Biodiversity and ecosystem services in urban green infrastructure planning: A case study from the metropolitan area of Rome (Italy)

Capotorti, Giulia; Ortí, Marta María Alós; Copiz, R.; Fusaro, Lina; Mollo, Barbara; Salvatori, Elisabetta; Zavattero, Laura

doi:10.1016/j.ufug.2017.12.014

Cited by 68 publications

(33 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Higher ENI 1 values were assigned to sites with higher concentrations of air pollution, as they were considered to receive the greatest benefit from the GI in terms of air quality [21][22][23][24]. In particular, LID (planted-based types) reduces the concentrations of a variety of air pollutants that are known to increase health risks, such as fine atmospheric particulate matter (PM 2.5 ) [72,73].…”

Section: Environmental Index (Eni) Developmentmentioning

confidence: 99%

“…Higher ENI 2 values were assigned to sites with higher biodiversity to ensure the existing bio-habitats were maintained. GI provides potential bio-habitats, and consequently, prevents the impact of urbanization on existing habitats [14,21,[27][28][29][30][31][32]. For example, previous studies have shown that green roofs can host diverse plants and animals, as well as function as stepping stones to other nearby habitats, particularly for immobile organisms [74].…”

Section: Environmental Index (Eni) Developmentmentioning

confidence: 99%

See 1 more Smart Citation

The Low-Impact Development Demand Index: A New Approach to Identifying Locations for LID

Kaykhosravi

Abogadil

Khan

et al. 2019

Water

View full text Add to dashboard Cite

The primary goal of low impact development (LID) is to capture urban stormwater runoff; however, multiple indirect benefits (environmental and socioeconomic benefits) also exist (e.g., improvements to human health and decreased air pollution). Identifying sites with the highest demand or need for LID ensures the maximization of all benefits. This is a spatial decision-making problem that has not been widely addressed in the literature and was the focus of this research. Previous research has focused on finding feasible sites for installing LID, whilst only considering insufficient criteria which represent the benefits of LID (either neglecting the hydrological and hydraulic benefits or indirect benefits). This research considered the hydrological and hydraulic, environmental, and socioeconomic benefits of LID to identify sites with the highest demand for LID. Specifically, a geospatial framework was proposed that uses publicly available data, hydrological-hydraulic principles, and a simple additive weighting (SAW) method within a hierarchical decision-making model. Three indices were developed to determine the LID demand: (1) hydrological-hydraulic index (HHI), (2) socioeconomic index (SEI), and (3) environmental index (ENI). The HHI was developed based on a heuristic model using hydrological-hydraulic principles and validated against the results of a physical model, the Hydrologic Engineering Center-Hydrologic Modeling System model (HEC-HMS). The other two indices were generated using the SAW hierarchical model and then incorporated into the HHI index to generate the LID demand index (LIDDI). The framework was applied to the City of Toronto, yielding results that are validated against historical flooding records.

show abstract

Section: Environmental Index (Eni) Developmentmentioning

confidence: 99%

Section: Environmental Index (Eni) Developmentmentioning

confidence: 99%

The Low-Impact Development Demand Index: A New Approach to Identifying Locations for LID

Kaykhosravi

Abogadil

Khan

et al. 2019

Water

View full text Add to dashboard Cite

show abstract

“…For the GI design, the multi-step planning process applied in an urban sector of the Municipality of Rome [48] was resumed and properly customised to the peri-urban agricultural setting at issue. Therefore, for each of the steps 'Selection of the objective', 'Definition of project site', and 'Definition of GI components/actions' (Figure 2a), specific prioritisation criteria ( Figure 2b) that operate at different scales and decision levels ( Figure 2c) were defined:…”

Section: Overall Gi Design Processmentioning

confidence: 99%

“…Regarding the enhancement of ecological connectivity, plant dispersal capacity and positive relationships with faunal biodiversity were taken into account. Thus, species with short-distance dispersal potential and/or high capacity to provide food and shelter for wild animals were considered relevant [48,[77][78][79]. The suitability to support wild pollinators was derived from regional lists of melliferous flora, which display plant species with a significant nectar, pollen or honeydew production capacity [80,81].…”

mentioning

confidence: 99%

Local Scale Prioritisation of Green Infrastructure for Enhancing Biodiversity in Peri-Urban Agroecosystems: A Multi-Step Process Applied in the Metropolitan City of Rome (Italy)

