Harnessing terrestrial laser scanning to predict understory biomass in temperate mixed forests

Forest understory vegetation plays an important role in providing food, nutrition and habitat for wildlife. The impact of wildlife foraging on forest understory biomass are often subtle processes that are difficult to capture using traditional field measurements. Field measurements are labor-intensi...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Shun Li, Tianming Wang, Zhengyang Hou, Yinan Gong, Limin Feng, Jianping Ge
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Terrestrial Laser Scanning (TLS) Forest understory Biomass mapping Herbivory Conservation management Ecology QH540-549.5
Acceso en línea:	https://doaj.org/article/6825a48173be430492a86b268ce739a9
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:6825a48173be430492a86b268ce739a9
record_format	dspace
spelling	oai:doaj.org-article:6825a48173be430492a86b268ce739a92021-12-01T04:32:23ZHarnessing terrestrial laser scanning to predict understory biomass in temperate mixed forests1470-160X10.1016/j.ecolind.2020.107011https://doaj.org/article/6825a48173be430492a86b268ce739a92021-02-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1470160X2030950Xhttps://doaj.org/toc/1470-160XForest understory vegetation plays an important role in providing food, nutrition and habitat for wildlife. The impact of wildlife foraging on forest understory biomass are often subtle processes that are difficult to capture using traditional field measurements. Field measurements are labor-intensive and impractical to cover and detect understory biomass changes at an extensive range with fine spatial resolution, thereby affecting the accuracy of habitat quality and food availability assessment for wildlife. Terrestrial Laser Scanning (TLS) is considered to have potential to improve the accuracy of understory biomass prediction, allowing for detailed monitoring of biomass changes under the influence of wildlife at fine scale. In this study, we first developed an efficient method to predict forest understory biomass by using variables from TLS with regression models, and second, we compared the prediction accuracy between TLS-based variables and field-measured variables. Third, the optimal models with TLS-based variables were applied to map and quantify the effect of herbivores density on understory biomass in temperate forests in northeastern China. Our results demonstrated that TLS-derived data were more accurate than field measurements in predicting understory biomass, that TLS-derived canopy cover yielded the highest herb layer biomass estimation accuracy (R2 = 0.72, RMSE = 12.73 g/m2), and that TLS-derived vegetation volume obtained the highest accuracy assessment for the shrub layer biomass prediction (R2 = 0.69, RMSE = 43.64 g/m2). There was a significant difference in the understory herb layer biomass in different deer-density plots, but no significant difference in shrub layer biomass. To quantify biomass changes in different plots, consistent monitoring method is needed, TLS data demonstrated the potential to capture and accurately quantify the biomass variation from forest understory. As tool for monitoring understory, TLS can be used as a supplementary to traditional understory monitoring methods to guide forest management policies and wildlife conservation strategies.Shun LiTianming WangZhengyang HouYinan GongLimin FengJianping GeElsevierarticleTerrestrial Laser Scanning (TLS)Forest understoryBiomass mappingHerbivoryConservation managementEcologyQH540-549.5ENEcological Indicators, Vol 121, Iss , Pp 107011- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Terrestrial Laser Scanning (TLS) Forest understory Biomass mapping Herbivory Conservation management Ecology QH540-549.5
spellingShingle	Terrestrial Laser Scanning (TLS) Forest understory Biomass mapping Herbivory Conservation management Ecology QH540-549.5 Shun Li Tianming Wang Zhengyang Hou Yinan Gong Limin Feng Jianping Ge Harnessing terrestrial laser scanning to predict understory biomass in temperate mixed forests
description	Forest understory vegetation plays an important role in providing food, nutrition and habitat for wildlife. The impact of wildlife foraging on forest understory biomass are often subtle processes that are difficult to capture using traditional field measurements. Field measurements are labor-intensive and impractical to cover and detect understory biomass changes at an extensive range with fine spatial resolution, thereby affecting the accuracy of habitat quality and food availability assessment for wildlife. Terrestrial Laser Scanning (TLS) is considered to have potential to improve the accuracy of understory biomass prediction, allowing for detailed monitoring of biomass changes under the influence of wildlife at fine scale. In this study, we first developed an efficient method to predict forest understory biomass by using variables from TLS with regression models, and second, we compared the prediction accuracy between TLS-based variables and field-measured variables. Third, the optimal models with TLS-based variables were applied to map and quantify the effect of herbivores density on understory biomass in temperate forests in northeastern China. Our results demonstrated that TLS-derived data were more accurate than field measurements in predicting understory biomass, that TLS-derived canopy cover yielded the highest herb layer biomass estimation accuracy (R2 = 0.72, RMSE = 12.73 g/m2), and that TLS-derived vegetation volume obtained the highest accuracy assessment for the shrub layer biomass prediction (R2 = 0.69, RMSE = 43.64 g/m2). There was a significant difference in the understory herb layer biomass in different deer-density plots, but no significant difference in shrub layer biomass. To quantify biomass changes in different plots, consistent monitoring method is needed, TLS data demonstrated the potential to capture and accurately quantify the biomass variation from forest understory. As tool for monitoring understory, TLS can be used as a supplementary to traditional understory monitoring methods to guide forest management policies and wildlife conservation strategies.
format	article
author	Shun Li Tianming Wang Zhengyang Hou Yinan Gong Limin Feng Jianping Ge
author_facet	Shun Li Tianming Wang Zhengyang Hou Yinan Gong Limin Feng Jianping Ge
author_sort	Shun Li
title	Harnessing terrestrial laser scanning to predict understory biomass in temperate mixed forests
title_short	Harnessing terrestrial laser scanning to predict understory biomass in temperate mixed forests
title_full	Harnessing terrestrial laser scanning to predict understory biomass in temperate mixed forests
title_fullStr	Harnessing terrestrial laser scanning to predict understory biomass in temperate mixed forests
title_full_unstemmed	Harnessing terrestrial laser scanning to predict understory biomass in temperate mixed forests
title_sort	harnessing terrestrial laser scanning to predict understory biomass in temperate mixed forests
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/6825a48173be430492a86b268ce739a9
work_keys_str_mv	AT shunli harnessingterrestriallaserscanningtopredictunderstorybiomassintemperatemixedforests AT tianmingwang harnessingterrestriallaserscanningtopredictunderstorybiomassintemperatemixedforests AT zhengyanghou harnessingterrestriallaserscanningtopredictunderstorybiomassintemperatemixedforests AT yinangong harnessingterrestriallaserscanningtopredictunderstorybiomassintemperatemixedforests AT liminfeng harnessingterrestriallaserscanningtopredictunderstorybiomassintemperatemixedforests AT jianpingge harnessingterrestriallaserscanningtopredictunderstorybiomassintemperatemixedforests
_version_	1718405847252467712

Harnessing terrestrial laser scanning to predict understory biomass in temperate mixed forests

Ejemplares similares