Next Article in Journal
Urban Fire Risk Dynamics and Mitigation Strategies in Shanghai: Integrating Spatial Analysis and Game Theory
Previous Article in Journal
Informal Urban Biodiversity in the Milan Metropolitan Area: The Role of Spontaneous Nature in the Leftover Regeneration Process
Previous Article in Special Issue
Conservation Responsibility for Priority Habitats under Future Climate Conditions: A Case Study on Juniperus drupacea Forests in Greece
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Land
Volume 13
Issue 8
10.3390/land13081124
land-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Characteristics of Changes in Typical Mountain Wetlands in the Middle and High Latitudes of China over the Past 30 Years

by
Nana Luo
,
Rui Yu
and
Bolong Wen
*
Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China
*
Author to whom correspondence should be addressed.
Land 2024, 13(8), 1124; https://doi.org/10.3390/land13081124
Submission received: 14 June 2024 / Revised: 17 July 2024 / Accepted: 22 July 2024 / Published: 24 July 2024
(This article belongs to the Special Issue Assess the Effects of Climate and Land-Use Change on Plant Species Distribution)
Browse Figures
Versions Notes

Abstract

:
Analysis of the driving mechanisms of wetland change can help identify spatial differences in the mechanisms affecting various elements, enabling a more scientific approach to the conservation and utilization of wetlands. This study investigated the impacts of natural and anthropogenic factors on the spatiotemporal evolution of the Altay and Greater and Lesser Khingan Mountains areas using Landsat satellite image data from 1980 to 2018 and fieldwork data from 2019 to 2020. A transfer matrix, correlation analysis, and dynamic characteristics were applied to calculate and analyze the transformation types and areas of wetland resources across all consecutive periods. Finally, the dominant factors influencing the spatiotemporal evolution of the wetland were explored and revealed using the drought index (Standardized Precipitation Index, SPEI) and statistical almanacs. The results showed: (1) From 1980 to 2018, the wetlands area in the Altay Mountains exhibited a decreasing trend, whereas the wetlands area in the Greater and Lesser Khingan Mountains showed an increasing trend. The primary type of wetland transfer in the Altay Mountains was grassland, whereas in the Greater and Lesser Khingan Mountains regions, the primary types of wetland transfer were grassland and forestland. The wetlands area transferred out of the Altay Mountain region was larger than the area of wetland types transferred into during 2010–2018, whereas the wetland areas of the Greater and Lesser Khingan Mountain areas showed the opposite trend. (2) From 1980 to 2018, the wetland ecosystem types in the Altay Mountains exhibited the highest dynamic and conversion degrees of the channels. Similarly, the mountain areas of the Greater Khingan Mountains showed the highest dynamic and conversion degrees of marshes and channels among the wetland types. In addition, the mountainous areas of the Lesser Khingan Mountains showed the highest dynamic and conversion degrees for reservoirs and rivers. (3) Natural driving factor analysis revealed that the SPEI values in the Altay Mountains and the Greater and Lesser Khingan Mountains areas exhibited an increasing trend, indicating that the climate has been warm and humid over the past 30 years and that the expansion of cropland and human-made wetland areas has been significantly influenced by human activities. Therefore, the wetland areas of the Greater and Lesser Khingan Mountains in the northeast are strongly influenced by human activities, whereas the wetland in the Altay Mountains in the northwest is strongly influenced by the climate.

1. Introduction

Wetland ecosystems, often referred to as the “kidneys of the Earth”, offer a range of ecosystem services to humans, including flood regulation, water conservation, and greenhouse effect mitigation [1,2]. Wetlands account for 6% of the Earth’s land area and retain approximately 770 billion tons of carbon, representing approximately 35% of the carbon storage in the terrestrial ecosystem. Approximately 500 billion tons of this carbon are stored in peatlands [3]. For example, 1.9 billion tons of peat are stored in 8 million ha of Zoige wetlands. This implies that the destruction of 1 ha of wetlands leads to carbon dioxide emissions of 15 thousand tons [4,5]. Therefore, understanding the evolution of wetland ecosystems requires an urgent investigation of the geographical and temporal properties of wetlands, as well as their driving factors.
Changes in wetlands are driven by both natural and artificial sources, and their effects vary depending on the type of wetland [6]. Changes in river wetland areas have been shown to be positively correlated with changes in temperature (mean annual temperature and extreme minimum temperature) and forest areas, whereas changes in settlement built-up areas and mean annual temperature are positively correlated with changes in reservoir wetland areas [7]. The causes and mechanisms of wetland degradation differ according to the geography and type of wetland [8,9]. For example, there has been a significant reduction in marshes and reservoir wetlands in Central and Eastern China, whereas an increase in river and lake wetlands has mainly been observed in Western China [10]. However, direct human activity may also be a major cause of wetland changes. In northern China, large areas of forestland, grasslands, and wetlands have been transformed into agricultural land, whereas in southern China, large areas of agricultural land have been transformed into settlement areas [11,12]. A study of wetland changes over the past 40 years in Shenzhen, China’s fastest-growing city, found that urban expansion was the main cause of wetland loss, with impacts varying according to wetland type [13]. Regional socioeconomic disparities and variations in the natural environment are the primary factors contributing to the differences in wetland dynamics across administrative regions [14].
Global warming will cause changes in the water cycle to a certain extent, resulting in an uneven spatial and temporal distribution of water resources. This affects the wet and dry conditions of the climate and disrupts the balance between the supply and demand of water resources [15,16]. Droughts and floods are among the most significant meteorological disasters in China, and droughts are particularly frequent, long-lasting, and widespread. These events have severe impacts on the national economy, particularly on agricultural production. In recent years, research on drought changes has received extensive attention from scholars [17,18]. Various calculation methods based on drought and flood indices have been proposed, both nationally and internationally. These methods include the Palmer Drought Index (PDI), the Surface Water Supply Index (SWSI), the Standardized Precipitation Index (SPI), the Standardized Precipitation Evapotranspiration Index (SPEI), the Relative Moisture Index (MI), and the Comprehensive Drought Index (CI). Studies on droughts and floods at regional and global scales have been conducted [19]. Among them, the SPEI not only considers the role of temperature and precipitation in drought formation but also has the characteristics of multiple timescales, which can accurately reflect dry and wet conditions. The SPEI multi-timescale includes scales of 1, 3, 6, 9, 12, 24, and 36 months [20]. In this study, we used the 12-month SPEI and assessed the changes in SPEI 12 to analyze the climate drivers of wetland area changes. Researchers nationally and internationally have conducted studies in different regions using this method [21,22]. In particular, the SPEI was selected to investigate the influence of climate on wetland areas in the Altay Mountains of northwest China and the Greater and Lesser Khingan Mountains of northeast China.
The Altay Mountains are typical arid and semi-arid regions with high alpine mountains. Dry and cold climates have been an important factor limiting ecosystem functions in the region for many years [23,24]. This study on Altay Mountain wetlands primarily focused on the investigation of wetland resources, the distribution of wetland spatial patterns, and the analysis of landscape pattern index changes in land use types. There is a lack of research and analyses on the dynamic changes in typical mountain wetlands in alpine mountains. Combined the analysis of driving factors with climate and human activities [25,26]. As an important wetland distribution area in China, the response of wetland ecosystems to climate change in northeast China has received widespread attention [27,28], as it plays an important role in maintaining regional ecological security [29]. Some studies have shown that the average annual temperatures in the Greater and Lesser Khingan regions have increased over the past 30 years [30]. Few studies have characterized the changes in mountain wetlands in the Greater and Lesser Khingan Mountains. In addition, limited research has compared the dynamics of mid- to high-latitude mountain wetlands in northeast and northwest China.
Climate change poses a serious threat to the fragile wetland ecosystems of the mid- to high-latitude mountainous region of northern China. At the same time, frequent human activities have produced a non-negligible effect on the wetland ecosystems of alpine mountain wetlands. In this study, we combined remote sensing image data, fieldwork data, and land use data to establish a wetland landscape over 38 years to analyze the dynamic characteristics of typical mountain wetlands. The objectives of this study were (1) to compare the changes in the Altay Mountains in northwest China and the Greater and Lesser Khingan Mountains in northeast China from 1980 to 2018 and (2) to explore the driving forces behind these changes. The findings of this study provide a theoretical basis for developing countries to effectively protect wetlands.

