The Influence of Vegetation on Climate Elements in Northwestern China

Abstract

Vegetation plays a crucial role in maintaining the balance between nature, water and soil resources. However, understanding its impact mechanisms in arid and semi-arid areas remains limited. This study aims to analyze the spatial–temporal characteristics of the vegetation leaf area index (LAI) and climate elements in typical regions of northwest China and the correlations between LAI and climate elements; it also aims to explore the influence of regional vegetation growth on climate change. The results reveal significant correlations between LAI and various climate elements. Specifically, within the same region, surface temperature, precipitation, vegetation transpiration, and total evaporation show positive correlations with the LAI, whereas surface albedo shows a negative correlation. Vegetation may affect climate through both heat and water exchange between the land and atmosphere. Increased vegetation leads to the enhanced absorption of solar radiation by the land surface, elevating surface temperature. Increased levels of vegetation also increase vegetation transpiration and total evaporation, increasing the water vapor content in the atmosphere and thus leading to increased surface precipitation. Therefore, vegetation distribution plays a role in climate change, and ecological restoration projects in the northwest region hold significant potential for addressing ecological challenges in its arid and semi-arid areas.

1. Introduction

Vegetation activity serves as an indispensable nexus, connecting the realms of atmosphere, soil, hydrosphere, and biosphere. Against the backdrop of climate warming, the phenomenon of vegetation degradation has emerged in various parts of the world, particularly in arid and semi-arid regions, exerting a profound impact on regional ecological equilibrium and sustainable development. Concurrently, vegetation activity assumes a pivotal role in harmonizing the ecological and atmospheric systems, manifesting its paramount significance in the regulation of material and energy exchanges between them [1,2,3]. Consequently, the degradation of vegetation inevitably leads to climate perturbations. Therefore, investigating the interactions and underlying mechanisms between climate change and vegetation provides valuable insights into the transformative features of regional climate and ecology within the overarching context of global warming.

A multitude of scholars have conducted extensive research into the mechanisms underlying the interaction between vegetation and climate change [4,5,6]. Existing studies have shed light on three primary pathways through which vegetation activity exerts regional feedback. Alkama et al. suggest that vegetation activity induces alterations in surface albedo, thereby exerting further influence on net shortwave radiation [7]. Lian et al. demonstrate that plant transpiration consumes a substantial portion of the net radiation absorbed by the land surface, subsequently releasing this energy back into the atmosphere in the form of sensible and latent heat. Consequently, the augmentation of vegetation activity profoundly impacts the distribution of net surface radiation between latent and sensible heat fluxes [8]. Chen et al. propose that changes in vegetation activity lead to modifications in surface roughness, indirectly affecting the magnitude and spatial distribution of latent and sensible heat fluxes [2].

Currently, the issues of “land desertification” and “deforestation of tropical rainforests” have garnered significant attention among scientists studying global vegetation changes. Land desertification, characterized by increased surface albedo, reduced soil moisture content, and decreased surface roughness, contributes to a decrease in precipitation and further degradation of vegetation and soil, thereby accelerating the desertification process. The deforestation of tropical rainforests results in a reduction in forest area, leading to decreased precipitation, elevated temperatures, diminished evapotranspiration, and weakened local water cycling [9]. In essence, a close relationship exists between vegetation cover and local climate characteristics. Whether it involves the expansion or degradation of vegetation, it significantly influences precipitation patterns and distribution, average surface temperature, and surface albedo [10,11]. The conversion of cropland to forests and desert greening in the northwest region of China significantly impacts local climate factors, and it is beneficial for strengthening and shifting the summer monsoon towards the north. This, in turn, affects precipitation, surface runoff, and soil moisture in the eastern regions [12,13]. However, some studies suggest that changes in the underlying surface of the western desert region may not cause large-scale alterations in atmospheric circulation patterns but rather variations in system strength. When the underlying surface is covered with grassland vegetation, it reinforces the upward airflow in the experimental area, weakening the thermally driven circulation between the plateau and the desert. Simultaneously, soil and surface temperatures rise, upper-level air humidity increases, and topographic thermal circulation weakens. These factors lead to decreased precipitation on the plateau and slightly increased precipitation in the North China region [14].

