Search NASA⌕ Search

SEARCH · Search NASA

Results for “Forest Modeling”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Data from: Age‐dependent leaf physiology and consequences for crown‐scale carbon uptake during the dry season in an Amazon evergreen forest

Satellite and tower-based metrics of forest-scale photosynthesis generally increase with dry season progression across central Amazônia, but the underlying mechanisms lack consensus. We conducted demographic surveys of leaf age composition, and measured age-dependence of leaf physiology in broadleaf canopy trees of abundant species at a central eastern Amazon site. Using a novel leaf-to-branch scaling approach, we used this data to independently test the much-debated hypothesis—arising from satellite and tower-based observations—that leaf phenology could explain the forest-scale pattern of dry season photosynthesis. Stomatal conductance and biochemical parameters of photosynthesis were higher for recently mature leaves than for old leaves. Most branches had multiple leaf age categories simultaneously present, and the number of recently mature leaves increased as the dry season progressed because old leaves were exchanged for new leaves. These findings provide the first direct field evidence that branch-scale photosynthetic capacity increases during the dry season, with a magnitude consistent with increases in ecosystem-scale photosynthetic capacity derived from flux towers. Interaction between leaf age-dependent physiology and shifting leaf age-demographic composition are sufficient to explain the dry season photosynthetic capacity pattern at this site, and should be considered in vegetation models of tropical evergreen forests.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Investigating old-growth ponderosa pine physiology using tree-rings, δ 13 C, δ 18 O, and a process-based model

In dealing with predicted changes in environmental conditions outside those experienced today, forest managers and researchers rely on process-based models to inform physiological processes and predict future forest growth responses. The carbon and oxygen isotope ratios of tree-ring cellulose (d13Ccell, d18Ocell) reveal long-term, integrated physiological responses to environmental conditions. We incorporated a submodel of d18Ocell into the widely used Physiological Principles in Predicting Growth (3-PG) model for the first time, to complement a recently added d13Ccell submodel. We parameterized the model using previously reported stand characteristics and long-term trajectories of tree-ring growth, d13Ccell, and d18Ocell collected from the Metolius AmeriFlux site in central Oregon (upland trees). We then applied the parameterized model to a nearby set of riparian trees to investigate the physiological drivers of differences in observed basal area increment (BAI) and d13Ccell trajectories between upland and riparian trees. The model showed that greater available soil water and maximum canopy conductance likely explain the greater observed BAI and lower d13Ccell of riparian trees. Unexpectedly, both observed and simulated d18Ocell trajectories did not differ between the upland and riparian trees, likely due to similar d18O of source water isotope composition. The d18Ocell submodel with a Peclet effect improved model estimates of d18Ocell because its calculation utilizes 3-PG growth and allocation processes. Because simulated stand-level transpiration (E) is used in the d18O submodel, aspects of leaf-level anatomy such as the effective path length for transport of water from the xylem to the sites of evaporation could be estimated.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Age-dependent leaf physiology and consequences for crown-scale carbon uptake during the dry season in an Amazon evergreen forest

Satellite and tower-based metrics of forest-scale photosynthesis generally increase with dry season progression across central Amazônia, but the underlying mechanisms lack consensus. We conducted demographic surveys of leaf age composition, and measured age-dependence of leaf physiology in broadleaf canopy trees of abundant species at a central eastern Amazon site. Using a novel leaf-to-branch scaling approach, we used this data to independently test the much-debated hypothesis—arising from satellite and tower-based observations—that leaf phenology could explain the forest-scale pattern of dry season photosynthesis. Stomatal conductance and biochemical parameters of photosynthesis were higher for recently mature leaves than for old leaves. Most branches had multiple leaf age categories simultaneously present, and the number of recently mature leaves increased as the dry season progressed because old leaves were exchanged for new leaves. These findings provide the first direct field evidence that branch-scale photosynthetic capacity increases during the dry season, with a magnitude consistent with increases in ecosystem-scale photosynthetic capacity derived from flux towers. In conclusion, interaction between leaf age-dependent physiology and shifting leaf age-demographic composition are sufficient to explain the dry season photosynthetic capacity pattern at this site, and should be considered in vegetation models of tropical evergreen forests.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