2. Materials and Methods

2.1. Study Area

The mid- to high-latitude regions (between 40° N and 50° N) experience long, cold winters with average monthly temperatures below 0 °C and short, warm summers with average monthly temperatures of 10 °C or higher. The annual precipitation ranges from 300 to 600 mm, with high relative humidity and significant annual temperature fluctuations. In this study, typical mountain peatlands in the middle- and high-latitude regions of China were selected as research objects. The study areas within the same latitude band (between 46° N and 50° N) (Figure 1) were selected for sampling because of their minimal human disturbance, more complete vegetation cover, and relatively closed hydrological conditions.
The Altay Mountains cover a vast area, with magnificent mountains spanning approximately 1650 km from east to west. This region includes the southern slope of the middle part of the Altay Mountains, situated in the northern Xinjiang Uygur Autonomous Region. The geographic coordinates range from 85°31′37″–91°01′15″ E to 46°30′35″–49°10′45″ N. The Greater Khingan Mountains are in the north of Heilongjiang Province in northeast China, neighboring the Lesser Khingan Mountains in the east, part of the western part of the Inner Mongolia Autonomous Region, Songnen Plain in the south, and Chita and Amur oblasts of Russia in the north. The geographical coordinates are 119°06′–127°01′ E and 46°39′–53°33′ N. The terrain is higher in the south and lower in the north, with a total length of approximately 1200 km, a width of 200–300 km, and an average elevation of 300–400 m. The Lesser Khingan region is northeast of Heilongjiang Province, China, between 46°28′–51°01′ N and 124°44′–130°46′ E. The main landforms consist of eroded mountains, hills, and valleys. There are also broad valleys, disk-shaped depressions, hot-melt lakes, and other ice-marginal landforms.

2.2. Data Sources and Processing

Wetland data were extracted from land cover data provided by the Data Center for Resources and Environmental Sciences of the Chinese Academy of Sciences (http://www.resdc.cn, accessed on 19 August 2019). By referring to the national standard for land use classification in China and considering the actual local situation, the wetland types involved in this study included natural wetlands (water bodies, permanent ice/snow, beaches, marshes, lakes, and rivers) and human-made wetlands (reservoirs and channels). The monthly SPEI dataset (SPEI base v2.5) with a spatial resolution of 0.5 was calculated by comparing precipitation and potential evapotranspiration. The timescale of the SPEI runs from 1 month to 48 months, reflecting the cumulative water status (deficit or surplus) over the preceding 1–48 months. Thus, it is suitable for characterizing various types of drought events [1,21]. The calculation of SEPI is publicized in Text S1.

2.3. Methods

Matrices for the transition probabilities of land use/cover types in different periods were established. Each matrix represents either the probability of persistence of each land use/cover category from the start date to the end date of the monitoring period or the probabilities of transition from one land use/cover category to another during the same period [31]. The matrix values were standardized to calculate the annual average change rates. The transition matrices were calculated using the transfer matrix calculation formulas given by [32]. The dynamic index is an important indicator commonly used to measure wetland variation. It quantitatively compares the differences in temporal and spatial variations between regions [33]. Spatial analysis of the SPEI was interpolated using the Kriging method in the ArcGIS software (version 10.2). The dynamic concept of wetlands was introduced to further explore the variability of wetland areas within a specific period in the study area. For information on the dynamic degree methods, refer to [25,34]. Spearman’s rank-order correlation coefficient [35] was used to examine the relationship between wetlands and the SPEI values throughout the study period. Meteorological factors were analyzed in relation to climate change. The six scales of SPEI1, SPEI3, SPEI6, SPEI9, SPEI12, and SPEI24 were first processed for the mean values of 5 and 10 years. In this study, the annual scale (SPEI-12) was used as the climate index.

3. Results

3.1. Wetland Area

The mountain area in the Altay Mountains with an elevation > 1000 m was selected for the spatial interpolation of 5-phase remote sensing image area data, and the spatial change characteristics of terrestrial ecosystems are shown in Figure S1 and Table 1. Data analysis revealed a decreasing trend in wetlands in the Altay Mountains from 1980 to 2018, reaching the highest value in 1990 (399 km2) and the lowest value in 2018 (329.7 km2). The channel area was the smallest (8.66 km2), whereas the marsh area was 13 km2 (Figure 2). Combined with the trend in change, the area decreased with increasing years. The marsh wetland area exhibited an increasing trend from 1980 to 1990; however, after 1990, it showed a decreasing trend. The areas of the channels and reservoirs showed an increasing trend.
Changes in each type of terrestrial and wetland ecosystem in the Greater Khingan mountainous area (elevation > 600 m) from 1980 to 2018 were obtained (Figure 3a and Figure S2 and Table 2). The wetlands exhibited a general increasing trend, with a mean value of 14,228 km2 from 1980 to 2018. Figure 3 and Figure S3 show that the wetland ecosystem has the largest area of marshes (mean value: 11145.8 km2), followed by lakes (mean value: 2622.1 km2), channels (mean value: 226.2 km2), and beaches (mean value: 204.3 km2), with reservoirs having the smallest area (mean value: 29.8 km2). The marsh area showed a decreasing trend before 1990 and an increasing trend after 1990. Channels and beaches both exhibited an increasing trend, whereas the areas of lakes and reservoirs demonstrated a decreasing trend.
Figure 3b and Figure S2 and Table 3 illustrate that wetland in the Lesser Khingan mountainous areas (elevation > 500 m) became more prominent after 2010, with both showing an increasing trend (mean value: 5642 km2). The areas of wetland ecosystems showed the following order: marshes > reservoirs > lakes > beaches > channels. All types showed an increasing trend except for the lake, which showed a decreasing trend. Lakes showed a decreasing trend, reaching their highest value in 2010 (89.8 km2) and the lowest value in 2018 (20.4 km2). The marsh area exhibited an increasing trend, reaching its lowest value (4867 km2) in 2010 and its highest value (7401 km2) in 2018. Reservoirs, channels, and beaches exhibited increasing trends, reaching their highest values in 2018 at 232 km2, 56.9 km2, and 38.4 km2, respectively.

