Alpine Meadow Research Articles

Litter Removal Counteracts the Effects of Warming on Soil Bacterial Communities in the Qinghai–Tibet Plateau

Climate warming and high-intensity human activities threaten the stability of alpine meadow ecosystems. The stability of the soil microbial community is crucial for maintaining ecological service function. However, the effects of warming and litter removal on microbial interactions, community-building processes, and species coexistence strategies remain unclear. In this study, we used a fiberglass open-top chamber to simulate global change, and moderate grazing in winter was simulated by removing above-ground litter from all plants in the Qinghai–Tibet Plateau, China, to investigate the effects of warming, litter removal, and interactions on soil microbial communities. The treatments included (1) warming treatment (W); (2) litter removal treatment (L); (3) the combined treatment (WL); and (4) control (CK). The results show that compared with the control treatment, warming, litter removal, and the combined treatments increased bacterial Shannon diversity but reduced fungal Shannon diversity, and warming treatment significantly changed the bacterial community composition. Warming, litter removal, and the combined treatments reduced the colinear network connectivity among microorganisms but increased the modularity of the network, and the average path distance and average clustering coefficient were higher than those in the control group. Stochastic processes played a more important role in shaping the microbial community composition, and soil–available phosphorus and soil ammonium contributed more to the βNTI of the bacterial community, while total phosphorus and NAG enzyme in the soil contributed more to the βNTI of the fungal community. Notably, litter removal counteracts the effects of warming on bacterial communities. These results suggest that litter removal may enhance bacterial community stability under warming conditions, providing insights for managing alpine meadow ecosystems in the context of climate change.

Correction: Experimental grazer exclusion increases pollination reliability and influences pollinator-mediated plant-plant interactions in Tibetan alpine meadows

Correction: Experimental grazer exclusion increases pollination reliability and influences pollinator-mediated plant-plant interactions in Tibetan alpine meadows

Exploring phyllosphere fungal communities of 29 alpine meadow plant species: composition, structure, function, and implications for plant fungal diseases

The phyllosphere of plants hosts diverse fungal microbial communities. Despite the significant impact of plant fungal diseases on productivity and community ecology, the relationship between phyllosphere fungal communities and plant health in natural environments remains poorly understood. This study utilized high-throughput sequencing and field investigations to explore the composition, dynamics, and incidence of fungal diseases across 29 plant species from four functional groups (forbs, grasses, legumes, and sedges) in alpine meadow plant communities of the Qinghai-Tibetan Plateau. We identified Ascomycetes and Basidiomycetes as the predominant phyllosphere fungi. Significant differences were observed in the Shannon diversity index, β-diversity, indicator fungi, and hub fungi among the functional groups. With the exception of the sedge group, the incidence of fungal diseases in other groups was positively correlated with the proportion of pathogens in the phyllosphere fungal community. Predictive analyses revealed that Ascochyta was strongly associated with high disease incidence in grasses, Cercospora in forbs, and Podosphaera in legumes, while Calophoma was associated with low disease incidence in sedges. These findings enhance our understanding of how plant phyllosphere fungal communities assemble in natural environments and improve our ability to predict and manage foliar fungal diseases in alpine meadows.

Invasion alters plant and mycorrhizal communities in an alpine tussock grassland.

Plant invasions are impacting alpine zones, altering key mutualisms that affect ecosystem functions. Plant-mycorrhizal associations are sensitive to invasion, but previous studies have been limited in the types of mycorrhizas examined. Consequently, little is known about how invaders that host rarer types of mycorrhizas may affect community and ecosystem properties. We studied invasion by an ericoid mycorrhizal host plant (Calluna vulgaris L., heather) in alpine tussock grasslands in New Zealand. We investigate the effects of increasing C. vulgaris density on the plant and soil microbial community and on mycorrhization in the dominant native species (Chionochloa rubra Z., red tussock), an arbuscular mycorrhizal host. We show that variation in plant community composition was primarily driven by invader density. High invader densities were associated with reductions in C. rubra diameter and in the cover, richness and diversity of the subordinate plant community. Belowground, we show that higher invader densities were associated with lower rates of mycorrhization in C. rubra and higher proportional abundance of the fungal lipid biomarker 18:2ω6 but had little effect on total microbial biomass, which may suggest increased ericoid mycorrhizal and fine root biomass in high C. vulgaris density stands. Our data suggest that disruption of native plant-arbuscular mycorrhizal networks may contribute to the competitive success of C. vulgaris, and that the dramatic decline of C. rubra with invasion reflects its relatively high mycorrhizal dependence. By exploring invasion of a plant with a less common mycorrhizal type, our study expands knowledge of the ecosystem consequences of biological invasions.

