Grassland Research Articles

Grazing and precipitation addition interactions alleviate dominant species overgrowth and promote community productivity and biodiversity in a typical steppe

Grazing and precipitation are pivotal factors influencing the productivity and biodiversity of grassland ecosystems, largely through their effects on the growth and reproduction of dominant species. Approximately 50 % of terrestrial ecosystems are concurrently affected by grazing and precipitation addition (PA), yet the interactive effects of these factors remain underexplored. To elucidate the combined impacts of grazing and PA on the growth of dominant species and their influence on community structure and function, we initiated a four-year combined grazing and PA experiment based on a long term of grazing experiment in a typical steppe. The synergistic interaction between PA and grazing enhanced canopy diameter (CD), tiller density (TD), and seedling density (SD) in dominant species, while decreasing reproductive branch density (RB). Conversely, an antagonistic interaction increased plant height (PH) and TD but reduced SD. These responses suggest that dominant species adapt to combined grazing and PA pressures by shifting growth strategies towards lateral growth and asexual reproduction. The growth characteristics of dominant species exhibited four response patterns to grazing and PA interactions: full saturation, sufficient saturation, equal saturation, and deficit saturation, each with three corresponding thresholds: adaptation, optimum, and saturation points. Grazing decreased the precipitation response thresholds for PH, CD, RB, and population density, while increasing the optimal points for TD and SD. These changes in the growth of the dominant species resulted in a 33 % reduction in the aboveground biomass (AGB) of the community and triggered a 18 % increase in the coupling index between AGB and species richness within the community. Our findings highlight the role of dominant species in facilitating community adaptation to increased precipitation and rotational grazing, offering critical insights for developing sustainable grazing strategies under climate change.

The Effects of swnN Gene Function of Endophytic Fungus Alternaria oxytropis OW 7.8 on Its Swainsonine Biosynthesis

The swnN gene in the endophytic fungus Alternaria oxytropis OW 7.8 isolated from Oxytropis glabra was identified, and the gene knockout mutant ΔswnN was first constructed in this study. Compared with A. oxytropis OW 7.8, the ΔswnN mutant exhibited altered colony and mycelia morphology, slower growth rate, and no swainsonine (SW) in mycelia. SW was detected in the gene function complementation strain ΔswnN/swnN, indicating that the function of the swnN gene promoted SW biosynthesis. Six differentially expressed genes (DEGs) closely associated with SW synthesis were identified by transcriptomic analysis of A. oxytropis OW 7.8 and ΔswnN, with P5CR, swnR, swnK, swnH2, and swnH1 down-regulating, and sac up-regulating. The expression levels of the six genes were consistent with the transcriptomic analysis results. Five differential metabolites (DEMs) closely associated with SW synthesis were identified by metabolomic analysis, with L-glutamate, α-ketoglutaric acid, and L-proline up-regulating, and phosphatidic acid (PA) and 2-aminoadipic acid down-regulating. The SW biosynthetic pathways in A. oxytropis OW 7.8 were predicted and refined. The results lay the foundation for in-depth elucidation of molecular mechanisms and the SW synthesis pathway in fungi. They are also of importance for the prevention of locoism in livestock, the control and utilization of locoweeds, and the protection and sustainable development of grassland ecosystems.

Precipitation-induced biomass enhancement and differential allocation in Inner Mongolia's herbaceous and shrub communities

Changes in precipitation patterns induced by global climate change have profound implications for the structure and function of grassland ecosystems. However, the relationship between plant diversity and ecosystem function across different grassland types, particularly those with varying plant compositions and dominant species, remains inadequately understood. To address this knowledge gap, a five-year experimental manipulation of precipitation was conducted within herbaceous and shrub communities in the desert grasslands of Inner Mongolia. We found that increased precipitation significantly enhances aboveground biomass (AGB), belowground biomass (BGB), and community total biomass (CTB) in both herbaceous and shrub communities. In herbaceous communities, increased precipitation led to a disproportionate increase in both aboveground and belowground biomass, supporting the optimal allocation hypothesis. Structural equation modeling (SEM) further elucidated that precipitation regulates AGB and CTB through species richness and functional traits in herbaceous communities. In shrub communities, precipitation influences AGB, BGB, and CTB by affecting species richness and soil water content. This study highlights the critical role of precipitation in shaping biomass dynamics and allocation strategies within herbaceous and shrub communities in desert steppe of Inner Mongolia. These findings provide essential insights into the potential responses of desert grassland ecosystems to ongoing climate change.

