Ecophysio-optical traits of semiarid Nebraska grasslands under different Juniperus virginiana and Pinus ponderosa canopy covers
Despite conservation efforts in the U.S. Great Plains, woody species have continued to expand at an unprecedented rate, threatening key ecosystem services and resilience. Cross-scale monitoring of these grasslands is key to successful integrative management strategies. In this study we measured plan...
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2021
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oai:doaj.org-article:fdcfbbcf4f1f480eaab2aca4154b91c02021-12-01T04:59:49ZEcophysio-optical traits of semiarid Nebraska grasslands under different Juniperus virginiana and Pinus ponderosa canopy covers1470-160X10.1016/j.ecolind.2021.108159https://doaj.org/article/fdcfbbcf4f1f480eaab2aca4154b91c02021-11-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1470160X21008244https://doaj.org/toc/1470-160XDespite conservation efforts in the U.S. Great Plains, woody species have continued to expand at an unprecedented rate, threatening key ecosystem services and resilience. Cross-scale monitoring of these grasslands is key to successful integrative management strategies. In this study we measured plant optical traits derived from hyperspectral proximal sensing techniques with a field spectrometer, coupled with field-based measurements, including fluorescence and chlorophyll content, to determine the impacts of Juniperus virginiana and Pinus ponderosa expansion on grasslands health in Nebraska Sandhills, and investigated the use of optical-based approaches as indicators of successful monitoring of grasslands. Our results showed that higher woody species cover in grasslands was associated with lower soil moisture, decline in forbs, shrubs, and grasses cover and productivity, as well as herbaceous chlorophyll content and fluorescence, compared to non-invaded grasslands. We derived 13 vegetation indices (VIs) from optical-based methods and validated them against traditional handheld measurements of plant ecophysiological traits and vegetation biomass and composition. VIs, including Normalized Difference Vegetation Index (NDVI), Water Index (WI) and Chlorophyll Index at red edge (CIred edge) performed best when tested against biomass, and chlorophyll content and fluorescence (Fv/Fm), suggesting their potential use for assessing grasslands vegetation health. We demonstrate that optical-based approaches can serve as efficient non-invasive tools that can be part of multi-scale successful integrative management strategies.Anastasios MazisJulie A. FowlerJeremy HillerYuzhen ZhouBrian D. WardlowDavid WedinTala AwadaElsevierarticleWoody plant invasionHerbaceous vegetationChlorophyllFluorescenceBiomassVegetation indicesEcologyQH540-549.5ENEcological Indicators, Vol 131, Iss , Pp 108159- (2021) |
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Woody plant invasion Herbaceous vegetation Chlorophyll Fluorescence Biomass Vegetation indices Ecology QH540-549.5 |
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Woody plant invasion Herbaceous vegetation Chlorophyll Fluorescence Biomass Vegetation indices Ecology QH540-549.5 Anastasios Mazis Julie A. Fowler Jeremy Hiller Yuzhen Zhou Brian D. Wardlow David Wedin Tala Awada Ecophysio-optical traits of semiarid Nebraska grasslands under different Juniperus virginiana and Pinus ponderosa canopy covers |
description |
Despite conservation efforts in the U.S. Great Plains, woody species have continued to expand at an unprecedented rate, threatening key ecosystem services and resilience. Cross-scale monitoring of these grasslands is key to successful integrative management strategies. In this study we measured plant optical traits derived from hyperspectral proximal sensing techniques with a field spectrometer, coupled with field-based measurements, including fluorescence and chlorophyll content, to determine the impacts of Juniperus virginiana and Pinus ponderosa expansion on grasslands health in Nebraska Sandhills, and investigated the use of optical-based approaches as indicators of successful monitoring of grasslands. Our results showed that higher woody species cover in grasslands was associated with lower soil moisture, decline in forbs, shrubs, and grasses cover and productivity, as well as herbaceous chlorophyll content and fluorescence, compared to non-invaded grasslands. We derived 13 vegetation indices (VIs) from optical-based methods and validated them against traditional handheld measurements of plant ecophysiological traits and vegetation biomass and composition. VIs, including Normalized Difference Vegetation Index (NDVI), Water Index (WI) and Chlorophyll Index at red edge (CIred edge) performed best when tested against biomass, and chlorophyll content and fluorescence (Fv/Fm), suggesting their potential use for assessing grasslands vegetation health. We demonstrate that optical-based approaches can serve as efficient non-invasive tools that can be part of multi-scale successful integrative management strategies. |
format |
article |
author |
Anastasios Mazis Julie A. Fowler Jeremy Hiller Yuzhen Zhou Brian D. Wardlow David Wedin Tala Awada |
author_facet |
Anastasios Mazis Julie A. Fowler Jeremy Hiller Yuzhen Zhou Brian D. Wardlow David Wedin Tala Awada |
author_sort |
Anastasios Mazis |
title |
Ecophysio-optical traits of semiarid Nebraska grasslands under different Juniperus virginiana and Pinus ponderosa canopy covers |
title_short |
Ecophysio-optical traits of semiarid Nebraska grasslands under different Juniperus virginiana and Pinus ponderosa canopy covers |
title_full |
Ecophysio-optical traits of semiarid Nebraska grasslands under different Juniperus virginiana and Pinus ponderosa canopy covers |
title_fullStr |
Ecophysio-optical traits of semiarid Nebraska grasslands under different Juniperus virginiana and Pinus ponderosa canopy covers |
title_full_unstemmed |
Ecophysio-optical traits of semiarid Nebraska grasslands under different Juniperus virginiana and Pinus ponderosa canopy covers |
title_sort |
ecophysio-optical traits of semiarid nebraska grasslands under different juniperus virginiana and pinus ponderosa canopy covers |
publisher |
Elsevier |
publishDate |
2021 |
url |
https://doaj.org/article/fdcfbbcf4f1f480eaab2aca4154b91c0 |
work_keys_str_mv |
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