Grassland Ecology Research Articles

Effects of grassland degradation on diversity of arbuscular mycorrhizal fungi of a pioneer plant.

Arbuscular mycorrhizal fungi (AMF) are obligate symbionts that engage in crucial interactions with plants, playing a vital role in grassland ecology. Our study focuses on the pioneer plant Agropyron cristatum, and we collected soil samples from four degraded grasslands in Yudaokou to investigate the response of community composition to the succession of degraded grasslands. We measured the vegetation status, soil physical and chemical properties, AMF colonization, and spore density in different degraded grasslands. High-throughput sequencing was employed to analyze AMF in soil samples. Correlations among community composition, soil characteristics, and plant factors were studied using principal component and regression analyses. The distribution of AMF in grasslands exhibited variation with different degrees of degradation, with Glomus, Scutellospora, and Diversispora being the dominant genera. The abundance of dominant genera in AMF also varied, showing a gradual increase in the relative abundance of the genus Diversispora with higher degradation levels. AMF diversity decreased from 27.7% to 12.4% throughout the degradation process. Among 180 samples of Agropyron cristatum plants, AMF hyphae and vesicles displayed the highest infection status in non-degraded grasslands and the lowest in severely degraded ones. Peak AMF spore production occurred in August, with maximum values in the 0-10-cm soil layer, and the highest spore densities were found in lightly degraded grasslands. Apart from pH, soil factors exhibited a positive correlation with AMF infection during grassland degradation. Furthermore, changes in AMF community composition were jointly driven by vegetation and soil characteristics, with vegetation coverage and soil organic carbon significantly impacting AMF distribution. Significant differences in AMF variables (spore number and diversity index) were also observed at different soil depths. Grassland successional degradation significantly influences AMF community structure and composition. Our future focus will be on understanding response mechanisms and implementing improvement methods for AMF during grassland degradation and subsequent restoration efforts.

Disembedding and Disentangling Grassland Valuation: Insights into Grassland Management Institutions and Ecological Research in China

After two decades of implementing top-down grassland restoration projects focused on reducing livestock numbers and pastoralist populations, the Chinese government’s well-funded efforts have not significantly reversed grassland degradation. This study reviews the institutional changes in grassland management over the past forty years, highlighting the Livestock and Grassland Double Contract Household Responsibility System of the early 1980s and the Grassland Ecological Reward and Compensation Policy introduced in 2011. It demonstrates how these institutional transformations have shaped pastoralists’ evolving understanding of grassland value and reveals that commodifying grassland’s economic and ecological value has led to the capitalization of nature, disembedding husbandry from grassland production, and undermining the effectiveness of conservation projects. This article also showcases the development of grassland ecology research in China, noting its increasing detachment from a holistic understanding of ecosystems and the interdisciplinary needs of management practices. The disjunction between grassland ecology research and practical management has resulted in a lack of techniques aligned with local ecological and socioeconomic contexts. This article champions active engagement with and protection of pastoralist communities to reintegrate grasslands’ true economic and ecological value into management practices, thereby effectively restoring degraded grasslands and achieving sustainable management.

Ecology of Grasslands of Central Nicobar

The tropical grasslands of the Central Nicobar Islands have long been perceived as anthropogenic formations, which has influenced their conservation and management in the region. Despite their ecological and cultural significance, these grasslands have received limited scholarly attention, rendering them vulnerable to alternative land uses and conversion. This study aims to address these knowledge gaps through an extensive vegetation survey, soil analysis, and ethnographic research. The outcomes of the vegetation survey and soil analysis reveal that these grasslands are the result of serpentine soil formations, managed by Nicobari communities by fire. The ethnographic research reveals the cultural importance of the grassland commons and its governance through the tuhet system. Further, the study shows that the access regimes have undergone a rapid transformation during post-tsunami resettlement, endangering local instuitions and the sustainability of the grassland commons of the Nicobars.

