The bacteria in the water column and surface sediments are inherently intertwined and inseparable in aquatic ecosystems, yet little is known about the integrated spatiotemporal dynamics and driving mechanisms of both planktonic and sedimentary bacterial communities in reservoirs. By investigating the planktonic and sedimentary bacteria during four seasons from 88 samples of 11 representative sites across the Danjiangkou reservoir, we depicted an integrated biogeographic pattern of bacterial communities in the water source of the world's largest water diversion project. Our study revealed both planktonic (mantel r = 0.502, P = 0.001) and sedimentary (mantel r = 0.131, P = 0.009) bacterial communities were significantly correlated with environmental heterogeneity, but a weak disparity along spatial heterogeneity, and the significant seasonal dynamics of planktonic (mantel r = 0.499, P = 0.001) rather than sedimentary bacteria. Particularly, rare biosphere played a main role in determining the community succession in the reservoir. It not only exhibited a more striking environmental separation than abundant taxa but also was an essential part in mediating spatiotemporal shifts of planktonic bacteria and maintaining the stability of bacterial community. These rare bacteria were respectively mediated by stochastic (62.68%) and selective (79.60%) processes in water and sediments despite abundant taxa being largely determined by stochastic processes (86.88-93.96%). Overall, our study not only fills a gap in understanding the bacterial community dynamics and underlying drivers in source water reservoirs, but also highlights the particular importance of rare bacteria in mediating biogeochemical cycles in world's large reservoir ecosystems.
Dissolved Rare Earth Elements (REE) and radiogenic neodymium (Nd) isotope composition (εNd) of seawater are widely used geochemical tools in studying marine processes, but their modern ocean budgets are poorly understood. Recent discoveries of large benthic fluxes of REE with unique εNd signatures from marine sediments, particularly in the deep-sea, have led to a “bottom-up” hypothesis, which suggests that early diagenesis below the sediment-water interface (SWI) controls the ocean's REE and εNd budgets. To investigate such sedimentary processes, we created a reactive-transport model for the biogeochemical cycling of Nd and εNd in marine sediments. Here, we attempt to quantify the roles of authigenesis, marine silicate weathering and reverse weathering in the diagenetic cycling of Nd and εNd at a deep-sea (3000 m) site on the Oregon margin. Our model predicts that, at this site, Nd carried by Fe/Mn oxides into sediments eventually transforms to authigenic Nd-phosphate, during which ∼9% of the incoming solid Nd flux is released as a dissolved benthic flux back to the overlying bottom water. We also find that the classic reversible scavenging formulation applied to Nd co-cycling with Fe/Mn oxides is inconsistent with the data. Rather, a co-precipitation formulation, assuming Nd is structurally incorporated into Fe/Mn oxides, successfully simulates the data. The model also shows that authigenesis alone cannot explain the pore water and authigenic εNd, which are both more radiogenic than bottom water at this site. However, the weathering of volcanic silicates sourced from the local subduction zone can successfully explain εNd. We suggest that, because reverse weathering by authigenic clay formation maintains the under-saturation of primary silicates in pore water, marine silicate weathering can proceed. The processes we model likely affect the sedimentary cycling of many other trace elements and isotopes, with much broader implications for the understanding of ocean biogeochemistry.
Summary A growing number of governments are pledging to achieve net-zero greenhouse gas emissions by mid-century. Despite such ambitions, realized emissions reductions continue to fall alarmingly short of modeled energy transition pathways for achieving net-zero. This gap is largely a result of the difficulty of realistically modeling all the techno-economic and sociopolitical capabilities that are required to deliver actual emissions reductions. This limitation of models suggests the need for an energy-systems analytical framework that goes well beyond energy-system modeling in order to close the gap between ambition and reality. Toward that end, we propose the Emissions-Sustainability-Governance-Operation (ESGO) framework for structured assessment and transparent communication of national capabilities and realization. We illustrate the critical role of energy modeling in ESGO using recent net-zero modeling studies for the world's two largest emitters, China and the United States. This illustration leads to recommendations for improvements to energy-system modeling to enable more productive ESGO implementation.
