
Heterogeneity of water-retention capacity of forest and its influencing factors based on meta-analysis in the Beijing-Tianjin-Hebei region
SHI Xiaoli, DU Chenliang, GUO Xudong, SHI Wenjiao
Journal of Geographical Sciences ›› 2021, Vol. 31 ›› Issue (1) : 69-90.
Heterogeneity of water-retention capacity of forest and its influencing factors based on meta-analysis in the Beijing-Tianjin-Hebei region
Water retention is important in forest ecosystem services. The heterogeneity analysis of water-retention capacity and its influencing factors is of great significance for the construction of water-retention functional areas, restoration of vegetation, and the protection of forest ecosystems in the Beijing-Tianjin-Hebei region. A total of 1366 records concerning water-retention capacity in the canopy layer, litter layer, and soil layer of forest ecosystem in this region were obtained from 193 literature published from 1980 to 2017. The influencing factors of water-retention capacity in each layer were analyzed, and path analysis was used to investigate the contribution of the factors to the water-retention capacity of the three layers. The results showed that mixed forests had the highest water-retention capacity, followed by broad-leaved forests, coniferous forests, and shrub forests. In addition, no matter the forest type, the ranking of the water-retention capacity was soil layer, canopy layer, and litter layer from high to low. The main influencing factors of water-retention capacity in forest canopy were leaf area index and maximum daily precipitation (R 2=0.49), and the influencing coefficients were 0.34 and 0.30, respectively. The main influencing factors of water-retention capacity in the litter layer were semi-decomposed litter (R 2=0.51), and the influencing coefficient was 0.51. The main influencing factors of water-retention capacity in the soil layer were non-capillary porosity and soil depth (R 2=0.61), the influencing coefficients were 0.60 and 0.38, respectively. This study verifies the simulation of the water balance model or inversion of remote sensing of the water-retention capacity at the site scale, and provides scientific basis for further study of the impact of global change on water retention.
meta-analysis / path analysis / water retention / Beijing-Tianjin-Hebei region {{custom_keyword}} /
Table 1 Correlation between water-retention capacity and its influencing factors of the canopy layer |
Sunshine duration | Maximum daily precipitation | LAI | Latitude | Evapotranspiration | Elevation | DBH | Slope | Stand age | Canopy interception | |
---|---|---|---|---|---|---|---|---|---|---|
Sunshine duration | 1 | |||||||||
Maximum daily precipitation | -0.75** | 1 | ||||||||
LAI | 0.00 | -0.57** | 1 | |||||||
Latitude | 0.58** | -0.38** | 0.56* | 1 | ||||||
Evapotranspiration | -0.48 | 0.60** | -0.23 | -0.17 | 1 | |||||
Elevation | 0.54 | -0.42** | 0.42 | 0.58** | -0.55** | 1 | ||||
DBH | -0.26 | 0.19 | 0.36 | 0.21* | -0.38** | 0.25** | 1 | |||
Slope | -0.31 | 0.07 | 0.47* | -0.22** | -0.34** | 0.18* | -0.04 | 1 | ||
Stand age | -0.21 | 0.10 | 0.76** | -0.21* | -0.06 | -0.16 | 0.25** | 0.13 | 1 | |
Canopy in terception | -0.61** | 0.49** | 0.47* | -0.30** | 0.28** | -0.27** | 0.24* | 0.23** | 0.22* | 1 |
Note: ** indicates a significant degree of correlation of 0.01, and * indicates a significant degree of correlation of 0.05. |
Table 2 Correlation between water-retention capacity and its influencing factors of the litter layer |
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Note:**indicates a significant degree of correlation of 0.01;*indicates a significant degree of correlation of 0.05. |
Table 3 Correlation between water-retention capacity and its influencing factors of the soil layer |
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Note:**indicates a significant degree of correlation of 0.01;* indicates a significant degree of correlation of 0.05. |
Table 4 Goodness of fit index of path analysis |
Index | Meaning | Reference ranges | Values of fit index in layers | ||
---|---|---|---|---|---|
Canopy | Litter | Soil | |||
c2 | Chi-square value | The smaller the value, the better | 7.94 | 3.80 | 9.47 |
c2/df | Chi-square degree of freedom ratio | < 2 | 0.16 | 1.27 | 1.35 |
P | Probability of significance | > 0.05 | 0.16 | 0.28 | 0.22 |
RMSEA | The root-mean-square error of approximation | < 0.05, very good; 0.05-0.08, good; 0.05-0.08, moderate; 0.08-0.10, fair; > 0.10, poor | 0.05 | 0.02 | 0.03 |
CFI | Comparative fit index | > 0.90 | 0.995 | 0.999 | 0.995 |
NFI | Normal fit index | > 0.90 | 0.986 | 0.997 | 0.983 |
