bluuebunny/crossref_metadata_2025_split huggingface dataset:
Challenges to Estimating Tree Height via LiDAR in Closed-Canopy Forests: A Parable from Western Oregon
Authors: Gatziolis Demetrios , Fried Jeremy S. , Monleon Vicente S. 
Published: April 2024

Abstract
We examine the accuracy of tree height estimates obtained via light detection and ranging (LiDAR) in a temperate rainforest characterized by complex terrain, steep slopes, and high canopy cover. The evaluation was based on precise top and base locations for &gt; 1,000 trees in 45 plots distributed across three forest types, a dense network of ground elevation recordings obtained with survey grade equipment, and LiDAR data from high return density acquisitions at leaf-on and leaf-off conditions. Overall, LiDAR error exceeded 10% of tree height for 60% of the trees and 43% of the plots at leaf-on and 55% of the trees and 38% of the plots at leaf-off. Total error was decomposed into contributions from errors in the estimates of tree top height, ground elevation model, and tree lean, and the relationships between those errors and stand- and site-level variables were explored. The magnitude of tree height error was much higher than those documented in other studies. These findings, coupled with observations that indicate suboptimal performance of standard algorithms for data preprocessing, suggest that obtaining accurate estimates of tree height via LiDAR in conditions similar to those in the US Pacific Northwest may require substantial investments in laser analysis techniques research and reevaluation of laser data acquisition specifications.
Forest Management and Carbon Sequestration in Size-Structured Forests: The Case of Pinus sylvestris in Spain
Authors: Goetz Renan-Ulrich , Hritonenko Natali , Mur Ruben Javier , Xabadia Angels , Yatsenko Yuri 
Published: April 2024

Abstract
The Kyoto protocol allows Annex I countries to deduct carbon sequestered by land use, land-use change, and forestry from their national carbon emissions. J. Thornley and M. Cannell (2000. Managing forests for wood yield and carbon storage: A theoretical study. Tree Physiol. 20:477–484) have demonstrated that the objectives of maximizing timber and carbon sequestration are not complementary. Based on this finding, this article presents a model that takes into account the dynamics of timber and carbon in the form of an integro-partial differential and an ordinary differential equation. The integrated biophysical and economic model allows the optimal selective management regime to be determined. The results show that an increase in the carbon price leads to a notable increase in the number of trees. The findings also suggest that carbon sequestration costs are significantly lower for a change in a forest management regime than for a change in land use (afforestation).
Stand Density Relationships in Baldcypress
Authors: Keim Richard F. , Dean Thomas J. , Chambers Jim L. , Conner William H. 
Published: April 2024

Abstract
Stand density indices (SDIs) are surrogate measures of site occupancy useful for developing quantitative management tools for forest types that have not been extensively studied. For example, there has been little research of growth-density relationships for baldcypress (Taxodium distichum [L.] L.C. Rich.). We used published data, forest inventory data, and a 25-year-old thinning study to identify maximum densities and density of incipient self-thinning in baldcypress. Results suggest that a maximum Reineke's SDI is approximately 1,200 (SI units) in baldcypress, which agrees with practical experience and the theoretical limit derived from observed correlations between a species wood density and maximum SDI. Thinning a baldcypress stand to ≥58% of maximum SDI did not affect tree-level or stand-level growth, but thinning to 40% of maximum SDI increased diameter increment and net volume increment (at α = 0.07) in the first 25 years after thinning. These results are consistent with expectations based on stand density-growth relationships for other species, which supports the general utility of management tools based on stand density concepts.
Harvest Choice and Timber Supply Models for Forest Forecasting
Authors: Polyakov Maksym , Wear David N. , Huggett Robert N. 
Published: April 2024

Abstract
Timber supply has traditionally been modeled using aggregate data, whereas individual harvest choices have been shown to be sensitive to the vintage and condition of forest capital stocks. In this article, we build aggregate supply models for four roundwood products in a seven-state region of the US South directly from stand-level harvest choice models applied to detailed forest inventories. These models allow for a more precise accounting of the biological and economic underpinnings of supply and support forecasting of changes in forest inventories with a high degree of detail. Estimation results support use of the approach. The elasticities of softwood and hardwood sawtimber supply, 0.34 and 0.31, respectively, are consistent with the elasticities reported by previous studies. The elasticities of softwood and hardwood pulpwood supply (respectively, 0.062 and 0.025) are much lower than previous studies found for pulpwood supply, and cross-price elasticities indicate a dominant influence of sawtimber markets on pulpwood supply. Results generally indicate complementarity between sawtimber and pulpwood supply in the short run. This approach can provide a means of predicting the supply consequences of exogenous factors that could alter forest inventories, e.g., climate change and invasive species, and support regular updating of supply models as new inventory data are recorded.
Evaluating the Financial Performance of Timberland Investments in the United States
Authors: Mei Bin , Clutter Michael L. 
Published: April 2024

