scholarly journals Stand-Level Components of a Growth and Yield Model for Nothofagus Mixed Forests from Southern Chile

Forests ◽  
2020 ◽  
Vol 11 (8) ◽  
pp. 810
Author(s):  
Sebastian Palmas ◽  
Paulo C. Moreno ◽  
Wendel P. Cropper ◽  
Alicia Ortega ◽  
Salvador A. Gezan

Reliable information on stand dynamics and development is needed to improve management decisions on mixed forests, and essential tools for this purpose are forest growth and yield (G&Y) models. In this study, stand-level G&Y models were built for cohorts within the natural mixed second-growth Nothofagus-dominated forests in Chile. All currently available (but limited) data, consisting of a series of stratified temporary and permanent plots established in the complete range of this forest type, were used to fit and validate these models. Linear and nonlinear models were considered, where dominant stand age, number of trees, and the proportion of basal area of Nothofagus species resulted in significant predictors to project future values of stand basal area for the different cohorts (with R2 > 0.51 for the validation datasets). Mortality was successfully modeled (R2 = 0.79), based on a small set of permanent plots, using the concept of self-thinning with a proposed model defined by the idea that, as stands get closer to a maximum density, they experience higher levels of mortality. The evaluation of these models indicated that they adequately represent the current understanding of dynamics of basal area and mortality of Nothofagus and companion species in these forests. These are the first models fitted over a large geographical area that consider the dynamics of these mixed forests. It is suggested that the proposed models should constitute the main components of future implementations of G&Y model systems.

2009 ◽  
Vol 85 (1) ◽  
pp. 57-64 ◽  
Author(s):  
C -H. Ung ◽  
P Y Bernier ◽  
X J Guo ◽  
M -C. Lambert

We have adjusted two growth and yield models to temporary sample plots from across Canada, and used climate variables in lieu of phytometric indices such as site index to represent, in part, the site-level variability in growth potential. Comparison of predicted increments in plot-level height, basal area and merchantable wood volume to increments of these variables measured in permanent sample plots shows a moderate to poor predictive ability. Comparison with the performance of four operational growth and yield models from different provinces across Canada shows comparable predictive power of this new model versus that of the provincial models. Based on these results, we suggest that the simplification of regional growth and yield models may be achieved without further loss of predictive power, and that the large error in the prediction of growth increment is mostly associated with the use of temporary sample plots which, by definition, contain little information on stand dynamics. We also suggest that, because of the empirical nature of these growth and yield models, the scale of application should determine the appropriate scale of the model. National estimates of forest growth are therefore less likely to be biased if obtained from a national model only than if obtained from a combination of regional models, where those exist, gap-filled with estimates from a national model. Key words: yield model, merchantable wood volume, stand age, climatic variables, simultaneous regression, robust regression


2011 ◽  
Vol 41 (10) ◽  
pp. 2077-2089 ◽  
Author(s):  
Rongxia Li ◽  
Aaron R. Weiskittel ◽  
John A. Kershaw

Forest tree ingrowth is a highly variable and largely stochastic process. Consequently, predicting occurrence, frequency, and composition of ingrowth is a challenging task but of great importance in long-term forest growth and yield model projections. However, ingrowth data often require different statistical techniques other than traditional Gaussian regression, because these data are often bounded, skewed, and non-normal and commonly contain a large fraction of zeros. This study presents a set of regression models based on discrete Poisson and negative binomial probability distributions for ingrowth data collected from permanent sample plots in the Acadian Forest Region of North America. Models considered here include regular Poisson, zero-inflated Poisson (ZIP), zero-altered Poisson (ZAP; hurdle Poisson), regular negative binomial (NB), zero-inflated negative binomial (ZINB), and zero-altered negative binomial (ZANB; hurdle NB). Plot-level random effects were incorporated into each of these models. The ZINB model with random effects was found to provide the best fit statistics for modeling annualized occurrence and frequency of ingrowth. The key explanatory variables were stand basal area per hectare, percentage of hardwood basal area, number of trees per hectare, a measure of site quality, and the minimum measured diameter at breast height of each plot. A similar model was developed to predict species composition. All models showed logical behavior despite the high variability observed in the original data.


