3PG Model Research Articles

Parameter testing and application of the 3PG model for Eucalyptus grandis x Urophylla in subtropical conditions in South Africa

Parameter testing and application of the 3PG model for Eucalyptus grandis x Urophylla in subtropical conditions in South Africa

Parameter Optimization of the 3PG Model Based on Sensitivity Analysis and a Bayesian Method

Sensitivity analysis and parameter optimization of stand models can improve their efficiency and accuracy, and increase their applicability. In this study, the sensitivity analysis, screening, and optimization of 63 model parameters of the Physiological Principles in Predicting Growth (3PG) model were performed by combining a sensitivity analysis method and the Markov chain Monte Carlo (MCMC) method of Bayesian posterior estimation theory. Additionally, a nine-year observational dataset of Chinese fir trees felled in the Shunchang Forest Farm, Nanping, was used to analyze, screen, and optimize the 63 model parameters of the 3PG model. The results showed the following: (1) The parameters that are most sensitive to stand stocking and diameter at breast height (DBH) are nWs(power in stem mass vs. diameter relationship), aWs(constant in stem mass vs. diameter relationship), alphaCx(maximum canopy quantum efficiency), k(extinction coefficient for PAR absorption by canopy), pRx(maximum fraction of NPP to roots), pRn(minimum fraction of NPP to roots), and CoeffCond(defines stomatal response to VPD); (2) MCMC can be used to optimize the parameters of the 3PG model, in which the posterior probability distributions of nWs, aWs, alphaCx, pRx, pRn, and CoeffCond conform to approximately normal or skewed distributions, and the peak value is prominent; and (3) compared with the accuracy before sensitivity analysis and a Bayesian method, the biomass simulation accuracy of the stand model was increased by 13.92%, and all indicators show that the accuracy of the improved model is superior. This method can be used to calibrate the parameters and analyze the uncertainty of multi-parameter complex stand growth models, which are important for the improvement of parameter estimation and simulation accuracy.

Application of 3PG carbon production model in the gross primary productivity estimation of broadleaved Korean pine forest in Changbai Mountain, China.

With the flux data of ChinaFLUX and the concurrent satellite remote sensing data in Changbai Mountain, we recombined parameters of four models, i.e., vegetation photosynthesis model (VPM), eddy covariance-light utility efficiency model (EC-LUE), terrestrial ecosystem model (TEM) and Carnegie-Ames-Stanford approach model (CASA) within 3PG model. The most suitable parameters of 3PG model were determined by comparing the root mean square error, coefficient of determination and average error between measured and observed flux values. To improve its accuracy in estimating gross primary productivity (GPP) of broadleaved Korean pine forest in Changbai Mountain, the fitness of the optimal model was validated using the observed flux data. The results showed that when temperature, enhanced vegetation index, and surface water index were used to characterize the temperature limiting factor, photosynthetic active radiation absorption ratio and water limiting factor in the original model to estimate GPP of broadleaved Korean pine forest, the simulation results were the best. The precision of the optimized model (R2=0.948, RMSE=0.035 mol·m-2·month-1) was better than that of the original model (R2=0.854, RMSE=0.177 mol·m-2·month-1), which could effectively improve the phenomenon of obvious overestimation of the original model in the growing season. Results from the parameter sensitivity analysis showed that the uncertainty of GPP estimation was dominated by temperature, followed by enhanced vegetation index, photosynthetically active radiation and land surface water index, as well as their interactions.

Productivity and profitability potential for non-native Eucalyptus plantings in the southern USA