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We summarized the process, characteristics and influence factors of litter decomposition, including the stage division of decomposition, the mass loss and changes of components and character of decomposing litter. The decomposition of litter includes physical leaching, biochemical decomposition, and fragmentation. Physical leaching and biochemical degradation are dominant in the early and later stages of decomposition, respectively. Litter decomposition shows characteristics of continuity and stage, with mass loss of being fast at first and then being slow. The humification is strengthened with the accumulation of substances which are decomposed difficultly, resulting in the enhancement of aromaticity and adsorption and the decrease of biodegradability. Nutrient concentrations change greatly during decomposition. The content of C element is generally decreased, while P and N are either accumulated or released, which are influenced by many factors. Litter decomposition is a process influenced by multiple factors. Overall, litter property is essential to the decomposition. Temperature, water, soil animal community can have distinct impacts on the decomposition. To a certain degree, increased moisture and temperature can accelerate the decomposition by promoting leaching process and microbial activity. Soil organisms have a significant contribution to the decomposition of litter. The role of microorganisms during decomposition is dominant and the soil animals play a supplementary role. Thus, studies on litter decomposition in the future should focus on the decomposition mechanism, the interaction between the factors, and the feedback of litter decomposition on the ecological changes.
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Water conservation is a comprehensive regulation function of forest ecosystem on water resources through various hydrological processes, including canopy interception, litter containment and soil retention. Forest ecosystem in Southern and Northern Pan River watershed is one of the significant ecological barriers in the upper reaches of the Pearl River, and its water conservation function would greatly influence the local development. Especially, it is also a typical karst mountain area in China, in which water is essential to the ecosystem recovery. Based on the forest resource inventory data, the integrated storage capacity method was applied to estimate the water conservation amount of forest ecosystem and its spatiotemporal variation in regional scale was also analyzed.
The results showed that the water conservation amount of forest ecosystem in the study area could reach to approximately 6.13×108 m3, in which the soil contributed to 73.65%. The broad-leaved forest and shrub contributed largest to the amount of water conservation(reaching 52.42%), while the bamboos contributed least. Analysis on different stand age showed that the young forest contributed largest to the amount of water conservation (reaching 45.95%). Forest in the middle of the mountain contributed largest to the amount of water conservation with the proportion of 75.46%. In terms of slope position, forest in middle slope and flat ground contributed largest to the amount of water conservation, while forest in valley contributed least. In recent 35 years, with the implementation of ecological projects, water conservation amount of forest ecosystem in study area was increased with the rate of 14 478 865 m3/a. In terms of water conservation capacity per unit area, the forest ecosystem in the study area could reach to 629.85 t/hm2, which was higher in eastern part and lower in western. Water conservation capacity was varied for different forest types, in which the mixed forest was largest (reaching 851.78 t/hm2). Over-mature forest was highest in water conservation capacity (reaching 909.84 t/hm2) while young forest was lowest. Forest in the middle of the mountain was slightly lower in water conservation capacity than that of the forest in the lower of mountain which was up to 763.46 t/hm2. In terms of slope position, water conservation capacity of forest in valley was highest, and forest in ridge was lowest. With the implementation of ecological projects during the past 35 years, water conservation capacity in the study area continued to rise with the rate of 5.33 t/(hm2·a), thus, the ecological projects contributed significantly to the increase of the water conservation function of forest ecosystem in the Southern and Northern Pan River watershed. Understanding the water conservation function of different forest ecosystems and their temporal and spatial distribution patterns is applicable for sustainable forest management and ecological recovery in Karst region, and useful for reaching the aims of maximizing water conservation capacity of forest ecosystem. {{custom_citation.content}}
