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。养分浓度和化学计量学选择了养分吸收相关的性状，如最大吸收率（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，并最终将溶解的营养物质转化为浮游植物的初级生产，作为生态系统功能的一个主要组成部分。与养分吸收相关的性状和权衡的种内和种间变异作为适应性生态进化动态的预测因素的作用仍有待了解，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，我们的目标是两个主要的浮游植物群，它们在获取营养的基本方式上不同，亲和力和速度都适应硝酸盐和磷酸盐，以硅藻和颗石藻为例。随着时间的推移，我们遵循生态进化动态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。这一点尤其重要，因为在许多海洋区域，由于水柱分层加强，营养物日益受到限制。在本项目中，我们跨越实验生态进化，分子方法和预测建模来验证以下假设：(1)由于竞争对手占据性状空间，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物种内和物种间与养分吸收相关的性状多样性的生态进化动态共同决定的，并取决于每个物种所占据的生态位空间范围。我们计划的实验将通过预测营养相关性状的建模和营养摄取相关基因表达的研究来支持。

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.