2013
DOI: 10.1088/1748-9326/8/4/045030
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Impacts of vegetation onset time on the net primary productivity in a mountainous island in Pacific Asia

Abstract: Vegetation phenology reflects the response of a terrestrial ecosystem to climate change. In this study, we attempt to evaluate the El Niño/La Niña-Southern Oscillation (ENSO)-associated temporal dynamics of the vegetation onset and its influence on the net primary productivity (NPP) in a subtropical island (Taiwan) of Pacific Asia. We utilized a decade-long (2001-2010) time series of photosynthetically active vegetation cover (PV) data, which were derived from the Moderate Resolution Imaging Spectroradiometer … Show more

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Cited by 31 publications
(26 citation statements)
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“…There was no apparent temperature anomaly during the observation periods based on nearly two decades of records (1993–2011) acquired from 136 widely distributed meteorological stations. However, consecutive months of severe drought were observed during 2002–2003 (Figure ) [ Chang et al , ].…”
Section: Methodsmentioning
confidence: 99%
“…There was no apparent temperature anomaly during the observation periods based on nearly two decades of records (1993–2011) acquired from 136 widely distributed meteorological stations. However, consecutive months of severe drought were observed during 2002–2003 (Figure ) [ Chang et al , ].…”
Section: Methodsmentioning
confidence: 99%
“…Meteorological factors have been reported as the key drivers of the change in vegetation cover [34,35] and their lag effects [1,36,37]. We therefore selected annual average temperature, precipitation, and relative humidity of the current year (the year that corresponds to the vegetation cover data) and one year before the vegetation cover investigation year as explanatory factors.…”
Section: Climatic Factorsmentioning
confidence: 99%
“…TIMESAT program is a common tool for phenology detection by setting a threshold value to determine the start of the season and end of the season [30,55,56]. The start of the season was defined as the point at which the EVI increased to a value that was set to 30% of the distance between the minimum and maximum of the left edge.…”
Section: Growing Season Length Detectionmentioning
confidence: 99%