Search Results (439)

The damage caused by soil erosion to global ecosystems is undeniable. However, traditional research methods often do not consider the unique soil characteristics specific to China and rainfall intensity variability in different periods on vegetation, and relatively few research efforts have addressed the attribution analysis of soil erosion changes in tropical islands. Therefore, this study applied a modification of the Chinese Soil Loss Equation (CSLE) to evaluate the monthly mean soil erosion modulus in Hainan Island over the past two decades, aiming to assess the potential soil erosion risk. The model demonstrated a relatively high R², with validation results for the three basins yielding R² values of 0.77, 0.64, and 0.78, respectively. The results indicated that the annual average soil erosion modulus was 92.76 t·hm⁻²·year⁻¹, and the monthly average soil erosion modulus was 7.73 t·hm⁻²·month⁻¹. The key months for soil erosion were May to October, which coincided with the rainy season, having an average erosion modulus of 8.11, 9.41, 14.49, 17.05, 18.33, and 15.36 t·hm⁻²·month⁻¹, respectively. September marked the most critical period for soil erosion. High-erosion-risk zones are predominantly distributed in the central and eastern sections of the study area, gradually extending into the southwest. The monthly average soil erosion modulus increased with rising elevation and slope. The monthly variation trend in rainfall erosivity factor had a greater impact on soil water erosion than vegetation cover and biological practice factor. The identification of dynamic factors is crucial in areas prone to soil erosion, as it provides a scientific underpinning for monitoring soil erosion and implementing comprehensive water erosion management in these regions. Full article

Exploring the phenological divergences in vegetation caused by global climate change is of great significance for gaining a deeper understanding of the carbon cycling process in natural ecosystems. However, in many existing studies, the response of the start of the growing season (SOS) and the end of the growing season (EOS) to temperature exhibited multi-scale inconsistencies. In view of this, we took 259 Chinese urban agglomerations and their rural regions as the study areas, using MODIS phenological products (MCD12Q2), land surface temperature (LST) datasets, altitude, and latitude as data, and explored the phenological divergences in vegetation with LST changes in different geographical zones through box plots, linear regression models, and Spearman’s correlation analysis. The mean SOS and EOS in urban areas were both the earliest on approximately the 100.06th day and 307.39th day, respectively, and were then gradually delayed and advanced separately along an urban–rural gradient of 0–25 km. The divergences in vegetation phenology were no longer significant in rural areas 10 km away from urban boundaries, with change amplitudes of less than 0.4 days. In high latitude (40–50° N) regions, the correlation coefficients between the SOS and EOS of various urban agglomerations and LST were −0.627 and 0.588, respectively, whereas in low latitude (18–25° N) regions, the correlation coefficients appeared to be the opposite, being 0.424 and −0.426, respectively. In mid- to high-altitude (150–400 m) areas, LST had a strong advanced effect on SOS, while in high-altitude (above 1200 m) areas, LST had a strong delayed effect on EOS, with the R² values all being above 0.7. In summary, our study has revealed that within the context of varying geographical zones, the effects of LST on phenology exhibited significant spatial heterogeneity. This may provide strong evidence for the inconsistencies in the trends of phenology observed across previous studies and more relevant constraints for improving vegetation phenology prediction models. Full article

Soil organic matter plays a crucial role in the global carbon cycle, yet the magnitude and direction of changes in soil carbon content following vegetation shifts in the tropics remain highly debated. Most studies have focused on short-term changes, typically spanning only a few months or years. In this study, we investigated the medium-term dynamics of organic matter at a site where savanna, protected from fire for 58 years, has gradually transitioned to woodland vegetation. Natural ¹³C abundance analysis combined with particle-size fractionation was used to characterize the changes in SOM over time. While carbon content remains relatively stable, δ¹³C exhibits a distinct shift, particularly in the surface layers, reflecting the gradual replacement of savanna-derived carbon with tree-derived carbon. All fractions were influenced by the inputs and outputs of carbon from both savanna and tree sources. In the coarse fractions, most of the carbon originates from trees; however, a significant proportion of savanna-derived carbon (ranging from 10% to 40%, depending on the fraction, depth, and patch) persists, likely in the form of black carbon. In the fine fractions, nearly half of the carbon (40% to 50%) remains derived from the savanna, highlighting the greater stability of organic matter that is physically bound to clays and protected within microaggregates. Full article

