期刊
PLOS ONE
卷 13, 期 6, 页码 -出版社
PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0198439
关键词
-
资金
- U.S. Department of Energy, Water Power Technologies Office within the Office of Energy Efficiency and Renewable Energy [DE-AC05-000R22725]
Describing the physical habitat diversity of stream types is important for understanding stream ecosystem complexity, but also prioritizing management of stream ecosystems, especially those that are rare. We developed a stream classification system of six physical habitat layers (size, gradient, hydrology, temperature, valley confinement, and substrate) for approximately 1 million stream reaches within the Eastern United States in order to conduct an inventory of different types of streams and examine stream diversity. Additionally, we compare stream diversity to patterns of anthropogenic disturbances to evaluate associations between stream types and human disturbances, but also to prioritize rare stream types that may lack natural representation in the landscape. Based on combinations of different layers, we estimate there are anywhere from 1,521 to 5,577 different physical types of stream reaches within the Eastern US. By accounting for uncertainty in class membership, these estimates could range from 1,434 to 6,856 stream types. However, 95% of total stream distance is represented by only 30% of the total stream habitat types, which suggests that most stream types are rare. Unfortunately, as much as one third of stream physical diversity within the region has been compromised by anthropogenic disturbances. To provide an example of the stream classification's utility in management of these ecosystems, we isolated 5% of stream length in the entire region that represented 87% of the total physical diversity of streams to prioritize streams for conservation protection, restoration, and biological monitoring. We suggest that our stream classification framework could be important for exploring the diversity of stream ecosystems and is flexible in that it can be combined with other stream classification frameworks developed at higher resolutions (meso-and micro-habitat scales). Additionally, the exploration of physical diversity helps to estimate the rarity and patchiness of riverscapes over large region and assist in conservation and management.
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