Grassland Types Research Articles

Design of Vehicle Image Stabilization System and Imaging Quality Impact Test for Typical Grasslands

Design of Vehicle Image Stabilization System and Imaging Quality Impact Test for Typical Grasslands

Temporal evolution and source apportionment of BC aerosols during autumn in the grassland of Ordos, China

AbstractMeteorological conditions and source emissions in grassland areas are quite different from those in urban areas, which significantly impacts the spatiotemporal characteristics of black carbon (BC). To obtain the characteristics of BC in the typical grassland environment in China, continuous observations of BC were carried out in Etuoke Banner, a typical grassland environment in Ordos, from September 8 to December 1, 2022. BC in Etuoke Banner in autumn is 22.4–4667.5 ng m−3, and the average concentration is 456.6 ng m−3, accounting for 2.20% of the mass fraction of PM2.5. BCliquid (BC generated from the combustion of liquid fuels) is the main component of BC (accounting for 79.2%); the average concentration is 361.7 ng m−3. The diurnal variations of BC, BCliquid, and BCsolid (BC generated from the combustion of solid fuels) are bimodal, with peaks at 08:00 and 18:00. The first peak is mainly related to traffic sources, cooking sources, and incomplete combustion of carbon‐containing substances; the second peak may be caused by emissions from residential cooking sources under the influence of meteorological conditions unfavorable to diffusion. The diurnal variation of absorption Ångström exponent (AAE) is unimodal, with the peak at 14:00. With the increase in BC mass concentration, AAE and visibility gradually decreased, wind speed first decreased and then increased, P and RH gradually increased, and the contribution of biomass combustion sources to BC decreased. In contrast, the contribution of traffic sources to BC increased. The evolution characteristics of atmospheric pollutants differed with the increase in BC concentration. The potential sources and affecting areas of BC and PM2.5 are mainly concentrated around Etuoke Banner and can affect the North China Plain after 48 h of transmission.

Alternating dominant effects of temperature and precipitation along elevational gradient on the alpine and subalpine vegetation activities in southwestern China

Elevation plays a pivotal role in modulating hydroclimatic dynamics, changing vegetation activity and shaping vegetation distribution patterns in alpine regions. Nevertheless, a conspicuous knowledge gap persists regarding the interaction between climate drivers on vegetation activity. In this study, we investigated the spatio-temporal patterns of the Normalized Difference Vegetation Index (NDVI), a proxy for vegetation activity, and examined its interactions with temperature (T) and precipitation (P) along elevational gradient (EG) in the Alpine and Sub-alpine Woodlands of Southwest China (ASWSC) during 2001–2018. We found that approximately 24% vegetation in ASWSC exhibited significant greening trend, as a result of regional warming and slight wetting during the study period. The greening and browning rates were both elevational asymmetric, with higher rates at lower elevations. We also illustrated an alternating domination of T - P on vegetation activity along EG. This suggested a roughly antagonistic effect between the two drivers within the whole vegetation elevation range except for a synergistic effect in the sub-alpine forests zone between 2300 - 4200 m. The antagonistic effect tended to be more pronounced in warm and dry years, while the synergistic effect was more evident in cold and wet years. Specifically for different vegetation types, we found an insignificant T - P interactive effect along EG in indigenous evergreen needleleaf forest (ENF) and evergreen broadleaf forest (EBF), in contrast to the significant synergistic effect in the regenerated deciduous broadleaf forest (DBF) and mixed forest (MF) and antagonistic effect in shrubland and grassland types. In summary, our study revealed alternating-dominant effects of temperature and precipitation on vegetation activity along EG. These findings will deepen our understanding of vegetation resistance and resilience to climate change and eventually contribute to establishing a scientific foundation for effective ecosystem management and conservation practices in alpine region.

