Evaluation of an autonomous acoustic surveying technique for grassland bird communities in Nebraska.

Monitoring trends in wildlife communities is integral to making informed land management decisions and applying conservation strategies. Birds inhabit most niches in every environment and because of this they are widely accepted as an indicator species for environmental health. Traditionally, point counts are the common method to survey bird populations, however, passive acoustic monitoring approaches using autonomous recording units have been shown to be cost-effective alternatives to point count surveys. Advancements in automatic acoustic classification technologies, such as BirdNET, can aid in these efforts by quickly processing large volumes of acoustic recordings to identify bird species. While the utility of BirdNET has been demonstrated in several applications, there is little understanding of its effectiveness in surveying declining grassland birds. We conducted a study to evaluate the performance of BirdNET to survey grassland bird communities in Nebraska by comparing this automated approach to point count surveys. We deployed ten autonomous recording units from March through September 2022: five recorders in row-crop fields and five recorders in perennial grassland fields. During this study period, we visited each site three times to conduct point count surveys. We compared focal grassland bird species richness between point count surveys and the autonomous recording units at two different temporal scales and at six different confidence thresholds. Total species richness (focal and non-focal) for both methods was also compared at five different confidence thresholds using species accumulation curves. The results from this study demonstrate the usefulness of BirdNET at estimating long-term grassland bird species richness at default confidence scores, however, obtaining accurate abundance estimates for uncommon bird species may require validation with traditional methods.

Changes in productivity partitioning induced by precipitation extremes increase inaccuracy of grassland carbon estimation.

The fraction of net primary productivity (NPP) allocated to belowground organs (fBNPP) in grasslands is a critical parameter in global carbon cycle models; moreover, understanding the effect of precipitation changes on this parameter is vital to accurately estimating carbon sequestration in grassland ecosystems. However, how fBNPP responds to temporal precipitation changes along a gradient from extreme drought to extreme wetness, remains unclear, mainly due to the lack of long-term data of belowground net primary productivity (BNPP) and the fact that most precipitation experiments did not have a gradient from extreme drought to extreme wetness. Here, by conducting both a precipitation gradient experiment (100-500 mm) and a long-term observational study (34 years) in the Inner Mongolia grassland, we showed that fBNPP decreased linearly along the precipitation gradient from extreme drought to extreme wetness due to stronger responses in aboveground NPP to drought and wet conditions than those of BNPP. Our further meta-analysis in grasslands worldwide also indicated that fBNPP increased when precipitation decreased, and the vice versa. Such a consistent pattern of fBNPP response suggests that plants increase the belowground allocation with decreasing precipitation, while increase the aboveground allocation with increasing precipitation. Thus, the linearly decreasing response pattern in fBNPP should be incorporated into models that forecast carbon sequestration in grassland ecosystems; failure to do so will lead to underestimation of the carbon stock in drought years and overestimation of the carbon stock in wet years in grasslands.

Application of remote sensing to understand the role of Galician feral horses in the biomass reduction of a shrub-grassland-dominated landscape.

Galician forests in northwestern Spain are subject to frequent wildfires with high environmental and economic costs. In addition, due to the consequences of climate change, these fires are becoming more virulent, occurring throughout the year, and taking place in populated areas, in some cases involving the loss of human life. Therefore, forest fire prevention is even more relevant than mitigating its consequences. Given the costs involved in forestry work, alternative measures to reduce fuel load and create vegetation gaps are needed. One involves grazing by an endemic species of feral horses (Equus ferus atlanticus) that feed on thicket-forming gorse (Ulex europaeus). In a 100-ha forest fenced study area stocked with 11 horses, four 50 m2 enclosed plots prevented the access of these wild animals to the vegetation, with the aim of manipulating their impact on the reduction of forest biomass. The measurement of biomass volumes is an important method that can describe the assessment of wildfire risks, unfortunately, high-resolution data collection at the regional scale is very time-consuming. The best result can be using drones (unmanned aerial vehicles - UAVs) as a method of collecting remotely sensed data at low cost. From September 2018 to November 2020, we collected information about aboveground biomass from these four enclosed plots and their surrounding areas available for horses to forage, via UAV. These data, together with environmental variables from the study site, were used as input for a fire model to assess the differences in the surface rate of spread (SROS) among grazed and ungrazed areas. Our results indicated a consistent but small reduction in the SROS between 0.55 and 3.10 m/min in the ungrazed enclosured plots in comparison to their grazed surrounding areas (which have an SROS between 15 and 25 m/min). The research showed that radar remote sensing (UAV) can be used to map forest aboveground biomass, and emphasized the importance and role of feral horses in Galicia as a prevention tool against wildfires in gorse-dominated landscapes.

