Saskatchewan Condition Assessment of Lotic Ecosystems (SCALE): A multivariate tool for assessing the integrity of Northern Great Plains wadeable rivers and streams

• 主要な著者: Iain D. Phillips (著者), Glen McMaster (著者), Douglas P. Chivers (著者), Michelle F. Bowman (著者)
• フォーマット: 図書
• 出版事項: Canadian Science Publishing, 2023-01-01T00:00:00Z.
• 主題: article
• オンライン･アクセス: Connect to this object online.
• Notes: 10.1139/facets-2022-0158; 2371-1671
• Keywords: macroinvertebrates; stream bioassessment; Northern Great Plains; reference condition approach; Test Site Analysis; Education; L; Science; Q
• Source: FACETS, Vol 8, Iss , Pp 1-31 (2023)

Human access to surface water resources in the Northern Great Plains (NGP) is challenged by availability and quality, and ecosystem health objectives for these characteristics have not been well developed. Here, we present a predictive multivariate model using the reference condition approach to inform goals for ecosystem health assessment. Benthic communities and abiotic variables were collected at 280 potential reference sites and 8 test sites, and of these, reference sites with least amount of human activity (n = 83) were classified into three community groups and summary metrics. Discriminant function analysis and cross-validation determined that stream order and ecoregion predicted 68.7% of the sites correctly, thus enabling comparison of sites with unknown condition to reference site groups. We then evaluated metrics through Test Site Analysis and stressor gradient analysis in each biological group. Beetle and amphipod fauna were found to be important for condition assessment in addition to traditional metrics of species richness, abundance, detritivory, Ephemeroptera/Plecoptera/Trichoptera dominance, and assemblage composition. These results provide least disturbed reference condition and ecological insights into land use impacts in the NGP. Ultimately, this model is an effective tool for evaluating biotic condition, enables prioritizing river management strategies, and can quantify the efficacy of mitigation measures.