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DOE OSTI2020

Calibrated soil moisture data from Manaus, Brazil, August 2018 - December 2019

This dataset contains calibrated soil moisture and rainfall data for ecohydrological studies in the Central Amazon (2.6099 ºS, 60.2093 ºW) taken at 30-min intervals. Soil moisture data was collected at depths of 0.025-, 0.05-, 0.15-, 0.30-, 0.50-,0.8-, 1.6-, 2.4-, 3.2-, 4.8-, 6.4-, 8.8-, and 14.20 m. Inconsistent data was removed during the QA/QC process. Further information including data collection methods are available in the associated publication, Negron-Juarez et al. 2020. Measurement and characterization of soil moisture dynamics in a Central Amazonian tropical forest (to be submitted).

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2004

Space-Based Sensor Web for Earth Science Applications: An Integrated Architecture for Providing Societal Benefits

There is a significant interest in the Earth Science research and user remote sensing community to substantially increase the number of useful observations relative to the current frequency of collection. The obvious reason for such a push is to improve the temporal, spectral, and spatial coverage of the area(s) under investigation. However, there is little analysis available in terms of the benefits, costs and the optimal set of sensors needed to make the necessary observations. Classic observing system solutions may no longer be applicable because of their point design philosophy. Instead, a new intelligent data collection system paradigm employing both reactive and proactive measurement strategies with adaptability to the dynamics of the phenomena should be developed. This is a complex problem that should be carefully studied and balanced across various boundaries including: science, modeling, applications, and technology. Modeling plays a crucial role in making useful predictions about naturally occurring or human-induced phenomena In particular, modeling can serve to mitigate the potentially deleterious impacts a phenomenon may have on human life, property, and the economy. This is especially significant when one is interested in learning about the dynamics of, for example, the spread of forest fires, regional to large-scale air quality issues, the spread of the harmful invasive species, or the atmospheric transport of volcanic plumes and ash. This paper identifies and examines these challenging issues and presents architectural alternatives for an integrated sensor web to provide observing scenarios driving the requisite dynamic spatial, spectral, and temporal characteristics to address these key application areas. A special emphasis is placed on the observing systems and its operational aspects in serving the multiple users and stakeholders in providing societal benefits. We also address how such systems will take advantage of technological advancement in small spacecraft and emerging information technologies, and how sensor web options may be realized and made affordable. Specialized detector subsystems and precision flying techniques may still require substantial innovation, development time and cost: we have presented the considerations for these issues. Finally, data and information gathering and compression techniques are also briefly described.

Habib, Shahid↗

DOE OSTI2022

Tree crown damage and its effects on forest carbon cycling in a tropical forest

Abstract Crown damage can account for over 23% of canopy biomass turnover in tropical forests and is a strong predictor of tree mortality; yet, it is not typically represented in vegetation models. We incorporate crown damage into the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), to evaluate how lags between damage and tree recovery or death alter demographic rates and patterns of carbon turnover. We represent crown damage as a reduction in a tree's crown area and leaf and branch biomass, and allow associated variation in the ratio of aboveground to belowground plant tissue. We compare simulations with crown damage to simulations with equivalent instant increases in mortality and benchmark results against data from Barro Colorado Island (BCI), Panama. In FATES, crown damage causes decreases in growth rates that match observations from BCI. Crown damage leads to increases in carbon starvation mortality in FATES, but only in configurations with high root respiration and decreases in carbon storage following damage. Crown damage also alters competitive dynamics, as plant functional types that can recover from crown damage outcompete those that cannot. This is a first exploration of the trade‐off between the additional complexity of the novel crown damage module and improved predictive capabilities. At BCI, a tropical forest that does not experience high levels of disturbance, both the crown damage simulations and simulations with equivalent increases in mortality does a reasonable job of capturing observations. The crown damage module provides functionality for exploring dynamics in forests with more extreme disturbances such as cyclones and for capturing the synergistic effects of disturbances that overlap in space and time.

