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Foliar functional traits from imaging spectroscopy across biomes in eastern North America.

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Title: Foliar functional traits from imaging spectroscopy across biomes in eastern North America.
Authors: Wang, Zhihui1 (AUTHOR) zwang896@wisc.edu, Chlus, Adam1 (AUTHOR), Geygan, Ryan1 (AUTHOR), Ye, Zhiwei1 (AUTHOR), Zheng, Ting1 (AUTHOR), Singh, Aditya2 (AUTHOR), Couture, John J.3 (AUTHOR), Cavender‐Bares, Jeannine4 (AUTHOR), Kruger, Eric L.1 (AUTHOR), Townsend, Philip A.1 (AUTHOR)
Source: New Phytologist. Oct2020, Vol. 228 Issue 2, p494-511. 18p.
Subjects: Spectral imaging, Partial least squares regression, Standard deviations, Biomes, Temperate forests
Geographic Terms: North America
Abstract: Summary: Foliar functional traits are widely used to characterize leaf and canopy properties that drive ecosystem processes and to infer physiological processes in Earth system models. Imaging spectroscopy provides great potential to map foliar traits to characterize continuous functional variation and diversity, but few studies have demonstrated consistent methods for mapping multiple traits across biomes.With airborne imaging spectroscopy data and field data from 19 sites, we developed trait models using partial least squares regression, and mapped 26 foliar traits in seven NEON (National Ecological Observatory Network) ecoregions (domains) including temperate and subtropical forests and grasslands of eastern North America.Model validation accuracy varied among traits (normalized root mean squared error, 9.1–19.4%; coefficient of determination, 0.28–0.82), with phenolic concentration, leaf mass per area and equivalent water thickness performing best across domains. Across all trait maps, 90% of vegetated pixels had reasonable values for one trait, and 28–81% provided high confidence for multiple traits concurrently.Maps of 26 traits and their uncertainties for eastern US NEON sites are available for download, and are being expanded to the western United States and tundra/boreal zone. These data enable better understanding of trait variations and relationships over large areas, calibration of ecosystem models, and assessment of continental‐scale functional diversity. [ABSTRACT FROM AUTHOR]
Copyright of New Phytologist is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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PubType: Academic Journal
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  Data: Foliar functional traits from imaging spectroscopy across biomes in eastern North America.
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  Data: <searchLink fieldCode="AR" term="%22Wang%2C+Zhihui%22">Wang, Zhihui</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> zwang896@wisc.edu</i><br /><searchLink fieldCode="AR" term="%22Chlus%2C+Adam%22">Chlus, Adam</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Geygan%2C+Ryan%22">Geygan, Ryan</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ye%2C+Zhiwei%22">Ye, Zhiwei</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zheng%2C+Ting%22">Zheng, Ting</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Singh%2C+Aditya%22">Singh, Aditya</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Couture%2C+John+J%2E%22">Couture, John J.</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Cavender‐Bares%2C+Jeannine%22">Cavender‐Bares, Jeannine</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Kruger%2C+Eric+L%2E%22">Kruger, Eric L.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Townsend%2C+Philip+A%2E%22">Townsend, Philip A.</searchLink><relatesTo>1</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="DE" term="%22Spectral+imaging%22">Spectral imaging</searchLink><br /><searchLink fieldCode="DE" term="%22Partial+least+squares+regression%22">Partial least squares regression</searchLink><br /><searchLink fieldCode="DE" term="%22Standard+deviations%22">Standard deviations</searchLink><br /><searchLink fieldCode="DE" term="%22Biomes%22">Biomes</searchLink><br /><searchLink fieldCode="DE" term="%22Temperate+forests%22">Temperate forests</searchLink>
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  Data: Summary: Foliar functional traits are widely used to characterize leaf and canopy properties that drive ecosystem processes and to infer physiological processes in Earth system models. Imaging spectroscopy provides great potential to map foliar traits to characterize continuous functional variation and diversity, but few studies have demonstrated consistent methods for mapping multiple traits across biomes.With airborne imaging spectroscopy data and field data from 19 sites, we developed trait models using partial least squares regression, and mapped 26 foliar traits in seven NEON (National Ecological Observatory Network) ecoregions (domains) including temperate and subtropical forests and grasslands of eastern North America.Model validation accuracy varied among traits (normalized root mean squared error, 9.1–19.4%; coefficient of determination, 0.28–0.82), with phenolic concentration, leaf mass per area and equivalent water thickness performing best across domains. Across all trait maps, 90% of vegetated pixels had reasonable values for one trait, and 28–81% provided high confidence for multiple traits concurrently.Maps of 26 traits and their uncertainties for eastern US NEON sites are available for download, and are being expanded to the western United States and tundra/boreal zone. These data enable better understanding of trait variations and relationships over large areas, calibration of ecosystem models, and assessment of continental‐scale functional diversity. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of New Phytologist is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1111/nph.16711
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        Text: English
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      – SubjectFull: Spectral imaging
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      – SubjectFull: Partial least squares regression
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      – SubjectFull: Standard deviations
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      – SubjectFull: Biomes
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      – SubjectFull: North America
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              Text: Oct2020
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