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 CO2 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 CO2 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 CO2 fixation, which may influence the predictions about carbon sinks
which are essential to balance CO2 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.
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