Accuracy and equivalence testing of crown ratio models and assessment of their impact on diameter growth and basal area increment predictions of two variants of the Forest Vegetation Simulator

2009 ◽  
Vol 39 (3) ◽  
pp. 655-665 ◽  
Author(s):  
Laura P. Leites ◽  
Andrew P. Robinson ◽  
Nicholas L. Crookston
Keyword(s):  
Predictor Variable ◽  
Basal Area ◽  
Forest Growth ◽  
Forest Vegetation ◽  
Basal Area Increment ◽  
Growth And Yield ◽  
Estimation Accuracy ◽  
Diameter Growth ◽  
Forest Vegetation Simulator ◽  
South Central

Diameter growth (DG) equations in many existing forest growth and yield models use tree crown ratio (CR) as a predictor variable. Where CR is not measured, it is estimated from other measured variables. We evaluated CR estimation accuracy for the models in two Forest Vegetation Simulator variants: the exponential and the logistic CR models used in the North Idaho (NI) variant, and the Weibull model used in the South Central Oregon and Northeast California (SO) variant. We also assessed the effects of using measured (CRm) versus predicted (CRp) crown ratio for predicting 10 year DG and 30 year basal area increment (BAI). Evaluation criteria included equivalence tests, bias, root mean square error, and Spearman’s coefficient of rank correlation. Inventory data from the Winema and the Colville National Forests were used. Results showed that the NI variant models overpredicted CR when CRm was below 40% and underpredicted CR when it was above 60%, whereas the SO variant model overpredicted CR when CRm was smaller than 60%. Differences between CRm and CRp were positively correlated with differences in DG predictions. Using CRm versus CRp resulted in 30 year BAI absolute percent differences of 10% or less for more than 50% of the plots.

scholarly journals Accuracy and Precision of 10 Year Predictions for Forest Vegetation Simulator—Lake States

2000 ◽  
Vol 17 (2) ◽  
pp. 62-70 ◽  
Author(s):  
Seal J. Canavan ◽  
Carl W. Ramm
Keyword(s):  
Basal Area ◽  
Forest Vegetation ◽  
Individual Species ◽  
Diameter Growth ◽  
Forest Vegetation Simulator ◽  
White Oak ◽  
Individual Tree ◽  
Projection System ◽  
Accuracy And Precision ◽  
Lake States

Abstract This study is a followup to the 5 yr validation of the Lake States TWIGS (The Woodsman's Ideal Growth Projection System) projection system by Guertin and Ramm (1996). Accuracy and precision of 10 yr diameter growth, basal area growth and mortality predicted by the Lake States variant of the Forest Vegetation Simulator (FVS) were evaluated for seven upland hardwood species in Michigan's northern Lower Peninsula. The robustness of FVS predictions was examined by varying projection cycle length and the level of detail of stand and tree-information included in growth projections.The data used in the analysis consisted of individual tree measurements from 44 stands across 10 ecological land type phases in the Manistee National Forest. FVS-Lake States was found to consistently overpredict 10 yr diameter growth across all seven species. Ten year diameter growth was predicted within ±0.5 in. across all projections for nearly all species and size-class combinations for the seven species examined. Basal area and mortality errors were less consistent. Mean errors for trees per acre ranged from -24 for red maple to +14 for white oak. These errors led to a consistent overprediction of basal area per acre for all species combined, while prediction errors for individual species were less than ±8 ft²/ac. Precision was variable, especially for mortality predictions. The most accurate predictions were obtained with longer cycle lengths and with projections using tree diameter, tree height, and crown ratio along with site index and individual tree past diameter growth. North. J. Appl. For. 17(2):62-70.

scholarly journals How random are predictions of forest growth? The importance of weather variability

2020 ◽  
Author(s):  
Joanna Horemans ◽  
Olga Vindušková ◽  
Gaby Deckmyn
Keyword(s):  
Climate Change ◽  
Uncertainty Analysis ◽  
Climate Models ◽  
Global Climate ◽  
Basal Area ◽  
Random Order ◽  
Forest Growth ◽  
Global Climate Models ◽  
Growth And Yield ◽  
Weather Variability

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%.

