Impact of Human Activities on Ecosystem

Identifying Priority Areas for Ecological Restoration based on GIS: A Case Study of Xiushui County, China

  • XIE Hualin , 1, 2 ,
  • SHENG Meiqi 1, 2 ,
  • HE Yafen , 1, 2, * ,
  • ZOU Pinjian 1, 2
  • 1. School of Applied Economics, Jiangxi University of Finance and Economics, Nanchang 330013, China
  • 2. Institute of Ecological Civilization, Jiangxi University of Finance and Economics, Nanchang 330013, China
*HE Yafen, E-mail:

XIE Hualin, E-mail:

Received date: 2023-04-02

  Accepted date: 2023-05-09

  Online published: 2023-08-02

Supported by

The National Natural Science Foundation of China(41971243)

The National Natural Science Foundation of China(41961035)

The Key Project of Jiangxi Natural Science Foundation(20202ACB203004)

The 68th Batch of China Postdoctoral Science Foundation Funding(2020M682106)

The 14th Batch of Jiangxi Postdoctoral Science Foundation Special Funding(2020KY29)


Integrating the landscape pattern holistically and identifying priority areas for ecological restoration scientifically are the key challenges of national land space planning and ecological protection. Taking Xiushui County, a fragile ecological region in the south, as an example, this study established an evaluation index system based on the pattern-process principle, including the importance of ecosystem services and ecosystem sensitivity, and explored regional priority areas for ecological restoration through GIS spatial analysis technology. The results show that the ecological restoration priority area in the case study area is 2880.64 km2 in total, covering 63.93% of the overall area. Of that amount, 367.55 km2 is the bottom-line priority areas for ecological restoration, accounting for 8.16%. Regarding land use types within the major ecological restoration priority area, the arable land and construction land areas are 210.83 km2 and 122.52 km2, covering 55.35% and 51.43% of the overall area, respectively. Determining the priority areas at different levels can help decision-makers to prioritize the restoration needs of degraded areas and provide a basis for adopting targeted ecological restoration measures for areas with different degrees of degradation. Identifying priority areas also provides basic information for the protection and construction of the eco-security pattern of the territorial space, which is vital for improving the regional ecological environmental safety and building a harmonious community between humans and nature.

Cite this article

XIE Hualin , SHENG Meiqi , HE Yafen , ZOU Pinjian . Identifying Priority Areas for Ecological Restoration based on GIS: A Case Study of Xiushui County, China[J]. Journal of Resources and Ecology, 2023 , 14(5) : 1015 -1025 . DOI: 10.5814/j.issn.1674-764x.2023.05.012