Of goats and heat, the differential impact of summer temperature on habitat selection and activity patterns in mountain goats of different ecotypes.

Climate change disproportionately affects northern and alpine environments, with faster rates of warming than the global average. Because alpine and northern species are particularly well adapted to cool temperatures, most species must modify their behavior when temperatures exceed a critical threshold. Evaluating how temperature increases affect species inhabiting northern and alpine environments is therefore essential to understand the effects of projected climate change on these ecosystems. We analyzed the influence of temperature on the activity patterns and habitat selection of four populations of a cold-adapted, mountain specialist, the mountain goat (Oreamnos americanus). We collected GPS location and activity sensor data during 2010-2019 from 223 mountain goats from two distinct ecotypes: coastal and continental. Using a resource selection modeling approach, we determined that mountain goats of both ecotypes decreased selection for alpine meadows when temperatures increased. Reduced selection for open, forage rich habitat was associated with increased selection for habitat dominated by snow/ice patches in coastal areas, and by forests in continental sites. Mountain goats in continental environments selected higher elevation habitats only when temperature increased, whereas goats in coastal environments selected higher elevation habitat at all temperatures. Mountain goats of both ecotypes reduced the proportion of time spent active when temperatures increased during the middle of the day. Our study reveals that mountain goats use diverse tactics to mitigate thermal stress, and that these tactics vary between ecotypes, highlighting the need for considering adaptation to specific environments within a species when assessing climate change impacts on populations.

Meadow degradation reduces microbial β diversity and network complexity while enhancing network stability

Continuing meadow degradation under the dual impacts of climate change and human activities has altered microbially-mediated biogeochemical cycles. However, microbial diversity and network stability in response to meadow degradation and their relationships to environmental variables remain insufficiently understood. This study focused on alpine meadows with varying degrees of degradation in the hinterland of the Qinghai-Tibetan Plateau. It analyzed the soil microbial diversity (α and β diversity) and ecological network topology characteristics under the degradation of alpine meadows. Furthermore, the extent to which these factors elucidate the environmental changes observed during degradation was explored. The results demonstrated that: (1) the α diversity of soil microbial under degradation of alpine meadows exhibited an increasing trend, although not significantly. The β diversity (community dissimilarity) exhibited a significant decreasing trend. These indicated that meadow degradation resulted in microbial homogenization intra- and inter-community. In the light degradation stage, the β diversity of bacteria and fungi significantly increased with geographic and environmental distance rise. Only bacterial β diversity significantly increased with geographical distance in the moderate degradation stage and environmental distance in the heavy degradation stage, respectively. This indicated that meadow degradation possibly altered microbial assembly, especially for fungi. (2) The degree of soil bacterial nodes exhibited a significant decreasing trend with degradation and fungal eigencentrality demonstrated a significant decreasing trend. After removing the identical nodes, the natural connectivity of the fungal network exhibited a significant decreasing trend with degradation. This suggested that the stability of the soil microbial network increased while the network complexity decreased under meadow degradation. These changes possibly marked the irreversible course of alpine meadow degradation. (3) The Mantel test indicated that bacterial diversity and network topological features were more strongly associated with environmental factors than those of fungi. Akaike information criterion (AIC) values and the upset matrix plots of variance partitioning based on Redundancy analysis (RDA) indicated that higher rates of soil factors, such as soil pH, organic carbon (SOC) content, and total potassium (TK), elucidated changes in microbial community diversity and network topological features. This study highlights the importance of soil microorganisms for ecological stability and the role of microorganisms should be emphasized in future efforts to restore alpine grasslands.

