bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Hedonic Approach to Value Pinus radiata Log Traits for Appearance-Grade Lumber Production
Authors: Alzamora Rosa M. , Apiolaza Luis A. 
Published: April 2024

Abstract
This study used a hedonic approach to estimate the economic value of radiata pine log attributes (small-end diameter, form, and internode length) for appearance-grade lumber, including molding and better, shop, and industrial finger joint. Models were also built at the tree level to investigate the effect of selection as conducted by breeders. A Chilean sawing study provided information on wood traits and log out-turn for 156 logs divided into three classes: pruned butt log, second log, and third log. The conversion return of logs, instead of log prices, was used as the measure of log economic value. The economic values of log small-end diameter were 0.33, 0.19, and 0.10 US$/mm for the first, second, and third log, respectively. Concerning form, those values were US$2.6, US$1.4, and US$0.63 for a marginal improvement of this characteristic. The value of mean internode length was 0.19 US$/cm for second unpruned logs. Values for other internode length indices are also presented in this article. Branch variables were not statistically significant to explain the log recovery value. Finally, log recovery value was found to be elastic to the changes in small-end diameter and form, but inelastic to changes in the mean internode length.
Identifying the Presence of Assessment Errors in Forest Inventory Data by Data Mining
Authors: Mäkinen Antti M. , Kangas Annika S. , Tokola Timo 
Published: April 2024

Abstract
All forest inventory methods are susceptible to assessment errors, and although the majority of these errors are relatively minor, some can be exceptionally large. Errors reduce data reliability and increase the probability of nonoptimal decisions in forest planning. We propose that outlier detection techniques based on data mining could be used to detect some of the assessment errors in forestry databases. We tested four outlier detection algorithms presented in previous data mining studies for detecting the errors in compartment-wise field inventory data used in forest planning and examined the relations between the outliers and assessment errors. There was a clear relation between outliers and assessment errors, but this varied somewhat among the algorithms. Compartments with large assessment errors had a higher probability of being classified as outliers. The findings suggest that outlier detection techniques based on data mining could provide a cost-efficient tool for detecting some of the largest assessment errors in inventory data and thus improve the reliability of the whole forest planning process.
Light Detection and Ranging-Based Measures of Mixed Hardwood Forest Structure
Authors: Hawbaker Todd J. , Gobakken Terje , Lesak Adrian , Trømborg Eric , Contrucci Kirk , Radeloff Volker 
Published: April 2024

Abstract
Light detection and ranging (LiDAR) is increasingly used to map terrain and vegetation. Data collection is expensive, but costs are reduced when multiple products are derived from each mission. We examined how well low-density leaf-off LiDAR, originally flown for terrain mapping, quantified hardwood forest structure. We measured tree density, dbh, basal area, mean tree height, Lorey's mean tree height, and sawtimber and pulpwood volume at 114 field plots. Using univariate and multivariate linear regression models, we related field data to LiDAR return heights. We compared models using all LiDAR returns and only first returns. First-return univariate models explained more variability than all-return models; however, the differences were small for multivariate models. Multiple regression models had R2 values of 65% for sawtimber and pulpwood volume, 63% for Lorey's mean tree height, 55% for mean tree height, 48% for mean dbh, 46% for basal area, and 13% for tree density. However, the standard error of the mean for predictions ranged between 1 and 4%, and this level of error is well within levels needed for broad-scale forest assessments. Our results suggest that low-density LiDAR intended for terrain mapping is valuable for broad-scale hardwood forest inventories.
Implications of Expanding Bioenergy Production from Wood in British Columbia: An Application of a Regional Wood Fiber Allocation Model
Authors: Stennes Brad K. , Niquidet Kurt , van Kooten G. Cornelis 
Published: April 2024

