4.7 Article

Unexpected resurgence of a large submersed plant bed in Chesapeake Bay: Analysis of time series data

期刊

LIMNOLOGY AND OCEANOGRAPHY
卷 59, 期 2, 页码 482-494

出版社

WILEY
DOI: 10.4319/lo.2014.59.2.0482

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  1. Maryland Sea Grant
  2. National Oceanographic and Atmospheric Administration [NA10/OAR4170072]
  3. University of Maryland Center for Environmental Science, Horn Point Laboratory

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An historically large (> 50 km(2)) submersed plant bed in upper Chesapeake Bay virtually disappeared in 1972, following Tropical Storm Agnes. The bed experienced little regrowth until the early 2000s, when plant abundance rapidly increased. Here, we analyze a suite of recent (1984-2010) and historical (1958-1983) time series datasets to assess alternative explanations for the submersed plant resurgence. Change-point analysis showed that spring nitrogen (N) loading increased from 1945 to 1988 and decreased from 1988 to 2010. Analysis of variance on recent time series showed a significant difference in submersed aquatic vegetation (SAV) abundance percent change during wet years (-7 +/- 11%) and dry years (53 +/- 20%), indicating that floods and droughts likely contributed to SAV loss and growth, respectively. In the historic dataset, however, increasingly poor water quality led to SAV loss despite an extended drought period, indicating that underlying water quality trends were also important in driving change in SAV abundance. Several water quality variables, including N concentration and turbidity, were lower inside the SAV bed than outside the SAV bed, implying the presence of feedback processes whereby the bed improves its own growing conditions by enhancing biophysical processes such as sediment deposition and nutrient cycling. Together, these analyses suggest that stochastic extremes in river discharge and long-term water quality trends synergistically facilitated sudden shifts in SAV abundance and that feedback processes likely reinforced the state of the bed before and after the shifts. Management efforts should consider these dynamic interactions and minimize chronic underlying stressors, which are often anthropogenic in origin.

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