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基于机器学习的阿勒泰地区草地地下生物量估测与数字制图 被引量:4
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作者 厉方桢 钟华平 +2 位作者 欧阳克蕙 赵小敏 李愈哲 《草业学报》 CSCD 北大核心 2022年第8期13-23,共11页
为精准估算草地地下生物量,分析其水平及垂直空间格局,实现草地地下生物量(BGB)的数字制图。调查了2015年阿勒泰地区草地生长季节(6-8月)的生态要素和地下生物量。以地理位置、地形、气候、土壤和植被中的代表性信息为基础,基于机器学... 为精准估算草地地下生物量,分析其水平及垂直空间格局,实现草地地下生物量(BGB)的数字制图。调查了2015年阿勒泰地区草地生长季节(6-8月)的生态要素和地下生物量。以地理位置、地形、气候、土壤和植被中的代表性信息为基础,基于机器学习算法估测研究区0~30 cm的草地地下生物量,并根据估测结果利用空间插值法得到地下生物量的空间分布格局,最终实现草地地下生物量的数字制图。结果表明:1)相比偏最小二乘回归(PLS)和随机森林模型(RF),支持向量机模型(SVM)在0~10 cm、10~20 cm和20~30 cm土层地下生物量的估测中表现出最高的精度,验证集数据的精度(R2)依次为0.77、0.67和0.69,相应的RMSE为245.56、98.81和63.58 g·m^(-2)。从空间插值的效果看,反距离权重插值(IDW)优于径向基函数插值(RBF)和张力样条插值(SPL)。2)进一步比较了不同估测模型与空间插值方法间的组合能力,结果显示,在阿勒泰地区的草地地下生物量研究中,SVM+IDW是可靠的估测模型和空间化方法的组合。在0~10 cm、10~20 cm和20~30 cm土层的草地地下生物量数字制图的R2为0.73、0.64和0.60,RMSE为269.73、10^(8).14和73.01 g·m^(-2)。3)阿勒泰地区草地地下生物量均值为1265 g·m^(-2),是全国平均值的两倍,与全球平均水平相当。其中,高寒草甸的地下生物量最大,为2908.50 g·m^(-2),温性荒漠的地下生物量最小,为776.84 g·m^(-2),全区草地地下生物量共计1.27×10^(8) t(≈0.13 Pg)。全区草地地下生物量的空间变化明显,整体上自北向南,由山地向平原呈递减的趋势。 展开更多
关键词 草地地下生物量 阿勒泰地区 机器学习 空间插值 SVM模型 IDW插值 数字制图
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Leaf and root phenology and biomass of Eriophorum vaginatum in response to warming in the Arctic 被引量:2
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作者 Ting Ma Thomas Parker +4 位作者 Ned Fetcher Steven L.Ungers Jon Gewirtzman Michael L.Moody Jianwu Tang 《Journal of Plant Ecology》 SCIE CSCD 2022年第5期1091-1105,共15页
The response of plant leaf and root phenology and biomass in the Arctic to global change remains unclear due to the lack of synchronous measurements of above-and belowground parts.Our objective was to determine the ph... The response of plant leaf and root phenology and biomass in the Arctic to global change remains unclear due to the lack of synchronous measurements of above-and belowground parts.Our objective was to determine the phenological dynamics of the above-and belowground parts of Eriophorum vaginatum in the Arctic and its response to warming.We established a common garden located at Toolik Lake Field Station;tussocks of E.vaginatum from three locations,Coldfoot,Toolik Lake and Sagwon,were transplanted into the common garden.Control and warming treatments for E.vaginatum were set up at the Toolik Lake during the growing seasons of 2016 and 2017.Digital cameras,a handheld sensor and minirhizotrons were used to simultaneously observe leaf greenness,normalized difference vegetation index and root length dynamics,respectively.Leaf and root growth rates of E.vaginatum were asynchronous such that the timing of maximal leaf growth(mid-july)was about 28 days earlier than that of root growth.Warming of air temperature by 1°C delayed the timing of leaf senescence and thus prolonged the growing season,but the temperature increase had no significant effect on root phenology.The seasonal dynamics of leaf biomass were affected by air temperature,whereas root biomass was correlated with soil thaw depth.Therefore,we suggest that leaf and root components should be considered comprehensively when using carbon and nutrient cycle models,as above-and belowground productivity and functional traits may have a different response to climate warming. 展开更多
关键词 Eriophorum vaginatum PHENOLOGY WARMING aboveground biomass belowground biomass
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