Grassland Research Articles

Phosphorus Dynamics in Managed and Natural Soils: SEM-PLS Analysis of Vaccinium, Forest, and Grassland Ecosystems

Phosphorus (P) availability in soils is often constrained by its accumulation in non-labile phosphorus (NLP) forms, limiting its accessibility to plants. This study examines how soil physical properties, chemical characteristics, and climatic conditions influence phosphorus fractionation and the transformation of NLP into plant-available labile phosphorus (LP). Utilizing global structural equation modeling (SEM), we found that silt content enhances organic phosphorus fractions, including NaHCO3-Po and NaOH-Po. In the upper 30 cm of soil, pH decreases the availability of NaHCO3-Po and NaOH-Po while stabilizing NLP, highlighting its essential role in phosphorus cycling under acidic conditions. In deeper soil layers, pH facilitates phosphorus mobilization from NLP pools, with effects varying across fractions. Long-term studies on Japanese Vaccinium soils reveal that pH and electrical conductivity (EC) management significantly promote NLP-to-LP conversion, primarily through NaOH-Po, thereby improving phosphorus use efficiency. These findings underscore the critical importance of prioritizing chemical property management over physical modifications to optimize nutrient cycling, preserve soil fertility, and reduce reliance on external phosphorus inputs in agricultural systems. Our study emphasizes the need for integrated approaches to achieve sustainable phosphorus management in both natural and managed ecosystems.

Declining Water Constraints at the Cost of Water Storage for Ecosystem on China's Loess Plateau.

Surface greenness alters regional water storage by regulating hydrological processes, thereby modulating water constraints on ecosystem functions and feeding back sustainability. In semi-arid regions, excessive revegetation may exacerbate regional water resource depletion, intensify water limitations on ecosystems, and threaten long-term sustainability. However, these changes have not been adequately assessed. In this study, we employed the Ecosystem Limitation Index (ELI) to differentiate water and energy limitations on ecosystem function. We analyzed its changes and relationship with water storage across China's semi-arid Loess Plateau, where strict revegetation has been implemented since the 2000s. Our results showed a substantial decline in ELI at the plateau scale, suggesting a significant reduction in water limitation. Whereas, ELI increased notably in the eastern and southwestern forest lands, covering 28.4% of the plateau, in contrast to the northwestern grass and desert lands (26.2%), where ELI decreased significantly. The increase in terrestrial water storage (TWS), especially groundwater storage (GWS) availability, is responsible for the declining water constraints on the ecosystem, albeit TWS and GWS substantially reduced with an annual rate of -0.76 cm and -0.49 cm in water thickness, respectively. Spatial trend analysis and Convergence Cross Mapping (CCM) causal detection revealed that the low surface greening rate before 2000 contributed to the regain in TWS and GWS, while the accelerated greening after 2000 has enhanced the shrinkage of regional TWS and GWS. Our findings suggested that the high greening rate of the Loess Plateau over the past decades was potentially achieved at the expense of regional water storage, underscoring the urgent need for water-saving strategies in future revegetation efforts to ensure ecosystem sustainability.

Urbanized lands degrade surrounding grasslands by deteriorating the interactions between plants and soil microbiome

To mitigate overgrazing on grasslands, towns were constructed in some pastoral regions of China to relocate pastoralists. Nevertheless, whether and how the urbanized lands impact the surrounding grassland ecosystem remains unclear. We assessed the impacts of urbanized lands on the plant and soil interactions within the surrounding grasslands in order to ensure an eco-sustainable pastoralist relocation. The town with 1 km radius was selected as urbanization sample and a grassland with 1 km radius was selected as nature grassland sample. Plants and soil were investigated in nature grassland (NG), and areas 1 km (T-1 km), 2 km (T-2 km), and 3 km (T-3 km) from the center of the town. In T-1 km and T-2 km, compared to the NG, plant diversity, the abundance of dominant plant species, the abundance of soil wood saprotroph fungi, soil water content (SWC), and total organic carbon (TOC) decreased, while soil plant pathogen fungi, soil pH, and total phosphatase (TP) increased. Conversely, no such changes were observed in T-3 km. The results of Mantel test and Partial least squares path model suggest that the decrease in soil TOC and SWC, along with the increase in pH and TP in T-1 km and T-2 km, lead to a decline in wood saprotroph fungi and an increase in plant pathogen fungi, ultimately resulting in reductions in plant diversity and the abundance of dominant plant species. These results indicate that towns in pastoral areas can lead to surrounding grassland degradation by deteriorating the plant–soil interactions.

