Quantifying the contribution of climate change and human activities to biophysical parameters in an arid region

Quantifying the variation of biophysical parameters and their driving mechanisms is essential for monitoring land surface environmental changes and for understanding the land–atmosphere interaction in the arid region. Due to the complexity of human activities, most researches are limited to climate...

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Autores principales:	Wenqiang Zhang, Geping Luo, Chunbo Chen, Friday U. Ochege, Olaf Hellwich, Hongwei Zheng, Rafiq Hamdi, Shixin Wu
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Climate change Human activities Biophysical parameters The Northern slope of the Tianshan Mountains Random Forest model Machine learning Ecology QH540-549.5
Acceso en línea:	https://doaj.org/article/9bc65210b6c7437d8d0ca41626b506b2
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spelling	oai:doaj.org-article:9bc65210b6c7437d8d0ca41626b506b22021-12-01T04:57:37ZQuantifying the contribution of climate change and human activities to biophysical parameters in an arid region1470-160X10.1016/j.ecolind.2021.107996https://doaj.org/article/9bc65210b6c7437d8d0ca41626b506b22021-10-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1470160X21006610https://doaj.org/toc/1470-160XQuantifying the variation of biophysical parameters and their driving mechanisms is essential for monitoring land surface environmental changes and for understanding the land–atmosphere interaction in the arid region. Due to the complexity of human activities, most researches are limited to climate change, whereas the response analysis of human activities to changes in biophysical parameters are still lacking or not comprehensively considered. Therefore, large biases and uncertainties still exist in the estimates of regional responses to global change. Firstly, we specifically quantified the main human activities related to land use/land cover change (LULCC) in the northern Tianshan Mountains (NTM), and identified the spatiotemporal changes of primary biophysical parameters, including Albedo, leaf area index (LAI), land surface temperature (LST), and Normalized Difference Vegetation Index (NDVI). Then, we tested the performance of the five models used, including multiple linear regression (MLR), random forest (RF), support vector regression (SVR), multi-layer perceptron (MLP), and K-nearest neighbor (KNN). RF outperformed others and was used to quantify and disaggregate the contribution of climate change and human activities to land surface parameters in the NTM. We found a strong spatial heterogeneity in the spatial variation of all biophysical parameters. Except for LST, the annual maximum Albedo, LAI, and NDVI showed a significant increasing trend in the NTM from 2000 to 2019 (p < 0.05). Generally, climate change contributed more to the biophysical parameters than human activities. However, the contribution of human activities to NDVI was 0.51, which was greater than that of climate change during 2000–2015. This study provides new insight on the impact of climate change and human activities on biophysical parameters and a scientific basis for model parameterization in the arid region.Wenqiang ZhangGeping LuoChunbo ChenFriday U. OchegeOlaf HellwichHongwei ZhengRafiq HamdiShixin WuElsevierarticleClimate changeHuman activitiesBiophysical parametersThe Northern slope of the Tianshan MountainsRandom Forest modelMachine learningEcologyQH540-549.5ENEcological Indicators, Vol 129, Iss , Pp 107996- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Climate change Human activities Biophysical parameters The Northern slope of the Tianshan Mountains Random Forest model Machine learning Ecology QH540-549.5
spellingShingle	Climate change Human activities Biophysical parameters The Northern slope of the Tianshan Mountains Random Forest model Machine learning Ecology QH540-549.5 Wenqiang Zhang Geping Luo Chunbo Chen Friday U. Ochege Olaf Hellwich Hongwei Zheng Rafiq Hamdi Shixin Wu Quantifying the contribution of climate change and human activities to biophysical parameters in an arid region
description	Quantifying the variation of biophysical parameters and their driving mechanisms is essential for monitoring land surface environmental changes and for understanding the land–atmosphere interaction in the arid region. Due to the complexity of human activities, most researches are limited to climate change, whereas the response analysis of human activities to changes in biophysical parameters are still lacking or not comprehensively considered. Therefore, large biases and uncertainties still exist in the estimates of regional responses to global change. Firstly, we specifically quantified the main human activities related to land use/land cover change (LULCC) in the northern Tianshan Mountains (NTM), and identified the spatiotemporal changes of primary biophysical parameters, including Albedo, leaf area index (LAI), land surface temperature (LST), and Normalized Difference Vegetation Index (NDVI). Then, we tested the performance of the five models used, including multiple linear regression (MLR), random forest (RF), support vector regression (SVR), multi-layer perceptron (MLP), and K-nearest neighbor (KNN). RF outperformed others and was used to quantify and disaggregate the contribution of climate change and human activities to land surface parameters in the NTM. We found a strong spatial heterogeneity in the spatial variation of all biophysical parameters. Except for LST, the annual maximum Albedo, LAI, and NDVI showed a significant increasing trend in the NTM from 2000 to 2019 (p < 0.05). Generally, climate change contributed more to the biophysical parameters than human activities. However, the contribution of human activities to NDVI was 0.51, which was greater than that of climate change during 2000–2015. This study provides new insight on the impact of climate change and human activities on biophysical parameters and a scientific basis for model parameterization in the arid region.
format	article
author	Wenqiang Zhang Geping Luo Chunbo Chen Friday U. Ochege Olaf Hellwich Hongwei Zheng Rafiq Hamdi Shixin Wu
author_facet	Wenqiang Zhang Geping Luo Chunbo Chen Friday U. Ochege Olaf Hellwich Hongwei Zheng Rafiq Hamdi Shixin Wu
author_sort	Wenqiang Zhang
title	Quantifying the contribution of climate change and human activities to biophysical parameters in an arid region
title_short	Quantifying the contribution of climate change and human activities to biophysical parameters in an arid region
title_full	Quantifying the contribution of climate change and human activities to biophysical parameters in an arid region
title_fullStr	Quantifying the contribution of climate change and human activities to biophysical parameters in an arid region
title_full_unstemmed	Quantifying the contribution of climate change and human activities to biophysical parameters in an arid region
title_sort	quantifying the contribution of climate change and human activities to biophysical parameters in an arid region
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/9bc65210b6c7437d8d0ca41626b506b2
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Quantifying the contribution of climate change and human activities to biophysical parameters in an arid region

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