Spatiotemporal Variation Characteristics and Driving Force Analysis of Precipitation Use Efficiency at the North Foot of Yinshan Mountain

The northern foothills of Yinshan Mountain are situated in northern China’s agricultural and pastoral ecotone, serving as a crucial ecological barrier. To comprehensively assess the impact of grassland resource restoration in this region since the initiation of the Grain-for-Green conversion project in 2000, this study analyzes the spatiotemporal characteristics of precipitation use efficiency (PUE) and investigates climate-driven factors during 2001–2021. The results showed that the grassland types at the north foot of Yinshan could be divided into four categories: warm-arid, warm subtropical semidesert (WSS), warm temperate-arid, warm temperate zonal semidesert (WZS), warm temperate-semiarid, warm temperate typical steppe (WTS), and warm temperate-subhumid forest steppe (WFT). The NPP of the four grassland species were 151.34 (WSS), 196.72 (WZS), 283.33 (WTS), and 118.06 gC·m−2 (WFT), and correspondingly, the PUE of the four grassland species were 0.66 (WSS), 0.66 (WZS), 0.80 (WTS), and 0.57 gC·m−2·mm−1 (WFT). From 2001 to 2021, PUE in grassland showed an overall upward trend, rising from 0.57 to 0.99 gC·m−2·mm−1. The trend analysis found that the vegetation ecological area of the northern foot of Yinshan became better, of which 54.36% was improved and 15.72% was degraded. It is worth pointing out that WSS had the highest degree of improvement, while WFT was in a degraded state. The climate driving force analysis shows that the regional contribution of precipitation is 19.57%, temperature is 28.33%, potential evapotranspiration is 13.65%, wind speed is 10.79%, and saturated vapor pressure is 27.66%.

Global response of different types of grasslands to precipitation and grazing, especially belowground biomass

Precipitation and grazing both modify the structure and function of grassland. Although the effects of site-scale precipitation and grazing on vegetation communities have been investigated, the differences between different grassland types at the global scale are still not clear. Therefore, we conducted a global-scale meta-analysis synthesizing 107 field studies with different grassland types (savanna grassland, temperate grassland, cold grassland, and alpine grassland) to quantify the effects of global changes in precipitation and grazing on community structure and function of grassland types. Results showed that regardless of grassland type, increased precipitation increased species richness by 7.8%, decreased belowground biomass (BGB) by 20.0%, and increased aboveground biomass (AGB) by 22.9%, but interestingly, decreased precipitation increased BGB by 17.7%, decreased AGB by 22.8%, and decreased species richness by 13.7%. Species richness of global grassland vegetation was positively correlated with grazing intensity. The total vegetation community biomass (TB) increased by 11.7% under moderate grazing intensity, while the species diversity of global grassland vegetation increased by 10.7% under heavy grazing intensity. Increased precipitation had negatively impacted BGB in temperate grassland, while increased precipitation significantly increased cool grassland BGB. In savanna grasslands, vegetation AGB decreased with increasing precipitation. Our results highlight the impact of altered precipitation on grassland vegetation under different climate types. We suggest that future studies of grassland management should consider incorporating grazing intensity and climate type, which will help to protect grassland vegetation species diversity and predict future carbon dynamics.

Effect of grazing and climatic factors on biodiversity-ecosystem functioning relationships in grassland ecosystems -a case study of typical steppe in Inner Mongolia, China.

Biodiversity underpins grassland ecological functions and productive capacities. By studying the mechanisms for the maintenance of species diversity in animal communities, we can provide important theoretical guidance for the optimization of grazing management and biodiversity protection. The typical grassland of Xilingol in Inner Mongolia, China, was used as the experimental area, and a grazing intensity experiment was set up. This consisted of four gradient levels that were grazed by sheep, which were available for continuous monitoring, namely control standard sheep unit·day·hectare-1·year-1 (CK, 0 SSU·d·hm-2y-1), light grazing (LG, 170 SSU·d·hm-2·y-1), moderate grazing (MG, 340 SSU·d·hm-2·y-1), and high grazing (HG, 510 SSU·d·hm-2·y-1). Nine consecutive years of multi-indicator monitoring of vegetation was carried out from 2014-2022, using monitoring data coupled with time series and inter-annual climatic (relative moisture index, RMI) fluctuations. This was done to analyze the impacts of disturbances, such as grazing use and climatic fluctuations, on the diversity of species and above-ground productivity of the community, thereby exploring the relationship between diversity and productivity, and provide possible explanations for the emergence of a range of ecological responses. The statistical analysis methods used were One-way Analysis of Variance (ANOVA), general linear regression and mixed-effects models. The main conclusions of this study are as follows: (1) The grassland in the experimental area under CK had the highest diversity and productivity and the ecosystem was better able to buffer the negative impacts of climatic drought. Furthermore, the effect of climate on productivity and diversity weakened as the intensity of grazing increased. (2) LG to MG had a constant diversity. (3) Grazing utilization changed the relationship between community species diversity and aboveground productivity by releasing spatial community resources, altering the structure of plant communities, weakening competitive exclusion, and strengthening complementary effects. However, under all of the conditions there is a brief stage in the time series when diversity is stimulated to increase, and the higher the grazing intensity, the earlier this occurs.

