Identification of ecosystem-level indicators to assess the state transition dynamics in a coastal wetland: Case study of a shallow tidal basin of the Venice lagoon

Abstract:

Coastal wetlands represent complex ecosystems prone to continuous changes. These changes are especially standing out nowadays due to the existing feedback loop between the impact of climate change and anthropic activities, ecosystem degradation and increase risk of natural disaster. Coastal wetlands represent particularly valuable natural resources, characterized by the interaction between their geomorphological and biological components. Their adaptation to the changing conditions depends on the rate and extent of spatial and temporal processes and their response is still poorly understood. Therefore, this work aims to improve the understanding of the transition dynamics in the evolution of eco-geomorphological structures in a coastal wetland ecosystem. To this end, the spatial patterns of the main vegetation and sediment typologies and their variation over time are analyzed by means of discrete and continuous analyses of spectral data, respectively. Landsat images from 1991 to 2011, field spectral library acquired in June of 2013, as well as yearly data of the mean sea level rise and the tide level, represent the input data used. The Linear Spectral Mixture Analysis, the Empirical Orthogonal Function and the Power Law Distribution are the data analysis techniques performed. The selected case study is the Venice lagoon, particularly its North-Eastern part: The Lido basin. The analysis allows identifying ecosystem-level indicators to assess the state transition dynamics, as well as the existence of external threats that increase the vulnerability of the coastal ecosystem. Specifically, conceptual models that link the sedimentology, the biology and the hydrodynamics acting within the Venice Lagoon, together with the spatiotemporal analysis performed, allow showing how vegetation can control the sediment stability during exposure of the intertidal mudflat and how morpho-biological changes can be detected by open satellite data.