1 Introduction

National land is the fundamental carrier of ecological civilization. Over the past two decades, the unreasonable exploitation of land resources by humans and socioeconomic activities that do not conform to ecological laws have led to a sharp decline in biodiversity, the destruction of forest vegetation, landscape fragmentation, and the degradation of other ecosystem functions and destructive behaviors (Prăvălie et al., 2021; Luo and Zhang, 2022), resulting in a variety of severe ecological crises. There is an urgent needed for China to harmonize the balance between economic growth and ecological civilization construction, and that even extends to the whole world (Zheng et al., 2019).
Based on the principles of landscape ecology, the priority areas for ecological restoration (hereafter referred to as PAER) can be identified by analyzing and simulating key regional landscape biological processes, such as disaster dispersion, water flow, urban expansion, material movement and species movement, in order to discern the landscape components, spatial positions, and spatial linkages that are crucial to regional ecological health and safety (Xie et al., 2018). Therefore, just like municipal infrastructure, the ecological restoration priority area is the ecological infrastructure that is necessary for sustainable regional development, provides integrated ecosystem services for the region, and holds the health and completion of regional ecosystem structures (Yu et al., 2010; Jiang et al., 2015). After determining the key ecological services, analyzing and simulating key landscape biological processes using landscape process-pattern principles to discern the ecologically important and sensitive space, which is significant for regional ecological health and safety, the regional priority area for ecological restoration can then be comprehensively identified.
In May 2018, the idea of “the mountain, water, forest, field, lake and grass is a community of life, integrated, holistic and multi-pronged measures” was first proposed at the national level to designate PAER in key ecological function areas and in ecologically sensitive and fragile areas, with the aim of moderating the paradox between ecology and growth. Similar concepts internationally include urban parks (Cavin, 2013; Fasihi and Parizadi, 2020), nature reserves (Wang et al., 2022) and natural historical and cultural heritage, as well as ecological infrastructure (EI) (Yu et al., 2017; Zhang et al., 2019), urban growth boundary (UGB) (Liu et al., 2017; Chakraborti et al., 2018), ecological redline (Liu et al., 2021; Xu et al., 2021), Habitat Network (Von and Reich, 2006; Xun et al., 2017), and others. With the gradual awakening of ecological awareness in the international community, evaluating and identifying sensitive spaces for habitats and establishing priority areas for restorationcan not only be beneficial for enhancing conservation value, but also minimize the possibility of loss (Brooks et al., 2006). In recent years, agricultural production activities have become more intensive, and the area of arable land has increased significantly. However, at the same time, rapid urbanization and industrialization have led to a simultaneous expansion of land for construction and the continuous encroachment of highly concentrated human activities on ecological space, which have reducedthe value of regional ecosystem services and increased ecological risks. Therefore, the ecological restoration of national land space is urgent needed in order to limit the interference from human activities in the ecological environment.
The importance of the PAER area is generally recognized, but accurately identifying and protecting it have become the central issues of scholarly investigation. Existing studies on the content of regional PAER delineation are concerned with three aspects. One aspect is the spatial identification of biodiversity conservation (Vimal et al., 2012; Liang et al., 2018). Vimal et al. (2012) assessed the vulnerability of different biodiversity descriptions, which include species, ecological integrity and landscape diversity as well as assessing vulnerability, and finally combined them in order to identify the priority restoration sites. Second is the identification of restoration priorities. Li et al. (2021) used the GIS-OWA method to identify priority restoration areas in the Issyk-Kul basin by comparing the restoration efficiencies under different scenarios. The third aspect is green space identification (Byomkesh et al., 2012; Cameron and Blanuša, 2016). Byomkesh et al. (2012) analyzed the relationship between urbanization and green space dynamics in Dhaka, the capital city of Bangladesh, and pointed out that strategic spatial planning is urgently needed to ensure the sustainability of green space (Zinia and Mcshane, 2021). In addition, Marull and Mallarach (2005) defined two new composite indices: ecological connectivity and barrier effect; and used a quantitative GIS approach to assess landscape and ecological connectivity based on landscape ecological principles, which can be used for the identification of vulnerable sites. In summary, the research on ecological spatial identification of biodiversity conservation is more in-depth, but only one-sided; and there is limited research on identifying the ecological restoration space by integrating regional water security, soil erosion conservation, biodiversity and so on.
Chinese scholars have laid a solid foundation in the priority areas of ecological restoration evaluation index systems (Xie et al., 2018; Shen et al., 2021), integrated methods (Andrea et al., 2019; Strassburg et al., 2022), and ecological security patterns (Peng et al., 2018; Fu et al., 2020). For example, Andrea et al. (2019) employed quantitative methodologies to evaluate biodiversity using selected species and three ecosystem services (flood regulation, crop fertilization, and entertainment), in order to spatially prioritize river-floodplain sections for restoration. Peng et al. (2018) evaluated land degradation risk by type transformation and functional damage risk, which combined with ecological functional importance, so as to quantify the comprehensive reserve value in order to identify the ecological safety zones in Shenzhen.
Comprehensive studies have been conducted, mainly focusing on PAER delineation, evaluation index systems, comprehensive methods, ecological security patterns, and other topics. Nevertheless, complete and systematic spatial identification methods for regional PAER are still lacking, which makes the results biased. In terms of research scale, most of the existing studies are at the county scale or provincial scale, while there are relatively few explicit identifications based on GIS raster data at small scales. Therefore, this study explores the regional PAER from the viewpoint of ecological background and human needs, taking Xiushui County, which is a fragile ecological region in the south, as the study area. With the help of a GIS platform, considering comprehensive factors such as the significance of ecosystem services, ecosystem sensitivity, biodiversity conservation, and especially the extreme events of climate change and the frequent impacts of disasters (Esteve et al., 2023), this study then established an evaluation index system to explore the regional priority areas forecological restoration.