A bibliometric analysis for remote sensing applications in bush encroachment mapping of grassland and savanna ecosystems

AbstractGrasslands and savannas are experiencing transformation and degradation due to bush encroachment (BE). BE has been monitored using restrictive traditional techniques that include field surveys and manual long-term observations. Owing to the limitations of traditional techniques, remote sensing (RS) is an attractive alternative to assess BE because of its generally high precision and return interval, cost-effectiveness, and availability of historical data archives. Furthermore, RS has an added advantage in its ability of acquiring global coherent data in near-real time compared to the snapshot acquisition mode with traditional surveying techniques. Despite its extensive application and vast possibilities, a critical synthesis for RS successes, shortcomings, and best practices in mapping BE in savannas and grasslands is lacking. Thus, broadly, the direction, which this type of investigation has taken over the years is largely unknown. This study sought to connect and measure the progress RS has made in mapping BE in grassland and savanna ecosystems through bibliometric analysis. One hundred and twenty-three peer-reviewed English written documents from the Web of Science and Scopus databases were evaluated. The study revealed 13.05% average annual publication growth, indicating that RS and BE mapping research in grasslands and savannas has been increasing over the survey period. Most published studies came from the USA, while the rest came from South Africa, China, and Australia. The results indicate that BE has been extensively mapped in grasslands and savannas using coarse to medium resolution data. As a result, there is a weak relationship (r² = 0.324) between the dependent variable (aerial images) and the independent variable (percentage of woody cover). This connotes the need to improve BE assessments in grasslands and savannas by integrating recent high-resolution data, machine learning algorithms and artificial intelligence.

Impact of naphthalene on soil fauna diversity: Consequences for ecosystem functioning and carbon cycling in grasslands

Soil fauna, key indicators of grassland ecosystem health, face significant threats from the vast amounts of chemical pollutants released by human activities. These organisms are crucial for fundamental processes such as litter decomposition and carbon cycling. However, the response of soil animal communities and their functional dynamics to environmental chemical stress remains poorly understood. To investigate this, we conducted a naphthalene addition and litterbag experiment in the Bashang Grassland, located on the southern Inner Mongolia Plateau, to analyze its effects on soil fauna and litter decomposition. The investigated soil fauna groups included Arachnida (Arachnids), Insecta (Insects), Collembola (Springtails), Enoplea (enopleans), and Chromadorea (chromadoreans). The litter composition included Leymus chinensis, Stipa krylovii, Artemisia, Saussurea amara, and Artemisia giraldii. The findings indicated that a high diversity of soil fauna enhanced the decomposition of litter and the release of organic carbon from the litter. While the addition of naphthalene decreased both the abundance of soil fauna and the rate of litter decomposition, it specifically increased the relative proportion of Collembola (Springtails). Microfauna and mesofauna (0.1–2.0 mm) contributed more to the loss of litter mass and the release of organic carbon from the litter than macrofauna (2.0–4.0 mm). The effects of diverse soil fauna on litter decomposition and soil organic carbon accumulation were diminished by naphthalene exposure. This study further reveals the relationship between composite soil fauna diversity, litter decomposition, and soil organic carbon under chemical stress, highlighting the threat of environmental pollution to ecosystem health. It also enriches our understanding of the complexity of grassland ecosystems, especially in response mechanisms under chemical pollution stress.

