论文标题
浮游植物的时间策略增加了海洋食品网络模型中的熵产生
Phytoplankton temporal strategies increase entropy production in a marine food web model
论文作者
论文摘要
我们开发了一个基于性状的模型，该模型基于以下假设，即生物系统发展和组织以通过实施时间策略来比非生物过程相比，在更长的时间尺度上散发化学和电磁潜力来最大化熵产生。由浮游植物，细菌和消费官能团组成的海洋食品网被用来探索在浅池中的时间策略或缺乏的时间策略或缺乏的熵产生，从而接收有机碳的连续流动以及与Diel和季节性辐射和季节性和季节性和季节性动力学的无机氮的连续流动。结果表明，采用显式昼夜节律时钟的时间策略比使用内部碳储存或平衡生长策略的被动策略要产生的熵更多，该策略需要浮游植物以固定的化学计量法生长。当社区被迫在2 D-1附近以高特异性增长率运行时，优化引导的模型选择了浮游植物生态型，这些生态型表现为冬季与夏季环境条件的补充，以增加熵产生。我们还提出了一种新型的基于性状的建模，其中特性值是通过最大化熵产生而不是随机选择来确定的。
We develop a trait-based model founded on the hypothesis that biological systems evolve and organize to maximize entropy production by dissipating chemical and electromagnetic potentials over longer time scales than abiotic processes by implementing temporal strategies. A marine food web consisting of phytoplankton, bacteria and consumer functional groups is used to explore how temporal strategies, or the lack there of, change entropy production in a shallow pond that receives a continuous flow of reduced organic carbon plus inorganic nitrogen and illumination from solar radiation with diel and seasonal dynamics. Results show that a temporal strategy that employs an explicit circadian clock produces more entropy than a passive strategy that uses internal carbon storage or a balanced growth strategy that requires phytoplankton to grow with fixed stoichiometry. When the community is forced to operate at high specific growth rates near 2 d-1, the optimization-guided model selects for phytoplankton ecotypes that exhibit complementary for winter versus summer environmental conditions to increase entropy production. We also present a new type of trait-based modeling where trait values are determined by maximizing entropy production rather than by random selection.
