Research Highlights: This review gives an overview of existing literature on the emerging topic of human wellbeing-forest contact nexus and provides a preliminary framework linking forests to wellbeing by highlighting key variables affecting this relationship. Background and Objectives: Existing literature reveals the psychological, physiological and social wellbeing benefits of contact with forest ecosystems; however, the role of forests in this relationship remains largely unexplored. The objectives of this review are twofold: (i) to provide an overview of the contributions of forest experiences to human wellbeing and the related interplay with forest ecosystems and (ii) to identify knowledge gaps to inform future research and systematize information available for forest managers and planners to support the development of effective forest-based initiatives. Materials and Methods: A scoping review was performed with a five-phase method integrating a systematic approach on Scopus, Web of Science and PubMed databases and snowball search. Studies were analyzed using a descriptive-analytical method. Results: Overall, 93 papers were included in the review. These are mainly from health-related sciences providing limited information for forest managers, planners and practitioners. Four main underlying variables of the forest-wellbeing relationship are identified: interaction, forest features, sensorial dimension of the forest and individual traits and reactions. Conclusions: Forest-based initiatives provide good opportunities for supporting public health and time spent in contact with forests seems to have a “health-bonus”. Whether and to what extent forest management can contribute to this is still poorly investigated. There is the need to better study causal relationships between specific forest features, type of interactions, frequency and “dose” of experiences, individual reactions and needs and wellbeing effects to maximize benefits from forest-based initiatives.

This study explored the land use land cover (LULC) change over 45 years (1975 -2020) in the world’s largest mangrove forest, Sundarbansusing Landsat imagery. LULC maps were created with same-season imagery with the lowest cloud cover at four intervals: 1975, 1990, 2005, and 2020. Maximum likelihood classification (MLC) was applied to assign five classes: dense forest, moderate forest, sparse forest, barren land, and water body. Accuracy assessment was carried out with 250 control points for each year resulting in overall accuracy and kappa coefficient ranging from 84.8% to 90.0% and 0.81 to 0.87, respectively. Results show dense forest at its highest cover in 1975 and then decreasing by an estimated annual rate of 1.3% from 1975 to 2020, but not consistently. Dense forest class mostly turned moderate and sparse; most of the sparse forest class turned to barren land. Most of the barren lands were located near the boundary between forest and human settlement, and these two classes were more frequent in the Indian part of Sundarbans than in the Bangladesh part. The conclusion is that the time-series of remote sensing data can validly support effective forest management by identifying space and time changes in the biodiversity of Sundarbans.

The sea level rise (SLR) in the Sundarbans areas is higher than the global-average rate of sea rise, and many studies assume that most of the dry land of the Sundarbans will be inundated by the end of the twenty-first century. This study aims to analyze the amount of dry land that can potentially be inundated by SLR in Sundarbans and the impact under different land cover conditions. Four SLR scenarios, a digital elevation data grid, and net subsidence data are used to map areas that will be potentially inundated by 2100. Results for the low (35 cm), mid (52 cm), high (70 cm), and extreme (147 cm) SLR scenarios indicate that the Sundarbans landmass area will be flooded up to 40 km² (1%), 72 km² (1.8%), 136 km² (3.4%), and 918 km² (23%), respectively, under the current net subsidence rate of −2.4 mm/year by 2100. Except for the extreme scenarios, the low, mid, and high SLR will result in riverbank and beach areas to be covered by water. The potential inundation areas of different vegetation cover classes that already exist today (2020) will be nominal for the low, mid, and high SLR scenarios. We also analyzed the sensitivity of the results through station-based SLR data, which fits with the low (35 cm) SLR scenarios under the −2.4 mm/year subsidence rate. This study concluded that the inundation aspect of SLR will not directly affect the Sundarbans; however, indirectly related threats and anthropogenic disturbances can be major drivers of the Sundarbans’ degradation by the end of the twenty-first century. This work discusses reasonable inundation scenarios integrating SLR and subsidence with a custom land-cover map that includes three forest-density categories. The study’s findings contribute to forest management planning and support the UN goals of the Bangladesh Delta Plan.

Increasing urbanization and climate change challenges are leading to relevant environmental, economic and social pressures on European cities. These include increasing flood hazards and the urban heat island (UHI) effect. Nature-Based Solutions (NBS) are increasingly recognized within strategies to provide multiple ecosystem services to mitigate existing risks and pressures, as well as to make cities more resilient and livable. Although being increasingly addressed within the literature, NBS implementation on the ground still faces many technical and financial barriers. This paper aims to test the potential of selected NBS in mitigating the effects of identified climate change risks, i.e., the UHI effect and urban floods, in the Turin urban area (north-western Italy). Four different intervention NBS-based scenarios are developed. The supply of ecosystem services by NBS in each scenario is assessed using InVEST models and the effectiveness of NBS investments is analyzed by calculating and comparing the associated costs and benefits. Different results in terms of effectiveness and economic viability are observed for each scenario and each NBS. Flood risk mitigation oriented NBS seem to have the most impact, in particular forested green areas and retention ponds. The results are relevant to suggest policy mix strategies to embed NBS in city planning.

Urban areas are experiencing major changes and facing significant sustainability challenges. Many cities are undergoing a transition towards a post-industrial phase and need to consider the regeneration of brownfield sites. Nature-Based Solutions (NBSs) are increasingly considered as tools for supporting this transition and promoting sustainable development by delivering multiple ecosystem services (ESs). Although the potential of NBSs as a cost-effective enabler of urban sustainability has been recognized, their implementation faces numerous barriers. The effective assessment of benefits delivered by urban NBSs is considered by existing literature as one of them. In order to contribute to filling this knowledge gap, we analyzed two alternative NBS-based intervention scenarios—i.e., (1) an urban forest and (2) meadows with sparse trees—for the redevelopment of an urban brownfield area within the municipality of Brescia (Northern Italy). Nine ESs were assessed both in biophysical and economic terms via a combination of modeling (InVEST, i-Tree and ESTIMAP) and traditional estimation methods. The results show that both scenarios improve ES stock and flow compared to the baseline, ensuring annual flows ranging between 140,000 and 360,000 EUR/year. Scenario 1 shows higher values when single ESs are considered, while scenario 2 shows higher total values, as it also accounts for the phytoremediation capacity that is not considered under the first scenario. All in all, regulating ESs represent the bulk of estimated ESs, thus highlighting the potential of proposed NBSs for improving urban resilience. The ES assessment and valuation exercise presented within this paper is an example of how research and practice can be integrated to inform urban management activities, and provide inputs for future decision making and planning regarding urban developments.