Benthic diversity patterns and predictors: A study case with inferences for conservation. (January 2020)

• Record Type: Journal Article
• Authors: Vassallo, Paolo; Paoli, Chiara; Aliani, Stefano; Cocito, Silvia; Morri, Carla; Bianchi, Carlo Nike
• Is Part Of: Marine pollution bulletin. Volume 150(2020)
• Publication Date: 2020-01
• Subjects: Macrobenthos -- Diversity -- Species richness -- Equitability -- Hot spots -- Marineprotectedareas -- Mediterranean Sea; Marine pollution -- Periodicals; Marine Biology -- Periodicals; Water Pollution -- Periodicals; Mer -- Pollution -- Périodiques; Publications périodiques; Pollution des mers; Lutte antipollution; Electronic journals; 363.7394
• DOI: 10.1016/j.marpolbul.2019.110748
• Languages: English
• ISSNs: 0025-326X

Abstract

Abstract: Understanding which drivers cause diversity patterns is a key issue in conservation. Here we applied a spatially explicit model to predict marine benthic diversity patterns according to environmental factors in the NW Mediterranean Sea. While most conservation-oriented diversity studies consider species richness only and neglect equitability, we measured separately species richness, equitability, and 'overall' diversity (i.e., the Shannon-Wiener H′ function) on a dataset of 890 benthic species × 209 samples. Diversity values were predicted by means of Random Forest regression, on the basis of 10 factors: depth, distance from the coast, distance from the shelf break, latitude, sea-floor slope, sediment grain size, sediment sorting, distance from harbours and marinas, distance from rivers, and sampling gear. Predictions by Random Forests were accurate, the main predictors being latitude, sediment grain size, depth and distance from the coast. Based on predicted values, diversity hotspots were identified as those localities where indices were in the 15% top segment of ranked values. Only a minority of the diversity hotspots was included within the boundaries of the protection institutes established in the region. Marine protected areas are often created in sites harbouring important coastal habitats, which risks neglecting the diversity hidden in the sedimentary seafloor. We suggest that marine protected areas should accommodate portions of sedimentary habitat within their boundaries to improve diversity conservation. Highlights: A spatially explicit model was applied to predict marine benthic diversity. Species richness, equitability, and the Shannon-Weaver function were analyzed. Predictions by random forests were accurate. A minority of the diversity hotspots were included in protected areas.