Larix chinensis Mill., the sole tree species that can form pure forests at the timberline of the Qinling Mountains, plays a crucial role in maintaining the stability of high-altitude ecosystems. Owing to its special habitat requirements and fragmented distribution pattern, populations of L. chinensis are in a clear degenerating stage. Numerous studies have underscored the significant effect of climate change on high-altitude vegetation. However, studies focusing on the shifts in the distribution of L. chinensis habitats and the key environmental factors hindering their suitable distribution remain limited. Therefore, this study aimed to explore the influence of climate change on the future potential distribution of L. chinensis in order to understand the response of timberlines to climate change. In this study, random forest algorithms were applied to project the future potential distribution of L. chinensis across the Qinling Mountains. The results found that temperature and precipitation play crucial roles in limiting the distribution of L. chinensis, particularly in cold–humid climates and rainy, foggy environments, which contribute to its patchy distribution pattern. Currently, L. chinensis populations are distributed in Taibai Mountain and its surrounding alpine areas, concentrated at elevations of 2900–3300 m and on southern slopes of 15–35°, covering approximately 3361 km². The ecological niche of L. chinensis is relatively narrow in terms of these environmental variables differing from the prevailing climate in the Qinling Mountains. During past climatic conditions or the last interglacial period (LIG period), the potential distribution range of L. chinensis gradually reduced, especially in low-elevation areas, nearly disappearing altogether. Projections under future climate scenarios suggest the contraction and fragmentation of suitable habitats for L. chinensis. The response of L. chinensis to the RCP 8.5 scenario exhibited the most pronounced changes, followed by the RCP 4.5 scenario. Under all climate scenarios in the 2050s, L. chinensis-suitable distribution exhibited varying degrees of reduction. Under the RCP 8.5 scenario, a significant decrease in suitable distribution is projected. Suitable distribution will continually decrease by the 2070s, with the most significant decline projected under the RCP 2.6 scenario. In conclusion, our findings not only offer management strategies for the populations of L. chinensis amidst climate change but also serve as crucial references for some endangered tree species in climate-sensitive areas. Full article

Environmental particulate pollution is a major global environmental health risk factor, which is associated with numerous adverse health outcomes, negatively impacting public health in many countries, including China. Despite the implementation of strict air quality management policies in China and a significant reduction in PM_2.5 concentrations in recent years, the health burden caused by PM_2.5 pollution has not decreased as expected. Therefore, a comprehensive analysis of the health burden caused by PM_2.5 is necessary for more effective air quality management. This study makes an innovative contribution by integrating the Enhanced Vegetation Index (EVI), Normalized Difference Vegetation Index (NDVI), and Soil-Adjusted Vegetation Index (SAVI), providing a comprehensive framework to assess the health impacts of green space coverage, promoting healthy urban environments and sustainable development. Using Nanjing, China, as a case study, we constructed a health impact assessment system based on PM_2.5 concentrations and quantitatively analyzed the spatiotemporal evolution of premature deaths caused by PM_2.5 from 2000 to 2020. Using Multiscale Geographically Weighted Regression (MGWR), we explored the impact of greening improvement on premature deaths attributed to PM_2.5 and proposed relevant sustainable governance strategies. The results showed that (1) premature deaths caused by PM_2.5 in Nanjing could be divided into two stages: 2000–2015 and 2015–2020. During the second stage, deaths due to respiratory and cardiovascular diseases decreased by 3105 and 1714, respectively. (2) The spatial variation process was slow, with the overall evolution direction predominantly from the southeast to northwest, and the spatial distribution center gradually shifted southward. On a global scale, the Moran’s I index increased from 0.247251 and 0.240792 in 2000 to 0.472201 and 0.468193 in 2020. The hotspot analysis revealed that high–high correlations slowly gathered toward central Nanjing, while the proportion of cold spots increased. (3) The MGWR results indicated a significant negative correlation between changes in green spaces and PM_2.5-related premature deaths, especially in densely vegetated areas. This study comprehensively considered the spatiotemporal changes in PM_2.5-related premature deaths and examined the health benefits of green space improvement, providing valuable references for promoting healthy and sustainable urban environmental governance and air quality management. Full article

