Spectral Heterogeneity Predicts Local-Scale Gamma and Beta Diversity of Mesic Grasslands

dc.contributor.author Polley, H. Wayne
dc.contributor.author Yang, Chenghai
dc.contributor.author Wilsey, Brian
dc.contributor.author Fay, Philip
dc.contributor.department Ecology, Evolution and Organismal Biology
dc.date 2019-03-07T04:14:56.000
dc.date.accessioned 2020-06-30T02:18:15Z
dc.date.available 2020-06-30T02:18:15Z
dc.date.issued 2019-01-01
dc.description.abstract <p>Plant species diversity is an important metric of ecosystem functioning, but field assessments of diversity are constrained in number and spatial extent by labor and other expenses. We tested the utility of using spatial heterogeneity in the remotely-sensed reflectance spectrum of grassland canopies to model both spatial turnover in species composition and abundances (β diversity) and species diversity at aggregate spatial scales (γ diversity). Shannon indices of γ and β diversity were calculated from field measurements of the number and relative abundances of plant species at each of two spatial grains (0.45 m<sup>2</sup> and 35.2 m<sup>2</sup>) in mesic grasslands in central Texas, USA. Spectral signatures of reflected radiation at each grain were measured from ground-level or an unmanned aerial vehicle (UAV). Partial least squares regression (PLSR) models explained 59–85% of variance in γ diversity and 68–79% of variance in β diversity using spatial heterogeneity in canopy optical properties. Variation in both γ and β diversity were associated most strongly with heterogeneity in reflectance in blue (350–370 nm), red (660–770 nm), and near infrared (810–1050 nm) wavebands. Modeled diversity was more sensitive by a factor of three to a given level of spectral heterogeneity when derived from data collected at the small than larger spatial grain. As estimated from calibrated PLSR models, β diversity was greater, but γ diversity was smaller for restored grassland on a lowland clay than upland silty clay soil. Both γ and β diversity of grassland can be modeled by using spatial heterogeneity in vegetation optical properties provided that the grain of reflectance measurements is conserved.</p>
dc.description.comments <p>This article is published as Polley, H. Wayne, Chenghai Yang, Brian J. Wilsey, and Philip A. Fay. "Spectral Heterogeneity Predicts Local-Scale Gamma and Beta Diversity of Mesic Grasslands." <em>Remote Sensing</em> 11, no. 4 (2019): 458. doi: <a href="https://doi.org/10.3390/rs11040458">10.3390/rs11040458</a>.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/eeob_ag_pubs/340/
dc.identifier.articleid 1345
dc.identifier.contextkey 13909603
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath eeob_ag_pubs/340
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/23224
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/eeob_ag_pubs/340/2019_Wilsey_SpectralHeterogeneity.pdf|||Fri Jan 14 23:41:32 UTC 2022
dc.source.uri 10.3390/rs11040458
dc.subject.disciplines Ecology and Evolutionary Biology
dc.subject.disciplines Plant Sciences
dc.subject.disciplines Statistical Models
dc.subject.keywords airborne remote sensing
dc.subject.keywords hyperspectral spectroradiometer
dc.subject.keywords partial least squares regression
dc.subject.keywords Shannon diversity
dc.subject.keywords spatial grain
dc.subject.keywords spatial heterogeneity in vegetation optical properties
dc.title Spectral Heterogeneity Predicts Local-Scale Gamma and Beta Diversity of Mesic Grasslands
dc.type article
dc.type.genre article
dspace.entity.type Publication
relation.isAuthorOfPublication 8c9719e8-92a4-4db1-bdf5-8e387ef59e2d
relation.isOrgUnitOfPublication 6fa4d3a0-d4c9-4940-945f-9e5923aed691
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