Leaf reflectance can surrogate foliar economics better than physiological traits across macrophyte species

Abstract Background Macrophytes are key players in aquatic ecosystems diversity, but knowledge on variability of their functional traits, among and within species, is still limited. Remote sensing is a high-throughput, feasible option for characterizing plant traits at different scales, provided tha...

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Autores principales:	Paolo Villa, Rossano Bolpagni, Monica Pinardi, Viktor R. Tóth
Formato:	article
Lenguaje:	EN
Publicado:	BMC 2021
Materias:	Aquatic plants Functional traits Intraspecific variability Leaf economics spectrum (LES) Remote sensing Spectroscopy Plant culture SB1-1110 Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/222e9b81eb6942158622a5212ae1fe13
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spelling	oai:doaj.org-article:222e9b81eb6942158622a5212ae1fe132021-11-14T12:11:15ZLeaf reflectance can surrogate foliar economics better than physiological traits across macrophyte species10.1186/s13007-021-00816-41746-4811https://doaj.org/article/222e9b81eb6942158622a5212ae1fe132021-11-01T00:00:00Zhttps://doi.org/10.1186/s13007-021-00816-4https://doaj.org/toc/1746-4811Abstract Background Macrophytes are key players in aquatic ecosystems diversity, but knowledge on variability of their functional traits, among and within species, is still limited. Remote sensing is a high-throughput, feasible option for characterizing plant traits at different scales, provided that reliable spectroscopy models are calibrated with congruous empirical data, but existing applications are biased towards terrestrial plants. We sampled leaves from six floating and emergent macrophyte species common in temperate areas, covering different phenological stages, seasons, and environmental conditions, and measured leaf reflectance (400–2500 nm) and leaf traits (dealing with photophysiology, pigments, and structure). We explored optimal spectral band combinations and established non-parametric reflectance-based models for selected traits, eventually showing how airborne hyperspectral data could capture spatial–temporal macrophyte variability. Results Our key finding is that structural—leaf dry matter content, leaf mass per area—and biochemical—chlorophyll-a content and chlorophylls to carotenoids ratio—traits can be surrogated by leaf reflectance with normalized error under 17% across macrophyte species. On the other hand, the performance of reflectance-based models for photophysiological traits substantively varies, depending on macrophyte species and target parameters. Conclusions Our main results show the link between leaf reflectance and leaf economics (structure and biochemistry) for aquatic plants, thus envisioning a crucial role for remote sensing in enhancing the level of detail of macrophyte functional diversity analysis to intra-site and intra-species scales. At the same time, we highlighted some difficulties in establishing a general link between reflectance and photosynthetic performance under high environmental heterogeneity, potentially opening further investigation directions.Paolo VillaRossano BolpagniMonica PinardiViktor R. TóthBMCarticleAquatic plantsFunctional traitsIntraspecific variabilityLeaf economics spectrum (LES)Remote sensingSpectroscopyPlant cultureSB1-1110Biology (General)QH301-705.5ENPlant Methods, Vol 17, Iss 1, Pp 1-16 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Aquatic plants Functional traits Intraspecific variability Leaf economics spectrum (LES) Remote sensing Spectroscopy Plant culture SB1-1110 Biology (General) QH301-705.5
spellingShingle	Aquatic plants Functional traits Intraspecific variability Leaf economics spectrum (LES) Remote sensing Spectroscopy Plant culture SB1-1110 Biology (General) QH301-705.5 Paolo Villa Rossano Bolpagni Monica Pinardi Viktor R. Tóth Leaf reflectance can surrogate foliar economics better than physiological traits across macrophyte species
description	Abstract Background Macrophytes are key players in aquatic ecosystems diversity, but knowledge on variability of their functional traits, among and within species, is still limited. Remote sensing is a high-throughput, feasible option for characterizing plant traits at different scales, provided that reliable spectroscopy models are calibrated with congruous empirical data, but existing applications are biased towards terrestrial plants. We sampled leaves from six floating and emergent macrophyte species common in temperate areas, covering different phenological stages, seasons, and environmental conditions, and measured leaf reflectance (400–2500 nm) and leaf traits (dealing with photophysiology, pigments, and structure). We explored optimal spectral band combinations and established non-parametric reflectance-based models for selected traits, eventually showing how airborne hyperspectral data could capture spatial–temporal macrophyte variability. Results Our key finding is that structural—leaf dry matter content, leaf mass per area—and biochemical—chlorophyll-a content and chlorophylls to carotenoids ratio—traits can be surrogated by leaf reflectance with normalized error under 17% across macrophyte species. On the other hand, the performance of reflectance-based models for photophysiological traits substantively varies, depending on macrophyte species and target parameters. Conclusions Our main results show the link between leaf reflectance and leaf economics (structure and biochemistry) for aquatic plants, thus envisioning a crucial role for remote sensing in enhancing the level of detail of macrophyte functional diversity analysis to intra-site and intra-species scales. At the same time, we highlighted some difficulties in establishing a general link between reflectance and photosynthetic performance under high environmental heterogeneity, potentially opening further investigation directions.
format	article
author	Paolo Villa Rossano Bolpagni Monica Pinardi Viktor R. Tóth
author_facet	Paolo Villa Rossano Bolpagni Monica Pinardi Viktor R. Tóth
author_sort	Paolo Villa
title	Leaf reflectance can surrogate foliar economics better than physiological traits across macrophyte species
title_short	Leaf reflectance can surrogate foliar economics better than physiological traits across macrophyte species
title_full	Leaf reflectance can surrogate foliar economics better than physiological traits across macrophyte species
title_fullStr	Leaf reflectance can surrogate foliar economics better than physiological traits across macrophyte species
title_full_unstemmed	Leaf reflectance can surrogate foliar economics better than physiological traits across macrophyte species
title_sort	leaf reflectance can surrogate foliar economics better than physiological traits across macrophyte species
publisher	BMC
publishDate	2021
url	https://doaj.org/article/222e9b81eb6942158622a5212ae1fe13
work_keys_str_mv	AT paolovilla leafreflectancecansurrogatefoliareconomicsbetterthanphysiologicaltraitsacrossmacrophytespecies AT rossanobolpagni leafreflectancecansurrogatefoliareconomicsbetterthanphysiologicaltraitsacrossmacrophytespecies AT monicapinardi leafreflectancecansurrogatefoliareconomicsbetterthanphysiologicaltraitsacrossmacrophytespecies AT viktorrtoth leafreflectancecansurrogatefoliareconomicsbetterthanphysiologicaltraitsacrossmacrophytespecies
_version_	1718429393538252800

Leaf reflectance can surrogate foliar economics better than physiological traits across macrophyte species

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