For Publishers
DiscoveryMetadataPeer reviewHostingPublishing
For Researchers
JoinPublishReviewCollect
Register
Blog
About
Search
Advanced search
My ScienceOpen
Search
For Publishers
For Researchers
Blog
About
3
views
55
references
 Top references
cited by
1
    
0 reviews
 Review
0
comments
 Comment
0
recommends
+1 Recommend
0 collections
    0
    shares
      111
      similar
       All similar
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Field investigation‐ and dietary metabarcoding‐based screening of arthropods that prey on primary tea pests

      research-article

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Predatory natural enemies play key functional roles in biological control. Abundant predatory arthropod species have been recorded in tea plantation ecosystems. However, few studies have comprehensively evaluated the control effect of predatory arthropods on tea pests in the field. We performed a 1‐year field investigation and collected predatory arthropods and pests in the tea canopy. A total of 7931 predatory arthropod individuals were collected, and Coleosoma blandum (Araneae, Theridiidae) was the most abundant species in the studied tea plantation. The population dynamics between C. blandum and four main tea pest species ( Aleurocanthus spiniferus, Empoasca onukii, Ectropis grisescens, and Scopula subpunctaria) were established using the individual number of predators and pests in each month. The results showed that C. blandum appeared to co‐occur in the tea canopy with A. spiniferus, Em. onukii, and Ec. grisescens in a longer period. The prey spectrum of C. blandum was further analyzed using DNA metabarcoding. Among prey species, A. spiniferus, Em. onukii, and Ec. grisescens were included, and the relative abundance and positive rates of target DNA fragments of A. spiniferus were greater than that of other two pests. Combined with the high dominance index of C. blandum, co‐occurrence between C. blandum and A. spiniferus in time and space and high positive rate and relative abundance of target DNA fragments of A. spiniferus, C. blandum was identified to prey on A. spiniferus, and C. blandum may be an important predator of A. spiniferus. Thus, C. blandum has potential as a biological control agent of A. spiniferus in an integrated pest management strategy.

          Abstract

          (1) Coleosoma blandum (Araneae, Theridiidae) was the most abundant species in the studied tea plantation and accounted for 34.80% of the total individual number of predatory arthropods; (2) C. blandum appeared to co‐occur in the tea canopy with three main tea pest species ( A. spiniferus, Em. onukii and Ec. grisescens) in a longer period; (3) A. spiniferus, Em. onukii and Ec. grisescens were included in the prey spectrum of C. blandum, and the relative abundance and positive rates of target DNA fragments of A. spiniferus were greater than that of other two pests

          Related collections

          Most cited references55

          • Record: found
          • Abstract: not found
          • Article: not found

          Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2

          Evan Bolyen, Jai Rideout, Matthew Dillon … (2019)
          Article 0 comments Cited 5539 times – based on 0 reviews     Review now
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Search and clustering orders of magnitude faster than BLAST.

            Robert Edgar (2010)
            Biological sequence data is accumulating rapidly, motivating the development of improved high-throughput methods for sequence classification. UBLAST and USEARCH are new algorithms enabling sensitive local and global search of large sequence databases at exceptionally high speeds. They are often orders of magnitude faster than BLAST in practical applications, though sensitivity to distant protein relationships is lower. UCLUST is a new clustering method that exploits USEARCH to assign sequences to clusters. UCLUST offers several advantages over the widely used program CD-HIT, including higher speed, lower memory use, improved sensitivity, clustering at lower identities and classification of much larger datasets. Binaries are available at no charge for non-commercial use at http://www.drive5.com/usearch.
            Article 0 comments Cited 3463 times – based on 0 reviews     Review now
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              VSEARCH: a versatile open source tool for metagenomics

