Ecosystem and Ecosystem Services

Ecosystem Service Functions of a Typical Karst Urban Basin based on Land Use Change

  • LI Yue , 1, * ,
  • GENG Huacai 1 ,
  • WU Luhua 2 ,
  • LUO Guangjie 3 ,
  • CHEN Fei 4
  • 1. College of Public Administration, Guizhou University of Finance and Economics, Guiyang 550025, China
  • 2. School of Economics and Management, Tongren University, Tongren, Guizhou 554300, China
  • 3. Guizhou Provincial Key Laboratory of Geographic State Monitoring of Watershed, Guizhou Education University, Guiyang 550018, China
  • 4. Guizhou Institute of Water Conservancy Science, Guiyang 550025, China
*LI Yue, E-mail:

Received date: 2023-04-14

  Accepted date: 2023-07-30

  Online published: 2023-12-27

Supported by

The Youth Talent Growth Project of Guizhou Provincial Department of Education(Qian Jiao He KY [2022] 202)

The Guizhou Provincial Basic Research Program (Natural Science)([2020]1Y157)

The Guizhou Provincial Program on Commercialization of Scientific and Technological Achievements([2022]010)

The Guizhou Provincial Science and Technology Projects(ZK[2023]-464)

The Scientific Research Projects in Higher Education Institutions of Guizhou Provincial Department of Education (Youth Project)(2022-351)

The Water Conservancy Science and Technology Funding Projects in Guizhou Province(KT202223)

The Water Conservancy Science and Technology Funding Projects in Guizhou Province(KT202316)

The Water Conservancy Science and Technology Funding Projects in Guizhou Province(KT202323)


Revealing the mechanism by which land use influences ecosystem service function in karst urban watersheds is of great significance for social and economic development and ecological environmental protection. In this study, the Nanming River Basin, a typical karst basin in Guizhou Province, was used as an example. The spatiotemporal dynamic changes in land use in the basin during three periods from 2000 to 2020 were analyzed using ArcGIS, and the ecosystem service functions of the different land use types in the basin were evaluated using an integrated valuation of ecosystem services and tradeoffs (InVEST) model. This analysis led to three outcomes. (1) Forest, cultivated land, and grassland make up most of the land uses. The land use change was mostly dependent on the growth of construction land, which expanded by 13.07%. (2) The watershed's water conservation function was significantly boosted during the study period. In contrast, the carbon stock function became slightly impaired, and the physical quality of both was regionally distributed as high in the northeast and low in the southwest. (3) The contributions of forest to total water conservation and carbon stock of the watershed are always the greatest, exceeding 57%, and the conversions of forest to construction land and cultivated land to forest are the two primary types of land use change in which the ecosystem service function was impaired and strengthened, respectively. The results of this study can provide important data support and scientific reference for land use structure optimization, soil and water resource exploitation, and sustainable ecosystem management in ecologically fragile areas.

Cite this article

LI Yue , GENG Huacai , WU Luhua , LUO Guangjie , CHEN Fei . Ecosystem Service Functions of a Typical Karst Urban Basin based on Land Use Change[J]. Journal of Resources and Ecology, 2024 , 15(1) : 1 -14 . DOI: 10.5814/j.issn.1674-764x.2024.01.001

