Data from: Plant diversity accurately predicts insect diversity in two tropical landscapes

Plant 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.

植物多样性无疑决定节肢动物（arthropod）多样性，但此前仅观测到节肢动物与植物物种丰富度间存在中等程度的相关性。直至Basset等人（《科学》（Science），338卷，2012年，第1481页）首次针对热带森林开展了前所未有的全面采样，并证实植物物种丰富度确实能够精准预测节肢动物物种丰富度。
如今，我们亟需构建一套高通量流程，将该研究成果付诸实践，从而实现三大目标：（i）检验关于热带节肢动物超多样性的多种竞争性解释假说；（ii）优化全球真核生物物种多样性的估算精度；（iii）将植物与节肢动物群落互为高效替代指标，进而提升保护规划效率，并优化森林退化与恢复状况的监测效能。
为此，我们针对中国境内两处热带景观的马氏诱捕器（Malaise-trap）样本开展了元条形码（metabarcoding）分析。研究结果表明，即便在面积广阔、生境异质性强且受人为活动干扰的景观中，植物物种丰富度仍可精准预测节肢动物（以昆虫为主）的物种丰富度，且植物与昆虫群落的组成具有高度相关性。
最后，我们综述了元条形码技术如何为热带超多样性的主要竞争性解释假说提供高重复率的检验可行性。