The Commonwealth Scientific and Industrial Research Organisation Wealth from Oceans Flagship, Marine Laboratories, Hobart, Tasmania, Australia.
PLoS One. 2012;7(5):e36558. doi: 10.1371/journal.pone.0036558. Epub 2012 May 11.
Understanding patterns of biodiversity in deep sea systems is increasingly important because human activities are extending further into these areas. However, obtaining data is difficult, limiting the ability of science to inform management decisions. We have used three different methods of quantifying biodiversity to describe patterns of biodiversity in an area that includes two marine reserves in deep water off southern Australia. We used biological data collected during a recent survey, combined with extensive physical data to model, predict and map three different attributes of biodiversity: distributions of common species, beta diversity and rank abundance distributions (RAD). The distribution of each of eight common species was unique, although all the species respond to a depth-correlated physical gradient. Changes in composition (beta diversity) were large, even between sites with very similar environmental conditions. Composition at any one site was highly uncertain, and the suite of species changed dramatically both across and down slope. In contrast, the distributions of the RAD components of biodiversity (community abundance, richness, and evenness) were relatively smooth across the study area, suggesting that assemblage structure (i.e. the distribution of abundances of species) is limited, irrespective of species composition. Seamounts had similar biodiversity based on metrics of species presence, beta diversity, total abundance, richness and evenness to the adjacent continental slope in the same depth ranges. These analyses suggest that conservation objectives need to clearly identify which aspects of biodiversity are valued, and employ an appropriate suite of methods to address these aspects, to ensure that conservation goals are met.
理解深海系统生物多样性的模式变得越来越重要,因为人类活动正在向这些区域进一步扩展。然而,获取数据具有难度,这限制了科学为管理决策提供信息的能力。我们使用了三种不同的量化生物多样性的方法来描述澳大利亚南部深海两个海洋保护区范围内的生物多样性模式。我们利用最近调查中收集的生物数据,并结合广泛的物理数据,对三种不同的生物多样性属性进行建模、预测和绘图:常见物种的分布、β多样性和等级丰度分布(RAD)。尽管所有物种都对与深度相关的物理梯度做出反应,但八种常见物种中的每一种的分布都是独特的。组成的变化(β多样性)很大,即使在环境条件非常相似的地点之间也是如此。任何一个地点的组成都高度不确定,物种组合在跨越和沿坡向下都发生了巨大变化。相比之下,生物多样性的 RAD 成分分布(群落丰度、丰富度和均匀度)在研究区域内相对平滑,这表明组合结构(即物种丰度的分布)是有限的,而与物种组成无关。在相同深度范围内,与相邻大陆坡相比,海山的生物多样性(基于物种存在、β多样性、总丰度、丰富度和均匀度的度量)相似。这些分析表明,保护目标需要明确确定哪些方面的生物多样性具有价值,并采用适当的方法来解决这些方面,以确保实现保护目标。