Analysis of the Heterogeneous Coordination between Urban Development Levels and the Ecological Environment in the Chinese Grassland Region (2000–2020): A Case Study of the Inner Mongolia Autonomous Region

Scientifically identifying the impact of urban development levels on the ecological environment in China’s grassland regions from a classification perspective is crucial for stabilizing grassland ecosystems and optimizing urban development in grassland cities. Using the Inner Mongolia Autonomous Region as a case study, this research constructs a conceptual analysis framework for the coordinated state between the urban development level and the ecological environment in China’s grassland regions based on the theory of dual economic structures. Employing the Granger causality test, nonlinear fitting, and coupling coordination degree model methods, the heterogeneity and coordination between urban development levels and ecological environment in China’s grassland areas from 2000 to 2020 are comprehensively analyzed. The findings reveal the following: (1) Capital-type central cities and growing resource-based cities, with high levels of development, positively nurture the grassland ecology, exhibit high labor mobility, and experience low endogenous and exogenous pressures, resulting in high coordination. (2) Pure agro-pastoral cities, with low development levels, negatively impact the grassland ecology, have low labor mobility, and face high endogenous and exogenous pressures, resulting in low coordination. (3) Regional central cities, with moderate development levels, exert a neutral counterbalance effect on the grassland ecology, with opposing endogenous and exogenous pressures, leading to moderate coordination. (4) When the impact relationship ranges from “positive-neutral-negative,” the endogenous and exogenous pressures on the grassland ecology by declining resource-based cities and developing agro-pastoral cities are determined by their specific development levels, showing variations from “large → balance → small” to “small → balance → large,” with coordination fluctuating between “high-moderate-low”. (5) Special ecological cities are less affected by urban development levels, with coordination levels determined by the ecological foundation. Analyzing the heterogeneous coordination between urban development levels and the ecological environment for different types of cities in grassland regions is significant for improving the overall quality of the grassland ecological environment and exploring distinctive urban development models.

How do short-term and long-term factors impact the aboveground biomass of grassland in Northern China?

The aboveground biomass (AGB) of grassland, a crucial indicator of productivity, is anticipated to widespread changes in key ecosystem attributes, functions and dynamics. Variations in grassland AGB have been extensively documented across various spatial and temporal scales. However, a precise method to disentangle long-term effects from short-term effects on grassland AGB and assess the attribution of explanatory factors for AGB change remains elusive. This study aimed to quantify the impact of key climatic factors, soil properties, and grazing intensity on grassland AGB changes, utilizing data spanning the 1980s and the 2000s in Northern China. The Co-regression model was explored to separate the long-term effects and short-term effects of grassland AGB, while the Generalized Linear Model (GLM) was utilized to analyze the contributions of key variables to AGB. This approach effectively avoids issues related to regression to the mean and mathematical coupling. The results revealed that the influence of climatic variables, soil texture and grazing intensity on grassland AGB changes could be decomposed into long-term, short-term and random effects. Long-term effects explained 73.6% of AGB variation, whereas short-term effect only accounted for 5.9% of AGB change. Additionally, the short-term effect was divided into direct and indirect effects, with the direct effect explaining 1.3% of AGB variation, and the indirect effect explained 4.6% of AGB dynamics. The relative importance of key variables in grassland AGB was assessed, identifying soil parameters and precipitation as the main driving factors in the study area. This study introduces a robust methodology to enhance model performance in distinguishing long-term and short-term effects on grassland AGB, contributing to the sustainable development of grassland ecology in similar regions.