1 Introduction

Land use/cover change (LUCC) is one of the most significant causes and drivers of global change (Turner et al., 1994; Huo et al., 2020), and its processes have a direct effect on the structure and function of ecosystems (Fu and Zhang, 2014). Studying the changes in ecosystem service functions in the background of LUCC is relevant from the perspectives of regional ecological safety and long-term development (Lou et al., 2019; Stammel et al., 2020; Liu et al., 2021). A frontier and hot topic in international research in ecology and related fields in recent years has been the study of ecosystem service function based on LUCC (Heinze et al., 2022; Ou et al., 2022; Qiu et al., 2022; Zeng et al., 2022).
As an essential part of the Earth's surface system, karst ecosystems are globally representative due to their unique features and vulnerability. They are also exemplary in the basic scientific research and comprehensive management of degraded ecosystems. Approximately one-third of China’s land area consists of karst terrain, and Southwestern China boasts one of the world’s largest karst areas. Guizhou has the largest karst landform area in China, occupying 61.9% of the province’s total area. Guizhou is representative of the primary type of ecologically fragile areas in China. Thus, one of the keys to resolving earth system scientific issues is addressing its ecological problems, which will also advance the development of ecological civilization in China and possibly the rest of the world.
As a natural biological unit and an important natural geographic division, basins have outstanding ecosystem integrity and ecological connectivity (Styers et al., 2010; Yang et al., 2023). As a unique complex ecosystem integrating society, economy, and nature (Zhao and Wang, 2019), the basin ecosystem provides the necessary resource base for human activities. However, as a result of climate change and increased disruption due to human activity, changes in watershed land use, destruction of the natural biological environment, increased soil erosion, reduced biodiversity, and increasingly problematic water pollution and eutrophication have adversely impacted watershed ecosystem services (Yang et al., 2010; Yang et al., 2020), resulting in an imbalance between economic development and ecological conservation (Zhao and Huang, 2022), which has piqued the interest of the academic community.
Evaluating watershed ecosystem service functions is a new study area that has emerged in recent years. Internationally (primarily in Europe, Africa, and the Americas), such research has mostly centered on watershed management, land/water use, economic policy formation, public education, and other objectives, including estimating the value of diverse ecosystem service functions such as watershed water resources, the preservation of soil and water, disaster mitigation (Venkateswarlu et al., 2020; Yohannes et al., 2021; Admasu et al., 2022; Teresa et al., 2022), weighing and analyzing the relationships between economic and ecological services (Aryal et al., 2022), upstream watershed protection and downstream economy (Dile et al., 2016), and analyzing the influences of agricultural development, land use change, and other policy measures on watershed ecosystem service functions (Anley et al., 2022; Berihun et al., 2022). Domestically, assessments of ecosystem service functions or values have been recorded for various systems, including the Heihe River, Haihe River, Huaihe River, Yellow River, Taihu Lake, Dongting Lake, Manas River, Shiyang River, Poyang Lake, and Jiulong River basins (Wang and Meng, 2017; Ran et al., 2019; Wang et al., 2019; Huang and Li, 2021). Current research focuses on quantifying the consequences of diverse human activities, such as land use change, agricultural practices, and hydropower generation, on watershed ecosystem services in order to promote a comprehensive understanding of the condition and role of watershed ecosystems in supporting economic development, maintaining ecosystem health, and guaranteeing ecological security, as well as to assist decision-makers in pursuing rational approaches to watershed land use planning, resource allocation, and ecosystem management.
By reviewing the relevant studies on karst ecosystem service functions at home and abroad, we found that this research has made positive progress in four main areas: comprehensive classification and evaluation of karst ecosystem service functions, assessment of individual ecosystem functions, natural and anthropogenic driving mechanisms of ecosystem services, and evaluation of ecological and economical composite systems and functions. The research contents primarily show the following traits. First, the focus on temporal and spatial scales is an essential entry point for the current research on karst ecosystem service functions, establishing the theoretical and scientific groundwork for this study. Second, studies on the mechanisms by which ecosystem service functions react to LUCC are primarily conducted at the provincial, county, and regional levels. However, in the academic setting of the quickly expanding field of global ecosystem service research, ecological and environmental issues brought on by urbanization have emerged as a significant challenge for human society, both now and in the long run. Rapid urbanization drives rapid economic development and causes basin ecosystem health problems. For example, the pressure on the urban environment continues to escalate, which causes several issues to emerge, including deterioration of water quality, spatial fragmentation, and loss of biodiversity (Zhou et al., 2017; Davis et al., 2022). These problems affect the basin through a complex feedback mechanism, which negatively impacts the development of the basin (Hao and Sun, 2021). In this regard, there is a pressing need to clarify how watershed LUCC affects ecosystem service functions in the context of growing urbanization and to offer scientific backing for integrated watershed management and ecological protection.
International research on urban watersheds is currently rich in many areas, including ecological risk assessment, ecosystem health assessment, and water quality pollution management (Meixler et al., 2022; Wang et al., 2022b; Zhou et al., 2022), and research on karst urban watersheds is still mainly focused on water quality and pollution control (Li et al., 2018; Dufresne et al., 2020). Even though the relevant research results have some scientific value for improving the quality of the water environment in watersheds, they disregard the fact that the LUCC in the process of fast urbanization transforms natural and semi-natural landscapes that were initially ideal for the regional biological environment into impermeable surface landscapes, which leads to the degradation of ecosystem service functions and causes harm to human well-being (Hao and Sun, 2021). Research on the ecosystem service functions of karst urban watersheds is deficient in data reserves and research accumulation, which limits the transformation of watershed management towards sustainable development to some extent.
The Nanming River Basin, situated in the social, economic, and cultural center of Guizhou Province, is a typical and exemplary urban watershed in a karst region (Wu et al., 2015; Wang et al., 2022a). With rapid socio-economic growth since the turn of the 21st century, the human demand for land has increased. The rapid development of urbanization has resulted in prominent changes in land use in this watershed, causing considerable damage to ecosystem service functions. Therefore, assessing the impact of LUCC on ecological service functions has become a critical concern in balancing “urban development” and “watershed ecosystem stability”. In this context, this study analyzed the temporal and spatial characteristics of land use evolution in the basin from 2000 to 2020, utilized the InVEST model in conjunction with meteorological, soil, and topographic data to assess the water conservation function and carbon stock function of different land use types in the basin, and assessed the influence of LUCC in the basin on the ecosystem service functions during the 21st century (i.e., from 2000 to 2020). The results of this study can offer a valuable addition to the global study of sustainable urban watershed development and provide crucial data support and scientific references for regional land use structure optimization, soil and water resource development, and sustainable ecosystem management.