The organic carbon pool in the field is one of the important carbon pools in the ecosystem. This study explored the changes in soil organic carbon fractions and their influencing mechanisms under different cultivation years of jujube trees in the sandy area. This study measured the bulk density, total porosity, water content, pH, salt content, organic matter, major elements, trace elements, and organic carbon fractions of soil in jujube orchards with cultivation years of 2 years, 4 years, 6 years, 8 years, and 10 years, and analyzed the influencing mechanism of physical and chemical properties on soil organic carbon fractions through structural equation modeling. The results showed that soil physical properties were beneficial to plant growth with the increase in limited planting years. Nitrogen, phosphorus, potassium, and other elements were highest in different soil layers in 6–8 years, and then their contents gradually decreased. Soil organic carbon content increased with the increase in different cultivation years and then remained in a stable state. In different soil layers, soil organic carbon is mainly affected by the active soil organic carbon pool (ASCP). The results of this study aim to explore the effect of vegetation on soil improvement in sandy areas and provide theoretical reference for soil restoration and improvement of the organic carbon pool of sandy soil in southern Xinjiang. Full article

This research explores the dynamics of vegetation patterns under changing environmental conditions, considering the United Nations Sustainable Development Goal 15: “Protect, restore, and promote the sustainable use of terrestrial ecosystems; combat desertification; halt and reverse land degradation; and prevent biodiversity loss”. In this context, this study presents a modeling and nonlinear analysis framework for plant–soil-moisture interactions, including Holling-II functional response and hyperbolic mortality models. The primary goal is to explore how nonlinear soil–water interactions influence vegetation patterns in semi-arid ecosystems. Moreover, the influence of nonlinear soil–water interaction on the establishment of population patterns is investigated. The formation and evolution of these patterns are explored using theoretical analysis and numerical simulations, as well as important factors and critical thresholds. These insights are crucial for addressing desertification, a key challenge in semi-arid regions that threatens biodiversity, ecosystem services, and sustainable land management. The model, which includes environmental parameters such as rainfall, plant growth rates, and soil moisture, was tested using both theoretical analysis and numerical simulations. These characteristics are carefully adjusted to find important thresholds influencing the danger of desertification. Simulation scenarios, run under set initial conditions and varying parameters, yield useful insights into the pattern of patch development under dynamically changing environmental conditions. The findings revealed that changes in environmental conditions, such as rainfall and plant growth rates, prompted Hopf bifurcation, resulting in the production of three distinct patterns: a dotted pattern, a striped pattern, and a combination of both. The creation of these patterns provides essential information about the sustainability of environmental equilibrium. The variation curve of the average plant biomass reveals that the biomass fluctuates around a constant period, with the amplitude initially increasing, then decreasing, and gradually stabilizing. This research provides a solid foundation for addressing desertification risks, using water resources responsibly, and contributing to a better understanding of ecosystem stability. Full article

