Plant litter as a cornerstone of grassland ecosystem services

ABSTRACTOrientallactaga sibirica (O. sibirica), a member of the family Dipodidae, is widely distributed across Central Asia and plays a significant role in grassland ecosystems. Although substantial ecological data exist for this species in China, research on intraspecific cranial variation is limited, and no comprehensive surveys have been conducted across its distribution range in China. This study aims to address this gap by collecting specimens of O. sibirica from various geographic regions in China, conducting geometric morphometric analyses of their skulls, and examining the influence of current climatic conditions on cranial morphology. Our results show that significant cranial variation in O. sibirica is observed in the nasal, parietal, and maxillary regions near the nasal end, as well as the zygomatic arch and preorbital bridge. These differences cause skulls from northeastern China to cluster distinctly from those from the Qinghai‐Tibet Plateau. Regression analyses indicated that skull size is primarily associated with annual precipitation, whereas skull shape is significantly associated with altitude. Our findings reveal a distinct morphological pattern in the Qinghai–Tibet Plateau population, suggesting a high degree of geographic differentiation that warrants further investigation. Characterizing environment‐associated intraspecific variation provides a baseline for understanding morphological diversity in O. sibirica across China.

ABSTRACT This paper reports on a new archaeological research project in the Stormberg region of South Africa’s Eastern Cape Province that began in 2018. After four prospecting surveys, an archaeological site — Marshill Rockshelter — was selected that could offer a long diachronic chronostratigraphic framework from the late Pleistocene to the Holocene in order to understand the deep past of this region and the long-term occupation of a mountain environment in the piedmont of the Maloti-Drakensberg Mountains. This paper presents the first archaeological analyses of this site’s stratigraphy, geochronology, faunal pollen, ceramic and lithic assemblages and rock art. Marshill has a long and complex stratigraphic sequence with three clusters of dates: one in the last 2000 years, a second around the terminal Pleistocene (10–15 kya) and a third at >20 kya. The archaeological materials found are in accordance with these initial ages and provide unique snapshots into the region’s past. A Middle Stone Age archaeological assemblage shows similarities with other sites in the Grassland, Savanna and Fynbos Biomes of southern Africa, although with the lithic evidence currently available it is difficult to establish stronger comparisons. Holocene layers, in contrast, produced microlithic Later Stone Age assemblages oriented towards the production of small flakes, most likely from unifacial cores. Initial faunal and pollen analyses accord with historical records in indicating an open grassland environment with thicketed valleys and gorges. The occurrence of domestic livestock in the upper Holocene layers suggests links to pastoralist groups and a herding economy. Preliminary ceramic analyses show several strategies for surface treatment, firing and modelling, while the textural groups defined document the use of fibre temper. Finally, the site’s rock paintings were created in a shaded and hard-edge technique with both ‘classic’ and more recent subject matter. In sum, the archaeological record from Marshill Shelter demonstrates a long but intermittent series of human occupations extending from the deep past to the historical period.

ABSTRACT Background High Nature Value farmland (HNVf) supports biodiverse, semi-natural habitats through extensive farming but is increasingly threatened in Ireland by land intensification and abandonment. Results-based payment schemes (RBPS) aim to maintain and enhance these habitats, yet their broader biodoversity benefits remain unclear. Aims This study examined the relationship between an RBPS scoring system developed for the protected hen harrier (Circus cyaneus) and semi-natural grassland plant communities. Methods Thirty grassland fields spanning a gradient of RBPS ecological condition scores from (0-10) were surveyed. Vegetation surveys were carried out in three 2 m × 2 m quadrats per fieldalong a ‘W’ transect walk, supplemented with additional environmental data as proxies for environmental conditions and management pressure. Non-metric Multidimensional Scaling was used to analyse species composition, and fields were assigned to a vegetation type using the Irish Vegetation Classification ERICA tool. Results Higher RBPS scores were positively associated with greater number and cover of positive indicator species, increased bryophyte cover, and higher floristic diversity indices. Lower scoring fields were associated with greater cover of negative indicator species, increased rush cover and higher Ellenberg’s Nitrogen and Reaction values. Eight wet grassland community types were identified. Conclusions Our findings indicate that an RBPS designed to incentivise ecological conditions for a target raptor species can also reflect wider plant diversity, supporting multiple ecosystem services in HNVf systems.

