The potential benefits of planting trees have generated significant interest with respect to sequestering carbon and restoring other forest based ecosystem services. Reliable estimates of carbon ...stocks are pivotal for understanding the global carbon balance and for promoting initiatives to mitigate CO2 emissions through forest management. There are numerous studies employing allometric regression models that convert inventory into aboveground biomass (AGB) and carbon (C). Yet the majority of allometric regression models do not consider the root system nor do these equations provide detail on the architecture and shape of different species. The root system is a vital piece toward understanding the hidden form and function roots play in carbon accumulation, nutrient and plant water uptake, and groundwater infiltration. Work that estimates C in forests as well as models that are used to better understand the hydrologic function of trees need better characterization of tree roots. We harvested 40 trees of six different species, including their roots down to 2 mm in diameter and created species-specific and multi-species models to calculate aboveground (AGB), coarse root belowground biomass (BGB), and total biomass (TB). We also explore the relationship between crown structure and root structure. We found that BGB contributes ~27.6% of a tree's TB, lateral roots extend over 1.25 times the distance of crown extent, root allocation patterns varied among species, and that AGB is a strong predictor of TB. These findings highlight the potential importance of including the root system in C estimates and lend important insights into the function roots play in water cycling.
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Synthetic Aperture Radar (SAR), as an active sensor transmitting long wavelengths, has the advantages of working day and night and without rain or cloud disturbance. It is further able to sense the ...geometric structure of forests more than passive optical sensors, making it a valuable tool for mapping forest Above Ground Biomass (AGB). This paper studies the ability of the single- and multi-temporal C-band Sentinel-1 and polarimetric L-band PALSAR-2 data to estimate live AGB based on ground truth data collected in New England, USA in 2017. Comparisons of results using the Simple Water Cloud Model (SWCM) on both VH and VV polarizations show that C-band reaches saturation much faster than the L-band due to its limited forest canopy penetration. The exhaustive search multiple linear regression model over the many polarimetric parameters from PALSAR-2 data shows that the combination of polarimetric parameters could slightly improve the AGB estimation, with an adjusted R2 as high as 0.43 and RMSE of around 70 Mg/ha when decomposed Pv component and Alpha angle are used. Additionally, the single- and multi-temporal C-band Sentinel-1 data are compared, which demonstrates that the multi-temporal Sentinel-1 significantly improves the AGB estimation, but still has a much lower adjusted R2 due to the limitations of the short wavelength. Finally, a site-level comparison between paired control and treatment sites shows that the L-band aligns better with the ground truth than the C-band, showing the high potential of the models to be applied to relative biomass change detection.
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► We modeled height–diameter scaling in trees from the northeastern United States. ► We tested multiple species traits as predictors. ► Results were not universally consistent with any of several ...theoretical models. ► Evergreenness and wood density were weak but significant predictors.
Several tree height–diameter scaling rules have been proposed based on mechanical considerations or metabolic scaling. I used data on 202,950 trees of 86 species from the northeastern United States to examine height–diameter scaling patterns, and to determine whether they were sensitive to phylogeny (angiosperm vs. gymnosperm), shade-, drought-, and waterlogging tolerance, evergreenness, and wood density. Mixed effects models were used to estimate average scaling relationships and to quantify variability due to species and site attributes. Results did not support the invariant 2/3 scaling exponent assumed by the Metabolic Ecology Model. Evergreenness and wood density emerged as the primary predictor of height–diameter scaling in this assemblage, with considerable variation remaining at the species and location level. The results suggest that greater ecological and ontogenetic variability must be incorporated into scaling theories if height–diameter scaling is to be predicted successfully.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
•We synthesize the measurement and dynamics of dead wood carbon and decomposition.•Many protocols exist for inventorying standing dead trees and downed woody debris.•Research needs are presented to ...promote the accurate quantification of dead wood.•Issues presented here are hindered by unknowns of future global change scenarios.