2 Methods

2.1 Study area

The case study areaselected in this studyis Xiushui County in northwestern Jiangxi Province (Fig. 1), which is located at 113°96′-114°95′E, 28°69′-29°37′N, and the total area is 4502.46 km2. The topography is mainly low and medium hills, which cover about 65% of the total area, and the major landform type is south hilly landscape. Geological hazards in Xiushui County are frequent, including landslides, debris flows, avalanches, ground subsidence, and others. In terms of climate, the county hasa humid subtropical monsoon climate, with multi-year average rainfall of 1782 mm per year. The rainfall shows an uneven seasonal distribution, with more than half of the annual rainfall concentrated in April-July. The average temperature throughout the year is 19.6 ℃, and the annual average frost-free period is 257 d. The water system is laid out in a vertical and horizontal distribution, like a network. Its main river, named Xiu River, has a basin area of 4227 km2, which is approximately 94% of the overall area. It is rich in water and energy resources, but has frequent disasters, especially droughts and floods. Therefore, Xiushui County was chosen as a typical case study area.

2.2 Data sources

The data included DEM, meteorological, soil, NDVI, NPP, land use data, socio-economic data, and related planning materials. Among them, DEMwas obtained from the Geospatial Data Cloud (; and the NDVI, NPP and land use data werefrom the Resource and Environment Science and Data Center ( The meteorological data werefrom the annual value dataset of China’s terrestrial climate information, including temperature and precipitation data, from the China Meteorological Science Data Sharing Service Network ( Soil information was derived from the Food and Agriculture Organization of the United Nations ( Socio-economic data were obtained from statistical yearbooks and government bulletins. Planning materials were retrieved from local planning authorities. All spatial data were resampled onto a 100 m×100 m raster.

2.3 Method for delineating priority areas for ecological restoration

In this study, the process of PAER delineation was carried out with the help of the spatial analysis platform of GIS. The specific technical route followed three steps (Fig. 2): 1) Construct three types of importance indices for regional biodiversity, soil conservation and water conservation, and two kinds of sensitivity indices for flooding and geological hazards; 2) Calculate and assign values to each index in a hierarchical manner in order to complete the identification of single-factor ecological land; and 3) Superimpose each single-factor ecological importance and sensitivity index to complete the identification of priority areas.

