Mapping the effect of spatial and temporal variation in climate and soils on Eucalyptus plantation production with 3-PG,a process-based growth model

In the wet tropics, near the Atlantic Coast of Brazil, drought may reduce plantation yields by as much one-third over a six-to-seven-year rotation. For land owners, annual variation in production cannot be estimated with empirical models. In this paper, we examine whether the process-based growth model, 3-PG is sufficiently sensitive to climatic variation to provide a virtual record of changes in growing stock across 180,000 ha eucalypt plantation estate. We first mapped variation in climate and soil properties, and then ran simulations for the current planted forest with ages varying from one to seven years. Model predictions of stand volume and mean tree diameter agreed closely with measurements acquired on 60 reference plots monitored over the test period; the prediction of mean annual increment (MAI) was less reliable. Available soil water (ASW) and leaf area index (LAI) were also measured and compared with the model estimations. Vapour pressure deficit (VPD) and ASW accounted for most of the variation in yields. We conclude that this spatial modelling approach offers a reasonable alternative to extensive ground surveys, particularly when climatic variation extends beyond the historical average for a region.     

Application of the 3PG forest growth model to a <Emphasis Type="Italic">Eucalyptus globulus</Emphasis> 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.     

Assessing rates of forest change and fragmentation in Alabama,USA, using the vegetation change tracker model

Forest change is of great concern for land use decision makers and conservation communities. Quantitative and spatial forest change information is critical for addressing many pressing issues, including global climate change, carbon budgets, and sustainability. In this study, our analysis focuses on the differences in geospatial patterns and their changes between federal forests and nonfederal forests in Alabama over the time period 1987–2005, by interpreting 163 Landsat Thematic Mapper (TM) scenes using a vegetation change tracker (VCT) model. Our analysis revealed that for the most part of 1990 s and between 2000 and 2005, Alabama lost about 2% of its forest on an annual basis due to disturbances, but much of the losses were balanced by forest regeneration from previous disturbances. The disturbance maps revealed that federal forests were reasonably well protected, with the fragmentation remaining relatively stable over time. In contrast, nonfederal forests, which are predominant in area share (about 95%), were heavily disturbed, clearly demonstrating decreasing levels of fragmentation during the time period 1987–1993 giving way to a subsequent accelerating fragmentation during the time period 1994–2005. Additionally, the identification of the statistical relationships between forest fragmentation status and forest loss rate and forest net change rate in relation to land ownership implied the distinct differences in forest cutting rate and cutting patterns between federal forests and nonfederal forests. The forest spatial change information derived from the model has provided valuable insights regarding regional forest management practices and disturbance regimes, which are closely associated with regional economics and environmental concerns.     

Comparison of Forest Inventory and Analysis surveys, basal area models, and fitting methods for the aspen forest type in Minnesota

The Forest Inventory and Analysis (FIA) unit of the U.S. Forest Service has collected, compiled, and made available plot data from three measurement periods (identified as 1977, 1990, and 2003, respectively) within Minnesota. Yet little if any research has compared the relative utility of these datasets for developing empirical yield models. This paper compares these and other subdatasets in the context of fitting a basal area (B) yield model to plot data from the aspen (Populus tremuloides Michx.) forest type. In addition, several models and fitting methods are compared for their applicability and stability over time. Results suggest that the three parent datasets, along with their subdatasets, provide very similar three parameter B yield model prediction capability, but as model complexity increases, variability in coefficient estimates increases between datasets. The absence of data for older aspen stands and the inherent noise within B data prevented the exact determination of an overall best model. However, the model B = b₁S^b₂(1 − exp( − b₃A)) with site index (S) and stand age (A) as predictors was found consistently among the highest in precision and stability. Additionally, nonlinear least squares and nonlinear mixed-effects fitting procedures produced similar model fits, but the latter is preferred for its potential to improve model projections. The results indicate little practical difference between datasets from different time periods and different sizes when used for fitting the models. Additionally, these results will likely extend to other states or regions with similar remeasurement data on aspen and other forest types, thus facilitating the development of other ecological models focused on forest management.