Contrasting potential impact patterns of unique and shared microbial species on nitrous oxide emissions in grassland soil on the Tibetan Plateau

Microbial nitrogen transformation processes in grasslands are important nitrous oxide (N2O) sources on the Tibetan Plateau. Different microorganisms carrying various functional nitrogen (N) cycling genes colonize different soil types and have varying impacts on N2O emissions. However, the role of specific microbial components such as unique and shared microbial species, in N2O flux in alpine grassland soils remains understudied. Thus, we combined gas chromatography-based static opaque chamber methods with metagenomic sequencing to investigate the role of unique and shared microbial species carrying N-cycling genes in N2O emissions from two alpine grassland types on the Tibetan Plateau. Our results showed that the N2O flux in the alpine meadows (9.48 × 10−9 g m−2 h−1) was higher than that in the alpine steppes (4.21 × 10−9 g m−2 h−1). Furthermore, our study revealed a significant negative correlation between the abundance of unique microbial species and the N2O flux in alpine steppes. In contrast, the abundance of shared microbial species was significantly and positively correlated with N2O flux. The unique microbial species in the phyla Chloroflexi and Actinobacteria carried the ureC, nasA and nirB genes, which could consume nitrogen substrates in forms other than producing N2O, which could explain the N2O reduction seen in the alpine steppes. In addition, the higher abundance of shared microbial species in the phyla Proteobacteria, Actinobacteria, Thaumarchaeota and Acidobacteria carried genes encoding denitrification pathways (nirK, narG, and norB) could interpret the higher N2O emissions in the alpine meadows. In addition, our study revealed that the soil substrate contents (e.g., soil organic carbon and total nitrogen) and soil environment factors (e.g., soil pH and soil moisture) were potentially important drivers of N2O emissions in soil via their regulation of the composition of unique and shared microbial communities carrying N-cycling genes. Collectively, our results suggested that identifying the unique and shared microbial species carrying different N-cycling genes could provide potential biological strategies for mitigating N2O emissions in alpine grasslands, such as blocking the growth of shared microbial species. Future management practices for mitigating N2O emissions in alpine grassland should also focus on adopting appropriate nutrient management strategies, such as balanced fertilization, to prevent excessive nutrient. Our findings provide insights for further elucidating the different potential regulatory effects of unique and shared microbial species on emissions under the control of the soil environment in different types of grasslands on the Tibetan Plateau.

Improving grassland classification accuracy using optimal spectral-phenological-topographic features in combination with machine learning algorithm

Accurate mapping of large-scale grassland types is important for grassland and water resources management. The similarity of spectral characteristics between grassland types lowers the classification accuracy of different grassland types. To improve the classification accuracy of large-scale grasslands, this study proposed a new framework which integrates Sentinel-2 images with DEM and climate zones data. In this framework, optimal spectral-phenological-topographic features are fed into Random Forest (RF) model based on Google Earth Engine (GEE) platform. The proposed framework was applied in Inner Mongolia, China. A grassland map of the region was obtained with an overall accuracy (OA) exceeding 80 %, which is higher than the OA (60 %-70 %) of current large-scale grassland type classification studies. In WIM (Western Inner Mongolia) and NEIM (Northeast Inner Mongolia), the OA reaches 96.97 % and 95.85 %, respectively. SWIR2 band and elevation have a clear advantage in distinguishing different grassland types. Compared to 1980s, the area of temperate meadow steppe (TMS) and temperate desert steppe (TDS) have increased by 111.94 % and 126.00 %, respectively. The area of temperate typical steppe (TTS) decreased by 7.38 %. The framework proposed in this study has a great potential to be applied to improve large-scale grassland classification in other regions in future.

