Mean Dominant Height Research Articles

Dominant tree selection for height estimation and its impact on site classification for African mahogany stands

African mahogany plantations are increasing in Brazil, especially those planted with the species Khaya grandifoliola C. DC. Despite the interest in establishing plantations, there is a lack of studies in management practices for the genus. This makes it difficult to improve methodologies that optimise forest inventory activities, which are essential to support forest management decisions. Therefore, this study aimed to evaluate the effect of the number of trees selected to determine the mean dominant height, and to verify its impact on site classification of African mahogany stands. This will then optimise height sampling and ensure correct site index estimation. To determine the dominant height, 11 treatments were tested, with the selection of 1st to 11th thickest trees per plot, representing between 9 and 102 dominant trees per hectare. The effect of the treatments was evaluated using the values of the mean dominant height and metrics regarding site index classification (stability, stratification capacity and relationship with stand growth). Treatments with inclusion of more dominant trees resulted in a more stable site classification at the expense of a lower correlation with stand growth. Treatments using fewer dominant trees resulted in a greater allocation of plots in the upper site classes, showing that the number of trees used to calculate the dominant height influences the distribution of plots in different site classes. We concluded that Treatments 3 (27 trees ha−1) to 6 (55 trees ha−1) had the best performance, guaranteeing adequate site index estimation. The selection of at least 27 and a maximum of 55 dominant trees per hectare is recommended for African mahogany plantations with low planting densities.

Estimation of mean dominant height using NAIP digital aerial photogrammetry and lidar over mixed deciduous forest in the southeastern USA

• Temperate deciduous tree heights estimated with point clouds from digital aerial photogrammetry. • Photogrammetrically-derived point clouds a possible surrogate for those derived from lidar data. • Lidar-derived DEM necessary to normalize point clouds derived from digital aerial photogrammetry. • A poor photogrammetric solution led to reduced estimation accuracy in some shadowed areas. In the absence of complete lidar coverage, digital surface models (DSMs) and point clouds produced from the United States Department of Agriculture National Agriculture Imagery Program (NAIP) are increasingly being analyzed for quality and application feasibility. This study compared canopy heights derived from NAIP DSMs (10 m) and point clouds to those derived from lidar data collected over Mountain Lake Biological Station and the Great Smoky Mountains Twin Creeks Site by the National Ecological Observatory Network (NEON) Airborne Observation Platform for 62 mixed deciduous tree plots. Mean dominant height (MDH) was estimated using lidar and the NAIP products using the 90th percentile of heights in a given plot as the independent variable for both the lidar- and NAIP-derived point clouds. The dependent variable was field-measured MDH, calculated using the four tallest trees for each 0.04-hectare plot based on the NEON woody vegetation structure dataset. All data (field and remotely sensed) were collected in 2018. Using maximum likelihood spatial error model for all analyses, the NAIP DSM (10 m resolution) resulted in a strong relationship with MDH (coefficient of determination ( R 2 ) = 0.90, standard error ( SE ) = 1.71 m). However, the 90th percentiles of heights derived from the point clouds were better at estimating MDH than was the comparatively coarse resolution DSM (NAIP point clouds: R 2 = 0.94, SE = 1.40 m; lidar: R 2 = 0.95, SE = 1.29 m, respectively) and are strongly correlated to each other ( R 2 = 0.99, SE = 0.68 m). The main limitation of the NAIP datasets was found to be where shadowing occurred due to steep terrain in the Great Smoky Mountain site. These areas resulted in erroneously high vegetation heights. Mean dominant heights estimated using NAIP DSMs and point clouds are thus comparable to those estimated using lidar data in these closed-canopy temperate deciduous forests where shadowing from steep terrain is not present. The utility of both the NAIP-derived 10 m DSM and the point clouds for estimating tree heights paves the way for statewide mapping of heights over the deciduous forests in Tennessee, Virginia, and possibly beyond.