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Beijing, as the political, communicational, cultural, and technological center of China, has been experiencing rapid urban expansion in recent years. This fast urbanization resulted in greater demands for ecosystem services from peri-urban ecosystems. Based on emergy analysis and using impact matrix, this study took the urban ecological conservation area (ECA) of Beijing as an example to evaluate the ecosystem services flows and the level of dependence between natural and urban systems. In terms of ecosystem types, results show that forest ecosystem contributes the most to ecosystem service provision in ECA, which represents 79.7% of total ecosystem services emergy in 2012. Meanwhile, cropland and aquatic ecosystems account for 19.7% and 0.6%, respectively. From the perspective of ecosystem services types, biomass production and water retention are the two dominative service types provided by forest ecosystem, accounting for 40.4% and 35.8% of forest ecosystem services emergy respectively. Food supply is the most significant emergy component in cropland ecosystem, which represents 70% of cropland ecosystem service emergy. Water supply, flood storage and aquatic product supply are the three most important emergy components in aquatic ecosystem, which account for 35.1%, 28.6% and 28.2% of the total aquatic emergy respectively. Results of emergy impact matrix suggest that forest biomass, soil water, groundwater and cropland biomass are the four vital providers of ecosystem services to urban system. At the temporal scale, results demonstrated that forest and aquatic ecosystems played more and more significant roles in water retention and water supply while cropland ecosystems became less and less important in food supply from 2004 to 2012. Urban system also transformed from a positive influencing to a passive receiving factor of ecosystem services in this period. Accordingly, more attention should be paid to conservation of forest and aquatic ecosystems in future urban planning in order to achieve better ecosystem service provision.
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The Three Rivers Source Area is the largest ecological function region of water source supply and conservation in China. As affected by a variety of driving factors, the ecosystems in this region are seriously degraded, giving definite impacts on the water source supply service. This paper approached the variation patterns of precipitation and runoff coefficient from 1981 to 2010, quantitatively estimated the water source supply of the ecosystems in the region from 1980 to 2005 based on InVEST model, and analyzed the spatiotemporal variation pattern and its causes of the water source supply in different periods. In 1981-2010, the precipitation in the Three Rivers Source Area had a trend of increase after an initial decrease, while the precipitation runoff coefficient presented an obvious decreasing trend, suggesting a reduced capability of runoff water source supply of this region. The potential evapotranspiration had a declining trend, but not obvious, with a rate of -0.226 mm x a(-1). In 1980-2005, the water source supply of the region represented an overall decreasing trend, which was most obvious in the Yellow River Source Area. The spatiotemporal variation of the water source supply in the Three Rivers Source Area was the results of the combined effects of climate and land use change, and the climate factors affected the water source supply mainly through affecting the precipitation and potential evapotranspiration. Climate and land use change induced the ecosystem degradation and underlying surface change, which could be the main driving forces of the declined water source supply in the Three Rivers Source Area.
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The shortage of water resources is a key factor limiting the sustainable development of the economy and society in Beijing. This study analysed the spatiotemporal patterns of Beijing’s water conservation services (WCS) based on the water balance equation at multiple scales, including city, main functional areas and key districts and counties, determined the differences in the water conservation amount among different land cover types and investigated the reasons for the spatiotemporal differences in the water conservation amount. The results indicated that: (1) compared to 2005, water conservation amount increased substantially in 2010. However, the overall water conservation capacity was low. (2) Among the various land cover types in Beijing, the average water conservation capacity decreased in the following order: wetland, forest, grassland, cropland, bare land and artificial surface. (3) The average water conservation amount in the main functional areas of Beijing varied substantially and was positive only in the ecological conservation area (ECA). (4) The water conservation capacity of each district and county varied substantially within ECA, among which the contribution of the forest in Miyun District, Huairou District and Pinggu District was the highest. The changes in the spatiotemporal patterns of Beijing’s WCS were the synthetic effects of changes in the land covers and meteorological conditions. This study is helpful in achieving the sustainable utilization of water resources in Beijing.
