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Predicting biological condition in southern California streams

Landscape and Urban Planning

By:
, , , , , and
DOI: 10.1016/j.landurbplan.2012.07.009

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Abstract

As understanding of the complex relations among environmental stressors and biological responses improves, a logical next step is predictive modeling of biological condition at unsampled sites. We developed a boosted regression tree (BRT) model of biological condition, as measured by a benthic macroinvertebrate index of biotic integrity (BIBI), for streams in urbanized Southern Coastal California. We also developed a multiple linear regression (MLR) model as a benchmark for comparison with the BRT model. The BRT model explained 66% of the variance in B-IBI, identifying watershed population density and combined percentage agricultural and urban land cover in the riparian buffer as the most important predictors of B-IBI, but with watershed mean precipitation and watershed density of manmade channels also important. The MLR model explained 48% of the variance in B-IBI and included watershed population density and combined percentage agricultural and urban land cover in the riparian buffer. For a verification data set, the BRT model correctly classified 75% of impaired sites (B-IBI < 40) and 78% of unimpaired sites (B-IBI = 40). For the same verification data set, the MLR model correctly classified 69% of impaired sites and 87% of unimpaired sites. The BRT model should not be used to predict B-IBI for specific sites; however, the model can be useful for general applications such as identifying and prioritizing regions for monitoring, remediation or preservation, stratifying new bioassessments according to anticipated biological condition, or assessing the potential for change in stream biological condition based on anticipated changes in population density and development in stream buffers.

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Additional Publication Details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
Predicting biological condition in southern California streams
Series title:
Landscape and Urban Planning
DOI:
10.1016/j.landurbplan.2012.07.009
Volume
108
Issue:
1
Year Published:
2012
Language:
English
Publisher:
Elsevier
Publisher location:
Amsterdam, Netherlands
Contributing office(s):
California Water Science Center
Description:
11 p.
Larger Work Type:
Article
Larger Work Subtype:
Journal Article
Larger Work Title:
Landscape and Urban Planning
First page:
17
Last page:
27
Country:
United States
State:
California