Needham, Jessica F.↗

DOE OSTI2025

Patchy burn severity explains heterogeneous soil viral and prokaryotic responses to fire in a mixed conifer forest

ABSTRACT Effects of fire on soil viruses and virus–host dynamics are largely unexplored, despite known microbial contributions to biogeochemical processes and ecosystem recovery. Here, we assessed how viral and prokaryotic communities responded to a prescribed burn in a mixed conifer forest. We sequenced 91 viral-size fraction metagenomes (viromes) and 115 16S rRNA gene amplicon libraries from 120 samples: four samples at five timepoints (two before fire and three after fire) at six sites (four treatment, two control). We hypothesized that compositional differences would be most significant between burned and unburned soils, but instead, plot location best distinguished viral communities, more than treatment (burned or not), depth (0–3 or 3–6 cm), or timepoint. For both viruses and prokaryotes, some burned communities resembled unburned controls, while others were significantly different, revealing heterogeneous responses to fire. These patterns were explained by burn severity, here defined by soil chemistry. Viral but not prokaryotic richness decreased significantly with burn severity, and low viromic DNA yields indicated substantial loss of viral biomass at higher severity. The relative abundances of Firmicutes, Actinobacteriota, and the viruses predicted to infect them increased significantly with burn severity, suggesting survival and viral infection of these fire-responsive and potentially spore-forming taxa. The degree of burn severity experienced by each patch of soil, rather than burn status alone, differed over mere meters in the same fire. Therefore, our analyses highlight the importance of high-resolution, paired biogeochemical data to explain soil community responses to fire. IMPORTANCE The impact of fire on the soil microbiome, particularly on understudied soil viral communities, warrants investigation, given known microbial contributions to biogeochemical processes and ecosystem recovery. Here, we collected 120 soil samples before and after a prescribed burn in a mixed conifer forest to assess the impacts of this disturbance on soil viral and prokaryotic communities. We show that simple categorical comparisons of burned and unburned areas were insufficient to reveal the underlying community response patterns. The patchy nature of the fire (indicated by soil chemistry data) led to significant changes in viral and prokaryotic community composition in areas of high burn severity, while communities that experienced lower burn severity were indistinguishable from those in unburned controls. Our results highlight the importance of considering highly resolved burn severity and biogeochemical measurements, even in nearby soils after the same fire, in order to understand soil microbial responses to prescribed burns.

Microbiology↗

DOE OSTI2025

Modeling the mechanisms of coastal vegetation dynamics and ecosystem responses to changing water levels

Coastal forests are increasingly experiencing mortality due to inundation by fresh- and seawater, leading to their replacement by marshes. These shifts alter vegetation composition, biogeochemical cycling, carbon storage, and hydrology. Using a hydraulically enabled ecosystem demography model (FATES-Hydro), we conducted numerical experiments to investigate the mechanisms behind inundation-driven forest loss and the ecosystem-scale consequences of forest-to-marsh transitions. We compared mortality processes and their effects across broadleaf and conifer trees at two coastal sites – Lake Erie (freshwater) and Chesapeake Bay (saline). Our simulations show that hydraulic failure, driven by root loss under prolonged flooding, is the primary mortality mechanism across both tree types and sites. Forest replacement by marsh reduced ecosystem-scale leaf area index (LAI), gross primary production (GPP), transpiration, and deep soil water uptake in conifer forests, while broadleaf forests experienced smaller changes due to lower initial LAI and greater marsh compensation. Marsh invasion occurred following canopy thinning driven by tree mortality. These findings suggest that, under similar root loss, hydraulic failure dominates coastal tree mortality regardless of species or water type, with denser forests experiencing stronger ecosystem impacts. Our study identifies key mortality mechanisms and offers testable hypotheses for future empirical studies on coastal vegetation change.

Ding, Junyan [Occidental College, Los Angeles, CA ↗

DOE OSTI2023

Climate Change Will Increase Biomass Proportion of Global Forest Carbon Stocks Under an SSP5–8.5 Climate Trajectory

Abstract A large amount of carbon is stored in global forests. However, the fraction of carbon stored as plant biomass versus soil organic carbon (SOC) varies among forest types, and potential changes over the 21st century are uncertain. Here, we used extensive data derived from inventories and remote sensing and Coupled Model Intercomparison Project Phase 6 (CMIP6) models to examine the current and 21st century dynamics in the proportion of biomass and SOC across global forests. We found that precipitation, elevation, soil, and wildfire were the primary controls of these differences in carbon pools. Under the SSP5–8.5 climate scenario, CMIP6 models project that the ratio of biomass to ecosystem carbon in global forests will increase across the 21st century, with the largest increases in boreal forests (95 ± 37%) compared to moist tropical forests (16 ± 15%). Changes in forest carbon pools resulting in greater biomass fraction will affect disturbance, and ecosystem carbon and energy balances, all of which interact with the climate system.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Differential effects of redox conditions on the decomposition of litter and soil organic matter