Grazing reduced greenhouse gas fluxes in Inner Mongolia grasslands: A meta-analysis

Grazing exerts a significant influence on greenhouse gases (GHGs) fluxes within temperate grasslands. While previous studies have explored the impact of varying grazing intensities on GHGs fluxes in meadow steppe, typical steppe, and desert steppe, there remains a knowledge gap regarding how grazing intensities affect GHGs fluxes across different grassland types and seasonal variations. In this study, we conducted a meta-analysis of Inner Mongolia grasslands involving 38 published reports and aggregating 143, 160, and 118 records for the CO2, CH4, and N2O, respectively. Our results demonstrated that grazing reduced annual mean CO2 emission, CH4 uptake, and N2O emission by 15.29%, 10.56%, and 24.73%, respectively (P < 0.05). Specifically, during the freeze-thaw period, grazing induced a decrease of 28.06% and 58.41% in CH4 uptake and N2O emissions, respectively, compared to ungrazed treatments (P < 0.05). Further dissecting the impact, we found that grazing reduced CO2 emissions in desert steppe, typical steppe, and meadow steppe by 20.28%, 15.54%, and 11.79%, respectively. In addition, grazing decreased CH4 uptake in typical steppe by 15.14% and decreased N2O emission in typical steppe, meadow steppe, and sown pasture by 20.25%, 24.18%, 52.91%, respectively. Crucially, the alteration in plant biomass due to grazing-induced changes underlying drivers that govern the responses of GHGs fluxes. These results furnish compelling evidence that grazing, particularly in non-growing season, holds the potential to mitigate grassland GHGs fluxes in temperate grasslands. Our results can deepen the understanding of the grazing effects on GHGs and offer valuable insights for refining grazing management strategies in pastoral regions.

Positive effects of leguminous shrub encroachment on multiple ecosystem functions of alpine meadows and steppes greatly depended on increasing soil nutrient

Shrub encroachment in grassland ecosystems is projected to intensify worldwide because of rapid climate change and anthropogenic activity, amplifying the encroachment of woody shrubs and strongly altering the ecosystem function. The effects of leguminous shrub encroachment on multiple dimensions of ecosystem functioning, however, remains poorly understood. This study experimentally quantified the effects of leguminous shrub encroachment (primarily Caragana spinifera Kom.) on various ecosystem functionality relevant to plant diversity, productivity, and storage of soil carbon (C) and nitrogen (N) in alpine meadows and steppes. Further, the study assessed the potential influences of shrub encroachment on ecosystem multifunctionality (EMF, EMF-diversity, EMF-productivity, EMF-C, and EMF-N). Our findings suggest that leguminous shrub encroachment enhanced ecosystem multifunctionality in alpine meadows and steppes. Plant diversity and aboveground biomass of herbaceous species increased after leguminous shrub encroachment. Additionally, the impacts of leguminous shrub encroachment on belowground biomass differed with grassland types, increasing in alpine steppes but decreasing in alpine meadows. The shrub encroachment resulted in significant increases in soil nitrogen and overall nutrient contents in both forms of alpine grasslands. Our findings highlight that shrub encroachment’s increasing of ecosystem multifunctionality was closely related to the promotion of plant diversity, biomass of herbaceous plants, and soil nutrients. Overall, our study demonstrates that the encroachment of leguminous shrubs can promote ecosystem multifunctionality in both alpine meadows and alpine steppes. These findings expand our understanding of the ecosystem functioning in leguminous shrub‐encroached alpine meadows and steppes.

Participation of grassland species in various successional series in a temperate European region and implications for habitat management

