Effects of different intensities of overstory thinning on tree growth and understory plant-species productivity in a semi-arid Pinus halepensis Mill. afforestation

It is becoming more and more common in the Mediterranean basin to guard against forest fires by creating wooded firebreak areas by reducing the overstory density, pruning the remaining trees and slash mulching. Nevertheless, very few attempts have been made to analyse the effect of this practice upon tree growth and the productivity of the understory plant species in semi-arid areas by following a well defined experimental design over any length of time. To remedy this lack of information, during the spring of 2005 we thinned the overstory in a semi-arid Aleppo pine (Pinus halepensis Mill.) afforestation in SE Spain (planted in the winter of 1993-1994) from an initial density of about 1,500 trees per ha according to three different thinning regimes. The annual growth data of each stand (diameter at breast height, canopy cover and basal area) were measured in randomly situated plots of 20 × 20 m and the above-ground biomass of understory plant species was also harvested from quadrats of 0.5 × 0.5 m during the early summers of 2005 to 2009. Our results showed a positive and significant response from trees in thinned stands compared to the controls, in spite of periods of low-rainfall and plague stress that unfortunately occurred during the study period. There were also statistical differences in understory biomass production within the different areas of overstory thinning as a response to the new conditions. Nevertheless, this biomass was only a small fraction of the total above-ground biomass of the afforestation, which was much higher in control plots. These tree responses and structural changes to the afforestation could be of great interest because of their implications for forest management in the context of global change in an area where increases in temperature and reductions and irregularity in precipitation, together with higher fire risks, are forecast.