Due to its rapid growth, the introduced mangrove species Sonneratia apetala from Bangladesh has been widely used in mangrove restoration in southeastern China since 1985. As an indigenous mangrove species in Hainan, China, Sonneratia caseolaris was also planted in Guangdong Province for afforestation purposes. Both species have developed well in their new habitats, but their ecophysiological differences with the native mangrove species have not been studied. In this study, leaf gas exchange, water and nitrogen use efficiencies of two Sonneratia species were compared with those of selected native mangrove species (Avicennia marina, Aegiceras corniculatum, Kandelia candel, and Excoecaria agallocha) in Hainan and Shenzhen. The introduced S. apetala maintained lower carbon assimilation rate (A) and photosynthetic nitrogen use efficiency (PNUE) than the indigenous S. caseolaris. In Shenzhen, the two introduced Sonneratia had comparable photosynthetic rates and water use efficiency (WUE) with the native mangrove species, except that PNUE in S. caseolaris was significantly higher than in the native mangrove species. The two Sonneratia species showed significant overlap in PNUE and long-term WUE. Photosynthetic parameters derived from leaf photosynthetic light–response curves and A–Ci curves also suggested lower carbon assimilation capacities for the introduced Sonneratia than for the native mangrove species in both study sites. The lower light compensation point (LCP) of two introduced Sonneratia in both study sites also indicated a better adaptation to a low light regime than the native mangrove species. The results of photosynthetic capacities indicated that the introduced mangrove species have little competitive advantage over local native mangrove species in their respective new habitats. 相似文献
Spatially-explicit estimation of aboveground biomass(AGB) plays an important role to generate action policies focused in climate change mitigation,since carbon(C) retained in the biomass is vital for regulating Earth’s temperature.This work estimates AGB using both chlorophyll(red,near infrared) and moisture(middle infrared) based normalized vegetation indices constructed with MCD43A4 MODerate-resolution Imaging Spectroradiometer(MODIS) and MOD44B vegetation continuous fields(VCF) data.The study area is located in San Luis Potosí,Mexico,a region that comprises a part of the upper limit of the intertropical zone.AGB estimations were made using both individual tree data from the National Forest Inventory of Mexico and allometric equations reported in scientific literature.Linear and nonlinear(expo-nential) models were fitted to find their predictive potential when using satellite spectral data as explanatory variables.Highly-significant correlations(p = 0.01) were found between all the explaining variables tested.NDVI62,linked to chlorophyll content and moisture stress,showed the highest correlation.The best model(nonlinear) showed an index of fit(Pseudo-r2) equal to 0.77 and a root mean square error equal to 26.00 Mg/ha using NDVI62 and VCF as explanatory variables.Validation correlation coefficients were similar for both models:lin-ear(r = 0.87**) and nonlinear(r = 0.86**). 相似文献