bluuebunny/crossref_metadata_2025_split huggingface dataset:
Using Segmented Regression to Estimate Stages and Phases of Stand Development
Authors: VanderSchaaf Curtis L. , Burkhart Harold E. 
Published: April 2024

Abstract
Size-density trajectories on the logarithmic scale are generally thought to consist of two major stages. The first major stage is often referred to as the density-independent mortality stage in which the probability of mortality is independent of stand density; in the second stage, often referred to as the density-dependent mortality or self-thinning stage, the probability of mortality is related to stand density. Within the self-thinning stage, segments of a size-density trajectory consisting of a nonlinear approach to a linear portion, a linear portion, and a divergence from the linear portion are generally assumed. Here, we define the maximum size-density relationship (MSDR) dynamic thinning line as the linear portion. A loblolly pine (Pinus taeda L.) planting density study was used to demonstrate the process of using segmented regression models for estimating stages and phases of stand development. After results from the segmented regression model analyses were obtained, full versus reduced model tests indicated that a portion of self-thinning can be represented as linear. Estimates of the logarithm of quadratic mean diameter (lnD q) and logarithm of trees per hectare (lnN) where the linear component begins and ends were obtained from the segmented regression analyses and used as response variables predicted as a function of planting density. Predicted values of the lnD q and lnN allow for the MSDR dynamic thinning line boundary level and slope to be estimated for any planting density. Estimates showed that MSDR dynamic thinning line boundaries did not all attain the same level but varied by planting density.
Spatial Dynamics of Natural Regeneration in Two Differently Managed Pinus sylvestris Stands before and after Silvicultural Intervention Using Replicated Spatial Point Patterns
Authors: Pardos Marta , Montes Fernando , Cañellas Isabel 
Published: April 2024

Abstract
Individual seedlings were mapped on eight 5 m × 5 m plots between 2003 and 2006, in two differently managed Pinus sylvestris forests in Spain (group shelterwood system in Valsaín forest versus uniform system followed by soil preparation in Navafría forest). The spatial pattern of the seedlings was analyzed through the L(d) function. The spatial relationship between seedlings before and after the regeneration felling was analyzed using the intertype Lrs (d) function. To study the spatial relationship between seedling distribution and either light availability or organic matter depth, the Krx (d) function was used. A practical method is proposed for obtaining the group-specific mean for several replicates: L std(d), based on the standardization of the L(d) function by the quantile bounds of the null model, which, once attained, is compared with the sum, weighted by the number of points in each replicate. Both the Lstd(d) group means and the point number weighted mean showed a cluster pattern for seedlings from germination to 6 years old, peaking at short scales (15–100 cm), before and after the cutting. After the cutting, the co-occurrence between germinants and older seedlings was not significant, although the Lrs (d) function was positive and presented a peak (50–100 cm). Seedling emergence was positively associated with organic matter depth after the cutting. The association between seedling distribution and light was modified when the cutting was severe (&gt;60% of tree basal area).
Spatial Pattern of Coast Redwood in Three Alluvial Flat Old-Growth Forests in Northern California
Authors: Dagley Christa M. 
Published: April 2024

Abstract
The spatial patterns of trees were investigated in old-growth redwood (Sequoia sempervirens [D. Don] Endl.) forests located in northern California to guide the design of restoration prescriptions. All stems ≥15 cm dbh were mapped and measured on three 1.5-ha plots. Patterns for trees in different size classes were analyzed separately with Ripley's K(d) function. Results revealed two patterns. At two sites, trees were randomly distributed throughout the stand and size classes were spatially independent of each other at scales of 0–50 m. At one site, a clumped spatial pattern was revealed for small- and medium-sized tree groups at small scales, whereas a random spatial pattern was detected for large trees at scales of 0–50 m. In addition, significant positive deviation from spatial independence at small scales suggested an attraction between tree groups. The spatial pattern of regeneration (trees &lt;15 cm dbh) was described using quadrat-based analyses. Regeneration was clumped at all three sites. Results indicate that old-growth redwood forests occurring on alluvial flats have different spatial patterns for similar size classes of trees despite the similarities in topography and stand structural characteristics. For land managers interested in restoration, these results suggest that past thinning guides that emphasized uniform spacing may not be appropriate in restoration efforts. Instead, trees should be retained in clumps or in random spatial patterns.
Changes in Forest Structure After a Large, Mixed-Severity Wildfire in Ponderosa Pine Forests of the Black Hills, South Dakota, USA
Authors: Keyser Tara L. , Lentile Leigh B. , Smith Frederick W. , Shepperd Wayne D. 
Published: April 2024