Variation characteristics and influencing mechanisms of CO2 flux from grassland ecosystem in the Central Tianshan Mountains, China

Variation characteristics and influencing mechanisms of CO2 flux from grassland ecosystem in the Central Tianshan Mountains, China

Spatio-temporal dynamics of grassland ecosystem services and the segmentation effects of their drivers: A case in South China Karst

Spatio-temporal dynamics of grassland ecosystem services and the segmentation effects of their drivers: A case in South China Karst

Shrubs alter microbial community dynamics across various soil depths in alpine grassland ecosystems on the eastern Tibetan Plateau

Shrubs alter microbial community dynamics across various soil depths in alpine grassland ecosystems on the eastern Tibetan Plateau

THE MORPHO-PRODUCTIVE CHARACTERIZATION OF THE PERENNIAL RYEGRASS GERMPLASM IN THE WESTERN PART OF ROMANIA

Perennial ryegrass-dominated grassland ecosystems are typically stable in terms of resilience, as persistence is an important evaluation criterion in perennial breeding programs. The aim of the study was to analyze the morpho-productive characterization of the germplasm collection of the perennial ryegrass collection to identify local provenances that exceed in phenotypic expression under current cultivation conditions in the western part of Romania. For that, numerous observations were made regarding the dynamics of the following traits: plant height (cm), number of leaves per plant, leaf width (cm), leaf length (cm) and the number of shoots. The biological material was made up of local provenances of Lolium perenne collected from three geographical areas: the Almaju Mountains, the Mehedinți Plateau and the Blahniței Plain. From the analysis of the correlation relationships highlighted between the five morpho-productive traits investigated, it can be observed the determining role of the height of the perennial ryegrass plant in the dimensioning and phenotypic expression of the traits. Thus, the height of the plant is in a direct interdependence relationship with traits such as the number of leaves per plant and the length and width of the leaf. These interdependencies are subject to the bio-morphological composition of the grass species in which the stem comprises nodes and internodes, and a leaf leaves from each node. In other words, the taller the plant is and the more nodes it has, the more leaves it has. The distinctly significant correlation relationship between the number of leaves per plant and the number of shoots where the growth in the form of a bush in perennial ryegrass explains this high correlation is also highlighted. The study provides a detailed analysis of linear regressions for different morpho-productive traits plant height (cm), number of leaves per plant, leaf width (cm), leaf length (cm) and number of shoots, with the aim of understanding how the collected genotypes influence these traits.

Root carbon inputs outweigh litter in shaping grassland soil microbiomes and ecosystem multifunctionality

Global change has the potential to alter soil carbon (C) inputs from above- and below-ground sources, with subsequent influences on soil microbial communities and ecological functions. Using data from a 13-year field experiment in a semi-arid grassland, we investigated the effects of litter manipulations and plant removal on soil microbiomes and ecosystem multifunctionality (EMF). Litter addition did not affect soil microbial α-diversity whereas litter removal reduced bacterial and fungal α-diversity due to decreased C substrate supply and soil moisture. By contrast, plant removal led to larger declines in bacterial and fungal α-diversity, lower microbial network stability and complexity. EMF was enhanced by litter addition but largely reduced by plant removal, primarily attributed to the loss of fungal diversity. Our findings underscore the importance of C inputs in shaping soil microbiomes and highlight the dominant role of plant root-derived C inputs in maintaining ecological functions under global change scenarios.

