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Livestock grazing may affect small mammalian herbivore-soil microbe interactions and their association with the structure and functions of the ecosystem. However, the role of factors such as vegetation and soil nutrients in regulating these impacts is not clear. Here we conducted a 9-year experiment in temperate steppe to study how Brandt’s vole (Lasiopodomys brandtii) affects the soil microbial community under different livestock grazing intensities. This experiment contained 12 field enclosures with three livestock grazing intensities: control (CK), light grazing (LG), and moderate grazing (MG). We found that vole activity does not significantly change soil microbial diversity under non-grazing conditions. However, under livestock grazing conditions, vole activity led to a significant reduction in soil bacterial diversity and an increase in fungal diversity, demonstrating the impacts of livestock grazing on rodents-soil microbe interactions. The activity of voles significantly altered soil bacterial community composition, with changes primarily attributed to variations in the relative abundance of the phyla Actinobacteria, Bacteroidetes, Firmicutes, Gemmatimonadetes, and Proteobacteria. The soil fungal community remained relatively stable despite vole activity, which can be attributed to the richness of fungal colonies in mycelium and their low sensitivity to changes in external conditions. Vole activity also influenced soil microbial functional groups, and the variations in these groups were further amplified by livestock grazing. Furthermore, the shift in the microbial community composition and diversity induced by vole activity were mainly associated with the reduction of plant aboveground biomass. Overall, our study suggested that livestock grazing enhanced the changes in the soil microbial community induced by rodents, underscoring the importance of managing livestock grazing regimes for grassland conservation.

The understanding of the interplay between the environment, ecosystem structure, and function is crucial for effectively managing ecosystems in the face of climate change and environmental disturbances. Numerous observations and simulation experiments relying on correlation analysis have yielded the conclusion that environmental factors can directly or indirectly affect ecosystem community structure and function. However, the limitations of traditional ecological approaches lie in their inadequate control over confounding factors, thus hindering our comprehensive understanding of the true causal relationships. Our study aims to address these limitations and obtain a more accurate picture of causality about environment, ecosystem structure and function within a long-term time series data of an ecosystem. Here, utilizing a 31-year dataset of typical temperate grassland ecosystems, we developed an advanced causal discovery model and further enhanced it to effectively identify the causal network within the ecosystem, while also quantifying the intensity of causal pathways connecting the environment, ecosystem structure, and function. We found that the primary driver for changes in ecosystem structure and function was the temperature during the growing season, with soil water content being the secondary factor. However, there was only a weak causal relationship between ecosystem structure and gross primary productivity (GPP), which was mediated by eurytopic xerophyte plants. These findings challenge the conventional notion that precipitation is a key driver of changes in ecosystem carbon fluxes, highlighting the importance of plant-available water in regulating ecosystem structure and function. Our results suggest that the effects of global warming and severe droughts on plant growth and carbon sequestration capacity necessitate significant attention and further mitigation measures in arid and semi-arid regions.

Abstract The aim of this study was to gain an understanding of the evolving landscape of research on the intricate relationship between COVID-19 and livelihoods, while also identifying research gaps and directions. To achieve this aim, a systematic review methodology was adopted, and metadata was developed using VOSviewer and R software. A total of 1988 relevant articles on COVID-19 and livelihoods were collected since the outbreak of the pandemic. However, after applying exclusion criteria and conducting thorough reviews, only 1503 articles were deemed suitable for analysis. The data was analyzed in relation to three phases of COVID-19 impacts: the early stage of COVID, the middle stages during the outbreak, and the post-recovery phase. We examined the distribution of research disciplines, regions, authors, institutions, and keywords across these phases. The findings revealed that coping strategies, food security, public health, mental health, social vulnerability, and regional differences were extensively researched areas in relation to COVID-19 and livelihoods. It was found that the United States had the highest volume of research on COVID-19 and livelihoods. Additionally, the top 1.28% of journals published 18.76% of the literature, with a predominantly focused on the environmental category. This study offers valuable perspectives into the vulnerability caused by the COVID-19 pandemic and its impacts on livelihoods. Furthermore, it provides lessons learned, outlines potential future research pathways to understand the dynamics between environmental factors (like COVID-19) and livelihood stress, and includes a comparison of traditional livelihoods research.

Differences in progress across sustainable development goals (SDGs) are widespread globally; meanwhile, the rising call for prioritizing specific SDGs may exacerbate such gaps. Nevertheless, how these progress differences would influence global sustainable development has been long neglected. Here, we present the first quantitative assessment of SDGs’ progress differences globally by adopting the SDGs progress evenness index. Our results highlight that the uneven progress across SDGs has been a hindrance to sustainable development because (1) it is strongly associated with many public health risks (e.g., air pollution), social inequalities (e.g., gender inequality, modern slavery, wealth gap), and a reduction in life expectancy; (2) it is also associated with deforestation and habitat loss in terrestrial and marine ecosystems, increasing the challenges related to biodiversity conservation; (3) most countries with low average SDGs performance show lower progress evenness, which further hinders their fulfillment of SDGs; and (4) many countries with high average SDGs performance also showcase stagnation or even retrogression in progress evenness, which is partly ascribed to the antagonism between climate actions and other goals. These findings highlight that while setting SDGs priorities may be more realistic under the constraints of multiple global stressors, caution must be exercised to avoid new problems from intensifying uneven progress across goals. Moreover, our study reveals that the urgent needs regarding SDGs of different regions seem complementary, emphasizing that regional collaborations (e.g., demand-oriented carbon trading between SDGs poorly performed and well-performed countries) may promote sustainable development achievements at the global scale.

