Eco-engineering controls vegetation trends in southwest China karst

Effectiveness and driving mechanism of ecological restoration efforts in China from 2009 to 2019

Over the past decades, China's rapid economic growth and industrialization have led to serious ecological concerns. To combat ecological degradation and promote ecosystem sustainability, China has made substantial investments in ecological restoration in recent decades. Nevertheless, a comprehensive analysis of the effectiveness and driving mechanisms of these efforts are still lacking. Therefore, this study aims to bridge this gap by employing national land-use survey data to evaluate the effectiveness and driving mechanisms of China's ecological restoration efforts during 2009-2019, with a specific focus on ecological land preservation, land use structure, and their contribution to ecosystem services. Additionally, the Geodetector model was used to detect potential influencing factors and driving mechanisms of these efforts. The results of this study revealed that: (1) Between 2009 and 2019, a total of 585,492.61 km2 of non-ecological land was successfully transformed into ecological land through various ecological restoration efforts. Most of these areas were previously unused or cultivated land. (2) Forest and grass plantations were the major ecological restoration efforts in China, accounting for 47.35% and 41.91% of the total restored ecological land, respectively. Grassland restoration clustered northwest of the Hu Line, while forest restoration concentrated mainly to the southeast. Water and wetlands restoration were mainly distributed around China's major rivers, such as the Yangtze River and Yellow River. (3) China's ecological restoration efforts contributed to a 2.53 trillion CNY yuan increase in ecosystem service value during 2009-2019, with over 65% of the increase attributed to ecosystem regulating services. (4) China's ecological restoration efforts were mainly influenced by anthropogenic factors, such as population, land use, and urbanization, while the non-linearly enhanced interaction between natural and other factors also deserves attention. China should balance urban expansion, agricultural development, and ecological preservation, aligning restoration with socioeconomic trends while establishing effective inter-regional ecological compensation mechanisms.

Trends and contribution of different grassland types in restoring the Three River Headwater Region, China, 1988-2012

Rapid greening of the Qinghai-Tibet Plateau had been confirmed, but the contributions to the overall change and its causes in various grassland types has been less studied. Previous research has focused on exogenous factors such as climate change and human activities, rather than on endogenous factors, such as grassland types. Using net primary productivity (NPP), precipitation and temperature data, we applied trend, contribution and pull contribution analysis to understand the spatiotemporal evolution and driving factors of six different grassland types at a pixel scale in the Three River Headwater Region (TRHR) of China from 1988 to 2012. The results showed that grassland NPP in the TRHR increased at an average growth amount of 3.46 gC m-2 yr-1 and an average growth rate of 2.26 %. The average growth amount of alpine desert and alpine steppe (0.42 gC m-2 yr-1, 1.74 gC m-2 yr-1, respectively) showed great potential improvement. The average growth rate (1.27 %, 1.87 %) of montane meadow and alpine meadow, respectively, presented a high potential to increase (P < 0.05). Alpine meadow, montane meadow and temperate steppe were positive pullers to the average growth amount. Alpine steppe and alpine desert were positive pullers to the average growth rate. In general, alpine meadow had the highest growth amount contribution (84.86 %), while alpine meadow and alpine steppe had the highest contribution to the growth rate (62.16 %, 34.24 %, respectively). The study implied that, in addition to external factors, differences in internal factors such as the community composition and structure of different grassland types could also affected the grassland recovery process. These results contribute to understanding the specific differences in the contribution of regional grassland restoration processes from vegetation composition. Assessing grasslands with the potential to increase productivity, we can provide scientific reference for implementing more precise and efficient measures in future grassland management restoration.

