Search Results (80)

Extreme weather events and rising temperatures pose significant risks, not only in urban areas but also in metropolitan forests, that affect the well-being of the people who visit them. City forests are considered one of the best bets for mitigating high temperatures within civic areas. Such areas modulate microclimates in contemporary cities, offering environmental, social, and economic advantages. Therefore, comprehending the intricate relationships between municipal forests and the climatic changes of various destinations is crucial for attaining healthier and more sustainable city environments for people. In this research, the thermal comfort index (Modified Temperature–Humidity Index (MTHI)) has been analysed using Landsat images of six urban forests in London during July 2022, when the area first experienced record-breaking temperatures of over 40 °C. Our results show a significant growth in the MTHI that goes from 2.5 (slightly hot) under normal conditions to 3.4 (hot) during the heat wave period. This situation intensifies the environmental discomfort for visitors and highlights the necessity to enhance their adaptability to future temperature increases. In turn, it was found that the places most affected by heat waves are those that have grass cover or that have small associated buildings. Conversely, forested regions or those with lakes and/or ponds exhibit lower temperatures, which results in enhanced resilience. These findings are noteworthy in their concentration on one of the UK’s most severe heat waves and illustrate the efficacy of integrating spectral measurements with statistical analyses to formulate customized regional initiatives. Therefore, the results reported will allow the implementation of new planning and adaptation policies such as incorporating thermal comfort into planning processes, improving green and blue amenities, increasing tree densities that are resilient to rising temperatures, and increasing environmental comfort conditions in metropolitan forests. Finally, the applicability of this approach in similar urban contexts is highlighted. Full article

Forest and grass systems are globally significant carbon-sequestering ecosystems, crucial for mitigating climate change and optimizing ecological management. To clarify the research history, major contributing groups, and research hotspots related to carbon sequestration in global forest and grass systems, this study utilizes the core ensemble of the Web of Science database as its data source. Employing bibliometric methodology and software, such as VOSviewer 1.6.20 and CiteSpace 5.7.R1, we analyzed the development of 594 relevant publications from 2010 to 2024, focusing on their developmental lineage, research groups, current research status, and visualizing and analyzing research hotspots and frontiers. The results indicate that the volume of the literature on carbon sequestration in forest and grass systems generally follows the pattern of a logistic growth curve, demonstrating an upward trend from 2010 to 2024. The primary contributors consist of 400 researchers, including Nath, Arun Jyoti, and Ajit, as well as 378 research organizations across 42 countries, including China, the USA, and India. China’s contribution to this field is rapidly increasing, accounting for over 20% of the total articles, with ‘Chinese Acad Sci’ and ‘Univ Chinese Acad Sci’ being the most prominent contributors, together representing 10.45% of the total publications in this field. The 179 journals, including Agroforestry Systems and Forests, serve as a significant platform for academic exchange in the development of this field. The predominant research directions are found in the areas of ‘Environmental Sciences & Ecology’ and ‘Agriculture’, which collectively account for over 50% of the publications. Additionally, research focused on ‘Sequestration’ is increasingly examining the relationship between carbon sequestration in forest and grassland systems and factors such as climate change, ecosystem productivity, and biodiversity. The keyword clusters ‘#0 ferralsol’ and ‘#4 forest ecosystem’ have consistently represented important research directions throughout this period. A total of 21 keywords were identified, with ‘land use change’ exhibiting the highest intensity at 4.4524. Future research should not only prioritize the integration of the impacts of global climate change but also enhance collaboration among authors and institutions. Furthermore, it is essential to promote multidisciplinary and cross-regional collaborative innovations by leveraging emerging technologies such as AI and genetic engineering. Full article