Modeling the number of the first- and second-order branches within the live tree crown of Korean larch plantations in Northeast China

Modeling the number of branches in a tree is fundamental for simulating other branch characteristics and crown structure. In this study, a total of 77 Korean larch (Larix olgensis Henry) trees were destructively sampled from plantations in Northeast China. The number of first- and second-order branches was modeled using seven count data models, namely Poisson, negative binomial (i.e., NB, including NB-1, NB-2, and NB-P), and generalized Poisson (i.e., GP, including GP-1, GP-2, and GP-P) regression models. Generalized linear mixed models (GLMMs) were then applied to those models using the sampled trees as the random effects. The results showed that (i) the Poisson regression was preferred for modeling the number of first-order branches; (ii) the GP-1 regression was considered the optimal model for the number of second-order branches; (iii) the significant predictor variables included tree height increment, branch position, relative tree size, mean dominant height, and tree age; (iv) the GLMMs significantly improved both model fit and prediction performance; (v) the prediction accuracy of the GLMMs increased gradually with increasing sample size; and (vi) a relatively small sample size with an appropriate sampling strategy would be adequate to provide a good estimation at a specific crown section.

SITE INDEX OF SIAMESE ROSEWOOD (Dalbergia cochinchinensis Pierre) IN PLANTATIONS OF THAILAND

Currently, decreased productivity of Siamese rosewood (Dalbergia cochinchinensis Pierre) is a problem due to illegal logging and the guidelines to manage this prevention being may be insufficient. Forest plantations should be promoted to achieve sustainable wood production for this species. Site index (SI) is a measure that can be used to predict forest productivity to identify appropriate sites for planting Siamese rosewood. The objective of the current study was to predict the SI for Siamese rosewood in Thailand. A sample of 78 temporary plots at 26 sites in 16 provinces of Thailand was selected to construct a site index curve with a base age of 30 years. The results showed that the mean age of Siamese rosewood was 28 years (between 13 and 55 years), the mean diameter at breast height (DBH) was 20.03 cm (between 7.99 and 33.80 cm), and the mean dominant height was 20.79 m (between 7.32 and 24.82 m). The SI equation was: SI = e(lnHdo-12.476(A-1-Ab-1)) with an R2 value of 0.406 at p < 0.0001 (chosen as 30 years in the present study). The equation indicated that 14, 18, 22, 26, and 30 m trees belonged to site classes Ι, ΙΙ, ΙΙΙ, ΙV, and V, respectively. Although in natural forest, Siamese rosewood is distributed in dry evergreen and mixed deciduous forests, in the present study, several sites in areas under both in situ and ex situ conservation were in the good and very good site categories. Thus, both areas can be used to plant Siamese rosewood and increase its productivity.

Environmental uniformity, site quality and tree competition interact to determine stand productivity of clonal Eucalyptus

Abstract The major determinants of productivity in Eucalyptus plantations include the site productive capacity, local environmental uniformity, and the tree genetics, which impact their growth potential and competitiveness. While these factors have received a lot of attention individually, less attention has been given to the relative importance of these factors and the interactions between them. We examined these factors and their interactions using eight experiments located along a gradient in site productivity, consisting of 54 clonal genotypes (Eucalyptus urophylla × E. grandis hybrids) at two plant spacings (3 × 3.33 and 3 × 2 m). Stand productivity was quantified as the mean annual increment at age 6 years (m3 ha−1 year−1). Site productive capacity was represented using a site index based on mean dominant height at age 6 years. Environmental uniformity was calculated from within-plot variability in growth of very young stands using residual spatial autocorrelation. The competitive ability of a given phenotype was calculated as the percent loss in potential growth due to neighbor competition. Productivity increased with all variables but site quality had the greatest effect, followed by environmental uniformity and then competitive ability, with corresponding changes in productivity of about 30, 20 and 10 m3 ha−1 year−1, respectively, across the range of the given variable. With higher environmental heterogeneity, competition among genotypes increased, especially at dense spacing, showing that in such situations, highly competitive genotypes may display productivities similar to the less competitive genotypes in uniform environments. Experimental plots distributed across site quality and uniformity gradients provide opportunity for greater genetic differentiation than plots covering more homogeneous environments, reinforcing the recommendation of establishing genetic tests in locations with extreme site qualities. Our work suggests that the G × E interaction is linked to site quality and, to a lesser degree, to the local environmental uniformity. This work shows the value of adopting environmental gradient-based approaches in tree genetic testing and clone recommendation as a way to more accurately match genotypes to specific sites.