Grassland canopy height is one of the most important traits for determining plant diversity and community structure, directly affecting the resource use efficiency of livestock in grassland ecosystems. However, broad-scale changes in grassland canopy height are seldom reported due to the complex effects of species aggregation on both interspecific and intraspecific structures. Here, we decouple grassland aboveground biomass into vertical and horizontal allocations, thereby offering a pathway to mirror changes in grassland canopy height. Grassland aboveground biomass is estimated using a machine learning algorithm by fusing climatic factors, satellite-driving metrics, and 8-year consecutive ground-truth surveys; the horizontal allocation of grassland aboveground biomass is derived from optimized linear spectral mixture analysis. We find that changes in horizontal biomass allocation primarily accounted for increases in Chinese grassland aboveground biomass from 2001 to 2022, resulting in a significant decline in grassland canopy height. The decline in grassland canopy height is shaped by reduced radiation and, more importantly, by the combined effects of warming and grazing, while also being related to variations in plant diversity. The dwarfing grassland community with declining canopy height may increase the impact of livestock disturbances, thus diminishing the resistance of grassland ecosystems to climate fluctuations.

Abstract In temperate grasslands, competition between plants and soil microbes for inorganic nitrogen (N) is a critical process in regulating N retention, loss and overall ecosystem productivity. However, how grazing intensity alters this competition, particularly for specific N forms such as ammonium (NH 4 + ) and nitrate (NO 3 − ) remains poorly understood. We conducted a dual 15 N labelling experiment in a semi‐arid steppe in Inner Mongolia, China, where four grazing intensities (none, light, moderate and heavy) have been maintained for 9 years. Grazing increased soil pH, reduced soil moisture and organic carbon, and decreased plant biomass (particularly under heavy grazing). Moderate grazing shifted microbial biomass and composition, declining Proteobacteria and increasing Ascomycota. These changes altered plant and microbial N uptake. Plant N preference shifted from NH 4 + to NO 3 − with increasing grazing intensity, while microbial NO 3 − uptake peaked under moderate grazing but declined under heavy grazing. In contrast, microbial NH 4 + uptake increased nonlinearly according to a quadratic relationship, resulting in microbial dominance under heavy grazing. The microbial‐to‐plant uptake ratio for NH 4 + revealed a tipping point, beyond which microbial uptake dominated. Our results demonstrate that grazing intensity regulates plant–microbial N competition by driving ammonium towards microbial immobilization and nitrate towards plant uptake, mediated by changes in microbial community composition. Fungal immobilization under heavy grazing drove microbial NH 4 + dominance, creating a tipping point. Synthesis . These findings highlight a threshold response in below‐ground nutrient partitioning and suggest that moderate grazing sustains balanced plant–microbe interactions in grassland ecosystems. This study provides a mechanistic framework based on a fungal‐driven NH 4 + tipping point, revealing critical competition thresholds that are not detectable in bulk N measurements.

Abstract Plant species richness patterns across vernal pool complexes are regulated by dynamic hydrologic processes, yet these controls remain difficult to quantify across space in ways that inform monitoring and conservation. In this study, we test whether microtopographic features can serve as proxies for hydrologic processes that shape plant species richness patterns. We evaluate this hypothesis by modeling relationships between unmanned aerial vehicle light detection and ranging (UAV-LiDAR)-derived microtopographic features and vascular, forb, and graminoid plant species richness across a vernal pool complex in central California, USA. We obtained plant assemblage data from surveys of 224 vernal pools in 2018 and 2019 and collected UAV-LiDAR data over the study area in 2020. We derived 11 features from UAV-LiDAR data and applied a recursive feature elimination procedure to optimize richness estimates. Poisson generalized linear models and a bootstrap cross-validation approach were used to construct species richness models for each plant functional type. Microtopographic features related to hydrologic connectivity, soil moisture gradients, and hydroperiod described substantial variation in vascular plant species richness patterns (median training r 2 = 0.35, median validation r 2 = 0.28) and were accurate to within 2-3 species per pool, consistent with similar ecological remote sensing efforts in tall prairie, salt meadow, and other grassland ecosystems. Forb richness, which disproportionately contribute to vascular plant richness, was highest in low-lying, hydrologically connected, and topographically uniform areas characteristic of vernal pools. Conversely, graminoid richness was higher at elevated, low-slope positions, such as mound tops across the mound–swale topography of the study area. These contrasting responses support the hypothesis that microtopography shapes hydrological niches favoring water-tolerant forbs in frequently inundated areas and graminoids in comparatively drier areas. Importantly, quantifying the link between microtopography and plant richness responses provides an ecologically grounded basis for managers to guide vernal pool conservation and restoration using microtopographic datasets.