2010 ◽  
Vol 40 (8) ◽  
pp. 1517-1528 ◽  
Author(s):  
Leah C. Rathbun ◽  
Valerie LeMay ◽  
Nick Smith

Individual-tree distance-independent models were developed to estimate regular mortality for western hemlock ( Tsuga heterophylla (Raf.) Sarg.), Douglas-fir ( Pseudotsuga menziesii (Mirb.) Franco var. menziesii), and western redcedar ( Thuja plicata Donn ex D. Don) in the coastal temperate rain forests of British Columbia, Canada. Permanent plots remeasured at intervals ranging from 1 to 17 years were used. Because of the irregular remeasurement intervals, survival was estimated using a generalized logistic model and mortality was calculated by subtraction. Basal area of trees larger than the subject tree provided reasonably accurate mortality estimates for larger trees. However, poor results were obtained for trees less than 7.5 cm in diameter at breast height, which had higher mortality rates than the larger trees. Since the implementation of a survival (or mortality) model within a growth and yield model environment can largely affect estimation accuracy, three methods of implementing the model were also evaluated. A probability multiplier approach where the stems per hectare surviving to the next period is estimated by multiplying the probability of survival by the stems per hectare at the beginning of the time period is recommended. This is equivalent to a stochastic approach averaged over many repetitions but with much less processing time.


1991 ◽  
Vol 15 (4) ◽  
pp. 213-216 ◽  
Author(s):  
Quang V. Cao ◽  
Kenneth M. Durand

Abstract A compatible growth and yield model was developed based on remeasurement data collected from 183 plots on unthinned improved eastern cottonwood (Populus deltoides Bartr.) plantations in the lower Mississippi Delta. The Sullivan and Clutter (1972) equation form was selected for predicting cubic-foot volume yield and projecting volume from site index and initial age and basal area. Yield equations explained 97% and 94%, respectively, of the variations in total outside bark and merchantable inside bark volumes. Mean annual increment of merchantable volume culminated between 8 and 15 years, depending on site index and initial basal area. South. J. Appl. For. 15(4):213-216.


Author(s):  
Joanna Horemans ◽  
Olga Vindušková ◽  
Gaby Deckmyn

Quantifying the output uncertainty and tracking down its origins is key to interpreting the results of model studies. We perform such an uncertainty analysis on the predictions of forest growth and yield under climate change. We specifically focus on the effect of the inter-annual climate variability. For that, the climate years in the model input (daily resolution) were randomly shuffled within each 5-year period. In total, 540 simulations (10 parameter sets, 9 climate shuffles, 3 global climate models and 2 mitigation scenarios), were made for one growing cycle (80 years) of a Scots pine forest growing in Peitz (Germany). Our results show that, besides the important effect of the parameter set, the random order of climate years can significantly change results such as basal area and produced volume, and the response of these to climate change. We stress that the effect of weather variability should be included in the design of impact model ensembles, and the accompanying uncertainty analysis. We further suggest presenting model results as likelihoods to allow risk assessment. For example, in our study the likelihood of a decrease in basal area of >10% with no mitigation was 20.4%, while the likelihood of an increase >10% was 34.4%.


2012 ◽  
Vol 88 (06) ◽  
pp. 708-721 ◽  
Author(s):  
M. Irfan Ashraf ◽  
Charles P.-A. Bourque ◽  
David A. MacLean ◽  
Thom Erdle ◽  
Fan-Rui Meng