Enhancing Livestock Detection: An Efficient Model Based on YOLOv8

Maintaining a harmonious balance between grassland ecology and local economic development necessitates effective management of livestock resources. Traditional approaches have proven inefficient, highlighting an urgent need for intelligent solutions. Accurate identification of livestock targets is pivotal for precise livestock farming management. However, the You Only Look Once version 8 (YOLOv8) model exhibits limitations in accuracy when confronted with complex backgrounds and densely clustered targets. To address these challenges, this study proposes an optimized CCS-YOLOv8 (Comprehensive Contextual Sensing YOLOv8) model. First, we curated a comprehensive livestock detection dataset encompassing the Qinghai region. Second, the YOLOv8n model underwent three key enhancements: (1) incorporating a Convolutional Block Attention Module (CBAM) to accentuate salient image information, thereby boosting feature representational power; (2) integrating a Content-Aware ReAssembly of FEatures (CARAFE) operator to mitigate irrelevant interference, improving the integrity and accuracy of feature extraction; and (3) introducing a dedicated small object detection layer to capture finer livestock details, enhancing the recognition of smaller targets. Experimental results on our dataset demonstrate the CCS-YOLOv8 model’s superior performance, achieving 84.1% precision, 82.2% recall, 84.4% mAP@0.5, 60.3% mAP@0.75, 53.6% mAP@0.5:0.95, and 83.1% F1-score. These metrics reflect substantial improvements of 1.1%, 7.9%, 5.8%, 6.6%, 4.8%, and 4.7%, respectively, over the baseline model. Compared to mainstream object detection models, CCS-YOLOv8 strikes an optimal balance between accuracy and real-time processing capability. Its robustness is further validated on the VisDrone2019 dataset. The CCS-YOLOv8 model enables rapid and accurate identification of livestock age groups and species, effectively overcoming the challenges posed by complex grassland backgrounds and densely clustered targets. It offers a novel strategy for precise livestock population management and overgrazing prevention, aligning seamlessly with the demands of modern precision livestock farming. Moreover, it promotes local environmental conservation and fosters sustainable development within the livestock industry.

Analysis of spatio-temporal changes in net primary productivity and their driving factors in ecological functional areas of the Yellow River Basin

The Yellow River Basin (YRB) is an important region for both ecological and economic growth in China, and a healthy and stable ecological environment is fundamental to achieving high-quality development. Investigating the spatio-temporal changs of vegetation carbon sinks in the YRB is necessary to improve understanding of the regional carbon cycle. This study analyzed the YRB using the Google Earth Engine (GEE) platform. The basin was divided into sections based on ecological function regionalization schemes. We applied Theil-Sen median trend analysis and Spearman correlation analysis, along with the lasso regression model, to examine the NPP's temporal and spatial patterns and its driving factors in these regions. The objective was to examine the NPP’ s temporal and spatial patterns and its driving factors in these regions, identifying commonalities within regions and differences between regions, while analyzing in a targeted manner the lack of vegetation carbon sequestration in ecological areas. This study highlighted the importance of ecological engineering in ecological civilization and carbon neutrality, providing scientific theoretical support and a decision-making basis for the realization of carbon neutrality. The research results indicate significant upward trends (p<0.001) in both the average annual NPP (AANPP) growth rate (57.98%) and the total annual NPP (TANPP) growth rate (41.9%) in the YRB from 2001 to 2020. The multi-year average NPP (MYANPP) exhibit a spatial distribution with high values in the south and low values in the north. The spatial distribution of NPP exhibits notable spatial aggregation and heterogeneity, where regions demonstrating improvement trends constitute 93.01% of the area, and approximately 79.73% of this region displays low volatility. A high-value area is concentrated in the Agroecological Zone of the Fenwei Basin (I-11), the Loess Plateau Agriculture and Grassland Ecological Zone (I-12), and the Qinba Mountains Deciduous and Evergreen Broad-leaved Forest Ecological Zone (I-15), with significant spatial differences. Temperature, precipitation, and forests are the foremost elements affecting NPP in the YRB, exhibiting positive correlations. Conversely, farmland displays negative correlations. Overall, NPP shows an increasing trend in all ecological function areas, and the NPP of the YRB shows a trend of improvement as a whole, as the ecological environment of the YRB has improved significantly.

Comparison and Evaluation of Five Global Land Cover Products on the Tibetan Plateau

The Tibetan Plateau (TP) region contains maximal alpine grassland ecology at the mid-latitudes. This region is also recognized as an ecologically fragile and sensitive area under the effects of global warming. Regional climate modeling and ecosystem research depend on accurate land cover (LC) information. In order to obtain accurate LC information over the TP, the reliability and precision of five moderate/high-resolution LC products (MCD12Q1, C3S-LC, GlobeLand30, GLC_FCS30, and ESA2020 in 2020) were analyzed and evaluated in this study. The different LC products were compared with each other in terms of areal/spatial consistency and assessed with four reference sample datasets (Geo-Wiki, GLCVSS, GOFC-GOLD, and USGS) using the confusion matrix method for accuracy evaluation over the TP. Based on the paired comparison of these five LC datasets, all five LC products show that grass is the major land cover type on the TP, but the range of grass coverage identified by the different products varies noticeably, from 43.35% to 65.49%. The fully consistent spatial regions account for 43.72% of the entire region of the TP, while, in the transition area between grass and bare soil, there is still a large area of medium-to-low consistency. In addition, a comparison of LC datasets using integrated reference datasets shows that the overall accuracies of MCD12Q1, C3S-LC, GlobeLand30, GLC_FCS30, and ESA2020 are 54.29%, 49.32%, 53.03%, 53.73%, and 60.11%, respectively. The producer accuracy of the five products is highest for grass, while glaciers have the most reliable and accurate characteristics among all LC products for users. These findings provide valuable insights for the selection of rational and appropriate LC datasets for studying land-atmosphere interactions and promoting ecological preservation in the TP.