The amount and dynamics of forest dead wood (both standing and downed) has been quantified by a variety of approaches throughout the forest science and ecology literature. Differences in the sampling and quantification of dead wood can lead to differences in our understanding of forests and their role in the sequestration and emissions of CO2, as well as in developing appropriate strategies for achieving dead wood-related objectives, including biodiversity protection, and procurement of forest bioenergy feedstocks. A thorough understanding of the various methods available for quantifying dead wood stores and decomposition is critical for comparing studies and drawing valid conclusions. General assessments of forest dead wood are conducted by numerous countries as a part of their national forest inventories, while detailed experiments that employ field-based and modeling methods to understand woody debris patterns and processes have greatly advanced our understanding of dead wood dynamics. We review methods for quantifying dead wood in forest ecosystems, with an emphasis on biomass and carbon attributes. These methods encompass various sampling protocols for inventorying standing dead trees and downed woody debris, and an assortment of approaches for forecasting wood decomposition through time. Recent research has provided insight on dead wood attributes related to biomass and carbon content, through the use of structural reduction factors and robust modeling approaches, both of which have improved our understanding of dead wood dynamics. Our review, while emphasizing temperate forests, identifies key research needs and knowledge which at present impede our ability to accurately characterize dead wood populations. In sum, we synthesize the current literature on the measurement and dynamics of forest dead wood carbon stores and decomposition as a baseline for researchers and natural resource managers concerned about forest dead wood patterns and processes.
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The most efficient way to obtain stand inventory data with terrestrial laser systems (TLS) is with the single-scan mode, which involves taking one scan at a single point. With a single-scan setup, ...there will be a nondetection of trees in a plot and the representation of the individual trees will be incomplete. We explore how stand-level volume estimates, based on the single-scan mode, perform compared with standard inventory estimates. We base our study on 166 plots in 12 mature stands dominated by Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies L. Karst) in southern Norway. First, we compare individual-tree volume estimates from TLS with estimates from volume functions and measurements from harvesters. We show that individual-tree volumes can be estimated with high precision and accuracy with TLS in single-scan mode. Secondly, we test three approaches for correction of nondetection relying on model-based estimates of the detection probability obtained by point transect sampling estimators. We show that all three approaches adjust for nondetection and yield stand-level volume estimates that are similar to those obtained by fixed-area sampling. In conclusion, our results indicate that stand-level volume estimates, based on single-scan mode TLS data, perform well compared with standard inventory estimates.
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The ability to automatically delineate individual tree crowns using remote sensing data opens the possibility to collect detailed tree information over large geographic regions. While individual tree ...crown delineation (ITCD) methods have proven successful in conifer-dominated forests using Light Detection and Ranging (LiDAR) data, it remains unclear how well these methods can be applied in deciduous broadleaf-dominated forests. We applied five automated LiDAR-based ITCD methods across fifteen plots ranging from conifer- to broadleaf-dominated forest stands at Harvard Forest in Petersham, MA, USA, and assessed accuracy against manual delineation of crowns from unmanned aerial vehicle (UAV) imagery. We then identified tree- and plot-level factors influencing the success of automated delineation techniques. There was relatively little difference in accuracy between automated crown delineation methods (51–59% aggregated plot accuracy) and, despite parameter tuning, none of the methods produced high accuracy across all plots (27—90% range in plot-level accuracy). The accuracy of all methods was significantly higher with increased plot conifer fraction, and individual conifer trees were identified with higher accuracy (mean 64%) than broadleaf trees (42%) across methods. Further, while tree-level factors (e.g., diameter at breast height, height and crown area) strongly influenced the success of crown delineations, the influence of plot-level factors varied. The most important plot-level factor was species evenness, a metric of relative species abundance that is related to both conifer fraction and the degree to which trees can fill canopy space. As species evenness decreased (e.g., high conifer fraction and less efficient filling of canopy space), the probability of successful delineation increased. Overall, our work suggests that the tested LiDAR-based ITCD methods perform equally well in a mixed temperate forest, but that delineation success is driven by forest characteristics like functional group, tree size, diversity, and crown architecture. While LiDAR-based ITCD methods are well suited for stands with distinct canopy structure, we suggest that future work explore the integration of phenology and spectral characteristics with existing LiDAR as an approach to improve crown delineation in broadleaf-dominated stands.