Abstract
We evaluated changes in forest structure related to fire severity after a wildfire in ponderosa pine forests of the Black Hills, South Dakota, where 25% burned at low, 48% at moderate, and 27% at high severity. We compared tree mortality, fine (FWD) and coarse woody debris (CWD) and tree regeneration in areas burned under different severity. With low severity, mortality was limited to small trees (&lt;15 cm dbh) with no reduction in basal area (BA) compared with unburned areas. FWD and CWD were 60% less than the unburned forest. With moderate severity, 100% mortality of small trees and significant large tree mortality resulted in an 50% reduction in BA and an open stand structure dominated by a few large trees. After 5 years, FWD and CWD recovered to unburned levels. With high severity, a lack of seed source makes regeneration unlikely. After 5 years, FWD equaled levels in unburned stands and CWD loads exceeded the unburned forest by 74%. The future landscape will be a mosaic of patches with forest structures determined by developmental trajectories set in motion by different fire severities. There will be patches of fully stocked, single canopy forest, multistory forest, and persistent grass- and shrub-dominated communities. High fuel loads in moderate and high severity areas remain a concern for management as does the lack of regeneration in high severity areas.
Problems of Scaling Plantation Plot Diameter Distributions to Stand Level
Authors: Borders Bruce E. , Wang Mingliang , Zhao Dehai 
Published: April 2024

Abstract
Diameter distribution models are used extensively in forest growth and yield modeling. They are usually fitted with fixed area sample plot data but applied at the stand level, the unit of forest production planning. In this process, the distribution obtained at the plot level is assumed to be representative of that at the stand level. In other words, the distribution from each plot of the same stand is assumed (roughly) to be the same, and therefore we can reasonably scale the plot distribution to the stand level. However, because of site-induced within-stand (between-plot) variability and spatial correlation introduced by tree competition and/or microsite effects or other factors, plot distributions may differ markedly from the stand distribution. We use data from 11 slash pine (Pinus elliottii) plantations, each consisting of 10 plots, to address differences in diameter distributions between plot level and stand level. The data indicate that (single) plot distributions are generally significantly different from their stand counterparts, because of spatial heterogeneity among plots within a given stand. For relatively homogeneous stands, diameter distributions obtained by averaging two to three plots may well represent the stand distribution within a certain precision, whereas for stands with more obvious spatial heterogeneity, a relatively large number of plots seem to be necessary for characterizing the stand distribution.
An Alternative View of Continuous Forest Inventories
Authors: Roesch Francis A. 
Published: April 2024

Abstract
A generalized three-dimensional concept of continuous forest inventories applicable to all common forest sample designs is presented and discussed. The concept recognizes the forest through time as a three-dimensional population, two dimensions in land area and the third in time. The sample is selected from a finite three-dimensional partitioning of the population. The partitioning is analogous to carving the volume into pieces like a three-dimensional jigsaw puzzle. Each puzzle piece is defined by the selection volumes of observation sets on the individual trees existing in the forest during the period of interest. The concept is a temporal extension of an alternative view of forest sampling offered in Roesch et al. (1993, Sur. Methods 19(2):199–204) and results in a finite number of independently selected three-dimensional sample units.
Sparse Bayesian Estimation of Forest Stand Characteristics from Airborne Laser Scanning
Authors: Junttila Virpi , Maltamo Matti , Kauranne Tuomo 
Published: April 2024

Abstract
In this article, a new method is applied to modeling forest stand characteristics from airborne laser scanning measurements. The method is an alternative to the cross-validation procedure of variable selection used in the ordinary least-squares (OLS) method and seemingly unrelated regression (SUR) with automatic selection of the features used in the model. This method is called the sparse Bayesian method. It does not suffer from overfitting thanks to the Bayesian formulation of the problem. The proposed method is applied to sample plot data obtained from inventory by compartments. The results show that the sparse Bayesian method performs as well as OLS and SUR methods, in terms of accuracy of total stand characteristics. The methods are comparable also in their demand for sample plot data. None of the methods lose much of their accuracy, even when just a few dozen sample plots are available. A Bayesian approach makes it possible to automate model formulation and sample plot selection processes. It is therefore possible to automatically generate a different model for intrastand strata, thus addressing intrastand variability. The proposed method automatically maintains a balance between the number of forest parameters and the rank of the model used to estimate them.
Evaluation of Four Methods to Estimate Parameters of an Annual Tree Survival and Diameter Growth Model
Authors: Cao Quang , Strub Mike 
Published: April 2024

