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• W2519544165 abstract "Inconsistent performance of Species Distribution Models (SDMs), which may depend on several factors such as the initial conditions or the applied modelling technique, is one of the greatest challenges in ecological modelling. To overcome this problem, ensemble modelling combines the forecasts of several individual models. A commonly applied ensemble modelling technique is the Multi–Layer Perceptron (MLP) Ensemble, which was envisaged in the 1990s. However, despite its potential for ecological modelling, it has received little attention in the development of SDMs for freshwater fish. Although this approach originally included all the developed MLPs, Genetic Algorithms (GA) now allow selection of the optimal subset of MLPs and thus substantial improvement of model performance. In this study, MLP Ensembles were used to develop SDMs for the redfin barbel (Barbus haasi; Mertens, 1925) at two different spatial scales: the micro–scale and the meso–scale. Finally, the potential of the MLP Ensembles for environmental flow (e–flow) assessment was tested by linking model results to hydraulic simulation. MLP Ensembles with a candidate selection based on GA outperformed the optimal single MLP or the ensemble of the whole set of MLPs. The micro–scale model complemented previous studies, showing high suitability of relatively deep areas with coarse substrate and corroborating the need for cover and the rheophilic nature of the redfin barbel. The meso–scale model highlighted the advantages of using cross–scale variables, since elevation (a macro–scale variable) was selected in the optimal model. Although the meso–scale model also demonstrated that redfin barbel selects deep areas, it partially contradicted the micro–scale model because velocity had a clearer positive effect on habitat suitability and redfin barbel showed a preference for fine substrate in the meso–scale model. Although the meso–scale model suggested an overall higher habitat suitability of the test site, this did not result in a notable higher minimum environmental flow. Our results demonstrate that MLP Ensembles are a promising tool in the development of SDMs for freshwater fish species and proficient in e–flow assessment." @default.
• W2519544165 created "2016-09-23" @default.
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• W2519544165 date "2017-01-01" @default.
• W2519544165 modified "2023-09-26" @default.
• W2519544165 title "On species distribution modelling, spatial scales and environmental flow assessment with Multi–Layer Perceptron Ensembles: A case study on the redfin barbel (Barbus haasi; Mertens, 1925)" @default.
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• W2519544165 doi "https://doi.org/10.1016/j.limno.2016.09.004" @default.
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