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- Title
基于底栖动物预测模型构建生物完整性指数评价河流健康.
- Authors
陈凯; 于海燕; 张汲伟; 王备新; 陈求稳
- Abstract
Improving the stability of integrity of biotic index (IBI; i.e., multi-metric indices, MMI) across temporal and spatial scales is one of the most important issues in water ecosystem integrity bioassessment and water environment management. Using datasets of field-based macroinvertebrate and physicochemical variables and GIS-based natural predictors (e.g., geomorphology and climate) and land use variables collected at 227 river sites from 2004 to 2011 across the Zhejiang Province, China, we used random forests (RF) to adjust the effects of natural variations at temporal and spatial scales on macroinvertebrate metrics. We then developed natural variations adjusted (predictive) and unadjusted (null) MMIs and compared performance between them. The core metrics selected for predictive and null MMIs were different from each other, and natural variations within core metrics in predictive MMI explained by RF models ranged between 11.4% and 61.2%. The predictive MMI was more precise and accurate, but less responsive and sensitive than null MMI. The multivariate nearest-neighbor test determined that 9 test sites and 1 most degraded site were flagged outside of the environmental space of the reference site network. We found that combination of predictive MMI developed by using predictive model and the nearest-neighbor test performed best and decreased risks of inferring type I (designating a water body as being in poor biological condition, when it was actually in good condition) and type II (designating a water body as being in good biological condition, when it was actually in poor condition) errors. Our results provided an effective method to improve the stability and performance of integrity of biotic index.
- Subjects
INVERTEBRATES; RIVER ecology; PREDICTION models; BIOTIC communities; GEOGRAPHIC information systems; RANDOM forest algorithms
- Publication
Yingyong Shengtai Xuebao, 2017, Vol 28, Issue 6, p1993
- ISSN
1001-9332
- Publication type
Article
- DOI
10.13287/j.1001-9332.201706.015