Mowing mitigates the negative impacts of long-term warming on community composition and niche characteristics of alpine meadow on the Tibetan Plateau

Climate warming and human disturbance are supposed to have significantly impacted the alpine grasslands. However, it is still unclear how human activity affects the community composition and niche characteristics in response to warming. We conducted a two-factorial experiment in an alpine meadow, and set up four treatments: warming, mowing, warming with mowing, and control. Based on the investigation of community composition and niche characteristics, we evaluated the impacts of soil carbon, nitrogen, and phosphorus on species niche overlap. The results showed that mowing significantly increased species richness of Grass, Sedge, Forbs and the importance value of Sedge compared to warming (P < 0.05). The niche breadth of species (>50%) was reduced by warming, but increased under mowing. The niche overlap mainly occurred between Grass and Forbs in warming, while it was evenly distributed among species after mowing, which alleviated the negative effects of warming on interspecific competitiveness. Warming increased the number of species pairs with a niche overlap value >0.9 by 24.15%, while warming with mowing decreased it by 2.7%. The number of species pairs with niche overlap was significantly correlated with soil total nitrogen and soil available nitrogen (P < 0.05). In particular, the species pairs with highly competitive showed a greater dependency on soil nitrogen. Our work highlights that moderate utilization and soil nitrogen are two crucial factors influencing the response of community structure in alpine meadows to future climate change. The study provides an important reference for predicting and addressing the impact of global climate change on adaptive management and grassland protection.

Assessing the Soil Infiltration Rate of Alpine Meadows Using the Electrolyte Tracer Method

ABSTRACTGrassland on the Qinghai‐Tibet Plateau is highly susceptible to climate change and human activities, and vegetation degradation can affect biodiversity and soil erosion. Soil infiltration is a crucial water flow process that determines the amount of runoff and water storage capacity, and it is of great importance in maintaining biodiversity. This research investigated the effects of vegetation degradation and soil rates on soil infiltration rate and processes using the electrolyte tracer method. This technique accurately calculated soil infiltration rate by tracking continuous changes in the solute concentration change process throughout the experimental period and did not require calibration. Findings indicate that vegetation type, root mass, soil water content and soil porosity significantly affect soil infiltration rate. In particular, root mass was found to have a negative effect on soil infiltration rate. Soil moisture content initially dominated soil infiltration, but subsequently, soil porosity became increasingly influential in affecting infiltration in degraded meadow. Soil infiltration capacity varied more with vegetation type than with surface runoff. Shrub meadows had the highest infiltration rate followed by normal alpine meadows and degraded meadows, indicating the importance of vegetation on soil infiltration. The research also shows that mixed shrub and meadow can improve the ecological environment by introducing a more complex root system and increasing the infiltration rate. The electrolyte tracer method was used as an alternative to other methods that can be used in different environments than the one studied in this research.

Metabolomic Analysis of Elymus sibiricus Exposed to UV-B Radiation Stress

Plants cultivated on the Qinghai-Tibet Plateau (QTP) are exposed to high ultraviolet radiation intensities, so they require effective mechanisms to adapt to these stress conditions. UV-B radiation is an abiotic stress factor that affects plant growth, development, and environmental adaptation. Elymus sibiricus is a common species in the alpine meadows of the QTP, with high-stress resistance, large biomass, and high nutritional value. This species plays an important role in establishing artificial grasslands and improving degraded grasslands. In this study, UV-B radiation-tolerant and UV-B radiation-sensitive E. sibiricus genotypes were subjected to simulated short-term (5 days, 10 days) and long-term (15 days, 20 days) UV-B radiation stress and the metabolite profiles evaluated to explore the mechanism underlying UV-B radiation resistance in E. sibiricus. A total of 699 metabolites were identified, including 11 primary metabolites such as lipids and lipid-like molecules, phenylpropanoids and polyketides, organic acids and their derivatives, and organic oxygen compounds. Principal component analysis distinctly clustered the samples according to the cultivar, indicating that the two genotypes exhibit distinct response mechanisms to UV-B radiation stress. The results showed that 14 metabolites, including linoleic acid, LPC 18:2, xanthosine, and 23 metabolites, including 2-one heptamethoxyflavone, glycyrrhizin, and caffeic acid were differentially expressed under short-term and long-term UV-B radiation stress, respectively. Therefore, these compounds are potential biomarkers for evaluating E. sibiricus response to UV-B radiation stress. Allantoin specific and consistent expression was up-regulated in the UV-B radiation-tolerant genotype, thereby it can be used to identify varieties resistant to UV-B radiation. Different metabolic profiles and UV-B radiation response mechanisms were observed between the UV-B radiation-tolerant and UV-B radiation-sensitive E. sibiricus genotypes. A model for the metabolic pathways and metabolic profiles was constructed for the two genotypes. This metabolomic study on the E. sibiricus response to UV-B radiation stress provides a reference for the breeding of new UV-B radiation-tolerant E. sibiricus cultivars.