Abstract
Energy has been produced from woody biomass in British Columbia for many decades, primarily within the pulp and paper sector, using residual streams from timber processing to create heat and electricity for on-site use. More recently, there has been some stand-alone electricity production and an increase in the capacity to produce wood pellets, both using “waste” from the sawmill sector. Hence, most of the low-cost feedstock sources associated with traditional timber processing are now fully employed. Although previous studies modeled bioenergy production in isolation, we used a fiber allocation and transportation model of the British Columbia forest sector with 24 regions to demonstrate that it is necessary to consider the interaction between use of woody feedstock for pellet production and electricity generation and its traditional uses (e.g., production of pulp, oriented-strandboard, and others). We find that, despite the availability of large areas of standing mountain pine beetle-killed timber, this wood does not enter the energy mix in a dedicated salvage timber harvest to energy system. Further expansion of biofeedstock for energy is met by a combination of woody debris collected at harvesting sites and/or bidding away of fiber from existing users.
Two-Component Mixture Models for Diameter Distributions in Mixed-Species, Two-Age Cohort Stands
Authors: Podlaski Rafał 
Published: April 2024

Abstract
The objectives of this study were to investigate the suitability of two-component Weibull and gamma mixtures to model the dbh distribution of a mixed-species, two-age cohort stands and for age cohort determination and to compare several methods to choose initial parameter values for maximum likelihood estimation of mixture models. Investigations were carried out in near-natural, fir (Abies alba Mill.)–beech (Fagus sylvatica L.), two-age cohort stands in the Świętokrzyski National Park (Central Poland), where unusually high mortality of fir followed by its recovery and revitalization has been observed. The age cohort YG1 is composed of trees from 60 to ∼150 years of breast height age, and the age cohort YG2 is composed of trees less than 60 years of breast height age. The empirical distributions for the stands in this study were equally well fit by both the mixture Weibull and gamma models. It has been assumed that the estimated values, the weights (fractions), the means, and the standard deviations of two-component mixture models, are the predicted values of dbh statistics of age cohorts. The mean absolute relative errors used to evaluate this assumption were least for age cohort YG2 (from 14.8 to 29.6%) and largest for age cohort YG1 (from 17.7 to 45.0%). The dbh component 1 of mixture models can be identified in the stands investigated with age cohort YG2 and to a lesser degree the dbh component 2 with age cohort YG1. The multistart method for choosing initial values for the numerical procedure (a combination of the expectation-maximization algorithm with the Newton-type method) was best but also the most labor-intensive. The optimal way to estimate parameters in two-component mixtures with the Weibull or the gamma distributions is to apply min/max and 0.5/1.5/mean methods and, additionally, but only if necessary, a multistart method.
Implications of Alternative Field-Sampling Designs on Landsat-Based Mapping of Stand Age and Carbon Stocks in Oregon Forests
Authors: Duane Maureen V. , Cohen Warren B. , Campbell John L. , Hudiburg Tara , Turner David P. , Weyermann Dale L. 
Published: April 2024

Abstract
Empirical models relating forest attributes to remotely sensed metrics are widespread in the literature and underpin many of our efforts to map forest structure across complex landscapes. In this study we compared empirical models relating Landsat reflectance to forest age across Oregon using two alternate sets of ground data: one from a large (n ∼ 1500) systematic forest inventory and another from a smaller set of plots (n &lt; 50) deliberately selected to represent pure conditions along predefined structural gradients. Models built with the smaller set of targeted ground data resulted in lower plot-level mapping error (root mean square error) and higher apparent explanatory power (R2) than those built with the larger, more widely distributed inventory data. However, in two of the three ecoregions considered, predictions derived from models built with the smaller ground data set displayed a bias relative to those built with the larger but noisier inventory data. A modeling exercise, wherein mapped forest age was translated into carbon, demonstrated how nonlinear ecological models can magnify these prediction biases over landscapes. From this study, it is clear that for mapping purposes, inventory data are superior to project-specific data sets if those data sets are not representative of the full region over which mapping is to be done.
Ponderosa Pine Characteristics Associated with Attack by the Roundheaded Pine Beetle
Authors: Fischer Melissa J. , Waring Kristen M. , Hofstetter Richard W. , Kolb Thomas E. 
Published: April 2024

