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Article

Land Use, Climate, and Socioeconomic Factors Determine the Variation in Hydrologic-Related Ecosystem Services in the Ecological Conservation Zone, Beijing, China

by
Lijuan Li
1,2,
Yanzheng Yang
2,
Tengyu Cui
3,
Ruonan Li
2,* and
Hua Zheng
2
1
Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, College of Life Sciences, Beijing Normal University, No. 19 Xinjiekouwai Avenue, Beijing 100875, China
2
State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
3
Center for Ecological Civilization Research, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
*
Author to whom correspondence should be addressed.
Water 2023, 15(11), 2022; https://doi.org/10.3390/w15112022
Submission received: 16 April 2023 / Revised: 18 May 2023 / Accepted: 24 May 2023 / Published: 26 May 2023
(This article belongs to the Section Water Resources Management, Policy and Governance)
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Abstract

:
The hydrologic-related ecosystem services of upstream ecological conservation zones have an important role in regulating the water scarcity and intense water conflicts of downstream regions. The joint effect of socioeconomic, land use, and climate factors on hydrologic-related ecosystem services is rarely analyzed; hence, its spatial heterogeneity and drivers remain unclear. We used the InVEST model and multivariate analysis to assess the interactions of land use, climate, and socioeconomic factors on hydrologic-related ecosystem services in the Beijing Ecological Conservation Development Zone (BECD) from 2000 to 2018. Our results show that land use shifts were mainly manifested by the conversion of cropland to forestland, grass land, and urban land, with conversion areas of 432 km2, 84.86 km2, and 162.57 km2, respectively. Water yield and water purification services exhibited significant temporal and spatial heterogeneity within the BECD. We also found that land use had the greatest impact on hydrologic-related ecosystem services, followed by climate and socioeconomic factors, with contributions of 44.29%, 7.09%, and 4.16%, respectively. Additionally, the contribution of the joint effect of land use and climate accounted for 13%. This study not only describes the variation in hydrologic-related ecosystem services within the BECD, but also offers a theoretical basis for policymakers and stakeholders to formulate land use policies.

1. Introduction

Ecosystem services can be defined as the direct and indirect contributions of ecosystems to humankind and are a bridge between natural ecosystems and the sustainable development of human societies [1,2,3]; hence, they have been a hot research topic in recent years [4,5]. Ecosystem services reflect the supply capacity of ecosystems to meet human needs based on the ecological structure and processes [5] and provide a broad range of basic life-support processes, such as water purification, water supply, and ecosystem goods (crops and timber), which play a vital role in human existence and development [3,6,7]. Due to the importance of water resources and the water cycle in ecosystems and human sustainable development, hydrologic-related ecosystem services have been the focus of attention in this field, especially in areas with acute water conflicts [8,9]. In hydrologic-related ecosystems, water provision and water purification are of interest because they can support the delivery of crucial ecosystem services [8], such as water purification, which can restore eutrophic waters and improve drinking water and species diversity [10].
Climate and land use change have been shown to have primary impacts on ecosystems and their associated ecosystem services [6,9,11,12]. Usually, the impact of climate change is widespread and causes relatively slow changes, but the consequences are irreversible, whereas ecological policy-induced land-use change has a less spatial impact with a quick but poor effect [13,14,15]. Climate change generally affects the supply of hydrologic-related ecosystem services [16], whereas ecological policy-induced land use affects supply, demand, and flow [4,17,18,19]. For instance, the most important land use change has been the expansion of cropland and urban land at the expense of forests and wetlands, which have been degraded [20,21,22]; this change can directly alter the provision and regulation of hydrologic-related ecosystem services [13,23], including water yield and water purification [8]. Land use changes can affect hydrologic-related ecosystem services by altering the properties of the underlying surface [24]. On a basin scale, land use change can be correlated with corresponding variations in hydrologic-related ecosystem services; increases in forestland and urban land raise water yield and enhance soil conservation, whereas reforestation and urbanization degrade water purification [25]. Zheng et al. (2016) found that ecological policy-induced land use change can alter water ecosystem types, patterns, processes, and services [4]. Schmalz et al. (2016) assessed hydrologic-related ecosystem services in three lowland river basins in Western Siberia and found that the spatial patterns of water flow and erosion-regulating services are influenced by seasonal change and land use change [26].
Other studies have evaluated the impacts of climate change on water yield and quantified ecosystem service provisioning under climate impact [11,16,27]. On the state scale, climate change has a greater effect than land use on water retention, nitrogen export, and phosphorus export [11]. Ferreira et al. (2019) projected that the negative effects of climate change are observed mainly in urban areas via a reduction in water quality [12]. Meanwhile, several studies have revealed that precipitation is the most critical climatic factor and positively affects water yield and water retention at both annual and seasonal time scales [24], and decreases in precipitation are reflected in substantial decreases in service water provisioning [28]. Existing studies have focused on the impact of land use and climate change on hydrologic-related ecosystem services and have seldom considered the comprehensive role of socioeconomic factors [16,25,28]. However, socioeconomic factors play a key role in connecting ecosystems with human society; they not only affect the supply, but also determine the demand for ecosystem services [29]. Most studies are related to the relationship among ecosystem services and socioeconomic factors [30,31], but the interaction of land use, climate, and socioeconomic factors is rarely considered [32,33], leading to an unclear understanding of their spatial heterogeneity and drivers.
Located in North China, Beijing has an extremely important status as the capital city and plays an important role as a political, economic, and cultural center. The rapid pursuit of socioeconomic factors over the past decades has been accompanied by dramatic changes in land use/cover, which has raised the risk of water pollution and water scarcity [15,16,18,34]. The Beijing Ecological Conservation Development Zone (BECD) is a crucial ecological barrier and water source protection area that supplies water and hydrologic-related resources to Beijing and North China. Here, the BECD was selected as the research area, and we aimed to (1) assess hydrologic-related ecosystem services from 2000–2018; (2) quantify land use drivers of hydrologic-related ecosystem services; and (3) determine the combined impacts and relative importance of land use, climate, and socioeconomic factors in determining shifts in hydrologic-related ecosystem services. We intend to fill this knowledge gap by analyzing the impacts of different drivers (land use, climate, and socioeconomic factors) on hydrologic-related ecosystem services and explaining their interplay in the ecological conservation area. Finally, understanding the interactions between factors helps identify potential synergies or conflicts, enabling policymakers to make informed decisions and prioritize interventions that maximize the restoration outcomes. This provides valuable information for decision-makers and stakeholders involved in land use planning and conservation, promoting sustainable development and ecosystem conservation.