Dynamic variations of terrestrial ecological drought and propagation analysis with meteorological drought across the mainland China

Ecological drought is a complex comprehensive process in which the water conditions for normal growth and development of vegetation are changed due to insufficient water supply. In this study, based on the remotely sensed vegetation health index (VHI) and the Famine Early Warning Systems Network Land Data Assimilation System (FLDAS) datasets from 1982 to 2020 in China, the Breaks For Additive Seasons and Trend algorithm (BFAST) was used to analyze the dynamic variations of ecological drought, the standardized regression coefficient method was applied to identify the primary drivers of ecological drought, and the regression analysis was adopted to reveal the coupling effect of atmospheric circulation factors on ecological drought. The results indicated that: (1) the ecological drought showed an overall decreasing trend during 1982-2020 in China, with a negative mutation point that occurred in April 1985; (2) spring drought and summer drought were more likely to occur in the South China, and autumn drought and winter drought were more likely to appear in the Sichuan Basin; (3) the propagation time from meteorological to ecological drought was shorter in summer (2.67 months) and longer in winter (7 months), with average r values of 0.76 and 0.53, respectively; (4) the Trans Polar Index (TPI), Arctic Oscillation (AO) and El Niño-Southern Oscillation (ENSO) had important impacts on ecological drought, which can be used as input factors of drought early warning system to improve the accuracy of drought prediction.

The Carbon Sink Potential of Southern China After Two Decades of Afforestation

Afforestation and land use changes that sequester carbon from the atmosphere in the form of woody biomass have turned southern China into one of the largest carbon sinks globally, which contributes to mitigating climate change. However, forest growth saturation and available land that can be forested limit the longevity of this carbon sink, and while a plethora of studies have quantified vegetation changes over the last decades, the remaining carbon sink potential of this area is currently unknown. Here, we train a model with multiple predictors characterizing the heterogeneous landscapes of southern China and predict the biomass carbon carrying capacity of the region for 2002-2017. We compare observed and predicted biomass carbon density and find that during about two decades of afforestation, 2.34 PgC have been sequestered between 2002 and 2017, and a total of 5.32 Pg carbon can potentially still be sequestrated. This means that the region has reached 73% of its aboveground biomass carbon carrying capacity in 2017, which is 12% more than in 2002, equal to a decrease of 0.77% per year. We identify potential afforestation areas that can still sequester 2.39 PgC, while old and new forests have reached 87% of their potential with 1.85 PgC remaining. Our work locates areas where vegetation has not yet reached its full potential but also shows that afforestation is not a long-term solution for climate change mitigation.

Ecological risk changes and their relationship with exposed surface fraction in the karst region of southern China from 1990 to 2020

Due to anthropogenic disturbances, the karst region in southern China is vulnerable to ecological problems such as soil erosion and surface exposure. However, limited studies on variations in large-scale ecological risk (ER) and their influencing factors, particularly the coupling/decoupling relationship with an exposed surface fraction (ESF), make ER regulations and ecological restoration challenging. The present study evaluates the ER of eight typical karst provinces in Southern China from 1990 to 2020 using the technique for order preference by similarity to an ideal solution (TOPSIS) model and ecosystem services (habitat quality, water yield, carbon storage, soil conservation, and food production), and extracts the contemporaneous ESF using Landsat satellite data in Google Earth Engine (GEE). The spatiotemporal change of ER and ESF are analyzed, and their coupling/decoupling relationship and driving mechanism are explored using coupling coordination degree (CCD) and multi-scale geographically weighted regression (MGWR) models. The results show that: (1) Over the past 30 years, the ER has increased until 2010 and subsequently declined, with an increasing mean value (0.463-0.503), except in Chongqing municipality. The ESF decreased significantly (the mean value dropped from 44.7% to 38.7%), except that in Sichuan province. (2) The average CCD between ER and ESF decreased with fluctuation of -0.017, with a decoupling relationship (58.18%). The coupling area is larger than the decoupling area in the Sichuan area, while other provinces are opposite. (3) The coupling/decoupling relationship in the study area is mainly driven by terrain (elevation, slope) and socio-economic (population density, per capita GDP) factors. More attention should be paid to the role of these factors in the continuous reduction and control of ESF and ER. This study can serve as a reference for similar studies in karst regions, such as risk assessment and surface monitoring, rocky desertification control, ecological engineering layout, and territorial planning.