Development of a stand density management diagram for Santalum album plantations in Karnataka, India

Stand density management diagrams are average stand-level models that graphically display the relationship between stand yield, density, height and diameter throughout the various stages of forest development in even-aged stands. These are useful tools for designing, displaying and evaluating alternative density regimes in even-aged forest ecosystems to achieve a desired future condition. In this paper, we present a stand density management diagram constructed for sandalwood stands in Karnataka state of India. The relationship between stand density, dominant height, quadratic mean diameter, relative spacing and stand volume is exhibited in one graph. The relative spacing index was used to characterise the growing stock level. Two equations were fitted to the data collected from 19 sample plots measured annually for three years: one relates quadratic mean diameter with stand density and dominant height, whereas the other relates total stand volume with quadratic mean diameter, stand density and dominant height.

Alternative silvicultural stand density management options for Chilimo dry afro-montane mixed natural uneven-aged forest using species proportion in Central Highlands, Ethiopia

Chilimo forest is one of the few remnants of dry afro-montane mixed uneven-aged natural forest located in Central Highlands of Ethiopia. Also it has been during the last century one of the most exploited and disturbed forest in the country. Stand density management diagram (SDMD) is a stand-level model that graphically illustrates the relationships between wood yield, density and mortality throughout all stages of stand development. SDMD is a useful tool for designing, displaying and evaluating alternative density management regimes for both even-aged and uneven-aged forest stands. However, information in this regard and other silvicultural management operations are lacking for most Ethiopian forests in general and Chilimo dry afro-montane forest in particular. The purpose of the study is to develop a SDMD model for the existing mixed natural forest using appropriate species proportion for Juniperus procera and Podocarpus falcatus. Two linear equations were simultaneously fitted to relate quadratic mean diameter with stand density and dominant height and relate it to total stand volume with quadratic mean diameter, stand density and dominant height. Moreover, dominant height and quadratic mean diameter were found to be the best endogenous variables for SDMD for Chilimo forest. The relationship between stand density, dominant height, quadratic mean diameter and stand volume is represented in the SDMD graph. Formulating SDMD using species proportion is better than treating each species independently. This SDMD is the first diagram model developed for mixed forest in Africa, and it can serve sustainable management of Chilimo dry afro-montane forest in particular and other dry afro-montane forests in general.

Using quadratic mean diameter and relative spacing index to enhance height–diameter and crown ratio models fitted to longitudinal data

The inclusion of quadratic mean diameter (QMD) and relative spacing index (RSI) substantially improved the predictive capacity of height–diameter at breast height (d.b.h.) and crown ratio models (CR), respectively. Data were obtained from 208 permanent plots established in western Arkansas and eastern Oklahoma during 1985–1987 and remeasured for the sixth time (2012–2014). Existing height–d.b.h. and CR estimation models for naturally occurring shortleaf pine forests (Pinus echinata Mill.) were updated and modified for improved performance. Additionally, eight height–d.b.h. relationship models that use only d.b.h. (fundamental local models) were modified using covariates. The model performance was evaluated using fit statistics [root mean square error (RMSE), Fit index and Akaike information criteria (AIC)]. The results showed that the best model form which was an extended non-linear model with autoregressive first order AR (1) structure and power variance function performed better than extended mixed-effects models and predicted well as an ordinary least squares non-linear model. The autocorrelation within individual trees was larger for the height–d.b.h. relationship than for CR estimation. The addition of QMD to mean dominant height (HD) greatly improved height–d.b.h. relationship with a reduction of 8 per cent in RMSE, compared with the use of basal area per hectare. Similarly, multiplying a fundamental local model by using QMD raised to a parametric power reduced RMSE by 16 per cent, improved Fit index by 12 per cent and decreased the AIC value by 7 per cent. D.b.h., HD and RSI best explained the crown ratio relationship with an improved Fit index by 6.7 per cent compared with alternative non-linear models without RSI. The logistic model for CR also provided prediction accuracy similar to that of a commonly used non-linear model. A non-linear model with an application of remedial measures to enhance adherence to modelling assumptions can provide better parameter estimates than mixed-effects modelling approach.

