Influence of environmental factors on the characteristics of macrobenthic communities in soft bottoms around coral reefs of Larak Island (Persian Gulf)

Abstract

The effective conservation of coastal ecosystems including soft bottoms around coral reefs of Larak Island, Persian Gulf, is requiring basis data on community structure at different relevant spatial scales. In this regard, the diversity and the abundance of the macrobenthic communities in soft bottoms around coral reefs of this area were described in relation to different environmental factors. A seasonal sampling was conducted at two stations located in the east and west of Larak Island, respectively, during 4 seasons, from spring to winter 2012. A total of 20 species which belong to 20 genera and 14 families were identified. The macrobenthic density showed significant differences among seasons. The Shannon-Wiener index ranged from 2.07 to 2.89 indicating a moderate diversity in both stations. The maximum diversity of macrobenthic organisms was observed during spring. A non-metric multidimensional scaling (NMDS) analysis showed a large overlap in the macrobenthic community structure between the two stations. A principal component analysis (PCA) analysis indicated that the main environmental factors controlling macrobenthic density were phosphate, dissolved oxygen and total organic matter (TOM). Our results indicated that coral macrobenthic communities in Larak Island were characterized by low density and uniform distribution of species.

Impact of physicochemical parameters of water on the biodiversity of the invertebrate fauna from Echatt Lake, Northeast Algeria

“…However, it is not statically interpretable in the case of a comparison between several stands. This parameter gives a very important place to rare species (Tavanayan et al 2021). The total richness is important at station 1 with 16 species but less important at stations 2 and 4.…”

“…Shannon and equitability indexes remain dependent on sample size and habitat type, even when not disturbed. Therefore, it isn't easy to use them as a descriptor of an environmental state unless threshold values are first determined for each habitat type and a given sampled area (Tavanayan et al 2021).…”