This paper mainly investigates whether emissions trading for pollutant permits more effective. By employing difference-in-differences method and a compressive firm-level dataset, we evaluate the impact of carbon trading system pilot cities policy on enterprises' energy-saving behavior. The findings indicate that after carbon trading system pilot cities policy, enterprises’ coal consumption and coal intensity decreased by almost 34 % and 33 % respectively. The policy effect is more pronounced for larger companies and for firms in energy-intensive sectors. Moreover, the policy effect becomes stronger over time. Our results satisfy the common trend assumption. Meanwhile, the investment in equipment and output are increased, which prove emissions marketization could bring about substantial improvements in productivity.

The conservation of the ecosystem in the Yellow River source region (YRSR) has become a crucial national strategy in China, emphasizing the need for evaluating ecosystem integrity to identify priority conservation areas (PCAs). Current research has primarily employed a limited number of indicators or a single dimension to assess ecosystem integrity, which may overlook comprehensive considerations required for effective conservation planning. To address this, a multidimensional approach was adopted in this study to evaluate ecosystem integrity, incorporating three dimensions: biological diversity, ecosystem function, and stress components. The MaxEnt and Fragstats models were employed to create an ecosystem integrity map and Marxan was used to identify priority conservation areas within the YRSR. Our results showed that (1) the index of ecosystem integrity gradually declined from east to west, consistent with the spatial distribution of biodiversity and ecosystem function, whereas the stress component exhibits a decreasing trend from northeast to southwest. (2) the priority protected areas were distributed in Maduo, Ruoergai, Maqu, Maqin, Henan, Gande, and Jiuzhi Counties. Furthermore, to address existing protection gaps and enhance connectivity, it was recommended to incorporate an additional 27,644 km2 of southwest and central YRSR into the PCAs. Overall, the study offered practical recommendations for the conservation of the ecosystem in the YRSR. In addition, the method of PCAs determination in this study could provide a reference for the government’s growing nature conservation affairs, which will contribute to sustainable development.

Micro- and nanoplastics (MNPs) emissions and pollution are a growing concern due to their potential impact on ecosystems and human health, particularly in soil. This study conducts a comprehensive bibliometric analysis of 2,451 publications spanning from 2006 to 2023. The aim is to assess the research landscape, trends, contributors, and collaborative efforts related to MNPs in soil. Moreover, it examines the extensive research on the effects of MNPs on soil organisms, including earthworms, nematodes, and other fauna as well as the physical–chemical impacts, nanoscale interactions, and ecotoxicological effects on soil microorganisms. Utilizing network analysis, this study explores the global distribution of research across countries, institutions, authors, and keywords, shedding light on the interconnected scientific exploration. The findings reveal a consistent rise in research output over the past decade, reflecting worldwide interest in soil MNPs pollution. It also identifies influential authors and interdisciplinary clusters, highlighting their significant collaborations. Moreover, it pinpoints key institutions and leading journals in this area. Keyword co-occurrence and time-series analysis uncover seven significant research clusters. All provide insights into crucial MNPs aspects and their environmental and health implications. Our findings guide future research and inform strategies to combat MNPs pollution in soils, underscore the need for interdisciplinary approaches to address this complex challenge. In essence, our comprehensive bibliometric analysis serves as a valuable resource, it benefits researchers, policy stakeholders by promoting further research and guiding strategies to mitigate MNPs pollution in soils, in support of ecosystem preservation and human health protection.

In alpine meadows, plants and soil microbes typically engage in competition for nitrogen (N) under N-deficient conditions. However, the acquisition and distribution of N among soil microbes and plants under alpine meadow degradation and climate warming induced by global climate change are still uncharacterized. In this study, we isotope labeled inorganic (NH4+-15N, NO3−-15N) and organic (glycine-15N) N in both degraded and non-degraded plots by using open-top chambers (OTC) to mimic increasing air temperatures. After 6 h, the 15N contents in soil microbes and plants were measured to investigate the effects of degradation and rising air temperature on N allocations in the ecosystems studied. Results showed that alpine meadow degradation significantly reduced soil microbial N accumulation by 52% compared to those in non-degraded plots. In non-degraded plots, warming significantly lowered the organic N levels of soil microbes by 49%, whereas in degraded ones, it reduced both NH4+-15N and NO3−-15N recovery by 80% and 45% on average but increased glycine-15N recovery by 653%. Meanwhile, warming decreased the plant recovery of NH4+-15N and NO3−-15N by 75% and 45% but increased the recovery of glycine-15N by 45% in non-degraded plots. Conversely, in degraded plots, warming markedly lowered NH4+-15N recovery by 40% but increased glycine-15N recovery by 114%. Warming mitigates the effects of alpine meadow degradation on nitrogen allocation among soil microbes and plants. In unwarmed plots, degradation significantly elevated the total 15N recovery ratio of soil microbes to plants by 60%. However, in warmed plots, the impact of degradation on this ratio was reduced. The responses of the 15N recovery ratio of soil microbes and plants to rising temperatures were closely related to alpine meadow quality. In non-degraded areas, warming enhanced the recovery ratio for NH4+-15N by 165% but reduced it for glycine-15N by 66%. Conversely, in degraded plots, warming decreased the recovery ratio for NH4+-15N by 66% but increased it for glycine-15N by 232%. This indicates that warming can increase carbon limitation for soil microbes in degraded alpine meadows, and the restoration of degraded alpine meadows should prioritize restoring carbon accumulation.

