文献类型：期刊文献

英文题名：Elm Tree (U. Pumila.) Sap Flux Prediction by Tower Sif in a Temperate Savanna

作者：Cong, Weiwei[1] Yang, Kaijie[2] Lu, Sen[3] Zhao, Tianhong[1] Wang, Feng[2] Lu, Qi[2]

第一作者：Cong, Weiwei

机构：[1] College of Agronomy, Shenyang Agricultural University, Shenyang, 110161, China; [2] Institute of Ecological Conservation and Restoration, Chinese Academy of Forestry, Beijing, 100091, China; [3] Key Laboratory of Tree Breeding and Cultivation of State Forestry Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing, 100091, China

年份：2024

外文期刊名：SSRN

收录：EI(收录号：20240177643)

语种：英文

外文关键词：Atmospheric temperature - Climate change - Ecosystems - Forestry - Hydraulics - Learning algorithms - Machine learning - Soil moisture

摘要：Accurate tracking Savanna woody plants hydraulics is the key step to understand its response to climate change and human management. Great inaccuracy existed in estimating vegetation hydraulics of Savanna ecosystem. Solar-induced fluorescence (SIF) has shown the potential to predict vegetation transpiration but the possibility of using it in vegetation hydraulics estimation of Savanna is not clear. Based on three years tower observed far-red SIF and ground sap flow monitoring in a temperate savanna of Otindag sandy land, China, we explore the relationship between far-red SIF and sap flux density and build up a SIF based random forest model for sap flux density estimation. Our results showed that SIF was linear related to sap flux density for elm (Ulmus pumila var. sabulosa) tree markedly at daily (R2=0.62-0.68, p ? 2024, The Authors. All rights reserved.