The northwest region of China serves as a typical arid and semi-arid area, exhibiting high sensitivity to global climate change, while the regional climate variations in this area are characterized by complexity and uncertainty [15,16]. In recent years, ecological restoration projects have been implemented in the northwest region, leading to a continuous increase in vegetation coverage through measures such as land conversion to forest and grassland restoration. Investigating the impact of regional ecosystem vegetation distribution on climate change in the northwest region will greatly contribute to addressing ecological issues in this area. This study aims to examine the role of vegetation in local climate and explore the influence of vegetation distribution on climate change in the northwest region. By studying the spatial–temporal distribution characteristics of vegetation and climate elements in northwest China and conducting correlation analysis between vegetation distribution and regional climate elements, we aim to uncover the potential reasons for the impact of ecosystem vegetation distribution on regional climate.

2. Materials and Methods

The northwest region of China is characterized by complex terrain, including plateaus, basins, mountains, and deserts. As a result, the vegetation coverage in this region exhibits significant variations. Key parameters for vegetation morphology include vegetation coverage and LAI. Vegetation coverage refers to the percentage of the vertical projection area of vegetation on the ground to the total statistical area, while LAI represents the multiple of the total leaf area of vegetation per unit land area. Given the diverse vegetation types in the northwest region of China, studying either vegetation coverage or LAI alone cannot fully capture the vegetation coverage situation. Therefore, this study combines these two parameters to provide a comprehensive understanding of vegetation coverage in the northwest region.

This study focuses on the northwest region of China within the longitude range of 73° E–109° E and latitude range of 35° N–50° N (Figure 1). The data used in this study includes monthly average vegetation coverage, LAI, surface temperature, surface precipitation, surface albedo, and other variables from 1979 to 2020, obtained from ERA5-Land (ERA5-Land is the fifth-generation land reanalysis dataset provided by the European Centre for Medium-Range Weather Forecasts, which accurately describes past climate with a temporal resolution of 1 h and a spatial resolution of 0.1° × 0.1°). Additionally, precipitation data from CN05.1 are used (CN05.1 is a reanalysis data set based on daily observations from over 2400 national-level stations in China, with a spatial resolution of 0.25° × 0.25°, interpolated by the National Meteorological Information Center). This study utilizes linear trend analysis and Pearson correlation analysis.

Linear trend estimation involves establishing a univariate linear regression between climate variables and time [17]. In Equation (1), X_i represents the meteorological variable, a₀ is the regression constant, and b is the regression coefficient. The sign and magnitude of b indicate the direction and magnitude of the variable’s trend and change. A negative value of b signifies a decreasing trend of variable X_i over time, while a positive value indicates an increasing trend. The specific calculation formula is as follows:

$$X_i=a_0+b{t}_i, (i=1,2,3,4\dots n)$$

(1)

The Pearson correlation coefficient is used to measure the linear relationship between two variables [18]. In this study, it is used to calculate the correlation between leaf area index and climate factors. If the two variables are denoted as X and Y, the specific calculation formula is as follows:

$$R=\frac{{\displaystyle {\sum }_{i=1}^n(X_i-\overline{X})}(Y_i-\overline{Y})}{\sqrt{{\displaystyle {\sum }_{i=1}^n{(X_i-\overline{X})}^2}}\sqrt{{\displaystyle {\sum }_{i=1}^n{(Y_i-\overline{Y})}^2}}}$$

(2)

3. Results

3.1. Spatiotemporal Evolution of Surface Vegetation in the Northwest Region

The high vegetation in the northwest region of China is primarily concentrated in the Tianshan Mountains and Qilian Mountains, while the low vegetation is mainly distributed in the Tianshan Mountains, Qilian Mountains, and the surrounding areas of the Junggar Basin (Figure 2). Based on the distribution of high and low vegetation in the northwest region of China, we selected the Tianshan region as the typical area with the highest vegetation coverage (Region I), the Qinghai–Tibet Plateau as the typical area with relatively high vegetation coverage (Region II), and the Taklimakan Desert as the typical area with low vegetation coverage (Region III) (Figure 2d).

