Abstract
The distribution of benthic ecosystems, dominated by filter-feeding communities, is highly influenced by the seabed geomorphology. However, the spatial variation in settlement of these species is also affected by near-bottom currents and any changes in light, nutrient concentration and food quality often associated with increases of suspended sediment concentrations within the water column. Detailed predictions of the geographic distribution of filter-feeder species and a deeper understanding of the physical processes influencing their distribution patterns is key for effective management and conservation. To date, predictive distribution modelling has been derived essentially from geomorphological parameters, mainly using spatially limited observations. In this study, seabed mapping, oceanographic modelling, hydrographic records and biological observations are integrated to provide high-resolution prediction of filter-feeder habitat distribution within Queen Charlotte Sound/Tōtaranui and Tory Channel/Kura Te Au, South Island of New Zealand. The aim is to evaluate potential suitable habitat areas for filter-feeders to inform where habitat restoration management should focus efforts to recover communities such as the horse mussel (Atrina zelandica) or the green-lipped mussel (Perna canaliculus), both of which have high economic impact in New Zealand. To accomplish this, Maximum Entropy (MaxEnt) predictive modelling was used to produce Habitat Suitability (HS) maps, using geomorphological parameters and seafloor classification information. Final HS maps also incorporated oceanographic and sediment dynamic information, showing that filter-feeder habitat distribution is highly influenced by the hydrodynamics and sedimentary processes apart from the seafloor geomorphology. Filter-feeder communities inhabit quiescent areas, limited by depth, slope and sediment type; and coincide with regions presenting low near-bottom currents and low turbidity levels. Additionally, the obtained results reveal the effects of the coastal settlements and major marine traffic routes, limiting the suitable habitats to areas with less human impact. This study demonstrates that a multidisciplinary approach is crucial to better predict the spatial distribution of benthic communities, which is key to improve benthic habitat restoration and recovery assessments.
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