In the current study, a novel approach combining quantile regression with nonlinear mixed-effects (QR-NLME) modeling was applied to predict the maximum crown width (cw_max) of three economically important forest species—the European beech (Fagus sylvatica L.), the black pine (Pinus nigra Arn.), and the Calabrian pine (Pinus brutia Ten.) at tree level. A power QR-NLME model was fitted first to a dataset including 1414 European beech trees obtained from 29 randomly distributed sample plots, 770 black pine trees from 25 sample plots, and 1880 Calabrian pine trees from 41 sample plots in Greece, to predict the cw_max at tree level. Additionally, a nonlinear mixed-effects model (NLME) was fitted to the same dataset to predict the average crown width at tree level for all species. In the second stage, the crown competition factor (CCF) was estimated based on the population average response of the cw_max predictions. The proposed approach presented sound results when compared with the outcomes of relevant models from other regions fitted to open-grown tree data, and therefore, it can be well implemented on clustered data structures, in cases of absence of open-grown tree data.

In forest science and practice, the total tree height is one of the basic morphometric attributes at the tree level and it has been closely linked with important stand attributes. In the current research, sixteen nonlinear functions for height prediction were tested in terms of their fitting ability against samples of Abies borisii regis and Pinus sylvestris trees from mountainous forests in central Greece. The fitting procedure was based on generalized nonlinear weighted regression. At the final stage, a five-quantile nonlinear height-diameter model was developed for both species through a quantile regression approach, to estimate the entire conditional distribution of tree height, enabling the evaluation of the diameter impact at various quantiles and providing a comprehensive understanding of the proposed relationship across the distribution. The results clearly showed that employing the diameter as the sole independent variable, the 3-parameter Hossfeld function and the 2-parameter Näslund function managed to explain approximately 84.0% and 81.7% of the total height variance in the case of King Boris fir and Scots pine species, respectively. Furthermore, the models exhibited low levels of error in both cases (2.310m for the fir and 3.004m for the pine), yielding unbiased predictions for both fir (−0.002m) and pine (−0.004m). Notably, all the required assumptions for homogeneity and normality of the associated residuals were achieved through the weighting procedure, while the quantile regression approach provided additional insights into the height-diameter allometry of the specific species. The proposed models can turn into valuable tools for operational forest management planning, particularly for wood production and conservation of mountainous forest ecosystems.

Virgin forests are considered valuable reference areas for studying forest ecosystem structures and functions as they have been naturally grown with no human interventions. In the Mediterranean region there are few such areas and even scarcer data on deadwood which is a key element for multi-functional forest management. Data regarding the amount and variety of standing and lying deadwood were recorded in the core zones of the Frakto virgin forest in the central Rodopi Mountains in eight square plots of 0.25 ha each. The average deadwood volume accounted for 175.71 m3 ha-1 with lying deadwood consisting mainly of conifers and representing over 60% of the total deadwood. The deadwood distribution showed a decreasing trend towards larger size classes while in terms of quality deadwood it was represented by all stages of decay, thus showing high variability. The research outcomes contribute to knowledge standards when adopting management regimes in mixed beech forests aiming at sustainable forest ecosystem management.

Knowledge of social perceptions and attitudes has emerged as a cornerstone for the successful implementation of Green Infrastructure (GI) projects. Relevant studies to date have almost always focused on large cities and ex-ante planning contexts. This paper aims to explore how citizens’ perceptions in the face of climate change adaptation and, particularly, Human Thermal Comfort enhancement and other co-benefits of diverse urban GI projects are being shaped during the GI implementation. Empirical data were gathered from a medium-sized hinterland city situated in northeastern Greece. The research included 200 respondents from the study population, and Principal Component Analysis, K-means clustering, and Discriminant Analysis were employed to depict citizens’ behavioral patterns. Three attitude patterns emerged through the study: i) climate detractors, ii) climate advocates, and iii) climate neutrals. The predicted classification of group membership exhibited overall very good accuracy, with 97.5% of the original grouped cases being correctly classified. This study can guide authorities of small and medium-sized cities as they develop GI projects aimed at climate change adaptation and other co-benefits, providing the required knowledge to formulate more effective communication strategies, encourage public participation, and increase the social acceptability of GI facilities.

The structural diversity of old-growth forests is a fundamental element as regards ecosystem stability and functionality. The current study aims at exploring the texture diversity in the unique virgin Frakto forest of Greece through the determination of the forest development phases and their related stages. Eight sample plots of 0.25 hectares each were randomly distributed to serve the field research needs. During the single phases, a significant number of variables at the stand level, such as the total dead and living timber volume and the density expressed as the number of stems per hectare and basal area, were calculated, and their values were merged into three main stages. The Frakto virgin forest was found to be dominated by the optimal stage (61.7%), followed by the decay stage (22.7%), and the initial stage (15.6%), in alignment with relevant distributions reported for other European virgin forests. Statistically significant differences in terms of stem density and woody volume between the stages demonstrated increased structural diversity and heterogeneity, a typical characteristic of primeval forests. The results offer an insight into forest growth dynamics under natural processes, thus providing a knowledge base for the promotion of sustainable forest management.