tailieunhanh - ECOTOXICOLOGY: A Comprehensive Treatment - Chapter 23

Cộng đồng Sinh thái học và sinh thái chất độc Phương pháp tiếp cận quan sát có thể cung cấp hỗ trợ cho một mối quan hệ quan hệ nhân quả giữa những căng thẳng và phản ứng của cộng đồng, tuy nhiên, các nghiên cứu mô tả một mình không có thể được sử dụng để hiển thị nhân quả. Trong khi ứng dụng của Koch định đề, Hill của tiêu chuẩn, và trọng lượng-của-bằng chứng phương pháp tiếp cận khác như phương pháp Bayesian có thể củng cố lập luận cho các mối quan hệ nhân quả (1998 Beyers,. | 23 Experimental Approaches in Community Ecology and Ecotoxicology Observational approaches may provide support for a causal relationship between stressors and community responses however descriptive studies alone cannot be used to show causation. While application of Koch s postulates Hill s criteria and other weight-of-evidence approaches such as Bayesian methods may strengthen arguments for causal relationships Beyers 1998 Suter 1993 to many researchers controlled experimental manipulations remain the only way to rigorously demonstrate causation in scientific investigations. The relationship between descriptive and experimental approaches in ecotoxicology can be depicted as continua along two axes that reflect the degree of experimental control replication and ecological relevance Figure . Experimental approaches such as single species toxicity tests and microcosm experiments provide rigorous control over confounding variables and are easily replicated but lack ecological realism. Purely descriptive studies . routine biomonitoring lack true replication and random assignment of treatments to experimental units. Because treatments are not assigned randomly differences between reference and impacted sites in biomonitoring studies cannot be directly attributed to a particular stressor. Several alternative experimental designs have been proposed that address problems associated with the lack of replication and random assignment of treatments however Beyers 1998 argues that it is fundamentally wrong to apply inferential statistics to pseudoreplicated data to show that an observed effect was caused by an impact. The widespread application of inferential statistics in published biomonitoring studies suggests that this opinion is not shared by many researchers or journal editors. As we will see the use of inferential statistics is not an essential component of all experimental designs. In some instances sustained manipulations at a large spatial or temporal scale