Effects of insecticide spray drift on arthropod prey resources of birds in grasslands in Minnesota

AbstractSoybean aphid (Aphis glycines) insecticides are used throughout the Upper Midwest and Great Plains regions of North America, including the farmland region of Minnesota, USA, to combat insect pests. These broad‐spectrum, foliar spray insecticides have the potential to drift beyond target fields into nearby grassland cover where birds and other insectivores forage. Arthropods serve important roles in grassland ecology and are susceptible to mortality and sublethal effects from exposure to these pesticides. Our objective was to assess effects of soybean aphid insecticides on grassland arthropods, especially those that are important in grassland bird diets. We measured the abundance, consumable biomass, and family richness of insects and spiders in grasslands adjacent to soybean fields in an agricultural landscape. Soybean fields were treated with chlorpyrifos and lambda‐cyhalothrin, which were the 2 most common foliar pesticides used to control soybean aphids in Minnesota. We compared measures at focal sites to samples collected at reference sites adjacent to corn fields not sprayed for aphids during 3 periods in mid‐to‐late summer: 1–3 days before spraying, 3–5 days post‐spraying, and 19–21 days post‐spraying. The abundance of arthropods in focal grasslands was lower 3–5 days after pesticide applications. Coleoptera family richness at focal sites was also lower than at reference sites 3–5 days after pesticide applications. These measures 19–21 days after application were similar to pre‐spraying levels, indicating that arthropod populations rebounded during this period. Measures of consumable dry biomass, bird prey abundance, bird prey biomass, family richness of Araneae, family richness of Hemiptera, and family richness of Orthoptera were not different between focal and reference sites after spraying. Our results reveal that reductions in arthropod food abundance for grassland birds are associated with pesticide applications up to 5 days after spraying. We suggest that natural resource managers factor proximity to row crop fields and susceptibility to pesticide drift into decisions about where to add grassland cover to landscapes.

Research on Classification of Grassland Degeneration Indicator Objects Based on UAV Hyperspectral Remote Sensing and 3D_RNet-O Model.

Real-time and high-precision land cover classification is the foundation for efficient and quantitative research on grassland degradation using remote sensing techniques. In view of the shortcomings of manual surveying and satellite remote sensing, this study focuses on the identification and classification of grass species indicating grassland degradation. We constructed a UAV-based hyperspectral remote sensing system and collected field data in grassland areas. By applying artificial intelligence technology, we developed a 3D_RNet-O model based on convolutional neural networks, effectively addressing technical challenges in hyperspectral remote sensing identification and classification of grassland degradation indicators, such as low reflectance of vegetation, flat spectral curves, and sparse distribution. The results showed that the model achieved a classification accuracy of 99.05% by optimizing hyperparameter combinations based on improving residual block structures. The establishment of the UAV-based hyperspectral remote sensing system and the proposed 3D_RNet-O classification model provide possibilities for further research on low-altitude hyperspectral remote sensing in grassland ecology.

Biological soil crusts and their potential applications in the sand land over Qinghai-Tibet Plateau

The Qinghai-Tibet Plateau is now experiencing ecological degradation risks as a result of climate change and human activities. The alpine grassland ecology in permafrost zones is fragile and susceptible to deterioration due to its high altitude, low temperature, and limited oxygen, which complicates the repair of damaged land. Biological soil crusts (BSCs) are crucial for land restoration in plateau regions because they can thrive in harsh conditions and have environmentally beneficial traits. Inoculated biological soil crust (IBSC) has shown success in low-altitude desert regions, but may not be easily duplicated to the plateau environment. Therefore, it is essential to do a comprehensive and multifaceted analysis of the basic theoretical comprehension and practical application of BSCs on the Tibetan Plateau. This review article aims to provide a brief summary of the ecological significance and the mechanisms related to the creation, growth, and progression of BSCs. It discusses the techniques used for cultivating BSCs in laboratories and using them in the field, focusing on the Qinghai-Tibet Plateau circumstance. We thoroughly discussed the potential and the required paths for further studies. This study may be used as a basis for selecting suitable microbial strains and accompanying supplemental actions for implementing IBSCs in the Qinghai-Tibet Plateau.

