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Nitrogen (N) deposition is known to increase carbon (C) sequestration in N-limited boreal forests. However, the long-term effects of N deposition on ecosystem carbon fluxes have been rarely investigated in old-growth boreal forests. Here we show that decade-long experimental N additions significantly stimulated net primary production (NPP) but the effect decreased with increasing N loads. The effect on soil heterotrophic respiration (Rh) shifted from a stimulation at low-level N additions to an inhibition at higher levels of N additions. Consequently, low-level N additions resulted in a neutral effect on net ecosystem productivity (NEP), due to a comparable stimulating effect on NPP and Rh, while NEP was increased by high-level N additions. Moreover, we found nonlinear temporal responses of NPP, Rh and NEP to low-level N additions. Our findings imply that actual N deposition in boreal forests likely exerts a minor contribution to their soil C storage.

Increased nitrogen (N) inputs are widely recognised to reduce soil respiration (Rs), but how N deposition affects the temporal dynamics of Rs remains unclear. Using a decade-long fertilisation experiment in a boreal larch forest (Larix gmelini) in northeast China, we found that the effects of N additions on Rs showed a temporal shift from a positive effect in the short-term (increased by 8% on average in the first year) to a negative effect over the longer term (decreased by 21% on average in the 11th year). The rates of decrease in Rs for the higher N levels were almost twice as high as those of the low N level. Our results suggest that the reduction in Rs in response to increased N input is accelerated by high-level N additions, and experimental high N applications are likely to overestimate the contribution of N deposition to soil carbon sequestration in a boreal forest.

Sugars will eventually be exported transporters (SWEETs) are a group of recently identified sugar transporters in plants that play important roles in diverse physiological processes. However, currently, limited information about this gene family is available in pineapple (Ananas comosus). The availability of the recently released pineapple genome sequence provides the opportunity to identify SWEET genes in a Bromeliaceae family member at the genome level. In this study, 39 pineapple SWEET genes were identified in two pineapple cultivars (18 AnfSWEET and 21 AnmSWEET) and further phylogenetically classified into five clades. A phylogenetic analysis revealed distinct evolutionary paths for the SWEET genes of the two pineapple cultivars. The MD2 cultivar might have experienced a different expansion than the F153 cultivar because two additional duplications exist, which separately gave rise to clades III and IV. A gene exon/intron structure analysis showed that the pineapple SWEET genes contained highly conserved exon/intron numbers. An analysis of public RNA-seq data and expression profiling showed that SWEET genes may be involved in fruit development and ripening processes. AnmSWEET5 and AnmSWEET11 were highly expressed in the early stages of pineapple fruit development and then decreased. The study increases the understanding of the roles of SWEET genes in pineapple.

The relationship between ascomycetes and basidiomycetes, the two main phyla of non-flagellated fungi, has rarely been investigated. In this study, we performed a comparative genomics analysis of genome sequences of 55 ascomycetes and 26 basidiomycetes species and detected 81 universal markers, 875 homologous genes and a conserved contig in the glucose-regulated protein gene. In dendrograms based on simple sequence repeat markers and homologous genes, ascomycetes and basidiomycetes formed distinct clusters, with each set of taxa having a high coefficient of relatedness. Ascomycetes and basidiomycetes also constituted distinct groups in a phylogenetic tree based on a conserved contig in the glucose-regulated protein gene. These results provide evidence that basidiomycetes may be derived from ascomycetes but are definitely genetically differentiated at the genomic level. The phylogenetic relationships of ascomycetes and basidiomycetes uncovered in this study provide new insights for future research related to fungal classification and evolution.

At present, the modern manufacturing and management concepts such as digitalization, networking and intellectualization have been popularized in the industry, and the degree of industrial automation and information has been improved unprecedentedly. Industrial products are everywhere in the world. They are involved in design, manufacture, operation, maintenance and recycling. The whole life cycle involves huge amounts of data. Improving data quality is very important for data mining and data analysis. To solve the problem of data inconsistency is a very important part of improving data quality.

Increasing atmospheric nitrogen (N) deposition is an important driver of biodiversity change. By conducting an eight-year N addition experiment (0, 20, 50 and 100 kg N ha−1 yr−1), we investigated the long-term effect of simulated N deposition on understory species composition and richness in a boreal forest, northeast China. We found that moss cover decreased significantly with increasing N addition. N addition had no significant effect on vascular plants species richness but changed the plant community composition. The relative coverage of evergreen shrubs decreased, while that of graminoids increased under high-level N addition (100 kg N ha−1 yr−1). Under the high-level N treatment, Deyeuxia angustifolia cover increased significantly after 4 years, while that of Vaccinium vitis-idaea decreased significantly after 3 years and almost disappeared after 5 years. The negative effect of N addition on mosses and evergreen shrubs accumulated over time, while the positive effect on graminoids increased during the first 4 years and did not change significantly thereafter. Our results suggest that the effect of N deposition varies across functional groups and shifts over time.

As an important part of data mining, data cleaning is also facing great pressure on the cleaning of mass data.This paper firstly introduces the research status of this topic, and on the Hadoop platform and data cleaning, outlier mining algorithms were introduced, and then based on the data cleaning program typically described, by contrast, proposes a Hadoop distributed data cleaning method.Next, the inconsistency and repeatability of metadata in heterogeneous data source of digital library are analyzed, and solutions are proposed. The basic framework, process, cleaning strategy and algorithm of data cleaning in the process of periodical metadata integration are designed. Finally, the cleaning experiment is carried out to verify the feasibility and effectiveness of the cleaning strategy and algorithm.

Global nitrogen (N) deposition has been enhanced with anthropogenic N emissions, and its impacts on mosses are receiving more and more attention. This study investigates how N deposition influence the biomass and stoichiometry of moss Rhytidium rugosum, using a 3-year N enrichment experiment with 0, 2, 5 and 10 g N m−2 yr−1 in a boreal forest in Northeast China. Low N additions caused an N redundancy and moderate to high N additions resulted in a biomass loss. N additions reduced biomass ratios of green to brown tissues and increased N and phosphorus (P) contents, suggesting changes in photosynthetic capacity and litter decomposition. Biomass N pools showed a unimodal response to the N additions, and P pools decreased under moderate and high N additions. Our findings indicate significant stoichiometric and biomass changes caused by N deposition may lead to a substantial carbon and nutrient loss in boreal moss carpets.