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Beta diversity of tropical marine benthic assemblages in the Spermonde Archipelago, Indonesia
Author(s) -
Becking Leontine E.,
Cleary Daniel F. R.,
Voogd Nicole J.,
Renema Willem,
Beer Ma,
Soest Rob W. M.,
Hoeksema Bert W.
Publication year - 2006
Publication title -
marine ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.668
H-Index - 58
eISSN - 1439-0485
pISSN - 0173-9565
DOI - 10.1111/j.1439-0485.2005.00051.x
Subject(s) - foraminifera , benthic zone , beta diversity , archipelago , ecology , spatial ecology , biological dispersal , invertebrate , species richness , oceanography , taxon , reef , ordination , geography , biology , geology , population , demography , sociology
In order to preserve diversity it is essential to understand how assemblages change across space. Despite this fact, we still know very little about how marine diversity is spatially distributed, especially among lesser‐studied invertebrate taxa. In the present study beta‐diversity patterns of sea urchins, sponges, mushroom corals and larger foraminifera were assessed in the Spermonde Archipelago (Indonesia). Using ordinations we showed that the inshore zone (<5 km offshore), midshore zone (5 < x < 30 km offshore) and distance offshore zone (>30 km offshore) all contained distinct assemblages of sponges and corals, while only foraminifera assemblages from the inshore (<5 km offshore) zone were distinct. There was a significant spatial pattern of community similarity for all taxa surveyed, but this pattern proved to be wholly related to environmental variables for sponges and foraminifera, and primarily for mushroom corals and sea urchins. The lack of a pure spatial component suggests that these taxa may not be dispersal limited within the spatial scales of this study ( c . 1600 km 2 ). The analyses of the corals and foraminifera were additionally tested at two spatial scales of sampling. Both taxa were primarily associated with local‐scale environmental variables at the local scale and larger‐scale variables at the larger scale. Mean inter‐plot similarity was also higher and variation lower at the larger scale. The results suggest that substantial variation in similarity can be predicted using simple locally assessed environmental variables combined with remotely sensed parameters.