Desarrollo de herramientas para la gestión selvícola de monte bajo de castaño en asturias

Resumo

This thesis covers the development and implementation of forest management tools for sweet chestnut forest stands in northern Spain, where traditional coppice stands, as a result of rural abandonment, have been degraded or abandoned. The main aim was to develop forest management tools to improve and optimize the silviculture of the sweet chestnut in the study area. The specific tools developed were: a dynamic growth stand model; predictive carbon forest management models; a tool for monitoring satellite time series images in order to remotely study the evolution over time of the canopy cover under different silvicultural treatments; and predictive models of Leaf Area Index (LAI) from LiDAR data to assess the impact of thinning treatments and for canopy characterization. The information used for this research comes from an experimental network of permanent plots established by the Forest and Wood Technology Centre (CETEMAS) in sweet chestnut coppice stands in Asturias. It is comprised of two sub-networks of plots, one without any type of forest management, formed by 32 circular permanent plots (15m radius) carefully chosen throughout the study area in order to represent the full range of ages, densities, site qualities and edaphoclimatic conditions of this species in the region. The other sub-network is managed (thinnings) and comprises three trials: (1) Control (2800–3300 stems ha-1), (2) Treatment 1 which consisted of a single thinning that left a living stock density of between 900 and 600 stems ha-1, and (3) Treatment 2, which involved a more intensive thinning that left a living stock density of around 400 stems ha-1. The results of this thesis were a dynamic growth model composed of three transition functions: basal area, dominant height and stems per hectare, which will help to predict rates of change of the variables of interest in forest stands. Predictive carbon models were also developed considering different forest management alternatives. They enable estimations of carbon sequestration and storage in sweet chestnut coppice, a valuable tool for taking into account climate change mitigation criteria. Studies carried out for this thesis revealed that forest management impacts on carbon sequestration and storage in that elongating the rotation period when one thinning is applied helps to combine wood production goals with meeting carbon storage and sequestration criteria. To study canopy cover development after thinnings, a tool using/based on the Area Under the Curve were used for testing whether time-series of remote sensing data is a useful tool for monitoring changes, in the case of this thesis, sweet chestnut coppice stands. The results show the tool to be useful for developing strategies for the management of sweet chestnut coppice on the basis of the timing of previous management interventions, information that, in many cases, would otherwise be impossible to ascertain. In addition, it was shown that LiDAR point cloud data could be used to distinguish the different canopy layers and understand how they are distributed throughout the canopy. This was achieved through the full characterization of the canopy, from the ground to maximum height, which provided not only data on the basis of which the different layers could be differentiated, but also a complete description of the distribution of each canopy zone. For sweet chestnut coppice forest stands, the resprout layer was demonstrated to have a high impact on forest vertical structure. It was also possible to create a mapping tool through the LiDAR metrics, implementing Leaf Area Index (LAI) models and other variables of interest. As a consequence of the work carried out here, all these forest management tools generate knowledge of the actual status of this species, which facilitates improvements in the silviculture and the forest management of this species. The incorporation of the results of studies that consider the dynamics of forest systems (thinnings) and their effects on long-term management are key since they significantly expand our knowledge of the adaptive capacity of sweet chestnut ecosystem in the face of global change. On the one hand, with the developed tools, better quality stands with better quality wood products will be obtained and it is considered an important aspect for improving the industry of the region. On the other hand, modelling their dynamics allows to know the potential of forests, not only as mitigators of climate change, but also to evaluate their potential to generate carbon credits in the near future.