Soil redox conditions exert substantial influence on biogeochemical processes in terrestrial ecosystems. Humid tropical forests are often characterized by fluctuating redox dynamics, yet how redox fluctuations affect patterns in soil versus litter decomposition and associated CO2 fluxes are not well understood in these ecosystems. We used a 13C-labeled litter addition to explicitly follow the decomposition of litter-derived vs. native soil-derived organic matter in response to four different soil redox regimes—static oxic or anoxic, and two oscillating treatments—in soil from the Luquillo Experimental Forest, Puerto Rico. We coupled this incubation experiment with high-resolution mass spectrometry analysis to characterize the preferential decomposition of specific classes of organic molecules. CO2 production from litter and soil organic matter (SOM) showed distinctly different responses to redox manipulation. The cumulative production of SOM-derived CO2 was positively correlated with the length of soil exposure to an oxic headspace (r = 0.89, n = 20), whereas cumulative 13C-litter-derived CO2 production was not linked to oxygen availability. The CO2 production rate from litter was highest under static anoxic conditions in the first half of the incubation period, and later dropped to the lowest among all redox treatments. In the consistently anoxic soils, we observed the depletion of more oxidized water-extractable organic matter (especially amino sugars, carbohydrates, and proteins) over time, suggesting that under anaerobic conditions, microbes preferentially used more oxidized litter-derived compounds during the early stages of decomposition. Results from kinetic modeling showed that more frequent anoxic exposure limited the decomposition of a slow-cycling C pool, but not a fast-cycling pool. Overall, our results demonstrate that substrate source—freshly added litter vs. native organic matter—plays an important role in the redox sensitivity of organic matter decomposition. In soil environments that regularly experience redox fluctuations, anaerobic heterotrophs can be surprisingly effective in degrading fresh plant litter.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2023

Two Decades of Land Cover Change and Forest Fragmentation in Liberia: Consequences for the Contribution of Nature to People

The Guinean forests of West Africa have been identified as a global biodiversity hotspot due to its exceptional concentrations of endemic species and exceptional loss of habitats. The majority of what remains of the Guinean forests lies within Liberia, a country whose share of total wealth is nearly equally distributed into human and natural capital. The Liberian government seeks a more inclusive development agenda that forges a path for improved human capital while sustainably managing its natural capital wealth, which requires consistent data on land cover change and forest disturbance over time. To address this need, Landsat data were used to map and quantify land cover change and forest fragmentation in Liberia between 2000 and 2018. In addition, LiDAR data from the Global Ecosystem Dynamics Investigation (GEDI) mission were applied to assess the integrity of forest remnants. Between 2000 and 2018, only 1% of all forest cover classes (i.e., dense/primary, open/secondary and sparse/degraded) were converted into non-forest classes, with the most observed change being between these three forest classes. During the study period, 27% of the dense/primary forest class transitioned to either the open/secondary or sparse/degraded canopy classes through consistent fragmentation along the edges of the last large remaining blocks of dense/primary forest located in the north-west and south-east of Liberia and more than 14% of dense/primary forest areas identified in previous studies as “essential natural capital” for either biodiversity, forest carbon storage or provision of freshwater ecosystem services were degraded. The 2018 GEDI-based measurements show that the overall average height of dense/primary forest decreases by 24% and 48%, and canopy closure decreases by 33% and 59%, when transitioned to the open/secondary and sparse/degraded classes, respectively. The information derived from this analysis will be critical for informing the development of new policies and actions, leading to more sustainable forest management in Liberia.

Celio De Sousa↗

NASA NTRS2017

Monitoring Land Surface Albedo and Vegetation Dynamics Using High Spatial and Temporal Resolution Synthetic Time Series from Landsat and the MODIS BRDF/NBAR/Albedo Product

