Author:
Tamvakis Androniki, ,Tsirtsis George,Karydis Michael,Patsidis Kleanthis,Kokkoris Giorgos D.
Abstract
<abstract>
<p>Harmful algal species are present in the Mediterranean Sea and are often associated with toxic events affecting the nearby coastal zones. The presence of 18 marine microalgae, at genus level, associated with potentially harmful characteristics was predicted using a number of machine learning techniques based exclusively on a small set of abiotic variables, already identified as drivers of blooms. Random Forest (RF) algorithm achieved the best predictive performance by correctly identifying the presence of most genera with a mean of 89.2% of total samples. Although, RF has shown lower predictive performance for genera present in a low number of samples, its predictive power remains at least "fair' in these cases. The main tree-based advantage of RF was thereafter used to assess the importance of the input variables in predicting the presence of the algal genera. Temperature had the most powerful effect on genera's presences, although this effect varies among genera. Finally, the genera were clustered based on their response to the considered abiotic variables and common trends in an ecological context were identified.</p>
</abstract>
Publisher
American Institute of Mathematical Sciences (AIMS)
Subject
Applied Mathematics,Computational Mathematics,General Agricultural and Biological Sciences,Modeling and Simulation,General Medicine
Reference86 articles.
1. M. I. Jordan, T. M. Mitchell, Machine learning: Trends, perspectives and prospects, Science, 349 (2015), 255-260.
2. E. Alpaydin, Introduction to machine learning, 2nd Ed., The MIT Press, Cambridge, (2010).
3. C. Crisci, B. Ghattas, G. Perera, A review of supervised machine learning algorithms and their applications to ecological data, Ecol. Modell., 240 (2012), 113-122.
4. G. P. Harris, Phytoplankton ecology: structure, function and fluctuation, Chapman and Hall, London, 1986.
5. K. H. Mann, J. R. N. Lazier, Dynamics of marine ecosystems: biological-physical interactions in the Oceans, Blackwell Scientific Publications, Oxford, (1991).
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