In the frame of Integrated Coastal Zone Management (ICZM) planners need tools to design and assess a sustainable state for the coast. Sustainability and progress indicator have to be integrated to identify improvements in the state of coastal zones as a result of ICZM implementation [1]. There are two useful approaches in order to take into account, system property, complexity and evolution, and integrating humans and bio-geospheres: system ecology (and ecosystem health concepts, as defined in [2]) and landscape science and ecology (as defined for example in [3–7]). The holistic approach in the context of human-nature relations is the real challenge of modern landscape ecology. It regards the background of increasing environmental problems and the discussion about sustainability [4] and for sustainability planning [8]. In the paper, it is proposed a brand new synthetic ecosystem indicator suited to monitoring regeneration plans of coastal zones: the Land Eco-Biodiversity. In order to have more benchmarks in assessing the state of implementation of a strategy, the plan, as well as from an ecosystemic point of view, is measured from a landscape point of view through Landscape Ecology indexes. In fact, the fragmentation of the landscape is part of the resource efficiency indicators defined by Eurostat in the context of monitoring the main objectives defined in the Europe 2020 strategy in the Category: “Nature and ecosystems | Biodiversity”. The study area is the Delta of Po River (Italy).

Ecosystem indicators and landscape ecology metrics as a tool to evaluate sustainable land planning in ICZM / Fiduccia, Andrea; Cattozzo, Luisa; Marotta, Leonardo; Filesi, Leonardo; Gugliermetti, Luca. - 11621:(2019), pp. 561-576. ((Intervento presentato al convegno 19th International Conference on Computational Science and Its Applications, ICCSA 2019 tenutosi a Saint Petersburg; Russia [10.1007/978-3-030-24302-9_40].

Ecosystem indicators and landscape ecology metrics as a tool to evaluate sustainable land planning in ICZM

Andrea Fiduccia
Conceptualization
;
Leonardo Filesi
Supervision
;
Luca Gugliermetti
2019

Abstract

In the frame of Integrated Coastal Zone Management (ICZM) planners need tools to design and assess a sustainable state for the coast. Sustainability and progress indicator have to be integrated to identify improvements in the state of coastal zones as a result of ICZM implementation [1]. There are two useful approaches in order to take into account, system property, complexity and evolution, and integrating humans and bio-geospheres: system ecology (and ecosystem health concepts, as defined in [2]) and landscape science and ecology (as defined for example in [3–7]). The holistic approach in the context of human-nature relations is the real challenge of modern landscape ecology. It regards the background of increasing environmental problems and the discussion about sustainability [4] and for sustainability planning [8]. In the paper, it is proposed a brand new synthetic ecosystem indicator suited to monitoring regeneration plans of coastal zones: the Land Eco-Biodiversity. In order to have more benchmarks in assessing the state of implementation of a strategy, the plan, as well as from an ecosystemic point of view, is measured from a landscape point of view through Landscape Ecology indexes. In fact, the fragmentation of the landscape is part of the resource efficiency indicators defined by Eurostat in the context of monitoring the main objectives defined in the Europe 2020 strategy in the Category: “Nature and ecosystems | Biodiversity”. The study area is the Delta of Po River (Italy).
19th International Conference on Computational Science and Its Applications, ICCSA 2019
ICZM; landscape ecology metrics; ecosystem indicators
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Ecosystem indicators and landscape ecology metrics as a tool to evaluate sustainable land planning in ICZM / Fiduccia, Andrea; Cattozzo, Luisa; Marotta, Leonardo; Filesi, Leonardo; Gugliermetti, Luca. - 11621:(2019), pp. 561-576. ((Intervento presentato al convegno 19th International Conference on Computational Science and Its Applications, ICCSA 2019 tenutosi a Saint Petersburg; Russia [10.1007/978-3-030-24302-9_40].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1315156
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