Hydrogeochemical Response of Cave Drips to Precipitation during Rainfall in a Karst Desertification Region: A Case Study of Shijiangjun Cave, South China

Exploring the hydrogeochemistry of cave drip water and its response to precipitation events in karst rocky desertification regions is of great significance to the paleoenvironment reconstruction of the karst desertification process using speleothem. We selected three perennial drip sites in the Shijiangjun Cave, located in Guizhou Province, Southwest China, and carried out high-frequency monitoring and sampling during two rainfalls from 22 to 25 May 2016. The major hydrogeochemical parameters of drip water and their relationships with karst desertification were analyzed. The results show that the hydrogeochemistry of the drip water in the Shijiangjun Cave, characterized by HCO₃-Ca·Mg, was dominated by the dissolution of calcareous dolomite. The three drip sites were classified into the delayed response type (W1) and the rapid response type (W2 and W3) based on the response speed of the drip water indicators to precipitation, which were highly influenced by the piston effect and precipitation dilution, respectively. Furthermore, the response sensitivity of the drip water indicators to precipitation was constrained by the desertification degree in the rainy season, specifically, the faster response appeared in the higher desertification degree area. It is essential to select appropriate drip sites and establish an applicable indicator system for the evolutional history reconstruction of karst desertification using speleothems.

Processes and mechanisms of vegetation ecosystem responding to climate and ecological restoration in China

Vegetation is an essential component of the earth's surface system and its dynamics is a clear indicator of global climate change. However, the vegetation trends of most studies were based on time-unvarying methods, cannot accurately detect the long-term nonlinear characteristics of vegetation changes. Here, the ensemble empirical mode decomposition and the Breaks for Additive Seasonal and Trend algorithm were applied to reconstruct the the normalized difference vegetation index (NDVI) data and diagnose spatiotemporal evolution and abrupt changes of long-term vegetation trends in China during 1982-2018. Residual analysis was used to separate the influence of climate and human activities on NDVI variations, and the effect of specific human drivers on vegetation growth was obtained. The results suggest that based on the time-varying analysis, high vegetation browning was masked by overall vegetation greening. Vegetation growth in China experienced an abrupt change in the 1990s and 2000s, accounting for 50% and 33.6% of the whole China respectively. Of the area before the breakpoint, 45.4% showed a trend of vegetation decrease, which was concentrated mainly in east China, while 43% of the area after the breakpoint also showed vegetation degradation, mainly in northwest China. Climate was an important driving force for vegetation change in China. It played a positive role in south China, but had a negative effect in northwest China. The impact of human activities on vegetation growthchanged from an initial negative influence to a positive one. In terms of human activities, an inverted-U-shaped relation was detected between CO₂ emissions and vegetation growth; that is, the fertilization effect of CO₂ had a certain threshold. Once that threshold was exceeded, it would hinder vegetation growth. Population density had a slight constraint on vegetation growth, and the implementation of ecological restoration projects (e.g., the Grain for Green Program) can promote vegetation growth to a certain extent.

Ecological restoration programs dominate vegetation greening in China

Many ecological restoration programs have been implemented in China during the last two decades. At the same time, the vegetation has turned green significantly in China. However, few studies have directly evaluated the contribution of the ecological restoration programs to vegetation greening in comparison with the contribution of climate change using high-resolution data of afforestation areas at the national scale. We used newly compiled high-resolution data on yearly forest plantation and mountain closure, the daily climate data from the 2480 meteorological stations and GIMMS 3g NDVI data. We used a multiple linear regression model to compare the influence of temperature, precipitation, and ecological restoration programs on NDVI dynamics. We then used the hierarchical variance partitioning method to evaluate the relative contribution of temperature, precipitation, and ecological restoration programs on NDVI dynamics. We found a significant greening trend in China from 1999 to 2015 with an annual increase rate of 0.0017 yr^-1 in the mean growing season NDVI. The ecological restoration programs dominated the vegetation greening in northern China and the southern coastal regions, indicating a good performance of restoration programs in these regions. In contrast, temperature or precipitation dominated the vegetation greening in southwestern China, Inner Mongolia and the implementation regions of several ecological restoration programs in northeastern China. Among the ecological restoration programs except the Three-North Shelterbelt Forest Program, the effect of ecological restoration programs on vegetation greening was stronger than the total effects of temperature and precipitation changes. Our study presents a systematic assessment on the contribution of ecological restoration programs to the vegetation greening in China, accessed the role on vegetation greening of different ecosystem restoration programs. We analyzed the reasons for the differences in the contribution of different ecological restoration programs to vegetation greening and provided insights facilitating policy makers to prioritize future restoration planning.

