Abstract:
Macroinvertebrates are important as ecosystem engineers that perform diverse ecosystem
functions to sustain ecosystem resilience. This study was conducted to assess the taxonomic and
functional diversity of macroinvertebrates and to understand the environmental drivers of their
community composition in Rekawa Lagoon. Physico-chemical parameters of water (temperature,
salinity, conductivity, pH, dissolved oxygen concentration, total dissolved solids, depth, and Secchi
depth) and sediment samples were collected from seven sites in the Rekawa lagoon during
September 2023. We identified macroinvertebrate species and calculated taxonomic and
functional diversity indexes. The correlation analysis, ANOVA, and redundancy analysis (RDA)
were performed to understand variations in macroinvertebrate species composition/diversity
indexes and their link to the environmental variables. There were nine species of benthic
macroinvertebrates named Grandidierella sp., Gammarus sp., Alitropus typus, Sphaerodema
rusticum, Chironomus sp. larvae, Melanoides tuberculata, Nassarius sp., Lymnaea stagnalis, and
Nereis sp. were in the lagoon. Shannon-Weiner index in sites 1, 2, and 6 was significantly higher
than in site 7. The highest functional richness (Fric) was recorded on site 5 as 16.44±0.73 and the
lowest on site 7 as 0.92±0.00. The lowest functional dispersion (Fdis) was also recorded at site 7
as 2.05±0.38 and it was significantly lower than sites 1, 2, 5, and 6. Overall, Site 7 showed
significantly lower functional diversity indexes compared to other sites that are characterized by
high salinity and conductivity in water. Gammarus sp. were highly correlated with DO
concentration. Grandidierella sp. and Chironomus sp. larvae were highly associated with soil
organic content. Our study gives insights into how site-specific management practices are needed
to manage and conserve the biodiversity of Rekawa Lagoon. Furthermore, we recommend
studying the functional diversity of the ecosystems which reveal different and more information
than traditional taxonomic indexes to understand our ecosystems.