ForC: a global database of forest carbon stocks and fluxes

Forests play an influential role in the global carbon (C) cycle, storing roughly half of terrestrial C and annually exchanging with the atmosphere more than ten times the carbon dioxide (CO 2 ) emitted by anthropogenic activities. Yet, scaling up from ground-based measurements of forest C stocks and fluxes to understand global scale C cycling and its climate sensitivity remains an important challenge. Tens of thousands of forest C measurements have been made, but these data have yet to be integrated into a single database that makes them accessible for integrated analyses. Here we present an open-access global Forest Carbon database (ForC) containing records of ground-based measurements of ecosystem-level C stocks and annual fluxes, along with disturbance history and methodological information. ForC expands upon the previously published tropical portion of this database, TropForC (DOI: 10.5061/dryad.t516f), now including 17,538 records (previously 3568) representing 2,731 plots (previously 845) in 826 geographically distinct areas (previously 178). The database covers all forested biogeographic and climate zones, represents forest stands of all ages, and includes 89 C cycle variables collected between 1934 and 2015. We expect that ForC will prove useful for macroecological analyses of forest C cycling, for evaluation of model predictions or remote sensing products, for quantifying the contribution of forests to the global C cycle, and for supporting international efforts to inventory forest carbon and greenhouse gas exchange. A dynamic version of ForC-db is maintained at https://github.com/forc-db, and we encourage the research community to collaborate in updating, correcting, expanding, and utilizing this database.

Anderson-Teixeira, Kristina J.↗
DOE OSTI2015

Using Atmosphere-Forest Measurements To Examine The Potential For Reduced Downwind Dose

A 2-D dispersion model was developed to address how airborne plumes interact with the forest at Savannah River Site. Parameters describing turbulence and mixing of the atmosphere within and just above the forest were estimated using measurements of water vapor or carbon dioxide concentration made at the Aiken AmeriFlux tower for a range of stability and seasonal conditions. Stability periods when the greatest amount of mixing of an airborne plume into the forest were found for 1) very unstable environments, when atmospheric turbulence is usually at a maximum, and 2) very stable environments, when the plume concentration at the forest top is at a maximum and small amounts of turbulent mixing can move a substantial portion of the plume into the forest. Plume interactions with the forest during stable periods are of particular importance because these conditions are usually considered the worst-case scenario for downwind effects from a plume. The pattern of plume mixing into the forest was similar during the year except during summer when the amount of plume mixed into the forest was nearly negligible for all but stable periods. If the model results indicating increased deposition into the forest during stable conditions can be confirmed, it would allow for a reduction in the limitations that restrict facility operations while maintaining conservative estimates for downwind effects. Continuing work is planned to confirm these results as well as estimate specific deposition velocity values for use in toolbox models used in regulatory roles.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Inferring the Thermal History of the Intergalactic Medium from the Properties of the Hydrogen and Helium Lyα Forest

The filamentary network of intergalactic medium (IGM) gas that gives origin to the Lyα forest in the spectra of distant quasars encodes information on the physics of structure formation and the early thermodynamics of diffuse baryonic material. Here we use a massive suite of more than 400 high-resolution cosmological hydrodynamical simulations run with the Graphics Processing Unit–accelerated code Cholla to study the IGM at high spatial resolution maintained over the entire computational volume. The simulations capture a wide range of possible IGM thermal histories by varying the photoheating and photoionizing background produced by star-forming galaxies and active galactic nuclei. A statistical comparison of synthetic spectra with the observed 1D flux power spectra of hydrogen at redshifts 2.2 ≤ z ≤ 5.0 and with the helium Lyα opacity at redshifts 2.4 < z < 2.9 tightly constrains the photoionization and photoheating history of the IGM. By leveraging the constraining power of the available Lyα forest data to break model degeneracies, we find that the IGM experienced two main reheating events over 1.2 Gyr of cosmic time. For our best-fit model, hydrogen reionization completes by z R ≈ 6.0 with a first IGM temperature peak of T 0 ≃ 1.3 × 10 4 K and is followed by the reionization of He ii that completes by z R ≈ 3.0 and yields a second temperature peak of T 0 ≃ 1.4 × 10 4 K. We discuss how our results can be used to obtain information on the timing and the sources of hydrogen and helium reionization.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1995