Information on soil phosphorus dynamics and its influence on soil carbon sequestration in different land use types is scanty. A research was conducted to determine the influence of soil phosphorus on soil organic carbon sequestration in four land use types in Abakaliki, south eastern Nigeria. The four land use types selected include managed forest plantation, fallow land, grass land and continuously cultivated soil. Soil samples were randomly collected from each of the land use types seasonally; two times in rainy season and two times in dry season annually at three months interval respectively for two years (2022 and 2023). Undisturbed and auger soil samples were collected at three soil depths (0 – 20 cm, 20 – 40 cm and 40 – 60 cm) in the selected land use types and replicated five times for bulk density determination and chemical analysis such as soil organic carbon and available phosphorus using standard methods. On the average, soil bulk density values obtained were lowest (1.54 gcm3) in the fallow land and highest (1.71 gcm3) in the continuously cultivated soil for both seasons and for the two years. On the average, managed Gmelina plantation (MP) recorded the highest soil organic carbon (SOC) (15.45 and 23.70 gkg-1 for dry and rainy seasons respectively) and mean available phosphorus (AP) (8.03 and 12.37 mgkg-1 for dry and rainy season respectively) while continuously cultivated soil (CCS) had the lowest values (9.03 and 8.88 gkg-1 for dry and rainy seasons respectively) and (0.93 and 0.95 gkg-1 for dry and rainy season respectively) for the soil nutrients in both seasons. The result on total organic C storage showed that continuously cultivated soil (CCS) had highest value (160.17 Mg C ha-1) and lowest(116.84 Mg C ha-1) in grass land (GL) in dry season year 1 while in rainy season year 1 managed Gmelina plantation recorded the highest (365.51 Mg C ha-1) and GL recorded the lowest (135.63 Mg C ha-1).Similarly, MP recorded the highest value (340.67 and 372.06 Mg C ha-1) while CCS recorded the lowest value (151.49 and 220.42 Mg C ha-1) for dry and rainy seasons respectively in second year. The results also showed that the soil physical and chemical properties were significantly different (P < 0.05) among the four land use types and depths. It is therefore recommended that continuous cultivation without organic amendments which exposes the soil should be discouraged. Also, management practices and land use types like managed forest plantation, fallow land and grass land that increase soil carbon content should be encouraged. This is because soil phosphorus encourages carbon sequestration that helps to mitigate the effect of climate change.