3.2. Transfer Matrix

3.2.1. Transfer Matrix of Altay Mountains

The transitions of ecosystem types in the Altay Mountains during the periods 1980–1990, 1990–2000, 2000–2010, and 2010–2018 were relatively consistent. Croplands were primarily converted into forestlands, grasslands, and other types of land (Figure 4). The main types of wetland transfer were other lands and grasslands, with small changes in wetland transfer areas, followed by the smallest transfer area to settlements.
From 1980 to 1990, the largest land transfer type was grasslands > forestlands > other lands > croplands > wetlands > settlements. From 1990 to 2000, the largest transfer type area was forestlands (3849.8 km2) > grasslands (3415.3 km2) > other lands (1237.1 km2) > croplands (134.7 km2) > wetlands (132 km2) > settlements (7.4 km2). From 2010 to 2018, the largest transfer type area was grasslands (5539.9 km2) > forestlands (3826.5 km2) > other lands (3318.9 km2) > wetlands (293.4 km2) > croplands (156.4 km2) > settlements (11.8 km2). Overall, the areas of the transfer types increased from 2010 to 2018. Among them, the area of wetlands transferred to other ecosystem types (293.4 km2) was larger than the area of all types of ecosystems transferred to wetlands (226.7 km2).

3.2.2. Transfer Matrix of the Greater Khingan Mountains

Changes in the transfer of ecosystem types in the mountainous areas of the Greater Khingan Mountains during the periods 1980–1990, 1990–2000, 2000–2010, and 2010–2018 were relatively consistent (Figure 5), with croplands mainly transitioning to the grassland, forestland, and wetland types. Wetlands mainly transform grassland, forestlands, and other land types. In the period from 1980 to 1990, the largest area of land transferred was grasslands (17,164.68 km2) > forestlands (14,769.22 km2) > wetlands (3100.4 km2) > croplands (2525.52 km2) > other lands (857.67 km2) > settlements (205.56 km2). Notably, the area of land transferred exceeded the area transferred out of wetlands. From 1990 to 2000, the largest area of land transferred was grassland (18,034.36 km2) > forestland (14,328.17 km2) > cropland (3767.91 km2) > wetland (3238.87 km2) > other lands (968.26 km2) > towns (279.15 km2). The area of land transferred into wetlands was smaller than the area transferred out of wetlands. From 2010 to 2018, the largest areas of transferred land were grassland (31,801.89 km2) > forestland (20,468.71 km2) > wetland (3102.47 km2) > cropland (2458.82 km2) > other lands (851.41 km2) > settlements (234.39 km2). The area of transferred wetlands was higher than the transferred area. Over time, the area of wetlands transferred to other ecosystem types (3102.47 km2) was smaller than the area of all types of ecosystems transferred to wetlands (25,058.78 km2) from 2010 to 2018.

3.2.3. Transfer Matrix of the Lesser Khingan Mountains

Data analysis showed that the transfer changes in each ecosystem type in the mountainous region of Little Greater Khingan were relatively consistent (Figure 6), with forestlands and grasslands being the main transfer types. From 1980 to 1990, the largest area of transferred land was forestlands (6175.18 km2) > grasslands (3748.3 km2) > wetlands (2703.19 km2) > croplands (2322.08 km2) > settlements (259.89 km2) > other lands (77.48 km2). The area of land transferred to wetlands was smaller than that transferred out. From 1990 to 2000, the largest area of transferred types was forestlands (9374.81 km2) > grasslands (3667.92 km2) > wetlands (2696.29 km2) > croplands (1970.44 km2) > settlements (279.15 km2) > other lands (94.52 km2). The area transferred to wetlands was smaller than the area transferred out. From 2010 to 2018, the largest area of transferred types was forestlands (8665.73 km2) > grasslands (5934.9 km2) > wetlands (3673.38 km2) > croplands (3563.92 km2) > settlements (291.37 km2) > other lands (124.13 km2). The area transferred to wetlands was higher than the area transferred out. From 2010 to 2018, the area of wetlands transferred to other ecosystem types (3673.38 km2) was smaller than the area of all types of ecosystems transferred to wetlands (6273.31 km2).

3.3. Dynamic Changes

As shown in Figure 7a, the changes in dynamics, depletion, and conversion degree in terrestrial and wetland ecosystems in the Altay Mountains were relatively small. In terrestrial ecosystems, settlements had the highest dynamic and conversion degrees, followed by cropland ecosystems, whereas wetland ecosystems exhibited the highest degree of depletion. In wetland ecosystems, the highest mobility and transmigration were observed in channels, followed by lakes. Marsh ecosystems exhibited the highest depletion and the lowest mobility, whereas the rest of the types showed less pronounced characteristics.
In the mountainous areas of the Greater Khingan Mountains (Figure 7b), there were significant variations in the dynamics of mobility and depletion of wetlands, settlements, and other lands. The observed pattern was wetlands > settlements > other lands. The degree of conversion was the opposite, showing that other lands > settlements > wetland ecosystems. The next most significant change was in cropland, with conversion degree > depletion degree > dynamic degree. The most significant change in wetland ecosystems was in marshes, which had the highest degree of conversion, followed by dynamic changes and the lowest degree of depletion. Channels and beaches ranked second only to marshes in terms of change, exhibiting a higher turnover rate than activity and a greater degree of depletion. Lakes were less variable, with reservoirs showing higher depletion than turnover.
The changing characteristics of wetlands and settlements in the Lesser Khingan mountainous area were relatively similar (Figure 7c). Both exhibited a pattern of conversion > depletion > dynamic degree, with settlements having a higher value than wetlands. Croplands mainly showed a high degree of conversion, followed by a dynamic degree, and a lower degree of depletion. Grasslands have a higher degree of depletion than other land types. The wetland ecosystems showed the highest changes in reservoirs, followed by channels. Reservoirs were more similar to channels in terms of conversion than dynamics, and the degree of depletion was the lowest. The beaches were characterized by their degree of conversion, depletion, and dynamics. Lakes showed less change, mainly because of higher depletion, and their dynamics were the lowest in the ecosystem.

4. Discussion

4.1. Spatiotemporal Variation of Natural Wetlands

Significant variations were observed between 1980 and 2018 within different types of wetland ecosystems in the Altay Mountains (Table 4a). The primary types of transformations from drylands were channels and reservoirs, whereas lakes were mainly converted into channels and marshes were predominantly converted into reservoirs. In addition, the marshes were converted into reservoirs. Changes in natural wetlands and human-made wetlands in the Altay Mountains are as follows: drylands were mainly transferred into human-made wetlands, with a total transferred area of 3.37 km2, whereas the area of human-made wetlands transferred into drylands was only 1.13 km2. The drylands area transferred to natural wetlands was 0.96 km2, whereas the area of natural wetlands transferred to drylands was 0.13 km2. Overall, the area of croplands transferred to wetlands in the Altay Mountains was larger than that transferred to drylands.
The changes in the area of natural wetlands and human-made wetlands in the Greater Khingan area are as follows (Table 4b): 8.99 km2 were transferred into human-made wetlands, 306.81 km2 were transferred into natural wetlands, and 0.16 km2 of drylands were transferred to paddy fields. Specifically, 2.25 km2 of human-made wetlands were transferred to dryland, and 121.67 km2 were transferred into natural wetlands. Human-made wetlands were restored as the area of natural wetlands showed an increasing trend. The main types of drylands transferred to the mountainous areas of the Greater Khingan Mountains included marshes, paddy fields, channels, reservoirs, and beaches, with the largest area being transferred to marshes. This indicates that the increase in marshes may also be due to the decrease in drylands, which were transferred to marshes, and the smaller area of paddy fields transferred to marshes, which was only 0.16 km2. The largest area transferred out of marshes was the dryland, indicating an increase in human activities reclaiming marshes for drylands. This increased the area of drylands and decreased the area of marshes. The largest area transferred out of the marshes was also dryland, totaling 242.6 km2, whereas the area transferred into the marshes was 300.18 km2. The area transferred out was larger than the area transferred in. It was further noted that human activities, particularly those related to reclaiming marshes for drylands, have a significant impact on the natural wetland areas of marshes.
In the Lesser Khingan Mountains, the area of drylands transferred to marshes was the largest, followed by reservoirs (Table 4c). Drylands were also transferred to channels, lakes, and beaches, leading to the expansion of marsh areas. The channel was mainly transferred to the marshes and drylands. The marsh areas were larger than the drylands, and reservoirs were transferred to different types of drylands and marshes. The area of the dryland transferred to paddy fields was 1.04 km2. The dryland area transferred to the natural wetlands was 586.93 km2, whereas the area transferred to the human-made wetlands was 36.81 km2.