2 Overview of the study area

The Nanming River Basin is in the central part of China’s Guizhou Province (26°15′-26°54′N, 106°26′-107°15′E) (Fig. 1). It is a first-class tributary on the right bank of the Wujiang River. With a 2158 km2 area, the basin has subtropical humid and mild weather, with 1200 mm of annual rainfall on average and an average temperature over many years of roughly 18 °C. Mountains and hills dominate the landforms; the landscape is high in the southwest and low in the northeast. The soil is predominantly paddy soil, limestone soil, and yellow soil (Fig. 2a), and the vegetation includes broad-leaved forest, coniferous forest, shrubs, and grassland. The karst landforms in the basin are extremely well-developed (Fig. 2b), occupying 93.17% of the total area. The ecological governance of the basin has produced impressive outcomes since 2012 (Zhang, 2021).
Fig. 1 Location and elevation map of the study area
Fig. 2 Maps showing (a) the soil type and (b) the geological background of the study area

3 Research methods and data sources

3.1 Research methods

3.1.1 Dynamics of LUCC

The dynamic degree of LUCC is capable of quantitatively describing the speed of LUCC. The single dynamic degree is calculated as follows:
$P=\frac{{{U}_{b}}-{{U}_{a}}}{{{U}_{a}}}\text{ }\!\!\times\!\!\text{ }\frac{1}{T}\text{ }\!\!\times\!\!\text{ }100\%$
where P is the single dynamic degree, Ua and Ub represent the areas of land use at the start and the end of the study, respectively (km2), and T is study time.
The comprehensive dynamic degree indicates the overall LUCC quantity in a certain period, and is calculated as follows:
${{L}_{c}}=\frac{\sum\limits_{i=1}^{n}{\Delta L{{U}_{i-j}}}}{2\sum\limits_{i=1}^{n}{L{{U}_{i}}}}\times \frac{1}{T}\times 100\%$
where Lc is the comprehensive dynamic degree, LUi is the land use area of type i in the initial stage; ΔLUi‒j represents the absolute value of the change in area from type i to non-type j during the study period, and n is the number of types of land use.

3.1.2 Land use transfer matrix

The land-use transfer matrix can represent the dynamic process of land-use conversion both statistically and qualitatively. The land-use transfer matrix is calculated as follows:
${{S}_{ij}}=\left( \begin{matrix} {{\text{S}}_{11}} & \ldots & {{\text{S}}_{1\text{n}}} \\ \vdots & \ddots & \vdots \\ {{\text{S}}_{\text{n}1}} & \cdots & {{\text{S}}_{\text{nn}}} \\ \end{matrix} \right)\ \ \ \ i,j=1,2,3,\cdots,\text{n}$
where ld Sij is the area transferred from i to j before transfer (km2); n is the amount of land use; and i and j indicate the land use types at the study’s beginning and end.

