Landscape Based Identification of Human Disturbance Gradients and Reference Conditions for Michigan Streams

摘要: Identification of reference streams and human disturbance gradients are crucial steps in assessing the effects disturbances on stream health. We describe a process for identifying reaches using readily available, geo-referenced databases. demonstrate utility this by applying it to wadeable Michigan, USA, use identify which have greatest impact streams. Approximately 38% cold-water 16% warm-water Michigan were identified as being least-disturbed condition. Conversely, approximately 3% 4% moderately severely disturbed landscape disturbances. Anthropogenic that had nutrient loading percent urban land within network watersheds. Our health represents significant advantage over other routinely used methods. It uses inter-confluence an assessment unit, permits evaluation across large regions, yields overall index is weighted sum multiple factors. The robustness our approach linked scale affect stream; will be less robust degraded or with localized With improved availability high-resolution datasets, provide more complete picture factors contributing degradation