Nutrient uptake-related trait variability and trade-offs - adaptive evolution and community functioning in competing phytoplankton species

海洋浮游植物群落在很大程度上受营养状况的调节。营养浓度和化学计量选择与营养吸收相关的性状，如最大吸收速率（Vmax）和半饱和常数（Kn）。这些特征和相关的权衡共同决定了浮游植物的生态位、竞争能力以及最终将溶解的营养物质转化为浮游植物初级生产力，这是生态系统功能的一个主要组成部分。长期的营养吸收相关性状的种内和种间变异和权衡作为适应性生态进化动力学的预测因子的作用仍有待了解，同样未知的是不同营养制度下实现初级生产的后果。在这里，我们针对两个主要的浮游植物群体不同的基本方式来获取营养物质，亲和力与速度适应硝酸盐和磷酸盐，例如硅藻和颗石藻物种。我们遵循生态进化动力学随着时间的推移作为营养制度和多样性的函数，并研究浮游植物群落功能的后果。这一点特别重要，因为许多海洋区域的水柱分层现象加剧，营养限制日益增加。在本项目中，我们跨越实验生态进化、分子方法和预测模型来验证以下假设：（1）由于竞争对手占据了性状空间，目标物种向新的最佳营养获取的适应性进化减慢;（2）浮游植物群落功能是由种内和种间与营养吸收相关的性状多样性的生态进化动力学共同决定的，并取决于每个物种所占据的生态位空间的范围。我们计划的实验将支持预测营养相关的性状为基础的建模和营养吸收相关的基因表达的调查。

Marine phytoplankton communities are largely regulated by nutrient regime. Both nutrient concentration and stoichiometry select for nutrient uptake-related traits such as maximum uptake rate (Vmax) and the half saturation constant (Kn). Jointly these traits and associated trade-offs determine phytoplankton ecological niche, competitive ability and ultimately the conversion of dissolved nutrients into phytoplankton primary production as one major component of ecosystem functioning. The role of standing intra- and interspecific variability of nutrient uptake-related traits and trade-offs as predictors for adaptive eco-evolutionary dynamics remains to be understood, and equally unknown are consequences for realized primary production under different nutrient regimes. Here we target two major phytoplankton groups differing in fundamental ways to acquire nutrients, affinity vs. velocity-adapted for both nitrate and phosphate, exemplified by a diatom and a coccolithophore species. We follow eco-evolutionary dynamics over time as a function of nutrient regime and diversity, and study the consequences for phytoplankton community functioning. This is particularly important in the light of increasing nutrient limitation owing to enhanced water column stratification in many oceanic regions. In this project, we span experimental eco-evolution, molecular approaches and predictive modelling to test the following hypotheses: (1) adaptive evolution towards new optimal nutrient acquisition in the target species is slowed down due to pre-occupied trait space by a competitor; (2) phytoplankton community functioning is jointly determined by eco-evolutionary dynamics of nutrient uptake-related trait diversity within- and among species, and depend on the range of occupied niche space by each species. Our planned experiments will be supported by predictive nutrient-related trait-based modeling and by investigations of nutrient uptake-related gene expression.