The stability mechanisms of ecosystem functions have been a hot topic in ecology. However, in wetland ecosystems, the mechanisms by which biotic and abiotic factors interact to affect ecosystem stability in changing environments remain largely unclear. This study investigated the key factors and underlying mechanisms that regulate the spatial variability of wetland productivity by measuring community productivity, multiple components of biodiversity (i.e., species diversity, community functional composition and diversity), and environmental factors along a well-characterized gradient of wetland degradation in the lower reaches of the Yellow River. The results showed that the spatial variability of productivity in wetlands increased with intensified degradation. The spatial variability of wetland productivity was not related to species richness, but was mainly affected by changes in community functional composition and diversity. Furthermore, degradation-induced changes in soil nutrients drove the spatial variability of productivity to increase with shifts in functional composition towards more conservative traits (i.e., higher leaf dry matter content and root tissue density), and to decrease with higher functional trait diversity. These findings reveal the driving mechanism of spatial variability in wetland productivity under degradation, and suggest that reduced nutrient availability, by altering plant resource strategies, can affect the spatial reliability of key ecosystem functions in wetlands.

Fine root dynamics are crucial for terrestrial ecosystem productivity and nutrient cycling. However, the effects of nitrogen (N) deposition on fine root dynamics in temperate ecosystems remain poorly understood. In this study, we used a meta-analysis to explore the general patterns and key drivers of fine root biomass and turnover in temperate forests and grasslands in response to N application. We found that N application significantly reduced fine root biomass compared to the control group (no N application), with notable differences across N forms. However, the impact of N application on fine root biomass remained consistent across ecosystem types, soil depths and root diameters. In terms of fine root turnover rate, N application had no significant overall effect, and the response did not vary across N forms, ecosystem types, soil depths or root diameters. However, significant differences were observed across methods for estimating fine root turnover rate. Multiple regression analysis showed that mean annual temperature (MAT) and experimental factors (including duration and N application rates) were the primary determinants of fine root biomass response to N application. In contrast, fine root turnover was not significantly influenced by any of the factors analyzed. Overall, our findings highlight the negative impact of N application on fine root biomass and the neutral effect on fine root turnover, and also suggest that find root dynamics are closely associated with experimental factors, including experiment duration and N application rate. This study provides an important advancement in understanding the feedback between root dynamics and global change, offering insights for developing management strategies to address belowground ecological processes under global change scenarios.

Soil microorganisms play a very important role in the alpine grassland ecosystem of the Qinghai-Tibetan Plateau as indicators of environmental change; scientific and reasonable rest-grazing can effectively curb the degradation of grassland, but the response of soil microbial communities to rest-grazing and the intrinsic driving factors are uncertain. Therefore, in this study, two types of winter-spring pastures, steppe meadow (StM) and swamp meadow (SwM), were selected for rest-grazing and grazing treatments in spring, and indicators such as vegetation community characteristics, soil properties and microbial community changes were measured to investigate the response of soil microbial communities to rest-grazing and its mechanisms. The results showed that rest-grazing in spring could significantly increase above-ground biomass and soil organic carbon in alpine grassland. In steppe meadow, Total PLFAs, Actinomycetes, Bacteria, Gram-positive bacterial and Gram-negative bacterial were lower than the control in StM1, higher than the control in StM2. Total PLFAs, Arbuscular mycorrhizal fungi, Actinomycetes, Bacteria, Fungi, Gram-positive bacterial, Gram-negative bacterial and ratio of Gram-positive bacterial to Gram-negative bacterial were higher than control in SwM. The stress indices of the two grassland types were lower than the control after rest-grazing. Fungi tended to increase with above-ground biomass when grassland type was not taken into account (P<0.05), Total PLFAs showed an increasing trend with above-ground biomass (P>0.05). The combination of soil physicochemical properties and vegetation community characteristics influences changes in soil microbial community structure (40.87%). Simpson, vegetation coverage, soil total phosphorus and soil bulk density significantly influenced the soil microbial community, with species diversity (Simpson) being the most significant contributor (60%) to the soil microbial community. In summary, rest-grazing in spring can beneficially affect the soil microbial community by improving the characteristics of alpine grassland vegetation communities and restoring soil properties, which in turn can beneficially affect the soil microbial community.

Canopy properties (e.g., canopy structure and spectral variables) strongly influence forest above-ground biomass (AGB). However, the importance of these canopy properties in driving AGB in natural forests, especially relative to other drivers such as plant species diversity and environmental conditions, remains poorly understood. We assessed the relative importance of canopy properties (structure and spectral variables) and plant species diversity (multidimensional diversity metrics and trait composition) in regulating AGB along environmental gradients (topography and soil nutrients) in a temperate forest in Northeast China, using UAV-based LiDAR and hyperspectral data. We found that the explanatory power of environmental conditions, plant species diversity, canopy spectral properties and canopy structure on temperate old-growth forests AGB was 3.8%, 8.0%, 4.1% and 13.3%, respectively. AGB increased with increasing canopy height and structural complexity. Canopy spectral diversity was a better predictor of AGB than traditional diversity metrics in old-growth forests. Canopy spectral composition also played an important role in explaining AGB in the secondary forests. In addition, plant phylogeny, functional diversity and the community-weighted mean (CWM) of acquisitive traits had significant direct positive effects on AGB. Finally, topography and soil nutrient content indirectly influenced AGB through canopy properties and plant species diversity. Our study highlights the key role of canopy properties in influencing AGB. For future monitoring, regular monitoring with spectral and LiDAR data should be emphasized to provide real-time insights for forest management.

Traits and their correlation networks can reflect plant adaptive strategies. However, variations in traits and trait correlation networks across heteromorphic leaves within species remain largely unexplored. In this study, we systematically quantified a diverse array of leaf traits—spanning morphology, anatomy, physiology and biochemistry—among the striped, lanceolate, ovate, and broadly ovate leaves of Populus euphratica, aiming to elucidate the adaptive differences across these various leaf types. We found that the four heteromorphic leaves showed significant differences in leaf traits. From striped leaves to broadly ovate leaves, leaf size, leaf thickness, water use efficiency and catalase content significantly increased, while specific leaf area showed the opposite pattern. Principal component analysis and cluster analysis revealed distinct aggregation and clear demarcation of the four leaf types, indicating substantial variations in trait compositions and their distinct ecological adaptations. Plant trait networks varied significantly across the four leaf types, with the broadly ovate leaves exhibiting a fragmented network structure that enhances their modularity. This suggests strong resilience to disturbances and is consistent with the characteristic foliage on mature trees. Regardless of leaf type, nitrogen and phosphorus consistently emerged as hub traits within plant trait networks, underscoring their fundamental role in driving physiological processes and influencing phenotypic expression. This study meticulously delineates the variations in both individual leaf traits and trait correlation networks across the heteromorphic leaves of P. euphratica, significantly deepening our understanding of plant adaptive strategies.