4.2. Main Driving Force of Natural Wetland

According to our team’s inspection of the Altay Mountains in Xinjiang, northwest China, and the peatlands of the Greater and Lesser Khingan Mountains in northeast China during 2019–2020 (Figure 8), the peatlands in the Altay Mountains were thicker and had higher TOC values [36]. There were more modern vegetation roots in peat swamp sediments, and human activities interfered with larger areas, particularly pastoral grazing. Cattle and sheep-nibbling activities were frequent, leading to varying degrees of peat swamp degradation. The accumulated peatlands in the mountainous areas of northeast China’s Greater and Lesser Khingan Mountains were thin, and the degree of peat development varied significantly. Moreover, they are frequently disturbed by human activities, and some peatlands have been developed into paddy fields [37].
The Altay Mountains are warm and humid, and the water supply is more abundant, which causes the swamp area to fluctuate and change. In addition, more swamps are being converted into farmland, reservoirs, and ponds owing to human activities, which is another factor contributing to the dynamic changes in the wetland area. In recent years, analysis of the Greater and Lesser Khingan Mountains has indicated that climate warming and humidification are evident. These factors are the main reasons for the expansion of wetland areas, social and economic development, and population growth. Moreover, new reservoirs and ponds have been constructed in northeast China, with many being converted into paddy fields. This conversion might explain the increase in human-made wetlands between 2000 and 2010. Meanwhile, some research analyses have shown that since 2005, the shrinkage of marsh wetland areas has slowed. However, wetlands are still facing the threat of degradation, which is primarily attributed to the degradation of marsh wetlands due to the agrarianizing of marsh wetlands caused by population growth, acceleration of urbanization and policy support, and degradation of wetlands due to water scarcity resulting from water conservation projects and groundwater exploitation.
Additionally, natural factors, including meteorological and topographic factors, have a driving effect on the wetlands. Subsequently, a correlation analysis was performed between the mean values for different mountain Marsh areas. The strongest correlation was observed between the SPEI and the mean value of the wetland area over five years. Spearman’s correlation analysis (Table 5) showed that the wetland areas of the Altay Mountains and the Greater and Lesser Khingan Mountains were positively correlated with the SPEI. Moreover, using linear trend analysis (Figure 9), the SPEI values of the Altay Mountain and the Greater and Lesser Khingan Mountains exhibited an increasing trend over the past 100 years. This trend was divided into three time periods, all of which demonstrated a decreasing trend from 1901 to 1926. Combined with climate change research in the Xinjiang (XJ) area in recent years, the XJ area is becoming warmer and wetter [36]. This is consistent with the results of this study. The Greater and Lesser Khingan Mountains showed an increasing trend between 1927 and 1976, whereas the Altay Mountains showed a decreasing trend between 1977 and 2016. The Greater Khingan and Altay Mountains showed an increasing trend, whereas the Lesser Khingan Mountains showed a decreasing trend. Warming and humidifying trends were more evident in the Greater Khingan and Altay Mountains. When the SPEI value is positive, it indicates that the climate is becoming wetter, and we find that the corresponding wetland area also shows an increasing trend during the same period.
As shown in Figure 10a, the wetland areas in Altay Mountain exhibited a change in characteristics over 2000 years. The annual SPEI value showed an increasing trend before 2000 and a decreasing trend after 2000, indicating significant humification in the region. Combined with the changes in wetland areas, natural wetlands exhibited a decreasing trend before 2000 and an increasing trend after 2000. Moreover, the increase in human-made wetlands was greater than that in natural wetlands.
Combined with a literature analysis of the Altay region in recent years, the climate has experienced warming and humidification. The climate was cold before the 1980s and then transformed into a warmer and more humid period [38]. The climate of Xinjiang has changed to a warm and humid period since 2000. This change has led to a large amount of permanent snow and glacier melting and an increase in the area of the river, coupled with an increase in precipitation and an increase in river replenishment, which has led to an increase in wetland area [39]. With the development of the social economy and the increase in population, the government has intensified its efforts to protect wetland resources, establish wetland nature reserves, and strengthen the management of water resources. To meet the demands of the population, Xinjiang has constructed new reservoirs and water conveyance canal systems in recent years. However, many man-made wetlands have been reclaimed as arable land. The increasing trend in the SPEI value indicated a wetter climate, confirming the significant influence of the SPEI on wetland areas. This further confirms that the SPEI has a significant influence on the dynamic changes in wetland areas. Therefore, it is important to explore the effects of drought on wetland areas using SPEI values. The Altay Mountains contain numerous rivers, lakes, and abundant water resources. In addition, the presence of many poorly drained mountain depressions in the region has facilitated the extensive growth of mountain marsh and aquatic plants. These conditions have created favorable geological conditions for the development of various types of wetlands in the Altay Mountains. Combined with the remote sensing image data, we observed a decreasing trend in the marsh area of the Altay Mountains from 1980 to 2018. Notably, there was an increasing trend from 1980 to 2015, with the highest value of 510.27 km2 recorded in 2015. A decreasing trend was observed after 2015, consistent with the findings of [40]. Combined with spatial distribution characterization, we found that the marshes were mainly distributed in the northwest and southeast of the Altay Mountains. Among these, the wetlands in Qinghe County in the Altay region have the widest distribution area. In addition, according to the Records of Mires in China [41] and the Altay Mountain Wetland Survey [42], the findings of the survey conducted by our team in the Altay Mountain region of Xinjiang in August 2014 showed that the peatlands in the Altay Mountain region of Xinjiang are mainly located in poorly drained depressions of the mountains, ranging from 1700 to 2500 m. Water recharge depends primarily on the ground surface, and water supply mainly occurs through the ground surface. Water supply mainly depends on surface runoff, alpine snow, and ice meltwater.
As shown in Figure 10b,c, the trend in annual SPEI values in the Greater and Lesser Khingan Mountains was relatively consistent, with a decreasing trend from 1990 to 2010 and an increasing trend after 2010, indicating a shift in the climate of the region from dry to wet. Yu and Ma studied climate change in northeast China and the change in annual mean temperature over the past 45 years (1961–2005), and their results showed that the annual mean temperature continuously showed an increasing trend, and the warming amplitude showed a positive correlation with latitude [43]. Jianying and Jianping showed that the average linear warming rate in the northeast region over the last 46 years (1961–2006) was 0.36/10 years [44]. The changes in precipitation were relatively small. However, the overall trend has decreased [45]. Combined with the change in wetland areas, both natural wetland and human-made wetland areas exhibited an increasing trend before 2000, followed by a decreasing trend and an increasing trend after 2000. The fluctuating increase in human-made wetlands was larger than that in natural wetlands, reaching its highest value in 2018. Combined with the literature analysis of the Greater Khingan Mountains area in recent years, it is evident that climate warming and humidification have been the main reasons for the increase in wetland areas [46,47].
According to Text S2 and Figures S3 and S4, with the development of the social economy and increase in population, new reservoirs have been added in recent years in northeast China. Additionally, most marshes have been reclaimed as paddy fields, which is likely the reason for the increase in human-made wetlands from 2000 to 2010. Combined with a literature analysis, it was found that 85.4% of agriculturally cultivated reclaimed marsh wetlands in China from 1990 to 2010 were distributed in the three northeastern provinces. The agriculturally cultivated reclaimed marsh wetlands were mainly reclaimed as drylands (75%), and approximately 3943 km2 of marsh wetlands in China were reclaimed as paddy fields from 1990 to 2010, with the majority located in the three northeastern provinces (90.8%) [48]. The analysis results of this study are consistent with the findings of a previous study [49], showing a continuous decrease in the overall wetland area in China. The number of natural wetlands has continued to decrease, whereas the number of man-made wetlands has shown an increasing trend. The decline in the total wetland area has slowed, and the area of man-made wetlands has significantly increased over the last 15 years. Some studies have shown that marsh wetland area shrinkage has slowed since 2005. However, wetlands still face the threat of degradation. This degradation of marsh wetlands has been caused by population growth, accelerated urbanization, and policy support. Other factors contributing to wetland degradation include water scarcity due to water conservation projects and groundwater exploitation, deforestation, industrial waste, pesticides, and fertilizers from oil extraction, as well as pollution of wetland water bodies and soil [50].
The mid- to high-latitude (between 40° N and 50° N) regions of northern China have long, cold winters with average monthly temperatures below 0 °C; summers are short and warm, with average monthly temperatures above 10 °C. Annual precipitation ranges from 300 to 600 mm, relative humidity is high, and the annual difference in temperature is large. Alpine mountain wetlands are very sensitive to climatic and environmental changes. For typical mountain wetlands in the middle and high latitudes of China, which are affected by climate in the northwest and northeast of the country and are affected by human activities in a single way, we used a comparative analysis method, combined with the proxy indicator of extreme climatic events (SEPI), to study the change in the area of the Altay Mountains affected by the westerly wind belt and the area of the Greater Khingan and Greater Khingan Mountains wetlands affected by the monsoon climate, and combined with the climate factor characteristics, we studied the change in the area of the mountain wetlands. We analyze the impact of anthropogenic activities on the area of wetland ecosystems by combining the field survey data and the indicators of population, GDP, and LUCC reflecting the intensity of anthropogenic activities, which enriches the study of wetland dynamics and makes up for the blank of the study of wetland dynamics in alpine mountainous areas, which has important scientific significance for the further understanding of regional responses to global climate instability in modern times. This is of great scientific significance for further understanding the regional response to the recent global climate instability and provides a reference for the sustainable development of wetland ecosystems. The accuracy of the remote sensing data in this study needs to be further improved. In the future, we will combine the indicators that can reflect the intensity of human activities, such as microplastics and other new pollutants, to reflect the impact of human activities on the wetland area in the alpine mountainous region in the past historical period. At the same time, we will analyze the climatic causes of wetland area changes in the alpine mountains by combining particle size, magnetization rate, and other climate indicators.