Renewed interest in non-native Eucalyptus species for planting in the southern US has been spurred by projections suggesting they are more productive than the widely cultured Pinus species, by warming temperatures, and by attempts to identify frost-tolerant species as well as developing genetically modified Eucalyptus for frost tolerance. In addition to questions of environmental suitability, the economic viability of Eucalyptus is a significant hurdle to widespread adoption for commercial plantings. We sought to assess the potential obtainable yields and economic feasibility of Eucalyptus grandis Hill ex. Maiden and E. benthamii Maiden et Cambage, two species suitable for the southern United States. Using the process-based growth model 3PG, we projected potential yields at the sub-county level for E. grandis in Florida where it is operationally grown and E. benthamii in USDA Plant Hardiness Zones 8a and 8b where it has shown tolerance to occasional low temperatures. The 3PG model estimated mean annual volume increment, inside bark (MAI) that was used to estimate land expectation value (LEV) and internal rate of return (IRR).The MAI of E. grandis ranged from 18 to 119 m3 ha−1year−1 (9 to 59.5 dry Mg ha−1 year−1) with a mean of 42.6 m3 ha−1year−1 (20.8 dry Mg ha−1 year−1) for sites in peninsular Florida. The lower growth projections came from north Florida areas where annual frosts occur. Excluding urban areas, the LEV of E. grandis ranged from $-1264 to $1710 ha−1 with a mean of $424 ha−1. The estimated IRR ranged from −9.7% to 16.9% with a mean of 8.2%. Eucalyptus benthamii MAI ranged from 3.3 to 76 m3 ha−1year−1 (1.8 to 41.8 Mg ha−1year−1), with a mean of 21.9 m3 ha−1year−1 (11.9 Mg ha−1year−1). The higher yields were primarily located in coastal regions of USDA Plant Hardiness Zone 8b. Excluding urban areas, LEV ranged from $-2707 ha−1 to $1532 ha−1. The maximum estimated IRR was 15.9%. Our results show that Eucalyptus is potentially profitable as a bioenergy crop in the southern USA, but potential profitability of E. benthamii was limited by low temperature; positive LEV was obtained where productivity was 30 m3 ha−1year−1 or more. Profitability was restricted to a small percentage (12%) of sites theoretically within the operational range in the southern U.S. indicating that a wholesale conversion of Pinus taeda plantations is unlikely.

Potential Profitability Zones for Populus spp. Biomass Plantings in the Eastern United States

Short rotation woody crops (SRWCs) are key renewable feedstocks for the emerging bioeconomy. A critical step in developing a bioeconomy is defining suitable regions for commercial SRWC activities. The goal of this study was to estimate the obtainable yield in mean annual increment and economic returns on investment for Populus deltoides and Populus hybrids for the 33 eastern states using the 3PG model (Physiological Principles Predicting Growth). Yields ranged from 0.5 to 11.9 oven-dry tons (ODT) ac−1yr−1 with a mean of 3.9 ODT ac−1yr−1. Spatially, southern Illinois, Louisiana, Indiana, and central Missouri have the highest yield production. Kentucky, Tennessee, North Carolina, Oklahoma, Arkansas, and Virginia, as well as other southern regions of Georgia, Alabama, Mississippi, and South Carolina, have the lowest potential yield production. Land expectation values of P. deltoides ranged from –$1,369.12 to $1556.14/ac. The median internal rate of return (IRR) for the northern states was 2.0%, with a range of −13.9% to 14.6%. Spatially explicit potential profitability zones are useful as a coarse filter for evaluating sites for bioenergy projects that are under construction, in operation, proposed, or where due diligence is required.

Estimating the yield potential of short-rotation willow in Canada using the 3PG model

The ability to predict short-rotation coppice (SRC) willow productivity for a given region would be very helpful for large-scale deployment of this crop. The objectives of this study were to calibrate and validate the 3PG model for two commonly used clones (SX64 and SX67) and to provide yield potential estimates for 16 sites across Canada. One dataset for each clone, including leaf area index (LAI) and stem biomass, was used for calibrating parameters controlling leaf and stem growth. All other datasets, coming from eight different willow plantations, were used for model validation. Model performance was good in predicting stem biomass for the SX64 (normalized mean error (NME) = –8%, normalized root mean square error (NRMSE) = 22%) and SX67 (NME = –3%, NRMSE = 16%) clones. Predictions were more scattered for LAI, with NRMSE close to 35% and 33% and NME of 1% and 8% for SX64 and SX67, respectively. The simulation results show that the greatest yields were obtained with the three-year rotation for the SX67 clone, whereas a two-year rotation seemed to be more appropriate for the SX64 clone. The simulation results also show that growing degree-days had a significant impact on yield potential, which varied from 10.5 to 16.5 t DM·ha−1 for SX64 and from 7.5 to 11.5 t DM·ha−1 for SX67.