Characterization and attribution of vegetation dynamics in the ecologically fragile South China Karst: Evidence from three decadal Landsat observations

Plant growth and its changes over space and time are effective indicators for signifying ecosystem health. However, large uncertainties remain in characterizing and attributing vegetation changes in the ecologically fragile South China Karst region, since most existing studies were conducted at a coarse spatial resolution or covered limited time spans. Considering the highly fragmented landscapes in the region, this hinders their capability in detecting fine information of vegetation dynamics taking place at local scales and comprehending the influence of climate change usually over relatively long temporal ranges. Here, we explored the spatiotemporal variations in vegetation greenness for the entire South China Karst region (1.9 million km²) at a resolution of 30m for the notably increased time span (1987-2018) using three decadal Landsat images and the cloud-based Google Earth Engine. Moreover, we spatially attributed the vegetation changes and quantified the relative contribution of driving factors. Our results revealed a widespread vegetation recovery in the South China Karst (74.80%) during the past three decades. Notably, the area of vegetation recovery tripled following the implementation of ecological engineering compared with the reference period (1987-1999). Meanwhile, the vegetation restoration trend was strongly sustainable beyond 2018 as demonstrated by the Hurst exponent. Furthermore, climate change contributed only one-fifth to vegetation restoration, whereas major vegetation recovery was highly attributable to afforestation projects, implying that anthropogenic influences accelerated vegetation greenness gains in karst areas since the start of the new millennium during which ecological engineering was continually established. Our study provides additional insights into ecological restoration and conservation in the highly heterogeneous karst landscapes and other similar ecologically fragile areas worldwide.

Sustainable Agricultural Development Models of the Ecologically Vulnerable Karst Areas in Southeast Yunnan from the Perspective of Human–Earth Areal System

Rocky desertification in ecologically-fragile karst areas limit regional socio-economic development in the face of significant human–earth conflict. Coordination of ecological restoration and agricultural development is critical for sustainable development in karst areas. From the perspective of the human–earth areal system, the framework of sustainable agricultural development was proposed in typically karst areas. We integrated principles of ecological vulnerability, resource and environmental carrying capacity, agricultural foundation, suitability of agricultural land, and the farmers’ willingness. In this study, we found the ecological vulnerability of Guangnan County was slight, but the proportion of moderate and severe vulnerability areas was high, with significant differences between the two sides of the line “Zhe (Zhetu)-Lian (Liancheng)-Yang (Yang Liu-jing)-Ban (Banbang)”. Then, we divided Guangnan County into three ecologically vulnerable zones. Following that, we proposed sustainable agricultural models for various zones. In slightly to mildly vulnerable zones, we propose constructing economic–ecological agricultural models, including woody oil, plateau characteristic fruiting forest, ecological tea plantations, suburban agriculture, and cultural–ecological tourism. In moderately to severely vulnerable zones, we recommend developing a stereoscopic agriculture model that combines planting and breeding, vegetation restoration, and herbivorous animal husbandry. In extremely vulnerable zones, we suggest constructing an ecologically natural restoration model and an agricultural ecological–tourism model. Our research provides references for ecological restoration, agricultural development, poverty alleviation consolidation, and rural revitalization in ecologically vulnerable karst areas of southeast Yunnan and similar regions.

