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DOI | 10.1016/j.foreco.2020.117986 |
Long-term effects of harvest on boreal forest soils in relation to a remote sensing-based soil moisture index | |
Sewell P.D.; Quideau S.A.; Dyck M.; Macdonald E. | |
发表日期 | 2020 |
ISSN | 0378-1127 |
卷号 | 462 |
英文摘要 | Storing a significant portion of the global carbon (C) stocks, soils of the boreal forest display a high degree of spatial heterogeneity across the landscape, arising from variation in forest structure and landscape morphology, as well as natural and anthropogenic disturbances. Because of this high degree of variability, accurately quantifying C storage in this ecosystem poses a challenge. Forestry is an important feature of Canada's natural resource-based economy, but there is still considerable uncertainty on how management practices will affect boreal soil C sequestration in the long-term. With increasing pressures due to a changing climate and intensified forest management, developing better tools and techniques to quantify soil C dynamics is of paramount importance. In this study, we measured soil C stocks and associated properties in the forest floors and mineral soils (0–7 cm) of conifer-dominated and deciduous (broadleaf)-dominated boreal forest stands, 17 years following variable retention harvest. We investigated if the Wet Areas Mapping-based depth-to-water (DTW) index, derived from remotely sensed Light Detection and Ranging (LiDAR) data, was related to soil properties of unharvested stands. In addition, relationships between harvest-induced changes in soil properties and the DTW index were examined. In unharvested stands, several forest floor properties were related to DTW. However, these relationships were stand-specific. In unharvested conifer-dominated stands, forest floor C stocks were positively related to site wetness, while in harvested stands there was no relationship; this suggests that C was differentially lost from wetter sites following harvesting. Conversely, in unharvested deciduous-dominated stands, there was no relationship between forest floor C stocks and site wetness, but in harvested stands, wetter sites had higher C stocks. The DTW index was more strongly related to soil properties in the mineral soil (0–7 cm) than in the forest floor. In both forest cover types, mineral soil C and N concentrations, and C stocks, increased with increasing wetness. Relationships between mineral soil properties and DTW were not stand-specific, and were of similar magnitude under deciduous-dominated and conifer-dominated cover. In addition, harvest and forest regeneration had limited impact on the relationships between DTW and mineral soil properties. This study highlights the potential of using remote sensing and the DTW index to model forest floor and mineral soil properties in the boreal forest. In turn, this approach may be utilized in effective forest management strategies that aim to conserve boreal C stocks. © 2020 |
关键词 | Digital storageFloorsHarvestingMineralsOptical radarRemote sensingSoil moistureBoreal mixedwoodsDepth-to-waterSoil carbonSoil responseTree species effectsVariable retentionsReforestationanthropogenic effectboreal forestcarbon sequestrationconiferous forestdeciduous forestecosystem modelingforest floorforest soilforestryheterogeneityindex methodlidarlong-term changemanagement practiceremote sensingsoil carbonsoil moisturestand structuretimber harvestingFloorsForest ManagementHarvestingMineralsMoisture ContentReforestationRemote SensingSoilCanadaConiferophyta |
语种 | 英语 |
来源机构 | Forest Ecology and Management |
文献类型 | 期刊论文 |
条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/132934 |
推荐引用方式 GB/T 7714 | Sewell P.D.,Quideau S.A.,Dyck M.,et al. Long-term effects of harvest on boreal forest soils in relation to a remote sensing-based soil moisture index[J]. Forest Ecology and Management,2020,462. |
APA | Sewell P.D.,Quideau S.A.,Dyck M.,&Macdonald E..(2020).Long-term effects of harvest on boreal forest soils in relation to a remote sensing-based soil moisture index.,462. |
MLA | Sewell P.D.,et al."Long-term effects of harvest on boreal forest soils in relation to a remote sensing-based soil moisture index".462(2020). |
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