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Lopatin. (2023). Interannual Variability of Remotely Sensed Phenology Relates to Plant Communities. IEEE Geosci. Remote. Sens. Lett., 20, 2502405.
Abstract: Vegetation phenology is considered an essential biological indicator in understanding the behavior of ecosystems and how they respond to environmental cues. However, the potential of interannual variations of remotely sensed phenology signals to differentiate plant types remains poorly understood, especially in understudied systems with highly heterogeneous landscapes such as wetlands. This study presents a case study in a San Francisco Bay area marsh that investigates the usefulness of interannual variation, defined as the root-mean-square error of enhanced vegetation index (EVI) measurements against a fitted phenology curve, at the beginning, middle, and end of the growing season as indicators of plant types. The study found that altitude above sea level and certain land surface phenology metrics, such as the day-of-the-year of the end of the season, the mid-autumn day, and the greening rate before the summer peak, were significantly related to these interannual variation trends. These results indicate that a detailed time-series analysis at the beginning and end of growing seasons may enhance large-scale wetland characterization. Overall, the findings of this study contribute to our understanding of vegetation phenology and provide a framework for more accurate wetland classification in future studies.
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Lopez, D., Leiva, A. M., Arismendi, W., & Vidal, G. (2019). Influence of design and operational parameters on the pathogens reduction in constructed wetland under the climate change scenario. Rev. Environ. Sci. Bio-Technol., 18(1), 101–125.
Abstract: Under the climate change scenario, constructed wetlands (CWs) as an engineered system for treating domestic wastewater will face different challenges. Some of them are: (a) the increase of pathogens concentration in wastewater due to the rise of global temperature; (b) higher precipitation that can cause an increase of pathogens due to runoff; (c) the reuse of treated wastewater related to the water scarcity. These problems can affect the capacity of CWs for removal pathogens. In this context, the objective of this review is to provide an overview of the influence of design and operational parameters on pathogens reduction in CWs. To accomplish with this purpose, the published information (>30 studies) about the reduction of pathogens and the operational and design parameters in different CWs configurations and were gathered. With this data, statistical analyses were performed considering the most relevant variables which significantly influence the removal of pathogens in CWs. For this, principal component analyses (PCA) were achieved for determining, separately, the correlation of operational parameters with fecal coliform (FC) and total coliform (TC) removal. The results of PCA showed that FC and TC were correlated positively with mass removal rates of chemical oxygen demand (COD) and biological oxygen Demand (BOD5), total suspended solids (TSS) removal and the size of support medium. This study is the first approach that analyzes together the design and operational parameters which influence the pathogen removal in CWs. For this reason, these parameters and the increase on microorganism concentrations due to the climate change have to be considered for the future design of CWs.
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