Proximal remote sensing and gross primary productivity in a temperate salt marsh

Vázquez-Lule, Alma; Vargas, Rodrigo

doi:10.1016/j.agrformet.2023.109639

Cited by 3 publications

(2 citation statements)

References 71 publications

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“…To examine diurnal dynamics, we used data only from 2020 to 2021, the period with the most complete record (i.e., containing 15% of data gaps) and when no substantial water surges or storm events occurred. To delineate growing and dormancy periods, we determined phenology dates with the Phenopix R package using the greenness chromatic coordinate (GCC) from a site phenocam (Filippa et al., 2016; Hill et al., 2021; Vázquez‐Lule & Vargas, 2023). Season start and end dates were calculated based on the upturn and recession dates of the annual GCC curve from daily midday images (Gu et al., 2009).…”

Section: Methodsmentioning

confidence: 99%

Empirical Dynamic Modeling Reveals Complexity of Methane Fluxes in a Temperate Salt Marsh

Hill,

Schäfer,

Forbrich

et al. 2024

JGR Biogeosciences

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Methane dynamics within salt marshes are complex because vegetation types, temperature, oscillating water levels, and changes in salinity and redox conditions influence CH4 production, consumption, oxidation, and emissions. These non‐linear and complex interactions among variables affect the traditionally expected functional relationships and present challenges for interpreting and developing process‐based models. We employed empirical dynamic modeling (EDM) and convergent cross mapping (CCM) as a novel approach for characterizing seasonal/multiday and diurnal CH4 dynamics by inferring causal variables, lags, and interconnections among multiple biophysical variables within a temperate salt marsh using 5 years of eddy covariance data. EDM/CCM is a nonparametric approach capable of quantifying the coupling between variables while determining time scales where variable interactions are the most relevant. We found that gross primary productivity, tidal creek dissolved oxygen, and temperature were important for seasonal/multiday dynamics (rho = 0.73–0.80), while water level was most important for diurnal dynamics during both the growing and dormancy phenoperiods (rho = 0.72 and 0.56, respectively). Lags for the top‐ranked variables (i.e., gross primary productivity, dissolved oxygen, temperature, water level) occurred between 1 and 5 weeks at the seasonal scale and 1–24 hr at the diurnal scale. The EDM had high prediction capabilities for intra‐/inter‐seasonal patterns and annual CH4 sums but had limitations in representing large, infrequent fluxes. Results highlight the importance of non‐linearity, drivers, lag times, and interconnections among multiple biophysical variables that regulate CH4 fluxes in tidal wetlands. This research introduces a novel approach to examining CH4 fluxes, which will aid in evaluating current paradigms in wetlands and other ecosystems.

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Section: Methodsmentioning

confidence: 99%

Empirical Dynamic Modeling Reveals Complexity of Methane Fluxes in a Temperate Salt Marsh

Hill,

Schäfer,

Forbrich

et al. 2024

JGR Biogeosciences

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“…EVI was incorporated into the temperature and greenness model [32], canopy reflectance model [33], vegetation photosynthesis model [29], and weather research and forecasting model coupled with the vegetation photosynthesis and respiration model (WRF-VPRM) [34,35] to simulate carbon flux. Furthermore, EVI was shown to exhibit strong correlations with GPP and NEE across diverse regions [36][37][38]. Meanwhile, since WRF-VPRM is a coupled model, it enables the study of the impacts and responses of climate on carbon flux [39,40].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Original and Water Stress-Incorporated Modified Weather Research and Forecasting Vegetation Photosynthesis and Respiration Model in Simulating CO2 Flux and Concentration Variability over the Tibetan Plateau

Niu,

Hu,

Shang

et al. 2023

Remote Sensing

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Terrestrial carbon fluxes are crucial to the global carbon cycle. Quantification of terrestrial carbon fluxes over the Tibetan Plateau (TP) has considerable uncertainties due to the unique ecosystem and climate and scarce flux observations. This study evaluated our recent improvement of terrestrial flux parameterization in the weather research and forecasting model coupled with the vegetation photosynthesis and respiration model (WRF-VPRM) in terms of reproducing observed net ecosystem exchange (NEE), gross ecosystem exchange (GEE), and ecosystem respiration (ER) over the TP. The improvement of VPRM relative to the officially released version considers the impact of water stress on terrestrial fluxes, making it superior to the officially released model due to its reductions in bias, root mean square error (RMSE), and ratio of standard deviation (RSD) of NEE to 0.850 μmol·m−2·s−1, 0.315 μmol·m−2·s−1, and 0.001, respectively. The improved VPRM also affects GEE simulation, increasing its RSD to 0.467 and decreasing its bias and RMSE by 1.175 and 0.324 μmol·m−2·s−1, respectively. Furthermore, bias and RMSE for ER were lowered to −0.417 and 0.954 μmol·m−2·s−1, with a corresponding increase in RSD by 0.6. The improved WRF-VPRM simulation indicates that eastward winds drive the transfer of lower CO2 concentrations from the eastern to the central and western TP and the influx of low-concentration CO2 inhibits biospheric CO2 uptake. The use of an improved WRF-VPRM in this study helps to reduce errors, improve our understanding of the role of carbon flux cycle over the TP, and ultimately reduce uncertainty in the carbon flux budget.

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Editorial special issue: Celebrating 25 years of AmeriFlux

Keenan,

Bohrer,

Scott

et al. 2024

Agricultural and Forest Meteorology

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Proximal remote sensing and gross primary productivity in a temperate salt marsh

Cited by 3 publications

References 71 publications

Empirical Dynamic Modeling Reveals Complexity of Methane Fluxes in a Temperate Salt Marsh

Empirical Dynamic Modeling Reveals Complexity of Methane Fluxes in a Temperate Salt Marsh

Evaluation of Original and Water Stress-Incorporated Modified Weather Research and Forecasting Vegetation Photosynthesis and Respiration Model in Simulating CO2 Flux and Concentration Variability over the Tibetan Plateau

Editorial special issue: Celebrating 25 years of AmeriFlux

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