2.3.1 Method for evaluating the importance of ecosystem services

(1) Evaluation of the water conservation function importance
Water conservation (Liu et al., 2022) is an ecosystem function that increases the available water resources by intercepting and storing precipitation via its structure and processes, enhancing soil infiltration, conserving soil moisture, replenishing groundwater, and regulating the flow of rivers and streams. Usually, the ecosystem water-holding service capacity index is used as the evaluation index, and the specific calculation is:
$WR=NP{{P}_{mean}}\times {{F}_{sic}}\times {{F}_{pre}}\times (1-{{F}_{slo}})$
where WR is the ecosystem water-holding service capacity index; NPPmean is the multi-year average of net primary productivity of the ecosystem in the evaluation area; Fsic is the soil infiltration factor; Fpre is the ten-year average annual precipitation interpolated and normalized; and Fslo is normalized, which can be calculated by DEM.
(2) Evaluation of the soil conservation function importance
Soil conservation is the role of ecosystems (e.g., bush, forest, etc.) in reducing soil erosion due to water flowby their structure and processes. The ecosystem soil conservation service capacity index was used as our evaluation index (Fayas et al., 2019).
$Sqr=R\times K\times L\times S\times (1-C)$
where Sqr is the ecosystem soil conservation service capacity index, R is the rainfall erosion force factor, K is the soil erodibility degree, L is the slope length, S is the slope, and C is the vegetation coverage.
The formula forrainfall erosion force factor R is:
$\begin{matrix} R=\underset{k=1}{\overset{24}{\mathop \sum }}\,\overline{{{R}_{k}}} \\ \end{matrix}$
$\begin{matrix} \overline{{{R}_{k}}}=\frac{1}{n}\underset{i=1}{\overset{n}{\mathop \sum }}\,\underset{j=0}{\overset{f}{\mathop \sum }}\,\left( \alpha \times {{P}_{i,j,k}}^{\beta } \right) \\ \end{matrix}$
where, $\overline{{{R}_{k}}}$ is the rainfall erosive power of the k-th half month, unit: MJ mm (ha h a)–1; k is equal to 24; i is the year of the rainfall used; j is the number of days of erosive rainfall, unit: day; Pi, j, k is the rainfall of the j-th erosive day in the k-th half month of the i-th year, unit: mm; α is amodel parameter reflecting the rain pattern characteristics of the cold and warm seasons, here 0.3937 for the warm season and 0.3101 for the cold season; β is 1.7265; n is the number of years of rainfall used; and f is the total number of erosive rainfall days.
The soil erodibility degree K was calculated as:
$\begin{matrix} K=0.1317\times \left( -0.01383+0.51575{{K}_{EPIC}} \right) \\ \end{matrix}$
$\begin{array}{*{35}{l}} \begin{align} & {{\text{K}}_{\text{EPIC}}}=\left\{ 0.2+0.3\exp \left[ -0.0256{{\text{m}}_{\text{s}}}\left( 1-\frac{{{\text{m}}_{\text{silt}}}}{100} \right) \right] \right\} \\ & \times {{\left[ {{\text{m}}_{\text{silt}}}/\left( {{\text{m}}_{\text{c}}}+{{\text{m}}_{\text{silt}}} \right) \right]}^{0.3}} \\ \end{align} \\ \times \left\{ 1-\frac{0.25\text{orgC}}{\left[ \text{orgC}+\exp \left( 3.72-2.95\text{orgC} \right) \right]} \right\} \\ \times \left\{ 1-\frac{0.7\left( 1-\frac{{{\text{m}}_{\text{s}}}}{100} \right)}{\left\{ \left( 1-\frac{{{\text{m}}_{\text{s}}}}{100} \right)+\exp \left[ -5.51+22.9\left( 1-\frac{{{\text{m}}_{\text{s}}}}{100} \right) \right] \right\}} \right\}~ \\ \end{array}$
In the above equation, K is the soil erodibility degree,${{K}_{EPIC}}$ is the soil erodibility in t ha h (ha MJ mm)–1; mc is the content of clay particles (<0.002 mm) (%); ${{m}_{silt}}$ is the content of powder particles (0.002–0.05 mm) (%); ${{m}_{s}}$ is the content of sand particles (0.05–2 mm) (%); and $orgC$ is the content of organic carbon (%).
The slope length $L$ and slope $S$ were calculated as:
$\begin{matrix} L={{\left( \frac{\lambda }{22.13} \right)}^{p}} \\ \end{matrix}$
$\begin{matrix} p=\gamma /\left( 1+\gamma \right) \\ \end{matrix}$
$\begin{matrix} \gamma =\left( \sin \text{ }\!\!\theta\!\!\text{ }/0.089 \right)/\left[ 3.0\times {{\left( \sin \theta \right)}^{0.8}}+0.56 \right] \\ \end{matrix}$
$S=\left\{ \begin{array}{*{35}{l}} 10.8\times \sin \theta +0.03\ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \theta <5.14 \\ 16.8\times \sin \theta -0.5\ \ \ \ \ \ \ \ \ \ 5.14\le \theta <10.20 \\ 21.91\times \sin \theta -0.96\ \ \ \ \ 10.20\le \theta <28.81 \\ 9.5988\ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \theta \ge 28.81 \\ \end{array} \right.$
In the above equation, L is the slope length, S is the slope, p is the slope length index; θ is the slope indegrees; λ is the slope length in meters; and r is the intermediate parameter.
(3) Evaluation of the biodiversity conservation function importance
Biodiversity conservation performs the function of maintaining genetic, species, and ecosystem diversity. Its evaluation often uses species-based evaluation methods and habitat diversity-based evaluation methods (Peng et al., 2015). The first method involves collecting data on regional plant and animal diversity and environmental resources, establishing a species distribution database, applying an SDM model to quantify the dependence of species on the environment, and finally delineating a PAER by combining their actual distribution ranges. The second method is mainly applied to cases where some species distribution data information are missing and distribution accuracy may be low (Liet al., 2011). In this study, the second method was used due to the incomplete distribution data of some species. It was calculated as:
$\begin{matrix} {{S}_{bio}}=NP{{P}_{mean}}\times {{F}_{pre}}\times {{F}_{tem}}\times {{F}_{alt}} \\ \end{matrix}$
where ${{S}_{bio}}$ is the biodiversity maintenance importance index, $NP{{P}_{mean}}$ is the net primary productivity; ${{F}_{pre}}$ is the multi-year average of annual precipitation interpolated and normalized to 0–1; ${{F}_{tem}}$ is the temperature parameter, and ${{F}_{alt}}$ is the normalized altitude parameter.