Abstract Background Despite the importance of root decomposition in predicting ecosystem responses to future climate change, the effects of branch order on root decomposition and the feedback to soil still remains poorly understood. Here we separated root samples taken from two tree species (Castanopsis fargesii and Schima superba in subtropical forests along the coastal area in eastern China) into four-order classes (1st–2nd order, 3rd order, 4th order, and 5th order) and conducted a 540-day litterbag incubation experiment in laboratory to examine root mass loss, nutrient release, and the influence on soil during decomposition. Results C. fargesii roots of 1st–2nd and 3rd order decayed more slowly than those of 4th and 5th order, but this pattern was not significant for S. superba. Of all the measured root traits, the decomposition rates correlated best with root C/N ratio, diameter and specific root length (SRL) based on the structural equation modeling. Both tree species and root order exhibited significantly effects on root initial traits. Overall, C. fargesii roots decay faster than S. superba, and this appears to be associated with root initial C quality and N concentration. In addition, root order positively affected root decomposition rates mainly through root diameter and SRL. However, no significant difference was found in C and N content between soils below the litterbag with different-order roots. Conclusions Our findings suggest the effects of branch order on root decomposition are dependent on tree species. Moreover, root morphological properties might also be the controlling factor in root decay besides root chemistry fractions. Overall, the integrative effects should be considered to improve our understanding of the fate of fine-root litter and their contribution to soil C and N pool.

Heavy rainfalls caused by global warming are increasing widespread in the future. As the second greenhouse gas, the biological processes of methane (CH4) uptake would be strongly affected by heavy rainfalls. However, how seasonal timing and plant composition affect CH4 uptake in response to heavy rainfalls is largely unknown. Here, we conducted a manipulative experiment to explore the effects of heavy rainfall imposed on middle and late growing season stage on CH4 uptake of constructed steppe communities including graminoid, shrub and their mixture in Inner Mongolia, China. The results of mixed effect model showed that both heavy rainfalls decreased CH4 uptake. Nevertheless, the effect magnitude and the pathways were varied with seasonal timing. Relatively, the late heavy rainfall had larger negative effects. Structural equation model suggested that late heavy rainfall decreased CH4 uptake through decreased diffusivity, pmoA abundance, and NH4+-N content, as products of high soil water content (SWC). However, middle heavy rainfall decreased CH4 uptake only by increasing SWC. Additionally, aboveground biomass (AGB) had negative effects on CH4 uptake under both heavy rainfalls. Additionally, plant composition not only affected CH4 uptake but also regulated CH4 uptake in response to heavy rainfalls. Late heavy rainfall had less negative effect on CH4 uptake in graminoid community than in other two communities, in coincidence with less reduction in NH4+-N content and less increase in SWC and AGB. In contrast, we did not observe obvious difference in effects of middle heavy rainfall on CH4 uptake across three communities. Our findings demonstrated that magnitude and pathways of heavy rainfall effects on CH4 uptake were strongly co-regulated by seasonal timing and plant composition.

Pretreatment of lignocellulosic biomass is crucial for the release of biofermentable sugars for biofuels production, which could greatly alleviate the burgeoning environment and energy crisis caused by the massive usage of traditional fossil fuels. Pyrolysis is a cost-saving pretreatment process that can readily decompose biomass into levoglucosan, a promising anhydrosugar; however, many undesired toxic compounds inhibitory to downstream microbial fermentation are also generated during the pyrolysis, immensely impeding the bioconversion of levoglucosan-containing pyrolysate. Here, we took the first insight into the proteomic responses of a levoglucosan-utilizing and ethanol-producing Escherichia coli to three representative biomass-derived inhibitors, identifying large amounts of differentially expressed proteins (DEPs) that could guide the downstream metabolic engineering for the development of inhibitor-resistant strains. Fifteen up- and eight down-regulated DEPs were further identified as the biomarker stress-responsive proteins candidate for cellular tolerance to multiple inhibitors. Among these biomarker proteins, YcfR exhibiting the highest expression fold-change level was chosen as the target of overexpression to validate proteomics results and develop robust strains with enhanced inhibitor tolerance and fermentation performance. Finally, based on four plasmid-borne genes encoding the levoglucosan kinase, pyruvate decarboxylase, alcohol dehydrogenase, and protein YcfR, a new recombinant strain E. coli LGE-ycfR was successfully created, showing much higher acetic acid-, furfural-, and phenol-tolerance levels compared to the control without overexpression of ycfR. The specific growth rate, final cell density, ethanol concentration, ethanol productivity, and levoglucosan consumption rate of the recombinant were also remarkably improved. From the proteomics-guided metabolic engineering and phenotypic observations, we for the first time corroborated that YcfR is a stress-induced protein responsive to multiple biomass-derived inhibitors, and also developed an inhibitors-resistant strain that could produce bioethanol from levoglucosan in the presence of inhibitors of relatively high concentration. The newly developed E. coli LGE-ycfR strain that could eliminate the commonly-used costly detoxicification processes, is of great potential for the in situ cost-effective bioethanol production from the biomass-derived pyrolytic substrates.