2. Materials and Methods

2.1. Study Area

The study area is the BECD, which is located in the northwest mountainous area and ranges from 39°31′ N to 41°3′ N and from 115°25′ E to 117°30′ E (Figure 1). The BECD spans 8746.6 km2 and occupies 53.3% of the proportion of Beijing. Its annual mean temperature is 11.6 °C, annual precipitation is 630 mm, and precipitation is mostly concentrated in June–September, accounting for 70–80% of the annual precipitation. The BECD has an estimated population of 5,223,000, with a GDP of RMB 2629.5 billion as of 2018. Located upstream of the downtown area, the BECD provides a variety of ecosystem services for urban development, especially water supply and purification [35]. In recent years, with economic development and urbanization intensification in Beijing, the contradiction between human needs and water resources has deepened, putting great pressure on the supply of ecosystem services in BECD.

2.2. Data Analysis

2.2.1. Data Sources

This study used land use, climate, and socioeconomic data from 2000 and 2018 (Table 1). Thematic mapper images used to extract land use information were acquired from GloVis-Home (usgs.gov). The land use types on these maps were originally classified into forest, grassland, cropland, water land, urban, and others (unused land) [2] (Figure 2). The socioeconomic data were obtained from the Resource and Environment Science and Data Center (https://www.resdc.cn/ (accessed on 12 June 2021)). The observed precipitation, evaporation, and temperature were collected from meteorological stations, which were obtained from the China Meteorological Data Service Center (http://data.cma.cn/ (accessed on 12 June 2021)). The kriging interpolation method was used to calculate and evaluate the mean meteorological data based on the ArcMap 10.6 platform, and the spatial scale of raster data was finally unified to 90 m.

