Assessment of above ground biomass and soil organic carbon in the forests of Nepal under climate change scenario

IF 2.7 3区 农林科学 Q2 ECOLOGY
Rajesh Malla, P. R. Neupane, Michael Köhl
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Abstract

Many factors, such as climate, topography, forest management, or tree/forest attributes, influence soil organic carbon (SOC) and above-ground tree biomass (AGTB). This study focuses on assessing relationship between various predictor variables and response variables (SOC and AGTB) in the perspective of climate change scenario. The study was conducted throughout in Nepal using forest resource assessment data (2010–2014).Our study applied a random forest model to assess the status of SOC and AGTB under future climate change scenarios using 19 bioclimatic variables accompanied by other variables such as altitude, aspect, basal area, crown cover development status, distance to settlement forest types, number of trees, macro-topography, management regime, physiographic zones, slope, and soil depth. The study used 737 (70%) samples as a training data for model development while 312 (30%) samples as a testing data for model validation.The respective RMSE, RMSE% and adjusted R2 of the Random Forest Model for SOC estimation were found to be 9.53 ton/ha, 15% and 0.746 while same for the AGTB were 37.55 ton/ha, 21.74% and 0.743. Particularly, changes in temperature and precipitation showed an effect on the amount of SOC and AGTB in the projected scenario i.e., CMIP6, SSP2 4.5 for 2040–2060. The study found the amount of SOC decreased by 3.85%, while AGTB increased by 2.96% in the projected scenario. The proposed approach which incorporates the effect of bioclimatic variables can be a better option for understanding the dynamics of SOC and AGTB in the future using climatic variables.
气候变化情景下尼泊尔森林地上生物量和土壤有机碳的评估
许多因素,如气候、地形、森林管理或树木/森林属性,影响土壤有机碳(SOC)和地上树木生物量(AGTB)。本研究重点评估了气候变化情景下各预测变量与响应变量(SOC和AGTB)之间的关系。该研究利用森林资源评估数据(2010-2014年)在尼泊尔全境开展。基于19个生物气候变量,结合海拔、坡向、基底面积、冠层发育状况、与聚落森林类型的距离、树木数量、宏观地形、管理制度、地理区划、坡度和土壤深度等变量,采用随机森林模型评估了未来气候变化情景下森林有机碳和AGTB的状况。本研究使用737个(70%)样本作为模型开发的训练数据,312个(30%)样本作为模型验证的测试数据。随机森林模型估算土壤有机碳的RMSE、RMSE%和调整后R2分别为9.53 t /ha、15%和0.746,而AGTB的RMSE、RMSE%和调整后R2分别为37.55 t /ha、21.74%和0.743。特别是,温度和降水的变化对2040-2060年CMIP6、SSP2 4.5的预估情景中SOC和AGTB的数量有影响。研究发现,在预测情景下,SOC减少了3.85%,而AGTB增加了2.96%。该方法结合了生物气候变量的影响,可为今后利用气候变量了解有机碳和AGTB的动态提供更好的选择。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
4.50
自引率
6.20%
发文量
256
审稿时长
12 weeks
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