Abstract
The roundheaded pine beetle (Dendroctonus adjunctus Blandford [Coleoptera: Curculionidae, Scolytinae]) is an aggressive (tree-killing) bark beetle species that attacks several species of pine. Characteristics of ponderosa pine (Pinus ponderosa Dougl. ex Laws.) trees chosen for attack by this beetle were studied in a current outbreak in northern Arizona. We found significant differences in basal area increment, crown width, lengths of internodes, subbranches, and needles, phloem thickness, and resin composition between attacked and unattacked trees. Attacked trees had significantly lower basal area increment and internode and needle lengths but longer subbranch lengths at the top of the crown and longer crown widths. Attacked trees also had thicker phloem and contained a significantly higher percentage of α-pinene in resin, but a lower percentage of longifolene than unattacked trees. A baited tree experiment showed that attacks by the roundheaded pine beetle did not affect resin composition through time. Overall, our results suggest that host selection by the roundheaded pine beetle may not be random and that tree growth characteristics and resin composition are probably important factors in host selection.
The Effects of Irrigation and Fertilization on Specific Gravity of Loblolly Pine
Authors: Love-Myers Kimberly R. , Clark Alexander , Schimleck Laurence R. , Dougherty Phillip M. , Daniels Richard F. 
Published: April 2024

Abstract
The effects of two treatments, irrigation and fertilization, were examined on specific gravity (SG)-related wood properties of loblolly pine trees (Pinus taeda L.) grown in Scotland County, North Carolina. The effects on the core as a whole, on the juvenile core, on the mature core, and from year to year were all analyzed. The results indicate that fertilization significantly lowered latewood SG, overall SG, and percent latewood and did so consistently throughout the period of study. Irrigation significantly lowered earlywood SG during the phase of juvenile wood production but significantly raised latewood SG during the period of mature wood production. Significant interaction between fertilization and irrigation indicated that irrigation helped overall SG and percent latewood of fertilized trees to increase to the level of untreated trees. Therefore, this study provides evidence that although fertilization significantly affects several SG-related properties, water availability is beneficial to the fertilization process; over time, an adequate water supply may help fertilized trees to maintain SG levels similar to those of unfertilized trees.
Optimizing Inventory and Yield Data Collection for Forest Management Planning
Authors: Gilabert Horacio , McDill Marc E. 
Published: April 2024

Abstract
This work uses a Cost+Loss approach to estimate the optimal investment in inventory information for forest planning. A bootstrapping approach is used to simulate the impact of different inventory intensities on the quality of decisions in a linear programming harvest scheduling model. Multiple formulations of the harvest model based on varying inventory intensities are used to calculate the value of a variable labeled Loss that measures the monetary losses resulting from the use of imperfect yield information in the harvest model. The variable Loss and the cost of obtaining the inventory information are used to estimate empirical relationships between their expected value and the amount of inventory information (number of inventory plots and number of experimental plots) used in the harvest models. These two relationships are combined to give an explicit estimate of the expected Cost+Loss as a function of the inventory intensity variables. This Cost+Loss relationship is minimized to estimate optimal number of inventory plots and the optimal number of experimental plots. An example is developed with radiata pine information from southern Chile. Results for this example suggest that current practice uses too many experimental plots and too few inventory plots.
Bootstrap Evaluation of a Young Douglas-Fir Height Growth Model for the Pacific Northwest
Authors: Vaughn Nicholas R. , Turnblom Eric C. , Ritchie Martin W. 
Published: April 2024

