Trait-based phytoplankton models in a changing world

浮游植物约占全球初级生产量的50%，它们将碳从大气输送到深海。这一碳通量约为11GtCa-1。这是一个很大的碳通量，因为它目前比每年人类对大气中碳的输入要大。海洋表面气候的变化，包括温度、大气二氧化碳、海洋pH值和风力驱动的混合，将改变浮游植物生物量和生产力的分布以及生物泵输出的碳的数量。目前，海洋界对初级产品和出口产品的数量以及人为气候变化预期的变化只有粗略的模型。我将开发海洋浮游植物生产力和生物量分布的数学模型，以预测环境条件变化对初级和出口生产的影响以及对生物地球化学循环的影响。我的项目目标是将浮游植物的生理机制，如对各种资源的适应与其生态和生物地球化学后果联系起来，以预测气候变化将如何改变海洋初级生产力、生态系统动力学和海洋碳循环。我将构建和测试浮游植物光合作用和生长以及群落组成的模型，并使用数据库和时间序列来评估这些建模方法，特别是基于分类和大小的性状和性状权衡。

Phytoplankton account for about 50% of global primary production and they drive a flux of carbon from the atmosphere to the deep ocean. This carbon flux is responsible for about 11 Gt C a-1. This is a significant flux of C as it is currently larger than the annual anthropogenic input of C into the atmosphere. Changing climate at the surface of the ocean, including temperature, atmospheric CO2, ocean pH, and wind-driven mixing, will alter the distribution of phytoplankton biomass and productivity and the amount of C exported by the biological pump. Presently the oceanographic community has only crude models for the amount of primary and export production and changes expected as a consequence of anthropogenic climate change. I will develop mathematical models of marine phytoplankton productivity and biomass distributions to predict effects of changing environmental conditions on primary and export production and consequences for biogeochemical cycles. My program goals are to connect phytoplankton physiological mechanisms such as acclimation to variable resources to their ecological and biogeochemical consequences, in order to predict how climate change will alter marine primary production, ecosystem dynamics and ocean carbon cycling. I will construct and test models of phytoplankton photosynthesis and growth and community composition and use databases and time-series to assess these modeling approaches, specifically taxonomic and size based traits and trait trade-offs.