Occurrence of Density-Dependent Height Repression within Jack Pine and Black Spruce Populations

The objective of this study was to investigate the occurrence of density-dependent height relationships in jack pine (Pinus banksiana Lamb.) and black spruce (Picea mariana (Mill.) B.S.P.) populations. After assessing and ruling out the presence of consequential spatial correlation effects, the analysis consisted of analyzing the relationship between mean dominant height and initial planting density within 28 Nelder plots located in the central portion of the Canadian Boreal Forest Region. Employing remeasurement data obtained at periodic intervals (16, 20 and 40–41 years post-establishment) across a stand density gradient ranging from a minimum of 1425 stems/ha to a maximum of 28,621 stems/ha, graphical and simple linear regression analyses were used to quantify the stand height–density relationship by species, plot and measurement year. The results indicated the presence of density-dependent effects on height development for both species: 65% of the 83 jack pine relationships and 89% of the 27 black spruce relationships had significant (p ≤ 0.05) and negative slope values. In regards to jack pine for which the data permitted, the occurrence and magnitude of the observed height repression effect increased over time. The asymptotic height repression effect for jack pine was 24% greater than that for black spruce. The results are discussed within the context of the applicability of the density-independent height growth assumption and potential implications for site quality estimation and thinning response modeling.

Population structure of two bamboo species in relation to topographical units in the Republic of Benin (West Africa): implications for sustainable management

A study was carried out in two phytodistricts (Ouémé-valley and Plateau) to assess the population structure of two bamboo species (Oxytenanthera abyssinica (A. Rich.) Munro and Bambusa vulgaris Schrad. ex J.C. Wendl. in two topographical units: plateau and wetlands. In each phytodistrict, bamboo stands were randomly selected in each topographical unit for inventory using a 0.25-ha square plot. Structural parameters of bamboos were computed and compared using a Wilcoxon rank test. Spatial distribution of the two bamboos was also assessed using the method of neighbourhood density in relation to a focal point. The observed culm diameter distribution was established for each stand and adjusted to the two-parameter Weibull distribution. Oxytenanthera abyssinica showed the highest culm and clump density values in both wetlands and plateau whereas B. vulgaris showed greater values of mean diameter and dominant height whatever the habitat. Diameter structures of bamboo stands showed a right asymmetric distribution and bamboo spatial distribution was highly aggregative, especially in wetlands. No significant difference in mean relative neighbourhood density between species was noted. However, a significant difference was observed between wetlands and plateau (p < 0.001) indicating strong influence of the topographical units on the relative neighbourhood density of bamboo species. All of these findings are determinants in designing suitable management strategies for bamboo populations in Benin, particularly with the increasing demand to build fish-traps and shelter in the traditional fishing systems “Acadja”.

ZONING AND SITE CLASSIFICATION FOR THE EVEN-AGED TEAK PLANTATIONS

The relatively high accuracy possible with growth and yield models for uniform standsresults partly from the precision with which it is possible to classify site. The height of auniform stand, at a given age is a good indicator of the productivity of that type of forest onthat particular site. Hence the construction of height/age curves corresponding to differentsite classes is the first step in growth and yield modeling. However the mean height of astand is usually sensitive not only to age and site, but also to stand density. Site for a standis area specific, where the site of a particular stand cannot be improved significantly bybetter management. Therefore, dominant height which is almost entirely insensitive tostand density, could be used as a good indicator for site classification. Dominant heightcan be defined in various ways, but the definition with the widest used is that the dominantheight of a stand is the mean height of the 100 thickest stems per hectare.In this study, when dominant height/age scatter graphs were constructed separately foreach district, it was clearly observed that these diagrams were similar in some districts andwere significantly different compared for others. The districts and were similar site trendcurves were combined together to give one teak zone where, within one zone, the variationin dominant height growth is very similar in all districts falling under that zone. Usingthis zonal categorization, it was easy to separate the growth variations among the teakgrowing areas in Sri Lanka. This zonal effect may possibly be due to genetic variation, butthis cannot be analysed because the genetic information is not available.Three zones have been identified for teak growing areas in the country. This was doneusing 'mean dominant height - age graphs, and constructing maximum, minimum andmedium trend curves for each district. These curves and scatter graphs were comparedwith each other and grouped into selected sets using graphical methods. Different zoneswere identified using this method.Once the zonal categorization had been done, each zone was considered separately for itssite classification. This was done using the mean dominant height-age-site indexrelationships, which are basic to uniform forest growth predictions. The relationships areusually referred to simply as the site index curves for a species in a given environment.For each zone the site index curves have been constructed using 20 years as the index age.The Schumacher equation was used in fitting a model for the medium trend curve. For siteindex curves both common slope and common intercept methods were used