Microbial functional genes play crucial roles in enhancing soil nutrient availability of halophyte rhizospheres in salinized grasslands.

Land degradation due to salinization threatens ecosystem health. Phytoremediation, facilitated by functional microorganisms, has gained attention for improving saline-alkali soils. However, the relationship between the functional potential of rhizosphere microbes involved in multi-element cycling and soil nutrient pools remain unclear. This study focused on the changes in functional genes related to carbon (C), nitrogen (N), and phosphorus (P) cycling in the rhizospheres of various halophytes and bulk soil in the grassland ecosystem of Chaka Salt Lake, Qinghai Province, China. Our evaluation of plant and soil characteristics revealed that halophyte growth increased soil hydrolase activity and nutrient levels, particularly available N. Significant differences were observed in foliage and root nutrients, rhizosphere soil properties, and microbial functional gene composition among plant species. Halophytes significantly altered the abundance of genes involved in C fixation (Calvin and DC/4-HB cycles), C degradation (starch, hemicellulose, cellulose, and pectin degradation), dissimilatory nitrate reduction (nirB), ammonification (ureC), organic P mineralization (phoA and ugpQ), P transport (phnE), and inorganic P dissolution (ppk1). C, N, and P cycling processes were closely related to soil N nutrients, available nutrient ratios, and C/N-cycling enzyme activities. Partial least squares path modeling (PLS-PM) analysis showed that microbial functional genes were directly associated with soil nutrient availability, with soil and plant variables indirectly affecting nutrient pools through the regulation of these genes. These findings enhance our understanding of the biochemical cycling in halophyte rhizospheres and highlight the role of microbial functional genes in saline-alkali soil restoration.

An Evaluation of the Performance of Remote Sensing Indices as an Indication of Spatial Variability and Vegetation Diversity in Alpine Grassland

Vegetation diversity is a crucial indicator for evaluating grassland ecosystems. Remote sensing technology has great potential in assessing grassland vegetation diversity. In this study, the relationship between remote sensing indices and species diversity was investigated at varying spatial and temporal scales in Bayanbulak Grassland National Nature Reserve, China. Spectral variation, defined as the coefficient of variation in vegetation indices, was used as a proxy for species diversity, which was quantified using species diversity indices. The “spectral diversity-species diversity” relationship was validated across diverse spatial scales and between different years using Sentinel-2 images and ground investigation data. This study found that Kendall’s τ coefficients showed the best performance in evaluating the relationship between the coefficient of variation in VIs (CVVIs) and species diversity index. The highest τ value was observed for CVNDVI in 2017 (τ = 0.660, p < 0.01), followed by the Shannon index in 2018 (τ = 0.451, p < 0.01). In addition, CVEVI demonstrated a significant positive correlation with the Shannon-Wiener Index at the 50 m scale (τ = 0.542), and the highest relationship τ between CVNDVI and the Shannon-Wiener Index was observed at the 100 m scale (τ = 0.660). The Shannon-Wiener Index in relation to CVVIs performs better in representing changes in grassland vegetation. Spatial scales and vegetation indices influence the assessment of grassland vegetation diversity. These findings underscore the critical role of remote sensing technology in assessing grassland vegetation diversity across various scales, offering valuable support tools for measuring regional grassland vegetation diversity.

Estimation of the Net Primary Productivity of Grasslands in the Qinghai Tibet Plateau Based on a Machine Learning Model and Sensitivity Analysis to Climate Change

