Characterizing seasonal variation in foliar biochemistry with airborne imaging spectroscopy.
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| Title: | Characterizing seasonal variation in foliar biochemistry with airborne imaging spectroscopy. |
|---|---|
| Authors: | Chlus, Adam1 (AUTHOR) chlus@wisc.edu, Townsend, Philip A.1 (AUTHOR) |
| Source: | Remote Sensing of Environment. Jun2022, Vol. 275, pN.PAG-N.PAG. 1p. |
| Subjects: | Spectral imaging, Partial least squares regression, Biochemistry, Deciduous forests, Seasons, Chlorophyll spectra |
| Geographic Terms: | Wisconsin |
| Abstract: | Foliar biochemical traits are important indicators of ecosystem functioning and health that are impractical to characterize at large spatial and temporal scales using traditional measurements. However, comprehensive inventories of foliar traits are important for understanding ecosystem responses to anthropogenic and natural disturbances, as inputs into ecosystem process models, and for quantifying spatial variation in functional diversity. Imaging spectroscopy has been demonstrated as a valuable tool for developing maps of ecologically important foliar traits at large scales, but its application to mapping foliar traits over the course of the growing season has been limited. We collected high-resolution imaging spectroscopy data over Blackhawk Island, Wisconsin, USA at eight time points during the 2018 growing season (May – October). Using partial least squares regression (PLSR) we developed predictive models applicable to all dates to produce canopy-level maps of eight traits related to ecophysiological function: chlorophyll content, leaf mass per area and concentrations of calcium, nitrogen, phosphorus, potassium, phenolics and lignin. The accuracy of our models varied across traits (R2: 0.25–0.86); traits with well-defined absorption features were retrieved with high accuracy including chlorophyll (R2: 0.86; %RMSE: 11.0) and total phenolics (R2: 0.86; %RMSE: 11.0). We also assessed how well our models estimated biochemistry on novel species and new dates using a cross-validation analysis. Chlorophyll and total phenolics were well estimated across withheld dates and species, whereas calcium was estimated poorly on both withheld species (R2: 0.08) and dates (R2: 0.07). Our canopy-level maps of macronutrients (N, P and K) showed general trends of decreasing concentration over the course of the year, reflecting dilution by carbon-rich compounds during the growing season and resorption during senescence. Conversely, recalcitrant compounds including lignin and calcium increased until late summer, after which they stabilized. These results demonstrate the potential of current and proposed spaceborne imaging spectroscopy missions for mapping seasonal patterns in foliar biochemistry at a global scale. • Seasonal dynamics of eight biochemicals were mapped in a temperate deciduous forest. • Biochemicals with well-defined absorption features were best estimated. • Seasonal patterns varied between foliar biochemicals and across species. [ABSTRACT FROM AUTHOR] |
| Copyright of Remote Sensing of Environment is the property of Elsevier B.V. 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.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 156420206 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Characterizing seasonal variation in foliar biochemistry with airborne imaging spectroscopy. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Chlus%2C+Adam%22">Chlus, Adam</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> chlus@wisc.edu</i><br /><searchLink fieldCode="AR" term="%22Townsend%2C+Philip+A%2E%22">Townsend, Philip A.</searchLink><relatesTo>1</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Remote+Sensing+of+Environment%22">Remote Sensing of Environment</searchLink>. Jun2022, Vol. 275, pN.PAG-N.PAG. 1p. – Name: Subject Label: Subjects Group: Su 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="%22Biochemistry%22">Biochemistry</searchLink><br /><searchLink fieldCode="DE" term="%22Deciduous+forests%22">Deciduous forests</searchLink><br /><searchLink fieldCode="DE" term="%22Seasons%22">Seasons</searchLink><br /><searchLink fieldCode="DE" term="%22Chlorophyll+spectra%22">Chlorophyll spectra</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Wisconsin%22">Wisconsin</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Foliar biochemical traits are important indicators of ecosystem functioning and health that are impractical to characterize at large spatial and temporal scales using traditional measurements. However, comprehensive inventories of foliar traits are important for understanding ecosystem responses to anthropogenic and natural disturbances, as inputs into ecosystem process models, and for quantifying spatial variation in functional diversity. Imaging spectroscopy has been demonstrated as a valuable tool for developing maps of ecologically important foliar traits at large scales, but its application to mapping foliar traits over the course of the growing season has been limited. We collected high-resolution imaging spectroscopy data over Blackhawk Island, Wisconsin, USA at eight time points during the 2018 growing season (May – October). Using partial least squares regression (PLSR) we developed predictive models applicable to all dates to produce canopy-level maps of eight traits related to ecophysiological function: chlorophyll content, leaf mass per area and concentrations of calcium, nitrogen, phosphorus, potassium, phenolics and lignin. The accuracy of our models varied across traits (R2: 0.25–0.86); traits with well-defined absorption features were retrieved with high accuracy including chlorophyll (R2: 0.86; %RMSE: 11.0) and total phenolics (R2: 0.86; %RMSE: 11.0). We also assessed how well our models estimated biochemistry on novel species and new dates using a cross-validation analysis. Chlorophyll and total phenolics were well estimated across withheld dates and species, whereas calcium was estimated poorly on both withheld species (R2: 0.08) and dates (R2: 0.07). Our canopy-level maps of macronutrients (N, P and K) showed general trends of decreasing concentration over the course of the year, reflecting dilution by carbon-rich compounds during the growing season and resorption during senescence. Conversely, recalcitrant compounds including lignin and calcium increased until late summer, after which they stabilized. These results demonstrate the potential of current and proposed spaceborne imaging spectroscopy missions for mapping seasonal patterns in foliar biochemistry at a global scale. • Seasonal dynamics of eight biochemicals were mapped in a temperate deciduous forest. • Biochemicals with well-defined absorption features were best estimated. • Seasonal patterns varied between foliar biochemicals and across species. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Remote Sensing of Environment is the property of Elsevier B.V. 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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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1016/j.rse.2022.113023 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 1 StartPage: N.PAG Subjects: – SubjectFull: Spectral imaging Type: general – SubjectFull: Partial least squares regression Type: general – SubjectFull: Biochemistry Type: general – SubjectFull: Deciduous forests Type: general – SubjectFull: Seasons Type: general – SubjectFull: Chlorophyll spectra Type: general – SubjectFull: Wisconsin Type: general Titles: – TitleFull: Characterizing seasonal variation in foliar biochemistry with airborne imaging spectroscopy. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Chlus, Adam – PersonEntity: Name: NameFull: Townsend, Philip A. IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 06 Text: Jun2022 Type: published Y: 2022 Identifiers: – Type: issn-print Value: 00344257 Numbering: – Type: volume Value: 275 Titles: – TitleFull: Remote Sensing of Environment Type: main |
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