Incubation dataset for DLNN model training and validating

Incubation experiment data used in 'Data-driven constraints on nutrient-controlled phytoplankton growth dynamics across varying oceanic regimes' to train and validate DLNN models of modeling the Chl a and μ variation patterns during the phytoplankton growth phases. Includes incubation data conducted in the Western Pacific from 2014 to 2017, as well as incubation data from global ocean collected in Browning & Moore (2023) (doi:10.1038/s41467-023-40774-0)本数据集为论文《不同海洋环境下营养盐调控浮游植物生长动态的数据驱动约束》（原英文标题：Data-driven constraints on nutrient-controlled phytoplankton growth dynamics across varying oceanic regimes）中所用的培养实验数据，用于训练并验证深度学习神经网络（Deep Learning Neural Network, DLNN）模型，以模拟浮游植物生长阶段的叶绿素a（Chlorophyll a, Chl a）与比生长速率（μ）的变化模式。数据集包含2014年至2017年在西太平洋开展的培养实验数据，以及取自Browning与Moore（2023）（DOI: 10.1038/s41467-023-40774-0）的全球海洋培养实验数据。