Global warming can trigger dramatic glacier area shrinkage and change the flux of glacial runoff, leading to the expansion and subsequent retreat of riparian wetlands. This elicits the interconversion of riparian wetlands and their adjacent ecosystems (e.g., alpine meadows), probably significantly impacting ecosystem nitrogen input by changing soil diazotrophic communities. However, the soil diazotrophic community differences between glacial riparian wetlands and their adjacent ecosystems remain largely unexplored. Here, soils were collected from riparian wetlands and their adjacent alpine meadows at six locations from glacier foreland to lake mouth along a typical Tibetan glacial river in the Namtso watershed. The abundance and diversity of soil diazotrophs were determined by real-time PCR and amplicon sequencing based on nifH gene. The soil diazotrophic community assembly mechanisms were analyzed via iCAMP, a recently developed null model-based method. The results showed that compared with the riparian wetlands, the abundance and diversity of the diazotrophs in the alpine meadow soils significantly decreased. The soil diazotrophic community profiles also significantly differed between the riparian wetlands and alpine meadows. For example, compared with the alpine meadows, the relative abundance of chemoheterotrophic and sulfate-respiration diazotrophs was significantly higher in the riparian wetland soils. In contrast, the diazotrophs related to ureolysis, photoautotrophy, and denitrification were significantly enriched in the alpine meadow soils. The iCAMP analysis showed that the assembly of soil diazotrophic community was mainly controlled by drift and dispersal limitation. Compared with the riparian wetlands, the assembly of the alpine meadow soil diazotrophic community was more affected by dispersal limitation and homogeneous selection. These findings suggest that the conversion of riparian wetlands and alpine meadows can significantly alter soil diazotrophic community and probably the ecosystem nitrogen input mechanisms, highlighting the enormous effects of climate change on alpine ecosystems.

Grassland degradation has become a global social–ecological problem, which seriously limits the sustainability of indigenous people’s livelihoods. Bibliometrics, a type of analysis based on the Science Citation Index—Expanded (SCI-E), was therefore performed to explore the research trends and focus areas of studies on sustainable livelihoods (SLs). We conducted an in-depth analysis of 489 research publications and their 25,144 references from 1991 to 2020. The results show that only few papers have been published, but the number of countries and research institutions involved shows an overall imbalance. We identified eight main clusters based on keyword co-occurrence, these being studies the content of which is an important representation of current research directions in this topic. The document co-citation analysis revealed 10 research clusters, representing the frontiers of research. Clusters included the following topics: NPP (Net Primary Productivity) dynamics, global change, ecological restoration, risk indicators, livelihood strategies, smallholder systems, drought relief, sustainable land management and common pool resources. We reviewed and interpreted these clusters in depth with a view to provide an up-to-date account of the dynamics of this research. As the first scientometric evaluation of research on sustainable livelihoods in grassland ecosystems, this study provides several theoretical and practical implications for global poverty eradication research, which are of great scientific value for global sustainable development.

As global change continues to intensify, the mode and rate of nitrogen input from the atmosphere to grassland ecosystems had changed dramatically. Firstly, we conducted a systematic analysis of the literature on the topic of nitrogen deposition impacts over the past 30 years using a bibliometric analysis. A systematic review of the global research status, publication patterns, research hotspots and important literature. We found a large number of publications in the Chinese region, and mainly focuses on the field of microorganisms. Secondly, we used a meta-analysis to focus on microbial changes using the Chinese grassland ecosystem as an example. The results show that the research on nitrogen deposition in grassland ecosystems shows an exponential development trend, and the authors and research institutions of the publications are mainly concentrated in China, North America, and Western Europe. The keyword clustering results showed 11 important themes labeled climate change, elevated CO2, species richness and diversity, etc. in these studies. The burst keyword analysis indicated that temperature sensitivity, microbial communities, etc. are the key research directions. The results of the meta-analysis found that nitrogen addition decreased soil microbial diversity, and different ecosystems may respond differently. Treatment time, nitrogen addition rate, external environmental conditions, and pH had major effects on microbial alpha diversity and biomass. The loss of microbial diversity and the reduction of biomass with nitrogen fertilizer addition will alter ecosystem functioning, with dramatic impacts on global climate change. The results of the study will help researchers to further understand the subject and have a deep understanding of research hotspots, which are of great value to future scientific research.

Globally, droughts are the most widespread climate factor impacting carbon (C) cycling. However, as the second-largest terrestrial C flux, the responses of soil respiration (Rs) to extreme droughts co-regulated by seasonal timing and PFT (plant functional type) are still not well understood. Here, a manipulative extreme-duration drought experiment (consecutive 30 days without rainfall) was designed to address the importance of drought timing (early-, mid-, or late growing season) for Rs and its components (heterotrophic respiration (Rh) and autotrophic respiration (Ra)) under three PFT treatments (two graminoids, two shrubs, and their combination). The results suggested that regardless of PFT, the mid-drought had the greatest negative effects while early-drought overall had little effect on Rh and its dominated Rs. However, PFT treatments had significant effects on Rh and Rs in response to the late drought, which was PFT-dependence: reduction in shrubs and combination but not in graminoids. Path analysis suggested that the decrease in Rs and Rh under droughts was through low soil water content induced reduction in MBC and GPP. These findings demonstrate that responses of Rs to droughts depend on seasonal timing and communities. Future droughts with different seasonal timing and induced shifts in plant structure would bring large uncertainty in predicting C dynamics under climate changes.

