Litterfall and Leaf Area Index in the CONECOFOR Permanent Monitoring Plots

Forest canopies are more sensitive and react more promptly to abiotic and biotic disturbances than other stand structural components. Monitoring crown and canopy characteristics is therefore a crucial issue for intensive and continuous monitoring programs of forest ecosystem status. These observations formed the basis for the measurement of annual litter production and leaf area index (LAI) in the Italian permanent monitoring plots (CONECOFOR program) established within the EC-UN/ECE program "Intensive Monitoring (Level II) of Forest Ecosystems". Preliminary results after three years of observation are presented. The low value of within plot mean relative standard deviation (20.8 ± 1.9%) of litter production, which in any case never exceeded 30%, accounted for the good sampling error and accuracy of the chosen method, which seems to be accurate enough to detect changes in litter production through the years. The higher inconsistency of the amount of woody and fruits fractions over the years demonstrated the greater reliability of leaf fraction or, on the other hand, of LAI compared to total litter. Mean values of annual leaf-litter and total litter production and LAI were rather high in comparison with data reported in literature for similar stands, and reflected both a medium-high productivity and a juvenile phase in the development of the selected stands on average. Focusing on changes in litter production through the years, statistical analysis on a sub-sample of plots showed the existence of significant differences both in leaf litter and total litter production. These findings seem to attribute to the "year" factor a driving role in determining changes in litter production and LAI. Temporal intermittence in data collection, together with the shortness of the monitoring period, make it difficult to speculate or arrive at definitive conclusions on changes in litter production due to time-dependent factors. The importance of having a complete database to increase index representativeness and reliability and, on the other hand, of performing an integrated results analysis which takes into account the outcomes of other research actions, is recognized as an indispensable requirement for achieving the goals of the monitoring program.