(abstract) Using an Inversion Algorithm to Retrieve Parameters and Monitor Changes over Forested Areas from SAR Data

In this work, the application of an inversion algorithm based on a nonlinear opimization technique to retrieve forest parameters from multifrequency polarimetric SAR data is discussed. The approach discussed here allows for retrieving and monitoring changes in forest parameters in a quantative and systematic fashion using SAR data. The parameters to be inverted directly from the data are the electromagnetic scattering properties of the forest components such as their dielectric constants and size characteristics. Once these are known, attributes such as canopy moisture content can be obtained, which are useful in the ecosystem models.

forest canopy SAR data algorithm radar scattering ↗
NASA NTRS1989

Ecological applications of high resolution spectrometry

Future directions of NASA's space program plans include a significant effort at studying the Earth as a system of interrelated ecosystems. As part of NASA's Earth Observing System (Eos) Program a series of space platforms will be launched and operated to study the Earth with a variety of active and passive instruments. Several of the Eos instruments will be capable of imaging the planet's surface reflectance on a large number of very narrow portions of the solar spectrum. After the development of appropriate algorithms, this reflectance information will be used to determine key parameters about the structure and function of terrestrial and aquatic ecosystems and the pattern and processes of those systems across large areas of the globe. Algorithm development applicable to terrestrial systems will permit the inference of ecological processes from high resolution spectrometry data, similar to that to be forthcoming from the Eos mission. The first summer was spent working with tropical soils and relating their reflectance characteristics to particle size, iron content, and color. This summer the emphasis is on vegetation and work was begun with the Forest Ecosystems Dynamics Project in the Earth Resources Branch where both optical and radar characteristics of a mixed conifer/hardwood forest in Maine are being studied for use in a ecological modeling effort. A major series of aircraft overflights will take place throughout the summer. Laboratory and field spectrometers are used to measure the spectral reflectance of a hierarchy of vegetation from individual leaves to whole canopies for eventual modeling of their nutrient content using reflectance data. Key leaf/canopy parameters are being approximated including chlorophyll, nitrogen, phosphorus, water content, and leaf specific weight using high resolution spectrometry alone. Measurements are made of carbon exchange across the landscape for input to a spatial modeling effort to gauge production within the forest. A Geographic Information System approach is used to associate these data, images, and other collateral information for the forest into a database with a common projection suitable for spatial modeling.

Lawrence, William T.↗
DOE OSTI2023

Canopy tree mortality depends on the proportion of crown exposed to sunlight, but this effect varies with species' wood density

Abstract Understanding what drives changes in tree mortality as well as the covariates influencing trees' response is a research priority to predict forest responses to global change. Here, we combined drone photogrammetry and ground‐based data to assess the influence of crown exposure to light (relative to total crown area), growth deviations (relative to conspecifics), tree size, and species' wood density (as a surrogate for light‐demanding and shade‐tolerant life‐history strategies) on the mortality of 984 canopy trees in an Amazonterra firmeforest. Trees with lower wood density were less prone to die when their proportion of crown was more exposed to sunlight, but this relationship with relative crown exposure weakened and slightly reversed as wood density increased. Trees growing less than their species average had higher mortality, especially when the species' wood density decreased. The role of wood density in determining the survival of canopy trees under varying light conditions indicates differential responses of light‐demanding versus shade‐tolerant species. Our results highlight the importance of accounting for life‐history strategies, via plant functional types, in vegetation dynamic models aiming to predict forest demography under a rapidly changing climate. Abstract in Spanish is available with online material.