Naturalized species drive functional trait shifts in plant communities

Despite decades of research documenting the consequences of naturalized and invasive plant species on ecosystem functions, our understanding of the functional underpinnings of these changes remains rudimentary. This is partially due to ineffective scaling of trait differences between native and naturalized species to whole plant communities. Working with data from over 75,000 plots and over 5,500 species from across the United States, we show that changes in the functional composition of communities associated with increasing abundance of naturalized species mirror the differences in traits between native and naturalized plants. We find that communities with greater abundance of naturalized species are more resource acquisitive aboveground and belowground, shorter, more shallowly rooted, and increasingly aligned with an independent strategy for belowground resource acquisition via thin fine roots with high specific root length. We observe shifts toward herbaceous-dominated communities but shifts within both woody and herbaceous functional groups follow community-level patterns for most traits. Patterns are remarkably similar across desert, grassland, and forest ecosystems. Our results demonstrate that the establishment and spread of naturalized species, likely in combination with underlying environmental shifts, leads to predictable and consistent changes in community-level traits that can alter ecosystem functions.

Cumulative and Lagged Effects: Seasonal Characteristics of Drought Effects on East Asian Grasslands

With the acceleration of global warming, droughts are expected to both intensify and become more frequent. More so than forests, the productivity of grasslands is largely controlled by soil moisture and is highly susceptible to drought. Drought can impact grasslands though the effects may lag and accumulate over time. Because prior research has mainly focused on the annual or growing season scale, it remains unclear whether there are seasonal differences in the cumulative and lagged effects (CALEs) of drought. This study uses Normalized Difference Vegetation Index (NDVI) and Standardized Precipitation Evapotranspiration Index (SPEI) data to explore the seasonal characteristics of the CALEs of drought on grassland growth in East Asia from 2001 to 2020. The main results include the following: (1) More than 40% of grasslands are significantly affected by the CALEs of drought for all three seasons (spring, summer, and autumn). (2) Grasslands are more sensitive to the CALEs of drought in summer. The spatial variability of the cumulative time scale is the greatest in spring, whereas the spatial variability of the lagged time scale is the greatest in summer. The lag time scale gradually shortens as moisture decreases in summer and autumn but shows an inverted U-shape in spring. As drought conditions intensify, the cumulative time scale gradually increases in spring and autumn, while gradually decreasing in summer. (3) The dominant drought effects vary among different seasons: the lagged effect (LE) predominates in spring and autumn, whereas in summer it is the cumulative effect (CE) that dominates. The LE exceeds the CE in 54.89% of the study area during the growing season. We emphasize that annual- or growing season-scale studies of drought CE and LE may obscure seasonal response characteristics. Given the seasonal nature of droughts and the seasonally varying sensitivities of grassland growth to these droughts, the impacts on vegetation fluctuate significantly across different seasons. The results help us more accurately predict grassland ecosystem changes under the background of global warming and the increasing probability of severe drought, providing important reference values for future grassland ecological protection and planning.

Non-linear response of plant caloric value to N addition and mowing treatments in a meadow steppe

BackgroundCaloric value is an important indicator of grassland ecosystem function, but the response of caloric value to nitrogen (N) addition and mowing is still unclear. We explored the adaptive changes of plant caloric value and energy standing crop along a N addition gradient after six-year NH4NO3 addition and mowing treatments in an Inner Mongolian temperate meadow steppe in northern China.ResultsWe found that the response of plant caloric value to N addition at different organizational levels was diverse. The caloric value of legumes increased linearly with N addition rates. The caloric value of grasses exhibited a non-linear response trend, initially increasing followed by saturation or decrease, with a N response threshold present. Due to the dominance of grass species, the caloric value at the community level followed a similar pattern to that of the grasses along the N addition gradient. Under mowing, the caloric value of plants at each organizational level increased and usually mowing enhanced the N response threshold. Amongst these, the N response threshold of Leymus chinensis increased from 3.302 to 5.443 g N m−2 yr−1, grasses increased from 4.414 to 5.746 g N m−2 yr−1, and community increased from 5.373 to 9.216 g N m−2 yr−1. Under non-mowing treatment, the N response thresholds of the most dominant species, Leymus chinensis, and community energy standing crop were 10.001 and 15.119 g N m−2 yr−1, respectively. Under mowing, the energy standing crops showed a linear increasing trend.ConclusionsN response thresholds of plant caloric value and energy standing crop vary at different organizational levels (community > functional group > species). The results reveal varying regulatory capabilities of plants on the ecological environment at different organizational levels. These findings enhance our understanding of plant-environment interactions in grassland ecosystems under N deposition from an energy perspective, which is of great significance to clarify the response mechanism of grassland ecosystem structure and function to N deposition.

