Spectrally defined plant functional types adequately capture multidimensional trait variation in herbaceous communities

Our ability to measure plant characteristics across space and time is crucial for understanding and tracking the diversity and functioning of ecosystems. Ecological approaches to synthesize these characteristics have evolved from allocating species to predefined conventional plant functional types (...

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Autores principales:	Elisa Van Cleemput, Kenny Helsen, Hannes Feilhauer, Olivier Honnay, Ben Somers
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Field spectroscopy Functional traits Plant functional types Optical types Herbaceous communities Partial least squares regression (PLSR) Ecology QH540-549.5
Acceso en línea:	https://doaj.org/article/827683fe8d474aad94bc95001eb7546c
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spelling	oai:doaj.org-article:827683fe8d474aad94bc95001eb7546c2021-12-01T04:31:13ZSpectrally defined plant functional types adequately capture multidimensional trait variation in herbaceous communities1470-160X10.1016/j.ecolind.2020.106970https://doaj.org/article/827683fe8d474aad94bc95001eb7546c2021-01-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1470160X20309092https://doaj.org/toc/1470-160XOur ability to measure plant characteristics across space and time is crucial for understanding and tracking the diversity and functioning of ecosystems. Ecological approaches to synthesize these characteristics have evolved from allocating species to predefined conventional plant functional types (cPFTs) to describing vegetation through delineating trait-based emergent plant functional types (ePFTs). At the same time, the remote sensing community has advanced in developing tools to measure functional traits, and defining plant optical types (POTs) from reflectance. However, the application of POTs is still underdeveloped and only few studies readily addressed the functional mechanisms underlying plant grouping. Especially at small ecological scales, relevant for studying community assembly processes and functional diversity, this is important because of scale-dependent sensitivity to drivers of trait variation. In this study, we therefore aimed to translate the ecological concept of ePFT delineation to spectrally measured data. We propose to cluster species based on traits estimated from reflectance (optical traits) to delineate emergent plant optical types (ePOTs). We conducted our study in herbaceous vegetation, where we examined four cPFT schemes, and measured the reflectance and six functional traits (four indicative of the leaf economics spectrum and two size-related) of 39 species across 11 sites (total of 73 site-specific species measurements). By means of PLSR models optical traits were retrieved with moderate to good accuracy (normalized RMSECV ranging between 4 and 22%, and R2CV ranging between 0.24 and 0.62). Subsequent agglomerative hierarchical clustering based on functional and optical traits resulted in 10 ePFTs and 9 ePOTs respectively, that well aligned (entanglement = 0.15). Whereas the four cPFT schemes poorly captured the multidimensional functional trait variation entailed in the dataset (R2 ranging between 0.05 and 0.43), the ePFTs and ePOTs much better represented functional trait (R2 = 0.70 and 0.52 respectively) and optical trait variation (R2 = 0.52 and 0.67 respectively). The presented ePOT delineation approach, combining spectrally measured data with standard ecological statistical approaches through optical traits, shows that spectral data can be used to delineate functional groups, while ensuring direct ecological interpretation. The method can easily be extended to different sets of traits to investigate specific responses and impacts of a plant community, and applied to larger spatial scales to study ecosystem functioning and biodiversity.Elisa Van CleemputKenny HelsenHannes FeilhauerOlivier HonnayBen SomersElsevierarticleField spectroscopyFunctional traitsPlant functional typesOptical typesHerbaceous communitiesPartial least squares regression (PLSR)EcologyQH540-549.5ENEcological Indicators, Vol 120, Iss , Pp 106970- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Field spectroscopy Functional traits Plant functional types Optical types Herbaceous communities Partial least squares regression (PLSR) Ecology QH540-549.5
spellingShingle	Field spectroscopy Functional traits Plant functional types Optical types Herbaceous communities Partial least squares regression (PLSR) Ecology QH540-549.5 Elisa Van Cleemput Kenny Helsen Hannes Feilhauer Olivier Honnay Ben Somers Spectrally defined plant functional types adequately capture multidimensional trait variation in herbaceous communities
description	Our ability to measure plant characteristics across space and time is crucial for understanding and tracking the diversity and functioning of ecosystems. Ecological approaches to synthesize these characteristics have evolved from allocating species to predefined conventional plant functional types (cPFTs) to describing vegetation through delineating trait-based emergent plant functional types (ePFTs). At the same time, the remote sensing community has advanced in developing tools to measure functional traits, and defining plant optical types (POTs) from reflectance. However, the application of POTs is still underdeveloped and only few studies readily addressed the functional mechanisms underlying plant grouping. Especially at small ecological scales, relevant for studying community assembly processes and functional diversity, this is important because of scale-dependent sensitivity to drivers of trait variation. In this study, we therefore aimed to translate the ecological concept of ePFT delineation to spectrally measured data. We propose to cluster species based on traits estimated from reflectance (optical traits) to delineate emergent plant optical types (ePOTs). We conducted our study in herbaceous vegetation, where we examined four cPFT schemes, and measured the reflectance and six functional traits (four indicative of the leaf economics spectrum and two size-related) of 39 species across 11 sites (total of 73 site-specific species measurements). By means of PLSR models optical traits were retrieved with moderate to good accuracy (normalized RMSECV ranging between 4 and 22%, and R2CV ranging between 0.24 and 0.62). Subsequent agglomerative hierarchical clustering based on functional and optical traits resulted in 10 ePFTs and 9 ePOTs respectively, that well aligned (entanglement = 0.15). Whereas the four cPFT schemes poorly captured the multidimensional functional trait variation entailed in the dataset (R2 ranging between 0.05 and 0.43), the ePFTs and ePOTs much better represented functional trait (R2 = 0.70 and 0.52 respectively) and optical trait variation (R2 = 0.52 and 0.67 respectively). The presented ePOT delineation approach, combining spectrally measured data with standard ecological statistical approaches through optical traits, shows that spectral data can be used to delineate functional groups, while ensuring direct ecological interpretation. The method can easily be extended to different sets of traits to investigate specific responses and impacts of a plant community, and applied to larger spatial scales to study ecosystem functioning and biodiversity.
format	article
author	Elisa Van Cleemput Kenny Helsen Hannes Feilhauer Olivier Honnay Ben Somers
author_facet	Elisa Van Cleemput Kenny Helsen Hannes Feilhauer Olivier Honnay Ben Somers
author_sort	Elisa Van Cleemput
title	Spectrally defined plant functional types adequately capture multidimensional trait variation in herbaceous communities
title_short	Spectrally defined plant functional types adequately capture multidimensional trait variation in herbaceous communities
title_full	Spectrally defined plant functional types adequately capture multidimensional trait variation in herbaceous communities
title_fullStr	Spectrally defined plant functional types adequately capture multidimensional trait variation in herbaceous communities
title_full_unstemmed	Spectrally defined plant functional types adequately capture multidimensional trait variation in herbaceous communities
title_sort	spectrally defined plant functional types adequately capture multidimensional trait variation in herbaceous communities
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/827683fe8d474aad94bc95001eb7546c
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Spectrally defined plant functional types adequately capture multidimensional trait variation in herbaceous communities

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