2019

Self Cite

View full text Add to dashboard Cite

Urban–rural interfaces represent complex systems that require complex solutions for sustainable development and resilience against pollution, habitat fragmentation, biodiversity loss and impaired flux of ecosystem services (ES). Green infrastructure (GI) is increasingly recognised as an effective tool for addressing such a complexity, but needs priority setting to maximise benefits and minimise drawbacks of implementation. Therefore, a prioritisation approach focused on biodiversity and ES in peri-urban areas is required. In the present work, a systematic and hierarchical framework is proposed for setting priority GI objectives, location and actions aimed at enhancing local biodiversity, ES flux and farming sustainability in urban peripheries. By means of a case study in the Metropolitan City of Rome, the framework allowed identification of the main demand for ES and biodiversity; the most suitable location for GI implementation; and the best cost-effective actions. The GI implementation showed an improvement in terms of wooded hedgerow density, an increase regarding the ecological connectivity of riparian ecosystems, and an increment of agroecosystems designated to enhance the ecological network and wildlife support. Finally, the prioritisation framework contributes to fostering environmental benefits while complying with regulations and management practices from the regional to the farm/field decision level.

show abstract

“…Thus far, scholars of various research fields have discussed the structure and function of the ecological network [3], as well as its construction and assessment [4,5]. In addition, they have also conducted a great deal of research about biodiversity protection [6,7], natural reserve design [8], optimization and assessment of urban (regional) landscape [9,10], landscape planning and design [11,12], forest management [13], land use planning and assessment [14], and ESP [1,15], etc. The research involving ecological networks and ecological security can be mainly divided into following three types: (1) improving the spatial structure of ecosystem; (2) protecting ecological functions and processes (like the habitat reconstruction of crucial species); (3) coupling ecosystem services (like ecology, entertainment and aesthetics).…”

Section: Introductionmentioning

confidence: 99%

The Construction of a Regional Ecological Security Pattern Based on Circuit Theory

Jiu-lin

Chu

2019

Sustainability

View full text Add to dashboard Cite

The construction of an ecological security pattern (ESP) is one of the basic methods to protect regional ecological security and enhance people’s well-being. In the case of Anhui province, located in the Yangtze River Delta region of China, regional ecological sources were assessed and recognized in terms of ecosystem services, and regional ESP was then constructed based on circuit theory. Current density was applied to analyze the significance of patches and corridors and recognize sticking points, and thereby strategies were introduced to optimize regional ESP. Results of ecosystem services function assessment showed that there were 47 ecological patches, 107 ecological corridors, 16 pinch points, and six sticking points in the ESP of Anhui province. The watershed of the Yangtze and Huai rivers divides the ESP of the northern and southern Anhui, which has huge landscape spatial heterogeneity. Areas with relatively good ecological resources were basically located between Dabie Mountain area in the west and the low hilly area in the south of Anhui, with mostly woodland and farmland as ecological sources. However, cities in the northern Anhui, also in the north of the watershed of the Yangtze and Huai rivers, face severe situations in terms of environmental protection. This study conducted spatial analyses on ESP with different thresholds and proposed to classify different ESPs according to ecological control. This helps to alleviate the contradiction between economic development and environmental protection, and improve the supply capacity of regional ecosystem services, in order to satisfy the regional demand for ecosystem services. Meanwhile, this study offers more methods to construct regional ESP and introduces targeted measures to improve connectivity, which is of practical guidance for the connectivity and optimization of ecological patterns.

show abstract

Biodiversity and ecosystem services in urban green infrastructure planning: A case study from the metropolitan area of Rome (Italy)

Cited by 68 publications

References 42 publications

The Low-Impact Development Demand Index: A New Approach to Identifying Locations for LID

The Low-Impact Development Demand Index: A New Approach to Identifying Locations for LID

Local Scale Prioritisation of Green Infrastructure for Enhancing Biodiversity in Peri-Urban Agroecosystems: A Multi-Step Process Applied in the Metropolitan City of Rome (Italy)

The Construction of a Regional Ecological Security Pattern Based on Circuit Theory

Contact Info

Product

Resources

About