Restoration strategies of semi-natural grasslands at various disturbed sites require an understanding of the resilience of these habitats and knowledge of their specific successional dynamics. Here, we assess (i) to what extent and under what circumstances grassland species can spontaneously establish and survive in various successional series, and (ii) whether some successional stages may provide surrogate habitats for typical grassland species. Besides grassland species, we evaluated the participation of other species groups, namely woodland, synanthropic and open wetland species, to demonstrate general successional trends. We studied 12 different successional series ca 60 years long in the Czech Republic, central Europe, and evaluated changes in species numbers and cover of species groups. Our results showed grassland species participated not only temporarily but also continuously during the first six decades of succession, as we had expected. Their decline in the late successional stages was only slightly visible despite the formation of woodland in most successional series. In some cases, the woodland was not completely closed and still allowed some grassland species to survive in the understorey. However, we found clear negative correlations between the participation of grassland and woodland species in the late successional stages. Woodland species generally increased, while synanthropic species clearly decreased during succession. Open wetland species slightly decreased, probably due to increasing site terrestrialisation in several successional series. The number and cover of dry grassland species decreased with increasing altitude, while those of mesic grassland species increased, indicating a decisive role of climate for their participation in succession. Successional trends discussed here represent general patterns but cannot be automatically applied in restoration without considering the specificity of each successional series. The establishment of grasslands in most successional series can be prevailingly maintained by management to reduce the establishment and expansion of woody species, otherwise grasslands only rarely persist in habitats under extreme site conditions or certain natural disturbances.

Exploring NDVI change patterns across the Tibetan Plateau at the hillslope scale using geomorphons

ABSTRACTWithin the Tibetan Plateau (TP), grassland degradation is of great concern, and there is a need to better understand the spatial variability and landscape patterns in grassland degradation across the TP. This study explores potential patterns in grassland degradation, estimated using Landsat-derived normalized difference vegetation index (NDVI) growing season change products generated by a prior study. Shuttle Radar Topography Mission (SRTM) digital terrain model (DTM)-derived geomorphons, topographic slope and the topographic position index (TPI) were used to explore grassland degradation and assess whether changes in growing season NDVI are associated with specific grasslands or landforms. An increase in NDVI within the TP was observed especially during the 1990 to 2018 and 2000 to 2018 time periods. Higher growing season median NDVI change values were found for the Southeast Tibet Shrublands and Meadows (SETSM) and TP Alpine Shrublands and Meadows (TPASM) grasslands in comparison to the other grassland types analysed, suggesting a more pronounced greening trend in the eastern portion of the plateau in comparison to the western portion. Small differences in NDVI change were observed for different geomorphon-based landforms, while topographic slope and TPI showed only modest correlations with NDVI change for all time periods and grassland types. More localized patterns of grassland degradation were masked by the widespread greening trends. Further analysis of only pixels that experienced a decreasing NDVI magnitude of less than or equal to −0.1 also generally suggested more change in the SETSM and TPASM. While this study generally supports the use of geomorphons as an analysis and aggregating unit for studying change patterns at the hillslope scale, more research is required to fully grasp the dynamics of landscape change at the hillslope scale in the TP.

Soil Moisture Rather Than Atmospheric Dryness Dominates CO2 Uptake in an Alpine Steppe

AbstractThe Tibetan Plateau (TP) has the largest area of alpine grasslands in the world. Among the various grassland types, alpine steppe covers 72 million hectares in the central–western TP, where the climate is even drier than in other alpine ecosystems. Rapid climate warming (0.34°C per decade) since the 1970s has caused significant atmospheric dryness—that is, an increase in the vapor pressure deficit—despite increases in both precipitation and soil moisture on the TP. However, it remains controversial whether the availability of atmospheric or soil moisture has a stronger role in the growth of vegetation. We used eddy covariance to measure the CO2 fluxes in a grazed alpine steppe over three consecutive years. Our results showed that the alpine steppe acted as a net CO2 sink of 47.9–72.7 g C m−2 yr−1 despite significant grazing. The CO2 fluxes showed a clear seasonal pattern, largely regulated by climate factors, although human activities were also documented. The soil moisture content dominated the seasonal variation in the net ecosystem productivity: the importance of soil moisture to the net ecosystem productivity was 49.0%, whereas the importance of the vapor pressure deficit was 36.5%. We found that the surface soil moisture, rather than the water content of soil layers deeper than 10 cm, affected the net CO2 uptake more strongly, although its role may have been affected by intense rainfall. This study emphasizes that the availability of surface soil water rather than atmospheric dryness regulates CO2 uptake in alpine steppe ecosystems, suggesting that a warming–wetting climate will favor the net uptake of CO2 by alpine steppes.

