The present study is an attempt to deepen the knowledge about energy patterns in a detritus based ecosystem located within a temporary wetland, where changes of water level can affect productivity, turnover of organic matter and the flow-through energy. Energy density was directly measured using an adiabatic bomb calorimeter in samples collected in autumn, spring and summer. Dipterans belonging to the genus Chironomus were the most common and representative invertebrates within the study area. Starting from these measures, a predictive model based on the relationship between energy density and percentage of dry weight was developed, validated and applied to build a multi-annual dataset. This model was used to investigate seasonal energy density trends on longer time-scale, in relation to physical and chemical features, weather conditions and decomposition dynamics. The used approach allowed to build a 3-year dataset and to identify clear seasonal trends; moreover, the application of the model highlighted patterns in relation to precipitation regime, decomposition dynamics and the effects due to variations of these features in the investigated temporary detritusbased system over a multi-annual scale.
Seasonal multi-annual trends in energy densities of the midges (genus Chironomus) in a Mediterranean temporary wetland (Natural Regional Reserve of the Isonzo River Mouth, Northeast Italy)
Marco BertoliInvestigation
;Paolo PastorinoMembro del Collaboration Group
;Alberto BassetMembro del Collaboration Group
;Elisabetta PizzulSupervision
2018-01-01
Abstract
The present study is an attempt to deepen the knowledge about energy patterns in a detritus based ecosystem located within a temporary wetland, where changes of water level can affect productivity, turnover of organic matter and the flow-through energy. Energy density was directly measured using an adiabatic bomb calorimeter in samples collected in autumn, spring and summer. Dipterans belonging to the genus Chironomus were the most common and representative invertebrates within the study area. Starting from these measures, a predictive model based on the relationship between energy density and percentage of dry weight was developed, validated and applied to build a multi-annual dataset. This model was used to investigate seasonal energy density trends on longer time-scale, in relation to physical and chemical features, weather conditions and decomposition dynamics. The used approach allowed to build a 3-year dataset and to identify clear seasonal trends; moreover, the application of the model highlighted patterns in relation to precipitation regime, decomposition dynamics and the effects due to variations of these features in the investigated temporary detritusbased system over a multi-annual scale.File | Dimensione | Formato | |
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