Modeling distribution of Mediterranean beech forests and soil carbon stock under climate change scenarios

Abstract

Climate change is forecasted to alter forest species distributions and the organic carbon cycle, particularly in the Mediterranean region. In this context, one of the most important carbon reservoirs, both in terms of living biomass and soil organic matter, is represented by beech forests, which are highly vulnerable to global warming. Accordingly, we investigated how the effects of climate change predicted for 2070 could affect both beech distribution and soil carbon stocks in Italy. In order to achieve this goal, we predicted beech distribution using state of the art ecological niche modeling, projecting its potential range under climate change scenarios. Moreover, a field survey was carried out to quantify the proportion of organic carbon in the first 5 cm of soil, which are the most sensitive to climate effects. The latter results were used to explore the relationship between organic carbon and ecogeographical variables, projecting this relationship onto the predicted beech distribution. Our outcomes showed a substantial reduction in beech distribution, especially at its southern range limits, along with a remarkable shift towards higher elevations and latitudes. The organic carbon in beech forests was significantly related to temperature seasonality and elevation, showing a decrease between 64.5 and 98.8% under different IPCC scenarios.

Explaining Intricate Morphometric Variability with Environmental Predictors: The Case of Globularia cordifolia Species Complex

“…Temperature seasonality is a measure of temperature change over the course of the year and it is computed as standard deviation of the 12 mean monthly temperature [52]. This variable has been shown to be an important ecological predictor for the distribution of many plant species, either rare or widespread [53][54][55][56][57]. This predictor clearly helped us to distinguish some populations (M-GP, M-MU, and M-FV) that are above 6.2 • C temperature seasonality, exhibiting the highest values of most morphological variables, as well as also explaining most of the variation in shape.…”

“…Predictors included latitude, longitude, elevation, solar radiation, wind speed, water vapor pressure, and 19 bioclimatic variables (bio_01-bio_19) derived from temperature and precipitation [52]. To avoid multicollinearity in the predictors, bioclimatic variables were selected using a variance inflation factor (VIF) approach by recursively dropping all variables with VIF ≥3 [55,56]. The procedure retained elevation, solar radiation, bio_04 (temperature seasonality), bio_09 (mean temperature of driest quarter), and bio_12 (annual precipitation).…”

Dynamics of Organic Matter in Leaf Litter and Topsoil within an Italian Alder (Alnus cordata (Loisel.) Desf.) Ecosystem

“…Although we did not collect data from the deeper layers of the soil, the topsoil (0-5 cm) had a high organic C stock, comparable to the same layer in several European beech ecosystems (e.g., 20-50 Mg/ha) [11,30]. For comparison with other alder ecosystems, a previous study [54] found approximately 38 Mg/ha in the first 10 cm of the organo-mineral A soil layer under black alder, while between 30 and 40 Mg/ha were observed in the first 10 cm of the topsoil under 15-25 years old grey alder stands [10].…”

“…[41], but generally inferior compared to non-European species such as Alnus nepalensis D.Don [42]. Compared to European beech (Fagus sylvatica L.), which is the most important forest species in Italy and the one with the highest C stocks in its soil [11], Italian alder litter input was intermediate between beech forests with a mean annual temperature of 6.0 • C (2.50 ± 0.18 Mg/ha) and 8.6 • C (4.31 ± 0.43 Mg/ha) [30].…”

“…The fine earth fraction was then ground until able to pass a 0.5 mm screen and stored for further chemical analyses. The topsoil stocks were computed as in [11] and expressed as Mg/ha. Both forest floor leaf litter and topsoil were sampled in three subplots per field plot, which were later pooled together in the laboratory in order to have enough material for the analyses and to account for spatial variability.…”