Response of Plant Phylogenetic Structure to Plateau Pika (Ochotona curzoniae) Disturbance on Alpine Meadow of Qinghai‐Tibetan Plateau

ABSTRACTPlant community construction is influenced by bottom‐up processes, such as environmental factors, and top‐down processes, such as herbivore disturbances. With climate change and overgrazing, the stability of plant community structure and function decreases, and more land at risk of degradation. However, the response of the plant community to interference from native herbivores under similar environmental conditions remains unclear. Plateau pika (Ochotona curzoniae) is an important small rodent inhabiting the alpine meadow of the Qinghai‐Tibetan Plateau, and its disturbance may accelerate the degradation of grassland ecosystems when its population experiences a burst. In this study, we investigated the plant communities, collected and analyzed the soil samples, to explore the effects of plateau pikas' disturbance intensity on species composition and phylogenetic structure of plant communities on the alpine meadow. We utilized the generalized additive model and structural equation model to explain and predict the response of plant phylogenetic structure and species competition to the disturbance of plateau pikas. Our results indicated that plateau pika disturbance altered the dominance of plant groups, increased species substitution, and facilitated coexistence among different species, and it affected deterministic processes, reduced interspecific competition intensity, and promoted the dispersion of phylogenetic structures. These findings suggested that plateau pika, as a small native herbivore, plays a significant role in fostering multi‐species plant communities. Therefore, it is essential to manage plateau pika disturbance intensity to maintain the stability of alpine meadow plant communities, as well as to influence the long‐term succession of grassland ecosystems. This study provides some new evidence for exploring the effects of native small herbivores on the changes in grassland plant communities.

Risk zoning of Gynaephora alpherakii (Lepidoptera: Lymantriidae) on the Qinghai-Tibetan Plateau.

Gynaephora alpherakii (Grum-Grschimailo) (Lepidoptera: Lymantriidae) is a major pest in alpine meadow areas in the Qinghai-Tibetan Plateau (QTP) and causes severe losses in the local livestock production industry. Assessing areas at high risk for G. alpherakii infestation is critical for the effective management of this pest. In this study, an ensemble distribution model was used to analyze areas suitable for G. alpherakii on the QTP. Risk zoning was performed based on the vegetation and environmental conditions in areas with high-occurrence points, and differences between high-occurrence points and other occurrence points were compared. The results revealed that the suitable areas for G. alpherakii on the QTP amounted to 28.27 × 104 hm2, accounting for 10.94% of the total area of the QTP; the area of high-risk was 19.07 × 104 hm2, and these areas were located mainly in the eastern part of the QTP. Qinghai Province had the highest risk, accounting for 77% of the total area identified as high-risk. In terms of habitat, G. alpherakii preferred alpine Kobresia meadows, which have abundant sunshine, loose soil, and scarce precipitation. This study supports efforts to manage G. alpherakii outbreaks and contributes to the ecological protection of the QTP.

Temporal variability and predictability predict alpine plant community composition and distribution patterns.