Nitrogen (N) addition can increase the vegetative growth, improve the plant production, and restore the degraded terrestrial ecosystems. But, it simultaneously aggravates the soil phosphorus (P) limitation for plant growth, thus affecting its positive effects on ecosystems. However, how plants and soil microorganisms will change under conditions of high P content in soil is still unknown. In this study, we explored the effects of three levels of N addition (0, 7.5, and 15 g.N.m–2.year–1) on plants and microorganisms at the high P addition level (13.09 g.P.m–2.year–1) in the alpine steppe. We found that the soil microbial community composition had no significant difference between different N addition levels, and the soil AN and AP had a significant effect on the phospholipid fatty acid (PLFA) composition. The abundance of the core PLFAs (i.e., 16:1ω7c, 16:0, a17:1, i17:0, 18:1ω9c, and 18:1ω7c) also remained unchanged after N addition, and microbes at individual, population, and community levels were all correlated with SOM, AK, AN, and pH. Conversely, plant biomass and nutrient content showed linear trends with increasing N addition, especially the dominant functional groups. Specifically, the biomass and plant tissue N content of Gramineae, and the total N content of aboveground biomass were all improved by N addition. They were correlated with soil ammonium and AP. The structural equation modeling (SEM) demonstrated that N addition had a direct negative effect on soil microbial biomass, but an indirect positive effect on aboveground biomass via soil ammonium. These findings clarify the importance of N-amendment in regulating plants and microorganisms under high P conditions and provide a better understanding of the N-added effects in the alpine steppe.

Extensive grassland degradation under climate change and intensified human activities has threatened ecological security and caused a variety of environmental problems. However, it is still challenging to predict the grassland degradation status on a large scale because it is a multi-factorial phenomenon with complex changes in ecosystem structure and function, which is hard to be fully characterized through mechanism models. The emergence of machine learning algorithms provides a potential to model complex systems and mine information from multi-source data without elucidating underlying mechanisms. Here, we utilized random forest and neural network algorithms to predict the grassland degradation represented by the net primary productivity (NPP) changing rate based on multi-source data including geographic, meteorological, plant traits, land use type and microbial variables in the Chinese Northern grassland. Particularly, the microbial roles in determining the degradation status were concerned. Results show that a high prediction precision was achieved by random forest model, rather than by neural network model, with a mean relative error of 16.9% and a mean square error of 9.273e-05. Besides identified longitude, arid index and current NPP state, specific soil microbial groups, mainly Solirubrobacter, were screened as credible biomarkers. Regarding model fitting, geographic, meteorological and plant variables explained 61.8% of the total variance, which was enhanced up to 72.8% by the rest microbial markers. These findings provide a theoretical basis to establish a pre-warning system for grassland management and policy-making.

Though being fundamental to global diversity distribution, little is known about the geographic pattern of soil microorganisms across different biotas on a large scale. Here, we investigated soil prokaryotic communities from Chinese northern grasslands on a scale up to 4000 km in both alpine and temperate biotas. Prokaryotic similarities increased over geographic distance after tipping points of 1760–1920 km, generating a significant U-shape pattern. Such pattern was likely due to decreased disparities in environmental heterogeneity over geographic distance when across biotas, supported by three lines of evidences: (1) prokaryotic similarities still decreased with the environmental distance, (2) environmental selection dominated prokaryotic assembly, and (3) short-term environmental heterogeneity followed the U-shape pattern spatially, especially attributed to dissolved nutrients. In sum, these results demonstrate that environmental selection overwhelmed the geographic ‘distance’ effect when across biotas, overturning the previously well-accepted geographic pattern for microbes on a large scale.

Drylands cover about 41% of the Earth’s land surface and are inhabited by more than two billion people, who rely on the diversified ecosystem services provided by drylands for their livelihoods. Achieving sustainable livelihoods (SLs) is a key component of achieving the sustainable development goals set by the agenda in 2030. Although it has aroused extensive interest, research on SLs in drylands at a regional scale is still limited. This paper aims to address this research gap by evaluating SLs through a geographic gradient of aridity in Inner Mongolia. A sustainable livelihood index (SLI) was developed using a wide range of indicators in a sustainable livelihood framework (SLF). The weight of the indicators was determined by the entropy weight method, and the characteristics of the spatial distribution of the SLI were analyzed. The results showed that the SLI varies greatly across aridity zones. In terms of livelihood assets, the SLI in the dry sub-humid zone was 15% higher than in the arid zones, while, surprisingly, semi-arid zones were found to have the most vulnerable livelihoods (rather than the arid zones). The reason for this is that land management and planning approaches are necessary in drylands. In further detail, Moran’s I index illustrated that the overall performance of the SLI of each league or city has a positive spatial correlation, while through local spatial correlation it was found that Hinggan and Chifeng are hot spot areas and Hohhot is a cold spot area. The lack of physical and social capital is an important obstacle for SLs. Based on the analysis of SLs in Inner Mongolia, the characteristics of the sustainable development of local residents were revealed. In this paper, we call for an integrated (i.e., focusing on natural and human capital) land management and planning approach for drylands to reflect the nature of the tightly coupled socio-ecological systems.