Vegetation indices are important representatives of plant growth. Climate change and human activities seriously affect vegetation. This study focuses on the Huojitu mining area in the Shendong region, utilizing the kNDVI index calculated via the Google Earth Engine (GEE) cloud platform. The Mann–Kendall mutation test and linear regression analysis were employed to examine the spatiotemporal changes in vegetation growth over a 25-year period from 1999 to 2023. Through correlation analysis, geographic detector models, and land use map fusion, combined with climate, topography, soil, mining, and land use data, this study investigates the influencing factors of vegetation growth evolution. The key findings are as follows: (1) kNDVI is more suitable for analyzing vegetation growth in this study compared to NDVI. (2) Over the past 25 years, vegetation growth has exhibited an overall fluctuating upward trend, with an annual growth rate of 0.0041/a. The annual average kNDVI value in the mining area is 0.121. Specifically, kNDVI initially increased gradually, then rapidly increased, and subsequently declined rapidly. (3) Vegetation growth in the study area has significantly improved, with areas of improved vegetation accounting for 89.08% of the total mining area, while degraded areas account for 11.02%. (4) Precipitation and air temperature are the primary natural factors influencing vegetation growth fluctuations in the mining area, with precipitation being the dominant factor (r = 0.81, p < 0.01). The spatial heterogeneity of vegetation growth is influenced by land use, topography, soil nutrients, and mining activities, with land use having the greatest impact (q = 0.43). Major land use changes contribute 46.45% to vegetation improvement and 13.43% to vegetation degradation. The findings of this study provide a scientific basis for ecological planning and the development of the Huojitu mining area. Full article

Net primary productivity (NPP) is a core ecological indicator within terrestrial ecosystems, representing the potential of vegetation growth to offset anthropogenic carbon emissions. Thus, assessing NPP in a given region is crucial for promoting regional ecological restoration and sustainable development. This study utilized the CASA model and GEE to calculate the annual average NPP in Shandong Province (2001–2020). Through trend analysis, Moran’s Index, and PLS−SEM, the spatiotemporal evolution and driving factors of NPP were explored. The results show that: (1) From 2001 to 2020, NPP in Shandong showed an overall increasing trend, rising from 254.96 to 322.49 g C·m⁻²/year. This shift was accompanied by a gradual eastward movement of the NPP centroid, indicating significant spatial changes in vegetation productivity. (2) Regionally, 47.9% of Shandong experienced significant NPP improvement, 27.6% saw slight improvement, and 20.1% exhibited slight degradation, highlighting notable spatial heterogeneity. (3) Driver analysis showed that climatic factors positively influenced NPP across all four periods (2005, 2010, 2015, 2020), with the strongest impact in 2015 (coefficient = 0.643). Topographic factors such as elevation and slope also had positive effects, peaking at 0.304 in 2015. In contrast, human activities, especially GDP and nighttime light intensity, negatively impacted NPP, with the strongest negative effect in 2010 (coefficient = −0.567). These findings provide valuable scientific evidence for ecosystem management in Shandong Province and offer key insights for ecological restoration and sustainable development strategies at the national level. Full article

The intensification of agriculture over the past 80 years has led to significant changes in farm management, resulting in the creation of large-scale fields and the elimination of ecological structural elements. The loss of these areas has dramatically affected natural communities. This study aimed to test whether the implementation of floral margins generates significant differences in insect abundance over time. The study was carried out on an intensive vegetable farm in Spain over a ten-year period (2013–2022) where a floral margin was sown and maintained over the years. The results showed a clear linear increase in insect individuals, with a total increase of 403.33% from 2013 to 2022. The number of species increased by 138.80% overall, with most growth occurring in the first three years before stabilising (0.63% increase from 2016 to 2022). The analysis of community structure demonstrates a gradual evolution in the insect population dynamics aligned significantly with both log-series and log-normal distributions (p-value > 0.05). This long-term study demonstrates that floral margins are an essential tool for fostering insect biodiversity in intensive agricultural areas. The steady, rather than abrupt, shift in the ecosystem suggests that sustained implementation of floral margins can effectively prevent or reverse insect decline over time. Full article