Monoculture and mixed sowing are common practices for restoring degraded alpine meadow grasslands. To investigate the effects of different sowing patterns on soil bacterial community characteristics in alpine artificial grasslands, this study examined a 20-year-old established artificial grassland, systematically analyzing plant community attributes, soil physicochemical properties, and the diversity and functional structure of soil bacterial communities under various monoculture and mixed-sowing treatments. The results showed that: (1) Mixed-sowing treatments significantly improved soil physicochemical properties and plant community characteristics. The P4 (Elymus nutans + Poa pratensis + Festuca sinensis + Poa crymophila) mixed-sowing treatment notably enhanced vegetation performance and soil conditions. Compared with the monoculture P1 (Elymus nutans) treatment, aboveground biomass (AGB) and soil organic matter (SOM) content increased by 57.23% and 68.25%, respectively, indicating that perennial grass mixtures improve soil water and nutrient retention, thereby promoting plant growth. (2) Microbiome analysis revealed that mixed sowing significantly optimized the structure of rhizosphere bacterial communities. Operational Taxonomic Units (OTUs), which represent sequence-based taxonomic units and their abundance information, were most abundant in the P4 mixed-sowing treatment, reaching a total of 5685 OTUs. In terms of bacterial diversity indices, the OTU richness, Ace index, and Chao1 index in the P4 mixed-sowing treatment were 26.12%, 25.81%, and 24.34% higher, respectively, than those in the monoculture P1 treatment, with all differences being statistically significant (p < 0.05). (3) Mantel test and redundancy analysis (RDA) revealed that soil electrical conductivity (SEC) and pH were negatively correlated with bacterial diversity indices, while soil organic matter (SOM) was identified as the key environmental driver shaping bacterial community assembly. In summary, appropriate grass mixtures effectively enhance "plant-soil-microbe" interactions, leading to improved soil fertility and optimized bacterial communities, representing a viable strategy for long-term ecological restoration and sustainability of alpine artificial grassland ecosystems. The P4 treatment-comprising a four-species mixture of Elymus nutans, Poa pratensis, Poa crymophila, and Festuca sinensis-achieved the best overall performance.

The Inner Mongolia Autonomous Region, located in northern China, represents a temperate semi-arid ecosystem dominated by steppe vegetation and characterized by rich, yet understudied, fungal diversity. During an investigation of microfungi associated with decaying plant materials in the desert regions of Inner Mongolia, two novel species of Comoclathris were collected and isolated. Detailed morphological examinations and multi-locus phylogenetic analyses based on ITS, LSU, SSU, and rpb2 sequence data support the establishment of these taxa as novel species: Comoclathris desertica and C. xiangshawanensis. These two species are described and illustrated herein, with particular attention to their differences from similar species with respect to ascomatal structures and ascospore morphology. The discovery of these new taxa expands the known diversity and distribution of Comoclathris in China and provides new insights into the saprobic fungal communities of semi-arid regions. This study also highlights the ecological and taxonomic significance of continued surveys on saprobic fungi in grassland and desert ecosystems of northern China.

Introduction Grassland degradation in karst regions is typically characterized by increased bedrock exposure, vegetation fragmentation, and soil structural instability. However, the mechanisms by which these changes affect hillslope erosion resistance remain poorly quantified. Methods In this study, natural grassland plots under four levels of degradation, defined by bedrock exposure rates (RER) of 0%, 20%, 40%, and 55%, were selected in representative limestone and dolomite areas in Guizhou Province, China. Undisturbed soil samples from the 0∼20 cm layer were collected for aggregate stability tests and undisturbed soil scouring experiment. Using 9 diagnostic indicators of soil structural function, the effects of degradation on soil retention capacity were quantitatively assessed. Results The results showed that with increasing RER, the proportion of macroaggregates (&amp;gt;2 mm) decreased by 31.6%, and mean weight diameter (MWD) declined by 58.3%. Relative dispersion index (RSI) and relative mechanical Breakdown index (RMI) increased to 1.96 and 2.21, respectively, with the most severe structural breakdown occurring under fast wetting conditions. In the scouring experiments, sediment concentration peaked at 1.8 g/min within the first minute in the 55% RER plots, significantly higher than in the 0% RER plots. Meanwhile, the soil resistance coefficient declined by more than 50%. Composite functional evaluation revealed that MWD, RSI, Anti-scourability coefficient (AS), and root surface area were the most sensitive indicators across degradation levels. Limestone grassland (LG) demonstrated stronger performance in maintaining structural integrity and erosion resistance compared to Dolomite grassland (DG). Discussion These findings provide a scientific basis for identifying early warning signs of erosion resistance loss and offer theoretical support for ecological restoration and degradation threshold identification in karst grassland ecosystems.