MODELING AND SIMULATION OF RELIEF INFLUENCE ON EUCALYPTUS FORESTS: INTERACTION BETWEEN SOLAR IRRADIANCE AND PRODUCTIVITY

ABSTRACT This study aimed to verify the differences in radiation intensity as a function of distinct relief exposure surfaces and to quantify these effects on the leaf area index (LAI) and other variables expressing eucalyptus forest productivity for simulations in a process-based growth model. The study was carried out at two contrasting edaphoclimatic locations in the Rio Doce basin in Minas Gerais, Brazil. Two stands with 32-year-old plantations were used, allocating fixed plots in locations with northern and southern exposure surfaces. The meteorological data were obtained from two automated weather stations located near the study sites. Solar radiation was corrected for terrain inclination and exposure surfaces, as it is measured based on the plane, perpendicularly to the vertical location. The LAI values collected in the field were used. For the comparative simulations in productivity variation, the mechanistic 3PG model was used, considering the relief exposure surfaces. It was verified that during most of the year, the southern surfaces showed lower availability of incident solar radiation, resulting in up to 66% losses, compared to the same surface considered plane, probably related to its geographical location and higher declivity. Higher values were obtained for the plantings located on the northern surface for the variables LAI, volume and mean annual wood increase, with this tendency being repeated in the 3PG model simulations.

Carbon sequestration by white spruce shelterbelts in Saskatchewan, Canada: 3PG and CBM-CFS3 model simulations

For more than a century, planted shelterbelts in Saskatchewan, Canada have protected farmyards from the elements, decreased soil erosion, sequestered atmospheric carbon, as well as provided many other ecological functions. It is estimated that there are >60,000km of planted shelterbelts throughout the province, and considerably more in all of the Canadian Prairies. This paper details the overall process of quantifying and mapping the carbon stocks in white spruce (Picea glauca) shelterbelts planted in Saskatchewan. Shelterbelt data collected from field sampling sites, which were identified by a unique site selection approach, were used to parameterize two models for use in shelterbelt systems; an independent data set was used to validate model predictions. Shelterbelt tree growth was modeled with the Physiological Principles in Predicting Growth (3PG) model, and carbon flux and stocks in shelterbelts were modeled with the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3). Annual total ecosystem carbon (TEC) flux in white spruce shelterbelts increased one order of magnitude, from −0.33 to 4.4Mg Ckm−1yr−1, for age 1–25 years, and reached a peak of 5.5Mg Ckm−1yr−1 (age 39 years). An initial soil carbon loss from the shelterbelt, caused by the land-use change, was offset in full by tree growth by age 17, 18, and 21 years for trees planted at 2.0, 3.5, and 5.0m spacing within a row, respectively. Increase in carbon stocks, after 60 years of growth, was predicted in the litter layer (21.8Mg Ckm−1), belowground biomass (26.1Mg Ckm−1), and aboveground biomass (117.6Mg Ckm−1). Across all the different provincial soils, carbon additions were 106–195Mg Ckm−1 in 60-yr-old white spruce shelterbelts. Cumulatively, accounting for eight decades of white spruce shelterbelt planting and tree growth, carbon additions totaled 50,440Mg C province-wide in 991km of white spruce shelterbelts. The C additions represented 38% of the province-wide TEC stocks, which totaled 131,750Mg C. The cumulative carbon storage in all components of planted white spruce shelterbelts far exceeded the initial carbon levels present at the time of shelterbelt planting.

Modeling poplar growth as a short rotation woody crop for biofuels in the Pacific Northwest

Predicting the economic viability and environmental sustainability of a biofuels industry based on intensively cultivated short rotation woody crops (SRWC) requires spatial predictions of growth and yield under various environmental conditions and across large regions. The Physiological Principles in Predicting Growth (3PG) model was modified to evaluate the growth and yield of coppiced poplar (Populus spp). This included an additional biomass partitioning method and developing a sub-model which takes into account the impact of coppicing on post harvest regeneration, extending the applicability of the 3PG model to coppice management regimes.The parameterized model was applied to the entire Pacific Northwest of the United States, using appropriate climate and soil input data. Results predict the yield of poplar cultivation at a spatial resolution of ≈64 km2 throughout the ≈8,000,000 km2 of the study region. Existing agricultural cultivation patterns were used to estimate regional water availability for irrigation, and for non-irrigated regions, land cover features including ownership, slope, soil salinity and water table depth where used to select areas with a real potential to support a SRWC plantation.Results can be integrated with other models that allow for optimizing crop selection and biorefinery site selection. Important results include; an updated 3PG model for coppiced SRWC plantings, estimates of biomass feedstock yields under different irrigation patterns and weather conditions, and estimates for feedstock availability when combined with crop adoption scenarios.

