Abstract A key challenge in ecology is to understand the relationships between organismal traits and ecosystem processes. Here, with a novel dataset of leaf length and width for 10 480 woody dicots in China and 2374 in North America, we show that the variation in community mean leaf size is highly correlated with the variation in climate and ecosystem primary productivity, independent of plant life form. These relationships likely reflect how natural selection modifies leaf size across varying climates in conjunction with how climate influences canopy total leaf area. We find that the leaf size‒primary productivity functions based on the Chinese dataset can predict productivity in North America and vice-versa. In addition to advancing understanding of the relationship between a climate-driven trait and ecosystem functioning, our findings suggest that leaf size can also be a promising tool in palaeoecology for scaling from fossil leaves to palaeo-primary productivity of woody ecosystems.
Microbial carbon has recently been highlighted to play a key role in the formation and persistence of soil organic carbon, bearing significant implications for regulating ecosystem carbon stocks under global changes. However, microbial carbon distribution and the link between biomass and necromass components are poorly understood in natural soils, especially at depth. Here, we employ various microbial biomarkers, including phospholipid fatty acids (PLFAs), amino sugars and glycerol dialkyl glycerol tetraethers (GDGTs), to investigate the spatial distribution patterns of microbial biomass and necromass components in the top- (0–10 cm) versus subsoils (30–50 cm) across Chinese temperate grasslands along an aridity gradient. We find that bacterial necromass components are better preserved relative to bacterial biomass in the sub- than topsoil, possibly due to a stronger association of microbial necromass with calcium and/or lower nitrogen competition between plants and microbes at depth in these neutral-to-alkaline soils. As a result, there is a stronger link between bacterial necromass components (especially for core lipid branched GDGTs and muramic acid) and their producers (reflected by intact polar lipid-derived branched GDGTs) in the sub- than topsoil, while such a trend is not observed for fungi- or archaea-derived components. Furthermore, using linear mixed effect model analyses, we find that aridity index best explains the concentration variance of most microbial biomarkers in the topsoil, whereas edaphic properties (i.e., pH and macronutrients) also contribute significantly to their variance in the subsoil. These findings highlight different links between microbial necromass and biomass components and distinct preservation mechanisms for microbial carbon at different soil depths, which is crucial for improved understanding of microbial carbon sequestration potentials at different depths in a changing environment.
Modeling and optimization of a large-scale urban energy-water nexus system with sufficient spatial resolutions is a complex challenge. By proper clustering technique, a large-scale problem could possibly be divided into small ones with high spatial resolution and accuracy. Existing literature tends to lower the complexity of large-scale urban energy system problem by accumulating demand profiles on the spatial dimension. This study proposes a flexible clustering approach based on density clustering method with combined index assessment process. The flexible approach considers not only the spatial dimensions but also the complementarity effect of different demand profile and control the computational time of system design and optimization. The approach can increase the clustering flexibility by providing more clustering options than conventional method, take advantages of complementarity effect to further improve the system economic performance and control the solving time in an acceptable range. The proposed approach is evaluated by a case study of a new business district in Shanghai, China with a proposed future energy-water nexus system. After three combined index assessment, 45 new clustering maps are generated by the flexible clustering approach and the final optimal solution obtained by the proposed approach can further obtain 6.74% cost savings compared with conventional clustering approach.
Fenton reaction can disinfect bacteria and degrade organic pollutants via the generation of OH through the reaction of Fe(II) and H2O2. However, its high efficiency only at very acidic conditions and the formation of Fe(III) sludge limit its practical application. Herein, magnetic Fe3O4-deposited flower-like MoS2 (MF) composites were fabricated to disinfect Escherichia coli and degrade diclofenac (DCF) with addition of small amount of H2O2 at a wide pH range (from 3.5 to 9.5). MF can efficiently inactivate bacteria and remove DCF at broad pH from 3.5 to 9.5. For example, 1.2 × 106 CFU mL-1 cells are completely disinfected by MF in 30 min at pH 6 with 5 mM H2O2, while 10 mg L-1 DCF is fully degraded in 7 min at pH 6 with 1 mM H2O2. MoS2 facilitates the conversion cycle of Fe(III)/Fe(II) and improves the generation of OH. MF can be easily collected by magnet after use. Confocal image, SEM images, the leakage of K+ and DNA were employed to determine the damage of cell membrane. Meanwhile, the theoretical density functional theory and the degradation intermediates determination were employed to provide the degradation pathway of DCF. MF exhibit excellent reusability and good catalytic performance towards sanitary sewage.