5. Conclusions

Dynamic changes in the characteristics of different mountain wetland areas were comprehensively explored using five periods of remote sensing image data, regional research information, and the results of peatlands resource surveys conducted in 2019 and 2020. Using the SPEI to analyze the driving factors, the study revealed that the area of the Altay Mountains in northwest China exhibited an increasing trend from 1980 to 1990 and a decreasing trend after 1990. In contrast, the area of the Greater Khingan Mountains in northeast China showed an opposite pattern, with a decreasing trend before 1990 and an increasing trend after 1990. The area of the Lesser Khingan Mountains showed a consistent increasing trend throughout the study period. Combined with the transferred area, wetlands in the Altay Mountain area were mainly transferred to other lands and grasslands. The main types of wetlands transferred into the Greater and Lesser Khingan areas were grasslands and forestlands. From 2010 to 2018, the area transferred to the wetlands ecosystem in the Altay Mountain region was larger than the area transferred out of wetland types, whereas the are transferred to of wetlands in the Greater and Lesser Khingan Mountain regions was smaller than the area transferred out. The most significant change in the internal wetland ecosystem type in the Altay Mountains was the channel, whereas the most significant change in the Greater and Lesser Khingan Mountains was the presence of swamps. The reservoirs were highest in the Lesser Khingan Mountains. The driver analysis revealed that the SPEI values in the study area have increased, indicating that climate change over the last hundred years has led to warming and increased humidity. The SPEI and wetland area were positively correlated, and the SPEI had a positive effect on the wetland area. The swamp area exhibited an increasing trend under the influence of climate change. An analysis of the driving factors of the mountain swamp area showed that climate warming and humidification were the primary factors for the change in the swamp area. The wetland areas in the mountainous regions of the Greater and Lesser Khingan Mountains in northeast China were strongly influenced by human activities, whereas the wetland area in the Altay Mountains in northwest China was predominantly influenced by climate.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/land13081124/s1, Text S1: SREI calculation; Text S2: Changes in GDP and POP from 1995 to 2019; Figure S1: Spatial variation characteristics of terrestrial ecosystems in the Altay Mountains (altitude > 1000 m) from 1980~2018; Figure S2: Spatial variation characteristics of terrestrial ecosystems from 1980 to 2018 in the Greater and Lesser Khingan Mountains; Figure S3: Spatial distribution of GDP; Figure S4:Spatial distribution of POP.

Author Contributions

Conceptualization, N.L. and B.W.; methodology and software, R.Y.; investigation, N.L. and R.Y. writing—original draft preparation, N.L.; supervision, B.W.; funding acquisition, N.L. and B.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Basic Research Program of China (No. 2013FY111800), R & D Innovative Teams of Major Scientific and Technological Projects of Jilin Province, the Science and Technology Development Program of Jilin Province (Special for XinJiang), the National Natural Science Foundation of China (42301134, Nana Luo), and the Survey of Basic Scientific and Technological Resources (2019FY100605-2).

Data Availability Statement

The authors have not obtained permission to publish the data. Therefore, the data can be obtained from the corresponding author upon reasonable request.