2.2.2. Methods to Quantify Hydrologic-Related Ecosystem Services

Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) is designed to provide information about how changes in ecosystems are likely to lead to changes in the flows of benefits to humans [36,37]. This study used the InVEST models to assess hydrologic-related ecosystem services in the ecological conservation area by using the module of water yield and water purification. The water yield and water purification have been verified with data (Table 1) in the BECD.
The InVEST water yield model estimates the relative contributions of water from different parts of a landscape, offering insight into how changes in land use patterns affect annual surface water yield; it is based on the Budyko curve and annual average precipitation [37]. This study determined the annual water yield Y(x) for each pixel on landscape x as follows:
Y ( x ) = ( 1   −   A E T ( x ) P ( x ) ) · P ( x )
where AET(x) is the annual actual evapotranspiration for pixel x, and P(x) is the annual precipitation on pixel x.
Water purification is a basic service provided by the ecosystem [37]; thus, we used the InVEST nutrient delivery ratio (NDR) to map nitrogen and phosphorus sources from watersheds and their transport to the stream. We determined the nitrogen and phosphorus export for each pixel on the landscape (x):
ALV(x) = HSS(x) pol(x)
where ALV(x) is the adjusted loading value at pixel (x), pol(x) is the export coefficient at pixel (x), and HSS(x) is the hydrologic sensitivity score at pixel (x), which is calculated as:
HSS ( x ) = λ ( x ) λ ( w )
where λ(x) is the runoff index at pixel x, calculated using the following equation, and λ(w) is the mean runoff index in the watershed of interest.
λ ( x ) = log ( ∑ U Y U )
where ∑ U Y U is the sum of the water yield of pixels along the flow path above pixel x. All spatial analyses were performed in ArcGIS 10.6.

2.2.3. Multivariate Analysis and Variance Partitioning

Redundancy analysis (RDA) is a common analysis method in ecological applications [38,39]. In RDA, a set of data for correlated variables is chosen to maximize the extent of their correlation with response variables. The ordination components are constrained to be linear combinations of the supplied driving variables [38]. Here, RDA was used to analyze the relationships of hydrologic-related ecosystem services to effect factors that were quantified in units of townships, including land use variables, climate variables, and economic variables. All the factors were natural log-transformed using the covariance matrix among factors with no need for further standardization [39]. We used the Legendre method to account for correlations between groups via the differentiation of unique and overlapping contributions from each group; this method can assign service variation to components linked to land use, climate, and socioeconomic factors and the intersections of these controls [39,40]. The results are presented as Venn diagrams. All these analyses were completed by using the vegan package in R.

3. Results

3.1. Land Use Changes from 2000 to 2018

Land use transfer in the BECD is mainly manifested in the conversion of crop land to forestland, grassland, and urban land. According to the maps of spatial changes in land cover and the chord diagram (Figure 2), which reflect the direction of land use transfer from 2000 to 2018, cultivated land was largely converted into woodland, grassland, and urban land, with areas of 432 km2, 84.86 km2, and 162.57 km2, respectively, and the change rate reached −44.55%. The urban area increased by 183.63 km2, with a change rate of 32.59%. The areas of wetland converted into cultivated land, woodland, and grassland were 17.15 km2, 26.07 km2, and 21.77 km2, respectively, with a change rate of −15.63%. The area of forestland increased the most, by 514.37 km2.

3.2. Spatiotemporal Pattern of Water Yield Services

Water yield services showed obvious temporal and spatial heterogeneity in the BECD. The analysis results showed that the service functions of water yield showed an overall upward trend from 2000 to 2018, with an increase of 9.05 × 108 m3 (Figure 3). From a spatial point of view, the water yield in the same year was unevenly distributed in different regions. A trend of degradation in water yield services was found in urban land of the BECD. When considering water yield change based on land use change pixels (Figure 4), the conversion of cropland to forest, urban, and grassland significantly increased water yield by 0.001, 0.0009, and 0.002 m3 per m2, respectively. The conversion of grassland to others and urban land decreased the water yield by 0.002 and 0.001 m3 per m2, respectively.

3.3. Spatiotemporal Pattern of Water Purification Services

Water purification services have strong temporal and spatial heterogeneity in the BECD. The calculation results of the InVEST model showed that the output of nitrogen and phosphorus displayed a decreasing trend in ecological conservation areas during 2000–2018 (Figure 5). The nitrogen output of the BECD was 1191.83 × 104 tons in 2018, decreasing by 10.89% compared with that in 2000. The phosphorus output of the ecological conservation area was 86.86 × 104 tons in 2018, a reduction of 16.27% compared with that in 2000.
From a spatial point of view, the output of nitrogen and phosphorus is unevenly distributed in different regions in the BECD. The output of nitrogen and phosphorus in the downstream area is higher than that in the upstream area, and the output of nitrogen and phosphorus in urban land is higher than that in forestland and grassland. The output of nitrogen and phosphorus showed an increasing trend in the local area of the BECD, of which the area of increased nitrogen output accounted for 13.64%, the area of reduced nitrogen output accounted for 86.36%, and the area of increased phosphorus output accounted for 9.51%. The proportion of variable areas is 4.12% and the proportion of reduced areas is 86.37%.
When considering water purification change based on land use change pixels (Figure 6), the conversion of cropland to forest, urban, grass, and wetland significantly decreased nitrogen and phosphorus export. At the same time, the conversion of urban land to forest, grass, and wetland also significantly decreased nitrogen and phosphorus export. The conversion of forest, grass, and wetland to crop land and urban land increased nitrogen and phosphorus export. In particular, the conversion of wetland to crop land increased nitrogen and phosphorus exports by 0.012 and 0.00084 kg/m2, respectively, and the conversion of urban land to woodland decreased nitrogen and phosphorus exports by 0.0066 and 0.00063 kg/m2, respectively.