Environmental Sciences & Ecology↗
DOE OSTI2025

Myco-CORPSE simulations assessing mycorrhizal carbon allocation across U.S. forests and global change scenarios

Plants allocate a substantial portion of their fixed carbon belowground to mycorrhizal fungi in exchange for nutrients and other benefits. However, most current ecosystem models omit mycorrhizal processes, limiting our ability to predict plant–soil carbon dynamics under environmental change. To address this gap, we used a mycorrhiza-explicit soil biogeochemical model, Myco-CORPSE (Mycorrhizal Carbon, Organisms, Rhizosphere, and Protection in the Soil Environment), to simulate tree carbon allocation to arbuscular mycorrhizal (AM) and ectomycorrhizal (ECM) fungi in temperate forests.The dataset includes outputs from two sets of model simulations:1. Perturbation experiments: Simulations across gradients of ECM dominance (0–100%), nitrogen deposition, soil temperature, and net primary productivity (NPP) to test how these factors affect mycorrhizal C allocation and nutrient cycling.2. FIA-based simulations: Model applications to over 1,800 U.S. forest sites using site-specific data from the U.S. Forest Inventory and Analysis (FIA) program, including vegetation composition, mycorrhizal type, climate, litter traits, soil properties, and N deposition.Model outputs include simulated mycorrhizal carbon allocation and related biogeochemical variables, such as soil and microbial carbon and nitrogen stocks. Data are provided in CSV format and organized by experiment type (in separate ZIP files). Python scripts for running simulations, plotting, and spatial mapping are also included and organized similarly. No proprietary software is required. These outputs support a peer-reviewed study and were used to generate figures and tables in the associated publication.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2018

El Nino Drought Increased Canopy Turnover in Amazon Forests

Amazon droughts, including the 2015-2016 El Ni~no, may reduce forest net primary productivityand increase canopy tree mortality, thereby altering both the short- and the longtermnet forest carbon balance. Given the broad extent of drought impacts, inventory plots oreddy flux towers may not capture regional variability in forest response to drought. We used multi-temporal airborne Lidar data and field measurements of coarse woodydebris to estimate patterns of canopy turnover and associated carbon losses in intact and fragmentedforests in the central Brazilian Amazon between 2013-2014 and 2014-2016. Average annualized canopy turnover rates increased by 65% during the drought period inboth intact and fragmented forests. The average size and height of turnover events was similarfor both time intervals, in contrast to expectations that the 2015-2016 El Ni~no droughtwould disproportionally affect large trees. Lidar biomass relationships between canopyturnover and field measurements of coarse woody debris were modest (R2 0.3), given similarcoarse woody debris production and Lidar-derived changes in canopy volume from singletree and multiple branch fall events. Our findings suggest that El Ni~no conditions accelerated canopy turnover in central Amazonforests, increasing coarse woody debris production by 62% to 1.22 Mg C ha1(exp) yr1(exp) indrought years.

ecosystem models↗
DOE OSTI2024

At Risk Population Estimates for Belarus, Poland and Slovakia with Machine Learning

High-resolution gridded population modeling is crucial for various applications, including disaster response planning, infectious disease spread modeling, climate change impact estimation, policy development, and more. Multiple gridded population datasets have been developed, each tailored to meet specific objectives. Among them, LandScan Global dataset is designed to represent ambient and unwarned population distributions. However, this dataset relies on a statistical approach that requires manual adjustments, making it time consuming and labour intensive. Existing machine learning (ML) methods often train and test at different spatial resolutions, potentially leading to inflated results, and they rely on Census population totals for disaggregation. To address these limitations, in this study we developed population estimates using ML models trained and tested at a consistent 30 arc-second resolution (≈1 square kilometer), specifically using Random Forest (RF) and XGBoost. These models were trained on 2020 datum to predict for 2021 for three countries: Belarus, Poland, and Slovakia. Our findings show that both RF (MAE varies from 5.75 to 13.25) and XGBoost (MAE varies from 8.15 to 23.44) model performance is close to LandScan Global estimates. Furthermore, neither of the models performed the best across all grid cells: the RF model was more effective in areas with lower populations, while XGBoost excelled in more densely populated regions. The proposed approach can be used for countries where the Census data is not available.

