在明确耕地细碎化(cultivated land fragmentation,CLF)会造成的消极和积极影响基础上,构建CLF评价体系,探索以因地制宜为理念差异化解决CLF现象的方法。以陕西省2020年耕地利用现状为例,从耕地的自然资源禀赋、空间聚集程度、利用便利...在明确耕地细碎化(cultivated land fragmentation,CLF)会造成的消极和积极影响基础上,构建CLF评价体系,探索以因地制宜为理念差异化解决CLF现象的方法。以陕西省2020年耕地利用现状为例,从耕地的自然资源禀赋、空间聚集程度、利用便利程度三个方面构建陕西省CLF程度三维魔方模型,对其CLF空间分异特征进行探索,并提出了改善CLF的策略。结果表明:陕西省CLF指数(CLFI)总体上呈现中间低、南北高的空间特征,CLFI最大值为0.796,最小值为0.020,均值为0.217,高值集中在陕南和关中交界的秦巴山区以及陕北东部地区。基于CLF特征和农业种植多样性、地区经济水平等影响因素以及耕地资源3个属性特征,提出了针对陕西省CLF的优化分区规划,其中包括保持提升区、集约归并区、设施优化区、资源改造区、综合提升区、综合整治区6类乡镇级引导分区,及以地区社会经济指标为基础划分的政策倾向区、加强整治区、资源倾向区、资源适配区4类县级引导分区,并结合两类分区结果的特征提出了不同地区土地整治的主要方向及关键问题。展开更多
大兴安岭林区土壤有机碳储量对于区域碳源汇变化及气候响应研究具有重要意义。本文基于土壤剖面数据,结合多种环境变量,采用随机森林(RF)模型,估计了大兴安岭卡马兰河流域0~30 cm深度的土壤有机碳储量(SOCS)及其空间分布特征。结果表明...大兴安岭林区土壤有机碳储量对于区域碳源汇变化及气候响应研究具有重要意义。本文基于土壤剖面数据,结合多种环境变量,采用随机森林(RF)模型,估计了大兴安岭卡马兰河流域0~30 cm深度的土壤有机碳储量(SOCS)及其空间分布特征。结果表明:RF模型(R2 = 0.75, RMSE = 6.81)对小尺度区域的模拟细节表现较好,研究区0~30 cm的SOCS主要分布在地势相对平坦的河流沿岸,与河流走向基本保持一致。研究结果得出了相对精确的卡马兰河流域表层土壤有机碳储量及空间分布特征,该成果能够丰富大兴安岭多年冻土区土壤有机碳储量的认识,并为生态过程相关模拟研究提供数据支持。Soil organic carbon stocks in the forested areas of Great Khingan are of great significance for the study of regional carbon source and sink changes and climate response. In this paper, based on soil profile data and combining multiple environmental variables, we estimated the soil organic carbon stock (SOCS) and its spatial distribution characteristics at 0~30 cm depth in the Kamalan River watershed of Great Khingan by using the random forest (RF) model. The results showed that the RF model (R2 = 0.75, RMSE = 6.81) performed well in simulation details for small-scale areas, and the SOCS at 0~30 cm in the study area was mainly distributed along the river with relatively flat topography, which was basically consistent with the river course. The results of the study yielded a relatively accurate characterisation of the surface soil organic carbon stock and spatial distribution in the Kamalan River basin, which can enrich the understanding of soil organic carbon stock in the perennial permafrost region of the Great Khingan and provide data support for simulation studies related to ecological processes.展开更多
文摘在明确耕地细碎化(cultivated land fragmentation,CLF)会造成的消极和积极影响基础上,构建CLF评价体系,探索以因地制宜为理念差异化解决CLF现象的方法。以陕西省2020年耕地利用现状为例,从耕地的自然资源禀赋、空间聚集程度、利用便利程度三个方面构建陕西省CLF程度三维魔方模型,对其CLF空间分异特征进行探索,并提出了改善CLF的策略。结果表明:陕西省CLF指数(CLFI)总体上呈现中间低、南北高的空间特征,CLFI最大值为0.796,最小值为0.020,均值为0.217,高值集中在陕南和关中交界的秦巴山区以及陕北东部地区。基于CLF特征和农业种植多样性、地区经济水平等影响因素以及耕地资源3个属性特征,提出了针对陕西省CLF的优化分区规划,其中包括保持提升区、集约归并区、设施优化区、资源改造区、综合提升区、综合整治区6类乡镇级引导分区,及以地区社会经济指标为基础划分的政策倾向区、加强整治区、资源倾向区、资源适配区4类县级引导分区,并结合两类分区结果的特征提出了不同地区土地整治的主要方向及关键问题。
文摘大兴安岭林区土壤有机碳储量对于区域碳源汇变化及气候响应研究具有重要意义。本文基于土壤剖面数据,结合多种环境变量,采用随机森林(RF)模型,估计了大兴安岭卡马兰河流域0~30 cm深度的土壤有机碳储量(SOCS)及其空间分布特征。结果表明:RF模型(R2 = 0.75, RMSE = 6.81)对小尺度区域的模拟细节表现较好,研究区0~30 cm的SOCS主要分布在地势相对平坦的河流沿岸,与河流走向基本保持一致。研究结果得出了相对精确的卡马兰河流域表层土壤有机碳储量及空间分布特征,该成果能够丰富大兴安岭多年冻土区土壤有机碳储量的认识,并为生态过程相关模拟研究提供数据支持。Soil organic carbon stocks in the forested areas of Great Khingan are of great significance for the study of regional carbon source and sink changes and climate response. In this paper, based on soil profile data and combining multiple environmental variables, we estimated the soil organic carbon stock (SOCS) and its spatial distribution characteristics at 0~30 cm depth in the Kamalan River watershed of Great Khingan by using the random forest (RF) model. The results showed that the RF model (R2 = 0.75, RMSE = 6.81) performed well in simulation details for small-scale areas, and the SOCS at 0~30 cm in the study area was mainly distributed along the river with relatively flat topography, which was basically consistent with the river course. The results of the study yielded a relatively accurate characterisation of the surface soil organic carbon stock and spatial distribution in the Kamalan River basin, which can enrich the understanding of soil organic carbon stock in the perennial permafrost region of the Great Khingan and provide data support for simulation studies related to ecological processes.