3.4. Multivariate Analysis and Variance Partitioning of Driving Factors

Three successive RDA axes (Figure 7) showed that climate and land use change are the main driving factors of hydrologic-related ecosystem services, and they explain 64.7% of the variation. The first RDA axis was overwhelmingly superior and was driven by temperature (p < 0.01), land use change (crop to forest and urbanization), and precipitation (p < 0.05). The second RDA axis was driven by crop to forest, urbanization, and precipitation (p < 0.05), and was negatively related to population and cropland.
Venn graphics (Figure 8) indicate the percentage contributions of climate, socioeconomic, land use, and their interactions to hydrologic-related ecosystem services and to each service (including water yield, nitrogen purification, and phosphorus purification). The intersection area of Figure 8 represents the interplay between the driving factors, and significant values are highlighted in bold. After comprehensive consideration of the contribution of all driving factors, the contribution rate of land use, climate, and economic factors to hydrologic-related ecosystem services was 65.6%. The major effect of land use change (44%) was independent of climate and socioeconomic factors; the effect of climate was independent of land use and economic factors (7%); some effects of socioeconomic factors were independent of land use and climate (4%); and the most important contribution was the joint effect of land use with climate (13%), independent of economy.
For a single hydrologic-related ecosystem service (Figure 8), 53% of the total variation in water yield (ES1) was linked to land use change and 44% to land use change, independent of other driving factors; 19% of the variation in water yield was linked to climate; 11% was linked to land use and climate together, independent of other controls, and only 0.2% to climate and socioeconomic factors together; and only 2% was linked to socioeconomic factors. For nitrogen purification (ES2), 32% of the total variation was linked to land use change and 12% to climate independent of other driving factors; only 2% was linked to socioeconomic factors. For phosphorus purification, 30% of the total variation was linked to land use change; 14% was linked to climate independent of land use and socioeconomic factors; and 1% is linked to socioeconomic factors.

4. Discussion

4.1. Impact of Environmental Factors on Hydrologic-Related Ecosystem Services

Our research reveals the different contributions of land use, climate, and socioeconomic factors, and their interactions to hydrologic-related ecosystem services. Land use has the greatest impact on changes in hydrologic-related ecosystem services, followed by climate and socioeconomic factors. A key finding of our study is to quantify the contribution of the joint effect of land use and climate on hydrologic-related ecosystem services at 13%.
As mentioned in the published literature, at a large scale, climate change has a greater impact than land use on water conservation. In contrast, at smaller regional scales, land use presented a more important influence on nitrogen export and phosphorus export than climate [11,17,41], which is in accordance with the outcomes of this study. Large changes in land use occurred during the study period, and the main impact of land use change was observed in urbanization, expansion of cropland, and the conversion of cropland to forest, which significantly influenced the water yield, nitrogen export, and phosphorus export. The climate was relatively stable during the study period, and the impacts of precipitation were great according to the water purification services. However, socioeconomic factors were not found to significantly affect hydrological-related ecosystem services (Figure 8). This result is not consistent with previous research [29,42], mainly because slow changes in socioeconomic factors have been affected by the ecological protection policy of the BECD. Compared with Beijing areas [43,44], socioeconomic factors have less impact on ecological conservation areas due to the implementation of protection policies.