Site index for teak in Colombia

Determination of site quality is a basic tool for proper selection of locations and species, in management of forest plantations. Throughout the Caribbean studies of site quality are few and are hampered by statistical limitations, inappropriate growth models, and limited data. We fitted growth curves for dominant height to evaluate and classify site quality of teak (Tectona grandis) plantations by using data from 44 permanent sample plots established since 1990 in 3–22 years old teak plantations in the Colombian Caribbean region. We used Korf’s and von Bertalanffy’s models to fit curves as non-linear effects models. Both models, with a single random parameter, were considered as adequate for dominant height growth modelling, but Korf’s model was superior. The resulting curves were anamorphic and closely reflected high variability in site quality. Five site classes were clarified: at a base age of 12 years old, teak reached a mean dominant height of 24.8 m on the best sites, 9.8 m in the worst sites, and in the averages sites, 15.8–18.8 m. Using this model, we identified the best and the worst sites for teak plantations in the Caribbean region. This model proved a useful tool, not only for site quality evaluation, but also for improved teak plantation planning and management.

Soil and forest productivity: a case study from Stone pine (Pinus pinea L.) stands in Calabria (southern Italy)

The objective of this study was to determine whether edaphic and/or topographic variables may be used as predictors of site productivity in Stone pine stands in Calabria (southern Italy). To accomplish this goal, a linear discriminant rule was developed using data from 16 pure Stone pine stands, grouped into three different classes based on the mean dominant height annual growth. The discriminant rule was based on three linear models (one for each class) that jointly predicts site class for a given stand. To test the accuracy of the proposed method, cross-validation was carried out by developing 16 alternative discriminant rules (excluding the analyzed data). Predictors tested were edaphic (texture, pH, organic matter) and topographic (altitude and slope) variables. The model obtained allow to discriminate poorest sites accurately (100% of sites were correctly re-classified using the discriminant functions obtained). In more productive areas, sites were correctly re-classified in the 33.33% of cases, while in intermediate sites the correct classification was equal to 50%. Our discriminant rule classifies correctly the poorest stands, suggesting that site index in plain site soils strongly depends on clay percentage. Overall, the edaphic model obtained classifies plots into the correct site index class 61.11% of cases, which is considered an acceptable value for these kinds of studies.

Investigating the impact of discrete-return lidar point density on estimations of mean and dominant plot-level tree height in Eucalyptus grandis plantations

The accuracy of lidar remote sensing in characterizing three-dimensional forest structural attributes has encouraged foresters to integrate lidar approaches in routine inventories. However, lidar point density is an important consideration when assessing forest biophysical parameters, given the direct relationship between higher spatial resolution and lidar acquisition and processing costs. The aim of this study was to investigate the effect of point density on mean and dominant tree height estimates at plot level. The study was conducted in an intensively managed Eucalyptus grandis plantation. High point density (eight points/m2) discrete-return, small-footprint lidar data were used to generate point density simulations averaging 0.25, one, two, three, four, five, and six points/m2. Field surveyed plot-level mean and dominant heights were regressed against metrics derived from lidar data at each simulated point density. Stepwise regression was used to identify which lidar metrics produced the best models. Mean height was estimated at accuracy of R2 ranging between 0.93 and 0.94 while dominant height was estimated with an R2 of 0.95. Root mean square error (RMSE) was also similar at all densities for mean height (∼1.0 m) and dominant height (∼1.2 m); the relative RMSE compared to field-measured mean was constant at approximately 5%. Analysis of bias showed that the estimation of both variables did not vary with density. The results indicated that all lidar point densities resulted in reliable models. It was concluded that plot-level height can be estimated with reliable accuracy using relatively low density lidar point spacing. Additional research is required to investigate the effect of low point density on estimation of other forest biophysical attributes.

Performance of eight eucalypt species and interspecific hybrid combinations at three sites in northern New South Wales, Australia

