Peck Mika Robert, Maddock Simon T, Morales Jorge Noe, Oñate Hugolino, Mafla-Endara Paola, Peñafiel Vanessa Aguirre, Torres-Carvajal Omar, Pozo-Rivera Wilmer E, Cueva-Arroyo Xavier A, Tolhurst Bryony A
School of Life Sciences, JMS Building, University of Sussex, Falmer, Brighton, BN1 9QJ, United Kingdom.
Conserv Biol. 2014 Oct;28(5):1331-41. doi: 10.1111/cobi.12373. Epub 2014 Aug 13.
In species-rich tropical forests, effective biodiversity management demands measures of progress, yet budgetary limitations typically constrain capacity of decision makers to assess response of biological communities to habitat change. One approach is to identify ecological-disturbance indicator species (EDIS) whose monitoring is also monetarily cost-effective. These species can be identified by determining individual species' responses to disturbance across a gradient; however, such responses may be confounded by factors other than disturbance. For example, in mountain environments the effects of anthropogenic habitat alteration are commonly confounded by elevation. EDIS have been identified with the indicator value (IndVal) metric, but there are weaknesses in the application of this approach in complex montane systems. We surveyed birds, small mammals, bats, and leaf-litter lizards in differentially disturbed cloud forest of the Ecuadorian Andes. We then incorporated elevation in generalized linear (mixed) models (GL(M)M) to screen for EDIS in the data set. Finally, we used rarefaction of species accumulation data to compare relative monetary costs of identifying and monitoring EDIS at equal sampling effort, based on species richness. Our GL(M)M generated greater numbers of EDIS but fewer characteristic species relative to IndVal. In absolute terms birds were the most cost-effective of the 4 taxa surveyed. We found one low-cost bird EDIS. In terms of the number of indicators generated as a proportion of species richness, EDIS of small mammals were the most cost-effective. Our approach has the potential to be a useful tool for facilitating more sustainable management of Andean forest systems.
在物种丰富的热带森林中,有效的生物多样性管理需要衡量进展的措施,但预算限制通常会制约决策者评估生物群落对栖息地变化的反应的能力。一种方法是识别生态干扰指示物种(EDIS),对其进行监测在资金方面也具有成本效益。这些物种可以通过确定单个物种在一个梯度上对干扰的反应来识别;然而,这种反应可能会受到干扰以外的其他因素的混淆。例如,在山区环境中,人为栖息地改变的影响通常会与海拔高度相互混淆。EDIS已通过指示值(IndVal)指标来识别,但在复杂的山地系统中应用这种方法存在缺陷。我们对厄瓜多尔安第斯山脉不同干扰程度的云雾森林中的鸟类、小型哺乳动物、蝙蝠和落叶层蜥蜴进行了调查。然后,我们将海拔高度纳入广义线性(混合)模型(GL(M)M)中,以在数据集中筛选EDIS。最后,我们使用物种累积数据的稀疏化方法,根据物种丰富度,比较在同等采样工作量下识别和监测EDIS的相对资金成本。相对于IndVal,我们的GL(M)M产生了更多的EDIS,但特征物种较少。从绝对值来看,在所调查的4个分类群中,鸟类是最具成本效益的。我们发现了一种低成本的鸟类EDIS。就作为物种丰富度比例产生的指示物种数量而言,小型哺乳动物的EDIS最具成本效益。我们的方法有可能成为促进安第斯森林系统更可持续管理的有用工具。