Logistic model outperforms allometric regression to estimate biomass of xerophytic shrubs

Allometric model has been applied worldwide to estimate vegetation biomass for decades. However, this model fails to restrict the accelerating increase of biomass as body size grows. That contradicts to the size-related resource limits and intra-specific competitions. Thus, we tested logistic model...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Jiemin Ma, Chuan Yuan, Jiayu Zhou, Yan Li, Guangyao Gao, Bojie Fu
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Equilibrium biomass Growth rate Point of inflection Goodness-of-fit Representative sampling Ecology QH540-549.5
Acceso en línea:	https://doaj.org/article/49011894308e4ac8b3819527b3d22c69
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:49011894308e4ac8b3819527b3d22c69
record_format	dspace
spelling	oai:doaj.org-article:49011894308e4ac8b3819527b3d22c692021-12-01T05:01:49ZLogistic model outperforms allometric regression to estimate biomass of xerophytic shrubs1470-160X10.1016/j.ecolind.2021.108278https://doaj.org/article/49011894308e4ac8b3819527b3d22c692021-12-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1470160X21009432https://doaj.org/toc/1470-160XAllometric model has been applied worldwide to estimate vegetation biomass for decades. However, this model fails to restrict the accelerating increase of biomass as body size grows. That contradicts to the size-related resource limits and intra-specific competitions. Thus, we tested logistic model with limiting factor of the carrying capacity at the 30-year dominant shrub species in Loess Plateau of China, including Caragana korshinskii (51 branches), Salix psammophila (44 branches) and Vitex negundo (28 branches). Our results indicated that logistic model was statistically effective as allometric model indicated by the adjusted code of determination, p-value, Akaike’s Information Criterion and Root Mean Square Error. It was also of more ecological significances by providing the equilibrium growth rate, equilibrium biomass (the asymptotic biomass as branch grew), and point-of-inflections (thresholds for different trends of biomass increase). That had been double-checked with our measured biomass and the published data in previous studies. The unrepresentative samples with the tendency favoring the small- and middle-sized branches, and the consequently biased tendency and overfitting in models from random quirks of samples, might partly explain the repeated validation of allometric model for estimating biomass in previous studies. In general, logistic model outperformed allometric model to estimate shrub biomass of allometric scaling with body size. An appropriate model for biomass estimation benefited to precisely compute carbon sequencing and to assess climate change impact on ecosystems functioning.Jiemin MaChuan YuanJiayu ZhouYan LiGuangyao GaoBojie FuElsevierarticleEquilibrium biomassGrowth ratePoint of inflectionGoodness-of-fitRepresentative samplingEcologyQH540-549.5ENEcological Indicators, Vol 132, Iss , Pp 108278- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Equilibrium biomass Growth rate Point of inflection Goodness-of-fit Representative sampling Ecology QH540-549.5
spellingShingle	Equilibrium biomass Growth rate Point of inflection Goodness-of-fit Representative sampling Ecology QH540-549.5 Jiemin Ma Chuan Yuan Jiayu Zhou Yan Li Guangyao Gao Bojie Fu Logistic model outperforms allometric regression to estimate biomass of xerophytic shrubs
description	Allometric model has been applied worldwide to estimate vegetation biomass for decades. However, this model fails to restrict the accelerating increase of biomass as body size grows. That contradicts to the size-related resource limits and intra-specific competitions. Thus, we tested logistic model with limiting factor of the carrying capacity at the 30-year dominant shrub species in Loess Plateau of China, including Caragana korshinskii (51 branches), Salix psammophila (44 branches) and Vitex negundo (28 branches). Our results indicated that logistic model was statistically effective as allometric model indicated by the adjusted code of determination, p-value, Akaike’s Information Criterion and Root Mean Square Error. It was also of more ecological significances by providing the equilibrium growth rate, equilibrium biomass (the asymptotic biomass as branch grew), and point-of-inflections (thresholds for different trends of biomass increase). That had been double-checked with our measured biomass and the published data in previous studies. The unrepresentative samples with the tendency favoring the small- and middle-sized branches, and the consequently biased tendency and overfitting in models from random quirks of samples, might partly explain the repeated validation of allometric model for estimating biomass in previous studies. In general, logistic model outperformed allometric model to estimate shrub biomass of allometric scaling with body size. An appropriate model for biomass estimation benefited to precisely compute carbon sequencing and to assess climate change impact on ecosystems functioning.
format	article
author	Jiemin Ma Chuan Yuan Jiayu Zhou Yan Li Guangyao Gao Bojie Fu
author_facet	Jiemin Ma Chuan Yuan Jiayu Zhou Yan Li Guangyao Gao Bojie Fu
author_sort	Jiemin Ma
title	Logistic model outperforms allometric regression to estimate biomass of xerophytic shrubs
title_short	Logistic model outperforms allometric regression to estimate biomass of xerophytic shrubs
title_full	Logistic model outperforms allometric regression to estimate biomass of xerophytic shrubs
title_fullStr	Logistic model outperforms allometric regression to estimate biomass of xerophytic shrubs
title_full_unstemmed	Logistic model outperforms allometric regression to estimate biomass of xerophytic shrubs
title_sort	logistic model outperforms allometric regression to estimate biomass of xerophytic shrubs
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/49011894308e4ac8b3819527b3d22c69
work_keys_str_mv	AT jieminma logisticmodeloutperformsallometricregressiontoestimatebiomassofxerophyticshrubs AT chuanyuan logisticmodeloutperformsallometricregressiontoestimatebiomassofxerophyticshrubs AT jiayuzhou logisticmodeloutperformsallometricregressiontoestimatebiomassofxerophyticshrubs AT yanli logisticmodeloutperformsallometricregressiontoestimatebiomassofxerophyticshrubs AT guangyaogao logisticmodeloutperformsallometricregressiontoestimatebiomassofxerophyticshrubs AT bojiefu logisticmodeloutperformsallometricregressiontoestimatebiomassofxerophyticshrubs
_version_	1718405597381001216

Logistic model outperforms allometric regression to estimate biomass of xerophytic shrubs

Ejemplares similares