Plants changed the response of bacterial community to the nitrogen and phosphorus addition ratio

IntroductionHuman activities have increased the nitrogen (N) and phosphorus (P) supply ratio of the natural ecosystem, which affects the growth of plants and the circulation of soil nutrients. However, the effect of the N and P supply ratio and the effect of plant on the soil microbial community are still unclear.MethodsIn this study, 16s rRNA sequencing was used to characterize the response of bacterial communities in Phragmites communis (P.communis) rhizosphere and non-rhizosphere soil to N and P addition ratio.ResultsThe results showed that the a-diversity of the P.communis rhizosphere soil bacterial community increased with increasing N and P addition ratio, which was caused by the increased salt and microbially available C content by the N and P ratio. N and P addition ratio decreased the pH of non-rhizosphere soil, which consequently decreased the a-diversity of the bacterial community. With increasing N and P addition ratio, the relative abundance of Proteobacteria and Bacteroidetes increased, while that of Actinobacteria and Acidobacteria decreased, which reflected the trophic strategy of the bacterial community. The bacterial community composition of the non-rhizosphere soil was significantly affected by salt, pH and total carbon (TC) content. Salt limited the relative abundance of Actinobacteria, and increased the relative abundance of Bacteroidetes. The symbiotic network of the rhizosphere soil bacterial community had lower robustness. This is attributed to the greater selective effect of plants on the bacterial community influenced by nutrient addition.DiscussionPlants played a regulatory role in the process of N and P addition affecting the bacterial community, and nutrient uptake by the root system reduced the negative impact of N and P addition on the bacterial community. The variations in the rhizosphere soil bacterial community were mainly caused by the response of the plant to the N and P addition ratio

Robustness of Cyber-Physical Systems against Simultaneous, Sequential and Composite Attack

In this paper, a failure model of Cyber-Physical systems and an attack model are proposed. We divide the attacks into three kinds: simultaneous attack, sequential attack and composite attack. Through numerical simulations, we find that: (1) the sequential attack may bring more damage in single physical systems; (2) the coupling process of cyber system and physical systems makes it possible that sequential attack causes more damage than simultaneous attacks when the attackers only attack the cyber system; (3) with some target sets, composite attack leads to more failures than both simultaneous attack and sequential attack. The above results suggest that defenders should take all the three kinds of attacks into account when they select the critical nodes

Rank correlation between centrality metrics in complex networks: an empirical study

Centrality is widely used to measure which nodes are important in a network. In recent decades, numerous metrics have been proposed with varying computation complexity. To test the idea that approximating a high-complexity metric by a low-complexity metric, researchers have studied the correlation between them. However, these works are based on Pearson correlation which is sensitive to the data distribution. Intuitively, a centrality metric is a ranking of nodes (or edges). It would be more reasonable to use rank correlation to do the measurement. In this paper, we use degree, a low-complexity metric, as the base to approximate three other metrics: closeness, betweenness, and eigenvector. We first demonstrate that rank correlation performs better than the Pearson one in scale-free networks. Then we study the correlation between centrality metrics in real networks, and find that the betweenness occupies the highest coefficient, closeness is at the middle level, and eigenvector fluctuates dramatically. At last, we evaluate the performance of using top degree nodes to approximate three other metrics in the real networks. We find that the intersection ratio of betweenness is the highest, and closeness and eigenvector follows; most often, the largest degree nodes could approximate largest betweenness and closeness nodes, but not the largest eigenvector nodes

Warming-driven migration of core microbiota indicates soil property changes at continental scale

Terrestrial species are predicted to migrate northward under global warming conditions, yet little is known about the direction and magnitude of change in microbial distribution patterns. In this continental-scale study with more than 1600 forest soil samples, we verify the existence of core microbiota and lump them into a manageable number of eco-clusters based on microbial habitat preferences. By projecting the abundance differences of eco-clusters between future and current climatic conditions, we observed the potential warming-driven migration of the core microbiota under warming, partially verified by a field warming experiment at Southwest China. Specifically, the species that favor low pH are potentially expanding and moving northward to medium-latitudes (25 degrees-45 degrees N), potentially implying that warm temperate forest would be under threat of soil acidification with warming. The eco-cluster of high-pH with high-annual mean temperature (AMT) experienced significant abundance increases at middle- (35 degrees-45 degrees N) to high-latitudes (> 45 degrees N), especially under Representative Concentration Pathway (RCP) 8.5, likely resulting in northward expansion. Furthermore, the eco-cluster that favors low-soil organic carbon (SOC) was projected to increase under warming scenarios at low-latitudes ( 45 degrees N) the changes in relative abundance of this eco-cluster is inversely related with the temperature variation trends, suggesting microbes-mediated soil organic carbon changes are more responsive to temperature variation in colder areas. These results have vital implications for the migration direction of microbial communities and its potential ecological consequences in future warming scenarios. (C) 2021 Science China Press. Published by Elsevier B.V. and Science China Press. All rights reserved

A meta-analysis of 1,119 manipulative experiments on terrestrial carbon-cycling responses to global change

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