ORCID Profile
0000-0002-9033-0024
Current Organisation
University of California Davis
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Publisher: American Geophysical Union (AGU)
Date: 03-2017
DOI: 10.1002/2016JG003580
Publisher: Wiley
Date: 17-02-2021
Publisher: Springer Science and Business Media LLC
Date: 15-02-2022
DOI: 10.1007/S00271-022-00777-Z
Abstract: Frequent drought and high temperature conditions in California vineyards necessitate plant stress detection to support irrigation management strategies and decision making. Remote sensing provides a powerful tool to continuously monitor vegetation function across spatial and temporal scales. In this study, we utilized a tower-based optical-remote sensing system to continuously monitor four vineyard subplots in California’s Central Valley. We compared the performance of the greenness-based normalized difference vegetation index (NDVI) and the physiology-based photochemical reflectance index (PRI) to track variations of eddy covariance estimated gross primary productivity (GPP) during four stress events between July and September 2020. Our results demonstrate that NDVI was invariant during stress events. In contrast, PRI was effective at tracking the short-term stress-induced declines and recovery of GPP associated with soil water depletion and increased air temperature, as well as reductions in GPP from decreased PAR caused by smokey conditions from nearby fires. Canopy-scale remote sensing can provide continuous real-time data, and physiology-based vegetation indices such as PRI can be used to monitor variation of photosynthetic activity during stress events to aid in management decisions.
Publisher: Copernicus GmbH
Date: 03-02-2020
DOI: 10.5194/BG-2019-508
Abstract: Abstract. Recent successes in passive remote sensing of far-red solar induced chlorophyll fluorescence (SIF) have spurred development and integration of canopy-level fluorescence models in global terrestrial biosphere models (TBMs) for climate and carbon cycle research. The interaction of fluorescence with photochemistry at the leaf- and canopy- scale provides opportunities to diagnose and constrain model simulations of photosynthesis and related processes, through direct comparison to and assimilation of tower, airborne, and satellite data. TBMs describe key processes relating to absorption of sunlight, leaf-level fluorescence emission, scattering and reabsorption throughout the canopy. Here, we analyze simulations from an ensemble of process-based TBM-SIF models (SiB3, SiB4, CLM4.5, CLM5.0, BETHY, ORCHIDEE, BEPS) at a subalpine evergreen needleleaf forest near Niwot Ridge, Colorado. These models are forced with tower observed meteorological data, and analyzed against continuous far-red SIF and gross primary productivity (GPP) partitioned eddy covariance data at diurnal and synoptic scales during the growing season (July–August 2017). Our primary objective is to summarize the site-level state of the art in TBM-SIF modeling over a relatively short time period (summer) when light, structure, and pigments are similar, setting the stage for regional- to global-scale analyses. We find that these models are generally well constrained in simulating photosynthetic yield, but show strongly ergent patterns in the simulation of absorbed photosynthetic active radiation (PAR), absolute GPP and fluorescence, quantum yields, and light response at leaf and canopy scale. This study highlights the need for mechanistic modeling of non-photochemical quenching in stressed and unstressed environments, and improved representation of light absorption (APAR), distribution of sunlit and shaded light, and radiative transfer from leaf to canopy scale.
Location: United States of America
No related grants have been discovered for Troy Magney.