Empirical growth and yield models developed from historical data are commonly used in developing long-term strategic forest management plans. Use of these models rests on an assumption that there will be no future change in the tree growing environment. However, major impacts on forest growing conditions are expected to occur with climate change. As a result, there is a pressing need for tools capable of incorporating outcomes of climate change in their predictions of forest growth and yield. Process-based models have this capability and may, therefore, help to satisfy this requirement. In this paper, we evaluate the suitability of an ecological, individual-tree-based model (JABOWA-3) in generating forest growth and yield projections for diverse forest conditions across Nova Scotia, Canada. Model prediction accuracy was analyzed statistically by comparing modelled with observed basal area and merchantable volume changes for 35 permanent sample plots (PSPs) measured over periods of at least 25 years. Generally, modelled basal area and merchantable volume agreed fairly well with observed data, yielding coefficients of determination (r2) of 0.97 and 0.94 and model efficiencies (ME) of 0.96 and 0.93, respectively. A Chi-square test was performed to assess model accuracy with respect to changes in species composition. We found that 83% of species-growth trajectories based on measured basal area were adequately modelled with JABOWA-3 (P > 0.9). Model-prediction accuracy, however, was substantially reduced for those PSPs altered by some level of disturbance. In general, JABOWA-3 is much better at providing forest yield predictions, subject to the availability of suitable climatic and soil information.


1999 ◽  
Vol 23 (3) ◽  
pp. 179-185 ◽  
Author(s):  
Stacey W. Martin ◽  
Graham H. Brister

Abstract Using 5 yr remeasurement data from even-aged natural loblolly pine (Pinus taeda L.) stands in the Georgia Piedmont, a system of growth equations was developed to project pine yield over time that accounts for hardwood competition. In this system, the increase in the proportion of hardwood basal area over time is estimated, then the projected pine basal area and trees per acre are adjusted inversely to account for this increase. The parameter estimates for this system ensure compatibility between volume prediction and projection equations and the proportion of hardwood basal area, pine basal area, dominant height, and trees per acre projection equations. The whole-stand growth and yield system developed here coupled with published merchantable yield equations allow for the evaluation of the impact of hardwoods on future stand yield and product distributions. The results indicate that the impact of hardwood competition on pine yield is substantial and occurs mainly as a reduction in sawtimber volume. South. J. Appl. For. 16(3):179-185.


2009 ◽  
Vol 33 (2) ◽  
pp. 69-76 ◽  
Author(s):  
Dean W. Coble

Abstract A new compatible whole-stand growth-and-yield model to predict total tree cubic-foot volume per acre yield (outside and inside bark) was developed for unmanaged loblolly pine (Pinus taeda) and slash pine (Pinus elliottii) plantations in East Texas. This model was compared with the noncompatible whole-stand model of Lenhart (<xref ref-type="bibr" rid="B15-2127">Lenhart, 1996</xref>, Total and partial stand-level yield prediction for loblolly and slash pine plantations in east Texas, South. J. Appl. For. 20(1):36–41) and the <xref ref-type="bibr" rid="B15-2127">Lenhart (1996)</xref> model refit to current data. For the two species, all three models were evaluated with independent observed data. The model developed in this study outperformed both Lenhart models in prediction of future yield and basal area per acre for all age classes combined and by 5-year age classes. The Lenhart models consistently overestimated yield and basal area per acre. All three models predicted surviving trees per acre similarly. An example is also provided to show users how to use the new whole-stand model.


1983 ◽  
Vol 13 (4) ◽  
pp. 563-571 ◽  
Author(s):  
Robert L. Bailey ◽  
Kenneth D. Ware

A measure of kind and level of thinning is developed and its relationship to other stand attributes such as number of trees, basal area, and volume removed in thinning is quantified. This measure or thinning index is based on the ratio of the quadratic mean diameter of thinned trees to the quadratic mean diameter of all trees before thinning. The thinning index is then logically incorporated into a thinning multiplier from which is derived a compatible basal-area growth projection model to generalize the previous concepts for thinning effects in systems for predicting growth and yield. Empirical tests with data from thinned and unthinned natural stands of loblolly pine, from thinned and unthinned slash pine plantations, and from thinned western larch stands show the model to provide estimates with improved properties. Hence, the thinning index and the thinning multiplier are also proposed for other situations involving effects of thinning.


1984 ◽  
Vol 14 (2) ◽  
pp. 295-295
Author(s):  
Robert L. Bailey ◽  
Kenneth D. Ware

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