Vegetation restoration enhancing soil carbon sequestration in karst rocky desertification ecosystems: A meta-analysis

Vegetation restoration measures have been increasingly employed to alleviate rocky desertification in karst ecosystems. However, the comprehensive effects of these interventions on soil properties and soil organic carbon (SOC) remain poorly understood. Herein, we gathered 644 paired observations from 68 studies and conducted a meta-analysis to quantify the performance of different vegetation restoration measures including moss (MS), grassland (GL), cash crop (CP), shrub (SH), and secondary forest (SF) through soil properties and SOC. Our results demonstrated significant effects of MS, GL, CP, SH, and SF on soil biotic and abiotic factors, each with distinct response characteristics. Particularly, MS significantly enhanced all soil properties (excluding a slight decrease in soil pH by 10.8%). Moreover, MS, GL, CP, SH, and SF could elevate SOC by 32.1%, 17.6%, 24.9%, 59.2%, and 48.7% respectively. Utilizing random forest and linear regression models, we identified primary drivers for SOC in MS, GL, CP, SH, and SF as soil moisture content, arbuscular mycorrhizal fungi, soil microbial phosphorus, total nitrogen, and β-1,4-glucosidase, respectively. This meta-analysis underlined the varied effects of vegetation restoration measures on soil properties and advocates for restoration measures that prioritize plant productivity and reduce soil temperature during the karst rocky desertification restoration process. Additionally, this study underscores the pivotal role of vegetation rehabilitation in environmental conservation and carbon sequestration of ecologically vulnerable regions.

Assessment of grassland carrying capacity drivers and evaluation of pasture-livestock balance: A case study of Xinjiang, China

Evaluating the spatiotemporal variations and driving mechanisms of carrying capacity (CC) is critical for optimizing grassland resource utilization and promoting sustainable development in grassland animal husbandry. This study focuses on Xinjiang, an arid and semi-arid region significantly impacted by environmental changes and human activities. To capture the dynamics of grassland CC, we employed Theil-Sen trend analysis and the Mann-Kendall test to assess spatiotemporal trends. The innovative use of the Geodetector method allowed for a detailed quantification of the influence of various environmental and human-related factors on grassland CC. Additionally, we incorporated livestock data to evaluate the overgrazing conditions of the grassland ecosystem. Our findings demonstrate that: (1) Grassland CC has shown a pronounced overall upward trajectory over the last twenty years, with notable inter-annual fluctuations and significant spatial variations, particularly between the northern and southern regions. (2) The spatial distribution of grassland CC is primarily influenced by precipitation patterns and population density, with key determining factors varying across different types of grasslands. Except for alpine steppe and alpine desert, the spatial distribution of grassland CC was primarily influenced by two-factor interactions, surpassing the impacts of single-factor effects. (3) The overgrazing rate has generally declined, peaking in 2014 and showing the mildest condition in 2017. In comparison, the overgrazing situation in Northern Xinjiang is relatively more favorable, whereas the southern and eastern regions necessitates more immediate and comprehensive ecological restoration and management measures. In summary, this study provides important scientific evidence for prioritizing grassland protection and planning for the sustainable animal husbandry development in arid and semi-arid regions.