Grazing is a pervasive disturbance in arid and semi-arid grasslands that can influence plant reproduction through both direct tissue removal and indirect soil-mediated pathways. Because seed production and allocation strategies determine population persistence and vegetation recovery under chronic disturbance, understanding how grazing reshapes reproductive investment is critical, particularly for long-lived desert shrubs. We investigated how different grazing intensity reshapes growth-reproduction trade-offs and seed allocation strategies of the dominant desert shrub Reaumuria soongorica in a desert steppe of northern China. Using a long-term grazing experiment with no grazing (CK), moderate grazing (MG), and heavy grazing (HG) treatments, we quantified shrub growth, reproductive traits, soil properties, and fertile island effects beneath shrub canopies and interspaces area. Grazing intensity exerted contrasting effects on shrub performance. Moderate grazing enhanced shrub biomass, seed production, and female fitness, whereas heavy grazing significantly suppressed reproductive traits, including seed number and seed mass. Across treatments, grazing induced a clear shift in seed allocation, strengthening the seed number-seed mass trade-off under increasing disturbance. Structural equation modeling revealed that grazing affected reproductive allocation through both direct negative effects and indirect soil-mediated pathways. Grazing increased soil carbon, nitrogen, and phosphorus beneath shrubs while exerting minimal effects on interspace soils, indicating spatial redistribution of nutrients and intensified fertile island effects. Soil fertility promoted reproduction, whereas altered soil stoichiometric ratios constrained growth, highlighting opposing soil controls on shrub performance. We further identified reciprocal feedback between shrub functional traits and fertile island effects, whereby trait-driven resource accumulation and grazing-enhanced soil heterogeneity jointly regulated reproductive strategies. These results demonstrate that long-term grazing reorganizes soil-plant feedbacks and seed allocation trade-offs, providing mechanistic insights into shrub persistence and informing sustainable grazing management in arid grassland ecosystems.

Understanding the ecological drivers of plant-associated microbiota is essential for predicting grassland ecosystem resilience. This study aimed to characterize the community structure, functional potential, and soil environmental drivers of rhizosphere and root endophytic microbiota associated with Polygonum divaricatum across three Hulunbuir Grassland sites. A nested sampling design was applied with three replicated plots per site, from which paired rhizosphere soil and root samples were collected. Each sample represented a composite of 15 plants, yielding six samples per site (total n = 18) and allowing the separation of compartmental and environmental effects on community assembly. P. divaricatum plays a key role in nutrient cycling and soil stability; however, its rhizosphere and root microbiomes remain poorly characterized. Fungal diversity was consistently higher in the root endosphere, whereas bacterial diversity was greater in rhizosphere soils. Fungal assemblages were dominated by Ascomycota and Mortierellomycota, primarily represented by Mortierella and Trichoderma, while bacterial communities were dominated by Actinomycetota and Pseudomonadota, enriched in Bradyrhizobium and Pseudonocardia. Community differentiation reflected strong compartmental filtering and responses to soil pH, organic carbon, nitrogen, and enzyme activities. Functional prediction indicated clear compartmental partitioning: in the rhizosphere, bacterial communities were enriched in pathways related to carbon and nitrogen metabolism and secondary metabolite biosynthesis, whereas in the root endosphere, functional profiles were more associated with transport, uptake, and fermentation; fungal communities were dominated by saprotrophic and symbiotrophic guilds. These findings demonstrate that soil biochemical gradients and host-driven filtering jointly structure the P. divaricatum microbiome, providing ecological insights into plant-microbe-soil interactions and the maintenance of grassland ecosystem stability.

Nitrogen addition and grazing, as common management tools in grasslands, alter the structure and function of soil microbial communities and have far-reaching effects on grassland ecosystems. However, the mechanisms by which nitrogen addition and grazing regulate the diversity and stability of soil microbial communities remain insufficiently understood. In this study, a field experiment was conducted in the temperate desert grassland of Xinjiang, combining nitrogen addition treatments with simulated grazing to investigate the response mechanisms of soil microbial communities to nitrogen addition and simulated grazing. The regulation of soil microbial community diversity and stability under the combined effects of nitrogen addition and grazing was examined by using mowing to simulate aboveground vegetation disturbance. The results showed that inorganic nitrogen (nitrate and ammonium nitrogen) was a key factor driving nitrogen-induced changes in microbial community structure, increasing the availability of soil nitrogen. Moderate nitrogen addition promoted bacterial community diversity, whereas excessive nitrogen input weakened this effect and reduced bacterial community complexity and co-occurrence network stability. Simulated grazing enhanced organic nitrogen catabolism through increased leucine aminopeptidase activity, thereby stabilizing bacterial community interactions under nitrogen-enriched conditions and alleviating the negative effects of nitrogen addition. These results indicate that grazing can buffer nitrogen-induced destabilization of soil microbial communities and highlight its role in maintaining microbial functional stability in grassland ecosystems under increasing nitrogen deposition.