In semi-arid basins, riparian vegetation is an important part of the river ecosystem. However, with the decrease in river runoff caused by human activities and the continuous changes in climate, riparian vegetation has gradually degraded. To identify the main influencing factors of riparian vegetation changes, we extracted the river flow indicators, climate indicators, and riparian vegetation indicators of a Xiliao River typical section from 1985 to 2020 in spring and summer, and established a random forest model to screen the key driving factors of riparian vegetation. Then, we simulated the response characteristics of riparian vegetation to the key driving factors in spring and summer based on nonlinear equations. The results showed that the contribution of river flow factors to riparian vegetation was higher than that of climate factors. In spring, the key driving factors of riparian vegetation were the average flow in May and the average flow from March to May; in summer, the key driving factors were the average flow in May, the maximum 90-day average flow, and the average flow from March to August. Among them, the average flow in May contributed more than 50% to the indicators of riparian vegetation in both spring and summer. The final conclusion is that in the optimal growth range of plants, increasing the base flow and pulse flow of rivers will promote seed germination and plant growth, but when the river flow exceeds this threshold, vegetation growth will stagnate. The research results improve the existing knowledge of the influencing factors of riparian vegetation in semi-arid basins, and provide a reference for improving the natural growth of riparian vegetation and guiding the ecological protection and restoration of rivers in semi-arid areas. Full article

Analyzing the current trends and causes of carbon storage changes and accurately predicting future land use and carbon storage changes under different climate scenarios is crucial for regional land use decision-making and carbon management. This study focuses on Beijing as its study area and introduces a framework that combines the Markov model, the Patch-based Land Use Simulation (PLUS) model, and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model to assess carbon storage at the sub-district level. This framework allows for a systematic analysis of land use and carbon storage spatiotemporal evolution in Beijing from 2000 to 2020, including the influence of driving factors on carbon storage. Moreover, it enables the simulation and prediction of land use and carbon storage changes in Beijing from 2025 to 2040 under various scenarios. The results show the following: (1) From 2000 to 2020, the overall land use change in Beijing showed a trend of “Significant decrease in cropland area; Forest increase gradually; Shrub and grassland area increase first and then decrease; Decrease and then increase in water; Impervious expands in a large scale”. (2) From 2000 to 2020, the carbon storage in Beijing showed a “decrease-increase” fluctuation, with an overall decrease of 1.3 Tg. In future carbon storage prediction, the ecological protection scenario will contribute to achieving the goals of carbon peak and carbon neutrality. (3) Among the various driving factors, slope has the strongest impact on the overall carbon storage in Beijing, followed by Human Activity Intensity (HAI) and Nighttime Light Data (NTL). In the analysis of carbon storage in the built-up areas, it was found that HAI and DEM (Digital Elevation Model) have the strongest effect, followed by NTL and Fractional Vegetation Cover (FVC). The findings from this study offer valuable insights for the sustainable advancement of ecological conservation and urban development in Beijing. Full article

Evapotranspiration (ET) is a critical process in the interaction between the terrestrial climate system and vegetation. In recent years, ET has undergone significant changes in the Jiziwan region of the Yellow River Basin, primarily due to the implementation of ecological restoration programs and the dual impacts of climate change. As a result, hydrological cycle processes have been profoundly affected, making it crucial to accurately capture trends in ET and its components, as well as to identify the key drivers of these changes. In this study, we first systematically analyzed the dynamic evolution of ET and its components in the Jiziwan of the Yellow River area between 1982 and 2018 from the perspective of land use change. To achieve accurate ET simulations, we introduced a multiple linear regression algorithm and quantitatively evaluated the specific contributions of five climate factors, including precipitation, temperature, wind speed, specific humidity, and radiation, as well as the normalized difference vegetation index (NDVI), a vegetation factor, to ET and its components. On this basis, we explored the combined influence mechanism of climate change and vegetation change on ET in detail. The results revealed that the structure of ET in the Jiziwan of the Yellow River area has changed significantly and that vegetation evapotranspiration has gradually replaced soil evaporation, occupies a dominant position, and has become the main component of ET in this area. Among the many factors affecting ET, the contribution of climate change is the most significant, with an average contribution rate of approximately 59%. Moreover, the influence of human activities on total ET and its components is also high. The factors that had the greatest impact on total ET, soil evaporation, and vegetation transpiration were precipitation, radiation, and the NDVI, respectively. In terms of spatial distribution, the eastern part of Jiziwan was more significantly affected by environmental changes, and the trends of the ET changes were more dramatic. This study not only enhances our scientific understanding of the changes in ET and their driving mechanisms in the Jiziwan area of the Yellow River but also provides a solid scientific foundation for the development of water resource management and ecological restoration strategies in the region. Full article