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To comprehensively evaluate the water conservation function of different forest ecosystems in mountain areas of Beijing, the landscape of forests was classified based on the data of CategoryⅡof the sixth forest inventory in Beijing. Function of the forest ecosystems in water conservation was estimated by means of InVEST model. The total area of 479 209 hm2 of Beijing mountain forests was divided into 18 forest types, and the total water conservation capacity was 1.62×1013 m3, equaling to average water conversation capacity of 75 mm. There was great difference in average water conversation capacity among various forest types. Larch plantation had the biggest capacity of 148 mm, while the other broadleaved tree species plantations had only 47.61 mm. Among all types of forests, the natural oak forest had the biggest total water holding capacity of 8.25×1012 m3, while the other broadleaved tree species plantations had only 6.07×109 m3.
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This study, taking the Weihe River Basin in the Guanzhong-Tianshui Economic Region of China as a case, establishes a water conservation ecosystem service network model. Based on Bayesian belief networks, the model forecasts the distribution probability of water conservation ecosystem services projected under different land-use scenarios for the year 2050 with a CA-Marcov model. A key variable subset method is proposed to optimize the spatial pattern of the water conservation ecosystem service. There were three key study findings. First, under the protection scenario, the area of woodland increased by 18.12%, mainly from the conversion of cultivated land. The grassland and cities increased by 0.73% and 0.38%, respectively. The water and unused land were reduced by 5.08% and 0.92%, respectively. The probability of high water conservation value under this scenario is the largest in the three scenarios, and the design of protection scenario is conducive to the formulation of future land use policies. Second, the key factors influencing water conservation ecosystem service include precipitation, evapotranspiration and land use. The state set corresponding to the highest state of water conservation ecosystem service is {precipitation = Highest, evapotranspiration = High, land use = High}, mainly distributed in areas with high annual average rainfall and evapotranspiration and high vegetation coverage. Third, the regions suitable for optimizing water conservation ecosystem service are mainly distributed in the southern part of Maiji District in Tianshui, southwest of Longxian and south of Weibin District in Baoji, northeast of Xunyi County and northwest of Yongshou County in Xianyang, and west of Yaozhou District in Tongchuan. Identifying the optimization regions of water conservation ecosystem service based on Bayesian belief networks, not only helps to develop a better understanding of the water conservation ecosystem services processes, but also increases the rationality of the scenario design and pattern optimization. On this basis, the key variable subset method is crucial to sound eco-environment construction and policy formulation in the study area.
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The water conservation capacities of main forests in Beijing, China were estimated through the quantitative analysis. Various methods developed in published papers on forest hydrology were employed. The forests in Huairou, Yanqing, Miyun, Mentougou and Fangshan districts are the main contributors to water conservation (the cumulative ratio reaches 65%), and the forests in Tongzhou, Chaoyang, Shunyi and Daxing districts have the highest water conservation capacity (3000 m3/ha). Altitude and slope are the key factors to affect the water conservation capacity. The forests located in Plain Area, Hilly Area, Low Mountain, and Middle Mountain contributes 27%, 28%, 24% and 21% of the conserved water, respectively. The water conservation capacity of forests in Plain Area (2 948 m3/ha), is superior to the forests in other regions. And the forests situated on Flat Slope, Moderate Slope and Gentle Slope constitute the largest proportion (nearly 93%) of water conservation, while the forests on Flat Slope has the highest water conservation capacity (2 797 m3/ha), and the forest on Steep slope has the lowest water conservation capacity (948 m3/ha).
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