2.3.2 Method for evaluating the sensitivity of ecosystem services

In view of the different sensitivities of each land type, aregional ecosystem sensitivity evaluation was carried out, including flood sensitivity and geological hazard sensitivity (Xie et al., 2018), and others. The evaluation results were graded using the natural break method, and the evaluation results were classified as insensitive, generally sensitive, mod- erately sensitive, highly sensitive and extremely sensitive.
(1) Flood sensitivityevaluation
This section jointly determines the flood sensitivity space based on river and lake buffers and flood inundation areas (Xie et al., 2018) (Table 1). The flood inundation areas determine the safety level based on the flood risk frequency, and use 10, 20, 50 and 100-year events as the sensitivity criteria. Simulating the hydrological process of dynamic submergence was used to work out the inundation extent at various flood hazard frequencies.
Table 1 Flood sensitivity evaluation index system and weights
Evaluation factor Insensitive Generally sensitive Moderately sensitive Sensitive Extremely sensitive
River and lake buffer zone distance (m) ≥20 15-20 10-15 5-10 ≤5
Flooded area scope (m) ≥120 115-120 110-115 105-110 ≤105
Grading assignment 1 3 5 7 9
(2) Geological hazard sensitivity evaluation
Geological hazardsare primarily gravity-based in the case study area, such as debris flows, landslides, and ground subsidence, so they are related to elevation, topographic slope, vegetation cover, topographic relief, and human intervention. Therefore, in this study, drawing on the influence and sensitivity of disaster-causing variables on geohazards based on previous research results (Rui et al., 2015), the geohazard sensitivity index was used:
$\begin{matrix} GS=\sqrt[5]{\prod {{G}_{i}}} \\ \end{matrix}$
where GS is the geohazard sensitivity index; Gi is the sensitivity level of i factors, and the specific evaluation factors are assigned as shown in Table 2.
Table 2 Geological hazard sensitivity evaluation index system and weight
Evaluation factor Insensitive Generally sensitive Moderately sensitive Sensitive Extremely sensitive
Elevation (m) <50 50-100 100-200 200-500 >500
Vegetation cover >0.8 0.6-0.8 0.4-0.6 0.2-0.4 0-0.2
Slope (°) <5 5-10 10-15 15-25 >25
Topographic relief (m) <20 20-50 50-100 100-300 >300
Human activity intensity Woodland, high cover grassland, lake, beach, mudflat Reservoir pit, wetland, other unutilized land Low and medium cover grassland, cultivated land, bare land Rural residential area, other construction land Urban, industrial and mining construction land
Grading assignment 1 3 5 7 9
(3) Evaluation and identification method for priority areas of ecological restoration
The importance and sensitivity of ecosystem services derived from a single-factor analysis can only reflect the process of a single factor. To comprehensively identify the regional PAER, it is necessary to calculate the comprehensive ecological land index for each spatial raster unit, and then obtain its spatial distribution level map. Therefore, this study adopted the analysis algorithm to calculate the comprehensive ecological land index as:
$\begin{matrix} EL=\max \left( W{{R}_{i}},Sq{{r}_{i}},{{S}_{bio}},Hlz{{h}_{i}},G{{S}_{i}} \right) \\ \end{matrix}$
Fig. 2 Ecological restoration priority area identification framework
where EL is the integrated ecological land index; WRi is the water conservation importance index of spatial unit i; Sqri is the soil conservation importance index of spatial unit i; Sbio is the biodiversity conservation importance index of spatial unit i; Hlzhi is the flood hazard sensitivity index of spatial unit i; and GSi is the landslide susceptibility index of spatial unit i.

