Coral Bleaching: Translating Response Models Across Scales

珊瑚白化：跨尺度转换响应模型

• 批准号: 0308960
• 负责人: Semen Koksal
• 金额: $ 9.72万
• 依托单位: Florida Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-08-01 至 2004-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0308960&HistoricalAwards=false
• 关键词: Coral; Bleaching; Translating; Response; Models

This project will assess relationships among population and community response variables and thermal stress gradients. It will also examine the relationship between population and physiological response variables. Since thermal stress is a function of intensity and duration of heating, the mathematical models will be developed more explicitly in terms of partial differential equations. The measured dependent variables will be expressed as a function of intensity and duration of thermal stress using for example, degree- heating weeks as independent variable. Functional response will be compared at the population and community levels, and at the population and physiology levels. The independent variable will be explored further, and cross correlations will be re-examined using other independent variables such as, effective degree-heating weeks which maybe considered as the integration of degree-heating weeks, water flow regimes and irradiance.In addition, the models will also include the assessment of questions involving thermal stress scenarios such as, how many habitats support species i, and how many species are supported at site k. Finally, the models will predict the future climates, in return, these predictions will allow us to examine potential population changes over time given different climatic scenarios.This IGMS project is jointly supported by the MPS Office of Multidisciplinary Activities (OMA) and the Division of Mathematical Sciences (DMS).

该项目将评估人口和社区反应变量与热应力梯度之间的关系。 它还将研究人口和生理反应变量之间的关系。由于热应力是加热强度和持续时间的函数，因此将以偏微分方程的形式更明确地建立数学模型。测量的因变量将表示为热应力强度和持续时间的函数，例如，使用加热周数作为自变量。 功能反应将在人口和社区水平，并在人口和生理水平进行比较。将进一步探索自变量，并使用其他自变量重新检查交叉相关性，例如，有效升温周数，可以认为是升温周数，水流状况和辐照度的综合。此外，模型还将评估涉及热应力情景的问题，例如，有多少栖息地支持物种i，以及在站点k处支持多少物种。最后，这些模型将预测未来的气候，作为回报，这些预测将使我们能够在不同的气候情景下研究潜在的人口变化。IGMS项目由MPS多学科活动办公室（OMA）和数学科学部（DMS）共同支持。