              Torbjørn Rognes, Tomáš Flouri, Ben Nichols … (2016)
              Background VSEARCH is an open source and free of charge multithreaded 64-bit tool for processing and preparing metagenomics, genomics and population genomics nucleotide sequence data. It is designed as an alternative to the widely used USEARCH tool (Edgar, 2010) for which the source code is not publicly available, algorithm details are only rudimentarily described, and only a memory-confined 32-bit version is freely available for academic use. Methods When searching nucleotide sequences, VSEARCH uses a fast heuristic based on words shared by the query and target sequences in order to quickly identify similar sequences, a similar strategy is probably used in USEARCH. VSEARCH then performs optimal global sequence alignment of the query against potential target sequences, using full dynamic programming instead of the seed-and-extend heuristic used by USEARCH. Pairwise alignments are computed in parallel using vectorisation and multiple threads. Results VSEARCH includes most commands for analysing nucleotide sequences available in USEARCH version 7 and several of those available in USEARCH version 8, including searching (exact or based on global alignment), clustering by similarity (using length pre-sorting, abundance pre-sorting or a user-defined order), chimera detection (reference-based or de novo), dereplication (full length or prefix), pairwise alignment, reverse complementation, sorting, and subsampling. VSEARCH also includes commands for FASTQ file processing, i.e., format detection, filtering, read quality statistics, and merging of paired reads. Furthermore, VSEARCH extends functionality with several new commands and improvements, including shuffling, rereplication, masking of low-complexity sequences with the well-known DUST algorithm, a choice among different similarity definitions, and FASTQ file format conversion. VSEARCH is here shown to be more accurate than USEARCH when performing searching, clustering, chimera detection and subsampling, while on a par with USEARCH for paired-ends read merging. VSEARCH is slower than USEARCH when performing clustering and chimera detection, but significantly faster when performing paired-end reads merging and dereplication. VSEARCH is available at https://github.com/torognes/vsearch under either the BSD 2-clause license or the GNU General Public License version 3.0. Discussion VSEARCH has been shown to be a fast, accurate and full-fledged alternative to USEARCH. A free and open-source versatile tool for sequence analysis is now available to the metagenomics community.
              Article 0 comments Cited 2439 times – based on 0 reviews     Review now
                Bookmark
                All references

                Author and article information

                Contributors
                Tingbang Yang:
                ORCID: https://orcid.org/0000-0002-6685-1209
                tingbang_yang@aliyun.com
                Journal
                Journal ID (nlm-ta): Ecol Evol
                Journal ID (iso-abbrev): Ecol Evol
                Journal ID (doi): 10.1002/(ISSN)2045-7758
                Journal ID (publisher-id): ECE3
                Title: Ecology and Evolution
                Publisher: John Wiley and Sons Inc. (Hoboken )
                ISSN (Electronic): 2045-7758
                Publication date (Electronic): 04 July 2022
                Publication date Collection: July 2022
                Volume: 12
                Issue: 7 ( doiID: 10.1002/ece3.v12.7 )
                Electronic Location Identifier: e9060
                Affiliations
                [ 1 ] Key Laboratory of Southwest China Wildlife Resources Conservation (Ministry of Education) China West Normal University Nanchong China
                [ 2 ] Institute of Ecology China West Normal University Nanchong China
                [ 3 ] School of Nuclear Technology and Chemistry & Biology Hubei University of Science and Technology Xianning China
                [ 4 ] Hubei Engineering Research Center for Fragrant Plants Hubei University of Science and Technology Xianning China
                Author notes
                [*] [* ] Correspondence

                Tingbang Yang, Key Laboratory of Southwest China Wildlife Resources Conservation (Ministry of Education), China West Normal University, Nanchong 637009, Sichuan, China.

                Email: tingbang_yang@ 123456aliyun.com

                Author information
                https://orcid.org/0000-0002-6685-1209
                https://orcid.org/0000-0002-8246-6677
                Article
                Publisher ID: ECE39060 Other ID: ECE-2022-03-00441.R2
                DOI: 10.1002/ece3.9060
                PMC ID: 9251880
                PubMed ID: 35813924
                SO-VID: 1316c435-ef6f-4da2-bbc3-a846262635f2
                Copyright © © 2022 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.
                License:

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                Date revision received : 30 May 2022
                Date received : 23 March 2022
                Date accepted : 10 June 2022
                Page count
                Figures: 6, Tables: 2, Pages: 11, Words: 8057
                Funding
                Funded by: Doctoral Scientific Research Funds of China West Normal University
                Award ID: 18Q050
                Funded by: Fundamental Research Funds of China West Normal University , doi 10.13039/501100012478;
                Award ID: 20A017
                Funded by: National Natural Science Foundation of China , doi 10.13039/501100001809;
                Award ID: 32101265
                Categories
                Subject: Agroecology
                Subject: Ecosystem Ecology
                Subject: Entomology
                Subject: Population Ecology
                Subject: Trophic Interactions
                Subject: Research Article
                Subject: Research Articles
                Custom metadata
                source-schema-version-number 2.0
                cover-date July 2022
                details-of-publishers-convertor Converter:WILEY_ML3GV2_TO_JATSPMC version:6.1.7 mode:remove_FC converted:04.07.2022

                ScienceOpen disciplines: Evolutionary Biology
                Keywords: biological control,diet analysis,dna metabarcoding,predatory arthropods,spiders,tea pests
                Data availability:
                ScienceOpen disciplines: Evolutionary Biology
                Keywords: biological control, diet analysis, dna metabarcoding, predatory arthropods, spiders, tea pests

                Comments

                Comment on this article

                scite_

                Similar content111

                See all similar

                Cited by1

                See all cited by

                Most referenced authors1,124

                See all reference authors