This study applies the Multilayer Perceptron (MLP) and Random Forest (RF) models, utilizing remote sensing and ground-based net primary productivity (NPP) data from 1992 to 2020, along with meteorological data and soil properties, to model the NPP in the alpine grassland and alpine meadow ecosystems of the Qinghai-Tibetan Plateau (TP) and assess their sensitivity to climate change. As a vital ecological barrier, the TP’s grassland ecosystems are critical for understanding the impacts of climate change. However, sensitivity analysis of the NPP in the TP grasslands has been limited, which this study aims to address by focusing on the effects of maximum temperature, solar radiation, and wind speed on the NPP. The results show that the MLP model outperforms the RF model in prediction accuracy (R2 = 0.98, RMSE = 16.24 g C·m−2·a−1, MAE = 9.04 g C·m−2·a−1). NPP responses to climate factors are diverse: linear with temperature and nonlinear with solar radiation and wind speed. Under multi-factor scenarios, the NPP in both alpine meadow and alpine grassland exhibit nonlinear trends, with a higher sensitivity to changes in all three factors than to single- or two-factor changes. Spatial distribution analysis revealed that the NPP in alpine meadows was more sensitive to climate change in the southern regions, while alpine grassland showed greater sensitivity in the central regions. This study, using machine learning models and sensitivity analysis, sheds light on the complex response of the NPP in the TP grasslands to climate change, offering valuable insights for carbon cycle research in cold ecosystems and regional climate adaptation management.

Precipitation in July maximizes total above-ground productivity of the desert steppe in Inner Mongolia, China.

Precipitation distribution during the growing season and interannual precipitation variation may have significant impacts on grassland ecosystem productivity at the site level. To explore the effect of the distribution of precipitation on plant communities in the Inner Mongolian desert steppe dominated by Stipa breviflora, we analyzed monthly precipitation patterns during the growing season (May-October) over the past 60 years (1961-2020) and identified four major precipitation distribution patterns. These included the concentrated precipitation during July (TΛ7), August (TΛ8), and during the early and late growth stages. However, with precipitation being scarce during the boom (TM), the distribution resembled a normal distribution (T∩). Field experiments simulating the four distributions were conducted from May to October 2021. The results showed that the effects of the distribution of precipitation on plant species, diversity, and abundance were not significant; only the Pielou evenness showed a significant effect after July. The total above-ground net primary productivity (ANPP) of TΛ7 was 55.4% higher than those of the other three patterns, whereas the differences among the other three precipitation distributions were not significant. The annual forb Neopallasia pectinate was the primary contributor to the increased ANPP of TΛ7. These results suggest that the S. breviflora desert steppe achieved maximum productivity when the precipitation reached 41.6% of the annual average during July and satisfied the basic plant growth requirements during other months. This study emphasizes the implementation of management measures (irrigation or artificial precipitation) for maximizing forage yield and forecasting the plant composition in desert steppes.

The impact of global change factors on the functional genes of soil nitrogen and methane cycles in grassland ecosystems: a meta-analysis.

Soil functional genes in grasslands are crucial for processes like nitrogen fixation, nitrification, denitrification, methane production, and oxidation, integral to nitrogen and methane cycles. However, the impact of global changes on these genes is not well understood. We reviewed 84 studies to examine the effects of nitrogen addition (N), warming (W), increased precipitation (PPT +), decreased precipitation (PPT-), and elevated CO2 (eCO2) on these functional genes. For nitrogen cycling, global changes mainly boost genes involved in nitrification but reduce those in denitrification, with nirK being the most sensitive. Most nitrogen fixation-related genes did not show a significant response. Among single factors, N and PPT + have the most significant effects. The impact of global changes on nitrogen cycling genes is largely additive, and their interaction with N is particularly influential. For methane cycling, global changes notably affect mcrA, while only PPT + significantly reduces pmoA. The magnitude and duration of global change treatments are more critical than the treatment form for nitrogen cycling genes. For methane cycling, the form and intensity of nitrogen addition, along with treatment duration, affect pmoA abundance. We also identified a competitive relationship between methane oxidation and nitrification and a complex coupling with denitrification. This study provides new insights into microbial responses in nitrogen and methane cycling under global changes, with significant implications for experimental design and management strategies in grassland ecosystems.

Changes in reproduction mediate the effects of climate change and grassland management on plant population dynamics.