Plant roots affect free-living diazotroph communities in temperate grassland soils despite decades of fertilization.

Fixation of atmospheric N2 by free-living diazotrophs accounts for an important proportion of nitrogen naturally introduced to temperate grasslands. The effect of plants or fertilization on the general microbial community has been extensively studied, yet an understanding of the potential combinatorial effects on the community structure and activity of free-living diazotrophs is lacking. In this study we provide a multilevel assessment of the single and interactive effects of different long-term fertilization treatments, plant species and vicinity to roots on the free-living diazotroph community in relation to the general microbial community in grassland soils. We sequenced the dinitrogenase reductase (nifH) and the 16S rRNA genes of bulk soil and root-associated compartments (rhizosphere soil, rhizoplane and root) of two grass species (Arrhenatherum elatius and Anthoxanthum odoratum) and two herb species (Galium album and Plantago lanceolata) growing in Austrian grassland soils treated with different fertilizers (N, P, NPK) since 1960. Overall, fertilization has the strongest effect on the diazotroph and general microbial community structure, however with vicinity to the root, the plant effect increases. Despite the long-term fertilization, plants strongly influence the diazotroph communities emphasizing the complexity of soil microbial communities' responses to changing nutrient conditions in temperate grasslands.

Climate change will lead to range shifts and genetic diversity losses of dung beetles in the Gobi Desert and Mongolian Steppe.

Desertification is known to be a major threat to biodiversity, yet our understanding of the consequent decline in biodiversity remains insufficient. Here, we predicted climate change-induced range shifts and genetic diversity losses in three model dung beetles: Colobopterus erraticus, Cheironitis eumenes, and Gymnopleurus mopsus, distributed across the Gobi Desert and Mongolian Steppe, areas known for desertification. Phylogeographic analyses of mitochondrial COI sequences and species distribution modeling, based on extensive field investigations spanning 14 years, were performed. Species confined to a single biome were predicted to contract and shift their distribution in response to climate change, whereas widespread species was predicted to expand even if affected by range shifts. We indicated that all species are expected to experience significant haplotype losses, yet the presence of high singleton frequencies and low genetic divergence across geographic configurations and lineages mitigate loss of genetic diversity. Notably, Cheironitis eumenes, a desert species with low genetic diversity, appears to be the most vulnerable to climate change due to the extensive degradation in the Gobi Desert. This is the first study to predict the response of insects to desertification in the Gobi Desert. Our findings highlight that dung beetles in the Gobi Desert and Mongolian Steppe might experience high rates of occupancy turnover and genetic loss, which could reshuffle the species composition.

Beyond fire: Flower production naturally occurs and is also influenced by leaf removal in a Neotropical savanna herb.

Several herbaceous species exhibit mass flowering after fires in Neotropical savannas. However, unequivocal evidence of fire dependency and the consequences for plant reproduction are lacking. In nutrient-poor fire-prone savannas, the damage caused by fire and by other means (e.g., leaf removal, but not necessarily having a negative impact) constrains the maintenance and expansion of plant population by affecting the ability of individuals to recover. Therefore, the compensatory responses of plants to both damages should be convergent in such environments. Using Bulbostylis paradoxa-reported to be fire-dependent to flower-as a model, we investigated the role of fire and leaf removal in anticipating the flowering and reproduction periods, and its possible consequences on seedling establishment. We monitored 70 burned individuals, 70 damaged/clipped, and 35 without damage to estimate time for flowering, seed quality and germination parameters. To expand our sampling coverage, we examined high-resolution images from herbarium collections in the SpeciesLink database. For each herbarium image, we recorded the presence or absence of a fire scar, the month of flowering, and the number of flowering stalks. Bulbostylis paradoxa was fire-stimulated but not dependent on fire to flower, with 65.7% of the individuals flowering in the burned area, 48.6% in the clipped, and 11.4% in the control. This was consistent with the analysis of the herbarium images in which 85.7% of the specimens with flowers had fire scars and 14.3% did not. Burned individuals synchronized flowering and produced more viable seeds. However, the seeds might face a period of unsuitable ecological conditions after early to mid-dry season fires. Flowering of unburned plants was synchronized with the onset of the rainy season. Flexibility in flowering and vegetative reproduction by fragmentation confer to this species, and most likely other plants from the herbaceous layer, the capability of site occupation and population persistence in burned and unburned savanna sites.