Model simulation of vegetation canopy precipitation interception in grassland ecosystems on the northeast margin of the Qinghai-Tibet Plateau

Canopy interception plays a crucial role in eco-hydrological processes, and the development of spatiotemporal simulation models of canopy interception is essential for the study of this phenomenon. This study aims to fill the gap in the application of modeling to the study of canopy interception in grassland ecosystems. By using the A.P.J. DE ROO model and the RS-Gash model in conjunction with remote sensing data, we quantitatively simulate and analyze the interception capacity of the grassland vegetation canopy in the study area during the decade. Remote sensing data and measured data are used to assess the simulation accuracy of the models. The model with higher accuracy is used to analyze the spatiotemporal interception of the vegetation canopy in the study area. The results show that the vegetation canopy interception model can be applied not only to forest ecosystems but also to grassland ecosystems; the RS-Gash model has higher simulation accuracy than the A.P.J.DE ROO model; the two models show different simulation accuracy for different grassland types; the vegetation canopy interception rates of different grassland types are different, respectively: alpine meadows is 3.11 %, mountain meadows is 3.82 %, temperate grassland is 2.45 % and temperate desert grassland is 1.13 %; the ratio of vegetation canopy interception area at different levels is roughly low interception area: medium interception area: high interception area = 5:4:1. It can be seen that the application of mechanistic models combined with remote sensing data to simulate canopy interception in grassland ecosystems has great potential. Alpine meadows and mountain meadows are the main contributors to the interception of the grassland vegetation canopy in the study area.

Is Spectral Unmixing Model or Nonlinear Statistical Model More Suitable for Shrub Coverage Estimation in Shrub-Encroached Grasslands Based on Earth Observation Data? A Case Study in Xilingol Grassland, China

Due to the effects of global climate change and altered human land-use patterns, typical shrub encroachment in grasslands has become one of the most prominent ecological problems in grassland ecosystems. Shrub coverage can quantitatively indicate the degree of shrub encroachment in grasslands; therefore, real-time and accurate monitoring of shrub coverage in large areas has important scientific significance for the protection and restoration of grassland ecosystems. As shrub-encroached grasslands (SEGs) are a type of grassland with continuous and alternating growth of shrubs and grasses, estimating shrub coverage is different from estimating vegetation coverage. It is not only necessary to consider the differences in the characteristics of vegetation and non-vegetation variables but also the differences in characteristics of shrubs and herbs, which can be a challenging estimation. There is a scientific need to estimate shrub coverage in SEGs to improve our understanding of the process of shrub encroachment in grasslands. This article discusses the spectral differences between herbs and shrubs and further points out the possibility of distinguishing between herbs and shrubs. We use Sentinel-2 and Gao Fen-6 (GF-6) Wide Field of View (WFV) as data sources to build a linear spectral mixture model and a random forest (RF) model via space–air–ground collaboration and investigate the effectiveness of different data sources, features and methods in estimating shrub coverage in SEGs, which provide promising ways to monitor the dynamics of SEGs. The results showed that (1) the linear spectral mixture model can hardly distinguish between shrubs and herbs from medium-resolution images in the SEG. (2) The RF model showed high estimation accuracy for shrub coverage in the SEG; the estimation accuracy (R2) of the Sentinel-2 image was 0.81, and the root-mean-square error (RMSE) was 0.03. The R2 of the GF6-WFV image was 0.72, and the RMSE was 0.03. (3) Texture feature introduced in RF models are helpful to estimate shrub coverage in SEGs. (4) Regardless of the linear spectral mixture model or the RF model being employed, the Sentinel-2 image presented a better estimation than the GF6-WFV image; thus, this data has great potential to monitor shrub encroachment in grasslands. This research aims to provide a scientific basis and reference for remote sensing-based monitoring of SEGs.

Composition, interaction networks, and nitrogen metabolism patterns of bacterioplankton communities in a grassland type Lake: a case of Hulun Lake, China