4.2. Spatiotemporal Changes in Hydrologic-Related Ecosystem Services in the BECD

Our hydrologic-related ecosystem services pattern and change maps showed that the conversion of farmland to forestland and grassland has resulted in increases in water yield; however, a trend of degradation in water yield was found in local areas, especially in urban land, mainly due to urbanization weakening the water yield service by reducing vegetation. The variance partitioning results presented here demonstrated that water yield changes are mainly related to land use changes and, to a lesser extent, climate. These findings corroborate the ideas of previous research, which maintain that land use typically results in large changes in water yield [11,45,46]. In our study, a decline in nitrogen and phosphorus export tended to increase water quality due to land conversion from agriculture to forests and grass, whereas it tended to decrease water quality in local areas, such as downstream areas or areas of urbanization (Figure 5), mainly as a result of the following: (1) forests and grass are more efficient at retaining nutrients and then purifying pollutants [47], and (2) urbanization leads to a decline in water quality due to an increase in nitrogen and phosphorus export. Multivariate analysis confirms that land use change is the first driver of water purification, followed by climate (Figure 7). The decline in water purification due to land use and climate change, especially land conversion from forests to farmland, can aggravate the negative effects of climate change on water purification [12]. In addition, the reductions in nutrient export are determined more by land use intensity; for example, forest restoration would lead to the greatest reductions in nitrogen and phosphorus export; however, urban sprawl and the intensification of agricultural production would cause substantial imports of negative externalities nutrients [4,48,49,50,51]. To conclude, land use change influences hydrologic-related ecosystem services via ecological processes, and climate change is an inextricable part of water provisioning and purification services [52].

4.3. Impact of Regional Ecological Policies on Hydrologic-Related Ecosystem Services

Although socioeconomic factors have little impact on hydrologic-related ecosystem services, they indirectly affect water yield and purification by directly changing land use types and climate factors (evaporation). To promote ecological protection, a series of policies involving the “General Planning of Beijing Municipality (2016–2035)”, the “Red Lines for Ecological Protection”, and the “13th Five-Year Plan of Environmental Protection and Ecological Construction” were introduced [42,53,54]. These policies have made it possible to return farmland to forests and then reduce evaporation due to increased vegetation coverage. The results in Figure 8 can also support this point, and the contribution rate of socioeconomic factors and land use independent of climate to ES is −1.68, which means that the protection policies reduce the negative impact of land use change on hydrologic-related ecosystem services. The contribution rate of socioeconomic factors independent of land use and climate to ES is 4.16%, but the overlap between socioeconomic factors and climate and land use is negative (−0.68%), which means that protection policies increase the positive impact of climate and land use change on hydrologic-related ecosystem services. This finding matches those mentioned in earlier studies that vegetation restoration in croplands can improve ecosystem services, and policymakers should set protection policies according to the function of ecological conservation areas [55,56]. Our study confirms that land use policies are effective, but how the effects are sustained is a question, and without policy support, negative effects can increase: failure to consider socioeconomic drivers can lead to implementation failure and low efficiency; however, this study can help with local land use decisions that minimize the impact of land use change on hydrologic-related ecosystem services [5,57,58,59,60,61].

5. Conclusions

In conclusion, this study used the InVEST model and multivariate analysis to assess the impact of land use, climate, and socioeconomic factors on hydrologic-related ecosystem services in the BECD for the period of 2000–2018. During this period, land use had the greatest impact on changes in hydrologic-related ecosystem services, followed by climate and socioeconomic factors. Practical land use management can effectively improve the adaptation capacity of water ecosystems to climate change and, thus, improve the provision of hydrologic-related ecosystem services. However, this study relied on data from 2000 to 2018, which restricts the analysis and comparison of changes in hydrologic-related ecosystem services to this specific time period and may not capture more recent changes. Additionally, although we employed the InVEST model and multivariate analysis, there may be other factors and interactions that were not considered in our study, such as human activities (pollution sources or excessive water usage), as well as infrastructure development. These factors could potentially limit the comprehensive understanding of the drivers and spatial heterogeneity of hydrologic-related ecosystem services. Future studies should aim to consider more factors (pollution sources, excessive water usage, infrastructure, etc.) and incorporate more up-to-date data to provide a comprehensive understanding of long-term trends.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/w15112022/s1, Figure S1: Change of climate factors (temperature and precipitation). Figure S2: Change of socioeconomic factors (populaiton and GDP).

Author Contributions

Individual contributions to the manuscript were as follows: conceptualization, L.L., R.L., T.C. and Y.Y.; methodology, L.L., R.L. and T.C.; formal analysis, investigation, L.L., Y.Y., T.C., R.L. and H.Z.; writing—original draft preparation, L.L. and R.L.; writing—review and editing, all authors. 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 (41871218 and 42171099).

Data Availability Statement

Data will be available upon request. Images employed for the study will be available online for readers (Supplementary materials).