Water scarcity is a growing global issue, especially in arid and semi-arid rangelands, primarily due to climate change and population growth. Groundwater is a crucial resource for vegetation in these ecosystems, yet its role in supporting plant life is often not fully understood. This review explores the interactions between groundwater and vegetation dynamics in various rangeland types. Groundwater serves as a critical water source that helps sustain plants, but changes in its availability, depth, and quality can significantly impact plant health, biodiversity, and ecosystem stability. Research indicates that groundwater depth affects vegetation types and their distribution, with specific plants thriving at certain groundwater levels. For instance, in grasslands, shallow groundwater can support diverse herbaceous species, while deeper conditions may favor drought-tolerant shrubs and trees. Similarly, in forest ecosystems, extensive root systems access both groundwater and soil moisture, playing a vital role in water regulation. Savanna environments showcase complex interactions, where trees and grasses compete for water, with groundwater potentially benefiting trees during dry seasons. Climate change poses additional challenges by altering rainfall patterns and temperatures, affecting groundwater recharge and availability. As a result, it is crucial to develop effective management strategies that integrate groundwater conservation with vegetation health. Innovative monitoring techniques, including remote sensing, can provide valuable information about groundwater levels and their impact on vegetation, enhancing water resource management. This review emphasizes the importance of understanding groundwater–vegetation interactions to guide sustainable land and water management practices. By enhancing our knowledge of these connections and utilizing advanced technologies, we can promote ecosystem resilience, secure water resources, and support biodiversity in rangeland systems. Collaborative efforts among local communities, scientists, and policymakers are essential to address the pressing issues of water scarcity and to ensure the sustainability of vital ecosystems for future generations. Full article

This study investigates the diversity and distribution of root endophyte fungi and bacteria across Festuca and Lolium grasses, including open-grassland and forest species. The species examined include perennials such as Festuca arundinacea, F. gigantea, F. pratensis, Lolium perenne, and L. perenne × F. gigantea hybrids and the annuals L. temulentum and L. multiflorum. A total of 21 fungal species (60 isolates) and 26 bacterial taxa (59 isolates) were recovered in the culture (PDA medium for fungi and LB for bacteria) from the root cuttings of these grasses. Microdochium bolleyi fungi and Bacillus sp. bacteria were the most prevalent endophytes, with each being identified in five of the seven plant species examined. The annuals L. multiflorum and L. temulentum exhibited a higher abundance of endophytes than that in their perennial relatives, suggesting the benefits of microbial associations in supporting their short life cycles. The woodland F. gigantea demonstrated the highest fungal endophyte diversity, with six species identified. In contrast, the open-grassland perennials F. arundinacea, F. pratensis, and L. perenne hosted only one to two species. Two Basidiomycota, Coprinellus disseminatus and Sistotrema brinkmannii, were exclusively obtained from the roots of the forest grass F. gigantea. Notably, the open-grassland perennial F. arundinacea exhibited the highest bacterial diversity, with nine species present. However, it showed the lowest fungal diversity, with only one species detected. Overall, our study reveals distinct patterns of fungal and bacterial endophyte diversity in the roots of Festuca and Lolium grasses, with variations linked to host species, growth type traits, and ecological adaptations. Among the root-derived endophytes isolated, several fungi and bacteria are potential candidates for plant growth promotion and biocontrol. Therefore, the findings of this study provide potential implications for improved grassland management and crop breeding strategies aimed at specific climate and/or soil conditions. Full article

Climate change and human activities have significantly impacted the long-term growth of vegetation, thereby altering the ecosystem’s response mechanisms. The Yellow River Water Conservation Area (YRWCA) is a critical ecological functional zone in China. Since 1982, the vegetation in the YRWCA has changed significantly, and the primary drivers of vegetation which changed before and after 2000 were identified as climate change and human activities, respectively. However, the extent to which different drivers contribute to the vegetation dynamics of the YRWCA remains uncertain. In this study, we introduced a modified deep Convolutional Long Short-Term Memory (ConvLSTM) model to quantify the contributions of climate change and human activities to vegetation change while considering the spatiotemporal heterogeneity. We identified areas with minimal human activity before 2000 using the residual trend method, and used the regional data from these areas to train the model. Subsequently, we applied the trained deep ConvLSTM model to perform an attribution analysis after 2000. The results show that the deep ConvLSTM effectively captures the impacts of climate change on vegetation growth and outperforms the widely used Random Forest model (RF). Despite the fact that the input data of RF were optimized, ConvLSTM still distinctly outperformed RF, achieving R², MAE, and RMSE values of 0.99, 0.013, and 0.018, respectively, compared to RF’s corresponding values of 0.94, 0.038, and 0.045. Since 2000, the regional normalized difference vegetation index (NDVI) has shown a broad increasing trend, particularly in dryland, primarily induced by human activities from 2006 to 2015. Furthermore, an analysis of changes in regional land use, particularly in drylands, revealed that the highest magnitude of conversion of farmland back to forest or grass was recorded from 2000 to 2005. However, the most significant contributions from human activities occurred from 2006 to 2015, indicating a time lag in vegetation recovery from these ecological programs. The attribution results provide valuable insights for the implementation of ecological programs, and the introduced deep ConvLSTM proves the suitability of deep learning models that capture spatiotemporal features in vegetation growth simulations, allowing for broader applications. Full article

