Fine-scale temperatures are important drivers of ecosystem functions and biodiversity in boreal forests. However, accounting for large thermal variability has been difficult due to the coarse spatiotemporal resolution of climate data that is commonly applied in studies of biodiversity and forest health. Here, we use a mechanistic microclimate model and geospatial environmental and weather data to reveal microclimate temperature variability in a broad macroclimatic gradient in boreal forest environments. We modelled hourly near-surface temperatures (0.15 m above ground) in May-August 2020 over three focus areas located in hemiboreal, southern boreal and northern boreal forest zone in Finland at a spatial resolution of 10 m x 10 m. A comparison against data from 150 microclimate stations showed reasonable agreement (root mean square error [RMSE] 2.9 °C) between the measured and modelled temperatures. RMSE for the three focus areas ranged 2.2 –3.2 °C, and the difference was found to be generally smaller under dense canopies compared to open areas. The modelling revealed substantial thermal variability over the landscapes; for example, seasonal near-surface temperature ranges varied 26.5 °C – 42.9 °C, with the variation being smallest in the hemiboreal landscape with multiple large waterbodies, and largest in southern boreal landscape with large wetland areas. These results demonstrate the great potential of mechanistic microclimate modelling to increase our understanding of the thermal characteristics of various boreal forest environments. Ultimately, high-resolution spatiotemporal microclimate data will permit better understanding of e.g., boreal species distribution under climate and land use change and fine-scale variability in disturbances, including insect pests and forest fires.

中文翻译：

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使用机械微气候模型揭示北方森林温度的精细变化

细尺度温度是北方森林生态系统功能和生物多样性的重要驱动因素。然而，由于生物多样性和森林健康研究中普遍应用的气候数据的粗略时空分辨率，解释大的温度变化一直很困难。在这里，我们使用机械微气候模型以及地理空间环境和天气数据来揭示北方森林环境中广泛的宏观气候梯度中的微气候温度变化。我们以 10 mx 10 m 的空间分辨率对芬兰半寒带、南部寒带和北部寒带森林区三个重点区域的 2020 年 5 月至 8 月每小时近地表温度（距地面 0.15 m）进行了建模。与 150 个小气候站的数据进行比较显示，测量温度和模拟温度之间具有合理的一致性（均方根误差 [RMSE] 2.9 °C）。三个重点区域的 RMSE 范围为 2.2 –3.2 °C，并且发现与开放区域相比，在密集的树冠下差异通常较小。模型揭示了景观中巨大的热变化；例如，季节性近地表温度范围为 26.5 °C – 42.9 °C，其中在具有多个大型水体的半寒带景观中变化最小，在具有大片湿地区域的南寒带景观中变化最大。这些结果证明了机械微气候建模在增进我们对各种北方森林环境热特性的理解方面的巨大潜力。最终，高分辨率时空微气候数据将有助于更好地了解气候和土地利用变化下的北方物种分布以及包括害虫和森林火灾在内的干扰的精细尺度变化。