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Location of the BECD.
Figure 1. Location of the BECD.
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Figure 2. Land use changes from 2000 to 2018 in the BECD.
Figure 2. Land use changes from 2000 to 2018 in the BECD.
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Figure 3. Changes in the spatial distribution of water yield services from 2000 to 2018.
Figure 3. Changes in the spatial distribution of water yield services from 2000 to 2018.
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Figure 4. Change in water yield per pixel of changing land use.
Figure 4. Change in water yield per pixel of changing land use.
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Figure 5. Changes in the spatial distribution of water purification services from 2000 to 2018.
Figure 5. Changes in the spatial distribution of water purification services from 2000 to 2018.
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Figure 6. Change in water purification per pixel of changing land use.
Figure 6. Change in water purification per pixel of changing land use.
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Figure 7. Hydrologic-related ecosystem service-related parameters from redundancy analysis (RDA); green circles are towns. The hydrologic-related ecosystem services are WY, water yield; WPp, phosphor of water purification; and WPn, nitrogen of water purification. The climate variables are Pre, precipitation; and Tem, temperature. The land-use changes are CF, cropland to forest, urbanization, and cropland expansion. The socioeconomic factors are GDP (gross domestic product) and population. The initial value is the normalized sum for all hydrologic-related ecosystem services (explained: 64.7%).
Figure 7. Hydrologic-related ecosystem service-related parameters from redundancy analysis (RDA); green circles are towns. The hydrologic-related ecosystem services are WY, water yield; WPp, phosphor of water purification; and WPn, nitrogen of water purification. The climate variables are Pre, precipitation; and Tem, temperature. The land-use changes are CF, cropland to forest, urbanization, and cropland expansion. The socioeconomic factors are GDP (gross domestic product) and population. The initial value is the normalized sum for all hydrologic-related ecosystem services (explained: 64.7%).
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Figure 8. Variance partitioning (%) for all driving factors considered together and for each hydrologic-related ecosystem separately. The hydrologic-related ecosystem services (ES) are as follows: ES1, water yield; ES2, nitrogen purification; ES3, phosphorus purification. The drivers are climate (Pre, precipitation; Tem: temperature), LUCC (CF, cropland to forest; urbanization, cropland expansion), and economic (socioeconomic: GDP and population). Positive and negative values represent the degree of contribution.
Figure 8. Variance partitioning (%) for all driving factors considered together and for each hydrologic-related ecosystem separately. The hydrologic-related ecosystem services (ES) are as follows: ES1, water yield; ES2, nitrogen purification; ES3, phosphorus purification. The drivers are climate (Pre, precipitation; Tem: temperature), LUCC (CF, cropland to forest; urbanization, cropland expansion), and economic (socioeconomic: GDP and population). Positive and negative values represent the degree of contribution.
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Table
Table 1. Drivers for the analysis of hydrologic-related ecosystem services.
Table 1. Drivers for the analysis of hydrologic-related ecosystem services.
CategoryFactors and DescriptionData Source
Land useLand use: area of forest, grass, crop, water, urban and other landGloVis-Home (usgs.gov)
ClimatePrecipitation: annual precipitation, mmChina Meteorological Data Service Center (http://data.cma.cn/) (accessed on 12 June 2021)
Temperature: annual air temperature, °C
SocioeconomicPopulation: total populationResource and Environment Science and Data Center (https://www.resdc.cn/) (accessed on 12 June 2021)
GDP: gross domestic product
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Li, L.; Yang, Y.; Cui, T.; Li, R.; Zheng, H. Land Use, Climate, and Socioeconomic Factors Determine the Variation in Hydrologic-Related Ecosystem Services in the Ecological Conservation Zone, Beijing, China. Water 2023, 15, 2022. https://doi.org/10.3390/w15112022

AMA Style

Li L, Yang Y, Cui T, Li R, Zheng H. Land Use, Climate, and Socioeconomic Factors Determine the Variation in Hydrologic-Related Ecosystem Services in the Ecological Conservation Zone, Beijing, China. Water. 2023; 15(11):2022. https://doi.org/10.3390/w15112022

Chicago/Turabian Style

Li, Lijuan, Yanzheng Yang, Tengyu Cui, Ruonan Li, and Hua Zheng. 2023. "Land Use, Climate, and Socioeconomic Factors Determine the Variation in Hydrologic-Related Ecosystem Services in the Ecological Conservation Zone, Beijing, China" Water 15, no. 11: 2022. https://doi.org/10.3390/w15112022

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