Population and Community Dynamics of Corals: A Long-Term Study

康奈尔这个项目是对珊瑚礁系统的长期研究。该项目的目标是：1）延长对澳大利亚大堡礁珊瑚和藻类生态群落的详细长期监测，这项监测在过去36年里一直在进行，是对任何珊瑚礁进行的最长的此类研究; 2）分析珊瑚和藻类在几个尺度上的空间格局和动态，从毫米到公里，无论是在斑块的殖民过程中，（由于干扰而打开），并且在大部分表面被许多殖民地拥挤之后;以及3）建立这些珊瑚和藻类种群和群落动态的数学模型和计算机模拟，包括：对未来变化的过去和现在条件的调查;时间和空间动态的特征;以及关于这些动态对社区的后果的假设的测试。该模型还将用于评估群落结构和动态可能或可能不受空间关系和相互作用细节影响的程度。这项拟议研究的意义是：扩大了珊瑚和藻类天然群落在长期环境变化中如何组装和结构的一般知识;揭示了环境与这些社区变化之间的一些联系机制，以及两者如何在短期和长期内以及在小型和大型空间尺度之间发生变化;提高了我们预测环境变化（包括人类活动造成的环境变化）对这些自然社区的影响的能力。

Connell This project is a long-term study of a coral reef system. The project goals are: 1) to extend the detailed long-term monitoring of ecological communities of corals and algae on the Great Barrier Reef, Australia, which has been carried on continuously over the past 36 years, the longest such study on any coral reef; 2) to analyze spatial patterns and dynamics of corals and algae at several scales, from mm to kilometers, both during the course of colonization of patches (opened by disturbances) and after most of the surface has become crowded by many colonies; and 3) to build mathematical models and computer simulations of the dynamics of these populations and communities of corals and algae that include: an investigation of past and present conditions on future changes; characterizations of temporal and spatial dynamics; and tests of hypotheses about the consequences of these dynamics to the community. The models also will be used to assess the degree to which community structure and dynamics may or may not be influenced by details of spatial relationships and interactions.The significance of this proposed research are: a extension of the general knowledge of how natural communities of corals and algae are assembled and structured in the face of changes in their environment over extended periods of time; a revelation of some of the mechanisms that link the environment with these community changes, and how both vary over short and long time periods and between small and larger spatial scales; and an increase in our ability to predict the effect of environmental changes, including those caused by human activity, on these natural communities.