首页 | 本学科首页   官方微博 | 高级检索  
     检索      


Mechanisms of Storm-Related Loss and Resilience in a Large Submersed Plant Bed
Authors:Cassie Gurbisz  W Michael Kemp  Lawrence P Sanford  Robert J Orth
Institution:1.University of Maryland Center for Environmental Science Horn Point Laboratory,Cambridge,USA;2.Virginia Institute of Marine Science,College of William and Mary,Gloucester Point,USA
Abstract:There is a growing emphasis on preserving ecological resilience, or a system’s capacity to absorb or recover quickly from perturbations, particularly in vulnerable coastal regions. However, the factors that affect resilience to a given disturbance are not always clear and may be system-specific. We analyzed and synthesized time series datasets to explore how extreme events impacted a large system of submersed aquatic vegetation (SAV) in upper Chesapeake Bay and to identify and understand associated mechanisms of resilience. We found that physical removal of plants around the edge of the bed by high flows during a major flood event as well as subsequent wind-driven resuspension of newly deposited sediment and attendant light-limiting conditions were detrimental to the SAV bed. Conversely, it appears that the bed attenuated high flows sufficiently to prevent plant erosion at its inner core. The bed also attenuated wind-driven wave amplitude during seasonal peaks in plant biomass, thereby decreasing sediment resuspension and increasing water clarity. In addition, clear water appeared to “spill over” into adjacent regions during ebb tide, improving the bed’s capacity for renewal by creating more favorable growing conditions in areas where plant loss had occurred. These analyses demonstrate that positive feedback processes, whereby an SAV bed modifies its environment in ways that improve its own growth, likely serve as mechanisms of SAV resilience to flood events. Although this work focuses on a specific system, the synthetic approach used here can be applied to any system for which routine monitoring data are available.
Keywords:
本文献已被 SpringerLink 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号