Abstract
Timberland properties have gained increasing attention in recent decades. The attractiveness of this asset primarily lies in its unique feature—the biological growth, which is independent of traditional financial markets. Using both parametric and nonparametric approaches, in this study we reexamine the financial performance of private- and public-equity timberland investments in the United States. Private-equity timberland returns are proxied by the National Council of Real Estate Investment Fiduciaries Timberland Index, whereas public-equity timberland returns are proxied by the value-weighted returns on a dynamic portfolio of the US publicly traded forestry firms that had or have been managing timberlands. The parametric analyses reveal that private-equity timberland assets outperform the market and have low systematic risk, whereas public-equity timberland assets fare similarly to the market. The nonparametric analyses reveal that both private- and public-equity timberland assets have higher excess returns.
Minimum-Inbreeding Seed Orchard Design
Authors: Lstibůrek Milan , El-Kassaby Yousry A. 
Published: April 2024

Abstract
The industrial concept of “quadratic assignment problem” (QAP) was used to develop a new seed orchard design that minimizes the level of inbreeding (minimum inbreeding [MI]) in an orchard's seed crop through the optimum allocation of clones within the orchard's grid. Spatial distribution of individual trees was done in proportion to their degree of genetic relatedness. The MI orchard design accommodates a variable number of unrelated or related clones with equal or variable sizes, and it is not restricted by the orchard's spatial configuration (shape or size). The proposed design is suitable for advanced generation populations that commonly harbor complicated pedigree relationships. The MI design was compared with the commonly used permutated neighborhood design and the completely randomized scheme, resulting in aggregate inbreeding distances of 6.82, 12.53, and 22.56, respectively, highlighting the effectiveness of the proposed design.
Subsurface Carbon Contents: Some Case Studies in Forest Soils
Authors: Johnson Dale W. , Murphy James D. , Rau Benjamin M. , Miller Watkins W. 
Published: April 2024

Abstract
This article evaluates the importance of deeper soil horizons for soil C inventories in forest ecosystems. For non-Spodosols, we categorized soils as to the degree of convexity of the cumulative soil C content profile. Soils with a highly convex or asymptotic soil C content profile contained a significantly lower fraction of their total C (36 ± 8%) below 20 cm than those with less convex (nonasymptotic) profiles (51 ± 2%), even though the more convex soils were 12 cm (23%) deeper. Spodosols contained the most C below 20 cm (66 ± 3%) as a result of the presence of spodic horizons. Spodosols also contained substantially more total soil profile C than non-Spodosols even though the average depths of sampling were similar. Langmuir and logarithmic equations predicted C contents of deeper horizons fairly well for most non-Spodosol soils, whereas C content declines systematically with depth. These equations were very poor for Spodosols, however, because of the increases in soil C with depth that often occur with spodic horizons. Two case studies from the Sierra Nevada mountains suggested that C concentration varies to a greater degree than does bulk density or fine earth (% &lt;2 mm) content, thus illustrating the importance of obtaining good estimates of the large stone content, which can offset differences in C concentration when C content is calculated in the normal fashion (i.e., ignoring the &gt;2-mm fraction). These case studies do not support the idea of estimating bulk density from soil C concentration.
Deep Soil Horizons: Contribution and Importance to Soil Carbon Pools and in Assessing Whole-Ecosystem Response to Management and Global Change
Authors: Harrison Robert B. , Footen Paul W. , Strahm Brian D. 
Published: April 2024

Abstract
Most of the C in terrestrial ecosystems is found in the soil. Although C calculations indicate that soils are more important than plants as reservoirs of C, soil rarely receives the attention given aboveground ecosystem components when C budgets are calculated. When soil pools are quantified they are typically sampled to relatively shallow depths. Shallow soil sampling in research includes studies that estimate C and nutrient pools and studies assessing the response of terrestrial ecosystems (i.e., forests, grasslands, and agricultural fields) to management treatments. Although many soils have sola that are substantially deeper than 20 cm and C accumulates well below these depths in many soils, the majority of studies of soil C sample to depths of 20 cm or less, generally because of the difficulty and cost of sampling the soil profile deeper. Shallow soil sampling is often justified by assuming that deeper soil horizons are stable and will not change over time, although some medium- and long-term studies do not support this assumption. Shallow soil sampling can result in both a major underestimate of soil C present in the soil profile and an inability to adequately measure the impacts of both treatments for specific goals (i.e., tillage, fertilization, and vegetation management) or other changes (i.e., global change and atmospheric inputs) over time in whole-ecosystem studies. We assessed the potential of shallow soil sampling to underestimate C in the soil profile as well as to change the conclusions of studies of management treatments on soil C. Results showed that where soils were sampled to at least 80 cm or more depth 27-77% of mineral soil C was found &gt;20 cm in depth. In addition, analysis of results for 105 different studies of N fertilization in forests and N fertilization or conversion to switchgrass in agricultural studies shows that deeper sampling can actually change the conclusions of results of some research studies of net C accumulation or loss. Researchers wishing to either quantify soil C pools or measure changes of soil C over time are cautioned to sample soil profiles as deeply as possible and not assume that deeper soil horizons are not a critical part of adequate ecosystem analysis.
Estimating Riparian Understory Vegetation Cover with Beta Regression and Copula Models
Authors: Eskelson Bianca N. I. , Madsen Lisa , Hagar Joan C. , Temesgen Hailemariam 
Published: April 2024

