RT Journal Article
SR Electronic
T1 Plant diversity accurately predicts insect diversity in two tropical landscapes
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 040105
DO 10.1101/040105
A1 Kai Zhang
A1 Siliang Lin
A1 Yinqiu Ji
A1 Chenxue Yang
A1 Xiaoyang Wang
A1 Chunyan Yang
A1 Hesheng Wang
A1 Haisheng Jiang
A1 Rhett D. Harrison
A1 Douglas W. Yu
YR 2016
UL http://biorxiv.org/content/early/2016/07/29/040105.abstract
AB 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.