Abstract Background The Xilingol grassland ecosystem has abundant superficial coal reserves. Opencast coal mining and burning of coal for electricity have caused a series of environmental challenges. Biogenic generation of methane from coal possesses the potential to improve economic and environmental outcomes of clean coal utilization. However, whether the microbes inhabiting the grassland soil have the functional potential to convert coal into biomethane is still unclear. Results Microbial communities in an opencast coal mine and in grassland soil covering and surrounding this mine and their biomethane production potential were investigated by Hiseq sequencing and anaerobic cultivation. The microbial communities in covering soil showed high similarity to those in the surrounding soil, according to the pairwise weighted UniFrac distances matrix. The majority of bacterial communities in coal and soil samples belonged to the phyla Firmicutes, Bacteroidetes, Actinobacteria and Proteobacteria. The dominant bacterial genera in grassland soil included Gaiella, Solirubrobacter, Sphingomonas and Streptomyces; whereas, the most abundant genus in coal was Pseudarthrobacter. In soil, hydrogenotrophic Methanobacterium was the dominant methanogen, and this methanogen, along with acetoclastic Methanosarcina and methylotrophic Methanomassiliicoccus, was detected in coal. Network-like Venn diagram showed that an average of 28.7% of microbial communities in the samples belonged to shared genera, indicating that there is considerable microbial overlap between coal and soil samples. Potential degraders and methanogens in the soil efficiently stimulated methane formation from coal samples by the culturing-based approach. The maximum biogenic methane yields from coal degradation by the microbial community cultured from grassland soil reached 22.4 μmol after 28 day. Conclusion The potential microbial coal degraders and methanogenic archaea in grassland soil were highly diverse. Significant amounts of biomethane were generated from coal by the addition of grassland soil microbial communities. The unique species present in grassland soil may contribute to efficient methanogenic coal bioconversion. This discovery not only contributes to a better understanding of global microbial biodiversity in coal mine environments, but also makes a contribution to our knowledge of the synthetic microbiology with regard to effective methanogenic microbial consortia for coal degradation.

A strong negative non-linear relationship exists between stomatal density (SD) and size (SS) or length (SL), which is of high importance in gas exchange and plant evolution. However, the cause of this relationship has not been clarified. In geometry, SD has an intrinsic relationship with SS−1 or SL−2, which is defined as a geometric constraint here. We compiled global data to clarify the influence of this geometric constraint on the SD-SS relationship. The log-log scaling slope of the relationship between SD and SS and between SD and SL was not significantly different from −1 and −2, respectively. Although the non-geometric effect drove the SD-SS curve away from the power function with −1, a larger influence of the geometric constraint on SD was found. Therefore, the higher geometric constraint possibly causes the SD-SS relationship to be inevitably non-linear and negative. Compared to pteridophyta and gymnosperms, the geometric constraint was lower for angiosperm species, possibly due to most of them having smaller stomata. The relaxation of the geometric constraint seems to extend the upper range of SD in angiosperm species and hence enable them to exploit a wide range of environments.

Grassland remote sensing (GRS) is an important research topic that applies remote sensing technology to grassland ecosystems, reflects the number of grassland resources and grassland health promptly, and provides inversion information used in sustainable development management. A scientometrics analysis based on Science Citation Index-Expanded (SCI-E) was performed to understand the research trends and areas of focus in GRS research studies. A total of 2692 papers related to GRS research studies and 82,208 references published from 1980 to 2020 were selected as the research objects. A comprehensive overview of the field based on the annual documents, research areas, institutions, influential journals, core authors, and temporal trends in keywords were presented in this study. The results showed that the annual number of documents increased exponentially, and more than 100 papers were published each year since 2010. Remote sensing, environmental sciences, and ecology were the most popular Web of Science research areas. The journal Remote Sensing was one of the most popular for researchers to publish documents and shows high development and publishing potential in GRS research studies. The institution with the greatest research documents and most citations was the Chinese Academy of Sciences. Guo X.L., Hill M.J., and Zhang L. were the most productive authors across the 40-year study period in terms of the number of articles published. Seven clusters of research areas were identified that generated contributions to this topic by keyword co-occurrence analysis. We also detected 17 main future directions of GRS research studies by document co-citation analysis. Emerging or underutilized methodologies and technologies, such as unmanned aerial systems (UASs), cloud computing, and deep learning, will continue to further enhance GRS research in the process of achieving sustainable development goals. These results can help related researchers better understand the past and future of GRS research studies.

The Hindu Kush Himalayan (HKH) region is one of the most ecologically vulnerable regions in the world. Several studies have been conducted on the dynamic changes of grassland in the HKH region, but few have considered grassland net ecosystem productivity (NEP). In this study, we quantitatively analyzed the temporal and spatial changes of NEP magnitude and the influence of climate factors on the HKH region from 2001 to 2018. The NEP magnitude was obtained by calculating the difference between the net primary production (NPP) estimated by the Carnegie–Ames Stanford Approach (CASA) model and the heterotrophic respiration (Rh) estimated by the geostatistical model. The results showed that the grassland ecosystem in the HKH region exhibited weak net carbon uptake with NEP values of 42.03 gC∙m−2∙yr−1, and the total net carbon sequestration was 0.077 Pg C. The distribution of NEP gradually increased from west to east, and in the Qinghai–Tibet Plateau, it gradually increased from northwest to southeast. The grassland carbon sources and sinks differed at different altitudes. The grassland was a carbon sink at 3000–5000 m, while grasslands below 3000 m and above 5000 m were carbon sources. Grassland NEP exhibited the strongest correlation with precipitation, and it had a lagging effect on precipitation. The correlation between NEP and the precipitation of the previous year was stronger than that of the current year. NEP was negatively correlated with temperature but not with solar radiation. The study of the temporal and spatial dynamics of NEP in the HKH region can provide a theoretical basis to help herders balance grazing and forage.