3.1.3 InVEST model

The free and open-source InVEST model, created with support from the Natural Capital Project, can quantify ecosystem services (Zhang et al., 2022b). The model gives managers a scientific foundation for balancing the benefits and effects of human activity by simulating changes in the quality and value of ecosystem services under various land cover scenarios; and it is used for ecosystem service function assessment (Shang et al., 2021). The visual depiction of the assessment results addresses the issue that earlier ecosystem service function assessments were abstractly described in words and not intuitive enough, and this is the model’s primary advantage over earlier ecosystem service function evaluation techniques. In this study, the InVEST model (version 3.10.8) was utilized to evaluate the ecosystem service functions.
Fig. 3 Interpolated mean annual precipitation data in 2000, 2010 and 2020
Fig. 4 Interpolated annual potential evaporation data in 2000, 2010, and 2020
The InVEST model’s water yield module is an estimation method based on the water balance principle and uses the combination of climate, topography, and soils to calculate the water yield of each raster in the basin (Li et al., 2020b). The water yield is calculated as follows:
$Yx,j=\left( 1-\frac{AETx,j}{Px} \right)\times Px$
$Wx=Z\times \frac{AWCx}{Px}$
$\begin{align} & AWC=54.509-0.132\times mSAN-0.003\times {{(mSAN)}^{2}} \\ & \text{ }-0.055\times mSIL-0.006\times {{(mSIL)}^{2}}-0.738\times mCLA \\ & \text{ }+0.007\times {{(mCLA)}^{2}}-2.668\times mC+0.501\times {{(mC)}^{2}} \\ \end{align}$
where $Yx,j$ is the water yield of a grid (mm); $AETx,j$ is the actual annual evapotranspiration of the grid (mm); Px is the annual precipitation of unit x (mm); $Rx,j$ is the Budyko dryness index; Wx represents the climate and soil properties; Z is a constant representing the seasonal characteristics of the precipitation; AWCx is the available water content of plants in grid unit x (mm); and mSAN, mSIL, mCLA, and mC are the gravel, silt, clay, and organic matter contents, respectively (%).
The carbon storage and sequestration module uses surface land use type as the evaluation unit and defines the regional terrestrial ecosystem carbon stock, which primarily includes above-ground biological carbon stock, below- ground biological carbon stock, soil carbon stock, and dead organic carbon stock. It is assessed based on the spatial dispersion and corresponding carbon density of each land use type, which is a measure of the amount of carbon that each kind of land use type stores. Furthermore, the model automatically generates a map of the regional distribution of the carbon stock (Xu and Zhang, 2018). The formula is expressed as:
$C\text{ }\!\!\_\!\!\text{ total}=C\text{ }\!\!\_\!\!\text{ above}+C\text{ }\!\!\_\!\!\text{ below}+C\text{ }\!\!\_\!\!\text{ dead}+C\text{ }\!\!\_\!\!\text{ soil}$
where $C\text{ }\!\!\_\!\!\text{ total}$ is the cumulative carbon stock (t); $C\text{ }\!\!\_\!\!\text{ above}$ is the carbon stock in the living plants above the soil (t); $C\text{ }\!\!\_\!\!\text{ below}$ is the carbon stock in the roots of the living plants below the soil (t); $C\text{ }\!\!\_\!\!\text{ dead}$ is the carbon stock (t) in dead plants, such as vegetation litter and dead wood; and $C\text{ }\!\!\_\!\!\text{ soil}$ is the organic carbon stock (t) in the soil.

3.1.4 Calculation of water conservation

In this study, the velocity coefficient, soil saturation hydraulic conductivity, and terrain index were used to correct the water yield by using ArcGIS 10.8 (Bao et al., 2016). The formula is as follows:
$\begin{align} & Retention\text{=min}\left( \text{1,}\frac{\text{249}}{Velocity} \right)\times \\ & \text{ min}\left( \text{1,}\frac{\text{0}\text{.9}\times TI}{\text{0}\text{.3}} \right)\times \text{min}\left( \text{1,}\frac{Ksat}{\text{300}} \right)\times Yield \\ \end{align}$
where Retention is the water conservation capacity (mm); Velocity is the velocity coefficient; $Ksat$ is the soil saturated hydraulic conductivity (cm d–1); TI is the terrain index; and $Yield$ is the water yield (mm).

3.2 Data sources

3.2.1 Land use data

In accordance with the requirements for land use type data for the dynamic evaluation of the ecological service functions in the basin, remote sensing images from three years (2000, 2010, and 2020) were acquired from the Geospatial Data Cloud Platform of the Chinese Academy of Sciences ( Based on the full consideration of the actual situation, the land use in the basin was classified into various categories, including waters, cultivated land, grassland, forest, and construction land. Since there was very little unused land in the basin, this type was not considered in the land use classification.

3.2.2 Annual water yield module data

According to the model user manual, the data required for the annual water yield module are described in Table 1.
Table 1 Data requirements and processing of the annual water production module of the Invest model
Basic data Data sources Data description Data processing tools Data processing method
DEM data Geospatial Data Cloud Platform (http://www.gscloud/) SRTMDEMUTM 30 m resolution data product ArcGIS 10.8 hydrological analysis tools Fill, analyze the flow direction and flow accumulation, build a river network
Meteorological data China Meteorological Network (
China's surface climate data dataset
Resolution of 1 km after interpolation
Daily maximum/minimum temperature
Average daily temperature
ArcGIS 10.8 interpolation analysis tool Precipitation data from 13 meteorological stations, inverse distance interpolation to obtain precipitation and potential evapotranspiration raster data (Figs. 3, 4)
Soil data Chinese soil dataset from Harmonized World Soil Database (HWSD) ( Resolution of 1 km REF_DEPTH
ArcGIS 10.8 raster calculator tool Use the empirical formula (Gupta and Larson, 1979) to calculate the available water content of the plants and the maximum burial depth of the soil roots
Remote sensing images Geospatial Data Cloud Platform (http://www.gscloud/) Two Landsat TM images acquired in 2000 and 2010 and Landsat 8 images acquired in 2020 ENVI5.3 Preprocessing such as radiometric calibration, atmospheric correction, geometric correction, cropping, and stitching

