Marine Biology

, Volume 154, Issue 6, pp 997–1007 | Cite as

Leaf consumption by Sesarma plicata in a mangrove forest at Jiulongjiang Estuary, China

  • Guang-Cheng Chen
  • Yong YeEmail author
Original Paper


The feeding ecology of Sesarma plicata (Grapsidae: Sesarminae), the most abundant crab species in a mangrove forest dominated by Kandelia candel at Jiulongjiang Estuary, China, was investigated through field and laboratory experiments. Feeding preference and consumption rates were determined on mature, senescent and decomposed leaves of Kandelia candel, Bruguiera gymnorrhiza and Aegiceras corniculatum. In the laboratory, S. plicata preferred leaves of K. candel over those of B. gymnorrhiza and A. corniculatum, and consumed significantly more decomposed leaves than mature and senescent ones, irrespective of crab size. Field experiments with limited power failed to reveal detectable species preferences despite more consumption of K. candel, but decomposed leaves of each species were again preferred. Leaf characteristics associated with preference changed with plant species and leaf state. Low tannins and high water content characterized the preference for decomposed state of leaves. Species preference was significantly and negatively related to crude fibers and C:N ratios for mature leaves, and crude fiber for senescent leaves, but significantly and positively related to water content for decomposed leaves. Leaf consumption rates averaged for all leaf categories from laboratory no-choice feeding experiments were 0.101, 0.055 and 0.017 gDW ind−1 d−1 for large, medium and small crabs, respectively. In this forest, mean density of S. plicata was 20.5 ind m−2 as assessed by a manual catching method. Leaf litter removal rate during neap tides by sesarmid crabs was about 1.33 gDW m−2 d−1 in April 2006. The leaves removed by crabs were grazed on the sediment surface or taken into crab burrows, shredded and stored before being eaten.


Leaf Litter Mangrove Forest Neap Tide Mangrove Species Senescent Leaf 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work was supported by National Natural Science Foundation of China (40476040) and New Century Excellent Talents in University (NCET). We thank F. Z. Zheng, H. Y. Hu, C. Q. Chao, J. S. Guo, M. L. Liu, H. H. Tang, Y. Y. Xu, X. X. Chen and Y. H. Yao for their dedicated work in the field and/or laboratory.


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Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  1. 1.State Key Laboratory of Marine Environmental ScienceXiamen UniversityXiamenChina

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