Improvement of Spatio-temporal Growth Estimates in Heterogeneous Forests Using Gaussian Bayesian Networks

Canopy leaf area index (LAI) is a quantitative measure of canopy foliar area. LAI values can be derived from Moderate Resolution Imaging Spectroradiometer (MODIS) images. In this paper, MODIS pixels from a heterogeneous forest located in The Netherlands were decomposed using the linear mixture model using class fractions derived from a high-resolution aerial image. Gaussian Bayesian networks (GBNs) were applied to improve the spatio-temporal estimation of LAI by combining the decomposed MODIS images with a spatial version of physiological principles predicting growth (3PG) model output at different moments in time. Results showed that the spatial-temporal output obtained with the GBN was 40% more accurate than the spatial 3PG, with a root-mean-square error below 0.25. We concluded that the GBNs improved the spatial estimation of LAI values of a heterogeneous forest by combining a spatial forest growth model with satellite imagery.

Design of a GIS-Based Web Application for Simulating Biofuel Feedstock Yields

Short rotation woody crops (SRWC), such as hybrid poplar, have the potential to serve as a valuable feedstock for cellulosic biofuels. Spatial estimates of biomass yields under different management regimes are required for assisting stakeholders in making better management decisions and to establish viable woody cropping systems for biofuel production. To support stakeholders in their management decisions, we have developed a GIS-based web interface using a modified 3PG model for spatially predicting poplar biomass yields under different management and climate conditions in the U.S. Pacific Northwest region. The application is implemented with standard HTML5 components, allowing its use in a modern browser and dynamically adjusting to the client screen size and device. In addition, cloud storage of the results makes them accessible on any Internet-enabled device. The web interface appears simple, but is powerful in parameter manipulation and in visualizing and sharing the results. Overall, this application comprises dynamic features that enable users to run SRWC crop growth simulations based on GIS information and contributes significantly to choosing appropriate feedstock growing locations, anticipating the desired physiological properties of the feedstock and incorporating the management and policy analysis needed for growing hybrid poplar plantations.

The carbon implications of large‐scale afforestation of agriculturally marginal land with short‐rotation willow in Saskatchewan

AbstractAfforestation with short‐rotation coppice (SRC) willow plantations for the purpose of producing bioenergy feedstock was contemplated as one potential climate change mitigation option. The objectives of this study were to assess the magnitude of this mitigation potential by addressing: (i) the land area potentially available for SRC systems in the province of Saskatchewan, Canada; (ii) the potential biomass yields of SRC plantations; and (iii) the carbon implications from such a large‐scale afforestation program. Digital soils and land‐use data were used to identify, map, and group into clusters of similar polygons 2.12 million hectares (Mha) of agriculturally marginal land that was potentially suitable for willow in the Boreal Plains and Prairies ecozones in Saskatchewan. The Physiological Principles in Predicting Growth (3PG) model was calibrated with data from SRC experiments in Saskatchewan, to quantify potential willow biomass yields, and the Carbon Budget Model of the Canadian Forest Sector (CBM‐CFS3), was used to simulate stand and landscape‐level C fluxes and stocks. Short‐rotation willow plantations managed in 3 year rotations for seven consecutive harvests (21 years) after coppicing at Year 1 produced about 12 Mg ha−1 yr−1 biomass. The more significant contribution to the C cycle was the cumulative harvest. After 44 years, the potential average cumulative harvested biomass C in the Prairies was 244 Mg C ha−1 (5.5 Mg C ha−1 yr−1) about 20% higher than the average for the Boreal Plains, 203 Mg C ha−1 (4.6 Mg C ha−1 yr−1). This analysis did not consider afforestation costs, rate of establishment of willow plantations, and other constraints, such as drought and disease effects on biomass yield. The results must therefore be interpreted as a biophysical mitigation potential with the technical and economic potential being both lower than our estimates. Nevertheless, short‐rotation bioenergy plantations offer one potential mitigation option to reduce the rate of CO2 accumulation in the earth's atmosphere and further research is needed to operationalise such a mitigation effort.