One of the most reliable features of natural systems is that they change through time. Theory predicts that temporally fluctuating conditions shape community composition, species distribution patterns, and life history variation, yet features of temporal variability are rarely incorporated into studies of species-environment associations. In this study, we evaluated how two components of temporal environmental variation-variability and predictability-impact plant community composition and species distribution patterns in the alpine tundra of the Southern Rocky Mountains in Colorado (USA). Using the Sensor Network Array at the Niwot Ridge Long-Term Ecological Research site, we used in situ, high-resolution temporal measurements of soil moisture and temperature from 13 locations ("nodes") distributed throughout an alpine catchment to characterize the annual mean, variability, and predictability in these variables in each of four consecutive years. We combined these data with annual vegetation surveys at each node to evaluate whether variability over short (within-day) and seasonal (2- to 4-month) timescales could predict patterns in plant community composition, species distributions, and species abundances better than models that considered average annual conditions alone. We found that metrics for variability and predictability in soil moisture and soil temperature, at both daily and seasonal timescales, improved our ability to explain spatial variation in alpine plant community composition. Daily variability in soil moisture and temperature, along with seasonal predictability in soil moisture, was particularly important in predicting community composition and species occurrences. These results indicate that the magnitude and patterns of fluctuations in soil moisture and temperature are important predictors of community composition and plant distribution patterns in alpine plant communities. More broadly, these results highlight that components of temporal change provide important niche axes that can partition species with different growth and life history strategies along environmental gradients in heterogeneous landscapes.

Waning snowfields have transformed into hotspots of greening within the alpine zone

Waning snowfields have transformed into hotspots of greening within the alpine zone

Patterns of foliar fungal diseases and the effects on aboveground biomass in alpine meadow under simulated climate change

1.Global warming and changes in precipitation patterns significantly affect plant fungal diseases, especially plant foliar fungal diseases. Research surrounding the effects of climate change on plants are mostly concentrated on aboveground vegetation and belowground soil microorganisms, with limited attention given to foliar fungal disease. Additionally, little is known whether climate change experiments can simulate the impact of variations on foliar diseases within real natural communities.2.We conducted a long-term experiment to investigate the effect of warming and altered precipitation on plant disease in an alpine grassland on the north-eastern Tibetan Plateau. Our study tracked foliar disease across 26 species of plants including non-legume forbs, legumes, grasses and sedges from 2019 to 2021. Each species was included in a two-factor full factorial experiment manipulating both temperature and precipitation.3.In our study the non-legume forb functional group carried the primary pathogen load, sedges maintained a near zero pathogen load across all investigated scenarios. Warming significantly elevated the pathogen load in legumes and non-legume forbs, while it reduced the pathogen load of grasses. Conversely, decreased precipitation significantly increased the pathogen load of non-legume forbs and increased the pathogen load of grasses. Notably, we found that pathogen load was primarily influenced by the direct effects of warming and precipitation, rather than indirectly through changes in plant community structure. Meanwhile, interannual climate variability exhibited a strong correlation with plant community pathogen loads. Areas experiencing increased temperature and precipitation showed lower fungal disease pressure, whereas regions with elevated temperatures combined with decreased precipitation faced a heightened risk of disease in alpine meadows on the Qinghai-Tibet Plateau.4.Our findings reveal that warming and decreased precipitation led to a reduction in above-ground biomass associated with increased the pathogen load of legumes. This underscores the importance of pathogen effects in both climate change prediction and ecological management.

Artificial Grassland Revegetation Improves Soil Water Retention and Storage Capacity of the Degraded Hillside Alpine Meadow

ABSTRACTThe crucial role of soil water retention and storage in soil hydrology and the water cycle is well established. However, in sensitive and degraded ecosystems like alpine meadows, the effectiveness of revegetation in enhancing these critical functions remains understudied. This study investigates the effects of revegetating severely degraded hillside meadows with artificial grasslands on soil water retention and storage capacity in the Qinghai‐Tibetan Plateau. Soil analyses at a depth of 0–20 cm revealed significant improvements in soil properties after revegetation, with increases in soil organic matter content (86.8%), total porosity (11.9%), capillary porosity (31.6%), and clay content (13.5%). Both the saturated hydraulic conductivity (Ks) and field capacity (FC) increased markedly, by 9.7% and 63.7% in the upper layer (0–10 cm) and 21.7% and 69.6% in the lower layer (10–20 cm), respectively. Structural equation modeling identified bulk density, root mass density, FC, capillary porosity, and clay content as the dominant direct factors influencing Ks with path coefficients of −0.56, 0.30, −0.53, 0.57, and −0.12, respectively, while vegetation cover and aboveground biomass were found to have indirect influences. These findings demonstrate that revegetation with artificial grasslands effectively improves soil water retention and storage capacity in degraded hillside alpine meadows by regulating key soil hydraulic and physical properties. This enhanced water‐holding capacity has significant implications for understanding the dynamics of revegetation by artificial grassland establishment in improving ecosystem health and eco‐hydrological functions in these vulnerable environments. Furthermore, the study provides valuable insights and a theoretical basis for developing ecological restoration solutions for degraded hillside meadows in other alpine regions.