Abstract
Understory vegetation communities are critical components of forest ecosystems. As a result, the importance of modeling understory vegetation characteristics in forested landscapes has become more apparent. Abundance measures such as shrub cover are bounded between 0 and 1, exhibit heteroscedastic error variance, and are often subject to spatial dependence. These distributional features tend to be ignored when shrub cover data are analyzed. The beta distribution has been used successfully to describe the frequency distribution of vegetation cover. Beta regression models ignoring spatial dependence (BR) and accounting for spatial dependence (BRdep) were used to estimate percent shrub cover as a function of topographic conditions and overstory vegetation structure in riparian zones in western Oregon. The BR models showed poor explanatory power (pseudo-R2 ≤ 0.34) but outperformed ordinary least-squares (OLS) and generalized least-squares (GLS) regression models with logit-transformed response in terms of mean square prediction error and absolute bias. We introduce a copula (COP) model that is based on the beta distribution and accounts for spatial dependence. A simulation study was designed to illustrate the effects of incorrectly assuming normality, equal variance, and spatial independence. It showed that BR, BRdep, and COP models provide unbiased parameter estimates, whereas OLS and GLS models result in slightly biased estimates for two of the three parameters. On the basis of the simulation study, 93–97% of the GLS, BRdep, and COP confidence intervals covered the true parameters, whereas OLS and BR only resulted in 84–88% coverage, which demonstrated the superiority of GLS, BRdep, and COP over OLS and BR models in providing standard errors for the parameter estimates in the presence of spatial dependence.
Canopy Structure in a 650-Year Douglas-Fir Chronosequence in Western Washington: Distribution of Canopy Elements and Open Space
Authors: Dial Roman J. , Nadkarni Nalini M. , Jewell Charles D. 
Published: April 2024

Abstract
Using within-canopy, side-viewing light detection and ranging (LiDAR), we measured canopy structure in a Douglas-fir (Pseudotsuga menziesii) chronosequence. We present foliage profiles, canopy composition, and a new metric quantifying the vertical distribution of open space, supporting and extending results from other structural studies. Foliage distribution shifted from vertically uniform in the youngest stand (50 years), to a canopy surface peak in mature forests (100–160 years old), to a near-ground maximum in old-growth (650 years). Leaf area index in old-growth and mature forests was similar but was smaller in young forest. Canopy composition changed with age: relatively more dead elements in young, boles in mature, and diversity in old-growth canopies. Older forest had greater mean and variance in open space than younger forests. Open space was vertically uniform in young, unimodal in mature, and greatest in the upper canopy in old-growth forests. Our results provide an integrated description of canopy structure over more than half a millennium, highlighting solid structure and its complement, open space. The unique element we present—open space—provides novel insights into the assessment of forest structure. This study provides a means to compare forests across ages, from immature to old-growth, with an additional canopy variable available for developing relationships between canopy structure and function.
Spatiotemporal Relationships between Climate and Whitebark Pine Mortality in the Greater Yellowstone Ecosystem
Authors: Jewett Jeffrey T. , Lawrence Rick L. , Marshall Lucy A. , Gessler Paul E. , Powell Scott L. , Savage Shannon L. 
Published: April 2024

Abstract
Whitebark pine (Pinus albicaulis) serves as a subalpine keystone species by regulating snowmelt runoff, reducing soil erosion, facilitating the growth of other plants, and providing food for wildlife. Mountain pine beetle (Dendroctonus ponderosae) is an ideal bioindicator of climate change, because its life cycle is temperature-dependent. Western North America is currently experiencing the largest outbreak of mountain pine beetle on record, and evidence suggests that a changing climate has accelerated the life cycle of this bark beetle. This study explored the relationships between climate, mountain pine beetles, and whitebark pine mortality in the Greater Yellowstone Ecosystem. A time series of Landsat satellite imagery (nine images) was used to monitor whitebark pine mortality in the Greater Yellowstone Ecosystem from 1999 to 2008. The patterns of mortality were analyzed with respect to monthly climate variations over the 9-year period. The impacts of topography and autocorrelation (both spatial and temporal) were also analyzed. The most important predictor variables were autocorrelation terms, indicating a strong host-tree depletion effect. Both drier and warmer climatic conditions favored increased whitebark pine mortality. These results show for the first time a statistical link between climate variability and whitebark pine mortality, probably mediated by mountain pine beetles.
Spatial Optimization of Wildlife Populations with Probabilistic Habitat Connections
Authors: Billionnet Alain 
Published: April 2024