3.2.3 Carbon storage and sequestration module data

The figures for the carbon density were obtained from earlier studies, and they are presented in Table 2.
Table 2 Carbon density figures of the different land use types in the Nanming River Basin (Unit: t ha-1)
Land use type Aboveground carbon density Underground carbon density Soil carbon density Dead organic matter carbon density Data source
Grassland 0.82 0.87 89.20 1.00 Yang and Wu, 2020
Forest 20.36 67.50 170.00 7.80 Yang and Wu, 2020
Cultivated land 38.90 7.30 89.18 0 Li et al., 2020a
Construction land 0 0 110.69 0 Li et al., 2020a
Waters 0 0 0 0 Huang, 2020

4 Results and analysis

4.1 Analysis of LUCC in the Nanming River Basin

4.1.1 Dynamic temporal and spatial analysis of LUCC in the Nanming River Basin

Figure 5 shows that the dominant land uses were forest, cultivated land, and grassland. The forests were concentrated in the Wudang and Longli areas in the northeastern part of the study area. The cultivated land was primarily dispersed in Huaxi District, Guiyang City and the eastern part of Pingba. The western region of Longli County, Zhongshan District, the eastern region of Baiyun District, and the northern portion of Huaxi District had the largest concentrations of grassland. Most of the construction land was located in the territory under Guiyang City’s authority. The waters were dispersed across the southwestern part of the basin in the form of a densely interconnected network.
Fig. 5 Land use maps of the Nanming River Basin in 2000, 2010, and 2020
Figure 6 shows the changing dynamics of land utilization inside the basin. From 2000 to 2020, two increases and three declines served as the main distinguishing factors of the different land type changes. In other words, the areas of construction land and waters increased, whereas the grassland, cultivated land, and forest areas decreased. The construction land was the land use type with the highest growth rate. The area of the waters increased by the second highest rate, with a yearly rise of 1.05% during 2000-2020 due to the construction of water-saving facilities such as reservoirs, ponds, and cascade hydropower stations in the basin. The grassland was the land use type that declined the most. Affected by policies such as returning farmland to forests, the cultivated land displayed a decreasing trend over the 20 years. Forest was the land use type with the lowest rate of decrease during 2000-2020, and the area showed a declining tendency.
Fig. 6 Dynamic degrees of land use in the Nanming River Basin in Guizhou from 2000 to 2020
The comprehensive dynamic degrees of land use in 2000-2010 and 2010-2020 were 0.38% and 0.65%, respectively, and the basin’s rate of shifting in land use gradually picked up speed.

4.1.2 Analysis of the land use in the Nanming River Basin

From 2000 to 2010, the transfer-out areas of forest and construction land in the basin were smaller than their transfer-in areas (Fig. 7a). The forests were primarily transformed into construction land and cultivated land. The construction land was mostly turned into forest and cultivated land, with only a minor portion converted to grassland. Most cultivated forest and grassland areas were transformed into construction land.
Fig. 7 Land use transformation in the Nanming River Basin from 2000 to 2020

Note: 1 indicates construction land; 2 indicates forest; 3 indicates waters; 4 indicates cultivated land; and 5 indicates grassland.

From 2010 to 2020, the cultivated land was mainly turned into construction land and forest (Fig. 7b). The grassland was mainly transferred to construction land. The area of the forest that was transferred out was almost 2.7 times larger than the area transferred in. The transfer-in areas of construction land were mainly converted from cultivated land, forest, and grassland.
From 2000 to 2020, the transfer-in areas of the forest were primarily converted from cultivated land and grassland (Fig. 7c), proving that the effort to convert cultivated land to forest, which was put into place in the basin recently, played a crucial role. Compared to the transfer-out area, the transfer-in area of the construction land was significantly larger. This was primarily carried out to meet a rapidly expanding population and increasing housing demand, and this transfer led to large-scale occupation and reclamation of cultivated land, forest, and grassland. Cultivated land was the land type with the largest area transferred out in the study area in the last 20 years, and the transfer was mainly in the directions of construction land and forest, followed by grassland, whose area transferred out was as much as five times the area transferred in.

