Institute of Cold Regions Science and Engineering, Northeast Forestry University, Harbin, China.
Ministry of Education Observation and Research Station of Permafrost Geo-Environment System in Northeast China, Harbin, China.
PLoS One. 2024 Feb 16;19(2):e0297029. doi: 10.1371/journal.pone.0297029. eCollection 2024.
Affected by global warming, the permafrost in Northeast China (NEC) has been continuously degrading in recent years. Many researchers have focused on the spatial and temporal distribution characteristics of permafrost in NEC, however, few studies have delved into the field scale. In this study, based on the Optimal Parameters-based Geographical Detector (OPGD) model and Receiver Operating Characteristic (ROC) test, the spatial stratified heterogeneity of permafrost distribution and the indicating performance of environmental variables on permafrost in NEC at the field scale were analyzed. Permafrost spatial distribution data were obtained from the Engineering Geological Investigation Reports (EGIR) of six highways located in NEC and a total of 19 environmental variables related to heat transfer, vegetation, soil, topography, moisture, and ecology were selected. The H-factors (variables with the highest contribution in factor detector results and interaction detector results): slope position (γ), surface frost number (SFN), elevation (DEM), topographic diversity (TD), and annual snow cover days (ASCD) were found to be the major contributors to the distribution of permafrost at the field scale. Among them, γ has the highest contribution and is a special explanatory variable for permafrost. In most cases, interaction can improve the impact of variables, especially the interaction between H-factors. The risk of permafrost decreases with the increase of TD, RN, and SBD, and increases with the increase of SFN. The performance of SFN to indicate permafrost distribution was found to be the best among all variables (AUC = 0.7063). There is spatial heterogeneity in the distribution of permafrost on highways in different spatial locations. This study summarized the numerical and spatial location between permafrost and different environmental variables at the field scale, and many results were found to be informative for environmental studies and engineering construction in NEC.
受全球变暖影响,近年来中国东北(Northeast China,NEC)多年冻土持续退化。许多研究人员关注东北多年冻土的时空分布特征,但很少有研究深入到场域尺度。本研究基于最优参数地理探测器(Optimal Parameters-based Geographical Detector,OPGD)模型和接收者操作特征(Receiver Operating Characteristic,ROC)检验,分析了东北多年冻土分布的空间分层异质性及环境变量在场域尺度上对多年冻土的指示性能。多年冻土空间分布数据来自位于东北的六条公路的工程地质调查报告(Engineering Geological Investigation Reports,EGIR),共选取了 19 个与热传递、植被、土壤、地形、水分和生态相关的环境变量。H 因子(在因子探测器结果和交互探测器结果中贡献最高的变量):坡度位置(γ)、地表霜数(SFN)、海拔(DEM)、地形多样性(TD)和年积雪覆盖天数(ASCD)被发现是场域尺度多年冻土分布的主要影响因素。其中,γ 的贡献最大,是多年冻土的特殊解释变量。在大多数情况下,交互作用可以提高变量的影响,特别是 H 因子之间的交互作用。多年冻土的风险随着 TD、RN 和 SBD 的增加而降低,随着 SFN 的增加而增加。SFN 对指示多年冻土分布的性能在所有变量中表现最好(AUC=0.7063)。不同空间位置的公路上多年冻土的分布存在空间异质性。本研究总结了场域尺度上多年冻土与不同环境变量之间的数值和空间位置关系,许多结果对东北的环境研究和工程建设具有信息价值。