[Differences and drivers of leaf stable carbon and nitrogen isotope in herbs under different vegetation types on the eastern Qinghai-Tibet Plateau]. / é’è—é«˜åŽŸä¸œç¼˜ä¸åŒæ¤è¢«ç±»åž‹ä¸‹è‰æœ¬æ¤ç‰©å¶ç‰‡ç¢³æ°®ç¨³å®šåŒä½ç´ å·®å¼‚åŠå ¶é©±åŠ¨å› ç´ .

The natural abundance of stable carbon and nitrogen isotopes (δ13C and δ15N) in leaves can provide comprehensive information on the physiological and ecological processes of plants and has been widely used in ecological research. However, recent studies on leaf δ13C and δ15N have focused mainly on woody species, few studies have been conducted on herbs in different vegetation types, and their differences and driving factors are still unclear. In this study, we focused on the herbs in subalpine coniferous forests, alpine shrublands, and alpine mea-dows on the eastern Qinghai-Tibet Plateau, and investigated the differences in leaf δ13C and δ15N of herbs and the driving factors. The results showed that there were significant differences in leaf δ13C and δ15N values of herbs among different vegetation types, with the highest δ13C and δ15N values in alpine meadows, followed by alpine shrublands, and the lowest in subalpine coniferous forests. Using variation partitioning analysis, we revealed that differences in leaf δ13C and δ15N of herbs among various vegetation types were driven by both leaf functional traits and climate factors, with the contribution of leaf functional traits being relatively higher than that of climate factors. Hierarchical partitioning results indicated that mean annual temperature (MAT), chlorophyll content index, leaf nitrogen content per unit area (Narea), and leaf mass per area were the main drivers of leaf δ13C variations of herbs across different vegetation types, while the relative importance of Narea and MAT for variation in leaf δ15N of herbs was much higher than those other variables. There was a strong coupling relationship between leaf δ13C and δ15N as indicated by the result of the ordinary least squares regression. Our findings could provide new insights into understanding the key drivers of leaf δ13C and δ15N variations in herbs across different vegetation types.

[Influence of climate change and human activities on grassland phenology in Anhui Province]. / 安徽省气候变化和人类活动对草地物候的影响.

To explore the influence of climate change and human activities on grassland phenology in Anhui Pro-vince, and quantify the contribution rate of climate change and human activities to phenology, we extracted the phenology of grassland, including the start of growing season (SOS) and the end of growing season (EOS), based on the normalized difference vegetation index (NDVI) dataset of Anhui Province from 2003 to 2020. The temporal and spatial characteristics and future evolution trends of phenological changes were analyzed using slope trend ana-lysis, Mann-Kendall non-parametric test, and Hurst index. We further conducted correlation analysis and residual analysis based on the datasets of mean annual temperature and mean annual precipitation to explore the responses of phenology to climate change and human activities, and quantify their contribution rate. The results showed that SOS and EOS showed an advancing trend with a rate of 0.8 and 0.7 days per year from 2003 to 2020. SOS in the sou-thern part of the study area was significantly earlier than in the central and northern regions, while EOS gradually advanced from south to north. Both SOS and EOS in the future showed an advancing trend. SOS was negatively correlated with annual average temperature, while positively correlated with annual precipitation. EOS was negatively correlated with both annual average temperature and annual precipitation. The proportion of the area where SOS was advanced driven by both climate change and human activities was 56.9%, and the value was 48.3% for EOS. Human activities were the main driving factor for phenology, and climate change was the secondary driving factor. The relative contributions of human activities and climate change to SOS were 66.4% and 33.6%, and to EOS were 61.2% and 38.8%, respectively. Human activities had stronger impact on SOS and EOS than climate change, resulting in earlier phenology.

