Understanding and explaining the use of green spaces and forests is challenging for sustainable urban planning. In recent years there has been increasing demand for novel approaches to investigate urban green infrastructure by capitalizing on large databases from existing citizen science tools. In this study, we analyzed iNaturalist data to perform an assessment of the intentional use of these urban spaces for their value and to understand the main drivers. We retrieved the total number of observations obtained across a set of 672 European cities and focused on reporting from mapped green areas and forests. We used two separate multivariate explanatory models to investigate which factors explained variations in the number of observations for green areas and forests. We found a relatively heterogeneous use of these two urban green spaces. Gross domestic product was important in explaining the number of visits. Availability and accessibility also had positive relationships with the use of green areas and forests in cities, respectively. This study paves the way for better integration of citizen science data in assessing cultural services provided by urban green infrastructure and therefore in supporting the evaluation of spatial planning policies for the sustainable development of urban areas.

Green spaces and trees are fundamental for the sustainability of cities. The use of management and planning indicators for green spaces, including urban forests, have been proposed, but are rarely applied and their potential to provide ecological, social, and economic benefits is usually overlooked by policy makers and managers. Here, we apply a set of indicators describing green spaces and their variability in different urban units within the Basso Isonzo, an area of the city of Padua (northern Italy). Eleven indicators were selected based on their capacity to consider availability, accessibility and the preservation or increase of urban green spaces and tree cover. The value of indicators was standardized and enabled to have five classes indicating increasing performance. The study indicates green spaces’ heterogeneous conditions. Interestingly, the indicators commonly change moving from the city center to the outskirts. Monitoring through these indicators will enable understanding whether specific management and planning targets are met and, in the absence of these targets, identifying main trends over time. The proposed approach and indicators applied are simple to collect, analyze, and convey information. The indicators are related to relevant social, economic and ecological conditions pertaining to green spaces. The proposed indicators can therefore be used as a simple tool to guide decision-making with the aim of enhancing green spaces.

Aim: To propose a Finite Mixture Model (FMM) as an additional approach for classifying large datasets of georeferenced vegetation plots from complex vegetation systems. Study area: The Italian peninsula including the two main islands (Sicily and Sardinia), but excluding the Alps and the Po plain. Methods: We used a database of 5,593 georeferenced plots and 1,586 vascular species of forest vegetation, created in TURBOVEG by storing published and unpublished phytosociological plots collected over the last 30 years. The plots were classified according to species composition and environmental variables using a FMM. Classification results were compared with those obtained by TWINSPAN algorithm. Groups were characterized in terms of ecological parameters, dominant and diagnostic species using the fidelity coefficient. Interpretation of resulting forest vegetation types was supported by a predictive map, produced using discriminant functions on environmental predictors, and by a non‐metric multidimensional scaling ordination. Results: FMM clustering obtained 24 groups that were compared with those from TWINSPAN, and similarities were found only at a higher classification level corresponding to the main orders of the Italian broadleaf forest vegetation: Fagetalia sylvaticae, Carpinetalia betuli, Quercetalia pubescenti-petraeae and Quercetalia ilicis. At lower syntaxonomic level, these 24 groups were referred to alliances and sub-alliances. Conclusions: Despite a greater computational complexity, FMM appears to be an effective alternative to the traditional classification methods through the incorporation of modelling in the classificatory process. This allows classification of both the co-occurrence of species and environmental factors so that groups are identified not only on their species composition, as in the case of TWINSPAN, but also on their specific environmental niche. Taxonomic reference: Conti et al. (2005). Abbreviations: CLM = Community-level models; FMM = Finite Mixture Model; NMDS = non‐metric multidimensional scaling.