Winter Grazing, Not Fencing or Unicast, Promotes Stability of Microbial Community and Function in the Qilian Mountains of Qinghai‐Xizang Plateau

ABSTRACTIn alpine meadows, microorganisms are essential to sustain the stability of terrestrial geochemical processes and vegetation–soil–microbial systems. The present study in order investigate how various management measures impact the microbial communities' composition and functionality, we utilize metagenomic sequencing techniques to examinate the composition and function of soil microbial communities in the southern Qilian Mountains of the Qinghai‐Xizang Plateau in response to the management practices of fencing enclose (FE), winter grazing (WG), transition zone between natural and artificial grasslands (TZ), and artificial unicast oats (AU). Vegetation diversity and soil physicochemical characteristics were dramatically altered by the management measures. The prokaryotic community structure was considerably similar in FE and WG, as well as in TZ and AU. Near‐natural (FE) and artificial establishment (AU) disturbances changed the fungal community structure. Enzymes related to carbon metabolism did not respond significantly to the management measures, whereas those related to nitrogen metabolism did not respond significantly in TZ and AU. The relative abundance of enzymes participating in nitrogen metabolism was higher under TZ and AU than under FE and WG. We concluded that grassland management measures altered the structure of aboveground graminoid and leguminous vegetation communities and belowground biomass allocation, resulting in changes in K uptake, causing striking changes in the structure of fungal communities and nitrogen‐metabolizing enzymes; moderate disturbance (WG) was beneficial for maintaining the stability of microbial communities in alpine grasslands.

Spatio-temporal patterns and driving factors of green development level in alpine meadow regions: A case study in Gannan Tibetan Autonomous Prefecture

Green development is an approach that harmonizes human beings with nature and leads to sustainable social and economic development. However, the factors influencing the level of green development are uncertain due to regional differences, especially in the alpine meadow regions. To explore the factors affecting green development in the alpine meadow region, we took the Gannan Tibetan Autonomous Prefecture as an example. Through a green development level evaluation index system, the DPSIR (Driver, Pressure, State, Impact, and Response) was constructed to comprehensively evaluate and analyze the green development level of the study area from 1990 to 2020. On this basis, the key influencing factors of the green development level was analyzed based on the GeoDetector. The findings indicate that the total level of green development in Gannan has an upward trend within the range of 0.044–0.535, moving towards high quality and sustainable development. Except for 2005, the spatial clustering characteristics of the green development level did not display obvious high values of spatial autocorrelation. The green development space is concentrated and stable, and the centre of gravity is in Zhuoni. The impact and response dimensions make the greatest contribution to green development. Different evaluation indicators have different impacts on green development during the study period. Specifically, people’s productive lives, the impact of social production and positive policy responses are the main factors contributing to green development. The findings will provide theoretical basis and case support for ecological security and green sustainable development in the alpine meadow regions.

Spectral Characteristics and Identification of Degraded Alpine Meadow in Qinghai–Tibetan Plateau Based on Hyperspectral Data