[Assessment of the lagging effect of vegetation response and loss probability in the Pearl River basin under drought stress]. / å¹²æ—±èƒè¿«ä¸‹ç æ±ŸæµåŸŸæ¤è¢«å“åº”çš„æ»žåŽæ•ˆåº”åŠæŸå¤±æ¦‚çŽ‡è¯„ä¼°.

We quantified the lag time of vegetation response to drought in the Pearl River basin (PRB) based on the standardized precipitation evapotranspiration index (SPEI) and normalized difference vegetation index (NDVI), and constructed a vegetation loss probability model under drought stress based on the Bayesian theory and two-dimensional joint distribution. We further quantitatively evaluated the spatial variations of loss probability of four vegetation types (evergreen broadleaf forest, mixed forest, grassland, and cropland) under different drought intensities. The results showed that the drought risk in eastern West River, the upper reaches of North River and East River, and southern Pearl River Delta was obviously higher than that in other regions during 1982-2020. The response time of vegetation to drought in high-altitude areas in the upper reaches of PRB (mostly<3 month) was generally shorter than that in low altitude areas (>8 month). Drought exacerbated the probability of vegetation loss, with higher vulnerability of mixed forest than the other three vegetation types. The loss probability of vegetation was lower in northwestern PRB than that in central PRB.

Extending grazing time during the warm season can reduce P limitation and increase the N cycling rate in arid desert steppes.

Ecological stoichiometry serves as a valuable tool for comprehending biogeochemical cycles within grassland ecosystems. The impact of grazing time on the concentration and stoichiometric characteristics of carbon (C), nitrogen (N), and phosphorus (P) in desert steppe ecosystems remains ambiguous. This research was carried out in a desert grassland utilizing a completely randomized experimental design. Four distinct grazing time treatments were implemented: fenced grassland (FG, control), delay to start and early to end grazing grassland (DEG), delay to start grazing grassland (DG), and traditional grazing grassland (TG). The patterns of C, N, and P concentrations and their stoichiometry in various components of the ecosystem, as well as their driving factors under different grazing times were examined. The results showed that grazing time positively influenced C and N concentrations in leaves, while negatively affecting N concentrations in roots. TG had a significant positive effect on soil P concentrations but a negative effect on soil C:P and N:P ratios. Plant C:N, C:P, and N: P ratios were mainly influenced by N and P. The soil C:N ratio was primarily influenced by soil N, the soil C:P ratio was affected by both soil C and P, and the soil N:P ratio was influenced by both soil N and P. The growth of plants in desert steppes is mainly limited by P; however, as grazing time increased, P limitation gradually decreased and the N cycling rate increased. C-N, C-P, and N-P in various plant organs and soils demonstrated significant anisotropic growth relationships at different grazing times. Soil organic carbon, pH, and soil total phosphorus were the main driving factors that affected changes in ecological C:N:P stoichiometry. These results will help improve grassland management and anticipate the response of grassland systems to external disturbances with greater accuracy.

An Improved Ningxia Desert Herbaceous Plant Classification Algorithm Based on YOLOv8.

Wild desert grasslands are characterized by diverse habitats, uneven plant distribution, similarities among plant class, and the presence of plant shadows. However, the existing models for detecting plant species in desert grasslands exhibit low precision, require a large number of parameters, and incur high computational cost, rendering them unsuitable for deployment in plant recognition scenarios within these environments. To address these challenges, this paper proposes a lightweight and fast plant species detection system, termed YOLOv8s-KDT, tailored for complex desert grassland environments. Firstly, the model introduces a dynamic convolutional KernelWarehouse method to reduce the dimensionality of convolutional kernels and increase their number, thus achieving a better balance between parameter efficiency and representation ability. Secondly, the model incorporates triplet attention into its feature extraction network, effectively capturing the relationship between channel and spatial position and enhancing the model's feature extraction capabilities. Finally, the introduction of a dynamic detection head tackles the issue related to target detection head and attention non-uniformity, thus improving the representation of the target detection head while reducing computational cost. The experimental results demonstrate that the upgraded YOLOv8s-KDT model can rapidly and effectively identify desert grassland plants. Compared to the original model, FLOPs decreased by 50.8%, accuracy improved by 4.5%, and mAP increased by 5.6%. Currently, the YOLOv8s-KDT model is deployed in the mobile plant identification APP of Ningxia desert grassland and the fixed-point ecological information observation platform. It facilitates the investigation of desert grassland vegetation distribution across the entire Ningxia region as well as long-term observation and tracking of plant ecological information in specific areas, such as Dashuikeng, Huangji Field, and Hongsibu in Ningxia.