Soils δ13C and δ15N are now regarded as useful indicators of nitrogen (N) status and dynamics of soil organic carbon (SOC). Numerous studies have explored the effects of various factors on soils δ13C and δ15N in terrestrial ecosystems on different scales, but it remains unclear how co-varying climatic, edaphic and biotic factors independently contribute to the variation in soil δ13C and δ15N in temperate grasslands on a large scale. To answer the above question, a large-scale soil collection was carried out along a vegetation transect across the temperate grasslands of Inner Mongolia. We found that mean annual precipitation (MAP) and mean annual temperature (MAT) do not correlate with soil δ15N along the transect, while soil δ13C linearly decreased with MAP and MAT. Soil δ15N logarithmically increased with concentrations of SOC, total N and total P. By comparison, soil δ13C linearly decreased with SOC, total N and total P. Soil δ15N logarithmically increased with microbial biomass C and microbial biomass N, while soil δ13C linearly decreased with microbial biomass C and microbial biomass N. Plant belowground biomass linearly increased with soil δ15N but decreased with soil δ13C. Soil δ15N decreased with soil δ13C along the transect. Multiple linear regressions showed that biotic and edaphic factors such as microbial biomass C and total N exert more effect on soil δ15N, whereas climatic and edaphic factors such as MAT and total P have more impact on soil δ13C. These findings show that soil C and N cycles in temperate grasslands are, to some extent, decoupled and dominantly controlled by different factors. Further investigations should focus on those ecological processes leading to decoupling of C and N cycles in temperate grassland soils.

The alpine grassland on the Qinghai-Tibet Plateau covers an area of about 1/3 of China’s total grassland area and plays a crucial role in regulating grassland ecological functions. Both environmental changes and irrational use of the grassland can result in severe grassland degradation in some areas of the Qinghai-Tibet Plateau. However, the magnitude and patterns of the physical and anthropogenic factors in driving grassland variation over northern Tibet remain debatable, and the interactive influences among those factors are still unclear. In this study, we employed a geographical detector model to quantify the primary and interactive impacts of both the physical factors (precipitation, temperature, sunshine duration, soil type, elevation, slope, and aspect) and the anthropogenic factors (population density, road density, residential density, grazing density, per capita GDP, and land use type) on vegetation variation from 2000 to 2015 in northern Tibet. Our results show that the vegetation index in northern Tibet significantly decreased from 2000 to 2015. Overall, the stability of vegetation types was sorted as follows: the alpine scrub > the alpine steppe > the alpine meadow. The physical factors, rather than the anthropogenic factors, have been the primary driving factors for vegetation dynamics in northern Tibet. Specifically, meteorological factors best explained the alpine meadow and alpine steppe variation. Precipitation was the key factor that influenced the alpine meadow variation, whereas temperature was the key factor that contributed to the alpine steppe variation. The anthropogenic factors, such as population density, grazing density and per capita GDP, influenced the alpine scrub variation most. The influence of population density is highly similar to that of grazing density, which may provide convenient access to simplify the study of the anthropogenic activities in the Tibet plateau. The interactions between the driving factors had larger effects on vegetation than any single factor. In the alpine meadow, the interaction between precipitation and temperature can explain 44.6% of the vegetation variation. In the alpine scrub, the interaction between temperature and GDP was the highest, accounting for 27.5% of vegetation variation. For the alpine steppe, the interaction between soil type and population density can explain 29.4% of the vegetation variation. The highest value of vegetation degradation occurred in the range of 448−469 mm rainfall in the alpine meadow, 0.61−1.23 people/km2 in the alpine scrub and −0.83−0.15 °C in the alpine steppe, respectively. These findings could contribute to a better understanding of degradation prevention and sustainable development of the alpine grassland ecosystem in northern Tibet.

In the alpine steppe zone on the Central Tibetan Plateau, a large amount of area has been degraded due to natural and artificial factors. N & P fertilization is widely accepted to recover degraded pastures in other regions all over the world. However, it is not clear how alpine steppe communities respond to N & P fertilization, and what is the optimal application rate, in the perspective of forage production. To attempt to explore these questions, in July 2013, two fencing sites were designed in Baingoin County with 12 treatments of different levels of nitrogen (N0: 0; N1: 7.5 g m(-2) yr(-1); N2: 15 g m(-2) yr(-1)) & phosphate (P0: 0; P1: 7.5 gP2O5 m(-2) yr(-1); P2: 15 gP2O5 m(-2) yr(-1); P3: 30 gP2O5 m(-2) yr(-1)). The results indicated N&P addition was capable to ameliorate the quality of the two sites in the Tibetan Plateau steppe. Increasing N application level resulted in significant increment in Gramineae and total biomass in the two sites. P addition significantly improved the quantity of Compositae, total biomass and the biomasss of other species in site II, while it only significantly improved the total biomass in site I. Gramineae was much more sensitive to N-induced changes than P-induced changes, and this indicated N addition was better to ameliorate the quality of plateau steppe than P-induced changes. No strong evidence was found for critical threshold within 15 g N m(-2) yr(-1), and there was decreasing tendency when P addition rate was above 15 g m(-2) yr(-1). N&P has the potential to accelerate soil acidification, which improved the content of available K, likely as a result of nonsignificant correlation between biomass and soil moisture. This work highlights the the tradeoffs that exist in N and P addition in recovering degraded steppe.