3 Results

3.1 Ecological importance space

Based on the ecosystem service importance evaluation method established above, ArcGIS10.2 software was employed to assess the single-factor importance of ecosystem functions in the case study area. The ecological importance spaces were divided into five categories by the natural breakpoint method, yielding the results shown in Table 3 and Fig. 3.
Table 3 The ecological importance space of the case study area
Evaluation factor Importance level Area (km2) Percentage (%) Cumulative percentage (%)
Water conservation importance space Unimportant 2642.32 58.68 58.68
Generally important 1202.69 26.71 85.39
Moderately important 607.94 13.50 98.89
Important 26.60 0.59 99.48
Extremely important 23.28 0.52 100.00
Soil conservation importance space Unimportant 3292.66 73.12 73.12
Generally important 723.71 16.07 89.20
Moderately important 317.86 7.06 96.26
Important 133.19 2.96 99.21
Extremely important 35.41 0.79 100.00
Biodiversity conservation
importance space
Unimportant 2426.44 53.89 53.89
Generally important 1392.68 30.93 84.82
Moderately important 442.03 9.82 94.63
Important 157.25 3.49 98.12
Extremely important 84.43 1.88 100.00
In terms of the evaluation of the water conservation importance, the data in Table 3 and Fig. 3a indicate that the extremely important and important areas are 23.28 km2 and 26.60 km2, covering 0.52% and 0.59% of the overall area, respectively. They account for a very small percentage and are mainly sporadically distributedin central and southeastern Xiushui County. These areas have a strong water conservation capacity and are vital formaintaining the security of local water resources.
In terms of the evaluation of the soil conservation importance, the data in Table 3 and Fig. 3b indicate that the extremely important and important areas are 35.41 km2 and 133.19 km2, which represent 0.79% and 2.96% of the overall area, respectively. These areas are mainly spreadout along the Makufu Mountains in the northwestern part and the Jiu Ling Mountain in the southeastern part of Xiushui County. Most of these areas have red soil, yellow soil, and yellow-brown soil with loose soil texture, which, together with the high altitude and undulating topography, are highly susceptible to soil erosion problems due to heavy precipitation and the high velocity of river and lake water flow.
Fig. 3 Ecological importance space distributions
Regarding the evaluation of the biodiversity conservation functional importance, the data in Table 3 and Fig. 3c indicate that the extremely important area is 84.43 km2, which represents 1.88% of the overall area. These areas are principally distributed along Jiu Ling Mountain, the southeastern boundary within thecounty, whichis the core area for biodiversity conservation, and they are rich in forest patches which are ideal habitats for most biological species. Next, the area of important areas is 157.25 km2, accounting for 3.49%. These areas are mainly distributed at the periphery of the extremely important areas, and act as buffer zones and isolation zones for the core habitats of local biological species.

3.2 Ecological sensitivity space

Based on the ecosystem sensitivity evaluation method established in aprevious paper, ArcGIS10.2 software was employed to assess the single-factor sensitivity of flooding and geological hazards in this case study area. The ecological sensitivity spaces were divided into five categories by the natural breakpoint method, yielding the results in Table 4 and Fig. 4.
Table 4 The ecological sensitivity space of the case study area
Evaluation factor Sensitivity level Area (km2) Percentage (%) Cumulative percentage (%)
Flood sensitive space Insensitive 4260.91 94.56 94.56
Generally sensitive 18.37 0.41 94.97
Moderately sensitive 17.32 0.38 95.36
Sensitive 17.92 0.40 95.75
Extremely sensitive 191.32 4.25 100.00
Geohazard sensitive space Insensitive 968.10 21.51 21.51
Generally sensitive 1385.22 30.78 52.30
Moderately sensitive 1981.10 44.03 96.32
Sensitive 118.49 2.63 98.96
Extremely sensitive 46.90 1.04 100.00
Fig. 4 Ecological sensitive space distributions
In terms of flood hazard sensitivity evaluation, the data in Table 4 and Fig. 4a indicate that the area of medium sensitivity and above is 209.24 km2, covering 4.64% of the overall area. Among these levels, the sensitive and extremely sensitive areas are 17.92 km2 and 191.32 km2, respectively. They are mainly distributed in the core restoration area of Xiu River, one of the five major water systems in Jiangxi Province, and its 11 tributaries and the western bubbling water area, showing a dendritic distribution, to the central river valley spoke. These areas are in the valley plain area withlow terrain, which is a concentrated collection of surface water sources. It is also a key area of water resource conservation and very prone to flooding due to heavy rainfall, upstream flooding, etc., threatening people’s lives and residential area security.
In terms of geological hazard sensitivity evaluation, the geological hazards in Xiushui County includemainly landslides, debris flows, avalanches, ground subsidence, and others. The data in Table 4 and Fig. 4b show that the extremely sensitive area is 46.9 km2, which represents a percentage of 1.04%. It is principally distributed in the northeastern area of Makufu Mountains and the northwestern area of Jiu Ling Mountain, and is sporadically distributed. Most of these areas have slopes greater than 25°, the surface is exposed, the ecological environment is relatively poor, and they are extreme risk areas where geological disasters are frequent. The sensitive areas cover 118.49 km2, accounting for 2.63% of the total area. They are principally distributed in the northwestern area of Makufu Mountains, the northeastern area of Jiu Ling Mountain and around the extremely sensitive areas, where there is a higher probabilityof geological hazards such as landslides, mudslides, and ground subsidence.