Abstract
An approach to simultaneously estimate parameters of an annual tree growth model was developed, in which the sum of log-likelihood functions for tree survival and diameter growth was maximized. Four methods for acquiring interim values of stand density were evaluated: (1) Updating Attributes, in which individual tree values were summarized at the end of each year within the growth period to predict interim stand-level attributes, (2) Predicting Attributes, in which stand attributes were predicted annually using a stand-level model, (3) Linear Interpolation, in which stand attributes were predicted by linear interpolation, and finally (4) Initial Values, in which stand attributes at the beginning of the growth period were used as predictors throughout the growing period, and the rate of change for tree survival and diameter was assumed to be constant for this period. Data from the Southwide Seed Source Study of loblolly pine (Pinus taeda L.) showed that, overall, the Updating Attributes and Predicting Attributes produced better evaluation statistics in predicting tree survival and diameter growth than did the other two methods. A simulation study confirmed that these two methods produced the least biased estimates of parameters. Compared with the Updating Attributes method, the Predicting Attributes method produced similar evaluation statistics in predicting tree survival and diameter growth and similar bias in estimating model parameters. The Predicting Attributes method therefore offers a reasonable alternative to the Updating Attributes method, because of the ease of programming in available software languages.
Crown Recession Patterns in Three Conifer Species of the Northern Rocky Mountains
Authors: Garber Sean M. , Monserud Robert A. , Maguire Douglas A. 
Published: April 2024

Abstract
Crown length is a fundamental tree dimension for characterizing growth potential, wildlife habitat, and wood quality. The relative rates of height growth and crown recession determine the progression of crown length over time. We investigated patterns in crown recession of three co-occurring species in the northern Rocky Mountains: western white pine (Pinus monticola Dougl. ex D. Don), ponderosa pine (Pinus ponderosa Dougl. ex P. & C. Laws.), and interior Douglas-fir (Pseudotsuga menziesii [Mirb.] Franco var. glauca). Past height, diameter, and crown base on 169 forest-grown trees were reconstructed by detailed stem analysis. Crown base was estimated for each year of the tree's life by dating the mortality of all whorl branches. Five-year crown recession was modeled in two parts, the first predicting the probability that a crown recedes and the second estimating recession conditional on its occurrence. The probability of crown recession increased and then decreased with an increasing crown ratio for all three species and similarly peaked over initial tree size. Conditional crown recession increased monotonically with crown ratio for ponderosa pine but peaked at crown ratios between 0.7 and 0.9 in western white pine and Douglas-fir. The resulting models lend insight into factors controlling rates of crown recession and their variation among species and differing initial conditions.
Identification of Scandinavian Commercial Species of Individual Trees from Airborne Laser Scanning Data Using Alpha Shape Metrics
Authors: Vauhkonen Jari , Tokola Timo , Packalén Petteri , Maltamo Matti 
Published: April 2024

Abstract
Airborne laser scanning (ALS) data are not usually considered to be very informative with respect to tree species, and this information is often obtained by combining such data with spectral image material. The aim here was to test the ability of variables derived solely from ALS data to describe the crown shape and structure characteristics required for tree species discrimination. For that purpose, we constructed tree crown approximations from the three-dimensional return data by applying a computational geometry approach, the alpha shape concept, and developed metrics for describing them. We examined the ability of these metrics to classify Scandinavian commercial species (pine, spruce, and deciduous trees) by means of linear discriminant analysis and compared the alpha shape metrics with groups of ALS-based height, density, intensity, and two-dimensional texture variables. For evaluating the classification accuracy, we used a test data set composed of 92 dominant or codominant trees detected and delineated manually from ALS data with a density of approximately 40 returns m−2. The alpha shape metrics proved capable of discriminating between all three species classes evaluated, and several height distribution and texture variables were found to discriminate between the coniferous tree species. An overall accuracy of approximately 95% and a κ coefficient of 0.90 was achieved using a combination of the variables. Because this initial application of the alpha shape metrics was carried out using a test data set on only such trees that are clearly detectable from remotely sensed data, further research is required to apply the approach presented here within stands with a continuous canopy. Furthermore, as the tree observations considered here were highly biased toward mature coniferous trees, experiments using more representative data sets are needed to generalize the result obtained.
Finding Efficient Harvest Schedules under Three Conflicting Objectives
Authors: Tóth Sándor F. , McDill Marc E. 
Published: April 2024

Abstract
Public forests have many conflicting uses. Designing forest management schemes that provide the public with an optimal bundle of benefits is therefore a major challenge. Although a capability to quantify and visualize the tradeoffs between the competing objectives can be very useful for decisionmakers, developing this capability presents unique difficulties if three or more conflicting objectives are present and the solution alternatives are discrete. This study extends four multiobjective programming methods to generate spatially explicit forest management alternatives that are efficient (nondominated) with respect to three or more competing objectives. The algorithms were applied to a hypothetical forest planning problem with three timber- and wildlife-related objectives. Whereas the ε-Constraining and the proposed Alpha-Delta methods found a larger number of efficient alternatives, the Modified Weighted Objective Function and the Tchebycheff methods provided better overall estimation of the timber and nontimber tradeoffs associated with the test problem. In addition, the former two methods allowed a greater degree of user control and are easier to generalize to n-objective problems.
A Balanced Repeated Replication Estimator of Sampling Variance for Apparent and Predicted Species Richness
Authors: Magnussen Steen 
Published: April 2024