Lebakula, Viswadeep [ORNL] (ORCID:0000000152935914↗
DOE OSTI2026

TCAD-Machine Learning Enabled TID Compact Model Development for Commercial SiC MOSFET

We propose a TCAD (Technology Computer Aided Design)-machine learning coupled approach that combines a TCAD tool (Charon), optimization/uncertainty quantification tool (Dakota), surrogate models, and Bayesian learning capabilities. The coupling approach is used for accurate modeling and calibration of total ionizing dose (TID) induced threshold voltage (V th ) shifts in Commercial-Off-The-Shelf (COTS) semiconductor devices and to develop physics-informed TID compact models. This versatile approach is applied to model the TID effect in an exemplar COTS 3.3 kV SiC power MOSFET (Metal-Oxide-Semiconductor Field-Effect Transistor). With the Charon-Dakota coupling, we can determine key device geometry and doping values based on device physics, which are difficult to obtain or not available for COTS devices but important for TCAD simulation; additionally, we can efficiently generate thousands of simulation results in a large parameter space, which makes it possible to develop data-driven surrogate models and perform Bayesian calibration. Utilizing the full tool-coupling approach, we achieve calibrated TCAD simulation models that accurately capture the average TID-induced V th shifts behavior with total doses and V th shifts saturation at high doses as observed in experimental data. More importantly, the calibrated TCAD simulations are obtained with determined TID model parameters (e.g., hole trap density and capture cross section) values that contain well quantified uncertainties. Furthermore, we can isolate and quantify the noises that are not captured by the TCAD models but exist in the measured data due to measurements and devices variabilities. Lastly, the calibrated surrogate models are used to develop physics-informed TID compact models. The method is generalizable to other devices and/or radiation conditions with few modifications and can provide well-determined uncertainties.

COTS↗
DOE OSTI2022

Dry Season Transpiration and Soil Water Dynamics in the Central Amazon

With current observations and future projections of more intense and frequent droughts in the tropics, understanding the impact that extensive dry periods may have on tree and ecosystem-level transpiration and concurrent carbon uptake has become increasingly important. Here, we investigate paired soil and tree water extraction dynamics in an old-growth upland forest in central Amazonia during the 2018 dry season. Tree water use was assessed via radial patterns of sap flow in eight dominant canopy trees, each a different species with a range in diameter, height, and wood density. Paired multi-sensor soil moisture probes used to quantify volumetric water content dynamics and soil water extraction within the upper 100 cm were installed adjacent to six of those trees. To link depth-specific water extraction patterns to root distribution, fine root biomass was assessed through the soil profile to 235 cm. To scale tree water use to the plot level (stand transpiration), basal area was measured for all trees within a 5 m radius around each soil moisture probe. The sensitivity of tree transpiration to reduced precipitation varied by tree, with some increasing and some decreasing in water use during the dry period. Tree-level water use scaled with sapwood area, from 11 to 190 L per day. Stand level water use, based on multiple plots encompassing sap flow and adjacent trees, varied from ∼1.7 to 3.3 mm per day, increasing linearly with plot basal area. Soil water extraction was dependent on root biomass, which was dense at the surface (i.e., 45% in the upper 5 cm) and declined dramatically with depth. As the dry season progressed and the upper soil dried, soil water extraction shifted to deeper levels and model projections suggest that much of the water used during the month-long dry-down could be extracted from the upper 2–3 m. Results indicate variation in rates of soil water extraction across the research area and, temporally, through the soil profile. These results provide key information on whole-tree contributions to transpiration by canopy trees as water availability changes. In addition, information on simultaneous stand level dynamics of soil water extraction that can inform mechanistic models that project tropical forest response to drought.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Interactions between land use change and carbon cycle feedbacks: Land Use and Carbon Cycle Feedbacks

We explore the role of human land use and land cover change (LULCC) in modifying the terrestrial carbon budget in simulations forced by Representative Concentration Pathway 8.5, extended to year 2300 by using the Community Earth System Model, . Overall, conversion of land (e.g., from forest to croplands via deforestation) results in a model-estimated, cumulative carbon loss of 490 Pg C between 1850 and 2300, larger than the 230 Pg C loss of carbon caused by climate change over this same interval. The LULCC carbon loss is a combination of a direct loss at the time of conversion and an indirect loss from the reduction of potential terrestrial carbon sinks. Approximately 40% of the carbon loss associated with LULCC in the simulations arises from direct human modification of the land surface; the remaining 60% is an indirect consequence of the loss of potential natural carbon sinks. Because of the multicentury carbon cycle legacy of current land use decisions, a globally averaged amplification factor of 2.6 must be applied to 2015 land use carbon losses to adjust for indirect effects. This estimate is 30% higher when considering the carbon cycle evolution after 2100. Most of the terrestrial uptake of anthropogenic carbon in the model occurs from the influence of rising atmospheric CO 2 on photosynthesis in trees, and thus, model-projected carbon feedbacks are especially sensitive to deforestation.