Clarifying the complex relationships among ecosystem services (ESs) and their driving mechanisms is essential for effective ecosystem management and enhancing human welfare. Nonetheless, the current research on these issues still remains limited; therefore, further theoretical exploration is required. This study aims to quantitatively illustrate the trade-off strength of ESs and investigate the spatiotemporal heterogeneity connections between these relationships and various anthropogenic and natural factors in Baiyangdian basin, China, integrating InVEST, RMSE, geographical detector and MGWR methods. From 2000 to 2020, the total water yield (WY) and nutrient export (NE) increased, while the total carbon storage (CS) and habitat quality (HQ) decreased slightly. The trade-offs of ESs showed spatiotemporal heterogeneity. The most serious trade-off occurred between regulating services (CS and NE) and supporting services (HQ) in 2000, which was mainly distributed in the densely forested and grassed western and northern regions of the basin. The trade-off intensities of half of the pairwise ESs in 2020 increased, with the strengthened areas mainly located in the southeast of the watershed where built-up lands are concentrated. Various factors dominated the trade-offs among ESs, with the interactive effects of multiple drivers being more significant than those of individual factors. Land use type, vegetation cover and precipitation have the most pronounced effect on the trade-offs among ESs. The findings of this study may suggest and advocate for spatial ecological strategies to enhance the integrated and holistic advancement of various ESs and also serve as a reference for regional ecosystem governance and the attainment of sustainable growth. Full article

Soil aggregation, an important indicator of soil restoration in degraded ecosystems, is a fundamental unit of soil structure. However, research on the influence of grass–shrub composites on the distribution of >0.25 mm soil water-stable aggregates (macroaggregates) is scarce. Therefore, this study focuses on the hill and gully region of the Loess Plateau, where vegetation has been well restored since the return of farmland to forests and grasslands. The study investigated the root and macroaggregate distribution characteristics and interrelationships of three widely distributed mixed vegetation types of Caragana korshinskii and Agropyron cristatum (C-AC), C. korshinskii and Bothriochloa ischaemum (C-BI), and C. korshinskii and Artemisia gmelinii (C-AG) in this area. The results indicate that soil macroaggregates decrease with increasing depth. Due to the spatial differences in the distribution of shrub root, the content of macroaggregates at 50 cm from the shrub base was higher than that at the shrub base, with an increase of 25.98%–34.27% in different vegetation associations. In this study, the root length density and root diameter better reflected the influence of roots on the distribution of macroaggregates, and the product of the two had a good power function relationship with the content of macroaggregates (R² ≥ 0.82, p < 0.01). Grey correlation analysis showed that the influence of root length density on the distribution of large aggregates was greater than that of root diameter. The content of macroaggregates in the vegetation association of taproot herbaceous plants and shrubs was higher than that of fibrous root herbaceous plants. The average soil macroaggregate content in the C-AG was 15.79%–248.6% higher than that in the C-BI and C-AC. In this study, the spatial distribution differences in root caused by shrub growth were the main reason for the spatial heterogeneity of soil macroaggregate content distribution. The improvement ability of soil macroaggregates was higher in the combination of taproot herbaceous plants and shrubs than in the combination of fibrous root herbaceous plants and shrubs. The results of this study can, to some extent, reveal the influence and mechanisms of plant roots on soil aggregates in grass–shrub vegetation association. Full article