3.2. Spatiotemporal Evolution of Surface Temperature in the Northwest Region

Changes in vegetation cover can lead to significant differences in the physical and biological characteristics of the land surface, thereby altering climate elements and influencing climate change. Figure 3d–f show that the surface temperature in Region I ranges from 273 to 277 K (0–4 °C), in Region II it ranges from 264 to 269 K (−9–4 °C), and in Region III it ranges from 287 to 290 K (14–17 °C). The surface temperature in Regions I and II has significantly increased (p < 0.01), while the surface temperature in Region III shows an increasing trend. The interannual and decadal variations in Regions I and III are generally similar, with the highest surface temperature occurring in 2008. In that year, Xinjiang experienced the most severe drought since 1974, and Regions I and III, which are located in Xinjiang, were affected by the drought, resulting in a sudden increase in surface temperature. The surface temperature in desert areas even reached 290 K. In comparison, the surface temperature in Region II increased more gradually. This is because this region is located in the Qinghai–Tibet Plateau, where there is a small amount of snow cover on the surface. The snow cover acts as insulation, keeping the surface temperature lower than in Region I and preventing drastic changes.

3.3. Spatiotemporal Evolution of Surface Albedo in the Northwest Region

Surface albedo refers to the ratio of solar radiation reflected by the Earth’s surface to the total solar radiation reaching the surface. It is an important indicator of the Earth’s ability to reflect solar radiation. In recent years, the surface albedo in the northwest region has significantly decreased (p < 0.01), and there are clear decadal variations. The surface albedo has remained above 0.3 almost every year, but it suddenly dropped below 0.29 in 2008 (Figure 3a). Research by Lu Yunbo et al. has shown that surface albedo in arid and semi-arid areas is negatively correlated with temperature, and high temperatures are often associated with droughts [19]. The drought in Xinjiang in 2008 meant that the temperature was higher that year, leading to a significant decrease in surface albedo (Figure 4b). This indicates that the average surface albedo in the western Tianshan Mountains and Kunlun Mountains is relatively high, above 0.5, while the average surface albedo in most areas of the northwest region is relatively low, below 0.4.

From the standardized anomalies of the three typical regions in Figure 4c, it can be seen that before 1995, the surface albedo in the three regions had their own characteristics. After 1995, the interannual variations in Regions I and II were roughly similar, while Region III showed larger fluctuations. Comparing the temporal distribution of the three regions in Figure 4d–f, it can be observed that the surface albedo in Region I ranges from 0.30 to 0.42, showing a significant decrease (p < 0.01) with decadal variations, reaching its lowest point during the severe drought in Xinjiang. The surface albedo in Region II ranges from 0.34 to 0.44, showing a slight increase, reaching its maximum value in 2019. The surface albedo in Region III ranges from 0.29 to 0.30; overall, it remains relatively stable, but with large interannual variations during the period of 1990–2010, reaching its maximum value in 2002.

3.4. Spatiotemporal Evolution of Surface Precipitation in the Northwest Region

The impact of vegetation cover change on surface precipitation in the northwest region of China is also significant. As can be seen from Figure 5a,b, surface precipitation in the northwest region has significantly increased (p < 0.01) in recent years, showing decadal variations, reaching its maximum value in 2016. The average annual surface precipitation in the Taklimakan Desert, Turpan Basin, and Qaidam Basin is the lowest, below 100 mm, while in the Alxa Plateau, Junggar Basin, and Qinghai–Tibet Plateau, the average annual precipitation is relatively low, below 30 mm. The precipitation in the Qilian Mountains and Tianshan Mountains is relatively high, above 400 mm.

The time series of surface precipitation in the three typical regions in Figure 5d–f show that the decadal variations in the three regions are basically consistent, with a peak in precipitation around 2017. The surface precipitation in Region I ranges from 250 to 500 mm, showing a significant increase (p < 0.01) over the 42-year period, with regular decadal variations. The surface precipitation in Region II ranges from 120 to 250 mm, showing a significant decreasing trend (p < 0.05), with more positive anomalies than negative anomalies. Since 2000, there has been a larger change in precipitation, with a significant decrease in precipitation in 2013–2014. The precipitation in Region III ranges from 20 to 100 mm, and this region is influenced by high mountains, making it difficult for water vapor to be transported, resulting in a slight overall increase in precipitation. There are larger interannual variations, with smaller changes during the period of 1990–2010. It can be concluded that surface precipitation in the northwest region of China increases with the increase in vegetation cover.

