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ARS Home » Plains Area » Temple, Texas » Grassland Soil and Water Research Laboratory » Research » Publications at this Location » Publication #365366

Research Project: Contributions of Climate, Soils, Species Diversity, and Management to Sustainable Crop, Grassland, and Livestock Production Systems

Location: Grassland Soil and Water Research Laboratory

Title: Spectrally derived values of community leaf dry matter content link shifts in grassland composition with change in biomass production

Author
item Polley, Herbert
item Yang, Chenghai
item WILSEY, BRIAN - Iowa State University
item Fay, Philip

Submitted to: Remote Sensing in Ecology and Conservation
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/20/2019
Publication Date: 1/13/2020
Citation: Polley, H.W., Yang, C., Wilsey, B.J., Fay, P.A. 2020. Spectrally derived values of community leaf dry matter content link shifts in grassland composition with change in biomass production. Remote Sensing in Ecology and Conservation. 6(3):344-353. https://doi.org/10.1002/rse2.145.
DOI: https://doi.org/10.1002/rse2.145

Interpretive Summary: Grassland biomass production varies in response to inter-annual variation in precipitation. The amount by which production changes as precipitation changes depends on both the plant species composition of grassland and responsiveness of abundant species to change in water availability. Differences in species composition and responsiveness to precipitation change are in turn associated with differences in leaf traits, implying that grassland response to precipitation change can be predicted by measuring leaf traits at the scale of grassland canopies. Such measurements are labor intensive, however, particularly over large areas. We used measurements of canopy reflectance of sunlight from grassland communities to develop a canopy-scale predictive model for one leaf trait, leaf dry matter content (LDMC; leaf dry weight/leaf saturated weight). There is evidence that differences in LDMC are reflected in differences in grassland response to precipitation. The predictive model for LDMC then was applied to airborne measurements of canopy reflectance to determine how canopy-scale LDMC interacts with inter-annual variation in precipitation to influence aboveground biomass production of grassland in central Texas over 4 years. Variation in grassland or canopy LDMC (LDMC per species weighted by species abundances) was correlated with variation in canopy reflectance in red and near-infrared portions of the light spectrum. LDMC was high in grassland areas dominated by annual forb species and decreased linearly as forb abundance declined. Grassland production increased as annual precipitation increased, but the production response to precipitation depended on LDMC. Aboveground biomass production increased linearly as community LDMC declined. Increased precipitation enhanced biomass both by reducing canopy LDMC by favoring species with low values of LDMC and by increasing the positive effect of low LDMC on biomass production. We find that grassland LDMC can be calculated from measurements of canopy reflectance. Remote estimates of grassland LDMC, in turn, provide insight into the likely responses of grassland composition and functioning to inter-annual variation in precipitation.

Technical Abstract: Leaf traits link environmental effects on plant species abundances to changes in ecosystem processes but are a challenge to measure regularly and over large areas. We used measurements of canopy reflectance from grassland communities to derive a regression model for one leaf trait, leaf dry matter content (LDMC). Partial least squares regression (PLSR) analysis was used to model community-weighted (species abundance-weighted) values of LDMC as a function of canopy reflectance in visible and near-infrared (NIR) wavebands. The PLSR model then was applied to airborne measurements of canopy reflectance to determine how community LDMC interacts with inter-annual variation in precipitation to influence aboveground biomass production of restored grassland during spring over 4 years. LDMC was well-described by a PLSR model that included reflectance measurements located primarily in red edge and NIR portions of the spectrum. Community LDMC was high in grassland areas dominated by annual forb species and decreased linearly as forb abundance declined. Aboveground production in spring, as indicated by maximum values of the normalized difference vegetation index (NDVI), declined linearly as community LDMC increased. NDVI-LDMC regression relationships differed among years but variation in NDVI-LDMC relationships was not correlated to inter-annual differences in precipitation. Community LDMC, by contrast, increased as annual precipitation declined. Inter-annual variation in biomass production depended more on precipitation-caused change in community LDMC than on change in NDVI-LDMC relationships. We find that grassland LDMC is well-described by a regression model using canopy reflectance in red edge and NIR wavebands. LDMC was strongly correlated with both grassland composition and functioning. Our results imply that precipitation affects spring biomass production in restored grassland more by altering abundances of functional groups of species than by changing the relationship between biomass production and grassland composition.