TY - JOUR T1 - Plant diversity accurately predicts insect diversity in two tropical landscapes JF - bioRxiv DO - 10.1101/040105 SP - 040105 AU - Kai Zhang AU - Siliang Lin AU - Yinqiu Ji AU - Chenxue Yang AU - Xiaoyang Wang AU - Chunyan Yang AU - Hesheng Wang AU - Haisheng Jiang AU - Rhett D. Harrison AU - Douglas W. Yu Y1 - 2016/01/01 UR - http://biorxiv.org/content/early/2016/07/29/040105.abstract N2 - Plant diversity surely determines arthropod diversity, but only moderate correlations between arthropod and plant species richness had been observed until Basset et al. (2012, Science 338: 1481-1484) 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 (1) test competing explanations for tropical arthropod megadiversity, (2) improve estimates of global eukaryotic species diversity, and (3) 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. ER -