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
Keyword(s):  
Forest Type ◽  
Geographical Area ◽  
Basal Area ◽  
Forest Growth ◽  
Model Systems ◽  
Growth And Yield ◽  
Permanent Plots ◽  
Stand Age ◽  
Yield Model ◽  
Mixed Forests

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.

scholarly journals Using JABOWA-3 for forest growth and yield predictions under diverse forest conditions of Nova Scotia, Canada

2012 ◽  
Vol 88 (06) ◽  
pp. 708-721 ◽  
Author(s):  
M. Irfan Ashraf ◽  
Charles P.-A. Bourque ◽  
David A. MacLean ◽  
Thom Erdle ◽  
Fan-Rui Meng
Keyword(s):  
Climate Change ◽  
Nova Scotia ◽  
Model Prediction ◽  
Prediction Accuracy ◽  
Basal Area ◽  
Forest Growth ◽  
Growth And Yield ◽  
Individual Tree ◽  
Forest Conditions ◽  
Forest Growth And Yield

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.

A comparison of the growth basal area stocking level curve to a number of curves developed from south central Oregon tree data

1986 ◽  
Vol 16 (3) ◽  
pp. 508-512
Author(s):  
William E. Hopkins
Keyword(s):  
Ponderosa Pine ◽  
Basal Area ◽  
Climatic Conditions ◽  
Diameter Growth ◽  
The West ◽  
South Central ◽  
White Fir ◽  
Significant Difference ◽  
Tree Data ◽  
Single Regression

A single regression supporting the growth basal area concept was compared with regressions developed from various south central Oregon coniferous trees. Growth basal area is the basal area at which dominant trees grow 1 in. (25 mm) in diameter per decade referenced at age 100 years. Regressions developed from ponderosa pine (Pinusponderosa Laws.) and lodgepole pine (Pinuscontorta Dougl.) data were significantly different from the single published regression. White fir (Abiesconcolor Gord. & Glend.) and Shasta red fir (Abiesmagnifica var. shastensis Lemm.) data also proved to be significantly different. Douglas-fir (Pseudotsugamenziesii (Mirb.) Franco) data indicated no significant difference when compared with the published growth basal area curve. Therefore, application of the published growth basal area curve to stands found in south central Oregon would be considerably less precise than those curves developed from tree data collected in south central Oregon. Since tree stockability and diameter growth react to both edaphic and climatic conditions, caution is extended to users in other parts of the west.

Testing the Lake States variant of FVS (Forest Vegetation Simulator) for the main forest types of northern Ontario

2004 ◽  
Vol 80 (4) ◽  
pp. 495-506 ◽  
Author(s):  
V. Lacerte ◽  
G R Larocque ◽  
M. Woods ◽  
W J Parton ◽  
M. Penner
Keyword(s):  
Black Spruce ◽  
Basal Area ◽  
Stand Density ◽  
Site Index ◽  
Forest Vegetation ◽  
Forest Vegetation Simulator ◽  
Consistency Analysis ◽  
Northern Ontario ◽  
Individual Tree ◽  
Stand Basal Area

