiversity and carbon sequestration during urbanisation. J. Environ. Manag. 2012, 101, 143–150. [CrossRef] 38. Wei, L.; Luo, Y.; Wang, M.; Cai, Y.; Su, S.; Li, B.; Ji, H. Multiscale identification of urban functional polycentricity for planning implications: An integrated approach using geo-big transport data and complex network modeling. Habitat Int. 2020, 97, 102134. [CrossRef] 39. Wang, C.; Chen, J.; Li, Z.; Abouel Nasr, E.S.; El-Tamimi, A.M. An indicator system for evaluating the development of land-sea coordination systems: A case study of Lianyungang port. Ecol. Indic. 2019, 98, 112–120. [CrossRef]