Abstract We present OH observations made in Amazonas, Brazil during the Green Ocean Amazon campaign (GoAmazon2014/5) from February to March of 2014. The average diurnal variation of OH peaked with a midday (10:00?15:00) average of 1.0 ? 106 (±0.6 ? 106) molecules cm?3. This was substantially lower than previously reported in other tropical forest photochemical environments (2?5 ? 106 molecules cm?3) while the simulated OH reactivity was lower. The observational data set was used to constrain a box model to examine how well current photochemical reaction mechanisms can simulate observed OH. We used one near-explicit mechanism (MCM v3.3.1) and four condensed mechanisms (i.e., RACM2, MOZART-T1, CB05, CB6r2) to simulate OH. A total of 14 days of analysis shows that all five chemical mechanisms were able to explain the measured OH within instrumental uncertainty of 40% during the campaign in the Amazonian rainforest environment. Future studies are required using more reliable NOx and VOC measurements to further investigate discrepancies in our understanding of the radical chemistry in the tropical rainforest.
Conventional digital cameras typically accumulate all the photons within an exposure period to form a snapshot image. It requires the scene to be quite still during the imaging time, otherwise it would result in blurry image for the moving objects. Recently, a retina-inspired spike camera has been proposed and shown great potential for recording high-speed motion scenes. Instead of capturing the visual scene by a single snapshot, the spike camera records the dynamic light intensity variation continuously. Each pixel on spike camera sensor accumulates the incoming photons independently and persistently, which fires a spike and restarts the photon accumulation immediately once the dispatch threshold is reached, producing a continuous stream of spikes recorded at very high temporal resolution. To recover the dynamic scene from captured spike stream, this paper presents an image reconstruction approach for spike camera. In order to generate high-quality reconstruction, we investigate the temporal correlation along motion trajectories and exploit it via adaptive temporal filtering. In particular, we present a hierarchical motion-aligned temporal filtering scheme, combining short-term filtering with long-term filtering to take advantage of long-term temporal correlation with low model complexity. Experimental results demonstrate that the proposed scheme outperforms the existing schemes significantly, producing much better objective and subjective qualities for spike camera image reconstruction.
Soil microbes assemble in highly complex and diverse microbial communities, and microbial diversity patterns and their drivers have been studied extensively. However, diversity correlations and co-occurrence patterns between bacterial, fungal, and archaeal domains and between microbial functional groups in arid regions remain poorly understood. Here we assessed the relationships between the diversity and abundance of bacteria, fungi, and archaea and explored how environmental factors influence these relationships. We sampled soil along a 1500-km-long aridity gradient in temperate grasslands of Inner Mongolia (China) and sequenced the 16S rRNA gene of bacteria and archaea and the ITS2 gene of fungi. The diversity correlations and co-occurrence patterns between bacterial, fungal, and archaeal domains and between different microbial functional groups were evaluated using α-diversity and co-occurrence networks based on microbial abundance. Our results indicate insignificant correlations among the diversity patterns of bacterial, fungal, and archaeal domains using α-diversity but mostly positive correlations among diversity patterns of microbial functional groups based on α-diversity and co-occurrence networks along the aridity gradient. These results suggest that studying microbial diversity patterns from the perspective of functional groups and co-occurrence networks can provide additional insights on patterns that cannot be accessed using only overall microbial α-diversity. Increase in aridity weakens the diversity correlations between bacteria and fungi and between bacterial and archaeal functional groups, but strengthens the positive diversity correlations between bacterial functional groups and between fungal functional groups and the negative diversity correlations between bacterial and fungal functional groups. These variations of the diversity correlations are associated with the different responses of microbes to environmental factors, especially aridity. Our findings demonstrate the complex responses of microbial community structure to environmental conditions (especially aridity) and suggest that understanding diversity correlations and co-occurrence patterns between soil microbial groups is essential for predicting changes in microbial communities under future climate change in arid regions.