The composition of bacterial communities in freshwater ecosystems is influenced by numerous factors including environmental conditions and biological interactions. In grassland inland closed lakes, factors affecting lake ecosystems are either exogenous or endogenous, contributing to the formation of distinct habitats in the surface and bottom waters of the bacterial communities. However, the extent to which environmental factors selectively shape the bacterial communities in aquatic systems remains unclear. Therefore, we sampled the surface, middle, and bottom waters at 13 sampling points in each layer. High-throughput sequencing techniques were employed to examine the spatial heterogeneity of the bacterial community structure during summer in Hulun Lake, the largest grassland-type lake in Inner Mongolia, China, to determine the microbial community dynamics and symbiosis patterns under different habitat conditions. Our results revealed a decrease in the diversity and heterogeneity of the bacterioplankton community, influenced by changes in the environment from exogenous inputs to endogenous releases. Furthermore, this alteration in community structure was concomitant with enhanced co-occurrences among microorganisms in the bottom water layers. This finding suggests that endogenous release promotes heightened symbiotic interactions, thereby facilitating the development of more complex modular structures. Symbiotic networks in different layers were differentiated by key species, with the ecological clustering modules of these species demonstrating dissimilar environmental preferences. The microbial communities were highly habitat-specific, mimicking responses to total nitrogen (TN) in the surface layer, pH in the middle layer, and chemical oxygen demand (COD) in the bottom layer. Bacterioplankton functions were assessed using Tax4Fun, indicating exogenous inputs and endogenous release increased the relative abundance of genes with nitrogen-fixing and nitrification potential nitrogen metabolism functions in surface and bottom waters, respectively. With Planctomycetota and Proteobacteria phyla as potential key groups for regulating nitrogen metabolic processes, Proteobacteria may facilitate the depletion of nitrate in surface and bottom waters, while the close contact of surface waters with the atmosphere accelerated Planctomycetota-dominated nitrogen fixation into the lake. Our findings contribute to the understanding of vertical microbial diversity and its network patterns in grassland type lakes, underscoring the potential role of environmental factors (exogenous inputs and endogenous releases) in bacterioplankton community formation.

Precipitation consistently promotes, but temperature oppositely drives carbon fluxes in temperate and alpine grasslands in China

Temperate grassland (TG) and alpine grassland (AG) are two distinct grassland types with different climatic backgrounds and adaptation patterns. Little is known about the universal and divergent responses of TGs and AGs to climate change, particularly with regard to the carbon (C) fluxes. The large-scale responses of the C fluxes in different grasslands to climate change remain unclear, with only a few comparative studies of distinct responses of the C fluxes in TGs and AGs to climate change hinders our understanding of this subject. In this study, we conducted a large-scale transect study across the Mongolian, Loess, and Tibetan Plateaus in China to reveal the similarities and differences in the responses of the C fluxes in TGs and AGs to climate change. We used C flux data measured by eddy covariance from ChinaFLUX and published literature, covering the period from 2003 to 2020. The results showed that TGs and AGs in China were weak C sinks. Net ecosystem productivity in TGs and AGs exhibited opposite trends with increasing latitude, longitude, and altitude. Elevated water (mean annual precipitation and soil water content) consistently increased the C fluxes. Conversely, increased temperature (mean annual temperature and mean annual soil temperature) reduced the C fluxes in TGs and increased the C fluxes in AGs. The water factors promoted the C fluxes in both TGs and AGs by improving the leaf area indices. Conversely, the temperature factors had a strong direct, negative effect on the C fluxes in TGs and a weak direct, positive effect on the C fluxes in AGs, emphasizing the divergent patterns of the C fluxes in TGs and AGs and their responses to climate change. Overall, this study enhances our knowledge on C sinks and various grassland hydrothermal sensitivities.

A spatio-temporal fusion strategy for improving the estimation accuracy of the aboveground biomass in grassland based on GF-1 and MODIS