Abstract
I consider a land area divided into cells and the problem that consists of determining the cells that must be harvested and the cells that must be left in old-growth to maximize the size of wildlife populations that depend on amounts of young- and old-growth forest. In each old-growth cell, the size of the old-growth-dependent population depends on the spatial arrangement of the old-growth cells, specifically of the probability that the cell is connected to at least one other old-growth cell. This problem suggested by Hof and Bevers can be easily formulated by a difficult nonlinear 0-1 program. These authors proposed a linear approximation of a special case of the pairwise connection probabilities. The aim of this article was to show that the problem can be solved simply and efficiently with any set of connection probabilities by using standard 0-1 linear programming software. The key feature to transform the nonlinear program into a linear program is an approximation of the logarithmic function curve by some of its tangents. Computational results on hypothetical grid forests with up to 900 cells are presented to illustrate potentialities of the approach. Near-optimal solutions guaranteed to be within 0.5% of the optimal solution are obtained in less than 10 minutes of computing time.
On Relative Maxima of Diameter Growth, Basal Area Growth, Volume Growth, and Mean Annual Increment for Individual Trees
Authors: Lynch Thomas B. , Zhang Difei 
Published: April 2024

Abstract
A mathematical demonstration for the fact that maximum individual tree diameter growth occurs at an earlier age than maximum individual tree basal area growth is reviewed. This demonstration assumes that the growth functions are continuous, are twice differentiable with respect to age, and increase monotonically to one maximum, thereafter to decline monotonically. The relationship of the age of maximum individual tree volume growth to the age of basal area growth is also discussed. Mathematical demonstrations are given for the fact that the culmination of mean annual increment occurs earlier for diameter than for basal area, and results on age of maximum growth and mean annual increment are also given for arbitrary power functions in diameter.
Comparing Traditional Longitudinal Modeling Strategies of Forestry with Mixed-Effects Models: Restrictions in Model Formulation
Authors: Stewart Brock , Jordan Lewis , Li Rongxia 
Published: April 2024

Abstract
Generalized algebraic difference approach and site index models, which are commonly fitted to repeated-measures data in forestry, are formulated by specifying that one or more regression parameters depend on a single, common subject-specific quantity. Their formulation leads to shortcomings not present with “effects” types of formulations, which involve specifying each subject-specific regression parameter as depending on at least one local quantity that no other parameters depend on. We give conceptual illustrations as well as empirical examples using published models.
Toward Efficient Management of Large Fires: A Mixed Integer Programming Model and Two Iterative Approaches
Authors: Wei Yu , Rideout Douglas B. , Hall Thomas B. 
Published: April 2024

Abstract
In this study, we developed an optimization model and two iterative approaches to improve the efficiency of large fire management. This model allocates suppression effort across time and space to minimize fire loss within a defined duration. It departs from previous research by replacing simplified fire containment rules with progress-based fire loss control. This is accomplished by extending the minimum travel time algorithm to build a large fire suppression model. Mixed integer programming is used to integrate spatial information such as fire behavior, firefighter safety, and values at risk to guide large fire suppression. The concern of time-specific suppression allocation is modeled through two iterative approaches using different logical procedures. Test cases demonstrate how this model assembles spatial data to support suppression decisions for one fire or multiple simultaneous fires. Suppression is also scheduled across 30 randomly simulated fires in Sequoia and Kings Canyon National Parks. Results demonstrate that suppression delay can significantly increase fire loss. Simulation results show that iterative approach A is more efficient in distributing suppression effort into short time periods.
Plantations for Bioenergy: Principles for Maintaining Biodiversity in Intensively Managed Forests
Authors: Flaspohler David J. , Webster Christopher R. 
Published: April 2024

Abstract
As the value of forests for providing a feedstock for bioenergy increases, more land will probably be converted to fast-growing tree plantations to increase short-term production of cellulose. In general, plantations support fewer plant and animal species than native forests because plantations are greatly simplified in terms of tree and other plant species richness and in terms of many structural and process-related forest functions. However, native biodiversity can be retained in some plantation forests if careful management is used in all stages of plantation establishment, tending, and harvest. Key considerations for conserving biodiversity as plantation forests grow as a proportion of total world forest cover include choice of plantation tree species, harvest frequency, rotation age, and care and management of biological legacies and forest understory plant and wildlife communities. We provide background and guidance that can be used to guide future plantation management in a new era of using forests to capture and store carbon and to generate bioenergy.