Quantitative Analysis of Natural and Anthropogenic Factors Influencing Vegetation NDVI Changes in Temperate Drylands from a Spatial Stratified Heterogeneity Perspective: A Case Study of Inner Mongolia Grasslands, China

The detection and attribution of vegetation dynamics in drylands is an important step for the development of effective adaptation and mitigation strategies to combat the challenges posed by human activities and climate change. However, due to the spatial heterogeneity and interactive influences of various factors, quantifying the contributions of driving forces on vegetation change remains challenging. In this study, using the normalized difference vegetation index (NDVI) as a proxy of vegetation growth status and coverage, we analyzed the temporal and spatial characteristics of the NDVI in China’s Inner Mongolian grasslands using Theil–Sen slope statistics and Mann–Kendall trend test methods. In addition, using the GeoDetector method, a spatially-based statistical technique, we assessed the individual and interactive influences of natural factors and human activities on vegetation-NDVI change. The results show that the growing season average NDVI exhibited a fluctuating upward trend of 0.003 per year from 2000 to 2018. The areas with significant increases in NDVI (p < 0.05) accounted for 45.63% of the entire region, and they were mainly distributed in the eastern part of the Mu Us sandy land and the eastern areas of the Greater Khingan Range. The regions with a decline in the NDVI were mainly distributed in the central and western regions of the study area. The GeoDetector results revealed that both natural and human factors had significant impacts on changes in the NDVI (p < 0.001). Precipitation, livestock density, wind speed, and population density were the dominant factors affecting NDVI changes in the Inner Mongolian grasslands, explaining more than 15% of the variability, while the contributions of the two topography factors (terrain slope and slope aspect) were relatively low (less than 2%). Furthermore, NDVI changes responded to the changes in the level of specific influencing factors in a nonlinear way, and the interaction of two factors enhanced the effect of each singular factor. The interaction between precipitation and temperature was the highest among all factors, accounting for 39.3% of NDVI variations. Findings from our study may aid policymakers in better understanding the relative importance of various factors and the impacts of the interactions between factors on vegetation change, which has important implications for preventing and mitigating land degradation and achieving sustainable pasture use in dryland ecosystems.

Dense canopies browning overshadowed by global greening dominant in sparse canopies

Greening, an increase in photosynthetically active plant biomass, has been widely reported as period-related and region-specific. We hypothesized that vegetation trends were highly density-dependent with intensified browning in dense canopies and increased greening in sparse canopies. We exploited this insight by estimating vegetation trends in peak growth from dense to sparse canopies graded from 1 to 20 using the non-parametric Mann-Kendall trend test based on the 500 m 8-day composite MODIS Near Infrared Reflectance of terrestrial vegetation (NIRv) time series datasets in the past two decades (2001-2019) at the global scale. We found that global greening increased by 1.42% per grade with strong fit before grade 15 (R² = 0.95): net browning (11% browning vs 9% greening) exhibited in high-density canopies (NIRv > 0.39) in contrast to 32% greening in low-density canopies (NIRv ≈ 0.15). While the density-dependent greening was evidenced across different biomes and ecosystems, the steepest gradient (changes per grade) in cropland highlighted the increasingly intensified agricultural activities globally. Greening gradients declined in the dryland, but enhanced in the High-latitude ecosystems driven by warming, especially in the shrubland. Density-dependent vegetation trends were accounted for by the disproportionately impacts from climate changes and the unequal contributions of Land Cover Changes (LCC) among dense and sparse canopies. Vegetation trends and greening gradients could be extensively facilitated by Wetting or Decreasing solar Radiation (WDR), especially in sparse grassland and shrubland. Browning was dominant in dense canopies, which was further aggravated by Drying and Increasing solar Radiation (DIR), especially woody vegetation. This study implied the widespread degradation or mortality of highly productive vegetation hidden among global greening dominant in open ecosystems, which might be further exacerbated by the predicted increasing drought under global warming.

