热带非洲河流污染评估的简单和经济有效的生物监测方法

J. D. Elias
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引用次数: 1

摘要

热带非洲地区依靠非热带生物监测方法来评估其河流中的水污染的采用规则,由于区域之间的环境变化而影响所采用方法的能力和可靠性的地理不相容而受到阻碍。同样,在开发现有的生物监测方法(即南非评分系统(SASS5)和坦桑尼亚河流评分系统(TARISS))时纳入所有已确定的大型无脊椎动物组合,使得它们在分类学上变得复杂,因为它们的使用需要用户在分类群鉴定过程中具有更高的专业知识和大量的时间。因此,在发展热带生物监测方法时,在采用或修改非热带生物监测方法方面的分类复杂性和相互矛盾的方面使得有必要设计这项研究,以便发展简单和具有成本效益的热带非洲生物监测方法,初步应用于坦桑尼亚河流。采用6个两两筛选标准来筛选具有独特纳入潜力的目,以开发简单而经济有效的生物监测方法。只有蜉蝣目、双翅目、齿翅目和毛翅目(EDOT)显示了它们区分参考点和监测点的能力,并与环境变量有很强的相关性,符合所有6个纳入标准。EDOT方法仅使用四种不同的目,发生范围更广,对污染更敏感,将最大限度地减少数据的可变性,减少对分类群鉴定过程中更多专业知识、成本和时间的需求。该方法的新颖之处在于简化了40年来现有指数固有的分类学复杂性,并应用模型模拟敏感性评分未知的分类群的敏感性权重。
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Simple and Cost-Effective Biomonitoring Method for Assessing Pollution in Tropical African Rivers
Adoption rule whereby tropical African regions rely on non-tropical biomonitoring methods to assess water pollution in their rivers has been hindered by geographical incompatibility due to environmental variations between the regions that affect the capability and reliability of adopted method. Likewise, inclusion of all identified macroinvertebrate assemblages in developing the existing biomonitoring methods (i.e., South African Scoring System (SASS5) and Tanzania Riverine Scoring System (TARISS)) has made them complex taxonomically as their use requires users of greater expertise and much time during taxa identification. Such taxonomic complications and conflicting aspects regarding the adoption or modification of non-tropical biomonitoring methods in developing tropical biomonitoring methods have therefore necessitated the design of this study in order to develop simple and cost-effective tropical African biomonitoring methods, for initial application in Tanzanian rivers. Six pairwise screening criteria were employed to select orders with distinctive potential for inclusion in developing simple and cost-effective biomonitoring method. Only Ephemeroptera, Diptera, Odonata and Trichoptera (EDOT) orders met all six inclusion criteria after showing their ability to discern reference sites from monitoring sites and correlating strongly with environmental variables. Being developed using only four diverse orders with the wider range of occurrences and sensitivity to pollution, the EDOT method will minimize data variability, the need for greater expertise, cost, and time during taxa identification. The novelty of the present approach lies on the simplification of the taxonomic complication that is inherent in existing indices for four decades and modelling application to simulate sensitivity weightings for taxa with unknown sensitivity score ratings.
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