title: Predicting species cover of marine macrophyte and invertebrate species combining hyperspectral remote sensing, machine learning and regression techniques.
abstract: In order to understand biotic patterns and their changes in nature there is an obvious need for high-quality seamless measurements of such patterns. If remote sensing methods have been applied with reasonable success in terrestrial environment, their use in aquatic ecosystems still remained challenging. In the present study we combined hyperspectral remote sensing and boosted regression tree modelling (BTR), an ensemble method for statistical techniques and machine learning, in order to test their applicability in predicting macrophyte and invertebrate species cover in the optically complex seawater of the Baltic Sea. The BRT technique combined with remote sensing and traditional spatial modelling succeeded in identifying, constructing and testing functionality of abiotic environmental predictors on the coverage of benthic macrophyte and invertebrate species. Our models easily predicted a large quantity of macrophyte and invertebrate species cover and recaptured multitude of interactions between environment and biota indicating a strong potential of the method in the modelling of aquatic species in the large variety of ecosystems.
authors.affiliation: Estonian Marine Institute, University of Tartu, Tallinn, Estonia. jonne.kotta@sea.ee
authors.forename: Jonne
authors.initials: J
authors.lastname: Kotta
authors.forename: Tiit
authors.initials: T
authors.lastname: Kutser
authors.forename: Karolin
authors.initials: K
authors.lastname: Teeveer
authors.forename: Ele
authors.initials: E
authors.lastname: Vahtmäe
authors.forename: Merli
authors.initials: M
authors.lastname: Pärnoja
mesh_terms: D000818:Animals; D059001:Aquatic Organisms / Q000502:physiology*; D001185:Artificial Intelligence; D017753:Ecosystem; D004957:Estonia; D005843:Geography; D007448:Invertebrates / Q000502:physiology*; D009792:Oceans and Seas; D025341:Principal Component Analysis; D012044:Regression Analysis; D058998:Remote Sensing Technology; D013045:Species Specificity