Abstract

Ya-Fang Li, Fei-Yan Du, Yang-Guang Gu, Jia-Jia Ning, and Liang-Gen Wang (2017) Sonneratia apetala, a non-native superior rapidly growing mangrove species with wide environmental tolerance, has been introduced to Futian National Nature Reserve in Shenzhen, Guangdong, China, for mangrove restoration since 1993. However, the community structure of the associated macrobenthic fauna, a vital component of energy ow and nutrient recycling, remains obscure. The present study analyzed the macrobenthic faunal community, associated habitat characteristics and physico-chemical properties of sediment in rehabilitated S. apetala forests at stand ages of 8, 9, 14, 16 and 20 years from November 2014 to May 2015. Habitat complexity and stand structural heterogeneity varied with stand age. Sediment physico-chemical properties were similar for all stands analyzed, although soil organic matter (SOM) content was significantly higher in the 20-year-old stand than in others. Shannon-Weaver (H') and Pielou's evenness (J) indices of macrobenthic fauna were highest in 14- and 16-year- old stands, respectively, and lowest in 8-year-old stands. In contrast, abundance and biomass peaked in 8-year- old stands and were lowest in 16-year-old stands. Multivariate analysis (cluster, ANOSIM and SIMPER) showed that the macrobenthic faunal community in the 20-year-old stand was different from other stand ages because of a greater abundance of small-sized mollusks and opportunistic species. Spearman correlation analysis showed that H' was positively correlated with salinity. The distance-based linear model suggested that SOM was a significant predictor variable correlated with the macrobenthic faunal community. However, SOM was the only significant predictor variable explaining 12.7% of the total variation; this implies that the spatial variation of the macrobenthic faunal community here was mostly independent of the sediment properties measured. Therefore, we conclude that habitat characteristics such as vegetation characteristics can potentially explain the majority of the variation.

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