The forest swamp ecosystem, as a special wetland ecosystem, is a key link in the material cycle and an important carbon sink in the carbon cycle. The global carbon cycle is of great significance, but the impact of forest swamp succession and soil depth on soil active organic matter and nematode community structure and diversity is unclear. This study used the “space instead of time” method to investigate the succession process of forest swamps from grasslands (WC) and shrubs (WG) to forests (WS) in national nature reserves. The results showed that during the forest succession process, the dominant nematode communities in the WC and WG stages were dominated by the genera Apis and Labroidei, while the dominant genera increased in the WS stage. The total abundance of nematodes increased, and the number of groups was ordered WG > WC > WS. The diversity in soil nematode communities according to Shannon–Wiener (H′), Pielou (J), and Trophic diversity (TD) was WS > WG > WC, which is related to vegetation, soil physical and chemical properties, and microbial community structure. The maturity index (MI) was WG > WS > WC. The soil food web was dominated by bacterial channels and had characteristics in forest metabolic activity and regulation ability. At different soil depths, there were significant differences in the community, with species such as the spiny cushioned blade genus being key. The number and group size of nematodes varied from 0–10 cm > 10–20 cm > 20–30 cm. The relative abundance of feeding nematodes changed with depth, while diversity indices such as H′, J, and TD decreased with depth. Ecological function indices such as MI and PPI showed depth variation patterns, while basic indices (BI) and channel indices (CI) showed significant differences. In terms of soil variables, during the forest succession stage, soil organic carbon (SOC), soluble organic nitrogen (DON), easily oxidizable organic carbon (ROC), microbial biomass carbon (MBC), and microbial biomass nitrogen (MBN) showed a gradually increasing trend with WC-WG-WS, while total nitrogen (TN), soluble organic carbon (DOC), soil temperature (ST), and soil moisture (SM) showed opposite changes. There were significant differences in soil ST, SM, and DON values with succession (p < 0.05). At different soil depths, except for DON and ROC, which increased first and then decrease with depth, the values of other physical and chemical factors and active carbon and nitrogen components at depths of 0–10 cm were higher than those at other depths and decreased with depth. An analysis of variance showed significant differences in MBC and MBN values at different soil depths (p < 0.05), which is of great significance for a deeper understanding of the mechanism of soil nematode community construction and its relationship with the environment. Full article

Manganese ore, as an important strategic metal resource for the country, was subject to unreasonable mining practices and outdated smelting technologies in early China, leading to severe ecological damage in mining areas. This study examines the trends in vegetation cover change in the historical manganese mining areas of Yongzhou under the influence of policy, providing technical references for mitigating the ecological impact of these legacy mining areas and offering a basis for adjusting mine restoration policies. This paper takes the manganese mining area in Yongzhou City, Hunan Province as a case study and selects multiple periods of Landsat satellite images from 2000 to 2023. By calculating the Normalized Difference Vegetation Index (NDVI) and the Fractional Vegetation Coverage (FVC), the spatiotemporal changes and driving factors of vegetation coverage in the Yongzhou manganese mining area from 2000 to 2023 were analyzed. The analysis results show that, in terms of time, from 2000 to 2012, the vegetation coverage in the manganese mining area decreased from 0.58 to 0.21, while from 2013 to 2023, it gradually recovered from 0.21 to 0.40. From a spatial perspective, in areas where artificial reclamation was conducted, the vegetation was mainly mildly and moderately degraded, while in areas where no artificial restoration was carried out, significant vegetation degradation was observed. Mining activities were the primary anthropogenic driving force behind the decrease in vegetation coverage, while effective ecological protection projects and proactive policy guidance were the main anthropogenic driving forces behind the increase in vegetation coverage in the mining area. Full article