Spatiotemporal Dynamics of Terrestrial Vegetation and Its Driver Analysis over Southwest China from 1982 to 2015

Global environmental changes have been dramatic recently, exerting substantial effects on the structures and functions of terrestrial ecosystems, especially for the ecologically-fragile karst regions. Southwest China is one of the largest karst continuum belts around the world, which also contributes about 1/3 of terrestrial carbon sequestration to China. Therefore, a deep understanding of the long-term changes of vegetation across Southwest China over the past decades is critical. Relying on the long time series of Advanced Very High Resolution Radiometer (AVHRR) Global Inventory Modeling and Mapping Studies normalized difference vegetation index (GIMMS NDVI3g) data set, this study examined the spatial and temporal patterns of vegetation conditions in Southwest China from 1982 to 2015, as well as their response to the environmental factors including temperature, precipitation and downward shortwave radiation. Multi-year mean NDVI showed that except the northwestern region, the NDVI of Southwest China was large, ranging from 0.5 to 0.8. Meanwhile, nearly 43.7% of the area experienced significant improvements in NDVI, whereas only 3.47% of the area exhibited significant decreases in NDVI. Interestingly, the NDVI in karst area increased more quickly with 1.035 × 10−3/a in comparison with that in the non-karst area with about 0.929 × 10−3/a. Further analysis revealed that temperature is the dominant environmental factor controlling the interannual changes in NDVI, accounting for 48.19% of the area, followed by radiation (3.71%) and precipitation (3.09%), respectively.

Ecological Engineering Projects Shifted the Dominance of Human Activity and Climate Variability on Vegetation Dynamics

Global greening and its eco-environmental outcomes are getting mounting international focus. The important contribution of China to the global greening is highly appreciated. However, the basic driving forces are still elusive. The Loess Plateau (LP) and Three-River Source Region (TRSR) were chased as study areas in Northern China. The prior one represents the region experiencing intensive human interventions from ecological engineering projects, while the latter is a typical region that is experiencing faster climate change. Hypothesized to be driven by a disproportionate rate of human activities and climates, also being regions of typical large-scale ecological engineering projects, the study goal is to identify the actual driving forces on vegetation dynamics in these two regions. Trend analysis, correlation analysis, and residual trend-based method (RESTREND) were utilized to understand the relationships between climate variability, human activities, and vegetation dynamics. The spatiotemporal variations of vegetation from 1982 to 2019 were evaluated and the respective impacts of climatic and anthropogenic factors on vegetation dynamics were disentangled. Indicating apparent vegetation restoration in LP and TRSR, the results depict that annual LAI has remarkably increased during the 38 years. Temperature and precipitation promoted vegetation growth, whereas the solar radiation and vapor pressure deficit hampered it. After implementing the ecological engineering projects, the primary climatic factor changed from temperature to precipitation. Meanwhile, human activities act as the major driving factor in vegetation greening in the entire study area, with a contribution rate exceeding 70%. This information highlights that ecological engineering can significantly reduce the risks of ecosystem degradation and effectively restore vegetation, especially in ecologically sensitive and vulnerable areas.

The Changes of Spatiotemporal Pattern of Rocky Desertification and Its Dominant Driving Factors in Typical Karst Mountainous Areas under the Background of Global Change

There are significant differences in the dominant driving factors of rocky desertification evolution in different historical periods in southwest karst mountainous areas. However, previous studies were mostly conducted in specific periods. In this study, taking Bijie City as an example, the spatial and temporal evolution pattern of rocky desertification in Bijie City in the recent 35 years was analyzed by introducing the feature space model and the gravity center model, and then the dominant driving factors of rocky desertification in the study area in different historical periods were clarified based on GeoDetector. The results were as follows: (1) The point-to-point B (bare land index)-DI (dryness index) feature space model has high applicability for rocky desertification monitoring, and its inversion accuracy was 91.3%. (2) During the past 35 years, the rocky desertification in Bijie belonged to the moderate rocky desertification on the whole, and zones of intensive and severe rocky desertification were mainly distributed in the Weining Yi, Hui, and Miao Autonomous Region. (3) During 1985–2020, the rocky desertification in Bijie City showed an overall weakening trend (‘weakening–aggravating–weakening’). (4) From 1985 to 2020, the gravity center of rocky desertification in Bijie City moved westward, indicating that the aggravating degree of rocky desertification in the western region of the study area was higher than that in the eastern region. (5) The dominant factors affecting the evolution of rocky desertification in the past 35 years shifted from natural factor (vegetation coverage) to human activity factor (population density). The research results could provide decision supports for the prevention and control of rocky desertification in Bijie City and even the southwest karst mountainous area.

