Abstract Climate is a major factor determining the distribution of plant species. Correlative models are frequently used to model the relationships between species distributions and climatic drivers but, increasingly, their use for prediction in novel scenarios such as climate change is being questioned. Mechanistic models, where processes limiting plant distribution are explicitly included, are regarded as preferable but more challenging. The availability of tools for simulating microclimates with high spatial and temporal definition has also opened new possibilities for simulating the limiting environmental stresses experienced by plants over their ontogeny. However, the field of mechanistic species distribution modelling is relatively new and the tools and theory for constructing these models are underdeveloped. In this paper we explore the potential for using a Dynamic Energy Budget model of organism growth integrated with microclimate and photosynthesis models. We model the interactions of plant growth and microclimatic stressors over the life stages of plant growth, and scale them up to demonstrate predictions of distribution at the continental scale. We develop the model using Julia, a new language for scientific computing, as a set of generic modelling packages. These have a modular, toolkit structure that has the potential to increase the efficiency and transparency of developing mechanistic SDMs.

中文翻译：

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整合动态植物生长模型和微气候以进行物种分布建模

摘要 气候是决定植物物种分布的主要因素。相关模型经常用于模拟物种分布和气候驱动因素之间的关系，但越来越多地，它们在气候变化等新情景中的预测用途受到质疑。机械模型，其中明确包括限制工厂分布的过程，被认为是可取的，但更具挑战性。用于模拟具有高时空定义的小气候的工具的可用性也为模拟植物在其个体发育过程中所经历的限制性环境压力开辟了新的可能性。然而，机械物种分布建模领域相对较新，构建这些模型的工具和理论还不发达。在本文中，我们探讨了使用与小气候和光合作用模型相结合的生物体生长动态能量预算模型的潜力。我们对植物生长和小气候压力因素在植物生长生命阶段的相互作用进行建模，并将它们按比例放大以证明对大陆尺度分布的预测。我们使用 Julia（一种用于科学计算的新语言）作为一组通用建模包来开发模型。它们具有模块化的工具包结构，有可能提高开发机械 SDM 的效率和透明度。并放大它们以证明对大陆尺度分布的预测。我们使用 Julia（一种用于科学计算的新语言）作为一组通用建模包来开发模型。它们具有模块化的工具包结构，有可能提高开发机械 SDM 的效率和透明度。并放大它们以证明对大陆尺度分布的预测。我们使用 Julia（一种用于科学计算的新语言）作为一组通用建模包来开发模型。它们具有模块化的工具包结构，有可能提高开发机械 SDM 的效率和透明度。