1. Ostracods are important components of groundwater communities that are influenced by abiotic environmental conditions and biotic interactions. We aimed to identify the factors associated with ostracod assemblages inhabiting groundwaters accessed through dug wells in several regions of Benin in West Africa, exposed to chronic influences of anthropogenic disturbances such as nutrient enrichment from infiltration of sewage or fertilisers from the surface. 2. Ostracods were collected from 219 wells in seven catchment areas using two complementary methods: active sampling with a phreatobiological net and passive trapping with a baited trap. Associations with 31 statistical predictor variables (a range of abiotic descriptors of water, hydrology, protection, usage and the type of well) and ostracod occurrence was evaluated using distance-based linear models and redundancy analysis. 3. We identified 60 ostracod species representing two ecological groups: 36 species of stygobites of the family Candonidae, an endemic species flock of a vast evolutionary radiation, and 24 species of non-stygobites, mostly of the family Cyprididae. This is the first large groundwater ostracod species flock reported from the entire African continent. 4. A number of variables associated with the structure of ostracod assemblages were identified. Except for the descriptors of wells, these included well-known chemical and physical properties (electrical conductivity, pH, temperature or bicarbonate concentration), but also the concentration of NO2−. Although NO2− has not yet been demonstrated to be important for ostracod assemblages, stygobites occurred significantly less frequently in higher concentrations of NO2− than most non-stygobites. 5. We determined that stygobitic (candonid) ostracod species and genera may be a good potential environmental indicator of groundwater quality especially nitrite pollution of groundwater in tropical West Africa. 6. In tropical West Africa, many human populations rely on groundwater for domestic use and agricultural irrigation, while these aquatic resources are also often affected by anthropogenic disturbances. The use of stygobitic ostracods as potential indicators of groundwater quality offers a valuable tool for environmental monitoring and protection in tropical regions in West Africa, and may be also globally.
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RBINS Staff Publications 2025
Subtidal natural hard substrates (SNHS) promote occupancy by rich benthic communities that provide irreplaceable and fundamental ecosystem functions, representing a global priority target for nature conservation and recognised in most European environmental legislation. However, scientifically validated methodologies for their quantitative spatial demarcation, including information on species occupancy and fine-scale environmental drivers (e.g., the effect of stone size on colonisation) are rare. This is, however, crucial information for sound ecological management. In this investigation, high-resolution (1 m) multibeam echosounder (MBES) depth and backscatter data and derivates, underwater imagery (UI) by video drop-frame, and grab sediment samples, all acquired within 32 km2 of seafloor in offshore Belgian waters, were integrated to produce a random forest (RF) spatial model, predicting the continuous distribution of the seafloor areal cover/m2 of the stones’ grain sizes promoting colonisation by sessile epilithic organisms. A semi-automated UI acquisition, processing, and analytical workflow was set up to quantitatively study the colonisation proportion of different grain sizes, identifying the colonisation potential to begin at stones with grain sizes Ø ≥ 2 cm. This parameter (i.e., % areal cover of stones Ø ≥ 2 cm/m2) was selected as the response variable for spatial predictive modelling. The model output is presented along with a protocol of error and uncertainty estimation. RF is confirmed as an accurate, versatile, and transferable mapping methodology, applicable to area-wide mapping of SNHS. UI is confirmed as an essential aid to acoustic seafloor classification, providing spatially representative numerical observations needed to carry out quantitative seafloor modelling of ecologically relevant parameters. This contribution sheds innovative insights into the ecologically relevant delineation of subtidal natural reef habitat, exploiting state-of-the-art underwater remote sensing and acoustic seafloor classification approaches.
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RBINS Staff Publications 2021