Analysis of rotational grazing management for sheep in mixed grassland.

Sown mixed grassland is rarely used for livestock raising and grazing; however, different forages can provide various nutrients for livestock, which may be beneficial to animal health and welfare. We established a sown mixed grassland and adopted a rotational grazing system, monitored the changes in aboveground biomass and sheep weights during the summer grazing period, measured the nutrients of forage by near-infrared spectroscopy, tested the contents of medium- and long-chain fatty acids by gas chromatography, and explored an efficient sheep fattening system that is suitable for agro-pastoral interlacing areas. The results showed that the maximum forage supply in a single grazing paddock was 4.6 kg DM/d, the highest dry matter intake (DMI) was 1.80 kg DM/ewe/d, the average daily weight gain (ADG) was 193.3 g, the DMI and ADG were significantly correlated (P < 0.05), and the average feed weight gain ratio (F/G) reached 8.02. The average crude protein and metabolizable energy intake by sheep were 286 g/ewe/d and 18.5 MJ/ewe/d respectively, and the n-6/n-3 ratio of polyunsaturated fatty acids in mutton was 2.84. The results indicated that the sheep fattening system had high feed conversion efficiency, could improve the yield and quality of sheep, and could be promoted in suitable regions.

Tibetan Plateau grasslands might increase sequestration of microbial necromass carbon under future warming.

Microbial necromass carbon (MNC) can reflect soil carbon (C) sequestration capacity. However, changes in the reserves of MNC in response to warming in alpine grasslands across the Tibetan Plateau are currently unclear. Based on large-scale sampling and published observations, we divided eco-clusters based on dominant phylotypes, calculated their relative abundance, and found that their averaged importance to MNC was higher than most other environmental variables. With a deep learning model based on stacked autoencoder, we proved that using eco-cluster relative abundance as the input variable of the model can accurately predict the overall distribution of MNC under current and warming conditions. It implied that warming could lead to an overall increase in the MNC in grassland topsoil across the Tibetan Plateau, with an average increase of 7.49 mg/g, a 68.3% increase. Collectively, this study concludes that alpine grassland has the tendency to increase soil C sequestration capacity on the Tibetan Plateau under future warming.

Effects of acid mine drainage and sediment contamination on soil bacterial communities, interaction patterns, and functions in alkaline desert grassland.

Acid mine drainage and sediments (AMD-Sed) contamination pose serious ecological and environmental problems. This study investigated the geochemical parameters and bacterial communities in the sediment layer (A) and buried soil layer (B) of desert grassland contaminated with AMD-Sed and compared them to an uncontaminated control soil layer (CK). The results showed that soil pH was significantly lower and iron, sulfur, and electroconductivity levels were significantly higher in the B layer compared to CK. A and B were dominated by Proteobacteria and Actinobacteriota, while CK was dominated by Firmicutes and Bacteroidota. The pH, Fe, S, and potentially toxic elements (PTEs) gradients were key influences on bacterial community variability, with AMD contamination characterization factors (pH, Fe, and S) explaining 48.6 % of bacterial community variation. A bacterial co-occurrence network analysis showed that AMD-Sed contamination significantly affected topological properties, reduced network complexity and stability, and increased the vulnerability of desert grassland soil ecosystems. In addition, AMD-Sed contamination reduced C/N-cycle functioning in B, but increased S-cycle functioning. The results highlight the effects of AMD-Sed contamination on soil bacterial communities and ecological functions in desert grassland and provide a reference basis for the management and restoration of desert grassland ecosystems in their later stages.

Predicting the potential risk of Caragana shrub encroachment in the Eurasian steppe under anthropogenic climate change.