Gross Primary Productivity (GPP) in grassland ecosystems is a fundamental eco-biophysical indicator for assessing carbon cycling, grazing capacity, and ecosystem responses to climatic stress. However, robust estimation of GPP in arid and semi-arid rangelands remains challenging because of pronounced spatial heterogeneity, strong climate variability, and inherent uncertainties associated with remotely sensed observations. Together, these factors constrain both modeling performance and out-of-sample generalization beyond the training domain. In this dryland grassland context, this study compares the performance of machine learning (ML) models for grassland GPP proxy-based characterization, downscaling, and predictive agreement using a multivariate dataset that integrates Sentinel-2-derived spectral and phenological features, a Moderate-Resolution Imaging Spectroradiometer (MODIS)-derived GPP proxy, and complementary climatic and geographic information. Pixel-level observations spanning multiple years are analyzed, with ordinary linear regression used as a baseline benchmark and ensemble decision-tree models, including Random Forest, Gradient Boosting, and Histogram-based Gradient Boosting (HGB), compared. Instead of relying solely on random cross-validation, model performance is systematically assessed using a combination of spatially structured validation and a leave-one-year-out scheme to explicitly examine spatial and temporal generalization. The results indicate that ensemble tree-based models outperform linear approaches, with the HGB model showing the strongest agreement with the MODIS-derived GPP proxy (R2 = 0.95, RMSE = 0.035 on the test set) and maintaining stable performance across spatial and temporal validations (R2 = 0.86–0.96 across years). Taken together, the findings demonstrate that integrating multi-source remote sensing data with climatic information within a rigorous validation framework enables a more reliable assessment of model generalization and gap-filling consistency with respect to a remote-sensing-based proxy target, rather than an absolute validation against ground-based measurements, thereby supporting sustainability-relevant monitoring of arid grassland ecosystems.

Abstract Premise Seed dispersal is a critical process for plant community assembly; however, natural rates of seed arrival are rarely quantified compared with other assembly mechanisms, especially in herbaceous communities. Methods Here we compare the utility of artificial grass carpet squares (“artificial grass”) for capturing seed rain with classic “sticky trap” methods. We placed paired sticky traps and artificial grass squares in two grassland ecosystems, added known numbers of seeds of multiple species to each trap, and recovered seeds at one‐week, one‐month, and two‐month intervals. Results We found that both trap types lost seeds through time at similar rates, but each trap type had advantages and disadvantages. Overall, sticky traps retained more seeds and measured primary dispersal, but recovering seeds was difficult and hindered by debris stuck to the traps. Alternatively, artificial grass traps measured effective dispersal as more seeds were lost through time to secondary dispersal and granivory, but recovered seeds could be handled easily and retained for long‐term storage and germination. Discussion We encourage the broad adoption of seed rain studies to improve links between theoretical and empirical community ecology. Both sticky traps and artificial grass traps are useful in measuring seed rain in grasslands but vary in the types of information they provide.

Large-scale ecological restoration programs have been widely implemented to alleviate ecological degradation and environmental stress in arid and semi-arid regions. However, evaluating their long-term ecological effectiveness remains challenging, particularly across large spatial extents and extended time periods. Using multi-source meteorological, topographic, soil, and remote sensing data for five benchmark years spanning 1985-2024, this study evaluates the long-term ecological effectiveness of the Three-North Shelterbelt Program from an ecosystem services perspective. Four key ecosystem services-water conservation, biodiversity maintenance, soil conservation, and wind erosion control-were quantified to analyze their spatiotemporal dynamics across the Three-North region. The results show that ecosystem services have generally increased over the past four decades, indicating an overall enhancement in ecosystem functioning across much of the study area. Spatially, ecosystem services exhibit a pronounced southeast-to-northwest gradient, with higher service levels in relatively humid southeastern and southern regions and lower levels in arid central and western areas. Analysis across land use types further shows that forest and grassland ecosystems play a critical role in sustaining ecosystem services. In addition, regions with differing levels of ecosystem services require differentiated protection and management strategies. Overall, this study provides a functional-level assessment of long-term ecological changes associated with the Three-North Shelterbelt Program and offers insights to support the design and management of large-scale ecological restoration initiatives in arid and semi-arid regions.

