Climate change is affecting species distribution and ecosystem form and function. Forests provide a range of ecosystem services, and understanding their vulnerability to climate change is important for designing effective adaptation strategies. Species Distribution Modelling (SDM) has been extensively used to derive habitat suitability maps under current conditions and project species distribution shifts under climate change. In this study, we model the current and future habitat suitability of the dominant tree species in Greece (Abies cephalonica, Abies borisii-regis, Pinus brutia, Pinus halepensis, Pinus nigra, Quercus ilex, Quercus pubescens, Quercus frainetto and Fagus sylvatica), based on species-specific presence data from the EU-Forest database, enhanced with data from Greece that is currently under-represented in terms of tree species occurrence points. By including these additional presence data, areas with relatively drier conditions for some of the study species were included in the SDM development, yielding a potentially lower vulnerability under climate change conditions. SDMs were developed for each taxon using climate and soil data at a resolution of ~1 km2. Model performance was assessed under current conditions and was found to adequately simulate potential distributions. Subsequently, the models were used to project the potential distribution of each species under the SSP1-2.6 and SSP5-8.5 scenarios for the 2041–2070 and 2071–2100 time periods. Under climate change scenarios, a reduction in habitat-suitable areas was predicted for most study species, with higher elevation taxa experiencing more pronounced potential habitat shrinkages. An exception was the endemic A. cephalonica and its sister species A. borisii-regis, which, although currently found at mid and high elevations, seem able to maintain their potential distribution under most climate change scenarios. Our findings suggest that climate change could significantly affect the distribution and dynamics of forest ecosystems in Greece, with important ecological, economic and social implications, and thus adequate mitigation measures should be implemented.

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Quantification of forest Gross Primary Productivity (GPP) is important for understanding ecosystem function and designing appropriate carbon mitigation strategies. Coupling forest biometric data with canopy photosynthesis models can provide a means to simulate GPP across different stand ages. In this study we developed a simple framework to integrate biometric and leaf gas-exchange measurements, and to estimate GPP across four Mediterranean pine forests of different post-fire age. We used three different methods to estimate the Leaf Area Index (LAI) of the stands, and monthly gas exchange data to calibrate the photosynthetic light response of the leaves. Upscaling of carbon sequestration at the canopy level was made by implementing a Big Leaf and a Sun/Shade model, using both average and variant (monthly) photosynthetic capacity values. The Big Leaf model simulations systematically underestimated GPP compared to the Sun/Shade model simulations. Our simulations suggest an increasing GPP with age up to a stand maturity stage. The shape of the GPP trend with stand age was not affected by the method used to parameterise the model. At the scale of our study, variability in stand and canopy structure among the study sites seems to be the key determinant of GPP.

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<p>Foliar properties play a crucial role in local and global biochemical cycles. Systematic variation in key leaf traits has been reported both between and within species. Intraspecific variation in leaf traits is controlled by micro-environmental conditions and follows seasonal patterns. In this study we examine the seasonal patterns of six foliar traits including leaf area (LA), leaf thickness (Lth), leaf mass per area (LMA), leaf dry matter content (LDMC), leaf area to sapwood area ratio (LA/SA) and branch wood density (WD) in addition to the associated parameters of the Michaelis-Menten light response curve (i.e. light saturated net photosynthetic rate (Asat), half saturation coefficient (Km) and dark respiration rate (Rd)). We measured on a monthly basis the foliar traits and developed light response curves in four Pinus brutia dominated stands along a post-fire chronosequence (15, 40, 70 and 90 years) from sunlit branches. Significant differences in the interannual trait variability were found between stands for LDMC, WD and Asat, with the highest variability identified in the younger plot. LA/SA, Rd and Km also showed strong interannual variability although not statistically different between plots. A mixed effect model analysis revealed high intraclass correlation coefficients for Km and Asat suggesting that net photosynthesis is following systematic seasonal patterns. Overall LA was higher and LDMC was lower in the oldest plot and WD was higher in the denser (40 years) plot. Interestingly gas exchange parameters did not show differences in their overall mean values. Across plots, Asat was strongly positively related to Km, and LMA was positively related to LDMC and Lth. LDMC was also positively related with Asat and negatively with Lth. A principal component analysis (PCA) revealed two major dimensions of intraspecific trait variability within our plots. The first PCA axis was positively related to Asat, Km, LDMC and LMA suggesting that regardless of the stand age needles are placed along a fast-slow carbon gain dimension with denser needles illustrating faster area-based photosynthesis. The second PCA axis was positively related to LA and Lth suggesting that bigger needles are also thicker. A subsequent permutational multivariate analysis of variance revealed that the centroids and the dispersion of the trait syndromes differed between stands, with the youngest plot illustrating higher trait dispersion and the oldest plot characterized by bigger and thicker needles. Thus, in older stands were competition for light is higher, needles are deployed to be bigger and thicker to optimize light capture, while in younger stands they are optimized along a leaf density - photosynthetic capacity spectrum depending on (more heterogeneous) microenvironmental conditions. Our findings illustrate that intraspecific variation can be attributed to either seasonal (abiotic) light availability or to (biotic) heterogeneity related to stand structure, and have important implications for local scale forest dynamics models.</p><p>«This research is co-financed by Greece and the European Union (European Social Fund- ESF) through the Operational Programme «Human Resources Development, Education and Lifelong Learning 2014-2020» in the context of the project “Carbon fluxes across a post-fire chronosequence in Pinus brutia Ten forests.” (MIS 5049513)».</p>