Changes in the Soil Labile Organic Carbon Fractions following Bedrock Exposure Rate in a Karst Context

Soil labile organic carbon fractions (SLOCFs) mainly include microbial biomass carbon (MBC), dissolved organic carbon (DOC), easily oxidized organic carbon (EOC) and light fraction organic carbon (LFOC). The link between bedrock exposure rates with SLOCFs and the carbon pool management index under karst rocky desertification has not been well understood. We selected the bedrock exposure rate and vegetation coverage of 30–50% (light bedrock exposure, LBE), 50–70% (moderate bedrock exposure, MBE) and >70% (intense bedrock exposure, IBE) as the experimental sample plots according to the classification standard of karst rocky desertification, and then selected a sample plot of 0–30% (secondary forest, SF) as the control. This study compared the concentrations and stocks of soil organic carbon (SOC) and SLOCFs and analyzed the relevant carbon pool management index on karst landforms at Anshun, S.W. China. The aims were to determine the relationship between bedrock exposure rates and SLOCFs and to identify the most limiting factors for SLOCFs in karst rocky desertification areas. We found that (1) the concentrations and stocks of SLOCFs declined with increasing soil depth. SOC, DOC and MBC showed IBE (intense bedrock exposure) > LBE (light bedrock exposure) > MBE (moderate bedrock exposure) > SF (secondary forest); LFOC decreased with increasing bedrock exposure rate, and EOC did not show obvious regularity. (2) The carbon pool management index and sensitivity index had significant differences under different bedrock exposure rates. Redundancy analysis and linear regression showed that the increase in bedrock exposure rate had a great impact on MBC, DOC, EOC and SOC. In conclusion, the increase of bedrock exposure rate has no side impact on the DOC, EOC and MBC of the soil, but side effects are exhibited by LFOC. secondary forest improves the integrity of karst landscapes, and does not change the soil properties as well as the concentrations and stocks of SLOCFs in karst rocky desertification areas.

How can massive ecological restoration programs interplay with social-ecological systems? A review of research in the South China karst region

Exploring the cost-effective pathways for restoring ecosystems is a fundamental aspect for scientific communities and policy-makers aiming for a sustainable future. The South China karst region has experienced severe environmental degradation because of unsustainable management practices in this vulnerable social-ecological context. However, it has also become one of the most stunning areas following its remarkable vegetation recovery over recent decades as a result of large-scale ecological restoration programs. There is an extensive body of literature focusing on how ecological restoration programs have altered the degraded environment in this region. By searching and comparing the published peer-reviewed articles, we reviewed the studies related to the effects of ecological restoration programs from the point of view of ecological, socio-economic, and integrated social-ecological impacts, as well as influencing factors and restoration approaches. We found independent evidence to support that large-scale ecological restoration programs increased biomass and carbon sequestration since 2000 across this region. The farmers' livelihoods have spontaneously transited from agriculture into forestry or non-farming sectors without financial compensation or incentive schemes, which coincided with a positive correlation between the implementation of ecological restoration programs and poverty alleviation. However, due to a lack of clear "before and after" comparisons, many studies have indirectly determined the impacts of ecological restoration with non-negligible uncertainties. In addition, considering the critical interactions between belowground and aboveground processes in karst regions, special attention should be given to the selection of tree species and restoration measures according to different bedrock types. In the future, to better understand the impacts of ecological restoration on social-ecological systems, research could be advanced by considering data access, context-based analysis, measurement-targeted assessment, and cross-scale integration.