Acknowledgments

The authors gratefully acknowledge the Resources and Environmental Science Data Center, Chinese Academy of Sciences, for providing land cover data.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Ramachandra, T.V.; Rajinikanth, R.; Ranjini, V.G. Economic valuation of wetlands. J. Environ. Biol. 2005, 26, 439–447. [Google Scholar] [PubMed]
  2. Wu, X.; Zhao, H.; Wang, M.; Yuan, Q.; Chen, Z.; Jiang, S.; Deng, W. Evolution of Wetland Patterns and Key Driving Forces in China’s Drylands. Remote Sens. 2024, 16, 702. [Google Scholar] [CrossRef]
  3. Ge, Y.; Sklenička, P.; Chen, Z. Socioeconomic and Climate Effects on Changes in Wetlands in China during a Three-Decade Period of Rapid Growth. Remote Sens. 2023, 15, 1683. [Google Scholar] [CrossRef]
  4. Xiao, D.; Deng, L.; Kim, D.; Huang, C.; Tian, K. Carbon budgets of wetland ecosystems in China. Glob. Change Biol. 2019, 25, 2061–2076. [Google Scholar] [CrossRef] [PubMed]
  5. Li, S.; Ma, H.; Yang, D.; Hu, W.; Li, H. The Main Drivers of Wetland Evolution in the Beijing-Tianjin-Hebei Plain. Land 2023, 12, 480. [Google Scholar] [CrossRef]
  6. Wei, C.; Guo, B.; Lu, M.; Zang, W.; Yang, F.; Liu, C.; Wang, B.; Huang, X.; Liu, Y.; Yu, Y.; et al. The Changes in Dominant Driving Factors in the Evolution Process of Wetland in the Yellow River Delta during 2015–2022. Remote Sens. 2023, 15, 2858. [Google Scholar] [CrossRef]
  7. Zhu, C.; Zhang, X.; Huang, Q. Four Decades of Estuarine Wetland Changes in the Yellow River Delta Based on Landsat Observations Between 1973 and 2013. Water 2018, 10, 933. [Google Scholar] [CrossRef]
  8. Ding, J.S.; Lin, J.X.; Gu, N.K. Studies on Reservoir Wetlands and Its Hydroecology Protection on Qinghai Plateau. J. Hydroecol. 2010, 2, 9–16. [Google Scholar]
  9. Song, C.; He, H.S.; Liu, K.; Du, H.; Krohn, J. Impact of historical pattern of human activities and natural environment on wetland in Heilongjiang River Basin. Front. Environ. Sci. Eng. 2023, 17, 151. [Google Scholar] [CrossRef]
  10. Yan, J.; Zhu, J.; Zhao, S.; Su, F. Coastal wetland degradation and ecosystem service value change in the Yellow River Delta, China. Glob. Ecol. Conserv. 2023, 44, e02501. [Google Scholar] [CrossRef]
  11. Kirwan, M.L.; Megonigal, J.P. Tidal wetland stability in the face of human impacts and sea-level rise. Nature 2013, 504, 53–60. [Google Scholar] [CrossRef]
  12. Bian, H.; Li, W.; Li, Y.; Ren, B.; Zeng, Z. Driving forces of changes in China’s wetland area from the first (1999–2001) to second (2009–2011) National Inventory of Wetland Resources. Glob. Ecol. Conserv. 2019, 21, e00867. [Google Scholar] [CrossRef]
  13. Meng, W.; He, M.; Hu, B.; Mo, X.; Li, H.; Liu, B.; Wang, Z. Status of wetlands in China: A review of extent, degradation, issues and recommendations for improvement. Ocean Coast. Manag. 2017, 146, 50–59. [Google Scholar] [CrossRef]
  14. Liu, J.; Tian, H.; Liu, M.; Zhuang, D.; Melillo, J.M.; Zhang, Z. China’s changing landscape during the 1990s: Large-scale land transformations estimated with satellite data. Geophys. Res. Lett. 2005, 32, L02405. [Google Scholar] [CrossRef]
  15. Li, M.; Sun, H.; Su, Z. Research progress in dry/wet climate variation in Northwest China. Geogr. Res. 2021, 40, 1180–1194. [Google Scholar]
  16. Zhao, R.; Sun, H.; Xing, L.; Li, R.; Li, M. Effects of anthropogenic climate change on the drought characteristics in China: From frequency, duration, intensity, and affected area. J. Hydrol. 2023, 617, 129008. [Google Scholar] [CrossRef]
  17. AghaKouchak, A.; Chiang, F.; Huning, L.S.; Love, C.A.; Mallakpour, I.; Mazdiyasni, O.; Moftakhari, H.; Papalexiou, S.M.; Ragno, E.; Sadegh, M. Climate Extremes and Compound Hazards in a Warming World. Annu. Rev. Earth Planet. Sci. 2020, 48, 519–548. [Google Scholar] [CrossRef]
  18. You, Q.; Kang, S.; Li, J.; Chen, D.; Zhai, P.; Ji, Z. Several research frontiers of climate change over the Tibetan Plateau. J. Glaciol. Geocryol. 2021, 43, 885–901. [Google Scholar]
  19. Ribeiro, K.; Pacheco, F.S.; Ferreira, J.W.; De Sousa-Neto, E.R.; Hastie, A.; Krieger Filho, G.C.; Alvalá, P.C.; Forti, M.C.; Ometto, J.P. Tropical peatlands and their contribution to the global carbon cycle and climate change. Glob. Chang. Biol. 2021, 27, 489–505. [Google Scholar] [CrossRef]
  20. Lee, J.; Park, S.; Kim, J.; Sur, C.; Chen, J. Extreme drought hotspot analysis for adaptation to a changing climate: Assessment of applicability to the five major river basins of the Korean Peninsula. Int. J. Clim. 2018, 38, 4025–4032. [Google Scholar] [CrossRef]
  21. Vicente-Serrano, S.M.; Beguería, S.; López-Moreno, J.I. A Multiscalar Drought Index Sensitive to Global Warming: The Standardized Precipitation Evapotranspiration Index. J. Clim. 2010, 23, 1696–1718. [Google Scholar] [CrossRef]
  22. Yang, Y.; Dai, E.; Yin, J.; Jia, L.; Zhang, P.; Sun, J. Spatial and Temporal Evolution Patterns of Droughts in China over the Past 61 Years Based on the Standardized Precipitation Evapotranspiration Index. Water 2024, 16, 1012. [Google Scholar] [CrossRef]
  23. Zhou, K.; Wu, S.; Li, J. Spatial and temporal variability of wetland resources in Xinjiang. Geogr. Arid. Zones 2004, 27, 4. [Google Scholar]
  24. Luo, N.; Yu, R.; Mao, D.; Wen, B.; Liu, X. Spatiotemporal variations of wetlands in the northern Xinjiang with relationship to climate change. Wetl. Ecol. Manag. 2021, 29, 617–631. [Google Scholar] [CrossRef]
  25. Gong, Z.; Li, H.; Zhao, W.; Gong, H. Driving forces analysis of reservoir wetland evolution in Beijing during 1984–2010. J. Geogr. Sci. 2013, 23, 753–768. [Google Scholar] [CrossRef]
  26. Jing, Y.; Zhang, F.; He, Y.; Kung, H.-T.; Johnson, V.C.; Arikena, M. Assessment of spatial and temporal variation of ecological environment quality in Ebinur Lake Wetland National Nature Reserve, Xinjiang, China. Ecol. Indic. 2020, 110, 105874. [Google Scholar] [CrossRef]
