Giuseppe Mancino

Assessing temporal variation of primary and ecosystem production in two Mediterranean forests using a modified 3-PG model

ContextForest ecosystem carbon uptake is heavily affected by increasing drought in the Mediterranean region.AimsThe objectives of this study were to assess the capacity of a modified 3-PG model to capture temporal variation in gross primary productivity (GPP), and ecosystem net carbon uptake (NEE) in two Mediterranean forest types.MethodsThe model was upgraded from a monthly (3-PG) to a daily time step (3-PGday), and a soil water balance routine was included to better represent soil water availability. The model was evaluated against seasonal GPP and NEE dynamics from eddy covariance measurements.ResultsSimulated and measured soil water content values were congruent throughout the study period for both forest types. 3-PGday effectively described the following: GPP and NEE seasonal patterns; the transition of forest ecosystems from carbon sink to carbon source; however, the model overestimated diurnal ecosystem respiration values and failed to predict ecosystem respiration peaks.ConclusionsThe model served as a rather effective tool to represent seasonal variation in gross primary productivity, and ecosystem net carbon uptake under Mediterranean drought-prone conditions. However, its semi-empirical nature and the simplicity inherent in the original model formulation are obstacles preventing the model working well for short-term daily predictions.

Shaping the role of 'fast' and 'slow' drivers of change in forest-shrubland socio-ecological systems

The temporal speeds and spatial scales at which ecosystem processes operate are often at odds with the scale and speed at which natural resources such as soil, water and vegetation are managed those. Scale mismatches often occur as a result of the time-lag between policy development, implementation and observable changes in natural capital in particular. In this study, we analyse some of the transformations that can occur in complex forest-shrubland socio-ecological systems undergoing biophysical and socioeconomic change. We use a Multiway Factor Analysis (MFA) applied to a representative set of variables to assess changes in components of natural, economic and social capitals over time. Our results indicate similarities among variables and spatial units (i.e. municipalities) which allows us to rank the variables used to describe the SES according to their rapidity of change. The novelty of the proposed framework lies in the fact that the assessment of rapidity-to-change, based on the MFA, takes into account the multivariate relationships among the systems variables, identifying the net rate of change for the whole system, and the relative impact that individual variables exert on the system itself. The aim of this study was to assess the influence of fast and slow variables on the evolution of socio-economic systems based on simplified multivariate procedures applicable to vastly different socio-economic contexts and conditions. This study also contributes to quantitative analysis methods for long-established socio-ecological systems, which may help in designing more effective, and sustainable land management strategies in environmentally sensitive areas.

A Multidimensional statistical framework to explore seasonal profile, severity and land-use preferences of wildfires in a Mediterranean country

SUMMARY This study analyses spatio-temporal patterns of wildfires in Greece using a multidimensional statistical framework based on non-parametric correlations, principal component analysis, clustering and stepwise discriminant analysis. Specifically, we assess the frequency, seasonal profile, severity and land-use type of 135 178 wildfires which occurred between 2000–2012 in Greece, one of the countries most affected by fire in Europe. Our results show that both the number of fires and the average size of the area covered by fire show a specific seasonal pattern with a marked increase during the dry season. Principal component analysis identifies three dimensions linked with the main type of land-use affected by the fires: (i) medium and large fires primarily affected landscapes composed of forests, mixed woodlands/shrublands and croplands; (ii) small fires mainly affected fragmented landscapes, i.e. those with mosaics of different crops, market gardens and non-vegetated, abandoned or marginal areas; (iii) fires affecting wetlands and pastures occurred particularly in late summer and showing medium-low severity. Hierarchical clustering highlights similarities in spatio-temporal patterns between fire indicators (ignition date, burnt land cover classes, fire size, fire density). K-means clustering allows us to distinguish between low-severity fires occurring in the wet season from intense and frequent fires occurring in the dry season but with distinct land-use selectivity. The research reported here contributes insight into the complexity of wild fires in the Mediterranean region and supports the design of more effective fire prevention measures including sustainable forest management practices and careful regional planning to minimise risk factors.