Towards generalised reference condition models for environmental assessment: a case study on rivers in Atlantic Canada

被引:11
作者
Armanini, D. G. [1 ,2 ]
Monk, W. A. [1 ]
Carter, L. [3 ]
Cote, D. [4 ]
Baird, D. J. [1 ]
机构
[1] Univ New Brunswick, Environm Canada, Canadian Rivers Inst, Dept Biol, Fredericton, NB E3B 5A3, Canada
[2] Prothea Srl, Milan, Italy
[3] Environm Canada Atlantic Water Qual Monitoring, Dartmouth, NS B2Y 2N6, Canada
[4] Pk Canada, Terra Nova Natl Pk, Glovertown, NF, Canada
关键词
Macroinvertebrate; Bioassessment; Geographic information system; RIVPACS; Monitoring; RUNNING-WATER SITES; MACROINVERTEBRATE FAUNA; PREDICTIVE MODELS; RARE TAXA; CLASSIFICATION; ASSEMBLAGES; BIOASSESSMENT; SENSITIVITY; QUALITY; STREAMS;
D O I
10.1007/s10661-012-3021-2
中图分类号
X [环境科学、安全科学];
学科分类号
083001 [环境科学];
摘要
Evaluation of the ecological status of river sites in Canada is supported by building models using the reference condition approach. However, geography, data scarcity and inter-operability constraints have frustrated attempts to monitor national-scale status and trends. This issue is particularly true in Atlantic Canada, where no ecological assessment system is currently available. Here, we present a reference condition model based on the River Invertebrate Prediction and Classification System approach with regional-scale applicability. To achieve this, we used biological monitoring data collected from wadeable streams across Atlantic Canada together with freely available, nationally consistent geographic information system (GIS) environmental data layers. For the first time, we demonstrated that it is possible to use data generated from different studies, even when collected using different sampling methods, to generate a robust predictive model. This model was successfully generated and tested using GIS-based rather than local habitat variables and showed improved performance when compared to a null model. In addition, ecological quality ratio data derived from the model responded to observed stressors in a test dataset. Implications for future large-scale implementation of river biomonitoring using a standardised approach with global application are presented.
引用
收藏
页码:6247 / 6259
页数:13
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