4.2 Evaluation of the water conservation function

4.2.1 Spatiotemporal variations in the water conservation function

Figure 8 shows the spatial distributions of water yield, and the Nanming River Basin’s capacity for water conservation was evaluated using ArcGIS 10.8. Temporally, the water conservation capacities in 2000, 2010 and 2020 were 1.06×106 m3, 0.72×106 m3, and 1.24×106 m3, respectively, exhibiting a decreasing-increasing fluctuating trend. Spatially, the regional variability of water conservation was not apparent, but was the opposite of the geographical distribution of the water yield. Most high-value locations were in the northeastern part, while the low-value sectors were concentrated in the southwest.
Fig. 8 Spatial distributions of the water yield and water conservation in the Nanming River Basin in 2000, 2010, and 2020

4.2.2 Analysis of the variations in water conservation for the different land use types

The water conservation function of each land use type varies because of the various soil characteristics and vegetation cover (Table 3). Furthermore, they can be listed in descending order as: forest > cultivated land > grassland > construction land > waters. From the viewpoint of land types, the water conservation capacities of grassland, cultivated land, construction land, and waters in the watershed are in line with the directions of alterations in their land use areas; however, the area of forest declined while its water conservation capacity increased. From the viewpoint of the increase or decrease in water conservation capacity, the capacity per unit area of grassland and cultivated land decreased by more than 1%, and capacity per unit area of construction land increased the most. The increased water conservation capacity per unit area of construction land did not compensate for the losses of cultivated land, grassland and waters. However, grassland, cultivated land, and forest still became important water conservation land types in the watershed with their advantages of area. In addition, as the minor land type in the basin, the waters had the most significant increase in the contribution to total water conservation, at 45.65%. During the study period, the decreases in water conservation mainly occurred in the southwest, where the shifting of forest and cultivated land to construction land was the primary type of land alteration. The increases in water conservation primarily occurred in the northeast, around Wudang Kaiyang, where the primary form of land change was the transformation of cultivated land into forest, indicating that the preservation of natural land types is essential for the steady improvement of ecosystem service functions.
Table 3 Changes in the water conservation values of the different land use types in the Nanming River Basin from 2000 to 2020 (Unit: 105 m3)
Land use type Water conservation Change in water conservation
2000 2010 2020 2000-2010 2010-2020 2000-2020
Grassland 1.71 0.95 1.62 -0.76 0.67 -0.09
Cultivated land 2.46 1.42 2.38 -1.04 0.96 -0.08
Construction land 0.41 0.82 0.92 0.41 0.10 0.51
Forest 6.02 3.94 7.51 -2.08 3.57 1.49
Waters 0.022 0.020 0.028 -0.002 0.008 0.006

4.3 Carbon stock function evaluation

4.3.1 Temporal and spatial variations in the carbon stock function

The data on carbon stocks are shown in Fig. 9. In terms of temporal changes during 2000-2020, there was an initial increase in the overall amount of carbon stock followed by a drop, with a total overall reduction of 5.63×105 t, demonstrating that the carbon stock function had weakened.
Fig. 9 Distribution of carbon reserves (carbon stocks) in the Nanming River Basin in 2000, 2010, and 2020
During 2000-2020, the regional changes in carbon stocks were not very noteworthy, and there was no obvious migration or change. The high-value carbon stock areas were focused in the northeastern part of the basin, specifically in Wudang and Kaiyang. The plants in this region were mostly in forest and cultivated land, and the carbon sequestration capability was relatively high. The low-value regions were primarily Guanshan Lake, Yunyan, and Nanming in the southwestern part of the basin, which were at lower elevations and more strongly affected by human activities.

4.3.2 Analysis of the variations in the carbon stocks in the different land use types

Table 4 shows the average carbon stock values in the different land types: forest > cultivated land > grassland > construction land > waters. From 2000 to 2020, carbon stock in forest increased and then decreased. Even though it decreased by 5.61×105 t, it always far exceeded the other land types, indicating that forest is an important carbon stock land type in the Nanming River basin. Land use changes in the watershed have had a direct impact on ecosystem carbon stocks, with a total reduction of 5.63×105 t over 20 years, of which 8.55×105 t was lost by the conversion of forest to construction land, mainly concentrated in Guanshan Lake and Huaxi districts in the southwestern part of the watershed. The conversion of cultivated land and grassland to forest is the primarily reason for the increase in the carbon stock. These two conversions contributed to the increase in total carbon stock by 45.93% and 35.00%, respectively.
Table 4 Changes in carbon stocks for the different land use types in the Nanming River Basin from 2000 to 2020 (×105 t)
Land use type Carbon stock Change in carbon stock
2000 2010 2020 2000-2010 2010-2020 2000-2020
Grassland 31.3 27.33 24.26 -3.97 -3.07 -6.87
Cultivated land 88.03 80.78 68.31 -7.25 -12.47 -19.72
Construction land 20.06 29.41 46.63 9.35 17.22 26.57
Forest 259.42 262.4 253.81 2.98 -8.59 -5.61
Waters 0 0 0 0 0 0

