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Plant diversity accurately predicts insect diversity in two tropical landscapes
Zhang, Kai1,2; Lin, Siliang3; Ji, Yinqiu1; Yang, Chenxue1; Wang, Xiaoyang1,2; Yang, Chunyan1; Wang, Hesheng3,4; Jiang, Haisheng; Harrison, Rhett D.5,6,8; Yu, Douglas W.1,7
2016-09-01
Source PublicationMOLECULAR ECOLOGY
Volume25Issue:17Pages:4407-4419
AbstractPlant diversity surely determines arthropod diversity, but only moderate correlations between arthropod and plant species richness had been observed until Basset et al. (Science, 338, 2012 and 1481) finally undertook an unprecedentedly comprehensive sampling of a tropical forest and demonstrated that plant species richness could indeed accurately predict arthropod species richness. We now require a high-throughput pipeline to operationalize this result so that we can (i) test competing explanations for tropical arthropod megadiversity, (ii) improve estimates of global eukaryotic species diversity, and (iii) use plant and arthropod communities as efficient proxies for each other, thus improving the efficiency of conservation planning and of detecting forest degradation and recovery. We therefore applied metabarcoding to Malaise-trap samples across two tropical landscapes in China. We demonstrate that plant species richness can accurately predict arthropod (mostly insect) species richness and that plant and insect community compositions are highly correlated, even in landscapes that are large, heterogeneous and anthropogenically modified. Finally, we review how metabarcoding makes feasible highly replicated tests of the major competing explanations for tropical megadiversity.
KeywordArthropoda Biodiversity Biomonitoring Host Specificity Insect-plant Interactions Surrogate Species
DOI10.1111/mec.13770
Indexed BySCI
Language英语
WOS Research AreaBiochemistry & Molecular Biology ; Environmental Sciences & Ecology ; Evolutionary Biology
WOS SubjectBiochemistry & Molecular Biology ; Ecology ; Evolutionary Biology
WOS IDWOS:000383343800021
Citation statistics
Cited Times:16[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.kib.ac.cn/handle/151853/33591
Collection资源植物与生物技术所级重点实验室
Affiliation1.Chinese Acad Sci, Kunming Inst Zool, State Key Lab Genet Resources & Evolut, Kunming 650223, Peoples R China
2.Univ Chinese Acad Sci, Kunming Coll Life Sci, Kunming 650204, Peoples R China
3.South China Normal Univ, Sch Life Sci, Guangzhou 510631, Guangdong, Peoples R China
4.Hainan Yinggeling Natl Nat Reserve, Baisha 572800, Peoples R China
5.East & Cent Asia Reg Off, World Agroforestry Ctr, Kunming 650201, Peoples R China
6.Chinese Acad Sci, Kunming Inst Bot, Ctr Mt Ecosyst Studies CMES, Kunming 650201, Peoples R China
7.Univ East Anglia, Sch Biol Sci, Norwich Res Pk, Norwich NR4 7TJ, Norfolk, England
8.East & Southern Africa Reg, World Agroforestry Ctr, 13 Elm Rd, Lusaka, Zambia
Recommended Citation
GB/T 7714
Zhang, Kai,Lin, Siliang,Ji, Yinqiu,et al. Plant diversity accurately predicts insect diversity in two tropical landscapes[J]. MOLECULAR ECOLOGY,2016,25(17):4407-4419.
APA Zhang, Kai.,Lin, Siliang.,Ji, Yinqiu.,Yang, Chenxue.,Wang, Xiaoyang.,...&Yu, Douglas W..(2016).Plant diversity accurately predicts insect diversity in two tropical landscapes.MOLECULAR ECOLOGY,25(17),4407-4419.
MLA Zhang, Kai,et al."Plant diversity accurately predicts insect diversity in two tropical landscapes".MOLECULAR ECOLOGY 25.17(2016):4407-4419.
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