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首页> 外文期刊>Freshwater science >Evaluation of methods to assess benthic biodiversity of desert sinkholes
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Evaluation of methods to assess benthic biodiversity of desert sinkholes

机译：评价沙漠下陷底栖生物多样性的方法

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Evaluators of aquatic systems often use benthic macroinvertebrates because they are central components in the food chain and useful for water-quality assessments and management decisions. More than 44 sampling devices are commonly used to collect benthic macroinvertebrates. Bitter Lake National Wildlife Refuge in New Mexico, USA, is a unique habitat with a complex of aquatic sinkholes. Morphometry, water chemistry, and biology differ vastly among sinkholes, creating challenges when deciding how to sample appropriately for benthic macroinvertebrates. We evaluated 5 sampling methods commonly used in lentic habitats: aquatic net (epibenthic sled), artificial substrate (Hester-Dendy multiplate [H-D] sampler), light trap, grab (Ponar grab), and suction sampler (pump sampler). We compared total number of taxa, % taxa detected, and total number of individuals collected among the 5 methods with a mixed-model incomplete block analysis of variance. The light trap caught the most taxa and yielded the highest % taxa detected. It also caught the most specimens. H-D samplers and Ponar grabs added taxa that were not commonly found in light traps, especially gastropods. We were unable to deploy the pump sampler and the epibenthic sled in all sinkholes, and they contributed little additional information. We recommend combined use of light traps, H-D samplers, and a Ponar grab to obtain a good representation of benthic invertebrates over a wide variety of environmental conditions in sinkholes and other lentic habitats. Together these methods detected 84 to 100% of taxa in each sinkhole.
机译：水生生物评估者经常使用底栖无脊椎动物，因为它们是食物链中的核心组成部分，可用于水质评估和管理决策。通常使用超过44种采样设备来收集底栖大型无脊椎动物。美国新墨西哥州的苦湖国家野生动物保护区是一个独特的栖息地，拥有大量的水坑。污水坑的形态，水化学和生物学差异很大，在决定如何对底栖无脊椎动物进行适当取样时提出了挑战。我们评估了5个通常在透镜体栖息地中使用的采样方法：水生网（表皮雪橇），人工基质（Hester-Dendy多板[H-D]采样器），光阱，抓斗（Ponar抓斗）和吸气采样器（泵采样器）。我们使用混合模型不完全方差分析比较了5种方法中的分类单元总数，检测到的分类单元百分比以及收集的个体总数。光线陷阱捕获到最多的分类单元，并产生了最高的％分类单元。它也捕获了最多的标本。 H-D采样器和Ponar捕获了在陷阱（尤其是腹足动物）中不常见的类群。我们无法在所有污水坑中部署泵采样器和上皮雪橇，它们几乎没有提供任何其他信息。我们建议结合使用光阱，H-D采样器和Ponar抓斗，以在下沉坑和其他透镜体生境的各种环境条件下获得良好的底栖无脊椎动物表现。这些方法一起在每个污水坑中检测到84％至100％的分类单元。

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