Spatial dynamics and drivers of recent changes in grass and shrub cover in submontane grassland plant communities

AbstractShrub encroachment into grassland ecosystems has been increasingly observed and documented worldwide in recent years. A grass–shrub transition can affect the diversity, abundance and functional integrity of grassland plant communities and understanding the drivers behind these processes is therefore crucial. While potential environmental drivers are often investigated, the role of spatial patterns of neighbouring shrub density in local shrub encroachment has been less well studied. The aim of this study is to investigate the relative role of neighbouring shrub density and topography as potential key drivers of shrub encroachment in a typical montane grassland ecosystem in New Zealand. We used the SPOT (Satellite Pour l’Observation) 6/7 multispectral imagery captured on one day in 2013 and in 2017 to calculate recent changes in shrub/grass cover during this period. Using the Normalised Difference Vegetation Index (NDVI), we classified the study area into grassland and shrubland and quantified the extent and change in these two land-cover types over the study period. We then investigated the relationships between changes in land cover and neighbourhood shrub density, elevation and aspect. Between 2013 and 2017, there was an overall shrubland increase of + 0.35% of the study area per year, and grassland decrease of −0.43% per year. Locations at which any change in vegetation type occurred were more likely to be at mid-elevation (c. 600–1,000 m a.s.l.) and on west-facing slopes. Highest shrub expansion rates were observed on areas that were on warmer, north-facing slopes and at elevations below 900 m a.s.l.; this is consistent with areas below the pre-human, natural treeline which is estimated to be at very similar elevations. We found a marked threshold in the degree to which neighbourhood shrub density correlated with local shrub encroachment: local shrub encroachment only occurred when shrub cover in the neighbourhood exceeded 40% and peaked at c. 60% indicating the potential for a sudden grass–shrub regime shift once shrub cover reaches a certain level. Our study provides new evidence from the Southern Hemisphere of a measurable and interacting effect of topography and neighbourhood shrub density on recent shrub encroachment rates in montane grasslands even over short time periods.

Sensitivity of montane grassland water fluxes to warming and elevated CO2 from local to catchment scale: A case study from the Austrian Alps

Study region: Montane grassland within the Gulling catchment, Austrian Alps. Study focus: A climate-change experiment in a grassland ecosystem used lysimeters and HYDRUS-1D models to quantify changes in evapotranspiration (ET) and groundwater recharge (GWR) due to warming (＋3 °C) and elevated CO2 concentrations (ΔCO2; ＋300 ppm). Findings at the plot-scale were generalized and transferred to the surrounding catchment, half comprised of grassland, using three lumped rainfall–runoff models and two spatially-distributed Community Water Models, differing in soil hydraulic properties.New hydrological insights for the region: Warming increased ET and decreased GWR and river discharge compared to ambient conditions. ΔCO2 increased stomatal resistance, which partially offset warming effects. In scenarios combining warming and ΔCO2, the impact of warming was higher than ΔCO2 effect. Elevation influenced the sensitivity of ET to warming, which was greater at the catchment scale than at the plot scale, while GWR was more sensitive to warming at the plot scale. Under dry conditions, GWR and discharge exhibited increased sensitivity to warming at both scales. HYDRUS-1D successfully reproduced lysimeter experiment results and their sensitivity to warming and ΔCO2. Despite model agreement on water flux sensitivity to climate changes, the varying response magnitudes highlight the need for a multi-model approach in climate impact assessments. This study provides insights into how climate change might impact hydrological dynamics of montane grassland systems across the Central European Alps.