A novel approach to simulate growth of multi-stem willow in bioenergy production systems with a simple process-based model (3PG)

An important requirement for commercialization of willow biomass production in short-rotation crop (SRC) plantations is the reliable and cost-efficient estimation of biomass yield. Predictions and simulations of willow stand biomass have been problematic due to issues with modeling the multi-stem growth form of willow. The aim of this paper was to develop a new approach for managing allometric measurements from multi-stemmed willow for stand growth simulations. The 3PG model (Physiological Principles in Predicting Growth) was parameterized for willow and was used for biomass yield simulation for an entire 22-yr cycle (seven 3-yr rotations) of willow in SRC plantations. The multi-stemmed growth form was transformed into a single-stem modeling form by deriving whole plant willow allometric relationships using detailed stem-level measurements of basal area, stem biomass and volume. 3PG model predictions for plant diameter, height, biomass, and stand biomass and volume were within the 95% confidence range of mean plot values. Model simulations showed that after seven 3-yr rotations only 20% of planted cuttings would survive (a decrease from 15,152 to 3022 plants ha −1 ), but stand volume would increase continuously with each subsequent rotation. 3PG predictions for cumulative (for 22 yr) aboveground biomass was 272 Mg ha −1 and mean annual yield was 12 Mg ha −1 yr −1 , comparing favorably with other findings. To our knowledge, this work is the first where the 3PG model was calibrated and used for willow species. Once parameterized for a specific willow clone, 3PG can predict biomass accumulation for any agricultural land in North America using only available soil and climate data.

Application of the 3PG forest growth model to a Eucalyptus globulus plantation in Northwest Spain

This paper presents an assessment of the ability of the 3PG process-based model to simulate height (h) and diameter at breast height (DBH) growth in three plots located in a Eucalyptus globulus plantation on the Atlantic coast of Galicia (Northwest Spain). The obtained results show how this model estimates adequately height (h) and DBH growth, and determination coefficients (R 2) between observed data and data predicted by the model are always higher than 0.97, root mean square error (RMSE) of 0.45–1.05 cm in DBH and 0.46–0.85 in h, and a model efficiency (EF) close to 1 (0.98–0.99). In order to improve the results predicted by the model, we propose modifying the nS and fullCanAge parameter values given by default so as to adjust growth rates in the plantation to the weather conditions in the site. The ability of the model to discriminate growth rates in the three plots must be noted, even when plots are located in the same plantation and they only show differences in aspects related to site factors. Given the obtained results in the three plots used in this study, its simplicity and the small number of parameters needed as input data, the 3PG model stands out as a very useful tool for forest plantation management.

Hybrid poplar growth in bioenergy production systems: Biomass prediction with a simple process-based model (3PG)

Establishing short-rotation tree plantations for bioenergy and fiber production on agricultural land (abandoned farmland) would provide significant environmental and economic benefits for rural communities and society as a whole. Walker hybrid poplar (Populus deltoides x P. nigra) is one of the most commonly used varieties cultivated in Saskatchewan, Canada; however, there are no existing hybrid poplar growth models in the literature. The aim of this work was to parameterize and evaluate the 3PG model (Physiological Principles in Predicting Growth) to predict Walker tree growth in the climate and soils of Saskatchewan. We used annual data from Walker poplar trials (4- to 11-yr old stands) established at three spacing levels (2.4, 3.0, and 3.7 m) at three sites located in central Saskatchewan, Hnr, BH, and ML sites. The data were split into two sets – the modeling set from the Hnr site was used to parameterize 3PG, and the testing sets from the BH and ML sites were used to evaluate Walker growth predictions made by 3PG. The bias, sum(predicted minus observed) divided by number of observations, for tree height predictions ranged from −1.76 to 1.45 m, and bias for diameter at breast height (DBH) ranged from −2.61 to 0.66 cm. Regression R-square values of 3PG-predicted versus observed height and DBH ranged from 0.75 to 0.98. Our results indicated that, once parameterized, 3PG could predict Walker hybrid poplar growth with desirable accuracy by only utilizing commonly available soils and climate data for marginal or more productive agricultural land across Saskatchewan.