3.5. Spatiotemporal Evolution of Total Evaporation in the Northwest Region

Figure 6a,b show the temporal distribution and spatial distribution of total evaporation in the northwest region of China over the past 42 years. Although the overall trend of total evaporation is decreasing, there are large interannual variations. The total evaporation in the Taklimakan Desert and Qaidam Basin is extremely low, below 0.2 mm, while in the Junggar Basin and Alxa Plateau, the total evaporation is relatively low, below 0.8 mm. The total evaporation in the Tianshan Mountains, Turpan Basin, and Qilian Mountains is relatively high, above 1.2 mm.

From the standardized anomalies of total evaporation in the three regions in Figure 6c, it can be concluded that the interannual variations in the three regions are roughly the same. The number of positive anomalies and negative anomalies is almost equal in Region I and Region III, while in Region II, there are more positive anomalies than negative anomalies, and most of them occurred after 1996. Analyzing the temporal distribution of total evaporation in the three regions (Figure 6d–f), Region I shows a significant increasing trend (p < 0.01), with total evaporation ranging from 0.95 to 1.20 mm. Region II shows a significant increase (p < 0.01), with total evaporation ranging from 0.75 to 1.05 mm. Region III shows a decreasing trend, with total evaporation ranging from 0.05 to 0.25 mm. In conclusion, with the increase in vegetation cover, the total evaporation also increases.

3.6. The Impact of Vegetation Distribution on Surface Climate Elements in Ecosystems

Based on Figure 2, it can be observed that the distribution of low vegetation LAI is more uneven and shows significant variations compared to high vegetation LAI. Therefore, the following discussion will focus on low vegetation LAI. Considering that Region III is located in a desert area with little variation in vegetation LAI, the analysis will only focus on Region I and Region II.

As the LAI increases, the surface temperature in Region I generally shows an upward trend, with a correlation coefficient (R value) of approximately 0.91 (Figure 7a). In Region II, the surface temperature also increases overall with an increase in LAI, with an R value of approximately 0.82 (Figure 7e). Thus, it can be concluded that there is a significant positive correlation between surface temperature and LAI.

From Figure 7b,d, it can be observed that the surface albedo in both Region I and Region II decreases as the LAI increases. The decreasing trend is less significant in Region II compared to Region I. The correlation coefficient (R value) between surface albedo and LAI is approximately −0.82 for Region I and approximately −0.66 for Region II. The difference in R values between the two regions is relatively large. Comparing Region I and Region II, it can be inferred that the more vegetation there is, the more sensitive the surface albedo is to changes in vegetation cover, and there is a negative correlation between surface albedo and LAI.

Figure 7c,g depict the relationship between surface precipitation and LAI in Region I and Region II. It can be observed that surface precipitation in both regions increases overall as the LAI increases, with a more pronounced upward trend in Region I. The R value is approximately 0.81 for Region I and approximately 0.89 for Region II. The correlation coefficients for surface precipitation and LAI are relatively close in the two regions, indicating a positive correlation.

From Figure 7d,h, it can be seen that the total evaporation in Region I shows a significant upward trend as the LAI increases, with an R value of approximately 0.93. In Region II, the total evaporation generally increases with an increase in LAI, with an R value of approximately 0.88. The correlation coefficients for total evaporation and LAI in both regions are around 0.9, indicating a significant positive correlation.