5 Discussion

5.1 Characteristics of the land use changes

LUCC is an essential topic in worldwide change research and one of the breakthroughs in studying the global and regional environment from both natural and socioeconomic perspectives, and it is capable of effectively projecting the correlation between socioeconomic development and land use. The findings of this study, which are in line with those of many other studies (Zhang and Ren, 2016; Guo et al., 2020; Chen and Gao, 2022), demonstrate that forest is consistently the dominant land type in the watershed, and it tended to grow and subsequently decline in area. The forest area in the context of the policy of returning farmland to forest may be decreasing for several reasons. On the one hand, the building of a second forest belt around Guiyang City has been planned by the local government since 2001. This project has directly increased the extent of forested land coverage in the watershed and strengthened forest protection. On the other hand, the increase in construction land always encroaches on other land types due to the significant increase in the population and rapid socioeconomic development. Although Guiyang City continues to implement important forestry conservation initiatives, such as converting cultivated land back to forest, the watershed is situated in the city's economic, cultural, and social core, so the associated social activities have surpassed the carrying capacity of the forest ecosystem. As a result, the forest area declined slightly from 2010 to 2020. In general, the rapid socio- economic development of the basin and the implementation of related policies have contributed to some extent to the accelerated rate of land use changes and significant changes in land use structure since the turn of the 21st century. In the process of rapid urbanization, the scale of construction land has been expanding, and the primary sources of this growth have been cultivated land and grassland.

5.2 Impact of land use changes on the Nanming River Basin ecosystem service function

The basin is situated in the center of Guizhou Province, a typical karst-concentrated and vulnerable ecological zone in China, so the reaction of the ecosystem service function to LUCC will be more sensitive to a certain extent. According to the findings of this study, the Nanming River watershed’s water conservation function is generally improving. The water conservation capacity of the northeastern portion of the watershed is significantly better than that of the southwestern portion, primarily because the primary land categories in the northeast were forest and cultivated land. The vegetation in these land use category areas is lush, and its roots can fully absorb the available water and enhance the water conservation capacity. In the southwestern zone, human actions occurred often, and the most common categories of land use were cultivated land, construction land, and waters, so the surfaces were mostly impervious. The water conservation function could have been better due to the combined effect of human actions, vegetation coverage, rainfall, and other factors. Notably, while the area of forest declined slightly, the contribution of its water conservation capacity to total water conservation capacity continued to increase, which contradicts the opinion of Wang et al. (2021b) that the water conservation capacity is positively connected with land type area. This contradiction might be due to the changes in land use and other natural factors like the impact of climate on how much water can be conserved (Anett et al., 2022). Among them, rainfall has a significant impact on soil moisture fluctuations, and forest has a higher soil moisture content than other land types throughout the dry and wet seasons (Zhao et al., 2021). We discovered that the average annual rainfall in the Nanming River watershed in 2020 reached 1416.88 mm, which was the highest value during the study period, increasing the soil moisture content absorbed by the forest so that the water content did not decline when the forest area was reduced. Additionally, as the smallest land use category in the watershed, the increase in the contribution of the waters land type to the overall water conservation of the watershed reached 45.65%. This is consistent with the findings of Jiang and Wu (2021) for Jiangsu Province, which shows that waters is critical to the stable improvement of urban ecosystem service functions.
Similar to the conclusions reached by related studies (Cheng et al., 2017; Fang et al., 2021), the intensification of human actions and the growth of construction land in the basin resulted in decreases in plant coverage and carbon sinks, and it ultimately caused the function of carbon stock to decline. The change in total carbon stock in the watershed under the effect of land use type changes displayed an increasing-decreasing trend, with a total loss of 5.63×105 t. The rapid socioeconomic growth of the basin and the execution of relevant policies have contributed to the quick transformations of land use types, which affects the basin's carbon stock. From 2000 to 2010, the forest in the watershed was effectively protected. The Huaxi district in the southwest of the watershed and the Wudang and Longli areas in the northeast were primarily converted from grassland and agriculture to forest, and these were areas with significantly increased carbon stocks. The watershed ecosystem continued to perform well in terms of carbon stock. However, during the period of 2010-2020, urbanization and industrialization were vigorously promoted in the watershed, tourism rose fast, the annual GDP growth rate was increasing (Wang and Ren, 2017; Ma, 2019), and considerable quantities of forest, cultivated land, and grassland were transferred to construction land to satisfy the increasing production and living needs. These changes resulted in a significant reduction in the carbon stock in the central city of Guiyang, which is located in the southwestern region of the watershed.

