Resilience of the Tidal Marsh Bird Community to Hurricane Sandy and Assessment of Restoration Efforts

semanticscholar(2018)

引用 0|浏览1
暂无评分
摘要
Changes in the frequency and severity of extreme weather may introduce new threats to species that are already under stress from habitat loss and gradual climate change. Coastal birds in particular are viewed as vulnerable to strengthening hurricanes, yet this assumption has not been tested, in part because of the difficulty of applying traditional concepts of resilience to dynamic populations. Here we provide a framework for applying ideas about ecological resilience to inform species conservation, based on a computational approach that 1) compares disturbance-impacted population projections to the normal range of variation in a population, taking into account annual variation in vital rates and demographic stochasticity, and 2) quantifies the full range of potential impacts. We illustrate this framework by developing population projection models for two declining and two stable tidal marsh specialists: saltmarsh sparrow (Ammodramus caudacutus), clapper rail (Rallus crepitans), seaside sparrow (Ammodramus maritimus), and willet (Tringa semipalmata). We found that the populations of these focal species are resilient to extreme disturbances, with high resistance to the effects of short-term reductions in vital rates and recovery to the range of normal variation within 20 years. For example, a 69% reduction in survival or a 95% reduction in fecundity was required to shift trajectories of clapper rail populations outside of normal variation 50% of the time. The simple computational approach used here can be applied to other models that project population or range dynamics, providing a general framework for quantifying population resilience to disturbance events. Applying this framework across potentially disturbance-prone species and ecosystems would generate specific projections of resilience that are needed for effective conservation planning and policy, especially for species that are vulnerable to stronger or more frequent weather events.
更多
查看译文
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