Beaver Jason, Curasi Salvatore R, Melton Joe R, Humphreys Elyn R, Hermosilla Txomin, Wulder Michael A
Department of Geography & Environmental Studies, Carleton University, Ottawa, ON, Canada.
National Wildlife Research Centre, Environment and Climate Change Canada, Ottawa, ON, Canada.
Sci Data. 2025 Aug 22;12(1):1469. doi: 10.1038/s41597-025-05123-4.
Spatially explicit fire and harvest data are useful for driving land surface model (LSM) simulations of the carbon cycle. From 1985-present, numerous Canadian disturbance datasets exist. However, before the launch of Landsat-4 (1984), few are available. We create spatially explicit LSM disturbance drivers for Canada for 1740-2018. We catalog and harmonize spatial and aspatial datasets and develop a novel algorithm that reconstructs disturbance far back in time using stand age. Based on possible historical scenarios, we reconstruct 283-394 Mha of fire and 3.42 Mha of harvest in total Canada-wide from 1740-1918. After 1918, when spatial records are available, we supplement them by reconstructing 25.79-60.30 Mha of fire and 24.75 Mha of harvest. After 1984, we exclusively use spatially explicit records. We verify the algorithm by comparing the inputs and resultant drivers and examine diagnostic metrics to disentangle the contribution of spatial, aspatial, and stand-age data. The resulting drivers primarily capture stand-replacing disturbance on forested land. Our forcings and algorithm will improve the representation of disturbance-mediated impacts on Canada's terrestrial carbon cycle and possibly in other regions.
空间明确的火灾和采伐数据有助于驱动陆地表面模型（LSM）对碳循环的模拟。从1985年至今，加拿大有大量的干扰数据集。然而，在陆地卫星4号（1984年）发射之前，可用的数据很少。我们创建了1740 - 2018年加拿大空间明确的LSM干扰驱动因素。我们对空间和非空间数据集进行编目和协调，并开发了一种新颖的算法，该算法利用林分年龄重建过去很长时间的干扰。基于可能的历史情景，我们在全加拿大范围内重建了1740 - 1918年总计283 - 394百万公顷的火灾面积和342万公顷的采伐面积。1918年之后，当有空间记录时，我们通过重建25.79 - 60.30百万公顷的火灾面积和2475万公顷的采伐面积来补充这些记录。1984年之后，我们专门使用空间明确的记录。我们通过比较输入数据和最终的驱动因素来验证算法，并检查诊断指标以区分空间、非空间和林分年龄数据的贡献。所得的驱动因素主要捕捉森林土地上的林分更替干扰。我们的强迫数据和算法将改善对干扰介导的对加拿大陆地碳循环以及可能对其他地区影响的表征。