In recent decades, satellite-derived start of vegetation growing season (SOS) has advanced in many northern temperate and boreal regions. Both the magnitude of temperature increase and the sensitivity of the greenness phenology to temperature-the phenological change per unit temperature-can contribute the advancement. To determine the temperature-sensitivity, we examined the satellite-derived SOS and the potentially effective pre-season temperature (T eff) from 1982 to 2008 for vegetated land between 30°N and 80°N. Earlier season vegetation types, i.e., the vegetation types with earlier SOSmean (mean SOS for 1982-2008), showed greater advancement of SOS during 1982-2008. The advancing rate of SOS against year was also greater in the vegetation with earlier SOSmean even the T eff increase was the same. These results suggest that the spring phenology of vegetation may have high temperature sensitivity in a warmer area. Therefore it is important to consider temperature-sensitivity in assessing broad-scale phenological responses to climatic warming. Further studies are needed to explore the mechanisms and ecological consequences of the temperature-sensitivity of start of growing season in a warming climate.

The wetlands of the Qinghai-Tibetan Plateau are believed to play an important role in global nutrient cycling, but the composition and diversity of microorganisms in this ecosystem are poorly characterized. An understanding of the effects of geography and microtopography on microbial populations will provide clues to the underlying mechanisms that structure microbial communities. In this study, we used pyrosequencing-based analysis of 16S rRNA gene sequences to assess and compare the composition of soil microbial communities present in hummock and hollow soils from three wetlands (Dangxiong, Hongyuan and Maduo) on the Qinghai-Tibetan Plateau, the world's highest plateau. A total of 36 bacterial phyla were detected. Proteobacteria (34.5% average relative abundance), Actinobacteria (17.3%) and Bacteroidetes (11%) had the highest relative abundances across all sites. Chloroflexi, Acidobacteria, Verrucomicrobia, Firmicutes, and Planctomycetes were also relatively abundant (1-10%). In addition, archaeal sequences belonging to Euryarchaea, Crenarchaea and Thaumarchaea were detected. Alphaproteobacteria sequences, especially of the order Rhodospirillales, were significantly more abundant in Maduo than Hongyuan and Dangxiong wetlands. Compared with Hongyuan soils, Dangxiong and Maduo had significantly higher relative abundances of Gammaproteobacteria sequences (mainly order Xanthomonadales). Hongyuan wetland had a relatively high abundance of methanogens (mainly genera Methanobacterium, Methanosarcina and Methanosaeta) and methanotrophs (mainly Methylocystis) compared with the other two wetlands. Principal coordinate analysis (PCoA) indicated that the microbial community structure differed between locations and microtopographies and canonical correspondence analysis indicated an association between microbial community structure and soil properties or geography. These insights into the microbial community structure and the main controlling factors in wetlands of the Qinghai-Tibetan Plateau provide a valuable background for further studies on biogeochemical processes in this distinct ecosystem.

Quantifying the variability and changes in phenology and gross primary production (GPP) of alpine wetlands in the Qinghai–Tibetan Plateau under climate change is essential for assessing carbon (C) balance dynamics at regional and global scales. In this study, in situ eddy covariance (EC) flux tower observations and remote sensing data were integrated with a modified, satellite-based vegetation photosynthesis model (VPM) to investigate the variability in climate change, phenology, and GPP of an alpine wetland ecosystem, located in Zoige, southwestern China. Two-year EC data and remote sensing vegetation indices showed that warmer temperatures corresponded to an earlier start date of the growing season, increased GPP, and ecosystem respiration, and hence increased the C sink strength of the alpine wetlands. Twelve-year long-term simulations (2000–2011) showed that: (1) there were significantly increasing trends for the mean annual enhanced vegetation index (EVI), land surface water index (LSWI), and growing season GPP (R2 ≥ 0.59, p < 0.01) at rates of 0.002, 0.11 year−1 and 16.32 g·C·m−2·year−1, respectively, which was in line with the observed warming trend (R2 = 0.54, p = 0.006); (2) the start and end of the vegetation growing season (SOS and EOS) experienced a continuous advancing trend at a rate of 1.61 days·year−1 and a delaying trend at a rate of 1.57 days·year−1 from 2000 to 2011 (p ≤ 0.04), respectively; and (3) with increasing temperature, the advanced SOS and delayed EOS prolonged the wetland’s phenological and photosynthetically active period and, thereby, increased wetland productivity by about 3.7–4.2 g·C·m−2·year−1 per day. Furthermore, our results indicated that warming and the extension of the growing season had positive effects on carbon uptake in this alpine wetland ecosystem.

This article uses 2011 sampling survey data on the nationwide state of employment of college graduates to investigate differences in the following three areas: starting salary, industry entry, and entry to state-owned work units between college students with urban and rural household registrations. The study finds that college students with rural registrations have differing degrees of disadvantages in the three aforementioned aspects, and the disadvantage for industry entry is the most prominent. Among the factors studied, family background and differences in social relationships during the employment search are the most important factors leading to employment inequalities among urban and rural college students. Choice of major can explain some of the disadvantages of rural students in starting salary and entrance to high-income industries, and school performance of college students was not a major cause of employment differences for urban and rural college students. [This article was translated by Jeff Keller.]