Model-based analysis of the relationship between macroinvertebrate traits and environmental river conditions. (August 2018)

• Record Type: Journal Article
• Authors: Forio, Marie Anne Eurie; Goethals, Peter L.M.; Lock, Koen; Asio, Victor; Bande, Marlito; Thas, Olivier
• Is Part Of: Environmental modelling & software. Volume 106(2018)
• Page Start: 57
• Page End: 67
• Publication Date: 2018-08
• Subjects: Negative binomial regression -- Feeding strategies -- Flow velocity -- Tropical island -- Generalized linear models -- Philippines; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2017.11.025
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Aquatic macroinvertebrates, 18 physical-chemical water characteristics and 30 hydromorphological variables were assessed at 85 locations on Leyte island, Philippines. Biological traits derived from literature were linked to the biological samples based on four different trait estimation methods. These data were used to determine the relation with river characteristics using negative binomial regression. At least five feeding habit modalities were associated with conductivity, velocity, pH, temperature, ammonium-N concentrations, and sediment. The various methods of estimating trait abundance differ in determined major patterns and ecological implications. Therefore, the estimation method used should be explicitly described in trait-related papers to avoid misinterpretation. Trait abundance-environment relationships can be linear or non-linear and therefore a careful selection of the functional relationship should be performed. The process of extracting knowledge from data is of paramount importance as relevant ecological insights were extracted providing insights on flow, wastewater and nutrient management in the rivers. Highlights: Biological traits were modelled with environmental river characteristics on a tropical island (Philippines). Four data processing methodologies resulted in very different estimates of trait abundance. The different methods of estimating trait abundance vary in determined major patterns and ecological implications. Trait-environment relationships can be linear or non-linear, thus, selection of functional relationship should be performed. Trait abundances increased with increasing velocity, thus flow alterations may have serious ecological implications.