451 Establishing producer research sites for the development of beef and bison climate-smart agriculture

Abstract Greenhouse gas (GHG) emissions and livestock production are topics that are increasingly intertwined. While livestock production is frequently presented as harmful to the environment, this perception fails to consider the carbon sequestration that takes place in livestock grazing systems and the role that grazing ruminants have in maintaining healthy grassland ecosystems. Grazing lands, which are often unsuited to row crop agriculture, are estimated to account for 25% of the global soil sequestration potential for soil carbon storage. Grazing livestock producers are often overlooked in the GHG reduction conversation, despite over 70% of beef GHG emissions being attributed to the cow-calf sector, which is primarily grazing. Furthermore, there is a relative lack of data surrounding the implementation of climate-smart agriculture practices on grazing operations and a lack of cost-effective methods to measure carbon/GHG sinks and sources on these landscapes. The potential climate benefits are considerable, with nearly 940 million acres of rangelands in the U.S. supporting forage-based livestock production. South Dakota State University recently received funding to support a large-scale climate-smart project focused on grazing beef and bison. For this project, we are utilizing the Cottonwood Field Station that has over 80 yr of historical grazing data, along with six grazing beef and bison ranching operations in the Northern Great Plains. The work on these ranches will focus on measuring and monitoring the impacts of climate-smart NRCS land practices, including cover crops, improved pasture and range seedings, prescribed grazing, and prescribed burning. A significant focus will be extensive, annual soil sampling across these operations to continuously monitor changes in soil organic carbon, bulk density, texture, pH, and soil microbiome community profiles. Each operation will have GreenFeed methane pasture units deployed for 5 yr to monitor changes in beef cattle and bison methane emissions in response to climate-smart practice adoption. We are also assessing biodiversity pre and post climate-smart practice adoption, as biodiversity improvements may be one of the most overlooked and yet most important responses to climate-smart land practice implementation. Over the duration of this project, a large-scale, comprehensive data collection will be achieved and used to refine GHG and carbon sequestration estimates associated with range livestock systems. Data resulting from this project will be used to inform research protocols and prediction models, fill knowledge gaps, and shape science-based discussions and marketing strategies for climate-smart agricultural commodities.

Soil labile organic carbon and nitrate nitrogen are the main factors driving carbon-fixing pathways during vegetation restoration in the Loess Plateau, China

Although the microbial fixation of CO2 is a key process in regulating soil carbon cycling, the effects of vegetation type on microbial carbon-fixing pathways and their driving factors in soils have yet to be sufficiently established. In this study, based on macro-genome sequencing and other analytical methods, we sought to determine the soil physicochemical properties, soil organic carbon contents, carbon-fixing microorganisms, and carbon-fixing genes in areas of farmland (FL), grassland (GL). Robinia pseudoacacia (RP), Caragana korshinskii (CAK), and Prunus sibirica (PS) in the Wuliwan watershed of the Loess Plateau region of China. Our findings revealed that the organic carbon contents of the assessed soils increased in the following order: FL < GL∼PS < CAK < RP (P < 0.05). Re-vegetation-based restoration was found to enhance soil organic carbon pool stability. Compared with farmland soil, the proportions of recalcitrant organic carbon had increased by 6 % and 9 % in the soil at sites that had undergone restoration with C. korshinskii and R. pseudoacacia respectively. Among the identified carbon fixation pathways, the DC/4-HB cycle had the highest relative abundance of 25.10–25.52 %. The dominant groups of carbon-fixing microorganisms were identified as Actinobacteria and Proteobacteria, accounting for over 60 % of the total abundance. Furthermore, analysis based on a partial least squares path model revealed labile organic carbon and soil nitrate nitrogen as the primary drivers of carbon fixation pathways. Collectively, our findings in this study provide evidence to indicate that restoration of vegetation on the Loess Plateau can contribute to increases in soil organic carbon content and stability and the abundance of carbon-fixing microorganisms, with R. pseudoacacia and C. korshinskii having the most significant effects in this regard. These findings have important implications for restorative vegetation carbon pool management and provide additional perspectives for understanding global carbon cycling.