Climate change is one of the largest threats to grassland plant species, which can be modified by land management. Although climate change and land management are expected to separately and interactively influence plant demography, this has been rarely considered in climate change experiments. We used a large-scale experiment in central Germany to quantify the effects of grassland management, climate change, and their joint effect on the demography and population growth rate of 11 plant species all native to this temperate grassland ecosystem. We parameterized integral projection models with five years of demographic data to project population growth rate. We hypothesized that plant populations perform better in the ambient than in the future climate treatment that creates hotter and drier summer conditions. Further, we hypothesized that plant performance interactively responds to climate and land management in a species-specific manner based on the drought, mowing, and grazing tolerances as well as the flowering phenology of each species. Due to extreme drought events, over half of our study species went quasi extinct, which highlights how extreme climate events can influence long-term experimental results. We found no consistent support for our expectation that plants perform better in ambient compared with future climate conditions. However, several species showed interactive responses to the treatments, indicating that optimal management strategies for plant performance are expected to shift with climate change. Changes in population growth rates of these species across treatments were mostly due to changes in plant reproduction. Experiments combined with measuring plant demographic responses provide a way to isolate the effects of different drivers on the long-term persistence of species and to identify the demographic vital rates that are critical to manage in the future. Our study suggests that it will become increasingly difficult to maintain species with preferences for moister soil conditions, and that climate and land use can interactively alter demographic responses of the remaining grassland species.

Forecasting of Grasslands Distribution on Mount Zireia Using Ecological Niche Modeling and Future Climatic Scenarios

Grassland ecosystems cover a high percentage of the terrestrial habitats of Earth and support the livelihood and well-being of at least one-fifth of the human population. Climate change and human activities are causing increasing pressure on arid and semi-arid regions. Land use/cover change significantly affects the function and distribution of grasslands, showing diverse patterns across space and time. The study investigated the spatial distribution of grasslands of Mount Zireia (Peloponnesus, Greece) using MaxEnt modeling based on CMIP6 models (CNRM-CM6 and CCMCC-ESM2) and two Shared Socioeconomic Pathways (SSP 245 and SSP 585) covering the period of 1970–2100. The results from the current (1970–2000) and several future periods (2020–2100) revealed that the MaxEnt model provided highly accurate forecasts. The grassland distribution was found to be significantly impacted by climate change, with impacts varying by period, scenario, and climate model used. In particular, the CNRM-CM6-1 model forecasts a substantial increase in grasslands at higher elevations up to 2100 m asl. The research emphasizes the importance of exploring the combined impacts of climate change and grazing intensity on land use and cover changes in mountainous grasslands.

Effect of Warming on Soil Fungal Community Along Altitude Gradients in a Subalpine Meadow.

The subalpine grassland ecosystem is sensitive to climatic changes. Previous studies investigated the effects of warming on grassland ecosystems at a single altitude, with little information about the response of subalpine meadows to warming along altitude gradients. This study aimed to evaluate the effects of warming on aboveground grass, belowground soil properties, and fungal community along altitude gradients in the subalpine meadow of Mount Wutai using the high-throughput sequencing method. Warming reduced the restriction of low temperatures on the growth of subalpine grass, resulting in increasing grass biomass, community height, and coverage. More grass biomass led to higher soil organic carbon resources, which primarily affected fungal community composition following warming. Warming might induce more stochastic processes of fungal community assembly, increasing fungal diversity at low altitudes. In contrast, warming triggered more deterministic processes to decrease fungal diversity at medium and high altitudes. Warming might improve the efficiency of soil nutrient cycling and organic matter turnover by increasing the relative abundance of soil saprotrophs and improving fungal network connectivity. The relative abundance of certain grass pathogens significantly increased following warming, thereby posing potential risks to the sustainability and stability of subalpine meadow ecosystems. Overall, this study comprehensively evaluated the response of the subalpine meadow ecosystems to warming along altitude gradients, clarifying that warming changes soil fungal community composition at different altitudes. The long-term monitoring of pathogen-related shifts should be conducted in subalpine meadow ecosystem following warming. This study provided significant scientific insights into the impact of future climatic changes on subalpine ecosystems.