Plant ecological strategies are essential for assessing habitat stress and disturbance and evaluating community productivity. These strategies provide theoretical frameworks for maintaining the natural state of vegetation and enhancing productivity. The functional traits of leaves reflect a plant’s responses to environmental changes and contribute to understanding ecosystem stability, providing a basis for species diversity maintenance and effective conservation efforts. The Wuyishan National Park, a biodiversity hotspot in China, is a focal point for ecological research. Its evergreen, broad-leaved forest, the zonal vegetation of Mt. Wuyi, underpins plant diversity protection in the region. This study investigates the CSR (competitor, stress-tolerator, ruderal) strategy of 126 species on Wuyi Mountain to elucidate prevalent ecological strategies. The main ecological strategy of plants in the study area is the CS (competitor, stress-tolerator) strategy. The species exhibit nine categories. The most abundant ecological strategy is S/CS (plants from Fagaceae), accounting for 38%, followed by S/CSR at 23% (plants from Theaceae), CS at 20% (plants from Fagaceae and Theaceae), and the remaining strategies collectively at 19%. The different growth habit categories showed variations in the CSR strategies. The trees clustered around a CS median strategy, with no R-selected trees observed. Shrubs and lianas centered around an S/CSR strategy, while grasses and understory shrubs clustered around CS/CSR. Redundancy analysis results indicate that leaf functional traits are primarily influenced by temperature, suggesting that temperature is the key environmental factor driving the differentiation of plant functional traits. This study provides insights into the ecological strategies of plant species in the Mt. Wuyi region, highlighting the importance of considering both biotic and abiotic factors in maintaining biodiversity and ecosystem stability. Full article

To optimize growth and management, precision agriculture relies on a deep understanding of agricultural dynamics, particularly crop water status analysis. Leveraging unmanned aerial vehicles, we can efficiently acquire high-resolution spatiotemporal samples by utilizing remote sensors. However, non-linear relationships among data features, localized within specific subgroups, frequently emerge in agricultural data. Interpreting these complex patterns requires sophisticated analysis due to the presence of noise, high variability, and non-stationarity behavior in the collected samples. Here, we introduce Local Biplot, a methodological framework tailored for discerning meaningful data patterns in non-stationary contexts for precision agriculture. Local Biplot relies on the well-known uniform manifold approximation and projection method, such as UMAP, and local affine transformations to codify non-stationary and non-linear data patterns while maintaining interpretability. This lets us find important clusters for transformation and projection within a single global axis pair. Hence, our framework encompasses variable and observational contributions within individual clusters. At the same time, we provide a relevance analysis strategy to help explain why those clusters exist, facilitating the understanding of data dynamics while favoring interpretability. We demonstrated our method’s capabilities through experiments on both synthetic and real-world datasets, covering scenarios involving grass and rice crops. Moreover, we use random forest and linear regression models to predict water status variables from our Local Biplot-based feature ranking and clusters. Our findings revealed enhanced clustering and prediction capability while emphasizing the importance of input features in precision agriculture. As a result, Local Biplot is a useful tool to visualize, analyze, and compare the intricate underlying patterns and internal structures of complex agricultural datasets. Full article

The deadwood contributes to an increase in soil heterogeneity due to the changing the microrelief (by the formation of windthrow-soil complexes), as well as changes in physical and chemical characteristics of decaying wood directly during xylolysis. We hypothesized that fallen logs as an element of microrelief influence the species composition and cover structure of vascular plants. We studied the influence of Picea abies (L.) Karst fallen logs of moderate and advanced decay stages on the horizontal distribution and heterogeneity of vascular plant cover in different microsite types (small boreal grass type, blueberry type, small boreal grass-blueberry type, herbs, and blueberry type) in old-growth middle taiga spruce forest in the Kivach State Nature Reserve (Republic of Karelia, Russia). The fallen deadwood acts as a factor of heterogeneity, causing reversible changes in the homogeneity of the original plant cover. The decaying logs influence the horizontal distribution of small herbs by changing the occurrence and density of shoots of Oxalis acetosella L., Maianthemum bifolium (L.) F.W. Schmidt, Vaccinium myrtillus L., and Vaccinium vitis-idaea L., as well as the occurrence of Luzula pilosa (L.) Willd. and Calamagrostis arundinacea (L.) Roth. Its impact on the heterogeneity parameters can be traced up to 20 cm from the log. The differences in vascular plant cover between fallen logs and the surrounding forest floor depend on the soil conditions of the microsite. The heterogeneity of conditions created by the logs smoothed out with increasing decay class, resulting in decreasing differences in the heterogeneity parameters of vascular plant cover between deadwood and forest floor. The changes in the homogeneity of the initial vascular plant cover by deadwood and the gradual smoothing of heterogeneity between the logs and the forest floor in rich and poor conditions have different, mainly opposite, trends. Finally, the structure of the vegetation cover reaches a state that is typical of particular growth conditions beyond deadwood. Full article