58 GEOSCIENCES↗
DOE OSTI2017

Reference scenarios for evaluating wood pellet production in the Southeastern United States

Wood pellet exports from the Southeastern United States (SE US) to Europe have been increasing in response to European Union member state policies to displace coal with renewable biomass for electricity generation. An understanding of the interactions among SE US forest markets, forest management, and forest ecosystem services is needed to quantify the effects of pellet production compared to what would be expected under a reference case or ‘counterfactual scenario’ without pellet production. Inconsistent methods to define and justify the counterfactual scenario result in conflicting estimates and large uncertainties about the impacts of pellet production on SE US forests. Guidelines to support more consistent and transparent counterfactual scenarios are proposed. The guidelines include identifying major influences on current SE US forest conditions, developing potential futures that clearly document underlying assumptions and associated uncertainties, identifying the most likely alternative feedstock fates, and estimating the effects of no pellet demand on future forest conditions. Finally, the guidelines can help modelers to more accurately reflect the past and current forest dynamics and to consider the implications for SE US forest landscapes of future scenarios with and without pellet production.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1991

The role of equiaxed particles on the yield stress of composites

Possible explanations are investigated for the yield strength enhancement of discontinuously reinforced Al alloy matrix MMCs, for the case of low temperature yield behavior where deformation occurs by dislocation slide. The Al alloys contain 0.1-10 micron diameter equiaxed particle discontinuous reinforcements of TiB2, Al2O3, and TiC. Attention is given to a single dislocation-particle interaction model, and both dislocation pile-up and forest-hardening multiple-dislocation particle interaction models.

Aikin, R. M., Jr.↗
DOE OSTI2017

Leaf surface traits and water storage retention affect photosynthetic responses to leaf surface wetness among wet tropical forest and semiarid savanna plants

While it is reasonable to predict that photosynthetic rates are inhibited while leaves are wet, leaf gas exchange measurements during wet conditions are challenging to obtain due to equipment limitations and the complexity of canopy-atmosphere interactions in forested environments. Thus, the objective of this study was to evaluate responses of seven tropical and three semiarid savanna plant species to simulated leaf wetness and test the hypotheses that (i) leaf wetness reduces photosynthetic rates (Anet), (ii) leaf traits explain different responses among species and (iii) leaves from wet environments are better adapted for wet leaf conditions than those from drier environments. The two sites were a tropical rainforest in northern Costa Rica with ~4200 mm annual rainfall and a savanna in central Texas with ~1100 mm. Gas exchange measurements were collected under dry and wet conditions on five sun-exposed leaf replicates from each species. Additional measurements included leaf wetness duration and stomatal density. We found that Anet responses varied greatly among species, but all plants maintained a baseline of activity under wet leaf conditions, suggesting that abaxial leaf Anet was a significant percentage of total leaf Anet for amphistomatous species. Among tropical species, Anet responses immediately after wetting ranged from -31% (Senna alata (L.) Roxb.) to +21% (Zamia skinneri Warsz. Ex. A. Dietr.), while all savanna species declined (up to -48%). After 10 min of drying, most species recovered Anet towards the observed status prior to wetting or surpassed it, with the exception of Quercus stellata Wangenh., a savanna species, which remained 13% below Anet dry. The combination of leaf wetness duration and leaf traits, such as stomatal density, trichomes or wax, most likely influenced Anet responses positively or negatively. There was also overlap between leaf traits and Anet responses of savanna and tropical plants. It is possible that these species converge on a relatively conservative response to wetness, each for divergent purposes (cooling, avoiding stomatal occlusion, or by several unique means of rapid drying). A better understanding of leaf wetness inhibiting photosynthesis is vital for accurate modeling of growth in forested environments; however, species adapted for wet environments may possess compensatory traits that mitigate these effects.

54 ENVIRONMENTAL SCIENCES↗