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Global warming is becoming a major concern affecting many components of the biodiversity at a global scale and disproportionately affecting the integrity of ecosystems, particularly the habitat of endemic species. Understanding its impacts on most vulnerable species is essential to improve knowledge on the ecology of these species and for their long-term management and conservation. Abies marocana Trabut (Moroccan fir), a remarkable forest tree of the Mediterranean basin, is an endangered species that is present in discreet small areas of the Rif Mountains, which is highly vulnerable to the ongoing climate warming and facing severe anthropogenic pressures. For conservation and management purposes, our work focused on improving understanding of the impacts of future climate change on the distribution of this species through its habitat suitability modeling. The maximum entropy approach was used, which achieved good predictive abilities. Habitat suitability was identified and then predicted under current and future climate conditions. A significant change and a gradual regression of the habitat suitability to A. marocana was shown under different future climate scenarios. The magnitude of the simulated changes is important and tends to have negative consequences for Moroccan fir conservation. For this purpose, outputs from models are useful to improve our knowledge about the ecology of A. marocana, and predictive maps produced under current and future climate conditions constitute reflection tools available to scientists and managers to better integrate actual and future climate impacts into existing and upcoming management strategies to prevent any future locale extinction.

Taper equations are indispensable tools for characterizing the stem profile of trees, providing valuable insights for forest management, timber inventory, and optimal assortments allocation. The recent progress in Terrestrial Laser Scanning (TLS) has revolutionized forest inventory practices by enabling nondestructive data collection. In this study, four taper models from three different model categories were established based on point cloud data of 219 Pinus nigra trees. The taper equations fitted with TLS data were used to predict the diameter at specific stem heights and the total stem volume. The results show that among fitted models, the Max and Burkhart segmented model calibrated by the means of a mixed-effects approach provided the best estimate of the diameter at different heights and the total stem volume evaluated for different diameter at breast height (DBH) classes. In numerical terms, this model estimated the diameter and the volume with a respective overall error of 0.781 cm and 0.021 m3. The predicted profile also shows that above a relative height of 0.7, the diameter error tends to increase due to the low reliability of data collected beyond the base of the crown primarily caused by interference from branches and leaves. Nevertheless, this study shows that TLS technology presents a compelling opportunity and a promising non-destructive alternative for generating taper profiles and estimating tree volume. [ABSTRACT FROM AUTHOR]