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Interactions between soil, topography, and climatic site factors can exacerbate and/or alleviate the vulnerability of oak woodland to climate change. Reducing climate-related impacts on oak woodland habitats and ecosystems through adaptation management requires knowledge of different site interactions in relation to species tolerance. In Britain, the required thematic detail of woodland type is unavailable from digital maps. A species distribution model (SDM) ensemble, using biomod2 algorithms, was used to predict oak woodland. The model was cross-validated (50%:50% - training:testing) 30 times, with each of 15 random sets of absence data, matching the size of presence data, to maximize environmental variation while maintaining data prevalence. Four biomod2 algorithms provided stable and consistent TSS-weighted ensemble mean results predicting oak woodland as a probability raster. Biophysical data from the Ecological Site Classification (forest site classification) for Britain were used to characterize oak woodland sites. Several forest datasets were used, each with merits and weaknesses: public forest estate subcompartment database map (PFE map) for oak-stand locations as a training dataset; the national forest inventory (NFI) "published regional reports" of oak woodland area; and an "NFI map" of indicative forest type broad habitat. Broadleaved woodland polygons of the NFI map were filled with the biomod2 oak woodland probability raster. Ranked pixels were selected up to the published NFI regional area estimate of oak woodland and matched to the elevation distribution of oak woodland stands, from "NFI survey" sample squares. Validation using separate oak woodland data showed that the elevation filter significantly improved the accuracy of predictions from 55% (p = .53) to 83% coincidence success rate (p < .0001). The biomod2 ensemble, with masking and filtering, produced a predicted oak woodland map, from which site characteristics will be used in climate change interaction studies, supporting adaptation management recommendations for forest policy and practice.

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The introduction of Douglas-fir [Pseudotsuga menziesii (Mirb.) Franco] in Europe has been one of the most important and extensive silvicultural experiments since the 1850s. This success was mainly supported by the species' wide genome and phenotypic plasticity even if the genetic origin of seeds used for plantations is nowadays often unknown. This is especially true for all the stands planted before the IUFRO experimentation in the 1960s. In this paper, a methodology to estimate the Douglas-fir provenances currently growing in Italy is proposed. The raw data from the last Italian National Forest Inventory were combined with literature information to obtain the current spatial distribution of the species in the country representing its successful introduction. Afterwards, a random forest classification model was run using downscaled climatic data as predictors and the classification scheme adopted in previous research studies in the Pacific North West of America. The analysis highlighted good matching between the native and the introduction range in Italy. Coastal provenances from British Columbia and the dry coast of Washington were detected as the most likely seed sources, covering 63.4% and 33.8% of the current distribution of the species in the country, respectively. Interior provenances and those from the dry coast of Oregon were also represented but limited to very few cases. The extension of the model on future scenarios predicted a gradual shift in suitable provenances with the dry coast of Oregon in the mid-term (2050s) and afterwards California (2080s) being highlighted as possible new seed sources. However, only further analysis with genetic markers and molecular methods will be able to confirm the proposed scenarios. A validation of the genotypes currently available in Italy will be mandatory as well as their regeneration processes (i.e., adaptation), which may also diverge from those occurring in the native range due to a different environmental pressure. This new information will also add important knowledge, allowing a refinement of the proposed modeling framework for a better support for forest managers.

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Interpolated climate data have become essential for regional or local climate change impact assessments and the development of climate change adaptation strategies. Here, we contribute an accessible, comprehensive database of interpolated climate data for Europe that includes monthly, annual, decadal, and 30-year normal climate data for the last 119 years (1901 to 2019) as well as multi-model CMIP5 climate change projections for the 21st century. The database also includes variables relevant for ecological research and infrastructure planning, comprising more than 20,000 climate grids that can be queried with a provided ClimateEU software package. In addition, 1 km and 2.5 km resolution gridded data generated by the software are available for download. The quality of ClimateEU estimates was evaluated against weather station data for a representative subset of climate variables. Dynamic environmental lapse rate algorithms employed by the software to generate scale-free climate variables for specific locations lead to improvements of 10 to 50% in accuracy compared to gridded data. We conclude with a discussion of applications and limitations of this database.

