Near-infrared spectrometry allows fast and extensive predictions of functional traits from dry leaves and branches
The linking of individual functional traits to ecosystem processes is the basis for making generalizations in ecology, but the measurement of individual values is laborious and time consuming, preventing large-scale trait mapping. Also, in hyper-diverse systems, errors occur because identification i...
| Autor principal: | Costa, Flávia Regina Capellotto |
|---|---|
| Outros Autores: | Lang, Carla, Almeida, Danilo Roberti Alves de, Castilho, Carolina Volkmer, Poorter, L. |
| Grau: | Artigo |
| Idioma: | English |
| Publicado em: |
Ecological Applications
2020
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| Acesso em linha: |
https://repositorio.inpa.gov.br/handle/1/16897 |
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oai:repositorio:1-16897 |
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oai:repositorio:1-16897 Near-infrared spectrometry allows fast and extensive predictions of functional traits from dry leaves and branches Costa, Flávia Regina Capellotto Lang, Carla Almeida, Danilo Roberti Alves de Castilho, Carolina Volkmer Poorter, L. Dry Matter Ecosystem Function Forest Ecosystem Intraspecific Variation Leaf Near Infrared Nutrient Budget Plant Plant Community Prediction Spectrometry Tropical Forest Upscaling Wood Amazonia Anatomy And Histology Brasil Infrared Spectroscopy Life History Trait Physiology Plant Leaf Plant Stem Rainforest Tree Brasil Life History Traits Plant Leaves Plant Stems Rainforest Fourier transform infrared spectroscopy Trees The linking of individual functional traits to ecosystem processes is the basis for making generalizations in ecology, but the measurement of individual values is laborious and time consuming, preventing large-scale trait mapping. Also, in hyper-diverse systems, errors occur because identification is difficult, and species level values ignore intra-specific variation. To allow extensive trait mapping at the individual level, we evaluated the potential of Fourrier-Transformed Near Infra-Red Spectrometry (FT-NIR) to adequately describe 14 traits that are key for plant carbon, water, and nutrient balance. FT-NIR absorption spectra (1,000–2,500 nm) were obtained from dry leaves and branches of 1,324 trees of 432 species from a hyper-diverse Amazonian forest. FT-NIR spectra were related to measured traits for the same plants using partial least squares regressions. A further 80 plants were collected from a different site to evaluate model applicability across sites. Relative prediction error (RMSErel) was calculated as the percentage of the trait value range represented by the final model RMSE. The key traits used in most functional trait studies; specific leaf area, leaf dry matter content, wood density and wood dry matter content can be well predicted by the model (R2 = 0.69–0.78, RMSErel = 9–11%), while leaf density, xylem proportion, bark density and bark dry matter content can be moderately well predicted (R2 = 0.53–0.61, RMSErel = 14–17%). Community-weighted means of all traits were well estimated with NIR, as did the shape of the frequency distribution of the community values for the above key traits. The model developed at the core site provided good estimations of the key traits of a different site. An evaluation of the sampling effort indicated that 400 or less individuals may be sufficient for establishing a good local model. We conclude that FT-NIR is an easy, fast and cheap method for the large-scale estimation of individual plant traits that was previously impossible. The ability to use dry intact leaves and branches unlocks the potential for using herbarium material to estimate functional traits; thus advancing our knowledge of community and ecosystem functioning from local to global scales. © 2018 by the Ecological Society of America 2020-06-15T21:37:06Z 2020-06-15T21:37:06Z 2018 Artigo https://repositorio.inpa.gov.br/handle/1/16897 10.1002/eap.1728 en Volume 28, Número 5, Pags. 1157-1167 Restrito Ecological Applications |
| institution |
Instituto Nacional de Pesquisas da Amazônia - Repositório Institucional |
| collection |
INPA-RI |
| language |
English |
| topic |
Dry Matter Ecosystem Function Forest Ecosystem Intraspecific Variation Leaf Near Infrared Nutrient Budget Plant Plant Community Prediction Spectrometry Tropical Forest Upscaling Wood Amazonia Anatomy And Histology Brasil Infrared Spectroscopy Life History Trait Physiology Plant Leaf Plant Stem Rainforest Tree Brasil Life History Traits Plant Leaves Plant Stems Rainforest Fourier transform infrared spectroscopy Trees |
