Outsized Nutrient Contributions From Small Tributaries To A Great Lake

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA(2020)

引用 48|浏览19
暂无评分
摘要
Excessive nitrogen (N) and phosphorus (P) loading is one of the greatest threats to aquatic ecosystems in the Anthropocene, causing eutrophication of rivers, lakes, and marine coastlines worldwide. For lakes across the United States, eutrophication is driven largely by nonpoint nutrient sources from tributaries that drain surrounding watersheds. Decades of monitoring and regu-latory efforts have paid little attention to small tributaries of large water bodies, despite their ubiquity and potential local importance. We used a snapshot of nutrient inputs from nearly all tributaries of Lake Michigan-the world's fifth largest freshwater lake by volume-to determine how land cover and dams alter nutrient inputs across watershed sizes. Loads, concentrations, stoichiometry (N:P), and bioavailability (percentage dissolved inorganic nutrients) varied by orders of magnitude among tributaries, creating a mosaic of coastal nutrient inputs. The 6 largest of 235 tributaries accounted for similar to 70% of the daily N and P delivered to Lake Michigan. However, small tributaries exhibited nutrient loads that were high for their size and biased toward dissolved inorganic forms. Higher bioavailability of nutrients from small watersheds suggests greater potential to fuel algal blooms in coastal areas, especially given the likelihood that their plumes become trapped and then overlap in the nearshore zone. Our findings reveal an underappreciated role that small streams may play in driving coastal eutrophication in large water bodies. Although they represent only a modest proportion of lake-wide loads, expanding nutrient management efforts to address smaller watersheds could reduce the ecological impacts of nutrient loading on valuable nearshore ecosystems.
更多
查看译文
关键词
tributary, nutrient loads, Laurentian Great Lakes, eutrophication
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要