Seasonal vegetation phenology can significantly alter surface albedo which in turn affects the global energy balance and the albedo warmingcooling feedbacks that impact climate change. To monitor and quantify the surface dynamics of heterogeneous landscapes, high temporal and spatial resolution synthetic time series of albedo and the enhanced vegetation index (EVI) were generated from the 500-meter Moderate Resolution Imaging Spectroradiometer (MODIS) operational Collection V006 daily BRDF (Bidirectional Reflectance Distribution Function) / NBAR (Nadir BRDF-Adjusted Reflectance) / albedo products and 30-meter Landsat 5 albedo and near-nadir reflectance data through the use of the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM). The traditional Landsat Albedo (Shuai et al., 2011) makes use of the MODIS BRDFAlbedo products (MCD43) by assigning appropriate BRDFs from coincident MODIS products to each Landsat image to generate a 30-meter Landsat albedo product for that acquisition date. The available cloud free Landsat 5 albedos (due to clouds, generated every 16 days at best) were used in conjunction with the daily MODIS albedos to determine the appropriate 30-meter albedos for the intervening daily time steps in this study. These enhanced daily 30-meter spatial resolution synthetic time series were then used to track albedo and vegetation phenology dynamics over three Ameriflux tower sites (Harvard Forest in 2007, Santa Rita in 2011 and Walker Branch in 2005). These Ameriflux sites were chosen as they are all quite nearby new towers coming on line for the National Ecological Observatory Network (NEON), and thus represent locations which will be served by spatially paired albedo measures in the near future. The availability of data from the NEON towers will greatly expand the sources of tower albedometer data available for evaluation of satellite products. At these three Ameriflux tower sites the synthetic time series of broadband shortwave albedos were evaluated using the tower albedo measurements with a Root Mean Square Error (RMSE) less than 0.013 and a bias within the range of 0.006. These synthetic time series provide much greater spatial detail than the 500 meter gridded MODIS data, especially over more heterogeneous surfaces, which improves the efforts to characterize and monitor the spatial variation across species and communities. The mean of the difference between maximum and minimum synthetic time series of albedo within the MODIS pixels over a subset of satellite data of Harvard Forest (16 kilometers by 14 kilometers) was as high as 0.2 during the snow-covered period and reduced to around 0.1 during the snow-free period. Similarly, we have used STARFM to also couple MODIS Nadir BRDF-Adjusted Reflectances (NBAR) values with Landsat 5 reflectances to generate daily synthetic times series of NBAR and thus Enhanced Vegetation Index (NBAR-EVI) at a 30-meter resolution. While normally STARFM is used with directional reflectances, the use of the view angle corrected daily MODIS NBAR values will provide more consistent time series. These synthetic times series of EVI are shown to capture seasonal vegetation dynamics with finer spatial and temporal details, especially over heterogeneous land surfaces.

Vegetation Index↗

DOE OSTI2024

Variation in forest root image annotation by experts, novices, and AI

Abstract Background The manual study of root dynamics using images requires huge investments of time and resources and is prone to previously poorly quantified annotator bias. Artificial intelligence (AI) image-processing tools have been successful in overcoming limitations of manual annotation in homogeneous soils, but their efficiency and accuracy is yet to be widely tested on less homogenous, non-agricultural soil profiles, e.g., that of forests, from which data on root dynamics are key to understanding the carbon cycle. Here, we quantify variance in root length measured by human annotators with varying experience levels. We evaluate the application of a convolutional neural network (CNN) model, trained on a software accessible to researchers without a machine learning background, on a heterogeneous minirhizotron image dataset taken in a multispecies, mature, deciduous temperate forest. Results Less experienced annotators consistently identified more root length than experienced annotators. Root length annotation also varied between experienced annotators. The CNN root length results were neither precise nor accurate, taking ~ 10% of the time but significantly overestimating root length compared to expert manual annotation ( p = 0.01). The CNN net root length change results were closer to manual ( p = 0.08) but there remained substantial variation. Conclusions Manual root length annotation is contingent on the individual annotator. The only accessible CNN model cannot yet produce root data of sufficient accuracy and precision for ecological applications when applied to a complex, heterogeneous forest image dataset. A continuing evaluation and development of accessible CNNs for natural ecosystems is required.

Handy, Grace↗

DOE OSTI2023

Vegetation browning: global drivers, impacts, and feedbacks

As global climate conditions continue to change, disturbance regimes and environmental drivers will continue to shift, impacting global vegetation dynamics. Following a period of vegetation greening, there has been a progressive increase in remotely sensed vegetation browning globally. Further, given the many societal benefits that forests provide, it is critical that we understand vegetation dynamic alterations. Here, we review associative drivers, impacts, and feedbacks, revealing the complexity of browning. Concomitant increases in browning include the weakening of ecosystem services and functions and alterations to vegetation structure and species composition as well as the development of potential positive climate change feedbacks. Also discussed are the current challenges in browning detection and understanding associated impacts and feedbacks. Finally, we outline recommended strategies.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2020

Satellite Monitoring of Global Surface Soil Organic Carbon Dynamics Using the SMAP Level 4 Carbon Product