The Lake States variant of the FVS (Forest Vegetation Simulator) model (LS-FVS), also known as the LS-TWIGS variant of FVS, was validated for black spruce (Picea mariana (Mill.) BSP), white spruce (Picea glauca (Moench) Voss), jack pine (Pinus banksiana Lamb.) and trembling aspen (Populus tremuloides Michx.) forests in northern Ontario. Individual-tree data from 537 remeasured sample plots were used. This dataset included different combinations of site index, stand density and age. It was possible to compare observations and predictions for different projection length periods. The validation exercise included a biological consistency analysis, the computation of mean percent difference (MPD) for stand density, stand basal area, top height and quadratic mean diameter (QMD) and the comparison of observed and predicted individual-tree dbh. The biological consistency analysis indicated that LS-FVS logically predicted the effect of site index on top height, stand basal area and QMD for black spruce and jack pine. However, the decrease in stand basal area at young ages was inconsistent with the normal development pattern of the forest stands under study and was attributed to deficiencies in the prediction of mortality. LS-FVS was found to underpredict stand density, stand basal area and top height and to over-predict QMD. Even though there were large errors in the prediction of change in stand density, LS-FVS was nevertheless consistent in the prediction of the shape of the dbh size distribution. Key words: FVS, Forest Vegetation Simulator, validation, biological consistency analysis

Predicting forest growth and yield in northeastern Ontario using the process-based model of TRIPLEX1.0

2005 ◽  
Vol 35 (9) ◽  
pp. 2268-2280 ◽  
Author(s):  
Xiaolu Zhou ◽  
Changhui Peng ◽  
Qing-Lai Dang ◽  
Jiaxin Chen ◽  
Sue Parton
Keyword(s):  
Black Spruce ◽  
Basal Area ◽  
Tree Height ◽  
Field Measurements ◽  
Forest Growth ◽  
Growth And Yield ◽  
Inventory Data ◽  
Yield Data ◽  
Yield Table ◽  
Forest Growth And Yield

Process-based carbon dynamic models are rarely validated against traditional forest growth and yield data and are difficult to use as a practical tool for forest management. To bridge the gap between empirical and process-based models, a simulation using a hybrid model of TRIPLEX1.0 was performed for the forest growth and yield of the boreal forest ecosystem in the Lake Abitibi Model Forest in northeastern Ontario. The model was tested using field measurements, forest inventory data, and the normal yield table. The model simulations of tree height and diameter at breast height (DBH) showed a good agreement with measurements for black spruce (Picea mariana (Mill.) BSP), jack pine (Pinus banksiana Lamb.), and trembling aspen (Populus tremuloides Michx.). The coefficients of determination (R2) between simulated values and permanent sample plot measurements were 0.92 for height and 0.95 for DBH. At the landscape scale, model predictions were compared with forest inventory data and the normal yield table. The R2 ranged from 0.73 to 0.89 for tree height and from 0.72 to 0.85 for DBH. The simulated basal area is consistent with the normal yield table. The R2 for basal area ranged from 0.82 to 0.96 for black spruce, jack pine, and trembling aspen for each site class. This study demonstrated the feasibility of testing the performance of the process-based carbon dynamic model using traditional forest growth and yield data and the ability of the TRIPLEX1.0 model for predicting growth and yield variables. The current work also introduces a means to test model accuracy and its prediction of forest stand variables to provide a complement to empirical growth and yield models for forest management practices, as well as for investigating climate change impacts on forest growth and yield in regions without sufficient established permanent sample plots and remote areas without suitable field measurements.

scholarly journals Trockenperioden seit 1900 und Waldwachstum: eine Analyse langfristiger Datenreihen | Drought periods since 1900 and growth of forest stands: an analysis of long-term data series

2008 ◽  
Vol 159 (10) ◽  
pp. 352-361 ◽  
Author(s):  
Andreas Zingg ◽  
Anton Bürgi
Keyword(s):  
Tree Growth ◽  
Abies Alba ◽  
Basal Area ◽  
Basal Area Increment ◽  
Growth And Yield ◽  
Data Series ◽  
Silver Fir ◽  
Eine Analyse ◽  
Daily Precipitation Data