Mapping Forest Restoration Probability and Driving Archetypes Using a Bayesian Belief Network and SOM: Towards Karst Ecological Restoration in Guizhou, China

To address ecological threats such as land degradation in the karst regions, several ecological restoration projects have been implemented for improved vegetation coverage. Forests are the most important types of vegetation. However, the evaluation of forest restoration is often uncertain, primarily owing to the complexity of the underlying factors and lack of information related to changes in forest coverage in the future. To address this issue, a systematic case study based on the Guizhou Province, China, was carried out. First, three archetypes of driving factors were recognized through the self-organizing maps (SOM) algorithm: the high-strength ecological archetype, marginal archetype, and high-strength archetype dominated by human influence. Then, the probability of forest restoration in the context of ecological restoration was predicted using Bayesian belief networks in an effort to decrease the uncertainty of evaluation. Results show that the overall probability of forest restoration in the study area ranged from 22.27 to 99.29%, which is quite high. The findings from regions with different landforms suggest that the forest restoration probabilities of karst regions in the grid and the regional scales were lower than in non-karst regions. However, this difference was insignificant mainly because the ecological restoration in the karst regions accelerated local forest restoration and decreased the ecological impact. The proposed method of driving-factor clustering based on restoration as well as the method of predicting restoration probability have a certain reference value for forest management and the layout of ecological restoration projects in the mid-latitude ecotone.

Nonlinear Characteristics of NPP Based on Ensemble Empirical Mode Decomposition from 1982 to 2015—A Case Study of Six Coastal Provinces in Southeast China

Monitoring vegetation net primary productivity (NPP) is very important for evaluating ecosystem health. However, the nonlinear characteristics of the vegetation NPP remain unclear in the six provinces along the Maritime Silk Road in China. In this study, using NDVI and meteorological data from 1982 to 2015, NPP was estimated with the Carnegie-Ames-Stanford Approach (CASA) model based on vegetation type dynamics, and its nonlinear characteristics were explored through the ensemble empirical mode decomposition (EEMD) method. The results showed that: (1) The total NPP in the changed vegetation types caused by ecological engineering and urbanization increased but decreased in those caused by agricultural reclamation and vegetation destruction, (2) the vegetation NPP was dominated by interannual variations, mainly in the middle of the study area, while by long-term trends, mainly in the southwest and northeast, (3) for most of the vegetation types, NPP was dominated by the monotonically increasing trend. Although vegetation NPP in the urban land mainly showed a decreasing trend (monotonic decrease and decrease from increase), there were large areas in which NPP increased from decreasing. Although vegetation NPP in the farmland mainly showed increasing trends, there were large areas that faced the risk of NPP decreasing; (4) dynamical changes of vegetation type by agricultural reclamation and vegetation destruction made the NPP trend monotonically decrease in large areas, leading to ecosystem degradation, while those caused by urbanization and ecological engineering mainly made the NPP increase from decreasing, leading to later recovery from early degradation. Our results highlighted the importance of vegetation type dynamics for accurately estimating vegetation NPP, as well as for assessing their impacts, and the importance of nonlinear analysis for deepening our understanding of vegetation NPP changes.

Spatiotemporal analysis and potential impact factors of vegetation variation in the karst region of Southwest China

The karst region of Southwest China is one of the largest in the world. Due to the effects of human activities and climate change, rocky desertification has become the primary ecological disaster which has significantly hindered the economic growth in Southwest China. In recent decades, the Chinese government has carried out a number of ecological restoration projects in Southwest China. This study aims to analyze the changes in vegetation coverage and its main driving factors in the Southwest China and the karst region of Southwest China from 2001 to 2015 through trend analysis, Hurst index correlation analysis, correlation analysis, and residual analysis. The results showed that (1) both Southwest China and the karst region of Southwest China experienced significant increasing trends in annual fractional vegetation cover, at a rate of 0.0028 year^-1 and 0.0029 year^-1, respectively; (2) the NDVI of the Southwest China and the karst region of Southwest China was stable, and the vegetation coverage areas showed low to medium fluctuations, accounting for 97.17% and 98.32% respectively; (3) the NDVI of the Southwest China and the karst region of Southwest China had strong sustainability, and the sustainable and improved regions account for 74.79% and 75.77% respectively; and (4) climate change had little influence on vegetation restoration, and human activities had a great influence on vegetation restoration. The relative contribution rates of human activities and climate change to vegetation NDVI changes in the Southwest China were 86% and 14%, respectively, and 90% and 10% in karst regions of Southwest China. Our findings contribute to a better understanding of the mechanisms of vegetation change in karst region and may provide scientific support for local vegetation restoration and conservation policies.