Analysis of Spatiotemporal Variation Characteristics and Influencing Factors of Grassland Vegetation Coverage in the Qinghai–Tibet Plateau from 2000 to 2023 Based on MODIS Data

Changes in grassland fractional vegetation coverage (FVC) are important indicators of global climate change. Due to the unique characteristics of the Tibetan Plateau ecosystem, variations in grassland coverage are crucial to its ecological stability. This study utilizes the Google Earth Engine (GEE) platform to retrieve long-term MODIS data and analyzes the spatiotemporal distribution of grassland FVC across the Qinghai–Tibet Plateau (QTP) over 24 years (2000–2023). The grassland growth index (GI) is used to evaluate the annual grassland growth at the pixel level. GI is an important indicator for measuring grassland growth status, which can effectively measure the changes in grassland growth in each year relative to the base year. FVC trends are monitored using Sen-Mann-Kendall slope estimation, the coefficient of variation, and the Hurst exponent. Geographic detectors and partial correlation analysis are then applied to explore the contribution rates of key driving factors to FVC. The results show: (1) From 2000 to 2023, FVC exhibited an overall upward trend, with an annual growth rate of 0.0881%. The distribution of FVC on the QTP follows a pattern of higher values in the east and lower values in the west; (2) Over the past 24 years, 54.05% of the total grassland area has shown a significant increase, 23.88% has remained stable, and only a small portion has shown a significant decrease. The overall trend is expected to continue with minimal variability, covering 82.36% of the total grassland area. The overall grassland GI suggests a balanced state of growth; (3) precipitation (Pre) and soil moisture (SM) are the main single factors affecting FVC changes in grasslands on the Tibetan Plateau (q = 0.59 and 0.46). In the interaction detection, in addition to the highest interaction between Pre and other factors, the interaction between SM and other factors also showed a significant impact on the changes in FVC of the QTP grassland; partial correlation analysis of hydrothermal factors and FVC of the QTP grassland. It shows that precipitation has a stronger correlation with QTP grassland FVC changes than temperature. This study has enhanced our understanding of grassland vegetation change and its driving factors on the QTP and quantitatively described the relationship between vegetation change and driving factors, which is of great significance for maintaining the sustainable development of grassland ecosystems.

Survival Risk Analysis for Four Endemic Ungulates on Grasslands of the Tibetan Plateau Based on the Grazing Pressure Index

Ungulates are essential for maintaining the health of grassland ecosystems on the Tibetan plateau. Increased livestock grazing has caused competition for food resources, threatening ungulates’ survival. The survival risk of food resources for ungulates can be quantified by the grazing pressure index, which requires accurate grassland carrying capacity. Previous research on the grazing pressure index has rarely taken into account the influence of wild ungulates, mainly due to the lack of precise spatial data on their quantity. In this study, we conducted field investigations to construct high-resolution spatial distributions for the four endemic ungulates on the Tibetan plateau. By factoring in the grazing consumption of these ungulates, we recalculated the grassland carrying capacity to obtain the grazing pressure index, which allowed us to assess the survival risks for each species. The results show: (1) Quantity estimates for Tibetan antelope (Pantholops hodgsonii), Tibetan wild donkey (Equus kiang), Tibetan gazelle (Procapra picticaudata), and wild yak (Bos mutus) of the Tibetan plateau are 24.57 × 104, 17.93 × 104, 7.16 × 104, and 1.88 × 104, respectively; they mainly distributed in the northern and western regions of the Tibetan plateau. (2) The grassland carrying capacity of the Tibetan plateau is 69.98 million sheep units, with ungulate grazing accounting for 5% of forage utilization. Alpine meadow and alpine steppe exhibit the highest grassland carrying capacity. (3) The grazing pressure index on the Tibetan plateau grasslands is 2.23, indicating a heightened grazing pressure in the southern and eastern regions. (4) The habitat survival risk analysis indicates that the high survival risk (the grazing pressure index exceeds 1.2) areas for the four ungulate species account for the following proportions of their total habitat areas: Tibetan wild donkeys (49.76%), Tibetan gazelles (47.00%), Tibetan antelopes (40.76%), and wild yaks (34.83%). These high-risk areas are primarily located within alpine meadow and temperate desert steppe. This study provides a quantitative assessment of survival risks for these four ungulate species on the Tibetan plateau grasslands and serves as a valuable reference for ungulate conservation and grassland ecosystem management.