3.3 Assessing the ecological restoration priority area types

According to the relevant research results, the extremely important and extremely sensitive areas in the evaluation of ecosystem service function importance and sensitivity arethe bottom-line ecological restoration priority areas. The important and sensitive areas are the crisis ecological restoration priority areas; while the moderately important and moderately sensitive areas are the buffer ecological restoration priority areas; and the generally important, generally sensitive, unimportant and insensitive areas arethe security ecological restoration areas. According to the PAER identification method established in aprevious paper, the analysis algorithm was used to obtain the PAER identification range of the case study area (Table 5 and Fig. 5).
Table 5 Identification of the ecological restoration priority areas in the case study area
Ecological restoration priority
area type
Non-ecological restoration priority area 1625.50 36.07 36.07
Buffer ecological restoration priority area 2133.48 47.35 83.42
Crisis ecological restoration priority area 379.61 8.42 91.84
Bottom-line ecological restoration priority area 367.55 8.16 100.00
Fig. 5 Distribution of ecological restoration priority area types
After comprehensive evaluation and identification, the spatial area of the bottom-line ecological restoration priority area is 367.55 km2, covering 8.16% of the overall area. It is intensively dispersed inthe northeast of Xiu River and the southeast of Jiu Ling Mountain in the case study area (Table 5 and Fig. 5). There are also a few patches in the region, such as large and medium-sized reservoirs and low hills and mountains in the north. This area iscentral for maintaining regional ecological security, with strong influencesfromhuman activities and a more fragile ecological environment. Next, the ecological restoration priority area is 379.61 km2, covering 8.42% of the overall area. It isprincipally distributed in the periphery of the Xiu Shui River system and around the bottom-line ecological restoration priority areas, with a fragmented distribution. Itis vital to regional ecosystem security, and principally distributed in the southeastern and northern parts of the county, as well as a small amount in the central part. The buffer ecological restoration priority area has the greatestspatial scope at 2133.48 km2, accounting for 47.35%, and its distribution is more concentrated, mostlyin the northeastern and southwestern parts of the county where the terrain is higher.

3.4 Conflict analysis of the ecological safety of current land use

Overlaying the construction land and agricultural land in the current land use system with the integrated ecological restoration priority areas, the distribution structure of the current land use was analyzed (Table 6).
Table 6 Current land use representing an ecological safety conflict zone
Ecological restoration priority area type Construction land Arable land
Area (km2) Percentage (%) Area (km2) Percentage (%)
Non-ecological restoration
priority area
98.84 44.65 199.11 48.57
Buffer ecological restoration priority area 52.00 23.49 112.90 27.54
Crisis ecological restoration priority area 21.48 9.70 42.91 10.47
Bottom-line ecological restoration priority area 49.04 22.15 55.02 13.42
Total 221.36 1 409.94 1
Among the land use types with intense human activities in the case study area in 2020, only about 45% of the construction land is in the ecologically safe or ecologically safer space, and about 22.15% of the construction land is in fragile or even extremely fragile ecological environments (Table 6). For the construction land in these areas, on the one hand there is a greater risk of life and property, while on the other hand their existence also poses a significant hazard to the regional natural environment and ecological security. But forthe arable land use, nearly 50% of itis in safe or safer areas, while about 13% of the arable land is in fragile or even extremely fragile ecological environments, and these zones threaten the regional ecological environment.