Climate change and human activities drive widespread shrub encroachment in global grassland ecosystems, particularly in the Eurasian steppe. Caragana shrubs, the primary contributors to shrub encroachment in this region, play a crucial role in shaping the ecosystem's structure and function. Future changes in the suitable distribution range of Caragana species will directly affect the ecological security and sustainable socio-economic development of the Eurasian steppe ecosystem. We used an ensemble modeling approach to predict Caragana shrub-dominated plant communities' current and future distribution in three major steppe subregions: the Black Sea-Kazakhstan steppe, the Tibetan Plateau steppe, and the Central Asian steppe. We assessed the potential risk of Caragana shrub encroachment by predicting changes in the suitable distribution area of 19 Caragana shrub species under future climate changes. Our research findings suggest that the expansion of Caragana species in different subregions of the Eurasian steppe is influenced by the effects of climate change in various ways. The distribution of Caragana species is primarily influenced by precipitation and temperature, and the global human modification (ghm) has a significant impact on the Central Asian and Tibetan Plateau subregions. Minimal changes are expected in the Black Sea-Kazakhstan subregion, a slight increase on the Tibetan Plateau, and a substantial rise in the Central Asian subregion, which suggests a higher potential risk of Caragana species shrub encroachment in that area. Our research provides valuable insights into the response of Caragana shrub encroachment to changing climates and human activities. It also has implications for the sustainable management of different areas of the vast Eurasian steppe ecosystem.

Taxon-dependent diversity response along a temperate elevation gradient covered by grassland.

Elevational gradients constitute excellent systems for understanding the mechanisms that generate and maintain global biodiversity patterns. Climatic gradients associated with elevation show strong influence on species distribution in mountains. The study of mountains covered by the same habitat type is an ideal scenario to compare alternatives to the energy hypotheses. Our aim was to investigate how changes in climatic conditions along the elevational gradient drive α- and ß-diversity of four taxa in a mountain system located within a grassland biome. We sampled ants, spiders, birds and plants, and measured climatic variables at six elevational bands (with 10 sampling sites each) established between 470 and 1,000 masl on a mountain from the Ventania Mountain System, Argentina. Species richness per site and ß-diversity (turnover and nestedness) between the lowest band and upper sites were estimated. For most taxa, species richness declined at high elevations and energy, through temperature, was the major driver of species richness for ants, plants and birds, prevailing over productivity and water availability. The major ß-diversity component was turnover for plants, spiders and birds, and nestedness for ants. The unique environmental conditions of the upper bands could favour the occurrence of specialist and endemic species.

[Application and prospects of hyperspectral remote sensing in monitoring plant diversity in grassland]. / é«˜å ‰è°±é¥æ„Ÿåœ¨è‰åŽŸæ¤ç‰©å¤šæ ·æ€§ç›‘æµ‹ä¸­çš„åº”ç”¨ä¸Žå±•æœ›.

The biodiversity of grasslands is important for ecosystem function and health. The protection and mana-gement of grassland biodiversity requires the collection of the information on plant diversity. Hyperspectral remote sensing, with its unique advantages of extensive coverage and high spectral resolution, offers a new solution for long-term monitoring of plant diversity. We first reviewed the development history of hyperspectral remote sensing technology, emphasized its advantages in monitoring grassland plant diversity, and further analyzed its specific applications in this field. Finally, we discussed the challenges faced by hyperspectral remote sensing technology in its applications, such as the complexity of data processing, accuracy of algorithms, and integration with ground-based remote sensing data, and proposes prospects for future research directions. With the advancement of remote sensing technology and the integrated application of multi-source data, hyperspectral remote sensing would play an increasingly important role in grassland ecological monitoring and biodiversity conservation, which could provide scientific basis and technical support for global ecological protection and sustainable development.

Correlative ecological niche model applications to predicting landscape-scale woody plant encroachment in Kansas tallgrass prairie systems.

Woody plant encroachment (WPE) in grassland ecosystems has been a pervasive process across the Great Plains, yet a predictive understanding of where it will occur has been elusive. As an exploration of tools of potential utility in this challenge, we mapped WPE processes over the years 2015-2021 in a set of 9 counties in central Kansas. We developed and tested two correlative models based on landscape features: one that assessed distribution of evergreen trees in 2015, and another that assessed areas of WPE in succeeding years. Both models were successful, being able to predict 2015 forest distributions and being able to predict WPE during 2015-2021, as functions of characteristics of landscapes. These simple, correlative models will certainly not be able to predict WPE processes globally, or even regionally, but provide first proof-of-concept explorations for the central Great Plains region.

