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Species ecological envelope maps were obtained for the two main Portuguese wood-production species (Eucalyptus globulus Labill. and Pinus pinaster Aiton) and projected future climate change scenarios. A machine learning approach was used to understand the most influential environmental variables that may explain current species distribution and productivity. Background and Objectives: The aims of the study were: (1) to map species potential suitability areas using ecological envelopes in the present and to project them in the future under climate change scenarios; (2) to map species current distributions; (3) to map species current productivity; and (4) to explore the most influential environmental variables on species current distribution and productivity. Materials and Methods: Climate, elevation data, and soil data sets were used to obtain present and future species ecological envelopes under two climate change scenarios. The o cial land cover maps were used to map species distributions. Forest inventory data were used to map the species productivity by geostatistical techniques. A Bayesian machine learning approach, supported by species distributions and productivity data, was used to explore the most influential environmental variables on species distribution and productivity and to validate species ecological envelopes. Results: The species ecological envelope methodology was found to be robust. Species’ ecological envelopes showed a high potential for both species’ a orestation. In the future, a decrease in the country’s area potentiality was forecasted for both species. The distribution of maritime pine was found to be mainly determined by precipitation-related variables, but the elevation and temperature-related variables were very important to di erentiate species productivity. For eucalypts, species distribution was mainly explained by temperature-related variables, as well as the species productivity. Conclusions: These findings are key to support recommendations for future a orestation and will bring value to policy-makers and environmental authorities in policy formulation under climate change scenarios.

Growing forests wildfires in Portugal are an increasing concern since forests in the Mediterranean region are vulnerable to recent global warming. Long-term negative effects are expected on the vegetation with the coming increasing drought. The strawberry tree (Arbutus unedo L.) displays potential to be a successfully business-like cultured in several regions of Portugal and southern Europe, as it is well adapted to climate and soils. In Portugal, this species has been used by local populations particularly for spirit production and for fruit consumption, although it has different possible commercial uses, from processed and fresh fruit production to ornamental, pharmaceutical and chemical applications. In addition, due to its pioneer status, it is valuable for land recovery and desertification avoidance, besides being fire resistant. The available strawberry tree’s data is presence-only. For modelling purposes, a set of placements within the landscape of interest (Portugal) was applied. The species, observed in 318 plots, together with a vector of environmental covariates (7 bioclimatic attributes, slope and altitude) and a defined background were used for modeling purposes. Maxent 3.4.1 was the used software, where the estimated quantity is the probability of the presence of the species, conditioned on the environment. Maxent uses the environmental covariate data from the occurrence records and the background sample, to estimate the ratio between the conditional density of the covariates at the presence sites and the marginal (i.e., unconditional) density of covariates across the study area and so, estimating the relative suitability of one place vs. another. Three different climate scenarios (control run; 2050 and 2070) were tested for two emission scenarios (RCP 4.5 and RCP 8.5, WorldClim), besides the past, 6,000 BP (Mid-Holocene). The reduction of habitat suitable for this species is very significant in the southern regions, even for the best warming scenario (RCP 4.5) in 2050. Central and Northern mountain regions are predicted refuge for this species. Forest policies and management should consider the impact of climate change on the usable areas for forestry, seeing a case-study species particularly adapted to the Mediterranean regions and wildfires, such as strawberry tree. The distribution of the species in the Middle Holocene agrees with previous genetic and fossils studies in the region, which supported two putative refuges for the species since the Last Glacial Maximum and a cryptic refugia in the East-Central mountain region.