4. Discussion

Vegetation has a significant impact on the Earth’s surface energy balance through modifying biophysical properties such as surface albedo, roughness, and evapotranspiration rates. These modifications drive changes in the exchange of energy and water between the land surface and the atmosphere, thereby affecting the dynamics of climate change [20,21]. Typically, forested areas show lower surface albedo compared to grasslands and croplands. The conversion of grasslands or croplands into forests results in decreased surface albedo, leading to enhanced absorption of net shortwave radiation, which contributes to surface warming [22]. This article provides a preliminary inference on the possible reasons for the impact of ecosystem vegetation distribution on regional climate. It suggests that vegetation distribution may influence climate change through the following two aspects. Firstly, vegetation cover can affect climate by altering the heat exchange between the land and the atmosphere. As mentioned earlier, in the same region, the land surface temperature is positively correlated with the LAI, while the surface albedo is negatively correlated with the LAI. With the increase in actual vegetation, the surface albedo decreases, resulting in less reflection of solar radiation and more absorption by the ground, leading to a significant increase in land surface temperature [22].

Many studies indicate that greening, or the increase in vegetation, could lead to an increase in precipitation [23,24]. Secondly, vegetation cover can affect climate by altering the water exchange between the land and the atmosphere. As mentioned earlier, surface precipitation, vegetation transpiration, and total evaporation are all positively correlated with the LAI. With the increase in vegetation, both vegetation transpiration and total evaporation increase, leading to an increase in atmospheric water vapor content and consequently an increase in precipitation.

After conducting a comparative analysis of the influence of vegetation distribution on various climate elements and performing a correlation study between LAI and these climate elements, the research has yielded the following principal conclusions:

(1) In the same region, the land surface temperature is positively correlated with the LAI, and the correlation coefficients are similar across different regions. The surface albedo is negatively correlated with the LAI, and the negative correlation becomes more significant in regions with more vegetation. Surface precipitation is positively correlated with the LAI, and the correlation coefficients are similar across different regions. Vegetation transpiration is positively correlated with the LAI, and the positive correlation becomes more significant in regions with more vegetation. Total evaporation is positively correlated with the LAI, and the correlation coefficients are similar across different regions.

(2) Based on the correlation analysis between the LAI and climate variables within Region I and Region II, a clear pattern emerges. Vegetation cover exhibits a direct, positive correlation with several climate elements including temperature, precipitation and evaporation, while showing an inverse relationship with surface albedo. The vegetative patterns within these ecosystems play a crucial role in climate dynamics, potentially influencing climate change through the modified exchange of thermal energy and moisture with the atmosphere. An increase in vegetation cover correlates with a decrease in surface albedo, leading to a rise in land surface temperatures. Concurrently, as vegetation cover expands, there is a corresponding increase in transpiration and the total rate of evaporation, contributing to increased atmospheric humidity and potentially an increase in precipitation.

There are also limitations in this study, as the specific physical mechanisms underlying the impact of vegetation on climate factors in the northwest region were only roughly investigated. In future research, we will utilize intrinsic biophysical mechanisms [25] to further explore the effects of vegetation on factors such as temperature under different scenarios.

5. Conclusions

This study primarily investigated the spatiotemporal distribution characteristics of LAI in typical vegetation areas of northwest China from 1979 to 2020. It also analyzed the correlation between LAI in these regions and various climate elements including temperature, albedo, precipitation, and evapotranspiration. By comparing the relationship between the low vegetation LAI and climate elements in two typical regions, one can infer the influence of vegetation changes on water and heat, which in turn affects the climate. This aids in understanding the potential mechanisms of vegetation impact on climate in arid and semi-arid areas. With an increase in LAI, surface albedo decreases, leading to an increase in the absorption of net shortwave radiation, thereby causing surface warming. This results in a positive correlation between the low vegetation LAI and temperature. In conclusion, the relationship between vegetation and climate is not only influenced by the effect of climate on vegetation but also influenced by the effect of vegetation on climate through feedback mechanisms. Specifically, in the case of the northwest region of China, the presence of vegetation reduces surface albedo, increases land surface temperature, and increases surface precipitation through the increase in vegetation transpiration and total evaporation. The present study acknowledges certain limitations arising from the complex interactions between vegetation and climate. Our analysis has focused on examining correlations between these factors. Future research will aim to quantitatively investigate the impact of vegetation on climate elements, particularly emphasizing measurable effects on temperature. Moreover, our ongoing research endeavors will prioritize elucidating the biophysical mechanisms, which may contribute to a more comprehensive understanding of how vegetation influences climate dynamics.