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The conic-paraboloid volume equation is receiving increased use with downed coarse woody material (CWM), but the consequences for taper have not been identified mathematically. Requiring that ...subdivision of a conic-paraboloid yields two smaller conic-paraboloids leads to an exact taper equation intermediate between those of cones and second-order paraboloids. This exact taper equation does not have an explicit inverse, however. An alternative, naive approach does have an explicit inverse, but subdivision does not yield two conic-paraboloids. The exact conic-paraboloid is closely approximated by Fermat’s paraboloid with exponent 7/5. The exact and naive conic-paraboloids match in volume; differences in taper are ≤2.2% of large-end cross-sectional area and ≤5.9% of large-end diameter, while differences in inverse taper are ≤3.7% of total length. Fermat’s paraboloid is always within 1.2% of total volume; differences in taper are ≤0.8% of large-end cross-sectional area and ≤2.0% of large-end diameter, while differences in inverse taper are ≤1.1% of total length. Such differences are negligible given the variety of CWM shapes and practical measurement challenges. Either the exact conic-paraboloid or the corresponding Fermat’s paraboloid provides appropriate equations for estimating the volume and taper of CWM that is intermediate between conical and ordinary paraboloid frusta.
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The pulp and paper industry in Indonesia is the tenth largest producer in the world, with Acacia and Eucalyptus as the main genera used for production; however, limited publications exist related to ...Eucalyptus growth models in Indonesia compared with other regions. Time-based models have been developed in which height, stand density, and basal area are predicted based on initial conditions and age. In contrast, a state-space approach utilizes the rate of change of these three state variables. Previous direct comparisons of these two approaches are generally limited. Consequently, the objective of this study was to compare two stand-level growth modeling approaches for Eucalyptus hybrid species on Sumatera (Sumatra) Island using both time-based and state-space methods. Our results indicate that dynamic models using either time-based or state-space approaches are adequate for predicting stand parameters to rotation age. A modified Bazukis matrix indicated that the behavior of both methods produced reliable predictions that were biologically reasonable in terms of stand development; however, the time-based approach provided better performance than the state-space approach on a variety of equivalence tests and goodness-of-fit statistics. Overall, the analysis highlights the advantages and disadvantages of these two commonly used, yet highly contrasting, stand-level growth modeling approaches, which need further consideration and evaluation.
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The forest understory is often associated with rapid rates of carbon and nutrient cycling, but cost-efficient quantification of its biomass remains challenging. We tested a new field technique for ...understory biomass assessment using an off-the-shelf handheld laser rangefinder. We conducted laser sampling in a pine forest with an understory dominated by invasive woody shrubs, especially Rhamnus frangula L. Laser sampling was conducted using a rangefinder, mounted on a monopod to provide a consistent reference height, and pointed vertically downward. Subsequently, the understory biomass was measured with destructive sampling. A series of metrics derived from the airborne LiDAR literature were evaluated alone and in combination for prediction of understory biomass using best-subsets regression. Resulting fits were good (r
2
= 0.85 and 0.84 for the best single metric and best additive metric, respectively, and R
2
= 0.93 for the best multivariate model). The results indicate that laser sampling could substantially reduce the need for costly destructive sampling within a double-sampling context.
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•Specific gravity and shade tolerance impact maximum stocking of tree species.•Temperature and precipitation interact with these traits to govern maximum stocking.•The results provide a simple, ...additive density measure for these complex forests.
Quantifying the density of live trees in forest stands and partitioning it between species or other stand components is critical for predicting forest dynamics and responses to management, as well as understanding the impacts of stand composition and structure on productivity. As plant traits such as shade tolerance have been proven to refine understanding of plant community dynamics, we extended a previous model relating maximum stand density to wood specific gravity to incorporate shade tolerance as an additional functional trait. Additionally, we included climatic variables that might influence ecological dynamics and modulate species-specific traits, across a region and also potentially over time under climate change scenarios. We used data from the USDA Forest Service, Forest Inventory and Analysis program for three states in the northern United States (Minnesota, Wisconsin, and Michigan) that reflect strong gradients in climate and species composition, to fit a maximum density model by quantile regression. The resulting strictly additive density measure conforms well to both existing silvicultural guidance and to observed densities of monocultures that lack such guidance. Wood specific gravity appears to interact with precipitation, while shade tolerance interacts with temperature, in driving maximum density relationships. Our proposed maximum stand density model is not only parsimonious for field application in management situations, but also empowers the evaluation of the effects of future climate and tree range scenarios on forest management guidelines.
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