Application of the forest growth model 3PG to Eucalyptus globulus stands in the central region of Portugal A. Amaral*, R. Salas **, F. Páscoa**, M. Tomé***, J. Tomé***, P. Soares*** * Superior School of Agricultural Sciences of Coimbra, Bencanta 3040-316 Coimbra, Portugal. E-mail: aamaral@esac.pt ** Superior School of Agricultural Sciences of Coimbra, Bencanta 3040-316 Coimbra, Portugal. *** Superior Institute of Agronomy, Technical University of Lisbon, Tapada da Ajuda, 1399 Lisboa Portugal. Abstract Significant efforts have been carried out modelling Eucalyptus globulus growth in Portugal. The objective of these models is to propose a reliable decision tool to forest planning and management. Models based on physiologic processes and environmental variables have as main advantage the possibility to foresee the consequences of climate changes on the forest growth, among others. This attribute make process-based models an essential instrument for nowadays forest management. The present work describes the application of 3PG process-based model - requiring a restricted number of parameters easy to gather combined with the empiric model Globulus 2.1. The study was carried out in E.globulus stands in two catchments in Caramulo, Portugal. We present the results obtained using new tuned parameters for Portugal. The first results evidence a good general behaviour of the model, concerning its predictive capacity of volume and biomass. Introduction Regarding Silvaqua Project: Assessment of Climatic Change Impact on Water Resources and CO 2 Fixation in Fast Growing Forest Stands in Portugal and some former projects about the effect of climate change on water availability in Mediterranean ecosystems, it become interesting to study the climate change influence on hydrological resources and CO 2 fixation on fast growing species stands. Recent studies refer that possible impact of climate change on evaporation rate of Portuguese forests as well as on hydrologic resources may be severe (Parry, 2000). Besides hydrologic resources it is predictable that several species get in to water stress (Coelho et al., 2001), producing changes in stand growth patterns, in water consumption and CO 2 fixation, which may influence the predictions about carbon sinks which are essential to balance CO 2 sources and to accomplish the Kyoto protocol. Scoop and Objectives The aim of this study is to collect forest inventory data which may be used to simulate the growth of E. globulus stands under the environmental conditions of these water catchments.
The collected data was projected with the empiric model Globulus 2.1, the reference model for E. globulus stands in Portugal, which will be used to estimate stand productivity in the study area. Globulus 2.1 is an empiric growth and yield model developed by Tomé et al., 2001. This model was developed for portuguese stands and it s validated to the whole country. Empiric forest models, broadly used and developed around the world, are based on the statistical description of a past phenomenon. However, increasing knowledge about processes and variables helps us to understand how the variables concerned in growth could affect the processes. In this way, for the last two decades researchers had developed mechanistic models of forest growth, turning out available better estimates of wood production due to the sensitivity to environmental variables variation over growth conditions. Physiologic processes are directly dependent from environmental, physical and climate variables. In this way the setup of variables running like model parameters allow us to predict and evaluate how climate change affect the process in study (Landsberg, 1997). To generate practical tools these process-based calculations must be combined with empirical relationships derived from experiments and measurements made over long periods in forests and plantations. 3PG was developed using this approach. The model requires little adjustment to obtain realistic forest growth estimates (Landsberg, 1997). In this work, we present the results of application of 3PG, using country specific parameters, and the empiric model Globulus 2.1 as the reference empiric model for E. globulus in Portugal (Tomé et al., 2004). 3PG is a process-based model broadly released and used in several regions in the world. Methods Study Area The study area consists of two adjacent water catchments. The total area is 80 ha from which 65ha consist of E. globulus stands. The two catchments are located at Caramulo Mountain, in Portugal. Data Collection A forest inventory was carried out on the study area with the aim of getting initial stand data. We decided to use a 100 m*100 m grid resulting in a proportion of one sample plot by hectare. A total of 81 sample plots were selected. Model Parameterization After forest inventory we determined the stands parameters using Globulus 2.1 and estimated present volume. 3PG was then calibrated with state, climate and stand variables. For Fertility Rating (FR) and Available Soil Water (ASW), we carried out a