The establishment of protective forests plays a crucial role in mitigating soil erosion on slopes within hilly and gully regions. However, in practical applications, the configuration of protective forests on slopes is intricate and diverse, and the suitability and rationality of different configuration patterns for various slope sections have not been thoroughly investigated. This study focuses on a 40-year-old artificial protective forest, examining 16 different configuration patterns on the top, middle, and lower slopes. It compares the growth conditions, community structure stability, and characteristics of the saturated soil’s hydraulic conductivity. The findings indicate that the top slope should be identified as a critical area for slope protection. The optimal configuration for this area is the “tree + grass” pattern with a spacing of 5 m × 5 m, which promotes the optimal growth of tree species and effectively reduces the surface runoff of gravel particles ranging from 1 cm to 3 cm in diameter. On the middle slope, the “tree + shrub + grass” structure proves effective in slowing down the erosive force of slope runoff. The recommended spacing for trees is 5 m × 6 m, and for understory shrubs, it is 1 m × 6 m. This configuration pattern results in the most stable structure for the plant community and maximizes the water conservation potential of forest litter. By analyzing the characteristics of the saturated soil’s hydraulic conductivity, we find that the complexity of the plant configuration on the lower slopes is correlated with a greater coefficient of variation in the saturated soil’s hydraulic conductivity. Nevertheless, there is no significant difference in the average soil saturated hydraulic conductivity per unit area between the different configuration patterns. Consequently, the lower slope can rely on the natural recovery of herbaceous plants. The results of this research contribute valuable scientific and technical insights to the management of soil erosion in hilly and gully areas, both in China and around the world. Full article

Flash droughts tend to cause severe damage to agriculture due to their characteristics of sudden onset and rapid intensification. Early detection of the response of vegetation to flash droughts is of utmost importance in mitigating the effects of flash droughts, as it can provide a scientific basis for establishing an early warning system. The commonly used method of determining the response time of vegetation to flash drought, based on the response time index or the correlation between the precipitation anomaly and vegetation growth anomaly, leads to the late detection of irreversible drought effects on vegetation, which may not be sufficient for use in analyzing the response of vegetation to flash drought for early earning. The evapotranspiration-based (ET-based) drought indices are an effective indicator for identifying and monitoring flash drought. This study proposes a novel approach that applies cross-spectral analysis to an ET-based drought index, i.e., Evaporative Stress Anomaly Index (ESAI), as the forcing and a vegetation-based drought index, i.e., Normalized Vegetation Anomaly Index (NVAI), as the response, both from medium-resolution remote sensing data, to estimate the time lag of the response of vegetation vitality status to flash drought. An experiment on the novel method was carried out in North China during March–September for the period of 2001–2020 using remote sensing products at 1 km spatial resolution. The results show that the average time lag of the response of vegetation to water availability during flash droughts estimated by the cross-spectral analysis over North China in 2001–2020 was 5.9 days, which is shorter than the results measured by the widely used response time index (26.5 days). The main difference between the phase lag from the cross-spectral analysis method and the response time from the response time index method lies in the fundamental processes behind the definitions of the vegetation response in the two methods, i.e., a subtle and dynamic fluctuation signature in the response signal (vegetation-based drought index) that correlates with the fluctuation in the forcing signal (ET-based drought index) versus an irreversible impact indicated by a negative NDVI anomaly. The time lag of the response of vegetation to flash droughts varied with vegetation types and irrigation conditions. The average time lag for rainfed cropland, irrigated cropland, grassland, and forest in North China was 5.4, 5.8, 6.1, and 6.9 days, respectively. Forests have a longer response time to flash droughts than grasses and crops due to their deeper root systems, and irrigation can mitigate the impacts of flash droughts. Our method, based on cross-spectral analysis and the ET-based drought index, is innovative and can provide an earlier warning of impending drought impacts, rather than waiting for the irreversible impacts to occur. The information detected at an earlier stage of flash droughts can help decision makers in developing more effective and timely strategies to mitigate the impact of flash droughts on ecosystems. Full article