Abstract
We evaluated the stability of a complex regression model developed to predict the annual height growth of young Douglas-fir. This model is highly nonlinear and is fit in an iterative manner for annual growth coefficients from data with multiple periodic remeasurement intervals. The traditional methods for such a sensitivity analysis either involve laborious math or rely on prior knowledge of parameter behavior. To achieve our goals, we incorporate a bootstrap approach to obtain estimates of the distribution of predicted height growth for any set of input variables. This allows for a sensitivity analysis with knowledge of the probability of a given outcome. The bootstrap distributions should approximate the variation we might expect from running the model on numerous independent datasets. From the variation in the model parameters, we are able to produce ranges of height growth prediction error falling under a given probability of occurrence. By evaluating these ranges under several combinations of input variables that represent extreme situations, we are able to visualize the stability of the model under each situation. Each of the four components of the model can be investigated separately, which allows us to determine which components of the model might benefit from reformulation. In this case we find that the model is less stable in extremely high site index, especially under low vegetation competition. Other than the computing time involved with the bootstrap, most of the analysis is fairly quick and easy to perform.
Total Soil Carbon in the Coarse Fraction and at Depth
Authors: Zabowski Darlene , Whitney Nicol , Gurung Janita , Hatten Jeffrey 
Published: April 2024

Abstract
Historically, most studies estimating soil carbon have been based almost exclusively on ≤2-mm soil particles (fine soil fraction) and generally excluded soil &gt;2-mm (coarse soil fraction) or soil at &gt;1-m depth. In fact, many studies have not examined soil carbon below 20 cm. This study was conducted to determine how much total soil C is underestimated by following traditional, or standard, soil sampling and analysis for both particle size fractions and depth. Seventeen soil series and one soil classified to the level of Great Group, were sampled in Alaska, Oregon, Puerto Rico, and Washington. Total soil C was quantified for the soil fine and coarse fractions, as well as for soil &gt;1-m deep. Results of this study showed substantial soil C contained in the coarse soil fraction (&lt;1-25%) and in soil greater than 1-m depth (3-48%). The combined exclusion of the coarse fraction and soil below 1 m could miss as much as one-half of the soil total C of a profile. These results indicate that to obtain a true value of soil total carbon, the entire soil must be sampled, including the coarse soil fraction and soil below 1 m.
Soil Carbon Change through 2 m during Forest Succession Alongside a 30-Year Agroecosystem Experiment
Authors: Devine Scott , Markewitz Daniel , Hendrix Paul , Coleman David 
Published: April 2024

Abstract
Forest succession (FS) and no-till (NT) agriculture are generally assumed to have a beneficial effect on surficial soil organic C (SOC) stocks compared with conventional tillage (CT) management; however, land use effects to depths &gt;30 cm remain uncertain. In this research we compared SOC contents and composition to 2 m under CT, NT, and FS at the 30-year Horseshoe Bend agroecosystem experiment in Athens, Georgia, USA. Soils from 0 to 2 m were fractionated into particulate organic C (POC) (53-2000 μm) and fine C (&lt;53 μm) fractions, and bulk soil δ13C signatures were determined. Soils from 0 to 28 cm were dry- and wet-sieved to estimate aggregate stability. Soil solutions were also collected at 0, 15, and 100 cm for dissolved organic C (DOC) analysis. Full-profile (0-2 m) SOC storage is 52 Mg ha−1 in CT, 60 Mg ha−1 in NT, and 62 Mg ha−1 in FS. Significant differences are limited to 0-5 cm and are linked to enhanced aggregate stability under NT and FS. Increases in subsoil POC under FS and changes in soil δ13C and C/N ratio indicate that substantial subsoil C cycling has occurred. DOC fluxes at 0 cm were significantly greater under NT (200 kg ha−1 year−1) and FS (210 kg ha−1 year−1) than under CT (80 kg ha−1 year−1). DOC fluxes at 15 cm are estimated to be 20 kg ha−1 year−1 under CT and NT and 40 kg ha−1 year−1 under FS. At 100 cm, DOC fluxes are 2 kg ha−1 year−1, regardless of land use. An increase in FS POC of 2 Mg ha−1 from 15 to 100 cm outweighs cumulative differences in DOC input to this layer, implicating deep forest rooting and bioturbation as active mechanisms in subsoil C change. Whereas differences in SOC content were concentrated near the surface, dynamic changes in C cycling extend well below the plow layer.
Carbon Inputs and Water Uptake in Deep Soils of an Eastern Amazon Forest
Authors: Davidson Eric , Lefebvre Paul A. , Brando Paulo M. , Ray David M. , Trumbore Susan E. , Solorzano Luis A. , Ferreira Joice N. , Bustamante Mercedes M. da C. , Nepstad Daniel C. 
Published: April 2024

