Collaborative Research: Population Ecology Models for Carbonate Sediments

碳酸盐沉积物广泛沉积在海洋中，是全球碳收支的重要因素。但它们很难理解，因为它们是生物学上创造的，然后在地质学上进行了修改。在这个项目之前，它们是用非常简单的基于规则的方法建模的，这些方法的名称是？碳酸盐工厂吗?。这个项目采取了下一步，直接应用生物学原理使用先进的数值模拟实际过程？？碳酸盐农场吗?。珊瑚、苔藓虫和藻类等碳酸盐骨架生物的种群和群落生态学用于构建逼真、详细的3D时间地质结构。这为碳循环、海洋酸化、岩石性质、油气资源和环境对全球变化的响应开辟了富有成效的新研究途径。流程建模无法实现的看法是错误的？关键是在适当的时间-空间尺度上，对关键生物体采用正确的数学策略。在原型中，这个项目已经产生了紧急的模型特征，如高产？骨的院子吗?生态学，以及对累积沉积物变异性的正确统计。输出结果甚至可以在岩心描述层面与综合海洋钻井计划（IODP）岩心测井和石油工业储层变异性统计数据进行比较，有望获得跨学科的结果。

EAGER: Collaborative Research: Population Ecology Models for Carbonate Sediments Christopher C. Jenkins EAR-1118297 University of Colorado, Boulder PI: Potts, Donald C. EAR-1118306 University of California-Santa CruzCarbonate sediments are deposited extensively in the oceans and are a significant factor in global carbon budgets. But they are challenging to understand because they are created biologically, then modified geologically. Prior to this project, they had been modeled with rather simple rules-based methods which go under the name ?carbonate factory?. This project takes the next step and directly applies biological principles using advanced numerical modeling on the actual processes ? ?carbonate farm?. The population and community ecology of carbonate-skeleton organisms such as corals, bryozoans and algae is used to build realistic, detailed 3D time-geologic architectures. This opens productive new research paths into the carbon cycle, ocean acidification, rock properties, oil-gas resources, and environmental responses to global change. Perceptions that process modeling is not achievable are wrong ? the key is to employ good math tactics on the correct set of processes, for the key organisms, at appropriate time-space scales. In prototype this project has already produced emergent model features such as high-production ?bone yard? ecologies, and correct statistics for the variability of the accumulated sediments. The outputs can be compared even at the core-description level with Integrated Ocean Drilling Program (IODP) core logs and oil-industry reservoir variability statistics, promising cross-discipline results.