Department of Paraclinical Sciences, Faculty of Veterinary Science, University of Pretoria, Private Bag X04, Onderstepoort, 0110, South Africa.
Laboratório associado IDL, Faculdade de Ciências, Universidade de Lisboa, Campo Grande, Lisbon, 1749-016, Portugal; Department of Botany, Biology Faculty, University of Santiago de Compostela, Campus Sur, Santiago de Compostela, 15076, Spain.
Sci Total Environ. 2018 Jan 15;612:214-222. doi: 10.1016/j.scitotenv.2017.08.181. Epub 2017 Sep 1.
Acid mine drainage (AMD) from coal mining in the Mpumalanga Highveld region of South Africa has caused severe chemical and biological degradation of aquatic habitats, specifically depressional wetlands, as mines use these wetlands for storage of AMD. Diatom-based multimetric indices (MMIs) to assess wetland condition have mostly been developed to assess agricultural and urban land use impacts. No diatom MMI of wetland condition has been developed to assess AMD impacts related to mining activities. Previous approaches to diatom-based MMI development in wetlands have not accounted for natural variability. Natural variability among depressional wetlands may influence the accuracy of MMIs. Epiphytic diatom MMIs sensitive to AMD were developed for a range of depressional wetland types to account for natural variation in biological metrics. For this, we classified wetland types based on diatom typologies. A range of 4-15 final metrics were selected from a pool of ~140 candidate metrics to develop the MMIs based on their: (1) broad range, (2) high separation power and (3) low correlation among metrics. Final metrics were selected from three categories: similarity to reference sites, functional groups, and taxonomic composition, which represent different aspects of diatom assemblage structure and function. MMI performances were evaluated according to their precision in distinguishing reference sites, responsiveness to discriminate reference and disturbed sites, sensitivity to human disturbances and relevancy to AMD-related stressors. Each MMI showed excellent discriminatory power, whether or not it accounted for natural variation. However, accounting for variation by grouping sites based on diatom typologies improved overall performance of MMIs. Our study highlights the usefulness of diatom-based metrics and provides a model for the biological assessment of depressional wetland condition in South Africa and elsewhere.
南非姆普马兰加高地地区煤矿开采导致的酸性矿山排水 (AMD) 对水生栖息地，特别是洼地湿地造成了严重的化学和生物退化，因为矿山将这些湿地用于 AMD 的储存。基于硅藻的多指标指数 (MMI) 主要用于评估农业和城市土地利用对湿地的影响。目前还没有开发用于评估与采矿活动相关的 AMD 影响的湿地条件硅藻 MMI。以前开发基于硅藻的湿地 MMI 的方法没有考虑自然变异性。洼地湿地之间的自然变异性可能会影响 MMI 的准确性。为了应对与采矿活动相关的 AMD 影响，我们开发了对 AMD 敏感的附生硅藻 MMI，用于一系列洼地湿地类型，以考虑生物指标的自然变化。为此，我们根据硅藻分类学对湿地类型进行分类。从大约 140 个候选指标中筛选出 4-15 个最终指标，以根据其以下三个标准来开发 MMI：(1) 广泛的范围；(2) 高分离能力；(3) 指标之间的低相关性。最终指标选自以下三个类别：与参考点的相似性、功能组和分类组成，它们代表硅藻组合结构和功能的不同方面。根据其区分参考点的精度、区分参考点和受干扰点的响应能力、对人为干扰的敏感性以及与 AMD 相关压力的相关性来评估 MMI 的性能。无论是否考虑到自然变化，每个 MMI 都显示出了极好的区分能力。然而，通过基于硅藻分类学对站点进行分组来考虑变异性，提高了 MMI 的整体性能。我们的研究强调了基于硅藻的指标的有用性，并为南非和其他地区洼地湿地条件的生物评估提供了模型。