Estimation of Forest Plantation Productivity Using a Physiologically Based Model Driven with Meteorological Data and Satellite-derived Estimates of Canopy Photosynthetic Capacity

Within the framework of Kyoto protocol, carbon sink concept is a major topic for the global climate change. There is an urgent need to collect some necessary data on the forest plantations. Therefore, there is a clear need to develop methods for estimating the biomass at diverse sites simply with non- destructive methods. Modeling is one of effective approaches and Process Based Models (PBMs) can provide a better understanding of stand growth and dynamics. A one simplified model of PBMs is 3PG model and modified one is 3PGS model; Physiological Principles Predicting Growth with Satellite data (1). The model enables to use parameters derived from satellite data such as Fraction of absorbed Photosynthetically Active Radiation (FPAR) as well as meteorological data. The objective of this study is to compare between 3PG model and 3PGS model by estimating above ground biomass (Wabv). Landsat Enhanced Thematic Mapper-Plus (ETM+) data were used for the model implementation. The estimated parameters were validated with the ground-measured values. Field measurements were conducted in Eucalyptus camaldulensis and Acacia mangium plantation. The 3PGS model outputs showed that there was very good relationship between measured (ground-based measurements) and simulated (modeled) values. Root mean square errors (RMSE) of 3PGS model results were less than the RSME of 3PG model results in Eucalyptus plot. The result applied for Acacia mangium showed it had higher RMSE between measured and simulated values than the result applied for Eucalyptus camaldulensis. The results indicate that the 3PGS model can provide reasonable estimates of Wabv.

04/02392 Fast pyrolysis in linseed: product yields and compositions: Acikgoz, C. et al. Journal of Analytical and Applied Pyrolysis, 2004, 71,(2), 417–429

Predicting the economic viability and environmental sustainability of a biofuels industry based on intensively cultivated short rotation woody crops (SRWC) requires spatial predictions of growth and yield under various environmental conditions and across large regions. The Physiological Principles in Predicting Growth (3PG) model was modified to evaluate the growth and yield of coppiced poplar (Populus spp). This included an additional biomass partitioning method and developing a sub-model which takes into account the impact of coppicing on post harvest regeneration, extending the applicability of the 3PG model to coppice management regimes.The parameterized model was applied to the entire Pacific Northwest of the United States, using appropriate climate and soil input data. Results predict the yield of poplar cultivation at a spatial resolution of ≈64 km2 throughout the ≈8,000,000 km2 of the study region. Existing agricultural cultivation patterns were used to estimate regional water availability for irrigation, and for non-irrigated regions, land cover features including ownership, slope, soil salinity and water table depth where used to select areas with a real potential to support a SRWC plantation.Results can be integrated with other models that allow for optimizing crop selection and biorefinery site selection. Important results include; an updated 3PG model for coppiced SRWC plantings, estimates of biomass feedstock yields under different irrigation patterns and weather conditions, and estimates for feedstock availability when combined with crop adoption scenarios.

A continental biomass stock and stock change estimation approach for Australia

Summary To implement Australia's National Carbon Accounting System it is necessary to estimate biomass stock, continentally, and change in stock, at a sub-hectare spatial resolution. The approach developed to meet this requirement is a hybrid between GIS-based process modelling and empiricism. Multi-temporal mapping of productivity was carried out using a variant of the 3PG (physiological principles predicting growth) model. Relationships were found between mapped productivity indices and measurements of biomass at maturity (i.e. long-term- undisturbed stands). This information was then used to interpolate maps of biomass potential. Simple growth formulae were used to plot biomass accumulation, with the ‘rate of approach to mature biomass’ set by the age at which maximum current annual increment occurs and the predicted site plant productivity over time. The age of the forest stand was determined from disturbance events detected by twelve national coverages of Landsat MSS, TM and ETM+ remotely-sensed data collected between 1972 and 2002. Responses to thinning of existing forests are calculated using an adjustment of stand age concurrent with the intensity of the thinning event.