High-resolution mapping of grassland canopy cover in China through the integration of extensive drone imagery and satellite data

Canopy cover is a crucial indicator for assessing grassland health and ecosystem services. However, achieving accurate high-resolution estimates of grassland canopy cover at a large spatial scale remains challenging due to the limited spatial coverage of field measurements and the scale mismatch between field measurements and satellite imagery. In this study, we addressed these challenges by proposing a regression-based approach to estimate large-scale grassland canopy cover, leveraging the integration of drone imagery and multisource remote sensing data. Specifically, over 90,000 10 × 10 m drone image tiles were collected at 1,255 sites across China. All drone image tiles were classified into grass and non-grass pixels to generate ground-truth canopy cover estimates. These estimates were then temporally aligned with satellite imagery-derived features to build a random forest regression model to map the grassland canopy cover distribution of China. Our results revealed that a single classification model can effectively distinguish between grass and non-grass pixels in drone images collected across diverse grassland types and large spatial scales, with multilayer perceptron demonstrating superior classification accuracy compared to Canopeo, support vector machine, random forest, and pyramid scene parsing network. The integration of extensive drone imagery successfully addressed the scale-mismatch issue between traditional ground measurements and satellite imagery, contributing significantly to enhancing mapping accuracy. The national canopy cover map of China generated for the year 2021 exhibited a spatial pattern of increasing canopy cover from northwest to southeast, with an average value of 56 % and a standard deviation of 26 %. Moreover, it demonstrated high accuracy, with a coefficient of determination of 0.89 and a root-mean-squared error of 12.38 %. The resulting high-resolution canopy cover map of China holds great potential in advancing our comprehension of grassland ecosystem processes and advocating for the sustainable management of grassland resources.

Drought and warming interaction cause substantial economic losses in the carbon market potential of China's northern grasslands

Grasslands are being threatened by global drought and warming. Economic assessments of changing grassland carbon sequestration, a prerequisite for nature-based climate-change mitigation policies, are limited when researchers inadequate consider interactions between drought and warming. Here, we quantified the responses of 35 grass biomasses to combined drought and warming, based on manipulation experiments from 34 peer-reviewed papers; subsequently, we matched them with grasslands in northern China—the eastern range of the larger Eurasian Steppe—and further projected the economic implications for carbon market trading and carbon-sequestration costs. The results show that carbon sequestration in all grassland types, except for forbrich steppe, was significantly reduced by the synergistic interactions of drought and warming. Approximately 10 % of the grasslands in central Xinjiang, identified as forbrich steppe, showed resilience to these stressors. In contrast, the rest of northern China's grasslands suffered increased carbon losses due to drought and warming. The combined effects of drought and warming have caused a loss of 1.6 × 104 million Chinese yuan (CNY) in revenue and excess carbon-sequestration costs exceeding 1.1 × 105 million CNY. Overall, our study results indicate that the synergistic effects of drought and warming significantly undermine the economic viability of carbon sequestration in most of northern China's grasslands. As climate change intensifies, understanding and incorporating the complex interactions of drought and warming can aid in the sustainable management of grassland ecosystems and the development of effective climate-change mitigation policies in arenas, including carbon markets.

Applications of satellite platforms and machine learning for mapping and monitoring grasslands and pastures: A systematic and comprehensive review

Grasslands and pastures are critical ecosystems globally, essential for their agricultural and environmental roles. Extensive research from 2000 to 2022, comprising 504 articles, has explored the integration of remote sensing and statistical modelling for mapping and monitoring grassland and pasture ecosystems. These articles were sourced from the SCOPUS database and analysed using text mining and natural language processing techniques to investigate the evolution of publication trends over the past twenty-two years. The number of publications per year on this topic has grown consistently in the considered period, from 3 in 2000 to 93 in 2022, doubling their weight compared to the total number of Scopus publications. The quantitative analysis of satellite platform utilisation revealed the increasing importance of Sentinel-2, even though MODIS remained the most utilised satellite platform throughout the study period. The increasing availability of big data has helped spread the utilisation of machine learning algorithms, mostly in the last ten years. Among these, random forest appeared to be the most widespread for grassland and pasture studies. Researchers' primary interest in this field centres on the technologies and their applications. This is evidenced by cluster analysis, which reveals a dominant focus on terms related to the 'Instruments' (25.8 %) and 'Parameters' (24.9 %) categories. This analysis aims to outline the progression of research, offering insights that could be useful in forecasting future trends and facilitating stakeholder engagement in this sector.

