Abstract
In this study, we examined the phenology of the salt marsh ecosystem across coastal Louisiana (LA) for a 16-year time period (2000–2015) using NASA’s Moderate Resolution Imaging Spectroradiometer’s (MODIS) eight-day average surface reflectance images (500 m). We compared the performances of least squares fitted asymmetric Gaussian (AG) and double logistic (DL) smoothing functions in terms of increasing the signal-to-noise ratio from the raw phenology derived from the time-series composites. We performed derivative analysis to determine the appropriate start of season (SOS) and end of season (EOS) thresholds. After that, we extracted the seasonality parameters in TIMESAT, and studied the effect of environmental disturbances/anomalies on the seasonality parameters. Finally, we performed trend analysis using the derived seasonality parameters such as base green biomass (GBM) value, maximum GBM value, seasonal amplitude, and small seasonal integral. Based on root mean square error (RMSE) values and residual plots, we selected the best thresholds for SOS (5% of amplitude) and EOS (20% of amplitude), along with the best smoothing function. The selected SOS and EOS thresholds were able to capture the environmental disturbances that have affected the salt marsh ecosystem during the 16-year time period. Our trend analysis results indicate positive trends in the base GBM values in the salt marshes of LA. However, we did not notice as much of a positive trend in the maximum GBM levels. Hence, we observed mostly negative changes in the GBM amplitude and small seasonal integral values. These negative changes indicated the overall progressive decline in the rates of photosynthesis and biomass allocation in the LA salt marsh ecosystem, which is most likely due to elevated atmospheric carbon dioxide levels and sea level rise. The results illustrate both the relative efficiency of MODIS-based biophysical models for analyzing salt marsh phenology, and performances of the smoothing techniques in terms of improving the signal-to-noise ratio of the MODIS-derived phenology.
Highlights
The global average atmospheric carbon dioxide (CO2) concentration has risen significantly since the pre-industrial revolution level of 280 ppm [1]
This study provides a comprehensive analysis of the phenological trends of the salt marsh ecosystem of LA, showcasing the efficiency of the Moderate Resolution Imaging Spectroradiometer (MODIS)-based biophysical model derived time-series composites of salt marsh green biomass (GBM)
We analyzed the seasonality in the start of season (SOS) and end of season (EOS) dates over a 16-year time period; the effects of the environmental events influencing the deviations from the normal SOS and EOS have been efficiently captured
Summary
The global average atmospheric carbon dioxide (CO2) concentration has risen significantly since the pre-industrial revolution level of 280 ppm [1]. The continuous monitoring of the phenology of salt marsh ecosystems for the detection and analysis of any such trends is of utmost priority for the successful implementation of conservation and restoration measures, both at site-specific and landscape levels [12]. One way to study and understand the productive health of any vegetation ecosystem is through analyzing long-term spatiotemporal trends in phenology in relation to their environment [10]. Phenological measurements such as the timing of budburst and flowering are widely used to detect and study the effect of climate variability on vegetation health, both at the site-specific anc broader landscape scale [13,14,15]. We validate our methods by analyzing the vanarniuatailovnas.riaFtiinoanlsly. ,Fwinealelyv,awlueateevtahluealtoentgh-etelromngc-htearnmgechtraenngdes tirnenthdes sineatshoenaseliatsyopnaarliatmy eptaerrasmuestienrgs sutsaitnisgtisctaaltitsrteincadl atrneanlydsaisntaelcyhsinsiqteucehsn. iques
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