Temperature drives elevational diversity patterns of different types of organisms in Qinghai-Tibetan Plateau wetlands

Elevation-associated pathways mediate aquatic biodiversity at multi-trophic levels along a plateau inland river

Aquatic biodiversity plays a significant role in maintaining the ecological balance and the overall health of riverine ecosystems. Elevation is an important factor influencing biodiversity patterns. However, it is still unclear through which pathway elevation influences riverine biodiversity at different trophic levels. In this study, the elevation-associated pathways affecting aquatic biodiversity at different trophic levels were explored using structural equation modeling (SEM) and taking the Bayin River, China as the case. The results showed that the elevational patterns were different among aquatic organisms at different trophic levels. For macroinvertebrates and bacteria, the pattern was hump-shaped; while for phytoplankton and zooplankton, it was U-shaped. Building upon these observed elevational patterns, our investigation delved into the direct and indirect pathways through which elevation influences aquatic biodiversity. We found that elevation exerts an impact on aquatic biodiversity via indirect pathways. For all aquatic organisms investigated, the major pathway through which elevation influences biodiversity is mediated by water temperature and water quality. For aquatic organisms at higher trophic levels, like macroinvertebrates and zooplankton, the crucial pathway is also mediated by the landscape. The results of this study contributed to understanding the effects of elevation on aquatic organisms at different trophic levels and provided an important basis for the assessment of riverine biodiversity at large scales.

Plant diversity is more important than soil microbial diversity in explaining soil multifunctionality in Qinghai-Tibetan plateau wetlands

The Qinghai-Tibetan Plateau harbors rich and diverse wetlands that provide multiple ecological functions simultaneously. Although the relationships between biodiversity and wetland functioning have been well studied in recent decades, the links between the multiple features of plant and microbial communities and soil multifunctionality (SMF) remain unknown in the high-altitude wetlands that are extremely sensitive to human disturbance. Here, using the single function, averaging, weighted, and multiple-threshold methods, we calculated the SMF of Qinghai-Tibetan wetlands based on 15 variables associated with soil nutrient status, nutrient cycle, and greenhouse gas emission. We then related SMF to multidimensional (species, phylogenetic, and functional) diversity of plants and soil microorganisms and microbial network modules. The results showed that plant diversity explained more variance in SMF than soil microbial diversity, and plant species richness and phylogenetic distance were positive predictors of SMF. Bacterial network modules were more positively related to SMF than fungal network modules, and the alpha diversity of bacterial network modules contributed more to SMF than the diversity of the whole bacterial community. Pediococcus, Hirsutella, and Rhodotorula were biomarkers for SMF and had significant relationships with nitrogen mineralization and greenhouse gas emissions. Together, these results highlight the importance of plant diversity and bacterial network modules in determining the SMF, which are crucial to predicting the response of ecosystem functioning to biodiversity loss under intensifying anthropogenic activities.

Linking ecosystem multifunctionality to microbial community features in rivers along a latitudinal gradient

Microorganisms regulate numerous ecosystem functions and show considerable differences along a latitudinal gradient. Although studies have revealed the latitudinal patterns of microbial community structure and single ecosystem function, the latitudinal patterns of ecosystem multifunctionality (EMF) and how microbial communities affect EMF along a latitudinal gradient remain unclear. Here, we collected channel sediments, riparian rhizosphere soils, and riparian bulk soils from 30 rivers across China and calculated EMF using 18 variables related to nitrogen cycling, nutrient pool, plant productivity, and water quality. We also determined microbial diversity (taxonomic and functional) and microbial network complexity using metagenomic sequencing. The results showed that EMF significantly decreased with increasing latitude in riparian rhizosphere and bulk soils but not in channel sediments. Microbial taxonomic and functional richness (observed species) in channel sediments were significantly higher in the low-latitude group than in the high-latitude group. However, microbial co-occurrence networks were more complex in the high-latitude group compared with the low-latitude group. Abiotic factors, primarily geographic and climatic factors, contributed more to EMF than microbial diversity and network complexity parameters in which only betweenness centralization had a significant relationship with EMF. Together, this study provides insight into the latitudinal pattern of EMF in rivers and highlights the importance of large-scale factors in explaining such latitudinal patterns.IMPORTANCEEcosystem multifunctionality (EMF) is the capacity of an ecosystem to provide multiple functions simultaneously. Microorganisms, as dominant drivers of belowground processes, have a profound effect on ecosystem functions. Although studies have revealed the latitudinal patterns of microbial community structure and single ecosystem function, the latitudinal patterns of EMF and how microbial communities affect EMF along a latitudinal gradient remain unclear. We collected channel sediments, riparian rhizosphere soils, and riparian bulk soils from 30 rivers along a latitudinal gradient across China and calculated EMF using 18 variables related to nitrogen cycling, nutrient pool, plant productivity, and water quality. This study fills a critical knowledge gap regarding the latitudinal patterns and drivers of EMF in river ecosystems and gives new insights into how microbial diversity and network complexity affect EMF from a metagenomic perspective.

Data-driven assessment of soil total nitrogen on the Qinghai-Tibet Plateau

The investigation of soil total nitrogen (STN) holds significant importance in the preservation and sustainability of Earth's ecosystems. The Qinghai-Tibet Plateau (QTP), renowned as the world's most expansive plateau and characterized by its exceptionally delicate ecosystem, demands an in-depth exploration of its STN content. In this study, we use a machine learning approach to extrapolate point-scale measured STN stocks to the entire QTP and calculated STN storage from 0 to 2 m. Our results show that the XGB algorithm performs well in modeling STN despite variations in simulation accuracy for specific depth ranges. The spatial distribution of STN across the QTP exhibits pronounced heterogeneity, especially for the 0-50 cm soil layer, with relatively higher STN stocks in the southeast and lower stocks in the northwest of QTP. The vertical distribution reveals a gradual decrease in STN storage with increasing depth. The 0-50 cm soil layer holds the highest STN stocks, averaging around 0.78 kg/m2, which is almost the sum of STN stocks in the 50-100 cm and 100-200 cm soil layers. Meanwhile, the STN stocks are smaller in permafrost zone than that in non-permafrost zone. We also investigate the impact factors that control the spatiotemporal distribution of STN. It indicates that vegetation, precipitation, temperature, and elevation are the major factors for STN distribution, while physical properties of the soil have a relatively smaller impact. These findings are crucial for understanding the distribution and evolution of STN on the QTP.