We analysed the floristic subdivisions of Albania by hierarchical clustering of all the vascular plant species of Albania over a grid of 25 km cells, adapting data from the Vascular Species Distribution Atlas in Albania of ( Barina Z (ed.) (2017) Distribution atlas of vascular plants in Albania. Hungarian Natural History Museum, Budapest). We identified the principal axes of variation of the flora and the bioclimatic variables that explain it. We also analysed the bioclimate of Albania by means of a self-organizing map (SOM) of the main climatic variables and the application of the global bioclimatic model of Rivas-Martínez. We compared the analysis based on the flora with that based on the bioclimate. The results divided Albania into eight floristic units corresponding to the main vegetation types (Carpinus orientalis woodlands, Quercus cerris woodlands, Quercus petraea and Fagus sylvatica woodlands, Quercus coccifera woodlands, Quercus coccifera and Quercus ithaburensis woodlands, Pinus heldreichii woodlands, alpine vegetation of North Albania, and alpine vegetation of eastern Albania). Two main trends of variation can be recognized: four elevational belts, strongly correlated with average July temperature, and a north–south subdivision, weakly correlated with annual rainfall and thermal excursion. The bioclimatic analysis (SOM and Rivas-Martínez model) resolves and adds detail to the axis of the elevational belts but cannot discern the north–south subdivision apart from the high mountains. We obtained a division into eight floristic units ordered according to two gradients: four elevational belts, each in turn subdivided into a north-central and a southern province. These two gradients seem to have a broader meaning in Southern Europe, particularly the north–south subdivision at about 30° latitude. The partial mismatch between the bioclimate and the flora indicates that bioclimatic models of Europe are in need of a revision and suggests that the history, in addition to the present-day climate (for instance, the vegetation of the last glacial maximum), can play a role in shaping the biogeography of Southern Europe.

Palo Laziale Wood is a relatively small biotope (129 ha) situated along the coast of the Metropolitan Area of Rome, Lazio region, Italy. Despite being one of the region's remaining patches of an ancient oak floodplain broad-leaved forest, it conserves numerous priority habitats and species of high conservation interest. The vegetation consists mainly of Turkey oak stands with small temporary ponds and flooded meadows. The forest underwent a dieback in 2003, triggered by a significantly hot and dry summer. In 2018, an ecological restoration project (LIFE PRIMED LIFE17 NAT/GR/000511) was initiated to restore Palo Laziale’s ecosystems. This paper presents the methodological approach employed to assess the vegetation ecology of a degraded forest ecosystem. Such an investigation was a key component of the Adaptative Restoration Plan of the Project. It provided the baseline necessary for designing and calibrating the planned direct conservation actions on the target habitat types (91M0: Pannonian-Balkanic turkey oak-sessile oak forests, 3170*: Mediterranean temporary ponds, 5230*: Arborescent matorral with Laurus nobilis, etc.) and establishing reference values to enable long-term monitoring. Plant taxa comparison from 1 ha square-grid sampling and multivariate analyses were carried out to group species and identify environmental and Ellenberg-based drivers. Six ecologically distinct units were found, eventually confirming the distinctive ecological heterogeneity of Mediterranean ecosystems. Amongst these, the hygrophilous vegetation has resulted to be the one mainly affected by the dieback outbreak. Due to the high heterogeneity, introduced by the massive tree mortality, the method of regular 1 ha squares turned out to be a reliable alternative to random vegetation sampling plots (e.g., phytosociological relevés) to disentangle ecological patterns of fragmented and disturbed habitats.

The Miyawaki method, developed by Akira Miyawaki, restores natural forests by planting diverse native species in compact spaces, rapidly creating compact, resilient ecosystems. Initially successful in Japan, its global application bloomed but remains rare in Mediterranean urban areas despite benefits like biodiversity enhancement and climate change mitigation. This method's effectiveness in Mediterranean climates, which face unique challenges like urban heat islands and biodiversity loss, is underexplored in literature and practice. We are leading a project in Italy to identify optimal plant assemblages, addressing the method's documentation gap in urban settings. It explores the potential of Tiny Forests to provide ecosystem services and improve urban liveability against climatic extremes. This note paper details the methodological steps undertaken in this experimental application, offering a tailored approach to test the method's adaptability and impact in Mediterranean urban environments, suggesting a significant opportunity for urban greening and resilience.