Thüs Holger, Wolseley Pat, Carpenter Dan, Eggleton Paul, Reynolds Glen, Vairappan Charles S, Weerakoon Gothamie, Mrowicki Robert J
Botany Department, State Museum of Natural History Stuttgart, 70191 Stuttgart, Germany.
Life Sciences Department, The Natural History Museum London, London SW7 5BD, UK.
Microorganisms. 2021 Mar 5;9(3):541. doi: 10.3390/microorganisms9030541.
Many lowland rainforests in Southeast Asia are severely altered by selective logging and there is a need for rapid assessment methods to identify characteristic communities of old growth forests and to monitor restoration success in regenerating forests. We have studied the effect of logging on the diversity and composition of lichen communities on trunks of trees in lowland rainforests of northeast Borneo dominated by Dipterocarpaceae. Using data from field observations and vouchers collected from plots in disturbed and undisturbed forests, we compared a taxonomy-based and a taxon-free method. Vouchers were identified to genus or genus group and assigned to functional groups based on sets of functional traits. Both datasets allowed the detection of significant differences in lichen communities between disturbed and undisturbed forest plots. Bark type diversity and the proportion of large trees, particularly those belonging to the family Dipterocarpaceae, were the main drivers of lichen community structure. Our results confirm the usefulness of a functional groups approach for the rapid assessment of tropical lowland rainforests in Southeast Asia. A high proportion of Dipterocarpaceae trees is revealed as an essential element for the restoration of near natural lichen communities in lowland rainforests of Southeast Asia.
东南亚的许多低地雨林因选择性采伐而遭到严重破坏,因此需要快速评估方法来识别原始森林的特征群落,并监测再生森林的恢复成效。我们研究了采伐对婆罗洲东北部以龙脑香科为主的低地雨林树木树干上地衣群落多样性和组成的影响。利用来自实地观察的数据以及从受干扰和未受干扰森林的样地收集的标本,我们比较了基于分类学的方法和无分类单元的方法。标本被鉴定到属或属组,并根据一系列功能性状分配到功能组。两个数据集都能检测出受干扰和未受干扰森林样地之间地衣群落的显著差异。树皮类型多样性和大树的比例,特别是属于龙脑香科的大树,是地衣群落结构的主要驱动因素。我们的结果证实了功能组方法在快速评估东南亚热带低地雨林方面的有用性。结果表明,高比例的龙脑香科树木是东南亚低地雨林恢复近自然地衣群落的关键要素。