Process-based models in Eucalyptus plantation management : reality and perspectives

Yield prediction in commercial forestry has been dominated by empirical modelling. Increasingly, however, process-based models are finding application either in support or instead of these traditional models. In this paper we draw the new forestry demands and how these models can answer different kinds of questions such as forest productivity in planted areas and new plantation, water-use, carbon sequestration and effects of climate change on forest production. In this paper we review current performance against management needs, concentrating in particular on the application of the 3-PG (Landsberg and Waring, 1997) and CABALA (Battaglia et al., 2004) process-based models. In general we find that process-based models have met many of the expectations of a decade ago. The paper briefly indicates new opportunities of process-based models in the area of wood properties and wood products prediction and in the area of forest health assessment.___________________________________La predicción de rendimientos en la silvicultura comercial ha estado dominada hasta ahora por el empleo de técnicas de modelización empíricas. Sin embargo, los modelos basados en procesos se están utilizando cada vez más como suplementos o incluso sustitutos de los tradicionales. En este artículo apuntamos nuevas demandas forestales y la forma en que los nuevos modelos pueden dar respuesta a diferentes cuestiones como la productividad forestal tanto en zonas plantadas como en nuevas plantaciones, el uso del agua, el secuestro de carbono y los efectos del cambio climático en la producción forestal. Asimismo, valoramos la eficacia de los modelos frente a las necesidades actuales de gestión, sobre todo en lo relativo a la aplicación de dos modelos basados en procesos: 3-PG (Landsberg y Waring, 1997) y CABALA (Battaglia et al., 2004). En general, los modelos de este tipo han colmado muchas de las expectativas que suscitaron hace una década. En este artículo se esbozan nuevas aplicaciones para estos modelos en cuanto a la predicción de propiedades y productos de la madera, así como a la valoración de la salud de los bosques

Evaluating methods of estimating global radiation and vapor pressure deficit using a dense network of automatic weather stations in coastal Brazil.

A dense network of automatic weather stations (AWS) in eastern Brazil provided the opportunity to test established relationships between global radiation (Rs), photosynthetically active radiation (Rp) and net radiation (Rn). We also examined the variation in vapor pressure deficit (VPD) across the region, and predictions of VPD from temperature data. Predictions of Rs using the MTCLIM package [Agric. For. Meteorol. 93 (1999) 211] accounted for 75% of the variance (r2 = 0.75) in monthly mean measured values but only 62% of the variance in daily values. A procedure described by [Int. J. Bio-meteorol. 44 (2000) 204] was less accurate. Relationships between Rn and Rs gave lower intercept values (indicative of net long-wave fluxes) than expected. Data for a year gave a value of 0.43 for the ratio of Rp to Rs; instrumental problems prevented longer-term comparisons. VPD during daylight hours (VPDday) varied significantly between the northernmost weather station (at 17°26′S) and the most inland, at 17°55′S but at slightly higher altitude (66m compared to 160 m). The r2 values for the linear relationships between maximum and minimum temperatures and VPD day varied across the region, ranging from 0.52 to 0.79. Using a process-based forest production model (3-PG; [For. Ecol. Manage. 95 (1997) 209]) we show that differences in VPD can lead to considerable (28%) reductions in the yield of plantation eucalyptus

Parameterisation of 3-PG model for fast-growing Eucalyptus grandis plantations

The 3-PG model [J.J. Landsberg, R.H. Waring, A generalised model of forest productivity using simplified concepts of radiation-use efficiency, carbon balance and partitioning, For. Ecol. Manage. 95 (1997) 209] was parameterised for Eucalyptus grandis hybrid plantations based on data collected in an experimental catchment. Model performance was compared with data collected monthly in 12 plots over 3.5 years from five genotypes in the catchment and in growth plots measured annually in two other regions. Application of the model using the parameter values determined in the study allowed us to describe accurately the growth patterns of stands in terms of mean annual increment, total stand volume, basal area, diameter at breast height, leaf area index and available soil water. The observed differences in production between genotypes (clones) could be attributed primarily to differences in biomass partitioning and secondarily to differences in stomatal conductance. There were differences between clones in parameters affecting the allometric relationship between stem mass and diameter at breast height, biomass allocation to roots, the ratio of foliage to stem allocation and maximum stomatal conductance. The model can be used to simulate growth and yield in areas for which it has not been calibrated, and parameters obtained in the calibration process described are being applied to estimate growth in 181 000 ha of E. grandis hybrid plantations in Brazil