Grassland degradation poses a significant challenge to achieving the Sustainable Development Goals (SDGs) on the Qinghai–Tibetan Plateau (QTP). Effective monitoring of grassland degradation is essential for ecological restoration. Hyperspectral technology offers efficient and accurate identification of degradation. However, the influence of observation time, data analysis methods and classification techniques on the accuracy of identifying alpine grasslands remains unclear. In this study, the spectral reflectance of degraded alpine meadow, alpine meadow, alpine shrub and Tibetan barley was measured from May to September 2023 using a ground spectrometer in the northeastern QTP. First-order derivatives (FDR) and continuum removal were applied to the spectra, and characteristic parameters and vegetation indices were calculated. Support vector machine (SVM), random forest (RF), artificial neural network (ANN) and decision tree (DT) were then used to compare the classification accuracy between different months, transformation methods and characteristic parameters. The results showed that the spectral reflectance peaked in July, with significant differences in the near infrared (NIR) bands between alpine meadow and degraded alpine meadow. Alpine shrub and Tibetan barley showed greater differences in reflectance compared to other vegetation types, especially in the NIR bands. Data transformations improved reflectance and absorption characteristics in the NIR and visible bands. Indices such as DVI, RVI and NDGI effectively differentiated vegetation types. Optimal accuracy for the identification of degraded alpine meadow in July was achieved using FDR transformations and ANN or SVM for classification. This study provides methodological insights for monitoring grassland degradation on the QTP.

Subfossil pollen spectra in the altitudinal belts of the Sikhote-Alin

This paper presents the characteristics and comparison of subfossil pollen spectra of modern plant communities in the altitudinal zones of the Northern Sikhote-Alin and the Southern Sikhote-Alin, using the cases of the Tordoki-Yani Mountain (absolute altitude 2090 m) and Oblachnaya Mountain (absolute altitude 1858 m). All pollen spectra from high mountains reflect the forests caused by long-distance transport of tree pollen. Due to the abundance of Picea pollen, the pollen spectra of the mountain tundra and upper part of the subalpine belts of the Northern Sikhote-Alin correspond to the most common type of vegetation at the upper forest borde r–the high-mountain spruce forest with Betula lanata, where Pinus pumila thickets can reach from the overlying belt. The largest amount of allochthonous pollen was found in the pollen spectra on the site without forest canopy. The pollen of broad-leaved trees was brought to high hypsometric levels by mountain-valley winds, rising air currents, from the underlying belts. The quantitative content of pollen of the main dominants of each altitudinal plant zone does not always accurately reflect the role of these taxa in the composition of the communities. The pollen productivity of Betula lanata exceeds the pollen productivity of the main forest forming species in all altitudinal zones, with the exception of the stone birch forests, therefore the share of its participation in the composition of the pollen spectra is overestimated. In the studied pollen spectra the content of Larix pollen is greatly underestimated compared to the role of this species in the forest stand, especially in soil samples from larch forest. It is associated with low pollen productivity, distribution and fossilization characteristics.

Estimating Grassland Carrying Capacity in the Source Area of Nujiang River and Selinco Lake, Tibetan Plateau (2001–2020) Based on Multisource Remote Sensing

Estimating the spatiotemporal variations in natural grassland carrying capacity is crucial for maintaining the balance between grasslands and livestock. However, accurately assessing this capacity presents significant challenges due to the high costs of biomass measurement and the impact of human activities. In this study, we propose a novel method to estimate grassland carrying capacity based on potential net primary productivity (NPP), applied to the source area of the Nujiang River and Selinco Lake on the Tibetan Plateau. Initially, we utilize multisource remote sensing data—including soil, topography, and climate information—and employ the random forest regression algorithm to model potential NPP in areas where grazing is banned. The construction of the random forest model involves rigorous feature selection and hyperparameter optimization, enhancing the model’s accuracy. Next, we apply this trained model to areas with grazing, ensuring a more accurate estimation of grassland carrying capacity. Finally, we analyze the spatiotemporal variations in grassland carrying capacity. The main results showed that the model achieved a high level of precision, with a root mean square error (RMSE) of 4.89, indicating reliable predictions of grassland carrying capacity. From 2001 to 2020, the average carrying capacity was estimated at 9.44 SU/km2, demonstrating a spatial distribution that decreases from southeast to northwest. A slight overall increase in carrying capacity was observed, with 65.7% of the area exhibiting an increasing trend, suggesting that climate change has a modest positive effect on the recovery of grassland carrying capacity. Most of the grassland carrying capacity is found in areas below 5000 m in altitude, with alpine meadows and alpine meadow steppes below 4750 m being particularly suitable for grazing. Given that the overall grassland carrying capacity remains low, it is crucial to strictly control local grazing intensity to mitigate the adverse impacts of human activities. This study provides a solid scientific foundation for developing targeted grassland management and protection policies.