Grassland Ecological Management and Utilization for Sustainability

Grasslands, covering 40% of the land surface area [...]

Impacts and mechanism of the new round of grassland tenure confirmation on grassland ecology:Take the pastural area of Inner Mongolia as an example

Impacts and mechanism of the new round of grassland tenure confirmation on grassland ecology:Take the pastural area of Inner Mongolia as an example

Innovation of grassland ecological governance systems: Synergy between government regulation and grassroots governance

Previous studies have revealed that grassroots governance has played active roles in protecting grassland ecology, however, the synergistic relationship between government regulation and grassroots governance in regulating herders' overgrazing behavior has been overlooked. Our study addresses this research gap using the fixed effects model based on a panel dataset of 711 herder households in pastoral areas of China. The findings show that the grassroots governance measures, i.e. informal institutions and punishment, can reduce overgrazing by 32.8% and 35.5%, respectively. Regarding government regulation measures, grazing monitoring by higher-level governments reduces overgrazing, in contrast to the positive effect of hiring grassland managers. We also find that grazing monitoring from higher-level governments weakens the inhibitory effect of grassroots informal institutions and punishment on herders' overgrazing; grassroots informal institutions attenuate the positive effect of hiring grassland managers on overgrazing. Hence, this study suggests that the government should be more attentive toward the coordinated development of government regulation and grassroots governance rather than dealing separately with the two.

Wakehurst's North American Prairie

SummaryThe theory behind the ecology and plant associations of prairie grasslands is summarised, and compared with conventional horticultural perennial planting.

Effects of Enclosure on Grassland Ecological and Economic Benefits in Northern China

Effects of Enclosure on Grassland Ecological and Economic Benefits in Northern China

Climate-induced shifts in grassland bird nesting phenology have implications for grassland management

Grasslands are among the most impacted ecosystems globally. In the midcontinent of North America, a > 80% loss of grasslands has made their conservation a major priority for resource managers. Grassland ecosystems evolved under periodic disturbances; consequently, grassland management often involves regular actions such as grazing, haying, or burning to maintain ecosystem integrity. The timing of such practices has direct implications on grassland ecology, agricultural economics, and survival and fecundity of grassland nesting birds (hereafter grassland birds). We conducted a meta-analysis on the nesting phenology of grassland birds throughout North America, focusing on nest-survival literature. We constructed a well-fitting model to predict median date of expected nest departure (hereafter fledge date) for grassland birds across the midcontinent. Predictions from our model demonstrate considerable spatial variation in median nesting phenology that is predictable using a spatially explicit spring phenology index. Median fledge dates were 8 or 13 days earlier in years of extreme weather conditions (dry or wet, respectively) than in years of average conditions. Species that generally nest in taller vegetation tended to have later median nest phenologies than those using shorter vegetation. Our results incorporate the most rigorous information available in the literature on nesting phenology of 36 grassland bird species and improve information available to managers about nesting phenology of grassland birds in the midcontinent of North America. Our predictions approximate the day when one-half of the nesting efforts would be complete for a given area within the midcontinent grasslands and can inform management and conservation decisions about the timing of management actions in grassland ecosystems.