Stream flow unaffected by Eucalyptus plantation harvesting implicates water use by the native forest streamside reserve

Study region: Tropical Atlantic Forest region, Brazil. Study focus: The temporal and spatial dynamics of soil water, water table depth and stream flow in relation to precipitation and the harvesting and regrowth cycle of a Eucalyptus grandis hybrid plantation in a headwater catchment. This landscape contains a mosaic of eucalypt plantation grown for pulpwood on plateau tops and native forest reserves in gullies. Instead of harvesting the native forest to test this effect, we conducted a virtual experiment using a soil and hydrological model (HYDRUS). New hydrological insights: Plantation harvest had little effect on steam flow, despite a 6–11 m rise in water table level under the plantation area. This result suggests that the native forest reserve intercepted groundwater moving laterally between the plantation and the stream. Measured and simulated runoff coefficients were similarly low (5% and 3%, respectively), but simulated removal of the native forest led to an increase to 38%. Therefore, plantation management in this type of landscape is likely to have little impact on stream flows where there is an intact native rainforest reserve beside the stream. Keywords: Eucalyptus plantation, Hydrology, Harvesting, Native forest, Stream flow, Modellin

Data_Sheet_1_Improving spatial predictions of Eucalypt plantation growth by combining interpretable machine learning with the 3-PG model.docx

Accurate predictions of forest plantation growth provide forest managers with improved forest inventory estimates, forest valuation, and timely harvest schedules. Forest process-based models are increasingly used for quantifying current and potential productivity, yield gaps, and factors limiting growth, such as climate variability, soil characteristics, and water deficit. Improvements in the availability and resolution of spatial and temporal data combined with advancements in machine learning algorithms provide new opportunities to improve model predictions. This study shows how interpretable machine learning (ML) can be used to independently predict site soil fertility rating (FR) and incorporate these results into the 3-PG forest process-based model to accurately predict plantation growth. Four ensemble decision tree machine learning models—random forest trees, extremely randomized trees, gradient boost, and XG boost—were trained and compared using spatial cross-validation across the study area. FR predictions were estimated in relation to the influencing soil type and terrain characteristics, and interpretable ML methods were used to show how input feature permutations may relate to the soil fertility predictions. The results show the explanatory variables are similar across the selected ML models, with the strongest influencing variables being water leaching index, site aspect, and the silt and sand soil texture properties. The extremely randomized tree models showed the overall best performance, with only a small variation in performance across the four ML models. The method was applied to Eucalyptus nitens plantations covering over 63,000 ha in north-west Tasmania, Australia. The results using the predicted FR spatial grid with 3-PG show a strong correlation with observed growth for tree diameter and stand volume (R2 tree diameter at breast height = 0.97, RMSE = 0.85 m; R2 stand volume = 0.96, RMSE = 23.1 m3 ha−1) obtained from 161 permanent sample inventory plots ranging from 3 to 31 years old. This method has practical utility for other study sites to calibrate forest plantation soil fertility rating, in both the spatial and point-scale 3-PG model, where spatial data of soil characteristics are available. The derived soil fertility grid can provide valuable insights into the spatial variability of soil fertility in unknown areas.</p

Needs and opportunities for using a process-based productivity model as a practical tool in Eucalyptus plantations.

This paper presents the application of a process-based model (PBM) to the management of 181,000 ha of Eucalyptus grandis plantations in Brazil owned by Aracruz Celulose (Arcel). The company recently adopted the process-based model 3-PG (Physiological Principles Predicting Growth) for use in research applications and as an analytical tool as part of its forest management systems. The model is being used to predict potential productivity in terms of forest volume in current production areas and on new lands, and to quantify the effects of environmental factors and management actions on forest productivity. This use allows quantification of the risks associated with production, and increases the quality of the decision-making process. The model was calibrated for an experimental catchment site, and when applied in other regions the goodness of fit between estimated and observed peak mean annual increment was high (r 2=0.93, P<0.05, S.E.=1.44 m3 ha-1 per year). Current research is focused on questions of soil fertility ratings, the physiological characteristics and differences among various clones at several sites, and on the application of 3-PG using spatial data bases running in a geographic information system. The progress made in applying 3-PG reported here demonstrates the valuable role that process-based models can play as practical and applied tools in commercial forest management, especially in fast-growing Eucalyptus plantations with short-rotation times (5-7 years), and for testing hypotheses about the way trees function and respond to environmental changes