Abstract
Design-based estimators of the sampling variance for apparent (S0 = observed) and predicted species richness (S̃) have been lacking. A balanced repeated replication (BRR) estimator is proposed and recommended for S0 and S̃. Good performance of the estimators is demonstrated in two contrasting examples with Monte Carlo (MC) simulations of simple random sampling with fixed area quadrats (plots) for estimating forest tree species richness. Chao and Lee's estimator of species richness was used for S̃. In BRR a set of half-samples forming an orthogonal design with respect to the inclusion/exclusion of sample records is used to produce estimates of S̃ from the observed half-sample and models for the effect of data-splitting. BRR estimates of the sampling variance of S0 were close to the MC estimates in the examples from eastern Canada (PROV) and the Barro Colorado Island (BCI) and clearly superior to naive model-based estimates. BRR estimates of S̃ were generally close to their MC counterparts, but in BCI a bias of approximately −10% was seen in small samples (n ≤ 24). BRR estimates of sampling variance of S̃ in PROV were close to the MC estimates for n ≤ 60. With larger sample sizes the BRR estimates drifted toward values obtained with Chao and Lee's model-based variance estimator. In BCI the opposite was true.
Short-Term Physiological Responses of Black Walnut (Juglans nigra L.) to Plantation Thinning
Authors: Gauthier Martin-Michel , Jacobs Douglass F. 
Published: April 2024

Abstract
We studied physiological responses of mature black walnut (Juglans nigra L.) trees to determine the time necessary for photosynthetic adaptation to plantation thinning. Measurements were taken before treatment (July 25, 2007) and for the first 3 days after thinning (July 29, 30, and 31, 2007). Measurements did not continue in August because trees had developed leaf anthracnose and senescence was occurring, but measurements resumed on May 29, 2008 and July 29, 2008. Repeated measures of net photosynthetic rates (A) showed that thinned trees did not respond immediately to partial release, but nearly doubled in A compared with a 35% increase in control trees 1 year after thinning. Significant increases in light, leaf water status, relative humidity of the air, and nitrogen content per unit leaf area were also found in thinned trees 1 year after treatment. From these variables, light (r2 = 0.79) showed the strongest relationship with A. Results suggest that black walnut requires a full growing season before it responds to treatment when thinned late in the growing season. Thinning earlier, such as in June, may trigger a more rapid adaptation in A of thinned trees that was not detected in our study.
Improved Calibration of Nonlinear Mixed-Effects Models Demonstrated on a Height Growth Function
Authors: Meng Shawn X. , Huang Shongming 
Published: April 2024

Abstract
The calibration of a nonlinear mixed-effects model is of critical importance in making local predictions. In previous applications, simplified equations were generally used to calibrate nonlinear mixed-effects models fitted using the first-order methods implemented through the NLINMIX macro in SAS. This simplification, however, could distort local predictions. In this study, using a nonlinear height growth model of lodgepole pine (Pinus contorta var. latifolia Engelm.), we demonstrated on two data sets the procedures to obtain an improved calibration of the height growth model. The differences between the improved and conventional calibrations were found to be significant. Calibration of the nonlinear mixed models using the improved method resulted in not only reduced bias but also reduced variance of the errors. It is recommended that the improved calibration method be used. A computing program detailing the procedures for obtaining the improved calibration was developed.
Automated Analysis of in Situ Canopy Images for the Estimation of Forest Canopy Cover
Authors: Korhonen Lauri , Heikkinen Jaakko 
Published: April 2024

Abstract
Forest canopy cover is a commonly used ecological indicator variable, but its reliable estimation in the field with, e.g., the line intersect sampling method is laborious. One alternative for obtaining this information quickly is to sample a larger area of canopy from each prespecified location within a sample plot by using digital cameras and then use image analysis techniques to extract canopy cover from the images. The first aim of this study was to implement an automated method for the estimation of canopy cover from skyward-looking canopy images obtained with standard digital cameras. The second aim was to compare the estimates obtained with the cameras and the automated analysis technique to control values measured with a vertical tube by using two different plot types and a varying angular field of view (1–50°). The results indicate that the automated analysis technique, involving an automated image thresholding algorithm and morphological image processing operations to eliminate the effect of within-crown gaps, can reliably replace manual postprocessing. With the tested sampling schemes, a 40° angle of view yielded the best approximation of the control.