  27. Mao, D.; Luo, L.; Wang, Z.; Wilson, M.C.; Zeng, Y.; Wu, B.; Wu, J. Conversions between natural wetlands and farmland in China: A multiscale geospatial analysis. Sci. Total Environ. 2018, 634, 550–560. [Google Scholar] [CrossRef] [PubMed]
  28. Pratte, S.; Bao, K.; Shen, J.; Mackenzie, L.; Klamt, A.-M.; Wang, G.; Xing, W. Recent atmospheric metal deposition in peatlands of northeast China: A review. Sci. Total Environ. 2018, 626, 1284–1294. [Google Scholar] [CrossRef]
  29. Bao, K.; Liu, T.; Chen, M.; Lin, Z.; Zhong, J.; Neupane, B. Peat records of atmospheric environmental changes in China: A brief review and recommendations for future research perspectives. Catena 2023, 229, 107234. [Google Scholar] [CrossRef]
  30. Chang, X.L.; Yu, S.P.; Jin, H.J.; Zhang, Y.L. Vegetation impact on the thermal regimes of the active layer and near-surface permafrost in the Greater Hinggan Mountains, Northeastern China. Sci. Cold Arid. Reg. 2014, 6, 511–520. [Google Scholar]
  31. Jin, X.; Qiang, H.; Zhao, L.; Jiang, S.; Cui, N.; Cao, Y.; Feng, Y. SPEI-based analysis of spatio-temporal variation characteristics for annual and seasonal drought in the Zoige Wetland, Southwest China from 1961 to 2016. Theor. Appl. Clim. 2020, 139, 711–725. [Google Scholar] [CrossRef]
  32. Zhang, H.; Chen, W.; Liu, Z. Spatiotemporal Evolution of Entrepreneurial Activities and Its Driving Factors in the Yangtze River Delta, China. Land 2022, 11, 216. [Google Scholar] [CrossRef]
  33. Shcheglova, A.A. Impulse Transfer Matrix of a Time-Varying System of Differential-Algebraic Equations. J. Comput. Syst. Sci. Int. 2023, 62, 1–16. [Google Scholar] [CrossRef]
  34. Anputhas, M.; Janmaat, J.J.A.; Nichol, C.F.; Wei, X.A. Modelling spatial association in pattern based land use simulation models. J. Environ. Manag. 2016, 181, 465–476. [Google Scholar] [CrossRef]
  35. Luo, N.; Wen, B.; Bao, K.; Yu, R.; Sun, J.; Li, X.; Liu, X. Centennial records of Polycyclic aromatic hydrocarbons and black carbon in Altay Mountains peatlands, Xinjiang, China. Front. Ecol. Evol. 2022, 10, 1046076. [Google Scholar] [CrossRef]
  36. Bishara, A.J.; Hittner, J.B. Testing the significance of a correlation with nonnormal data: Comparison of Pearson, Spearman, transformation, and resampling approaches. Psychol. Methods 2012, 17, 399–417. [Google Scholar] [CrossRef] [PubMed]
  37. Zhang, Y.; Yang, P.; Tong, C.; Liu, X.; Zhang, Z.; Wang, G.; Meyers, P.A. Palynological record of Holocene vegetation and climate changes in a high-resolution peat profile from the Xinjiang Altai Mountains, northwestern China. Quat. Sci. Rev. Int. Multidiscip. Rev. J. 2018, 201, 111–123. [Google Scholar] [CrossRef]
  38. Wu, X.; Zhang, C.; Dong, S.; Hu, J.; Tong, X.; Zheng, X. Spatiotemporal changes of the aridity index in Xinjiang over the past 60 years. Environ. Earth Sci. 2023, 82, 392. [Google Scholar] [CrossRef]
  39. Wang, W.; Jiao, A.; Shan, Q.; Wang, Z.; Kong, Z.; Ling, H.; Deng, X. Expansion of typical lakes in Xinjiang under the combined effects of climate change and human activities. Front. Environ. Sci. 2022, 10, 1015543, Correction in Front. Environ. Sci. 2023, 11, 1187155. [Google Scholar] [CrossRef]
  40. Mamitiya, Y. Study on the Dynamic Changes of Peat Wetlands in Altay Mountains of China and Countermeasures for Their Restoration. Master’s Thesis, Xinjiang University, Xinjiang, China, 2011. [Google Scholar]
  41. Zhao, K.Y. Rcords of Mires in China; Science Press: Beijing, China, 1999. [Google Scholar]
  42. Nuerbyi, A.; Yelebolati, T.; Kong, Q.Y. Investigation and study of Wetlands in Altay area. J. Urumqi Vocat. Univ. 2008, 6, 8–13. [Google Scholar]
  43. Yu, X.; Ma, Y. Spatial and Temporal Analysis of Extreme Climate Events over Northeast China. Atmosphere. 2022, 13, 1197. [Google Scholar] [CrossRef]
  44. Jia, J.; Guo, J. Characteristics of climate change in northeast China for last 46 years. J. Arid. Land Resour. Environ. 2011, 25, 109–115. [Google Scholar]
  45. Sun, F.; Yang, X.; Lu, S.; Yang, S. The contrast analysis on the average and extremum temperature trend in northeast China. Sci. Meteorol. Sin. 2006, 26, 157–163. [Google Scholar]
  46. Jiao, R.M. A Review of the Causes of Extreme Weather and Climate Events in Northeast China since Modern Times. Soc. Sci. J. 2013, 6, 156–162. [Google Scholar]
  47. Zhao, D.D. The Change of Wetland distribution and the Simulated Response to Climatic Change in the Great Xing’an Mountains. Ph.D. Thesis, Northeast Normal University, Changchun, China, 2019. [Google Scholar]
  48. Li, Y.; Mao, D.; Wang, Z.; Wang, X.; Tan, X.; Jia, M.; Ren, C. Identifying variable changes in wetlands and their anthropogenic threats bordering the Yellow Sea for water bird conservation. Glob. Ecol. Conserv. 2021, 27, e01613. [Google Scholar] [CrossRef]
  49. Xu, W.; Fan, X.; Ma, J.; Pimm, S.L.; Kong, L.; Zeng, Y.; Li, X.; Xiao, Y.; Zheng, H.; Liu, J.; et al. Hidden Loss of Wetlands in China. Curr. Biol. 2019, 29, 3065–3071.e2. [Google Scholar] [CrossRef]
  50. Liu, Y.; Liu, X.; Liu, Z. Effects of climate change on paddy expansion and potential adaption strategies for sustainable agriculture development across Northeast China. Appl. Geogr. 2022, 141, 102667. [Google Scholar] [CrossRef]
Land 13 01124 g001
Figure 1. Spatial map of the geographic location of the study area (a) Altay Mountains, (b) Greater and Lesser Khingan Mountains.
Figure 1. Spatial map of the geographic location of the study area (a) Altay Mountains, (b) Greater and Lesser Khingan Mountains.
Land 13 01124 g001
Land 13 01124 g002
Figure 2. Characteristics of wetland ecosystem changes from 1980 to 2018 in the Altay Mountains.
Figure 2. Characteristics of wetland ecosystem changes from 1980 to 2018 in the Altay Mountains.
Land 13 01124 g002
Land 13 01124 g003
Figure 3. Characteristics of wetland ecosystem changes from 1980 to 2018 (a) Greater Khingan, Mountains (b) Lesser Khingan Mountains.
Figure 3. Characteristics of wetland ecosystem changes from 1980 to 2018 (a) Greater Khingan, Mountains (b) Lesser Khingan Mountains.
