Ana Cristina Gonçalves

Canopy cover influence on macrofungal richness and sporocarp production in montado ecosystems

In this study we aimed to find out how macrofungi richness and sporocarp production varies in relation to both canopy cover and proximity of crown projection area, in order to discuss strategies and point out management actions that ensure macrofungal communities sustainability in montado ecosystems. The sporocarp survey was conducted once every two weeks, from October to February, between 2007 and 2009 in two representative sites of the most common (cork and holm oak) open montado ecosystems in southern Portugal. Results showed that canopy cover strongly shaped macrofungal communities composition and yield. Denser canopy cover enhanced mycorrhizal richness and reduced saprotrophic yield. Furthermore, mycorrhizal richness and yield increased with tree proximity. Finally some forest management strategies are suggested in order to enhance macrofungal richness and productivity, in montado ecosystems.

Multi Level Monitoring System for Cork Oak (Quercus Suber L.) Stands in Portugal

Cork oak stands occupy about 22% (750000 ha) of the Portuguese forest area with a relevant economic importance. They are managed in agro-silvo-pasture systems whose sustainability depends on balanced relations between their components. An integrated multilevel monitoring procedure was created in order to understand the system dynamics, with the following components: (i) aerial photography: crown cover diachronic studies, single tree spatial structure modelling; (i) stand: stand dendrometrics, soil and climate monitoring; (iii) tree: growth modelling in mature and young trees, with individual spatial information. The monitoring components as well as the available results are presented.

FUNÇÃO ALOMÉTRICA DE BIOMASSA COM IMAGENS DE SATÉLITE DE ALTA RESOLUÇÃO ESPACIAL

The aim of this study was to fit functions to estimate with data derived from high spatial resolution satellite images, the total biomass of Eucalyptus at local and regional scale. For this purpose, models were fit combining values of biomass estimated from forest inventory plots and vegetation indices based on Pleiades images. The function with which presented the best performance in the estimation of the total biomass, was the one that used as an independent variable the IV-SAVI, presenting a coefficient of determination (R 2 ) of 64.6%, however without great difference for the NDVI and SR. The fit functions can be used in other regions for the same species, and similar climate and local characteristics. This approach can be used as a low cost tool to produce estimations of biomass at local and regional level.

Functions for aboveground biomass estimation derived from satellite images data in Mediterranean agroforestry systems

Forest biomass has been having an increasing importance in the world economy and in the evaluation of the forests development and monitoring. The main goal of this study is the development of functions for the estimation of aboveground biomass, using crown cover as independent variable, for Quercus rotundifolia, Quercus suber and Pinus pinea in agroforestry systems, both for monospecies and multispecies stands, based on Portuguese data. Crown cover per specie was derived from crown horizontal projection obtained by processing very high spatial resolution satellite images (Quickbird and Worldview-2), with contrast split segmentation method and object-oriented classification. The stand species composition distinguished species and monospecies from multispecies stands. The best model was the one with crown cover and dummy variables for composition as explanatory variables, reflecting the differences between species and stand structure. Aboveground biomass with this function should ideally be calculated with the grid areas applied in this study, though similar accuracies can be obtained for other grid sizes.

Above‐Ground Biomass Estimation with High Spatial Resolution Satellite Images

Assessment and monitoring of forest biomass are frequently done with allometric functions per species for inventory plots. The estimation per area unit is carried out with an extrapolation method. In this chapter, a review of the recent methods to estimate forest above‐ground biomass (AGB) using remote sensing data is presented. A case study is given with an innovative methodology to estimate above‐ground biomass based on crown horizontal projection obtained with high spatial resolution satellite images for two evergreen oak species. The linear functions fitted for pure, mixed and both compositions showed a good performance. Also, the functions with dummy variables to distinguish species and compositions adjusted had the best performance. An error threshold of 5% corresponds to stand areas of 8.7 and 5.5 ha for the functions of all species and compositions without and with dummy variables. This method enables the overall area evaluation, and it is easily implemented in a geographic information system environment.