Purpose The purpose of this study is to investigate the competitive dynamics between cattle and invertebrates for grass biomass in a grassland ecosystem using a fractional-order nonlinear mathematical model. Design/methodology/approach A fractional-order grassland competition model is formulated using the Caputo fractional derivative of order ρ ∈ (0, 1]. The qualitative behavior of the system is analyzed by establishing the non-negativity and boundedness of solutions, followed by a stability analysis of the equilibrium points. Numerical simulations are performed using a generalized fractional Runge–Kutta second-order (RK2) scheme to examine the influence of fractional orders and interspecific competition parameters on system dynamics. Findings The results demonstrate that the proposed model admits biologically feasible solutions that remain non-negative and bounded. Stability analysis reveals that fractional-order dynamics significantly affect the equilibrium behavior of the system. Numerical simulations show that varying the fractional order and competition coefficients leads to substantial changes in grass biomass and population dynamics. In particular, fractional-order models exhibit enhanced stability and reduced oscillatory behavior compared to classical integer-order models. Originality/value This study provides a novel fractional-order framework for modeling grassland competition involving cattle and invertebrates. The findings highlight the advantages of fractional-order models in capturing memory effects and improving stability characteristics, offering valuable insights for ecological modeling and sustainable grassland management.

Grassland aboveground biomass (AGB) is a key indicator of grassland ecosystem structure and function, and its accurate monitoring is of great importance for assessing grassland ecological conditions and supporting sustainable grassland management. Traditional biomass estimation methods based on vegetation indices (VIs) often suffer from saturation due to canopy shading. However, comparative studies on VI saturation and the saturation height of AGB detectable by different indices remain limited. In this study, we evaluated 12 commonly used VIs based on field-measured AGB and hyperspectral data in the Hulunbuir meadow steppe. Relationships between vertically accumulated biomass and VIs were analyzed to identify optimal AGB fitting models and to determine the saturation height of each index. Results showed that vertical distribution of AGB followed a unimodal pattern, with biomass peaking at approximately 36 cm in this region. This study employed four models (namely the Linear model, the Logarithmic model, the Power Function model and the Gompertz model) to fit the relationship between the vegetation index and AGB. Among them, Gompertz models consistently outperformed other models, indicating saturation across all indices. Based on saturation height, the 12 VIs were classified into two groups: ARVI, GNDVI, NDRE, OSAVI, and SAVI saturated at 40 cm, whereas DVI, EVI, MSAVI, NDPI, NDVI, RVI, and VARI maintained sensitivity up to 50 cm, demonstrating a stronger anti-saturation capacity. NDVI and NDPI exhibited the highest fitting accuracy and resistance to saturation. These findings validate the saturation limitations of VIs and provide guidance for selecting appropriate indices to improve the accuracy of grassland biomass retrieval.

Abstract Plant root growth accounts for a major part of the net primary production in grassland and forest ecosystems and influences the global carbon and nutrient cycles. Measuring the production of roots is inherently difficult, prone to inconsistencies and time‐consuming. Notably, there are currently no methods yet to automate this task. We have developed GINGER, a new method for automated estimation of the fine root production from a time series of minirhizotron images. It compares pairs of consecutive images with each other, separating new root growth from standing crop. The method was evaluated on four datasets from grassland, drained fen peatland and forest ecosystems. It exhibits performance on a similar level to that of human annotators while substantially reducing the time required for the data analysis. Human annotators showed a significant degree of variability among each other, confirming that the task is subjective and error‐prone. For demonstration, this pipeline was applied on two real‐world image datasets, spanning 2 and 3 years, to compute the total annual root production. End‐to‐end, including annotation and model training, GINGER reduced the required human workload from several thousand to less than 40 work hours. It could allow to scale up monitoring efforts and enable full automation in the future.