Drought during the vegetation period has en effect on tree growth. Using daily precipitation data and growth records from long-term research plots, we investigated what can be defined as “drought” and how strong its effect is. Dry or humid periods are defined as the deviation from the long-term daily mean of precipitation. Such periods must last at least 60 days to be considered as being decisive for tree growth. The drought values are used together with other site and stand parameters as explaining variables in a model for the basal area increment for Norway spruce (Picea abies [L] H. Karst.), silver fir (Abies alba Mill.), European beech (Fagus sylvatica L.) and oak (Quercus L), based on data from long-term growth and yield plots which are located in the neighbourhood of precipitation measurement stations. These models explain 55 to 89% of the variance. In drought situations basal area increment drops clearly for spruce and beech, for fir only weakly and oak shows no reaction. Furthermore, we checked if there happened additional or compulsory felling after drought periods and if the basal area growth changed significantly compared to the growth in the period before. For both it is not the case, despite distinct drought periods in the last century, especially in the 40s with the extreme year of 1947. Therefore we do not expect dramatic changes for the investigated species in similar drought situations under the prerequisite that the other conditions do not change essentially.

Modeling annualized occurrence, frequency, and composition of ingrowth using mixed-effects zero-inflated models and permanent plots in the Acadian Forest Region of North America

2011 ◽  
Vol 41 (10) ◽  
pp. 2077-2089 ◽  
Author(s):  
Rongxia Li ◽  
Aaron R. Weiskittel ◽  
John A. Kershaw
Keyword(s):  
North America ◽  
Random Effects ◽  
Negative Binomial ◽  
Basal Area ◽  
Forest Growth ◽  
Occurrence Frequency ◽  
Growth And Yield ◽  
Permanent Plots ◽  
Forest Region ◽  
Acadian Forest

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.

Evaluating Long-Term Seedling Growth across Densities Using Nelder Plots and the Forest Vegetation Simulator (FVS) in the Black Hills, South Dakota, USA

2021 ◽  
Author(s):  
Wade T Tinkham ◽  
Mike A Battaglia ◽  
Chad M Hoffman
Keyword(s):  
Seedling Growth ◽  
Tree Growth ◽  
Forest Growth ◽  
Forest Vegetation ◽  
Planting Density ◽  
Harvest Scheduling ◽  
Sustainable Harvest ◽  
Forest Vegetation Simulator ◽  
Small Tree ◽  
Fuel Treatment

Abstract Small-tree development affects future stand dynamics and dictates many ecological processes within a site. Accurately representing this critical component of stand development is important for evaluating treatment alternatives from fuel hazard reduction to harvest scheduling. As with all forest growth, competition with other vegetation is known to regulate small-tree growth dynamics. This study uses three Nelder plots with 45 years of ponderosa pine growth to understand competition effects on seedling growth and evaluate the Forest Vegetation Simulator (FVS) Central Rockies (CR) variant’s ability to represent these dynamics. Removal of herbaceous competition before planting increased tree diameters by 50–135% and height by 35–75% across a planting density gradient at age 12. However, by age 45, the effect of herbaceous competition on tree size was no longer evident. Instead, trees at the lowest planting density had diameters 2.5–3 times larger than the most densely grown trees. Forest Vegetation Simulator (FVS) simulations underpredicted diameter at breast height (dbh) by 35–50% and 0–35% for 12 and 45-year-old trees, respectively. There was an underprediction bias of 15–20% for heights at age 12 and overpredictions of 5–10% at age 45. Continuous underprediction of dbh will affect the reliability of modeled fuel treatment longevity and sustainable harvest scheduling. Study Implications: Management and modeling of small-tree growth can affect decision-making for a range of activities, from assessing fuel treatment effectiveness to sustainable harvest scheduling. Effective small-tree density management can increase tree diameters at age 45 by 2.5–3 times the diameter of unthinned sites. FVS-CR underpredicted age 12 heights by 0–45% and age 45 diameters by 0–35% as a function of planting density, suggesting that the model fails to capture the intensity or timing of density-induced competition. These underpredictions will inflate the length of time fuel treatments remain effective and decrease projected sustainable harvest levels supported by responsible management.

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