Assessment of State Transition Dynamics of Coastal Wetlands in Northern Venice Lagoon, Italy

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 not...

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Main Authors: Andrea Taramelli, Emiliana Valentini, Laura Piedelobo, Margherita Righini, Sergio Cappucci
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:Sustainability
Subjects:
Online Access:https://www.mdpi.com/2071-1050/13/8/4102
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spelling doaj-30cbd045d8b54ab1b05145659912a5d42021-04-07T23:02:34ZengMDPI AGSustainability2071-10502021-04-01134102410210.3390/su13084102Assessment of State Transition Dynamics of Coastal Wetlands in Northern Venice Lagoon, ItalyAndrea Taramelli0Emiliana Valentini1Laura Piedelobo2Margherita Righini3Sergio Cappucci4Istituto Universitario di Studi Superiori di Pavia (IUSS), Palazzo del Broletto, Piazza della Vittoria 15, 27100 Pavia, ItalyInstitute for Environmental Protection and Research (ISPRA), via Vitaliano Brancati 48, 00144 Roma, ItalyIstituto Universitario di Studi Superiori di Pavia (IUSS), Palazzo del Broletto, Piazza della Vittoria 15, 27100 Pavia, ItalyIstituto Universitario di Studi Superiori di Pavia (IUSS), Palazzo del Broletto, Piazza della Vittoria 15, 27100 Pavia, ItalyTerritorial and Production Systems Sustainability Department, Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), via Anguillarese 301, 00123 Rome, ItalyCoastal 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 not fully understood. This work aims at detecting and improving the understanding of the transition dynamics on eco-geomorphological structures in a coastal wetland ecosystem. The approach could support sustainable habitat management improving the detection and optimizing the offer of Earth Observation (EO) products for coastal system monitoring. Such course of action will strengthen evidence-based policy making, surface biophysical data sovereignty and the Space Data downstream sector through remote sensing techniques thanks to the capability of investigating larger scale and short-to-long-term dynamics. The selected case study is the Lido basin (Venice Lagoon, Italy). Our methodology offers a support in the framework of nature-based solutions, allowing the identification of ecosystem-level indicators of the surface biophysical properties influencing stability and evolution of intertidal flats on which a conceptual model is implemented. Landsat satellite imagery is used to delineate the spatial and temporal variability of the main vegetation and sediment typologies in 1990–2011. Within this period, specific anthropic activities were carried out for morphological restoration and flood protection interventions. Specifically, the lower saltmarsh shows its more fragmented part in the Baccan islet, a residual sandy spit in front of the Lido inlet. The area covered by <i>Sarcocornia-Limonium</i>, that triggers sediment deposition, has fluctuated yearly, from a minimum coverage of 13% to a maximum of 50%. The second decade (2001–2009) is identified as the period with major changes of halophytic and Algae-Biofilm cover typologies distribution. The power law and related thresholds, representing the patch size frequency distribution, is an indicator of the ecosystem state transition dynamics. The approach, based on multi-temporal and spatial EO analysis, is scalable elsewhere, from regional to local-to-global scale, considering the variability of climate data and anthropogenic activities. The present research also supports sustainable habitat management, improving the detection, and optimizing the offer of EO products for coastal system monitoring.https://www.mdpi.com/2071-1050/13/8/4102coastal wetlandbio-geomorphologyVenice Lagoonsatellite remote sensingLandsatLinear Spectral Mixture Analysis
collection DOAJ
language English
format Article
sources DOAJ
author Andrea Taramelli
Emiliana Valentini
Laura Piedelobo
Margherita Righini
Sergio Cappucci
spellingShingle Andrea Taramelli
Emiliana Valentini
Laura Piedelobo
Margherita Righini
Sergio Cappucci
Assessment of State Transition Dynamics of Coastal Wetlands in Northern Venice Lagoon, Italy
Sustainability
coastal wetland
bio-geomorphology
Venice Lagoon
satellite remote sensing
Landsat
Linear Spectral Mixture Analysis
author_facet Andrea Taramelli
Emiliana Valentini
Laura Piedelobo
Margherita Righini
Sergio Cappucci
author_sort Andrea Taramelli
title Assessment of State Transition Dynamics of Coastal Wetlands in Northern Venice Lagoon, Italy
title_short Assessment of State Transition Dynamics of Coastal Wetlands in Northern Venice Lagoon, Italy
title_full Assessment of State Transition Dynamics of Coastal Wetlands in Northern Venice Lagoon, Italy
title_fullStr Assessment of State Transition Dynamics of Coastal Wetlands in Northern Venice Lagoon, Italy
title_full_unstemmed Assessment of State Transition Dynamics of Coastal Wetlands in Northern Venice Lagoon, Italy
title_sort assessment of state transition dynamics of coastal wetlands in northern venice lagoon, italy
publisher MDPI AG
series Sustainability
issn 2071-1050
publishDate 2021-04-01
description 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 not fully understood. This work aims at detecting and improving the understanding of the transition dynamics on eco-geomorphological structures in a coastal wetland ecosystem. The approach could support sustainable habitat management improving the detection and optimizing the offer of Earth Observation (EO) products for coastal system monitoring. Such course of action will strengthen evidence-based policy making, surface biophysical data sovereignty and the Space Data downstream sector through remote sensing techniques thanks to the capability of investigating larger scale and short-to-long-term dynamics. The selected case study is the Lido basin (Venice Lagoon, Italy). Our methodology offers a support in the framework of nature-based solutions, allowing the identification of ecosystem-level indicators of the surface biophysical properties influencing stability and evolution of intertidal flats on which a conceptual model is implemented. Landsat satellite imagery is used to delineate the spatial and temporal variability of the main vegetation and sediment typologies in 1990–2011. Within this period, specific anthropic activities were carried out for morphological restoration and flood protection interventions. Specifically, the lower saltmarsh shows its more fragmented part in the Baccan islet, a residual sandy spit in front of the Lido inlet. The area covered by <i>Sarcocornia-Limonium</i>, that triggers sediment deposition, has fluctuated yearly, from a minimum coverage of 13% to a maximum of 50%. The second decade (2001–2009) is identified as the period with major changes of halophytic and Algae-Biofilm cover typologies distribution. The power law and related thresholds, representing the patch size frequency distribution, is an indicator of the ecosystem state transition dynamics. The approach, based on multi-temporal and spatial EO analysis, is scalable elsewhere, from regional to local-to-global scale, considering the variability of climate data and anthropogenic activities. The present research also supports sustainable habitat management, improving the detection, and optimizing the offer of EO products for coastal system monitoring.
topic coastal wetland
bio-geomorphology
Venice Lagoon
satellite remote sensing
Landsat
Linear Spectral Mixture Analysis
url https://www.mdpi.com/2071-1050/13/8/4102
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