Abstract
Rooting depth affects soil profiles of water uptake and carbon inputs. Here we explore the importance of deep roots in a mature tropical forest of eastern Amazonia, where a throughfall exclusion experiment was conducted to test the resilience of the forest to experimentally induced drought. We hypothesized that soil water depletion occurred below the depth previously measured by sensors in 11-m-deep soil pits and that only a small root biomass is necessary to affect water uptake and the isotopic signature of soil CO2. A noninvasive electrical profiling method demonstrated greater depletion of soil water in the 11-18 m depth increment in the exclusion plot compared with the control plot by the end of the 3rd year of the experiment. A fine root biomass of only 0.1 g/cm3 measured at 3-6 m was sufficient for soil water drawdown and for imparting an isotopic signature of modern soil 14CO2 in both plots. A soil 13CO2 profile indicated drought stress in the exclusion plot. Fine root inputs of organic C to deep soils are small with respect to the carbon dynamics of the forest, but the deep rooting habit clearly affects the ecosystem water balance and profiles of soil CO2.
Estimating Wood Volume of the Stem and Branches of Sugar Maple (Acer saccharum Marsh.) Using a Stem Profile Model with Implicit Height
Authors: Zakrzewski Wojciech T. 
Published: April 2024

Abstract
A taper model-based solution for estimating volume of wood in sugar maple (Acer saccharum Marsh.) in Ontario, Canada, is presented. This practical procedure, using a reformulated version of the 1999 taper model of Zakrzewski, requires measuring only dbh and produces estimates of commercial wood volume allocated in stems and (or) branches, along tree length. The suggested methodology allows tree height to be treated as an implicit variable: either unobserved or unobservable (latent). Using the dbh-based taper model, a standard height/dbh curve may be generated without height measurements. The methodology presented here may be also treated as a modeling framework for developing dbh-based biomass equations as well as for investigating spatial allocation of wood within trees, e.g., for studying the influence of the competitive environment (forest stand density) of a tree on height growth. Sample data used were measurements from 1,113 sugar maple trees from Ontario's Algonquin region.
Modeling the Effect of Midrotation Fertilization on Specific Gravity of Loblolly Pine (Pinus taeda L.)
Authors: Antony Finto , Schimleck Laurence R. , Hall Daniel B. , Clark Alexander , Daniels Richard F. 
Published: April 2024

Abstract
Ring specific gravity, earlywood and latewood specific gravity, and percent latewood were measured on cores collected at breast height from a thinned and fertilized midrotation loblolly pine (Pinus taeda L.) plantation in the lower Coastal Plain of North Carolina. The study was laid out in a randomized complete block design receiving four levels of nitrogen (N) fertilizer in 1984: 000 (control), 112, 224, and 336 kg/ha plus 28 kg/ha of phosphorus with each treatment. A consistent pattern of response was observed in latewood specific gravity (LWSG) after the application of different levels of fertilizer and used as a variable for modeling. The LWSG profiles of unfertilized trees followed a nonlinear relation with ring number from pith. A three-parameter asymptotic function was used to explain the LWSG profile of unfertilized trees with ring number as a covariate. Application of N reduced LWSG and was modeled using a two-parameter response function with year since fertilization as a covariate and separate parameter estimates for each fertilization level. On the basis of the model, the magnitude of maximum cumulative response was −0.025, −0.049, and −0.074 attained at 3.7, 1.9, and 0.8 years after fertilization for the 112, 224, and 336 kg/ha treatments, respectively.