A Review of Studies on the Effects of Anthropogenic Disturbances on Plant–Soil–Microorganism Interactions in Grassland Ecosystems: Based on Grazing and Tourism Perspectives

As the most widely distributed and largest terrestrial ecosystem in the world, grasslands play an important role in supporting global livestock production and maintaining ecosystem services. In light of the accelerated global socio-economic development and sustained population growth, grassland ecosystems are increasingly subjected to anthropogenic disturbances. However, there is a paucity of research examining the impact of such disturbances on plant–soil–microorganism interactions in grassland systems, particularly from the perspectives of grazing and tourism. Accordingly, this study presents a comprehensive analysis of the impacts of anthropogenic disturbance on grassland ecosystems over the past two decades, employing a dual perspective of grazing and tourism and utilizing econometric analysis of the existing literature through software such as CiteSpace. The results of this study demonstrate the following: (1) The current research focus is primarily concentrated in the fields of ecology and environmental sciences, particularly on the topics of plant diversity, abundance, and diversity, as well as the intensity of grazing. These areas may represent key development direction of future research. (2) The impact of anthropogenic disturbances on grassland ecosystems is primarily associated with grazing activities. Moderate grazing disturbances can facilitate the healthy development of grassland ecosystems. However, the intermediate disturbance hypothesis (IDH) may not fully account for the effects of grazing intensity on grassland ecology. At present, there is still a paucity of systematic research to determine the ecological indicators of grassland under a dual-disturbance scenario. It is recommended that future research be carried out to investigate the compound effects of trampling by tourism activities on plant–soil–microorganism interactions in grassland ecosystems. (3) The mutual feedback mechanism may represent a potential mechanism by which anthropogenic disturbances affect the coupled relationship between the plant, soil, and microbial systems in grassland ecosystems. Furthermore, the interaction among these three systems has the potential to exert direct or indirect impacts on the structure and function of grassland ecosystems in the context of disturbances. The present study aims to provide an overview of the structure and function of grassland ecosystems under anthropogenic disturbances. The objective is to identify a balance between the rational use of grassland and ecological protection under anthropogenic disturbance and to provide scientific reference for the sustainable use of grassland worldwide.

Grassland biome fragmentation analysis using sentinal-2 images and support vector machine learning model in South Africa

The grassland biome, which is classified as a terrestrial ecosystem, contributes significantly to carbon sequestration. About one third of this ecosystem covers the land surface in south Africa and faces the danger of being eradicated. Much of the pressure is attributed to by synthetic initiatives that seeks to expand the economy of the country thereby meeting the demands of cumulative population. Mining, agriculture, and human settlement are the main characters. Given the paucity of research on the threatened ecosystem, the support vector machine learning algorithm (SVM) is employed to investigate fragmentation from 2016 to 2023. We used Sentinel-2A/B satellite images to learn more about spatial and temporal patterns, as well as the distribution of fragmentation in the grassland biome, using the Google Earth Engine platform. The findings revealed that grassland occupied 66% of the area in 2016, decreased to 52% in 2019, and then increased to 59% by 2023. The inconsistency in the pattern or trend of the grassland class is likely attributable to the expansion of the other classes. The SVM model indicated an overall classification accuracy of 97.62%, 97.66% and 98.58% in 2016, 2019, and 2023, respectively. In contrast, the models developed to relate LAI to NDVI, MSAVI2, OSAVI, and NDRE produced R2 values of 0.6396, 0.6325, 0.6387, and 0.6344, respectively. An in-depth understanding of the fragmentation patterns observed in grasslands yields valuable information for the formulation of conservation strategies, sustainable land-use planning, and climate-resilient management approaches aimed at safeguarding South Africa's distinctive grassland ecosystems.