Abstract Aquaculture is an industry with the capacity for further growth that can contribute to sustainable food systems to feed an increasing global population. Sugar kelp (Saccharina latissima) is of particular interest for farmers as a fast-growing species that benefits ecosystems as a primary producer. However, as a new industry in the U.S., farmers interested in growing S. latissima lack data on growth dynamics. To address this gap, we calibrated a Dynamic Energy Budget (DEB) model to data from the literature and field-based growth experiments in Rhode Island (U.S.A.). Environmental variables forcing model dynamics include temperature, irradiance, dissolved inorganic carbon concentration, and nitrate and nitrite concentration. The modeled estimates for field S. latissima blade length were accurate despite underestimation of early season growth. In some simulations, winter growth was limited by the rate at which the light-dependent reaction of photosynthesis, the first step of carbon assimilation, was performed. Nitrogen (N) reserves were also an important limiting factor especially later in the spring season as irradiance increased, although the low resolution of N forcing concentrations might restrict the model accuracy. Since this model is focused on S. latissima grown in an aquaculture setting with winter and spring growth, no specific assumptions were made to include summer growth patterns such as tissue loss or reproduction. The results indicate that this mechanistic model for S. latissima captures growth dynamics and blade length at the time of harvest, thus it could be used for spatial predictions of S. latissima aquaculture production across a range of environmental conditions and locations. The model could be a particularly useful tool for further development of sustainable ocean food production systems involving seaweed.

中文翻译：

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使用动态能量收支理论模拟水产养殖系统中糖海带（Saccharina latissima）的生长

摘要 水产养殖是一个具有进一步增长能力的行业，可以促进可持续粮食系统以养活不断增长的全球人口。糖海带 (Saccharina latissima) 作为一种快速生长的物种，对作为初级生产者的生态系统有益，农民特别感兴趣。然而，作为美国的一个新兴产业，对种植 S. latissima 感兴趣的农民缺乏有关生长动态的数据。为了解决这一差距，我们根据来自罗德岛（美国）的文献和实地增长实验中的数据校准了动态能源预算 (DEB) 模型。强制模型动力学的环境变量包括温度、辐照度、溶解的无机碳浓度以及硝酸盐和亚硝酸盐浓度。字段 S 的建模估计值。尽管低估了早期的生长速度，但 latssima 叶片长度是准确的。在一些模拟中，冬季生长受到光合作用的光依赖反应（碳同化的第一步）的速度的限制。氮 (N) 储备也是一个重要的限制因素，尤其是在春季后期，随着辐照度的增加，尽管 N 强迫浓度的低分辨率可能会限制模型的准确性。由于该模型侧重于在冬季和春季生长的水产养殖环境中生长的 S. latissima，因此没有做出具体假设以包括夏季生长模式，例如组织损失或繁殖。结果表明，这种 S. latissima 的机械模型捕获了收获时的生长动态和叶片长度，因此，它可用于对一系列环境条件和地点的 S. latissima 水产养殖产量进行空间预测。该模型可以成为进一步发展涉及海藻的可持续海洋食品生产系统的特别有用的工具。