Experimental warming reduces ecosystem resistance and resilience to severe flooding in a wetland

The cost of adaptability: resource availability constrains functional stability under pulsed disturbances

Global change exposes ecosystems to changes in the frequency, magnitude, and concomitancy of disturbances, which impact the composition and functioning of these systems. Here, we experimentally evaluate the effects of salinity disturbances and eutrophication on bacterial communities from coastal ecosystems. The functional stability of these communities is critically important for maintaining water quality, productivity, and ecosystem services, such as fishery yields. Microbial functional stability can be maintained via resistance and resilience, which are reflected in genomic traits such as genome size and codon usage bias and may be linked to metabolic costs. However, little is known about the mechanisms that select these traits under varying nutrient regimes. To study the impact of pulsed disturbances on community assembly and functioning depending on metabolic costs, we performed a 41-day pulse disturbance experiment across two levels of resource availability. Our setup triggered stochastic community re-assembly processes in all treatments. In contrast, we observed consistent and resource availability-dependent patterns of superordinate community functioning and structural patterns, such as functional resistance in response to disturbances, genomic trait distributions, and species diversity. Predicted genomic traits reflected the selection for taxa possessing resistant- and resilience-related traits, particularly under high nutrient availability. Our findings are a step toward unraveling the compositional and genomic underpinnings of functional resistance in microbial communities after exposure to consecutive pulse disturbances. Our work demonstrates how resource availability alleviates metabolic constraints on resistance and resilience, and this has important consequences for predicting water quality and ecosystem productivity of environments exposed to global change.

IMPORTANCE

Understanding the communities' responses to disturbances is a prerequisite to predicting ecosystem dynamics and, thus, highly relevant considering global change. Microbial communities play key roles in numerous ecosystem functions and services, and the large diversity, rapid growth, and phenotypic plasticity of microorganisms are thought to allow high resistance and resilience. While potential metabolic costs associated with adaptations to fluctuating environments have been debated, little evidence supports trade-offs between resource availability, resistance, and resilience. Here, we experimentally assessed the compositional and functional responses of an aquatic microbial model community to disturbances and systematically manipulated resource availability. Our results demonstrate that the capacity to tolerate environmental fluctuations is constrained by resource availability and reflected in the selection of genomic traits.

Climate warming negatively affects plant water-use efficiency in a seasonal hydroperiod wetland

Climate warming has substantial influences on plant water-use efficiency (PWUE), which is defined as the ratio of plant CO2 uptake to water loss and is central to the cycles of carbon and water in ecosystems. However, it remains uncertain how does climate warming affect PWUE in wetland ecosystems, especially those with seasonally alternating water availability during the growing season. In this study, we used a continuous 10-year (2011-2020) eddy covariance (EC) dataset from a seasonal hydroperiod wetland coupled with a 15-year (2003-2017) satellite-based dataset (called PML-V2) and an in situ warming experiment to examine the climate warming impacts on wetland PWUE. The 10-year EC observational results revealed that rising temperatures had significant negative impacts on the interannual variations in wetland PWUE, and increased transpiration (Et) rather than changes in gross primary productivity (GPP) dominated these negative impacts. Furthermore, the 15-year satellite-based evidence confirmed that, in the study region, climate warming had significant negative consequences for the interannual variations in wetland PWUE by enhancing wetland Et. Lastly, at the leaf-scale, the light response curves of leaf photosynthesis, leaf Et, and leaf-scale PWUE indicated that wetland plants need to consume more water during the photosynthesis process under warmer conditions. These findings provide a fresh perspective on how climate warming influences carbon and water cycles in wetland ecosystems.

Ambient precipitation determines the sensitivity of soil respiration to precipitation treatments in a marsh

The effects in field manipulation experiments are strongly influenced by amplified interannual variation in ambient climate as the experimental duration increases. Soil respiration (SR), as an important part of the carbon cycle in terrestrial ecosystems, is sensitive to climate changes such as temperature and precipitation changes. A growing body of evidence has indicated that ambient climate affects the temperature sensitivity of SR, which benchmarks the strength of terrestrial soil carbon-climate feedbacks. However, whether SR sensitivity to precipitation changes is influenced by ambient climate is still not clear. In addition, the mechanism driving the above phenomenon is still poorly understood. Here, a long-term field manipulation experiment with five precipitation treatments (-60%, -40%, +0%, +40%, and +60% of annual precipitation) was conducted in a marsh in the Yellow River Delta, China, which is sensitive to soil drying-wetting cycle caused by precipitation changes. Results showed that SR increased exponentially along the experimental precipitation gradient each year and the sensitivity of SR (standardized by per 100 mm change in precipitation under precipitation treatments) exhibited significant interannual variation from 2016 to 2021. In addition, temperature, net radiation, and ambient precipitation all exhibited dramatic interannual variability; however, only ambient precipitation had a significant negative correlation with SR sensitivity. Moreover, the sensitivity of SR was significantly positively related to the sensitivity of belowground biomass (BGB) across 6 years. Structural equation modeling and regression analysis also showed that precipitation treatments significantly affected SR and its autotrophic and heterotrophic components by altering BGB. Our study demonstrated that ambient precipitation determines the sensitivity of SR to precipitation treatments in marshes. The findings underscore the importance of ambient climate in regulating ecosystem responses in long-term field manipulation experiments.

Spatial and Temporal Distribution and the Driving Factors of Carbon Emissions from Urban Production Energy Consumption

Urban production energy consumption produces a large amount of carbon emissions, which is an important source of global warming. This study measures the quantity and intensity of carbon emissions in 30 provinces of China based on urban production energy consumption from 2005-2019, and uses the Dagum Gini coefficient, kernel density estimation, carbon emission classification and spatial econometric model to analyze the spatial and temporal distribution and driving factors of quantity and intensity of carbon emissions from China and regional production energy consumption. It was found that the growth rate of carbon emission quantity and carbon emission intensity of production energy consumption decreased year by year in each province during the study period. The imbalance of carbon emission was strong, with different degrees of increase and decrease, and there were big differences between eastern and western regions. The classification of carbon emissions differed among provinces and there was heterogeneity among regions. The quantity and intensity of carbon emissions of production energy consumption qwre affected by multiple factors, such as industrial structure. This study provides an in-depth comparison of the spatial and temporal distribution and driving factors of quantity and intensity of carbon emissions of production energy consumption across the country and regions, and provides targeted policies for carbon emission reduction across the country and regions, so as to help achieve China's "double carbon" target quickly and effectively.