Mowing aggravates the adverse effects of nitrogen addition on soil acid neutralizing capacity in a meadow steppe.

Soil acidification induced by reactive nitrogen (N) inputs is a major environmental issue in grasslands, as it lowers the acid neutralizing capacity (ANC). The specific impacts of different N compound forms on ANC remain unclear. Grassland management practices like mowing and grazing can remove a considerable amount of soil N and other nutrients, potentially mitigating soil acidification by removing N from the ecosystem or aggravating it by removing base cations. However, empirical evidence regarding the joint effects of adding different forms of N compounds and mowing on ANC changes in different-sized soil aggregates is still lacking. This study aimed to address this knowledge gap by examining the effects of three N compounds (urea, ammonium nitrate, and ammonium sulfate) combined with mowing (mown vs. unmown) on soil ANC in different soil aggregate sizes (>2000 µm, 250-2000 µm, and <250 µm) through a 6-year field experiment in Inner Mongolia grasslands. We found that the average decline in soil ANC caused by ammonium sulfate (AS) addition (-78.9%) was much greater than that by urea (-25.0%) and ammonium nitrate (AN) (-52.1%) as compared to control. This decline was attributed to increased proton (H+) release from nitrification and the leaching of exchangeable Ca2+ and Mg2+. Mowing aggravated the adverse effects of urea and AN on ANC, primarily due to the reduction in soil organic matter (SOM) contents and the removal of exchangeable Ca2+, K+, and Na + via plant biomass harvest. This pattern was consistent across all aggregate fractions. The lack of variation in soil ANC among different soil aggregate fractions is likely due to the contrasting trend in the distribution of exchangeable Ca2+ and Mg2+. Specifically, the concentration of exchangeable Ca2+ increased with increasing aggregate size, while the opposite was true for that of exchangeable Mg2+. These findings underscore the importance of considering the forms of N compounds when assessing the declines of ANC induced by N inputs, which also calls for an urgent need to reduce N emissions to ensure the sustainable development of the meadow ecosystems.

Analyses of LULC dynamics in a socio-ecological system of the Bale Mountains Eco Region of Southeast Ethiopia.

Analysis of land use and land cover (LULC) change and its drivers and impacts in the biodiversity hotspot of Bale Mountain's socio-ecological system is crucial for formulating plausible policies and strategies that can enhance sustainable development. The study aimed to analyze spatio-temporal LULC changes and their trends, extents, drives, and impacts over the last 48 years in the Bale Mountain social-ecological system. Landsat imagery data from the years 1973, 1986, 1996, 2014, and 2021 together with qualitative data were used. LULC classification scheme employed a supervised classification method with the application of the maximum likelihood algorithm technique. In the period between 1973 and 2021, agriculture, bare land, and settlement showed areal increment by 153.13%, 295.57%, and 49.03% with the corresponding increased annual rate of 1.93%, 2.86%, and 0.83%, respectively. On the contrary, forest, wood land, bushland, grass land, and water body decreased by 29.97%, 1.36%, 28.16%, 8.63%, and 84.36% during the study period, respectively. During the period, major LULC change dynamics were also observed; the majority of woodland was converted to agriculture (757.8 km2) and grassland (531.3 km2); and forests were converted to other LULC classes, namely woodland (766.5 km2), agriculture (706.1 km2), grassland (34.6 km2), bushland (31.9 km2), settlement (20.5 km2), and bare land (14.3 km2). LULC changes were caused by the expansion of agriculture, settlement, overgrazing, infrastructure development, and fire that were driven by population growth and climate change, and supplemented by inadequate policy and institutional factors. Social and environmental importance and values of land uses and land covers in the study area necessitate further assessment of potential natural resources' user groups and valuation of ecosystem services in the study area. Hence, we suggest the identification of potential natural resource-based user groups, and assessment of the influence of LULC changes on ecosystem services in Bale Mountains Eco Region (BMER) for the sustainable use and managements of land resources.