Partial Calibration of "ONTWIGS": A Forest Growth and Yield Projection System Adapted for Ontario

1994 ◽  
Vol 11 (2) ◽  
pp. 41-46 ◽  
Author(s):  
Bijan Payandeh ◽  
Pia Papadopol
Keyword(s):  
Basal Area ◽  
Forest Growth ◽  
Data Sets ◽  
Prediction Errors ◽  
Northern Ontario ◽  
Quadratic Mean ◽  
Tree Survival ◽  
Mean Diameter ◽  
Quadratic Mean Diameter ◽  
Stand Attributes

Abstract "ONTWIGS" (an adaptation of "LSTWIGS" for Ontario), was partially calibrated for permanent plots data sets from northern Ontario. Stand attributes used for calibration were quadratic mean diameter, number of trees, and basal area/ha. Simple local calibration was accomplished by adjusting tree survival and potential diameter growth coefficients so as to reduce the prediction errors to within 10% of the actual values over a 5-yr period. This resulted in prediction errors ranging from -9.9 to 6.9%, but with an overall average of only: -1.4, 1.0, and 0.2% for the spruce fir data; from -8.5 to 2.8%, but with an overall average of only -0.7, 0.5, and 0.4% for a black spruce drainage and fertilization experiment; and from -6.6 to 9.8%, but with an overall average of only -1.7, 0.0, and -1.8% for an unthinned red pine plantation for number of trees/ha, quadratic mean diameter, and basal area/ha, respectively. Results indicate that "ONTWIGS" may be locally calibrated through simple procedures to increase its prediction accuracy to ±5% of the observed stand attributes, averaging less than 3% for the major timber species in northern Ontario and for short to medium projection periods. However, the uncalibrated model should be used with caution for short terms, only and where no other projection tools are available. More extensive calibrations of "ONTWIGS" on larger and more representative data sets are currently underway. North. J. Appl. For. 11(2):41-46.

A Stocking Guide for Southern Bottomland Hardwoods

1995 ◽  
Vol 19 (3) ◽  
pp. 103-104 ◽  
Author(s):  
J. C. G. Goelz
Keyword(s):  
Basal Area ◽  
Bottomland Hardwoods ◽  
Quadratic Mean ◽  
Mean Diameter ◽  
Quadratic Mean Diameter

Abstract A stocking guide was developed from the data of Putnam, et al. (1960). The form of the stocking guide follows Gingrich (1967), although the “B”-line is based on the suggested residual stocking of Putnam, et al. (1960) rather than on minimum full stocking. This stocking guide is similar to the stocking guide for central upland hardwoods constructed by Gingrich, except that 100% stocking is 5-7 ft2² of basal area lower for the southern bottomland guide, across a range of quadratic mean diameter. South. J. Appl. For. 19(3):103-104.

Compatible basal-area growth and yield model for thinned and unthinned stands

1983 ◽  
Vol 13 (4) ◽  
pp. 563-571 ◽  
Author(s):  
Robert L. Bailey ◽  
Kenneth D. Ware
Keyword(s):  
Loblolly Pine ◽  
Basal Area ◽  
Growth And Yield ◽  
Yield Model ◽  
Projection Model ◽  
Quadratic Mean ◽  
Basal Area Growth ◽  
Area Growth ◽  
Mean Diameter ◽  
Quadratic Mean Diameter

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.

scholarly journals Development of Water Tupelo Coppice Stands on the Mobile-Tensaw River Delta for Five Years After Precommercial Thinning and Cleaning

2001 ◽  
Vol 25 (4) ◽  
pp. 165-172 ◽  
Author(s):  
J.C.G. Goelz ◽  
J.S. Meadows ◽  
T.C. Fristoe
Keyword(s):  
Basal Area ◽  
Individual Tree ◽  
Quadratic Mean ◽  
Precommercial Thinning ◽  
Mean Diameter ◽  
Water Tupelo ◽  
Rotation Age ◽  
Large Water ◽  
Quadratic Mean Diameter ◽  
The Individual

Abstract Three 4-yr-old stands (or locations) were selected for treatment. Treatment consisted of two components: (1) thinning water tupelo (Nyssa aquatica L.) stump sprouts and (2) cutting all stems of Carolina ash (Fraxinus caroliniana Mill.) and black willow (Salix nigra Marsh.) (cleaning). Contrary to results in other areas, survival of water tupelo coppice was very high and was not affected by the treatments. Cleaning had little or no positive effect on the individual tree or stand-level variables we measured. Thinning sprout clumps significantly increased diameter growth of water tupelo; the effect of thinning was considerably larger for one location. Stand basal area growth was decreased by thinning sprout clumps. However, quadratic mean diameter was increased by thinning, particularly at one location. Although thinning decreased basal area 5 yr after treatment, the increase in quadratic mean diameter was sufficient for there to be no significant effect of thinning on total volume 5 yr after treatment. Because of this, and in anticipation of imminent natural thinning of the unthinned plots, we suspect that the thinned plots will eventually have significantly greater standing volume than the unthinned plots, at least for the location where density of large sprouts was initially the highest. Rotation age will be decreased for that stand because stems will achieve merchantable size sooner. Thus we consider precommercial thinning of sprout clumps to be a potentially effective practice in stands with a high density of large water tupelo sprouts. South. J. Appl. For. 25(4):165–172.

scholarly journals Relating Forest Attributes with Area- and Tree-Based Light Detection and Ranging Metrics for Western Oregon

2010 ◽  
Vol 25 (3) ◽  
pp. 105-111 ◽  
Author(s):  
Michael E. Goerndt ◽  
Vincente J. Monleon ◽  
Hailemariam Temesgen
Keyword(s):  
Basal Area ◽  
Light Detection And Ranging ◽  
Stem Volume ◽  
Height Distribution ◽  
Light Detection ◽  
Quadratic Mean ◽  
Crown Width ◽  
Mean Diameter ◽  
Forest Attributes ◽  
Quadratic Mean Diameter

Abstract Three sets of linear models were developed to predict several forest attributes, using stand-level and single-tree remote sensing (STRS) light detection and ranging (LiDAR) metrics as predictor variables. The first used only area-level metrics (ALM) associated with first-return height distribution, percentage of cover, and canopy transparency. The second alternative included metrics of first-return LiDAR intensity. The third alternative used area-level variables derived from STRS LiDAR metrics. The ALM model for Lorey's height did not change with inclusion of intensity and yielded the best results in terms of both model fit (adjusted R2 = 0.93) and cross-validated relative root mean squared error (RRMSE = 8.1%). The ALM model for density (stems per hectare) had the poorest precision initially (RRMSE = 39.3%), but it improved dramatically (RRMSE = 27.2%) when intensity metrics were included. The resulting RRMSE values of the ALM models excluding intensity for basal area, quadratic mean diameter, cubic stem volume, and average crown width were 20.7, 19.9, 30.7, and 17.1%, respectively. The STRS model for Lorey's height showed a 3% improvement in RRMSE over the ALM models. The STRS basal area and density models significantly underperformed compared with the ALM models, with RRMSE values of 31.6 and 47.2%, respectively. The performance of STRS models for crown width, volume, and quadratic mean diameter was comparable to that of the ALM models.

scholarly journals Stocking Diagrams for Silvicultural Guideline in Korean Pines and Japanese Larch

Forests ◽  
2020 ◽  
Vol 11 (8) ◽  
pp. 833
Author(s):  
Daesung Lee ◽  
Jungkee Choi
Keyword(s):  
Basal Area ◽  
Stand Density ◽  
Japanese Larch ◽  
Larix Kaempferi ◽  
White Pine ◽  
Individual Tree ◽  
Quadratic Mean ◽  
Mean Diameter ◽  
Quadratic Mean Diameter ◽  
Species Specific

Appropriate management of stand density is necessary to avoid wasted growing space and overcrowding-induced self-thinning and therefore to optimize profitability. We developed a Gingrich-style stocking chart for Korean red pine (Pinus densiflora), Korean white pine (P. koraiensis), and Japanese larch (Larix kaempferi) in Korea. Datasets for even-aged stands were categorized into two censored datasets via relative density based on species-specific stand density indices to assign adequate plots for tree allometry. Censored plot data for maximum density on full stocking were used to develop A-level stocking based on mean individual tree area. In censored plot data for minimum density on full stocking, individual trees represented open-grown trees, and a crown competition factor of 100 was proposed as B-level stocking. Based on parameters estimated from allometry, stocking diagrams comprising quadratic mean diameter, number of trees, and basal area were correctly expressed. A-level stocking at the same quadratic mean diameter revealed that Korean white pine had the most trees and largest basal area, while Japanese larch had the fewest trees and smallest basal area. In contrast, B-level stocking disclosed that Japanese larch had the most trees and basal area, whereas Korean white pine had the fewest trees and smallest basal area. The stocking diagrams suggest that silvicultural treatments for these species should be species-specific.

Effects of density control and fertilization on growth and yield of young Douglas-fir plantations in the Pacific Northwest

2007 ◽  
Vol 37 (2) ◽  
pp. 449-461 ◽  
Author(s):  
Yuzhen Li ◽  
Eric C. Turnblom ◽  
David G. Briggs
Keyword(s):  
Basal Area ◽  
Douglas Fir ◽  
Growth And Yield ◽  
Quadratic Mean ◽  
Stand Growth ◽  
Density Control ◽  
Mean Diameter ◽  
Quadratic Mean Diameter ◽  
Area And Volume ◽  
Effects Of Density

To examine the effects of density control and fertilization on stand growth and yield of young Douglas-fir ( Pseudotsuga menziesii (Mirb.) Franco) plantations, seven treatment regimes were applied in sixty-three 9-year-old plots from nine installations across western Washington and Oregon. Fertilizer was applied at the rate of 220 kg N·ha–1 (as urea) at stand establishment and every 4 years thereafter. Results after 12 years showed that widely spaced stands exhibited significantly larger quadratic mean diameter than did narrowly spaced stands. The densest stands initially had the greatest overall stand basal area and volume, but accumulation rate in the dense stands had been declining with time. After 12 years, the less dense stands had met or exceeded the basal area periodic annual increment of dense stands. Across all densities, the periodic annual increments of quadratic mean diameter, basal area, and volume in fertilized plots were significantly greater than in unfertilized plots following the first and second urea applications. However, the first fertilization was insufficient to produce a significant increase in stand yield and the significant fertilization increases in yield were found following the second and the third urea applications. This study showed neither significant fertilization effect nor density effect on dominant height. In addition, no significant interactions were found for any stand growth and yield variables considered, but fertilization responses showed different trends among density treatments over time.

Eastern cottonwood clonal mixing study: predicted diameter distributions

1994 ◽  
Vol 24 (2) ◽  
pp. 405-414 ◽  
Author(s):  
Steven A. Knowe ◽  
G. Sam Foster ◽  
Randall J. Rousseau ◽  
Warren L. Nance
Keyword(s):  
Weibull Distribution ◽  
Basal Area ◽  
Diameter Distribution ◽  
Minimum Diameter ◽  
Quadratic Mean ◽  
Parameter Recovery ◽  
Eastern Cottonwood ◽  
Mean Diameter ◽  
Quadratic Mean Diameter ◽  
Diameter Distributions

A parameter recovery procedure for the Weibull distribution function was modified to incorporate monocultures and mixtures of eastern cottonwood (Populusdeltoides Bartr.) clones planted in Mississippi and Kentucky. Components of the system included functions to predict stand-level basal area and four percentiles (0th, 25th, 50th, and 95th) of the cumulative diameter distribution. Basal area was predicted as a function of surviving number of trees, dominant height, age, planting location, and the proportion of each clone planted. Clonal proportions, which accounted for 3.6% of the variation in observed basal area, were more important than differences in planting locations, which accounted for 3.0% of the variation. Interactions between clones in mixtures were not significant (p = 0.5676), but some cases of both over- and under-compensation appeared to be developing. Percentiles of the cumulative diameter distribution were predicted as functions of quadratic mean diameter, and therefore included indirect effects of both genetic and planting site differences. Only the minimum diameter (D0) was directly affected by proportions of clones planted. Most of the monocultures and mixtures of clones had smaller minimum diameters than expected for a given value of quadratic mean diameter. The predicted quadratic mean diameter and percentiles were used to recover parameters of the Weibull distribution such that the predicted diameter distribution has the same quadratic mean diameter as obtained from the stand basal area model. The predicted distributions indicated that a common stand-level model was not sufficient for accounting for variations in diameter distributions of eastern cottonwood clones. As a result of the differences in diameter distributions, monocultures and mixtures of the Texas clones appeared to have less volume and greater stand variance than the Mississippi clones.

Properties of the quadratic mean diameter in balanced diameter distributions

1985 ◽  
Vol 15 (2) ◽  
pp. 474-476
Author(s):  
Donald J. Weatherhead ◽  
Roger C. Chapman ◽  
John H. Bassman
Keyword(s):  
Stand Structure ◽  
Basal Area ◽  
Tree Size ◽  
Diameter Distribution ◽  
Quadratic Mean ◽  
Growing Stock ◽  
Mean Diameter ◽  
Quadratic Mean Diameter ◽  
Stand Basal Area ◽  
Diameter Distributions

Balanced diameter distributions are widely used to describe stand structure goals for residual growing stock in uneven-aged forests. The quadratic mean diameter is frequently used as a descriptor of a balanced diameter distribution. In this paper the quadratic mean diameter is shown to be independent of stand basal area for balanced diameter distributions with a common class width, maximum and minimum diameters, and de Liocourt's q ratio. Additionally it is shown that the quadratic mean diameter is relatively insensitive to changes in maximum tree size and q ratios for q ratios 1.5 and larger.

scholarly journals Chimera: A Multi-Task Recurrent Convolutional Neural Network for Forest Classification and Structural Estimation

2019 ◽  
Vol 11 (7) ◽  
pp. 768 ◽  
Author(s):  
Tony Chang ◽  
Brandon Rasmussen ◽  
Brett Dickson ◽  
Luke Zachmann
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Forest Structure ◽  
Canopy Cover ◽  
Basal Area ◽  
Above Ground Biomass ◽  
Test Set ◽  
Quadratic Mean ◽  
Mean Diameter ◽  
Quadratic Mean Diameter

More consistent and current estimates of forest land cover type and forest structural metrics are needed to guide national policies on forest management, carbon sequestration, and ecosystem health. In recent years, the increased availability of high-resolution (<30 m) imagery and advancements in machine learning algorithms have opened up a new opportunity to fuse multiple datasets of varying spatial, spectral, and temporal resolutions. Here, we present a new model, based on a deep learning architecture, that performs both classification and regression concurrently, thereby consolidating what was previously several independent tasks and models into one stream. The model, a multi-task recurrent convolutional neural network that we call the Chimera, integrates varying resolution, freely available aerial and satellite imagery, as well as relevant environmental factors (e.g., climate, terrain) to simultaneously classify five forest cover types (`conifer’, `deciduous’, `mixed’, `dead’, `none’ (non-forest)) and to estimate four continuous forest structure metrics (above ground biomass, quadratic mean diameter, basal area, canopy cover). We demonstrate the performance of our approach by training an ensemble of Chimera models on 9967 georeferenced (true locations) Forest Inventory and Analysis field plots from the USDA Forest Service within California and Nevada. Classification diagnostics for the Chimera ensemble on an independent test set produces an overall average precision, recall, and F1-score of 0.92, 0.92, and 0.92. Class-wise F1-scores were high for `none’ (0.99) and `conifer’ (0.85) cover classes, and moderate for the `mixed’ (0.74) class samples. This demonstrates a strong ability to discriminate locations with and without trees. Regression diagnostics on the test set indicate very high accuracy for ensembled estimates of above ground biomass ( R 2 = 0 . 84 , RMSE = 37 . 28 Mg/ha), quadratic mean diameter ( R 2 = 0 . 81 , RMSE = 3 . 74 inches), basal area ( R 2 = 0 . 87 , RMSE = 25 . 88 ft 2 /ac), and canopy cover ( R 2 = 0 . 89 , RMSE = 8 . 01 percent). Comparative analysis of the Chimera ensemble versus support vector machine and random forest approaches demonstrates increased performance over both methods. Future implementations of the Chimera ensemble on a distributed computing platform could provide continuous, annual estimates of forest structure for other forested landscapes at regional or national scales.

scholarly journals Modeling Dynamics of Structural Components of Forest Stands Based on Trivariate Stochastic Differential Equation

Forests ◽  
2019 ◽  
Vol 10 (6) ◽  
pp. 506 ◽  
Author(s):  
Petras Rupšys
Keyword(s):  
Differential Equation ◽  
Basal Area ◽  
Growth And Yield ◽  
Mixed Effect ◽  
Stand Volume ◽  
Quadratic Mean ◽  
Stand Growth ◽  
Mean Diameter ◽  
Quadratic Mean Diameter ◽  
Stand Basal Area

Research Highlights: Today’s approaches to modeling of forest stands are in most cases based on that the regression models and they are constructed as static sub-models describing individual stands variables. The disadvantages of this method; it is laborious because too many different equations need to be assessed and empirical choices of candidate equations make the results subjective; it does not relate to the stand variables dynamics against the age dimension (time); and does not consider the underlying covariance structure driving changes in the stand variables. In this study, the dynamical model defined by a fixed-and mixed effect parameters trivariate stochastic differential equation (SDE) is introduced and described how such a model can be used to model quadratic mean diameter, mean height, number of trees per hectare, self-thinning line, stand basal area, stand volume per hectare and much more. Background and Objectives: New developed marginal and conditional trivariate probability density functions, combining information generated from an age-dependent variance-covariance matrix of quadratic mean diameter, mean height and number of trees per hectare, improve stand growth prediction, and forecast (in forecast the future is completely unavailable and must only be estimated from historical patterns) accuracies. Materials and Methods: Fixed-and mixed effect parameters SDE models were harmonized to predict and forecast the dynamics of quadratic mean diameter, mean height, number of trees per hectare, basal area, stand volume per hectare, and their current and mean increments. The results and experience from applying the SDE concepts and techniques in an extensive whole stand growth and yield analysis are described using a Scots pine (Pinus sylvestris L.) experimental dataset in Lithuania. Results: The mixed effects scenario SDE model showed high accuracy, the percentage root mean square error values for quadratic mean diameter, mean height, number of trees per hectare, stand basal area and stand volume per hectare predictions (forecasts) were 3.37% (10.44%), 1.82% (2.07%), 1.76% (2.93%), 6.65% (10.41%) and 6.50% (8.93%), respectively. In the same way, the quadratic mean diameter, mean height, number of trees per hectare, stand basal area and stand volume per hectare prediction (forecast) relationships had high values of the coefficient of determination, R2, 0.998 (0.987), 0.997 (0.992), 0.997 (0.988), 0.968 (0.984) and 0.966 (0.980), respectively. Conclusions: The approach presented in this paper can be used for developing a new generation stand growth and yield models.

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