4 Discussion

This study identified the priority areas of ecological restoration in the case study area. To better protect the regional ecological environment, we proposed corresponding regulatory measures for the different priority areas, which are beneficial to keep harmonious coexistence between humans and nature.
(1) For the bottom-line ecological restoration priority area, relevant policies and regulations can be formulated to incorporate this area into the prohibited development area for urban development, economic development, urban and rural construction land expansion and arable land reclamation, whileat the same time, strictly prohibiting any urban development and construction activities in the core areas of ecological conservation. We should strengthen the publicity and education and promote public participation in ecological conservation. Adopting ecological conservation and control measures, and implementing ecological migration in key areas, would relieve the pressure on the local ecological environment.
(2) For the crisis ecological restoration priority area, based on the above control measures, we should implement regional land use ecological compensation policies, define the objects of compensation, compensation standards and methods, etc., and reasonably compensate the conservation objects of the ecological environment in terms of economic benefits, and other considerations. Meanwhile, we should innovate the land use ecological compensation mechanisms, which can guide the regional ecological security to a healthy path through taxation leverage.
(3) For the buffer ecological restoration priority area, strengthening the dynamic monitoring of ecological security and determining the control indexes of natural ecological land, agricultural land and urban construction land, which can ensure their dynamic balance and continuously optimize the ecological security pattern. In addition, in order to discover and deal with ecological damage in a timely manner, all competent departments of environmental conservation should coordinate with each other, so that minimizing the impacts of ecologically threatening behaviors.
We think that factor selection and the delineation of the single-factor ecological safety pattern is the key to influencing the rationality of the whole ecological safety pattern and the reliability of the construction land expansion plan, althoughmost of the existing studies are at the county scale or provincial scale, and it is still in the exploration stage. At the same time, there are also some identification methods, such as ecological networks (Chen et al., 2023), that canrationally and comprehensively describe the PAER, but they cannot determine the restoration order according to the degree of importance. Thus, the identification of PAER based on GIS raster data at small scales can improve conservation efficiency and accuracy. In addition, our research can provide a reference value for prioritizing the restoration of national land space. Arable land and construction land are impacted by the greatest intensity of human interference. Once the intensity exceeds ecological tolerance, it will affect the normal operation of ecosystem functions, ultimatelythreatening the ecological security of the local area or even the whole region (Liu et al., 2022). Therefore, it is necessary to identify the PAER, which can provide early warning of the conflicting spatial locations in the process of agricultural and urban development, in addition to laying a foundation for rational and scientific land use planning.
In the future, we will optimize the identification of PAER to improve replicability. Although this study obtained the degree of restoration priority, it did not assess how effective the landscape coherence and ecological conservation would be in areas following the implementation of conservation and restoration initiatives.

5 Conclusions

According to ecological functions of different land types and the distinctiveness of evaluation objectives, from two aspects of ecosystem importance and ecosystem sensitivity, this study selected the five single-factor ecological processes of water conservation, soil conservation, biodiversity conservation, flood and geological hazards, and constructed an assessment framework to discern the regional PAER based on RS, GIS and other relevant spatial information technologies. This analysis led to the following conclusions.
(1) This study divided the PAER zone into bottom-line ecological restoration priority areas, crisis ecological restoration priority areas and buffer ecological restoration priority areas. Through superposition analysis, the results showed that the PAER is 2880.64 km2, covering about 63.93% of the overall area. Of that amount, the buffer ecological restoration priority area accounts for the largest proportion at 47.35%, or about one-half of the whole region.
(2) The crisis ecological restoration priority areas and the bottom-line ecological restoration priority areas are the next largest, at 8.42% and 8.16%, respectively. The identification results better reflect the spatially distributed distinctions of the natural ecological circumstances and the scope of human activities in the maintenance zone, and they also verify the feasibility of the evaluation method for identifying the regional PAER.
(3) Within the priority areas of ecological restoration, the arable land and construction land areas cover 210.83 km2 and 122.52 km2, or 55.35% and 51.43% of the over all priority areas, respectively.
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