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Plants have evolved complex mechanisms to reprogram growth in response to drought stress. In herbaceous perennial plant species, the rhizome, which is normally an organ for propagation and food storage, can also support plant growth in stressful environments, and allows the plant to perennate and survive stress damage. However, the mechanisms that regulate rhizome growth in perennial herbs during abiotic stresses are unknown. Here, we identified a chrysanthemum (Chrysanthemum morifolium) DEAD-box RNA helicase gene, CmRH56, that is specifically expressed in the rhizome shoot apex. Knock down of CmRH56 transcript levels decreased the number of rhizomes and enhanced drought stress tolerance. We determined that CmRH56 represses the expression of a putative gibberellin (GA) catabolic gene, GA2 oxidase6 (CmGA2ox6). Exogenous GA treatment and silencing of CmGA2ox6 resulted in more rhizomes. These results demonstrate that CmRH56 suppresses rhizome outgrowth under drought stress conditions by blocking GA biosynthesis.

Fragile wetland habitats are susceptible to multiple threats from anthropogenic activities. Direct waste deposition, habitat modification and overexploitation of fish have caused alternations in food webs in wetlands. Kingfishers are ecological indicators with the potential ability to respond to the minute changes in their microenvironment. Their abundance and distribution at wetland habitats are affected by multiple environmental factors. We studied the kingfisher assemblages in India to determine proximate and ultimate causes of their decline. We recorded the abundance of five species of kingfishers across five wetland habitats from 2011 to 2020 in Kerala, southwest coast of India. Kingfishers were counted twice in a month between 6.00 and 12.00 hrs. Air temperature, water temperature, humidity and turbidity were recorded. We measured fish diversity and abundance and organic waste as an additional explanatory variable. One-way ANOVA, Autoregressive Integrated Moving Average model and structural equation modelling were used to determine which explanatory variables affected kingfisher populations. Air temperature, water temperature and turbidity increased significantly during the study and had negative effects on the abundance of kingfishers. Humidity decreased significantly but had no effect on the kingfisher abundance. Fish abundance declined and had a strong positive effect on the abundance of kingfishers. The analysis of incidence of wastes across the study areas revealed that, all the sites were severely polluted. We also observed drastic decline in the abundance of all the species of kingfishers studied across the sites with a rapid decline in Pied Kingfisher and slower decline in White-throated Kingfisher. Black-capped Kingfisher is a local migrant to the study areas and is already red listed and categorized as Vulnerable (VU). This study suggests that kingfisher assemblages are declining along with the health status of the habitat. Urgent action is needed to help in designing and implementing effective management strategies for the sustainability of wetlands in the region.

Identifying influential spreaders is a crucial aspect of network science with various applications, including rumor control, viral marketing and epidemic spread limitation. Despite the availability of various methods for identifying these spreaders in complex networks, there remains a fundamental question regarding their accurate and discriminative identification. To address the issues and account for each node's propagation ability, we propose an algorithm to identify influential spreaders based on the node's weight and spreading probability (NWSP) for identifying influential spreaders. The effectiveness of the proposed method is evaluated using the Susceptible–Infected–Recovered (SIR) model, Kendall's Tau (τ) and monotonicity. The proposed method is compared with several well-known metrics, including degree centrality, K-shell decomposition, betweenness centrality, closeness centrality, eigenvector centrality and the centrality method based on node spreading probability (SPC), in ten real networks. Experimental results demonstrate the superiority ability of the proposed algorithm to accurately and discriminatively identify influential spreaders. [ABSTRACT FROM AUTHOR]

Age, as a threshold of floral competence acquisition, prevents precocious flowering when there is insufficient biomass, and ensures flowering independent of environmental conditions; however, the underlying regulatory mechanisms are largely unknown. In this study, silencing the expression of a nuclear factor gene, CmNF-YB8, from the short day plant chrysanthemum (Chrysanthemum morifolium), results in precocious transition from juvenile to adult, as well as early flowering, regardless of day length conditions. The expression of SQUAMOSA PROMOTER BINDING-LIKE (SPL) family members, SPL3, SPL5, and SPL9, is upregulated in CmNF-YB8-RNAi plants, while expression of the microRNA, cmo-MIR156, is downregulated. In addition, CmNF-YB8 is shown to bind to the promoter of the cmo-MIR156 gene. Ectopic expression of cmo-miR156, using a virus-based microRNA expression system, restores the early flowering phenotype caused by CmNF-YB8 silencing. These results show that CmNF-YB8 influences flowering time through directly regulating the expression of cmo-MIR156 in the aging pathway.The mechanisms by which plant age regulates flowering remain incompletely understood. Here the authors show that age dependent regulation of SPL transcription factors by miR156 influence flowering via control of NF-YB8 expression in Chrysanthemum.