soil analysis on the study area. After the complete parameterization we simulated again the present volume. 3PG can be run in several modes, depending on the stand available data. We can chose to simultaneously simulate several stands with common features, which is MultiSite Run, or we can independently simulate each stand by its own, which is SingleSite Run. 3PG allows stands projections based on seedling mass or based in stand biomass at a certain age, derived from forest inventory data. Growth Simulation and Data Treatment Referring to 3PG calibration parameters for Portugal, we found the canopy quantum efficiency (cqe) parameter uncommonly low regarding several other studies and we chose to run the model using the cqe value tuned for Portugal (0.046) and the most common cqe value (0.06). The predictions of the mean volume per hectare obtained with 3PG were compared with the values obtained with the empirical model Globulus 2.1 by means of an ANOVA. Afterwards a Tukey test was run to the projection means, using the Globulus 2.1 figures as the reference values. Results and Discussion Depending on the parameters used to initialise the model and on the simulation mode, the predictions of both models produced similar results, showing no statistical significant differences, with exception of Sernadinha catchment when using standard calibration. Serra de Cima Catchment No significant differences were observed when 3PG was run with the calibration performed by Tomé et al., 2004 and using the environmental parameters for the water catchments, mentioned above. We compared the results of Globulus 2.1 with 3PG ones. Changing the cqe value from 0.046 to 0.06 produces a better fit of the 3PG results to the Globulus 2.1 ones. Using standard calibration, the best fit is achieved with 3PG projections run with stand biomass MultiSite 3 and SingleSite 4 when compared with the figures obtained with seedling biomass. In other way, altering the cqe value from 0.046 to 0.06 in the 3PG model, results in the projections become closer to the values obtained with 3PG projections to much similar figures of those obtained with Globulus 2.1 model. In other way, 3PG simulations run with stand biomass seem to be less sensible to this change of cqe parameter value. Sernadinha Catchment In Sernadinha catchment the results revealed significant differences in the forecasts when 3PG was run using standard calibration. The Tukey test applied for the mean volume per hectare comparisons, showed that 3PG simulations run with seedling biomass and standard calibration leads to higher deviation against Globulus 2.1 projections, presenting statistical significant differences on MultiSite 1 and SingleSite 5.
MultiSite 3 and SingleSite 4 although statistically similar, also present higher deviations than those occurred in Serra de Cima catchment. Changing the cqe value from 0.046 to 0.06 leads to much better simulation results, when using seedling biomass. Similarly, like was observed in Serra de Cima, projections drived with stand biomass showed no variation, seeming to be less sensitive to the change of cqe value. Conclusions Using standard calibration, simulations modes drived with stand biomass showed a better fit than the modes drived with seedling biomass, which is according to the results presented in reference bibliography. Shifting canopy quantum efficiency parameter from 0.046 to 0.06, 3PG simulations modes using seedling biomass show on their turn a better fit to Globulus 2.1 projections, as the simulations modes using stand biomass keep the same figures. 3PG simulations modes using stand biomass seem to the very robust and less sensible to physiologic parameters. 3PG evidence a good predictive quality in global terms. Reference Coelho, C., Ferreira, A., Boulet, A. and Keizer J. (2001). Impacto das mudanças nos usos do solo e da variabilidade da precipitação sobre a resposta hidrológica de pequenas bacias hidrográficas florestadas. VII Conf. Nac. Sobre a Qualidade do Ambiente, Aveiro, 18-20Abril. Landsberg, J.J., Waring, R.H. (1997) A generalized model of forest productivity using simplified concepts of radiation-use efficiency, carbon balance and partitioning. Forest Ecology and Management 95, 209-228. Landsberg, J.J., Waring, R.H. and Coops, N.C. (2003) Performance of the forest productivity model 3PG applied to a wide range of forest types. Forest Ecology and Management 172, 199-214. Parry, M. (2000) Assessment of potential effects and adaptations for climate change in Europe. The Europe Acacia Project. University of East Anglia, Norwich, 320pp. Reed, D., Tomé, M. (1998) Total aboveground biomass and net dry matter accumulation by plant component in young Eucalyptus globulus in response to irrigation. Forest Ecology and Management 103, 21-32. Sands, P. (2003). 3PGPJS a User-Friendly Interface to 3PG, the Landsberg and Waring Model of Forest Productivity. Technical Report No.29, Edition 2.3. Cooperative Research Centre for Sustainable Production Forestry and CSIRO Forestry and Forest Products, Australia Tomé, J., Tomé, M., Fontes L., Soares P., Pacheco C. and Araújo C. (2004) Testing 3PG with irrigated and fertilized plots established in Eucalyptus globulus plantations in
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