Summary Eight eucalypt taxa, represented by six seedlots and nine clones (two seedlots of Corymbia citriodora subsp. variegata (CCV), one seedlot each of Eucalyptus cloeziana, E. dunnii and E. pilularis, one seedlot and two clones of E. grandis, one clone of E. saligna, three clones of the interspecific hybrid E. grandis × E. camaldulensis and five clones of the hybrid E. urophylla × E. grandis) were tested in taxa trials on three sites in northern New South Wales, Australia. Significant differences between sites and between taxa in survival, growth, stem form and attack by stem-boring insect larvae were demonstrated. All taxa grew best on the Convery site that had the highest mean annual rainfall, 1400 mm, on a Red Ferrosol soil derived from volcanic parent material; E. dunnii and E. pilularis grew to a mean dominant height of 17 m in 6 y, E. cloeziana to 15 m, C. citriodora subsp. variegata and E. saligna to 14 m. Fewer than 2% of trees of all taxa at this site were attacked by insects. The other two sites had Brown Dermosol soils and were drier, the Muller site receiving 1200 mm y−1 and the Ironbolt site 1100 mm y−1. Height and diameter growth of all taxa was slower at these sites, with E. pilularis and E. cloeziana showing the greatest reduction in growth while E. grandis × E. camaldulensis showed the least reduction. Overall survival at age 6 y was acceptable at all three sites, being highest at Convery site (86%) followed by Muller (77%) and Ironbolt (74%). While C. citriodora subsp. variegata and E. cloeziana had minimal damage at Mueller and Ironbolt, the other taxa had from 9% to 100% of stems affected by borers, with E. grandis, the E. saligna clone and E. urophylla × E. grandis proving particularly susceptible on these sites.

Base–age Invariant Polymorphic Height Growth and Site Index Equations for Peatland Black Spruce Stands

Abstract The goal of this study was to develop base–age invariant polymorphic height growth and site index equations for peatland black spruce (Picea mariana [Mill.]; BSP) stands situated within the western portion of the Northern Clay section of the Canadian Boreal Forest region. Procedurally, equation parameters were estimated via ordinary least squares analysis using 291 mean dominant height − mean stand age (Hd − As) data pairs derived from 42 permanent sample plots (PSPs). The predictive ability of the resultant height growth equation was evaluated by examining mean absolute and relative errors and associated 95% prediction intervals over 5-, 15-, 25-, 35-, and 45-year projection periods. Furthermore, using an independent data set consisting of 129 Hd − As data pairs derived from 24 PSP, the new height growth equation was compared with two preexisting equations. Overall, the results indicated that the predictions derived from the new equation were unbiased irrespective of error type or projection period length and that the new equation exhibited greater predictive accuracy and was more consistent with expected dominant height development patterns than the preexisting equations. Consequently, the new equations are recommended for use when describing height growth patterns or quantifying site quality within peatland black spruce stands.

Stand Density Management Diagrams for two Mediterranean pine species in Eastern Spain

Stand Density Management Diagrams are useful tools for designing, displaying and evaluating alternative density management regimes in even-aged stands, with which to achieve a desired future stand condition. The stands studied, of Pinus halepensis and Pinus pinaster, have low productivity, and managers need easy, efficient tools to obtain the best yield. These diagrams help the managers of these stands determine thinning prescriptions. The relationship between stand density, dominant height, quadratic mean diameter and stand volume is represented in just one graph. Two equations were fitted simultaneously: one that relates quadratic mean diameter with stand density and dominant height, and another that relates total stand volume with quadratic mean diameter, stand density and dominant height.

Growth and carbon sequestration rates at age ten years of some eucalypt species in the low-to medium-rainfall areas of New South Wales, Australia

SummaryThis paper presents the results of a study of tree growth in farm forestry eucalypt plantations in the low—to medium-rainfall (450–700 mm y−1) regions of New South Wales, Australia, in an attempt to estimate the productivity of the plantations. The species measured include Eucalyptus camaldulensis, E. botryoides, E. globulus, E. albens, E. polyanthemos, E. microcarpa, E. melliodora, E. sideroxylon, E. crebra and Corymbia maculata. At age 10 y, mean dominant height (100 tallest trees per hectare) ranged from 7.5 to 18.8 m, mean top basal area (thickest 100 stems ha−1) from 1.5 to 9.2 m2ha−1, volume from 9.5 to 125.9 m3 ha−1, total above-ground biomass from 12.5 to 105.8 t ha−1, and mean carbon density (above ground) from 11.2 to 35.2 t ha−1.