| spellingShingle |
Dry Matter Ecosystem Function Forest Ecosystem Intraspecific Variation Leaf Near Infrared Nutrient Budget Plant Plant Community Prediction Spectrometry Tropical Forest Upscaling Wood Amazonia Anatomy And Histology Brasil Infrared Spectroscopy Life History Trait Physiology Plant Leaf Plant Stem Rainforest Tree Brasil Life History Traits Plant Leaves Plant Stems Rainforest Fourier transform infrared spectroscopy Trees Costa, Flávia Regina Capellotto Near-infrared spectrometry allows fast and extensive predictions of functional traits from dry leaves and branches |
| topic_facet |
Dry Matter Ecosystem Function Forest Ecosystem Intraspecific Variation Leaf Near Infrared Nutrient Budget Plant Plant Community Prediction Spectrometry Tropical Forest Upscaling Wood Amazonia Anatomy And Histology Brasil Infrared Spectroscopy Life History Trait Physiology Plant Leaf Plant Stem Rainforest Tree Brasil Life History Traits Plant Leaves Plant Stems Rainforest Fourier transform infrared spectroscopy Trees |
| description |
The linking of individual functional traits to ecosystem processes is the basis for making generalizations in ecology, but the measurement of individual values is laborious and time consuming, preventing large-scale trait mapping. Also, in hyper-diverse systems, errors occur because identification is difficult, and species level values ignore intra-specific variation. To allow extensive trait mapping at the individual level, we evaluated the potential of Fourrier-Transformed Near Infra-Red Spectrometry (FT-NIR) to adequately describe 14 traits that are key for plant carbon, water, and nutrient balance. FT-NIR absorption spectra (1,000–2,500 nm) were obtained from dry leaves and branches of 1,324 trees of 432 species from a hyper-diverse Amazonian forest. FT-NIR spectra were related to measured traits for the same plants using partial least squares regressions. A further 80 plants were collected from a different site to evaluate model applicability across sites. Relative prediction error (RMSErel) was calculated as the percentage of the trait value range represented by the final model RMSE. The key traits used in most functional trait studies; specific leaf area, leaf dry matter content, wood density and wood dry matter content can be well predicted by the model (R2 = 0.69–0.78, RMSErel = 9–11%), while leaf density, xylem proportion, bark density and bark dry matter content can be moderately well predicted (R2 = 0.53–0.61, RMSErel = 14–17%). Community-weighted means of all traits were well estimated with NIR, as did the shape of the frequency distribution of the community values for the above key traits. The model developed at the core site provided good estimations of the key traits of a different site. An evaluation of the sampling effort indicated that 400 or less individuals may be sufficient for establishing a good local model. We conclude that FT-NIR is an easy, fast and cheap method for the large-scale estimation of individual plant traits that was previously impossible. The ability to use dry intact leaves and branches unlocks the potential for using herbarium material to estimate functional traits; thus advancing our knowledge of community and ecosystem functioning from local to global scales. © 2018 by the Ecological Society of America |
| format |
Artigo |
| author |
Costa, Flávia Regina Capellotto |
| author2 |
Lang, Carla Almeida, Danilo Roberti Alves de Castilho, Carolina Volkmer Poorter, L. |
| author2Str |
Lang, Carla Almeida, Danilo Roberti Alves de Castilho, Carolina Volkmer Poorter, L. |
| title |
Near-infrared spectrometry allows fast and extensive predictions of functional traits from dry leaves and branches |
| title_short |
Near-infrared spectrometry allows fast and extensive predictions of functional traits from dry leaves and branches |
| title_full |
Near-infrared spectrometry allows fast and extensive predictions of functional traits from dry leaves and branches |
| title_fullStr |
Near-infrared spectrometry allows fast and extensive predictions of functional traits from dry leaves and branches |
| title_full_unstemmed |
Near-infrared spectrometry allows fast and extensive predictions of functional traits from dry leaves and branches |
| title_sort |
near-infrared spectrometry allows fast and extensive predictions of functional traits from dry leaves and branches |
| publisher |
Ecological Applications |
| publishDate |
2020 |
| url |
https://repositorio.inpa.gov.br/handle/1/16897 |
| _version_ |
1787145077465808896 |
| score |
11.755432 |