Soil organic carbon (SOC) is an important metric of soil health and the terrestrial carbon balance. Short‐term climate variations affect SOC through changes in temperature and moisture, which control vegetation growth and soil decomposition. We evaluated a satellite data‐driven carbon model, operating under the NASA Soil Moisture Active‐Passive (SMAP) mission, as a means of monitoring global surface SOC dynamics. The SMAP Level 4 Carbon (L4C) product estimates a daily global carbon budget including surface (0‐ to 5‐cm depth) SOC. We found that the L4C mean latitudinal SOC distribution is generally consistent with alternative assessments from static soil inventory records and dynamic global vegetation models (r ≥ 0.89). Within forest systems, based on inventory data, L4C SOC is most similar in magnitude to litterfall but is correlated with coarse woody debris ( urn:x-wiley:jgrg:media:jgrg21790:jgrg21790-math-0001) and total SOC ( urn:x-wiley:jgrg:media:jgrg21790:jgrg21790-math-0002). L4C SOC is sensitive to seasonal and annual climate variability, with mean residence times that range from 1.5 years in the wet tropics to 17 years in the cold tundra. Incorporating soil moisture retrievals from the SMAP L‐band (1.4 GHz) microwave radiometer within the L4C algorithm provides enhanced soil moisture sensitivity under low‐to‐moderate vegetation cover (<5 kg/sq.m vegetation water content). The L‐band soil moisture had the greatest impact on the L4C carbon budget in semiarid regions, which span almost 60% of the globe and account for substantial variability in the terrestrial carbon sink. The L4C operational product enables prognostic investigations into effects of recent climate trends and anomalies (e.g., droughts and pluvials) on shallow soil carbon dynamics.

K. Arthur Endsley↗

DOE OSTI2025

Role of Forest Carbon Change in Shaping Future Land Use and Land Cover Change

Global change, particularly the changes in atmospheric CO 2 concentration, climatic variables, and nitrogen deposition, has been widely recognized and examined to have worldwide impacts on forest carbon. However, its influence on forest area required to meet the demand for timber and carbon storage and subsequent land use and land cover change (LULCC) is rarely studied. This study explores the role of global change-driven forest carbon change in shaping future global LULCC projections and investigates underlying drivers. We incorporated the global change impacts on forest carbon from the Canadian Land Surface Scheme Including Biogeochemical Cycles model simulations (driven by meteorological forcing projections from two Earth system models [ESMs]) into the Global Change Analysis Model, under three combinations of shared socioeconomic pathways and representative concentration pathways (SSP126, SSP370, and SSP585). Including forest carbon change decreases the projected expansion of managed forest and managed pasture, reduces the loss of unmanaged pastures and forests, and provides more cropland. The relative change in managed forest by 2100 is -4.0%, -21.7%, and -31.9%, under SSP126, SSP370, and SSP585, respectively, when forest carbon change is considered. CO 2 fertilization is the dominant driver, increasing forest vegetation and soil carbon by 37% and 4.1%, and leading to 78.6% of the total area with a change in land use types by 2100 under SSP585. In comparison, climate change reduces forest vegetation and soil carbon by -3.5% and -0.8%, influencing 23.9% of the total area with a change in land use types by 2100 under SSP585, while nitrogen deposition has minor impacts. Using meteorological forcing data from two ESMs leads to similar impacts of forest carbon change on LULCC in terms of sign and trend but different magnitudes. This study highlights the large impact of forest carbon change on shaping future LULCC dynamics and the critical role of CO 2 fertilization.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2019

On Promoting the Use of Lidar Systems in Forest Ecosystem Research

Forest structure is an important driver of ecosystem dynamics, including the exchange of carbon, water and energy between canopies and the atmosphere. Structural descriptors are also used in numerous studies of eco-logical processes and ecosystem services. Over the last 20+ years, lidar technology has fundamentally changed the way we observe and describe forest structure, and it will continue to impact the ways in which we investigate and monitor the relations between forest structure and functions. Here we present the currently available lidar system types (ground, air, and space-based), we highlight opportunities and challenges associated with each system, as well as challenges associated with a wider use of lidar technology and wider availability of lidar derived products. We also suggest pathways for lidar to further contribute to addressing questions in forest ecosystem science and increase benefits to a wider community of researchers.