Different effects of long-term grazing exclusion and growth stages on soil fungi and bacteria in an alpine steppe on the Qinghai-Tibetan Plateau

Changes in soil microorganisms caused by enclosure have long been an important topic in grassland ecology. However, few studies have described the responses of the soil microbial community composition, functional groups, and co-occurrence networks at different growth stages to long-term grazing exclusion or compared the indicative abilities of diversity and network parameters on soil ecosystem functions after grazing exclusion. In this study, we conducted a field experiment to evaluate the response of soil microbes to long-term grazing exclusion in an alpine steppe on the Qinghai-Tibetan Plateau. Our results showed that both soil fungal and bacterial community compositions at different growth stages showed significant differences. However, the enclosure only altered the fungal community composition. Differences in soil microbial functional groups between fungi and bacteria were also detected. The leading group in soil fungi was governed by grazing exclusion, and most bacterial functional groups showed significant differences between the growth stages. The co-occurrence network patterns of the fungi and bacteria differed significantly. Unexpectedly, the enclosure did not significantly alter the fungal or bacterial co-occurrence networks. Network parameters had a stronger ability to indicate soil ecosystem functions than the diversity index, displaying better relationships between network parameters and soil organic carbon and nitrate. These findings suggest that elucidating the responses of soil microbes at different growth stages is necessary to comprehensively understand soil ecosystems after long-term grazing exclusion in the alpine steppe.

UAV Monitoring Topsoil Moisture in an Alpine Meadow on the Qinghai–Tibet Plateau

Soil moisture is one of the most critical soil components for sustained plant growth and grassland management. Unmanned aerial vehicles (UAVs) are gradually replacing manual labor in various aspects of grassland management. However, their potential for monitoring soil moisture in grasslands remains largely unexplored. High vegetation coverage and frequent rainfall in the Tibetan Plateau pose a challenge for personnel working in alpine meadows. To explore the potential of UAV technology for soil moisture detection in these areas, we conducted a rainfall reduction experiment in Maqu County, China to understand the relationships among soil moisture, vegetation coverage, and visible-light images captured using UAVs. The findings indicated a significant correlation between topsoil moisture and the brightness values in visible-light images acquired by UAVs (p &lt; 0.0001). These results demonstrated that visible-light brightness, vegetation coverage, rainfall reduction, and aboveground biomass can be utilized for estimating the topsoil moisture using these images (y = −0.2676 × Brightness + 0.2808 × Vegetation coverage −0.1862 × Rainfall reduction + 0.1357 × Aboveground biomass + 37.77). The model validation worked well (E = 0.8291, RS = −3.58%, RMA = 10.38%, RMSE = 3.5878, Pearson’s r = 0.9631, PSI = 0.0125). This study further addresses the problem of topsoil moisture measurement in flat areas of mesoscale moist alpine meadows and is expected to facilitate the widespread adoption of UAV use in grassland ecology research.

Study on Forest and Grassland Ecological Space Structure in Eyu Mining Area and Potential Alternatives for Enhancing Carbon Sequestration

Optimizing the connectivity-carbon sequestration coupling coordination of forest and grassland ecological spaces (F&amp;GES) is a crucial measure to enhance carbon sequestration effectively in mining areas. However, the prevailing strategies for optimizing F&amp;GES often overlook the connectivity-carbon sequestration coupling coordination of the network. Therefore, this study aimed to propose a novel restoration plan to improve the connectivity-carbon sequestration coupling coordination of existing networks. Taking a typical mining area in northwestern China (Eyu County) as an example, we extracted the existing F&amp;GES based on remote sensing ecological indicators and ecological risk assessments. Subsequently, we optimized the network using the connectivity-carbon sequestration coupling coordination degree (CSCCD) model from the perspective of connectivity-carbon sequestration coupling coordination, proposed potential alternative optimization schemes, and evaluated the optimization effects. The results showed that the range of Eyu County’s F&amp;GES structure had been determined. Ecological source sites with better carbon sequestration effects were primarily distributed in the central and northeastern parts of Eyu County. After optimization, the network added 26 ecological patches, and the added area reached 641.57 km2. Furthermore, the connectivity robustness, edge restoration robustness, and node restoration robustness of the optimized network were significantly improved, and the carbon sequestration effect of the forest and grassland ecological space was increased by 6.78%. The contribution rate of ecological source sites was 97.66%, and that of ecological corridors was 2.34%. The CSCCD model proposed in this study can effectively improve the carbon sequestration effect in mining areas, promote carbon neutrality, and save network optimization time while improving efficiency. This restoration strategy is also applicable to forest and grassland ecosystem management and optimization of ecological spaces in other mining areas, which has positive implications for promoting ecological civilization construction and sustainable development.