Designing and delivering climate training for natural resource managers: Increasing climate literacy and action through education and engagement

AbstractResponding to climate impacts and expanding adaptation efforts necessitates getting the right knowledge and tools in the hands of land managers and decision‐makers. In 2022–2023, several regional US Geological Survey Climate Adaptation Science Centers partnered with the US Fish and Wildlife Service (FWS) Science Applications Program on the first targeted climate training series designed for the FWS Grassland Ecosystem Team. This training spanned multiple months and formats with self‐paced virtual lessons, webinars, and an in‐person workshop. As the FWS Grassland Ecosystem Team is tasked with conservation planning for grassland birds and other species, the focus of the workshop was an interactive collaborative activity incorporating species adaptive capacity assessments, future climate projections, and adaptation menus into the decision‐making process. Herein, we describe the methods used to design and deliver the training series, as well as lessons learned for future climate literacy programs aimed at natural resource managers.

Characteristics of Vegetation and Soil of Degraded Grasslands and Their Relationships in Xizang

To investigate the characteristics of grassland degradation on a regional scale in Xizang, data on grassland degradation from the second grassland survey of Xizang and 12 vegetation and soil indicators from the National Tibetan Plateau Data Center were collected. Using ArcMap, 10 000 random sample points were selected on raster data （excluding non-grassland, desertification, and salinization data, leaving 7 949 valid sample points）. The multi-value extraction to-point method was applied to extract degradation and indicator data for each sample point. The characteristics of degraded grassland vegetation and soil and their relationships were analyzed in Xizang. Moreover, random forest modeling was conducted to predict the trend of grassland ecosystem changes. The results indicated that： ① The grasslands in Xizang were primarily composed of alpine steppe and alpine meadow types, accounting for 45.83% and 41.15% of the valid sample points, respectively. ② With the intensification of grassland degradation, the number of steppe-type species among the 17 grassland types gradually decreased, and the proportion of steppe dominated by species such as Stipa purpurea and Carex moorcroftii decreased, whereas the proportion of miscellaneous grasses and Dasiphora fruticosa increased. ③ As the degree of degradation increased, vegetation indicators generally showed a declining trend, with soil total nitrogen, total phosphorus, total potassium, and organic carbon decreasing, whereas soil pH and bulk density increased, and soil moisture content was not significant. ④ A positive correlation exists between soil moisture content, total nitrogen, total phosphorus, total potassium, organic carbon, vegetation cover, net primary productivity of vegetation, normalized difference vegetation index, aboveground biomass, and habitat quality. However, there was a negative correlation between pH and soil bulk density, and the correlation coefficients among various indicators decreased with the intensification of degradation. ⑤ The random forest simulation results showed that during the degradation process, the contribution rates of soil bulk density and habitat quality both exceeded 12%, with the model prediction accuracy reaching 78%. The study revealed that grassland degradation in Xizang was closely related to soil bulk density and habitat quality, indicating that higher soil bulk density or lower habitat quality may correspond to more severe grassland degradation. This provides a scientific basis for future grassland conservation and management.

Revisiting past savanna environments: Pollen analysis of the Colbyn wetland on the southern African central plateau

A high-resolution, radiocarbon dated, pollen sequence of the ecotone between the Grassland and Savanna Biomes, was extracted from a 2.5 m peat core at the Colbyn wetland in South Africa. The lithology indicates transitions between organic sediment, clay, and well-preserved peat layers. The pollen and micro-charcoal records suggest interactions between the seasonal climate, burning and possible human and other disturbance. The vegetation development over the last 4000 cal yr BP is compared with chronologically parallel pollen sequences from the nearby Moreleta River and Rietvlei Dam sequences. The study, that can be correlated with wider regional isotopic records of the region, shows drier conditions c. 3800 to 3400 cal yr BP, and around 800 cal yr BP, and a wetter phase at Colbyn c. 3000–1500 cal yr BP.