Comparative evaluation of five height–diameter models developed for black spruce and jack pine stand-types in terms of goodness-of-fit, lack-of-fit and predictive ability

The objective of this study was to comparatively evaluate five nonlinear models on their ability to describe the relationship between total height ( H; m) and diameter at breast-height ( D; cm) within six commercially-important boreal stand-types. Specifically, the five models evaluated were as follows: (1) the constrained (i.e., H = 1.3 when D = 0) Chapman–Richards-based model proposed by Peng, Zhang and Liu [Peng, C., Zhang, L, Liu, L., 2001. Developing and validating nonlinear height-diameter models for major species of Ontario's boreal forests. NJAF 18, 87–94; denoted Model 1] which excludes consideration of stand-level effects; (2 and 3) the constrained Chapman–Richards-based models proposed by Sharma and Zhang [Sharma, M., Zhang, S.Y., 2004. Height–diameter models using stand characteristics for Pinus banksiana and Picea mariana. Scand. J. For. Res. 19, 442–451; denoted Models 2 and 3] which includes consideration of stand-level density effects through the explicit inclusion of density-based predictor variables (density ( N; stems/ha) and basal area ( G; m 2/ha)); and (4 and 5) constrained and unconstrained allometric-based models (denoted Models 4 and 5, respectively) derived from a multivariate expansion of the equation of simple allometry which includes consideration of stand-level effects via the explicit inclusion of density and stand developmental predictor variables (relative density index ( R; %/100) and mean dominant height ( H D; m), respectively). The six stand-types considered were (1 and 2) natural (density unregulated) and managed (density regulated) upland black spruce ( Picea mariana (Mill.) B.S.P.) stands (denoted PIm UL(N) and PIm UL(M), respectively), (3 and 4) natural and managed jack pine ( Pinus banksiana Lamb.) stands (denoted PNb (N) and PNb (M), respectively), (5) natural black spruce–jack pine mixed stands (denoted PImPNb (N)), and (6) natural lowland black spruce stands (denoted PIm LL(N)). The full dataset, consisting of 26741 H– D measurements and associated stand-level variables ( N, G, R and H D) obtained from 985 sample plots situated throughout the central portion of the Canadian Boreal Forest Region, was randomly subdivided into calibration and validation subsets of approximately equal size by stand-type. Parameter estimates for each model were obtained using the calibration subsets in combination with nonlinear regression (Models 1–3) and multiple regression (Models 4 and 5) analyses. Employing the validation subsets, the calibrated models were evaluated using goodness-of-fit, lack-of-fit and prediction error indices at both the diameter class and stand levels. The results indicated that the best performing models were as follows: (1) Model 3 for PIm UL(N); (2) Model 5 for PIm UL(M); (3) Model 4 for PNb (N); (4) Model 5 for PNb (M); (5) Model 2 for PImPNb (N); and (6) Model 5 for PIm LL(N). Collectively, these results (1) reconfirms the utility of explicitly incorporating stand-level variables within the model specification when developing H– D models, (2) demonstrates the superiority of the newly introduced allometric-based H– D composite model which incorporates both stand density and developmental effects for four of the six stand-types assessed, and (3) provides a suite of calibrated functions and associated performance metrics for potential use in product recovery and value estimation, stand structural analyses, growth and yield projection systems, and carbon budgeting models. Furthermore, given the success of the allometric-based models derived from the multivariate expansion of the equation of simple allometry, suggests that this modeling approach may have wider applicability in the (1) development of prediction equations for other important dimensional relationships used in forest management (e.g., localizing stem taper, volume and biomass equations) and (2) study of allometry in general (e.g., provide analytical direction in the assessment of population-level effects on allometric scaling relationships).

Mapping stand-level forest biophysical variables for a mixedwood boreal forest using lidar: an examination of scanning density

Light detection and ranging (lidar) is becoming an increasingly popular technology among scientists for the development of predictive models of forest biophysical variables. However, before this technology can be adopted with confidence for long-term monitoring applications in Canada, robust models must be developed that can be applied and validated over large and complex forested areas. This will require "scaling-up" from current models developed from high-density lidar data to low-density data collected at higher altitudes. This paper investigates the effect of lowering the average point spacing of discrete lidar returns on models of forest biophysical variables. Validation of results revealed that high-density models are well correlated with mean dominant height, basal area, crown closure, and average aboveground biomass (R2 = 0.84, 0.89, 0.60, and 0.91, respectively). Low-density models could not accurately predict crown closure (R2 = 0.36). However, they did provide slightly improved estimates for mean dominant height, basal area, and average aboveground biomass (R2 = 0.90, 0.91, and 0.92, respectively). Maps were generated and validated for the entire study area from the low-density models. The ability of low-density models to accurately map key biophysical variables is a positive indicator for the utility of lidar data for monitoring large forested areas.