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Volumetric stability is an important aspect of the performance of building materials, and the shrinkage of CaO-FeOx-Al2O3-SiO2-rich inorganic polymers (IPs) has not been thoroughly investigated yet. Hence, this paper describes the outcome of a study conducted to investigate ways to minimize their shrinkage using different curing regimes. Two different slags were used as case studies to assess the robustness of the developed mitigation strategies. IP pastes and mortars were cured at (i) room condition, (ii) in slightly elevated temperature (60 °C for 2 d) and (iii) in a water-saturated environment. The reaction kinetics and formed products were examined on IP pastes, while mortars were made to characterize the 28 d pore structure, autogenous shrinkage, drying shrinkage, and strength development. The results showed that the precursors' reactivity and curing conditions severely affect shrinkage mechanisms and magnitude. Volumetric changes in the plastic stage can be related to the precursors' reactivity but drying shrinkage was the driving mechanism affecting the volumetric stability of all IP mortars. Understanding the effect of a precursor's composition and curing conditions on shrinkage is fundamental to develop proper mitigation strategies and to overcome one of IPs' main technical drawbacks.

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Soil plays a fundamental role in many ecological processes, throughout a complex network of above- and below-ground interactions. This has aroused increasing interest in the use of correlates for biodiversity assessment and has demonstrated their reliability with respect to proxies based on environmental data alone. Although co-variation of species richness and composition in forests has been discussed in the literature, only a few studies have explored these elements in forest plantations, which are generally thought to be poor in biodiversity, being aimed at timber production. Based on this premise our aims were 1) to test if cross-taxon congruence across different groups of organisms (bacteria, vascular plants, mushrooms, ectomycorrhizae, mycelium, carabids, microarthropods, nematodes) is consistent in artificial stands; 2) to evaluate the strength of relationships due to the existing environmental gradients as expressed by abiotic and biotic factors (soil, spatial-topographic, dendrometric variables). Correlations between groups were studied with Mantel and partial Mantel tests, while variance partition analysis was applied to assess the relative effect of environmental variables on the robustness of observed relationships. Significant cross-taxon congruence was observed across almost all taxonomic groups pairs. However, only bacteria/mycelium and mushrooms/mycelium correlations remained significant after removing the environmental effect, suggesting that a strong abiotic influence drives species composition. Considering variation partitioning, the results highlighted the importance of bacteria as a potential indicator: bacteria were the taxonomic group with the highest compositional variance explained by the predictors used; furthermore, they proved to be involved in the only cases where the variance attributed solely to the pure effect of biotic or abiotic predictors was significant. Remarkably, the co-dependent effect of all predictors always explained the highest portion of total variation in all dependent taxa, testifying the intricate and dynamic interplay of environmental factors and biotic interactions in explaining cross-taxon congruence in forest plantations.

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Wildfires, a key socio-environmental challenge in Mediterranean regions, are influenced by anthropogenic factors shaping land-use and socioeconomic spatial structures. By assuming that the dominant socioeconomic structure of local districts exerts a variable impact on wildfire spatial regimes, the present study investigates 174 indicators on a municipal scale in Italy, identifying a multidimensional relationship between wildfire characteristics and socioeconomic contexts. An exploratory statistical approach was adopted to identify linear and non-linear relationships among variables assessing socioeconomic contexts and wildfire patterns. Empirical results demonstrate that characteristic wildfire attributes (frequency, intensity and severity) are systematically higher in socioeconomic contexts characterized by rural poverty, unemployment and deregulated urban expansion, especially in southern Italy. A higher fire frequency was typically observed in (i) peri-urban districts with a dynamic socio-demographic profile and (ii) in rural districts with intensive cropping systems. Joint information on socioeconomic structure/dynamics and environmental change, is crucial for a better understanding of local-scale spatial patterns of wildfires in the Mediterranean region. Integrated socio-environmental information provides a better understanding of the local communities' role in the management of wildfire-prone land, contributing to implement more effective strategies aimed at minimizing wildfire impact on land resources.

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Shifts in government priorities in response to the 2007 global recession have affected wildfire management and natural disaster funding arrangements, leading to a reduced effectiveness of fire suppression actions and increasing fire vulnerability. Our study investigates the role of local socioeconomic contexts on fire suppression effectiveness under economic expansion and recession in a Mediterranean region (Attica, Greece) strongly affected by 2007 crisis and displaying a persistently high density of peri-urban wildfires. Basic characteristics of wildfires (spatial distribution, intensity, and land use preferences) were investigated in the study area over two consecutive 8-year time intervals characterized by economic expansion (2000-2007) and recession (2008-2015). An integrated approach based on multivariate statistics and artificial neural networks was implemented to evaluate latent relationships between fire suppression time, wildfire characteristics, and socioeconomic dynamics. Controlling for wildfires' characteristics over the two time intervals, fire time length increased under crisis-mainly for small and medium-sized fires-possibly as an indirect response to reduced effectiveness of forest land management. Local contexts and political decisions influenced by economic downturns are relevant factors shaping wildfires' severity in the Mediterranean region. With recession, local contexts vulnerable to wildfires require more effective fire prevention measures, sustainable forest management, and regional planning.

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