The accurate estimation of the aboveground biomass (AGB) is crucial for the sustainable utilization and management of grassland resources. Spatio-temporal inconsistencies between field samples and satellite images are major source of error in the estimation of grassland AGB. To solve this problem, this study selected the Three Rivers Headwater Region as the study area and proposed a selection strategy for base-period images of spatio-temporal fusion that was suitable for use at a large spatial scale in which cloud-free images are difficult to obtain. The spatial and temporal adaptive reflectance fusion model (STARFM) based on the selection strategy was used to generate a synthetic Normalized Difference Vegetation Index (NDVI) dataset with high spatial-temporal resolution by using the maximum value composite of GF-1 NDVI and MODIS NDVI to enhance the spatial-temporal quality of the images for field-scale application. Three estimation models for grassland AGB were then constructed by the random forest algorithm using synthetic NDVI, MODIS NDVI, GF-1 NDVI respectively, together with ancillary data. Following this, the estimation model with the highest accuracy was used to generate a 16-m eight-day time-series AGB in the growing season. The results showed: (1) The synthetic NDVI was correlated closely with the observed GF-1 NDVI, with an average R of 0.825 and a RMSE of 0.087. The temporal trend of the synthetic NDVI for each grassland type was highly consistent with that of the MODIS NDVI in the growing season with a correlation higher than 0.9. (2) The synthetic NDVI reduced the spatial difference between field samples and images to 16-fold, and the temporal difference was controlled to within four days under ideal conditions. (3) The synthetic NDVI improved the estimation accuracy of grassland AGB by about 15.9% and 19.7% (R2), and 13.7% and 17.5% (RMSE) relative to MODIS NDVI and GF-1 NDVI, respectively. (4) The time-series AGB revealed accurately the spatial distribution of and seasonal temporal variations in the grassland biomass. The results of this study may serve as scientific guidance for timely monitoring of grassland conditions and precise management of grassland resources in China.

Assessing long-term trends in vegetation cover change in the Xilin River Basin: Potential for monitoring grassland degradation and restoration

Under the influence of climate change and human activities, the problem of grassland degradation is becoming increasingly severe. Detection of changes in vegetation cover is crucial for a better understanding of the interaction between humans and ecosystems. This study maps changes in vegetation cover using the Google Earth Engine (GEE). We used 36 years of Landsat satellite imagery (1985–2020) in the Xilin River Basin, China, to classify grassland conditions and validated the results with field observation data. The overall classification of the model accuracy assessment was 83.3%. The Dynamic Reference Vegetation Cover Method (DRCM) was adopted to remove the effect of interannual variation of rainfall, allowing to focus on the impact of human activities on vegetation cover changes. The results identify five categories of vegetation cover changes: significantly increased, potentially increased, stable, potentially decreased, and significantly decreased. The reference level is derived from the most persistent land surface coverage across different grassland types and all years. Overall, 9.3% of the study area had a significant increase in vegetation cover, 14.2% a potential increase, 48.6% of the area showed a stable vegetation condition, 9.8% showed a potential decrease, and 18.1% a significant decrease in vegetation cover. The largest proportion of combined potential and significant reduction was 35.2% for desert grassland, where the vegetation faced the most severe reduction. This study will provide a basis for identifying grassland degradation and developing scientific management policies.

Impact of precipitation and grazing on recovery of plant vegetation in temperate grasslands

AbstractGrasslands support a rich diversity that plays a pivotal role in ecological balance, carbon sequestration, and climate regulation. Grassland ecosystems are facing a loss of biodiversity and a decline in soil function due to precipitation variations caused by climate change. However, variations in grassland species diversity are not clearly known, especially under the combined effects of precipitation and grazing. Based on a 5‐year split‐plot experiment with two grazing regimes (i.e., moderate grazing and grazing prohibition) along with three precipitation controls (ambient precipitation and ±50% precipitation) in Inner Mongolian grasslands, we researched the response of precipitation variability and grazing prohibition to vegetation diversity indices and investigated the response of vegetation community composition and biomass to these factors. Five years results showed that increasing precipitation resulted in a significant increase in the coverage of perennial forbs, annual and biennial plants, and Gramineae. Grazing prohibition and increased precipitation significantly increased biomass and species richness compared to all other treatment combinations. Interestingly, grazing exclusion significantly reduced the percentage of Amaryllidaceae, especially in the presence of altered precipitation. The vegetation community composition of a typical grassland was correlated with soil volumetric water content (VWC), bulk density (SBD) and pH, soil organic carbon (SOC), and total nitrogen (TN). VWC, SBD, and TN were found to be the most significant factors affecting vegetation diversity under grazing. Partial canonical ordination revealed that soil moisture, soil bulk density, and SOC had the most significant correlation with vegetation diversity under both grazing prohibition and increased precipitation treatment conditions. These results suggested that alterations in precipitation can change the species composition and ecosystem function of plant communities, leading to a close relationship between species diversity and soil properties. Our results underline the importance of species diversity for soil characteristics and environmental factors in a typical Eurasian steppe ecosystem.