Lidar systems↗

DOE OSTI2023

Drought–induced increase in tree mortality and corresponding decrease in the carbon sink capacity of Canada's boreal forests from 1970 to 2020

Canada's boreal forests, which occupy approximately 30% of boreal forests world wide, play an important role in the global carbon budget. However, there is lit tle quantitative information available regarding the spatiotemporal changes in the drought-induced tree mortality of Canada's boreal forests overall and their associ ated impacts on biomass carbon dynamics. Here, we develop spatiotemporally ex plicit estimates of drought-induced tree mortality and corresponding biomass carbon sink capacity changes in Canada's boreal forests from 1970 to 2020. We show that the average annual tree mortality rate is approximately 2.7%. Approximately 43% of Canada's boreal forests have experienced significantly increasing tree mortality trends (71% of which are located in the western region of the country), and these trends have accelerated since 2002. This increase in tree mortality has resulted in sig nificant biomass carbon losses at an approximate rate of 1.51±0.29 MgC ha -1 year -1 (95% confidence interval) with an approximate total loss of 0.46±0.09 PgC year -1 (95% confidence interval). Under the drought condition increases predicted for this century, the capacity of Canada's boreal forests to act as a carbon sink will be further reduced, potentially leading to a significant positive climate feedback effect

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Plant roots stimulate the decomposition of complex, but not simple, soil carbon

Roots release carbon into soil and can alleviate energy limitation of microbial organic matter decomposition. We know little about the effects of roots on microbial decomposition of different organic matter substrates, despite the importance for soil carbon stocks and turnover. Through implementing root-microbe interactions, the Carbon, Organisms, Rhizosphere, and Protection in the Soil Environment (CORPSE) model was previously shown to represent dynamics of total soil carbon in temperate forest field experiments. However, the model permits alternative hypotheses concerning microbial-substrate affinity. We investigated how root inputs affect decomposition of soil organic carbon (SOC) with variable decomposability. We simulated SOC stocks in CORPSE and compared microbial degradation of two substrates types with varying root-microbe interactions under two alternative hypotheses that varied in microbial-substrate affinity. We compared our modeled hypotheses to a forest field experiment where we quantified decomposition of isotopically-labeled starch and leaf tissues in soils with manipulated root access to microbes. Here, we tested the hypothesis that decomposition of leaves would be more sensitive to root inputs than decomposition of starch, corresponding to the alternative model hypothesis. In the field study, leaf decomposition increased with root density while starch decomposition was unchanged by root density. Microbial biomass and enzyme activity consistently increased with root inputs in CORPSE and the field study. Our field experiment supported the CORPSE simulations with high microbial-substrate affinity. Roots stimulated microbial growth and enzyme production, which increased degradation of more complex substrates such as leaf tissues. Substrates that were easily decomposed, such as starch, may already be degrading at a maximum rate in the absence of rhizosphere influence because their decomposition rate was unchanged by root inputs. We found that the degree to which roots stimulate microbial decomposition depends on the substrate being decomposed, and that root-microbe interactions influenced SOC stocks in both our model and field experiment. Environmental changes that alter root-microbe interactions could, therefore, alter soil C stocks and biogeochemical cycling, and models of these interactions should incorporate differential influence of rhizosphere inputs on different substrates.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1990

Interfacing geographic information systems and remote sensing for rural land-use analysis

Recent advances in computer-based geographic information systems (GISs) are briefly reviewed, with an emphasis on the incorporation of remote-sensing data in GISs for rural applications. Topics addressed include sampling procedures for rural land-use analyses; GIS-based mapping of agricultural land use and productivity; remote sensing of land use and agricultural, forest, rangeland, and water resources; monitoring the dynamics of irrigation agriculture; GIS methods for detecting changes in land use over time; and the development of land-use modeling strategies.

Nellis, M. Duane↗

DOE OSTI2025

Environmental drivers of spatial variation in tropical forest canopy height: Insights from NASA’s GEDI spaceborne LiDAR

Forest canopy height is a fundamental ecosystem property—influencing patterns of forest carbon storage and forest ecosystem responses to climate variability and change. Previous studies have analyzed environmental drivers influencing spatial variation in canopy height at landscape-to-regional scales; however, far less is known about the environmental determinants underlying regional and global scale variation in forest canopy height. Using the canopy height metrics products from Global Ecosystem Dynamics Investigation (GEDI), a space-borne Light Detection and Ranging (LiDAR) instrument specifically designed to characterize forest structure, we analyze the environmental correlates of spatial variation of global tropical forest canopy height. Our study demonstrates that climate, topography, and soil properties account for 75% of the variation in tropical forest canopy height. Elevation, dry season length, and solar radiation are the most important drivers in determining canopy height both locally and regionally. These results emphasize the vulnerability of tropical forest structure to ongoing changes in the earth’s climate and provide a valuable empirical baseline for tropical forest management.

Science & Technology - Other Topics↗