The global demand for forest products will increase in the coming decades due to population growth and increasing environmental awareness. Therefore, the production of forest products through multifunctional forest restoration could be a meaningful opportunity for large-scale restoration while promoting sustainability and vegetation recovery. We conducted a comprehensive literature review to explore how forest restoration in Brazil can meet the growing global demand for forest products, thereby promoting the widespread adoption of restoration practices. The number of forest restoration publications addressing forest product supply has increased, but remains limited. Notably, only studies on payments for environmental services have increased significantly over the years, while studies on non-timber forest products and timber have not increased significantly. Similar patterns and trends were found in earlier studies. Many studies do not provide insights into the socioeconomic outcomes of multifunctional forest restoration, which is consistent with other research findings. The studies cited 108 native species of commercial value. According to the literature, these species can provide multiple forest products, making their management economically attractive. Multifunctional restoration in Brazil has the potential for meeting global demand for forest products and supporting large-scale restoration. However, advancing scientific and technological knowledge in this area is needed to make this feasible.

The mosaic landscape composition of forest fragments located on high slopes, shallow soils hinder ecological interactions and the survival of plant species. This study aimed to show, in an environment with these characteristics, the effect of the environmental gradient relating the soil, slope, and vegetation of a fragment of the Montane Seasonal Semideciduous Forest. The forest structure was sampled in 12 continuous rectangular plots, with 30 X 20m, totaling 0.72ha. Soil samples were taken by drilling every 20m along the hydrographic divisor and opening of three trenches used as soil sampling sites for in situ determination of soil color, horizon, and nutrients. Horizons were classified as O/A/Cr in the altered rock with a marked presence of gravels, and the soil was classified as Litholic Neosol. The area has a steep slope, from 18.05% to 36.99%. Linear regression analysis indicated an opposite pattern for species richness in relation to slope and a positive relationship between slope and the number of standing dead individuals. Species richness was also positively related to the distance from forest edges. The evaluation evidenced the strong influence of slope and human activities in forest remnant as common to several high-altitude remnants, and small conservation actions can guarantee their maintenance.

The increasing need to understand how environmental risks affect ecosystem services has led to the development of multiple assessment approaches. However, information on risk–ecosystem service interactions remain fragmented across the scientific literature, limiting comparability and constraining the development of consistent analytical frameworks. This study proposes an evidence-based framework for analysing interactions between risks and ecosystem services. The approach integrates a matrix-based structure with a multi-criteria indicator, allowing the synthesis of different types of information documented in the literature. The framework is implemented through a reproducible workflow in R, enabling standardised application across different contexts. To evaluate model performance, a sensitivity analysis was conducted using alternative weighting configurations applied to the indicator. The results show that variations in weights affect numerical values but produce only limited changes in interaction categories, indicating that the model maintains consistent interpretation under different parameter settings. The proposed framework does not estimate risk magnitude directly but organizes the structure of available evidence. In doing so, it reveals asymmetries in how interactions are documented, indicating that ecosystem services supported by limited evidence may be underrepresented in conventional assessments. This approach reframes the analysis of risk–ecosystem service interactions by treating the structure of scientific evidence as an explicit analytical dimension, enabling the identification of knowledge asymmetries and a more robust interpretation of uncertainty.

The increasing need to understand how socio-environmental risks affect ecosystem services has led to the development of multiple assessment approaches. However, evidence on risk–ecosystem service interactions remains fragmented across the scientific literature, limiting comparability and the systematic characterization of available knowledge. This study proposes an evidence-based framework for analysing interactions between socio-environmental risks and ecosystem services. The framework integrates a risk–ecosystem service matrix with the Ecosystem Service Risk Evidence Index (ESREI), which synthesizes the number of retained studies and the extent to which explicit impacts and socioeconomic information are documented in the scientific literature. The framework was applied to wildfire risk and four ecosystem services in Portugal using evidence identified through a systematic literature review. The ESREI was calculated for each risk–ecosystem service interaction using a reproducible workflow implemented in R. A sensitivity analysis was conducted by applying alternative weighting configurations to the three indicators. The results showed that changes in weighting coefficients affected the numerical ESREI values, while producing relatively limited changes in the corresponding evidence categories. The framework therefore does not estimate risk magnitude directly, but provides a standardized representation of the structure and characterization of available scientific evidence. By making differences in evidence availability and characterization explicit, the ESREI supports the identification of well-documented interactions and areas in which risk–ecosystem service relationships remain insufficiently characterized