The spatial pattern and community assembly of soil microbial taxa have notable meanings for biodiversity shaping and maintaining mechanisms. Rare fungal taxa may exhibit distinct patterns and assembly mechanisms compared to abundant taxa, but such information is limited, especially at large scales. Here, we investigated distance-decay patterns and underlying assembly mechanisms for abundant and rare fungal taxa in 129 soil samples collected across 4,000 km in Chinese Northern grasslands, based on high-throughput sequencing data. A total of 208 abundant OTUs (relative abundance > 0.1%, 2.73% of entire OTUs) and 5,779 rare OTUs (relative abundance < 0.01%, 75.85% of entire OTUs) were identified. Both abundant and rare fungal taxa showed significant distance-decay relationships (P < 0.001), but the turnover rate for rare taxa (0.0024 per 100 km) was nearly half that of abundant taxa (0.0054 per 100 km) based on the binary Bray-Curtis distance. The lower turnover of rare fungal taxa was likely due to their community assembly mechanism dominated by stochastic processes, which were less influenced by environmental gradients. In contrast, abundant taxa assembly was dominated by deterministic factors like soil variables and plant traits, which varied significantly along the geographic distance. Consistently, rare fungal taxa were also less sensitive to environmental changes, with a lower turnover rate by environmental distance (0.0027 vs. 0.0099) than abundant taxa. In summary, our findings revealed that rare fungal taxa, shaped mainly by stochastic processes, had lower spatial turnover compared to abundant taxa, dominated by deterministic processes, enhancing our understanding of rare microbial biogeography.

We analyzed the patterns variation of blue and green waters in the Yellow River Basin from 1998 to 2020 and evaluated the contributions of climate change and human activity on those variations. During the study period, both blue water volume and green waters flow increased overall across the Basin. Water withdrawal and water consumption showed an increasing trend, mainly due to increases in domestic and ecological water withdrawal and water consumption; the trend concentrated mainly in the Toudaoguai (TDG) area. Water return flow showed a decreasing trend, mainly due to decreases in agricultural and industrial water return flow in the Yellow River Basin. Throughout the study period, blue water volume and green waters flow were higher in the west than in the east, while precipitation was higher in the southeast than in the northwest. Changes in land cover were able to explain 87% of the observed variation in water return flow and 95% of the observed variation in water consumption. Changes in land cover indirectly affected blue water volume (the path coefficient β = 0.209) and green water flow (β = 0.273). Through its influence on precipitation, climate change affected blue water volume and green waters flows (β > 0.8). Through its influence on water consumption, water withdrawal affected green water flows (β = 0.4), the extent of which depended on precipitation. These findings highlight the need for efficient water management in the Yellow River Basin to ensure the long-term health of its ecosystems.

Arid and semi-arid vegetation is characterized by plant patches of different sizes, and plant cover is determined by patch size (PS) and number of patches (NP). However, it is still unclear how PS and NP contribute to the restoration of degraded grasslands through grazing exclusion (GE). Transect lines were sampled in six alpine steppe communities in Tibet in 2017 and 2018. Both PS and NP were assessed and compared between inside and outside grazing exclosures. Our results showed that grazing exclosures increased the mean size but decreased the total number of plant patches. This pattern of change was common to other species and could not be attributed to a shift in community composition. The results suggest that the recovery of the degraded alpine steppe is being driven by PS at the expense of NP. By promoting the expansion of the larger patches while excluding the smaller ones, GE led to an aggregating pattern with a higher proportion of bare ground, potentially reducing primary productivity.

Complex ecosystems exhibit more nonlinearity and stochasticity than the simple ones, rendering timely and accurate detection regime shifts in complex dynamic ecosystems a challenge. To resolve this dilemma, one of the most critical steps is to determine and quantify the equilibrium states reached by complex ecosystems under a given disturbance. This study utilizes the energy-transfer-network equilibrium model based on Nash-equilibrium theory and the maximum power principle to quantify and predict the equilibrium state of a complex ecosystem with multiple trophic levels. The model successfully simulated ecosystem energy transfer under equilibrium and quantified ecosystem state. The application of the model to monitor the aboveground biomass of a long-term dataset of un-grazed steppe achieved the description and prediction of the regime shift. This approach can possibly be used not only to find the equilibrium state for complex and simple ecosystems but also to remove the limitations of current methods to determine the attraction domain or stable points through statistical or difference equations in regime shift studies.

The impacts of human-driven environmental changes on the stability of natural grasslands have been assessed by comparing differences between manipulative warming and grazing plots and reference plots. However, little is known about whether or how ambient climate regulates the effects of manipulative treatments. A 36-year observational dataset shows that there is a nonlinear response of community stability to ambient climate. Manipulative warming and grazing decrease community stability with experiment duration through an increase in legume coverage and/or decrease in species asynchrony, due to exceeding the threshold of background annual mean air temperature with decreasing background annual mean air temperature through time during the 10-year experiment period. Moreover, the temperature sensitivity of community stability is more sensitive under the ambient treatment than under the manipulative treatments. Therefore, our study emphasizes the importance of the context dependency of the response of community stability to human-driven environmental changes.

Understanding the microbial linkages among the soils, plants and animals is crucial for maintaining the balance of an ecosystem in grazed grasslands. However, previous studies always focused on the biotopes of soil, phyllosphere and faeces separately and little has been known about the microbial distribution and migration among these biotopes. In this study, a systematic survey to investigate the overlap and differentiation among the various microbiotas of biotopes and how the environmental filter on microorganisms served for the ecosystem was conducted at the molecular level. Our findings revealed the biotopes' role of biofilter leads to the discrepancy of microbiota distribution among the soil, phyllosphere and faeces. The substantial overlaps between soil and phyllosphere in fungi, bacteria and archaea indicated that soil could potentially perform as the microbial reservoir for phyllosphere. However, there was only fungal mass migration running through the ecosystem to link all the biotopes while there are little communal OTUs of bacteria and archaea. These findings promoted our understanding of the biotope contribution to microbial migration and improved the knowledge of microbial linkages in the grazed grassland ecosystem.