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A national green planning strategy has recently been introduced in the Italian urban planning sector, aimed at making all local initiatives undertaken nationwide consistent with each other. At a regional level, Friuli Venezia-Giulia has recently implemented a Landscaping Plan, which is of an urban planning and ecological nature at an intermediate level between national and local. This article describes the local green plan of Latisana, which has been titled Ecopolitana, given that it represents the experimental phase, at a regional level, of the possibilities offered by landscape planning and design. Specifically, it outlines the multi-disciplinary approach used, demonstrating how landscape planning can be compared to the sustainable development of cities, with specific regard to the agricultural sector. In this regard, a low-intensity cropping model is also suggested, based on the principles of agroecology and landscape ecology, which has already been implemented in the historical rural landscape of Plasencis (UD) and investigated through GIS analysis and remote sensing processes. Its aim is to be the starting point for the achievement of the goals set in the 2030 Agenda, especially Goals 13 (climate action) and 15 (life on land), given the current scarcity of agroecological infrastructures in the area of Latisana (UD) and the high percentage of soil used for intensive cropping. [ABSTRACT FROM AUTHOR]

Increased frequency of tree mortality and forest decline due to anomalous drought events calls for the adoption of effective monitoring of tree water status over large spatial and temporal scales. We correlated field-measured and remotely sensed plant water status parameters, to test the possibility of monitoring the risk of drought-induced dehydration and hydraulic failure using satellite images calibrated on reliable physiological indicators of tree hydraulics. The study was conducted during summer 2019 in the Karst plateau (NE Italy) in a woodland dominated by Fraxinus ornus L.; Sentinel-2 images were acquired on a seasonal scale on the same dates when absolute water content (AbWC), relative water content (RWC), and minimum water potential (Ψmin) were measured in the field. Plant water status parameters were correlated with normalized difference vegetation index (NDVI and NDVI 8A), normalized difference water index (NDWI), and soil-adjusted vegetation index (SAVI). Significant Pearson and Spearman linear correlations (α < 0.05) emerged between all tree-level measured variables and NDWI, while for NDVI, NDVI 8A, and SAVI no correlation was found. Our results suggest the possibility of using the NDWI as a proxy of tree water content and water potential. [ABSTRACT FROM AUTHOR]

On the 29th of October 2018, a storm named "Vaia" hit North-Eastern Italy, causing the loss of 8 million m3 of standing trees and creating serious damage to the forested areas, with many economic and ecological implications. This event brought up the necessity of a standard procedure for windthrow detection and monitoring based on satellite data as an alternative to foresters' fieldwork. The proposed methodology was applied in Carnic Alps (Friuli Venezia Giulia, NE Italy) in natural stands dominated by Picea abies and Abies alba. We used images from the Sentinel-2 mission: 1) to test vegetation indices performance in monitoring the vegetation dynamics in the short period after the storm, and 2) to create a windthrow map for the whole Friuli Venezia Giulia region. Results showed that windthrows in forests have a significant influence on visible and short-wave infrared (SWIR) spectral bands of Sentinel-2, both in the short and the long-term timeframes. NDWI8A and NDWI were the best indices for windthrow detection (R2 = 0.80 and 0.77, respectively) and NDVI, PSRI, SAVI and GNDVI had an overall good performance in spotting wind-damaged areas (R2 = 0.60–0.76). Moreover, these indices allowed to monitor post-Vaia forest die-off and showed a dynamic recovery process in cleaned sites. The NDWI8A index, employed in the vegetation index differencing (VID) change detection technique, delimited damaged areas comparable to the estimations provided by Regional Forest System (2545 ha and 3183 ha, respectively). Damaged forests detected by NDWI8A VID ranged from 500 m to 1500 m a.s.l., mainly covering steep slopes in the south and east aspects (42% and 25%, respectively). Our results suggested that the NDWI8A VID method may be a cost-effective and accurate way to produce windthrow maps, which could limit the risks associated with fieldwork and may provide a valuable tool to plan tree removal interventions in a more efficient way. [ABSTRACT FROM AUTHOR]

Biological invasions are deemed to be the second most important global driver of biodiversity loss, right behind habitat destruction and fragmentation. In this study, we aimed at testing if community invasibility, defined as the vulnerability to invasion of a community, could be associated with the characteristics of a given habitat, as described by the composition and structure of its native species. Based on a probabilistic sampling of the alien flora occurring in the temperate wetland Lake Doberdò (Friuli Venezia Giulia region, NE Italy) and using a null-model-based approach, the observed occurrence of Invasive Alien Species (IAS) within sampling units was randomized within habitats. While testing the degree of invasibility for each habitat within the wetland, our null hypothesis postulated that habitats are equally invaded by IAS, as IAS can spread homogeneously in the environment thanks to their plasticity in functional traits that makes them able to cope with different ecological conditions. The obtained results comparing observed IAS frequencies, abundance and richness to those obtained by the null model randomizations show that, for all habitats, invasion was selective. Specifically, a marked preference for habitats with an intermediate disturbance level, a high nutrients level and a medium-high light availability was observed, while an avoidance was detected for habitats characterized by lower levels of nutrients and light availability or extreme conditions caused by prolonged submersion. This method allows us to provide useful information using a simple-to-run simulation for the management of the IAS threat within protected areas. Moreover, the method allows us to infer important ecological characteristics leading to habitat invasion without sampling the environmental characteristic of the habitats, which is an expensive operation in terms of time and money. [ABSTRACT FROM AUTHOR]