Forest ecosystems are essential to the global carbon cycle because they are the biggest terrestrial carbon reserves. In the management of forests, thinning is a commonly employed strategy, impacting the respiration and biomass loss of trees, thereby modifying forest carbon dynamics. However, there is a lack of scientific research to confirm the impacts of thinning intensities on carbon storage in trees, soil layers, shrubs, and ground vegetation layers as well as its impact on wood production and growth rate. The goal of this study was to find the optimal thinning levels for increasing carbon sequestration during the growth stage of the Korean pine (Pinus koraiensis) middle-aged plantations in Northeast China. In this study, thinning intensity (0, 10, 11, 16, 18, and 22%) affected the carbon storage of trees, tree growth, volume, and, we suspected, soil layer, shrubs, and vegetation (herbs, litter, and grass) also. Specifically, after four years of thinning, the 18% treatment significantly increased total carbon storage, individual organ storage, growth, and tree volume (p < 0.05). These results give us abundant information about how thinning affects the dynamics of carbon storage, wood production, and the interactions between soil and plants in P. koraiensis plantations, contributing to multi-objective management strategies for optimizing carbon sequestration, wood production, and ecosystem health. Full article

At the southeastern periphery of the Tibetan Plateau, the subalpine ecosystem hosts grasses as some of the most substantial species. However, the community and function of arbuscular mycorrhizal fungi (AMF) around the rhizospheres of grasses in the subalpine zone are still poorly understood. In the present study, 28 soils and 11 species of dominant grasses collected from four microhabitats (shrubland, grassland, woodland, and forest) in the subalpine zone of northwestern Yunnan, China, were used to investigate the AMF community by Illumina MiSeq high-throughput sequencing technology as well as nutrient contents. Among the four microhabitats, the maximum soil nutrient levels around the rhizospheres of grasses were observed in woodland. The nitrogen, phosphorus, and potassium concentrations in Dactylis glomerata shoots were significantly higher than those in the other 10 grass species. The AMF diversity of grassland in summer was substantially greater than that of the other three microhabitats (p < 0.05). Discrepancies were observed within a given plant species across microhabitats; for example, in summer, the nitrogen concentration in the shoot of Iris tectorum in woodland was significantly higher than that in both forest and shrubland (p < 0.05). A total of eight genera were detected in the AMF communities, which were dominated by Glomus, with a relative abundance of 45.4%–94.4% in summer and 60.5%–84.3% in winter. Moreover, the abundance of Glomus was significantly positively correlated with the content of alkali-hydrolyzable nitrogen in soil and nitrogen in grasses according to the Mantel test. As a critical nutrient element in soil, nitrogen is beneficial for plant growth. Thus, these results provide a better understanding of the resilience of soil AMF community and the ecological adaptability of grasses in the subalpine ecosystems of northwestern Yunnan. Full article

Aboveground biomass (AGB) is a key indicator of the physiological status and productivity of grasslands, and its accurate estimation is essential for understanding regional carbon cycles. In this study, we developed a suitable AGB model for grasslands in Xinjiang based on the random forest algorithm, using AGB observation data, remote sensing vegetation indices, and meteorological data. We estimated the grassland AGB from 2000 to 2022, analyzed its spatiotemporal changes, and explored its response to climatic factors. The results showed that (1) the model was reliable (R² = 0.55, RMSE = 64.33 g·m⁻²) and accurately estimated the AGB of grassland in Xinjiang; (2) the spatial distribution of grassland AGB in Xinjiang showed high levels in the northwest and low values in the southeast. AGB showed a growing trend in most areas, with a share of 61.19%. Among these areas, lowland meadows showed the fastest growth, with an average annual increment of 0.65 g·m⁻²·a⁻¹; and (3) Xinjiang’s climate exhibited characteristics of warm humidification, and grassland AGB showed a higher correlation with precipitation than temperature. Developing remote sensing models based on random forest algorithms proves an effective approach for estimating AGB, providing fundamental data for maintaining the balance between grass and livestock and for the sustainable use and conservation of grassland resources in Xinjiang, China. Full article