Maurizio Mulas

Along with the concept of improving reforestation efforts in Lebanon, this study aimed to provide a land suitability analysis for forest species in Lebanon while considering the effect of climate change. Herein, the soil evaluation criteria developed by FAO (The Food and Agriculture Organization) for land suitability classification were implemented through the weighted overlay method to produce suitability maps based on natural variables (soil, climate, and topography) influencing the presence of the species on the land. Cedrus libani, Quercus calliprinos, Ceratonia siliqua, Eucalyptus globulus, and Pinus halepensis are the species considered in this study. The results of this study provide useful information to inform reforestation activities in Lebanon, considering the expected climate change projections for medium- (2050) and long-term (2070) periods, according to two different scenarios (RCP4.5 and RCP8.5) and three General Circulation Models: CCSM4, GFDL-CM3, and HadGEM2-ES. The suitability maps showed a generally critical situation for the spatial distribution of forest species under future climate change compared to the current situation (1970–2000). The distribution of thermophilic species, which tolerate high temperatures (over 20 °C), was projected to expand compared to the current situation. In contrast, the expansion of cold-adapted species may be limited by future climate change conditions. It is crucial to consider the expected effects of climate change to better select species for reforestation and, therefore, to maintain forest cover in Lebanon.

Modeling phenological phases in a Mediterranean environment often implies tangible challenges to reconstructing regional trends over heterogenous areas using limited and scattered observations. The present investigation aimed to project phenological phases (i.e., sprouting, blooming, and pit hardening) for early and mid–late olive cultivars in the Mediterranean, comparing two phenological modeling approaches. Phenoflex is a rather integrated but data-demanding model, while a combined model of chill and anti-chill days and growing degree days (CAC_GDD) offers a more parsimonious and general approach in terms of data requirements for parameterization. We gathered phenological observations from nine experimental sites in Italy and temperature timeseries from the European Centre for Medium-Range Weather Forecasts, Reanalysis v5. The best performances of the CAC_GDD (RMSE: 4 days) and PhenoFlex models (RMSE: 5–9.5 days) were identified for the blooming and sprouting phases of mid–late cultivars, respectively. The CAC_GDD model was better suited to our experimental conditions for projecting pit hardening and blooming dates (correlation: 0.80 and 0.70, normalized RMSE: 0.6 and 0.8, normalized standard deviation: 0.9 and 1.0). The optimization of the principal parameters confirmed that the mid–late cultivars were more adaptable to thermal variability. The spatial distribution illustrated the near synchrony of blooming dates between the early and mid–late cultivars compared to other phases.