5.3 Ecological conservation in karst urban watersheds: Insights and suggestions

Karst ecosystems provide several ecological functions to the soil-water-gas cycle of matter and energy in the earth's surface critical zone and the human living environment in their natural state (Song et al., 2016). Since the beginning of the 21st century, China’s karst regions have undergone significant land use changes, directly contributing to the deterioration of karst ecosystem service functions. Therefore, enhancing the diversity, stability, and sustainability of ecosystems is one of the essential tactics for establishing a “community of life between humans and nature” and the key to adapting to global changes. As a typical karst urban watershed, the Nanming River supports and maintains the natural environmental conditions for human survival with ample water resources and sustains biodiversity with broad waters. However, the distinctive dualistic hydrogeological structure of its ecosystem results in low environmental capacity and low disturbance resistance. Previous studies and the findings of this study show that urban sprawl, population growth, and socioeconomic activities will place stress and challenges on ecosystem services (Wang et al., 2021a; Chen et al., 2022; Liu et al., 2022; Zhang et al., 2022a). Consequently, we suggest that strengthening the ecosystem service function and supporting sustainable development can be regarded from four perspectives. 1) The spatiotemporal evolution and distribution characteristics of ecosystem service functions in the watershed obtained via this study can be utilized as data support for the development of advanced and differentiated land use pattern optimization and regulation measures. 2) Rationally planning the amount of construction land in the watershed will boost the efficiency of its use and slow down its rate of expansion. 3) To improve the function of waters in conserving water, water protection management should be strengthened. 4) The sustainable use of natural resources on the land, such as cultivated land, forest, and grassland, should be strengthened and the biodiversity of the watershed should be increased.

5.4 Uncertainty analysis

Scientific research and the introduction and use of models cannot ideally match realistic scenarios. Despite such issues, the use of models can still reflect the scientific validity and realism of a problem to a certain extent, while avoiding the over-simplification of the relevant complex steps, and most significantly, this approach can be relied upon to solve some crucial and fundamental issues in the actual task. The InVEST model faces the same issues, and various modules have some uncertainties and flaws. The collection of data related to the water yield module is typically constrained, and empirical formulas or even empirical values from the literature were used to calculate the root depth layer data. The topography and vegetation cover influence each land type, and their internal conditions are complex. Our solution was a generalization of the actual situation, and the accuracy of the critical parameters should be enhanced in the future through actual measurements and adjustments. In addition, the carbon stock module simplifies the carbon cycle process to some degree. It uses the static carbon density as the basis for carbon stock estimation, but ignores the regional heterogeneity of carbon density within the same land use type, resulting in estimation accuracy that is readily affected. Therefore, to improve the accuracy of carbon stock estimations, future research should consider combining the investigation and acquisition of a significant amount of field measurement data to enrich the dynamic carbon density database and, concurrently, strengthen the monitoring of carbon density data at sample sites to ensure the validity of the carbon density data.

6 Conclusions

In this study, a typical karst urban basin, the Nanming River Basin, was taken as the research object. ArcGIS 10.8 and the InVEST model were used to comprehensively evaluate the ecosystem service functions, including water conservation and carbon stock. The key findings are threefold.
(1) Nanming River Basin consists primarily of the forest, cultivated land, and grassland. The features of the changes from 2000-2020 are “two increases and three reductions”, with the annual rate of change for construction land growing the most, reaching 13.07%, and the change in the dynamic degree of comprehensive land use progressively accelerating to a maximum of 0.65%, primarily due to the transformation of cultivated land into construction land.
(2) Since the beginning of the 21st century, the water conservation function of the watershed has significantly increased, but the carbon stock function has diminished slightly. The ecosystem service function is substantially more significant in the northeastern part of the watershed, where forest and grassland are concentrated, than in the southwestern part, where construction land is distributed continuously.
(3) The functions of ecosystem services for each type of land use are different from one another. The average water conservation capacity and carbon stock capacity are as follows: forest > cultivated land > grassland > Construction land > waters. Additionally, forest always contributes the most water and carbon stock to the watershed, with 57.83% of the total water content and 60.09% of the total carbon stock. From the point of view of land use change, the conversion of cultivated land to forest was the primary factor in enhancing ecosystem service function in the northeast. In contrast, the transformation of the forest into construction land resulted in a weakening of the ecosystem service function in the southwest.
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