Land 13 01124 g003
Land 13 01124 g004
Figure 4. Transfer matrix of different land classes in the Altay Mountains (a) 1980–1990, (b) 1990–2000, (c) 2000–2010, (d) 2010–2018.
Figure 4. Transfer matrix of different land classes in the Altay Mountains (a) 1980–1990, (b) 1990–2000, (c) 2000–2010, (d) 2010–2018.
Land 13 01124 g004
Land 13 01124 g005
Figure 5. Transfer matrix of different land classes in the Greater Khingan Mountains (a) 1980–1990, (b) 1990–2000, (c) 2000–2010, (d) 2010–2018.
Figure 5. Transfer matrix of different land classes in the Greater Khingan Mountains (a) 1980–1990, (b) 1990–2000, (c) 2000–2010, (d) 2010–2018.
Land 13 01124 g005
Land 13 01124 g006
Figure 6. Transfer matrix of different land classes in the Lesser Khingan Mountains (a) 1980–1990, (b) 1990–2000, (c) 2000–2010, (d) 2010–2018.
Figure 6. Transfer matrix of different land classes in the Lesser Khingan Mountains (a) 1980–1990, (b) 1990–2000, (c) 2000–2010, (d) 2010–2018.
Land 13 01124 g006
Land 13 01124 g007
Figure 7. Characteristics of dynamic changes in different degrees (a) Altay Mountains, (b) Greater Khingan Mountains, (c) Lesser Khingan Mountains.
Figure 7. Characteristics of dynamic changes in different degrees (a) Altay Mountains, (b) Greater Khingan Mountains, (c) Lesser Khingan Mountains.
Land 13 01124 g007
Land 13 01124 g008
Figure 8. Wetland resource visits (a) Altay Mountain peatlands (cattle and sheep activities), (b) Greater Khingan Mountains peatlands (pastoral activities), (c) Lesser Khingan Mountains peatlands (artificial drainage ditches).
Figure 8. Wetland resource visits (a) Altay Mountain peatlands (cattle and sheep activities), (b) Greater Khingan Mountains peatlands (pastoral activities), (c) Lesser Khingan Mountains peatlands (artificial drainage ditches).
Land 13 01124 g008
Land 13 01124 g009
Figure 9. Characteristics of interannual variation trends in SPEI-12 values in different regions. (a) Altay Mountains, (b) Greater Khingan Mountains, (c) Lesser Khingan Mountains.
Figure 9. Characteristics of interannual variation trends in SPEI-12 values in different regions. (a) Altay Mountains, (b) Greater Khingan Mountains, (c) Lesser Khingan Mountains.
Land 13 01124 g009
Land 13 01124 g010
Figure 10. Characteristics of changes in area and SPEI of various types of wetlands in different regions (a) Altay region, (b) Greater Khingan area, (c) Lesser Khingan region.
Figure 10. Characteristics of changes in area and SPEI of various types of wetlands in different regions (a) Altay region, (b) Greater Khingan area, (c) Lesser Khingan region.
Land 13 01124 g010
Table 1. Areas of terrestrial ecosystem type (km2).
Table 1. Areas of terrestrial ecosystem type (km2).
Time-PeriodCroplandsForestlandsGrasslandsWetlands and Water BodiesSettlementsOther Lands
1980269.157671.7925,009.9387.096.6915,448.44
1990248.627602.7424,679.8399.738.3115,711.05
2000259.896502.4426,322.0370.6613.2115,327.42
2010290.026499.8526,304.4372.6015.2115,310.08
2018440.934922.2227,330.4329.7774.3815,498.44
Table 2. Area of terrestrial ecosystem types in the Greater Khingan Mountains (km2).
Table 2. Area of terrestrial ecosystem types in the Greater Khingan Mountains (km2).
Time PeriodCroplandsForestlandsGrasslandsWetlands and Water BodiesSettlementOther Lands
19805958.1138,974.088,780.39869.2341.21433.5
19906016.3138,445.088,653.310,041.2481.91525.9
20005971.4138,907.088,634.59875.7511.81458.0
20106101.8139,135.088,281.19692.0525.11624.5
20187452.6133,914.067,252.231,663.01001.33942.3
Table 3. Area of terrestrial ecosystem types in the Lesser Khingan Mountains (km2).
Table 3. Area of terrestrial ecosystem types in the Lesser Khingan Mountains (km2).
Time PeriodCroplandsForestlandsGrasslandsWetlands and Water BodiesSettlementOther Lands
19807398.860,176.56393.65110.5290.7175.9
19907575.360,261.16158.65054.2307.0192.9
200011,035.156,155.36709.15144.8320.5181.5
201011,090.256,178.26613.05151.9333.4181.5
201813,497.654,972.52782.57749.7443.7100.8
Table 4. Transform matrix of wetlands ecosystem from 1980 to 2018 (km2).
Table 4. Transform matrix of wetlands ecosystem from 1980 to 2018 (km2).
(a) Altay MountainDrylandLakePermanent Glacial SnowReservoirsChannel
Dryland118.370.96/2.151.22
Reservoirs1.13//10.99/
Lake/15.73//0.76
Permanent glacial snow/2.1458.04//
Beach/////
Marshes0.13//0.33/
(b) Greater Khingan MountainsPaddy FieldsDrylandLakeBeachMarshesReservoirsChannel
Dryland0.162302.57/6.63300.180.658.34
Reservoirs//2.00/13.12//
Channel/2.257.865.2793.43/18.15
Lake/1.642246.7315.16119.8//
Beach/8.780.971.25114.22/13.89
Marshes1.37242.635.24108.733815.88.3850.90
(c) Lesser Khingan MountainsPaddy FieldsDrylandLakeBeachMarshesReservoirsChannel
Dryland1.045630.546.590.22580.1334.642.18
Reservoirs/21.764.70/7.284.09/
Channel/0.48//2.78/0.24
Lake/23.113.17/3.3130.97/
Beach/1.30/1.640.12//
Marshes3.931885.850.624.001321.7352.446.20
Table 5. Correlation characteristics of peatland area and SPEI in different regions.
Table 5. Correlation characteristics of peatland area and SPEI in different regions.
Study AreaCorrelation Coefficient
Altay mountains0.85
Greater Khingan Mountains0.90 *
Lesser Khingan Mountains0.32
* Significance at the 0.05 level.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Luo, N.; Yu, R.; Wen, B. Characteristics of Changes in Typical Mountain Wetlands in the Middle and High Latitudes of China over the Past 30 Years. Land 2024, 13, 1124. https://doi.org/10.3390/land13081124

AMA Style

Luo N, Yu R, Wen B. Characteristics of Changes in Typical Mountain Wetlands in the Middle and High Latitudes of China over the Past 30 Years. Land. 2024; 13(8):1124. https://doi.org/10.3390/land13081124

Chicago/Turabian Style

Luo, Nana, Rui Yu, and Bolong Wen. 2024. "Characteristics of Changes in Typical Mountain Wetlands in the Middle and High Latitudes of China over the Past 30 Years" Land 13, no. 8: 1124. https://doi.org/10.3390/land13081124

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop