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

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.

2001 ◽  
Vol 25 (4) ◽  
pp. 165-172 ◽  
Author(s):  
J.C.G. Goelz ◽  
J.S. Meadows ◽  
T.C. Fristoe

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.


2013 ◽  
Vol 43 (9) ◽  
pp. 852-860 ◽  
Author(s):  
Thomas J. Dean ◽  
Scott D. Roberts ◽  
Robert S. Seymour

A general form for expressing gross volume increment in terms of stand density is derived and tested with data from spacing trials in red alder (Alnus rubra Bong.), eastern white pine (Pinus strobus L.), longleaf pine (Pinus palustris Mill.), and loblolly pine (Pinus taeda L.). The equation relates the stand sum of individual-tree volume increment per metre height increment to a power function of quadratic mean diameter times tree density. The proposed equation fit the data best when the model included an intercept. Within each species, the fits were unbiased with respect to the independent variables, plantation age, and site height, and with the exception of the youngest ages for red alder and loblolly pine, they were unbiased with respect to the plot sums of individual-tree volume increment divided by individual height increment. Exponents estimated for quadratic mean diameter for each species ranged from 1.58 to 1.80. The resulting equations indicate a linear relationship between the stand sum of individual-tree volume increment per metre height increment and stand density. Scattergrams of gross-volume increment per hectare per year and stand density can be recovered by multiplying the predicted values of the regressions by Lorey’s height. The regressions support the hypothesis that each metre of height growth produces consistent changes in stem size, regardless of initial tree size, age, or site quality, and implies that the change in stem size is a predictable power function of stem diameter for an individual tree or quadratic mean diameter for a stand.


1995 ◽  
Vol 19 (3) ◽  
pp. 103-104 ◽  
Author(s):  
J. C. G. Goelz

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.


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.


2008 ◽  
Vol 25 (4) ◽  
pp. 186-194 ◽  
Author(s):  
Don C. Bragg

Abstract By adapting data from national and state champion lists and the predictions of an existing height model, an exponential function was developed to improve tree height estimation. As a case study, comparisons between the original and redesigned model were made with eastern white pine (Pinus strobus L.). For example, the heights predicted by the new design varied by centimeters from the original until the pines were more than 25 cm dbh, after which the differences increased notably. On a very good site (50-year base age site index [SI50] = 27.4 m) at the upper end of the range of basal area (BA; 68.9 m2/ha) for the region, the redesigned model predicted a champion-sized eastern white pine (actual measurements: 97.0 cm dbh, 50.9 m tall) to be 51.3 m tall, compared with 38.8 m using the original formulation under the same conditions. The NORTHWDS Individual Response Model (NIRM) individual tree model further highlighted the influence of these differences with long-term simulations of eastern white pine height. On a moderate site (SI50 = 18.7 m) with intermediate (BA = 15 m2/ha) stand density, NIRM results show that the original model consistently predicts heights to be 20–30% lower for mature white pine.


1994 ◽  
Vol 11 (2) ◽  
pp. 41-46 ◽  
Author(s):  
Bijan Payandeh ◽  
Pia Papadopol

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.


1997 ◽  
Vol 73 (2) ◽  
pp. 257-265 ◽  
Author(s):  
P. F. Newton

Algorithmic versions of stand density management diagrams (SDMDs) were developed for natural and managed black spruce (Picea mariana (Mill.) B.S.P.) stands. Specifically, the IBM-compatible PC-based algorithms (1) graphically illustrate site-specific size-density trajectories for eight user-specified initial density regimes, (2) given (1), calculate and subsequent tabulate periodic yield estimates (mean dominant height, density, mean volume, total volume, total merchantable volume, quadratic mean diameter, and basal area), and (3) given (2), graphically illustrate empirically-derived yield production curves for total merchantable volume ha−1 and stems m−3 with user-specified operability criteria superimposed. Instructions on acquiring the executable algorithmic versions including the required graphical subroutines via the Internet are described. Currently, the algorithms are restricted in applicability to central insular Newfoundland. Key words: stand density management diagrams, black spruce, algorithms, microcomputer, World-Wide Web (WWW), hypertext browser, file transfer protocol (FTP).


2007 ◽  
Vol 24 (1) ◽  
pp. 61-64 ◽  
Author(s):  
Gregory J. Jordan ◽  
Mark J. Ducey

Abstract Using data from 449 trees on 69 growth-and-yield plots located in southern and central New Hampshire, we developed models of crown radius for stand-grown eastern white pine (Pinus strobus L.) in New Hampshire. In addition to dbh, we tested single-tree measurements sometimes collected in forest inventories (such as live crown length and live crown ratio [LCR]), as well as simple variables to compensate for stand density and competitive position of the tree. A model using dbh, stand basal area (BA), and LCR provided the best predictions, but a model using dbh, stand BA, and the ratio of dbh to stand quadratic mean diameter proved nearly as accurate. We compare these equations to previously published equations for white pine.


2010 ◽  
Vol 25 (3) ◽  
pp. 105-111 ◽  
Author(s):  
Michael E. Goerndt ◽  
Vincente J. Monleon ◽  
Hailemariam Temesgen

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.


2017 ◽  
Vol 47 (6) ◽  
pp. 788-799 ◽  
Author(s):  
F. Mauro ◽  
V.J. Monleon ◽  
H. Temesgen ◽  
L.A. Ruiz

Accounting for spatial correlation of LiDAR model errors can improve the precision of model-based estimators. To estimate spatial correlation, sample designs that provide close observations are needed, but their implementation might be prohibitively expensive. To quantify the gains obtained by accounting for the spatial correlation of model errors, we examined (i) the spatial correlation patterns of residuals from LiDAR linear models developed to predict volume, total and stem biomass per hectare, quadratic mean diameter (QMD), basal area, mean and dominant height, and stand density and (ii) the impact of field plot size on the spatial correlation patterns in a standwise managed Mediterranean forest in central Spain. For all variables, the correlation range of model residuals consistently increased with plot radius and was always below 60 m except for stand density, where it reached 85 m. Except for QMD, correlation ranges of model residuals were between 1.06 and 8.16 times shorter than those observed for the raw variables. Based on the relatively short correlation ranges observed when the LiDAR metrics were used as predictors, the assumption of independent errors in many forest management inventories seems to be reasonable and appropriate in practice.


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