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DOE OSTI2025

Methane emission hotspots in a boreal forest-fen mosaic potentially linked to deep taliks

Permafrost thaw is transforming boreal forests into mosaics of wetlands and drier uplands. Topographic controls on hydrological and ecological conditions impact methane (CH 4 ) fluxes, contributing to uncertainty in local and regional CH 4 budgets and underlying drivers. The objective of this study was to explore CH 4 fluxes and their drivers in a transitioning boreal forest-fen ecosystem (Goldstream Valley, Alaska, USA). This landscape is characterized by thawing discontinuous permafrost and heterogeneous mosaics of fens, collapse-scar channels, and small mounds of permafrost soils. From a survey in July 2021, observed chamber CH4 fluxes included fen areas with intermediate to very high emissions (29.8–635.3 mg CH 4 m −2 d −1 ), clustered locations with CH 4 uptake (−2.11 to −0.7 mg CH 4 m −2 d −1 ), and three anomalous emission hotspots (342.4–772.4 mg CH 4 m −2 d −1 ) that were located near samples with lower emissions. Some surface and near-surface variables partially explained the spatial variation in CH 4 flux. Log-transformed CH 4 flux had a positive linear relationship with soil moisture at 20 cm depth ( R 2 = 0.31, p -value < 1e-5) and negative linear relationships with microtopography ( R 2 = 0.13, p -value < 0.006) and slope ( R 2 = 0.28, p -value < 2e-5). Methane emissions generally occurred in flat, wet, graminoid-dominated fens, whereas CH 4 uptake occurred on permafrost mounds dominated by feather mosses and woody vegetation. However, the CH 4 hotspots occurred on drier, slightly sloped locations with low or undetectable near-surface methanogen abundance, suggesting that CH 4 was produced in deeper soils. When the hotspot samples were omitted, log-transformed CH 4 flux had a positive linear relationship with near-surface methanogen abundance ( R 2 = 0.29, p -value = 0.0023), and stronger linear relationships with soil moisture, slope, and soil macronutrient concentrations. Our findings suggest that some CH 4 emission hotspots could arise from CH 4 in deep taliks. The inference that methanogenesis occurs in deep taliks was strengthened by the identification of intrapermafrost taliks across the study area using low-frequency geophysical induction. This study assesses surface spatial heterogeneity in the context of subsurface permafrost conditions and highlights the complexity of CH 4 flux patterns in transitioning forest-wetland ecosystems. To better inform regional CH 4 budgets, further research is needed to understand the spatial distribution of terrestrial CH 4 hotspots and to resolve their surface, near-surface, and subsurface drivers.

boreal↗

DOE OSTI2024

Pinus ponderosa physiology data from the 2022 shade manipulation field experiment at Game Ridge, Missoula County, Montana, USA

This dataset contains physiology data on Pinus ponderosa saplings, including: leaf water potential (MPa, megapascals), leaf osmotic potential (MPa, megapascals), leaf pressure potential (MPa, megapascals), leaf relative water content (% saturated mass), as well as soluble sugars (% dry mass),starch (% dry mass), and total nonstructural carbohydrates (% dry mass) found in branch phloem and xylem. Data files and data dictionary(ies) are uploaded as .csv files and .xlsx files. The Users Guide is a .pdf file. Location data can be found in the Google Earth file GameRidge_SitePlotCoordinates.kmz.kml included here. These datasets were collected for Plant Carbohydrate Depletion, Mycorrhizal Networks, and Vulnerability to Drought: An Experimental Test in the Field. This experiment examined the interdependency between plant hydraulics and carbohydrate availability and sought to develop ways to incorporate interactions with below ground symbiotic organisms to better model and quantify forest response to drought.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Pinus ponderosa physiology data from the 2023 girdling manipulation field experiment at Game Ridge, Missoula County, Montana, USA

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Data for Regier et al. (2025), "Short-term experimental flooding impacts soil biogeochemistry but not aboveground vegetation in a coastal forest"

Rising sea levels and intensifying storms increase flooding pressure on coastal forests, but the mechanisms that drive coastal forest mortality remain unclear. This study used an ecosystem-scale manipulation (TEMPEST, Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments) to simulate hurricane-level flooding of a coastal forest and explore the individual and interactive impacts of inundation and salinity. This dataset comprises the results reported by Regier et al. (2025) in their paper "Short-term experimental flooding impacts soil biogeochemistry but not aboveground vegetation in a coastal forest." It consists of measurements of:- Belowground conductance- Soil dissolved oxygen and redox- Soil and tree greenhouse gas fluxes- Leaf photosynthesis, stomatal conductance, and intercellular carbon dioxide- Sap flux- Soil volumetric water content and electrical conductivityAll files are plain-text CSV (comma separated value) and no special software is required to read them.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1973

Multispectral scanner imagery for plant community classification.

Optimum channel selection among 12 channels of multispectral scanner imagery identified six as providing the best information for computerized classification of 11 plant communities and two nonvegetation classes. Intensive preprocessing of the spectral data was required to eliminate bidirectional reflectance effects of the spectral imagery caused by scanner view angle and varying geometry of the plant canopy. Generalized plant community types - forest, grassland, and hydrophytic systems - were acceptably classified based on ecological analysis. Serious, but soluble, errors occurred with attempts to classify specific community types within the grassland system. However, special clustering analyses provided for improved classification of specific grassland communities.

Driscoll, R. S.↗

NASA NTRS1975

NASA Earth Resources Survey Symposium. Volume 1-A: Agriculture, environment

A number of papers dealing with the practical application of imagery obtained from remote sensors on LANDSAT satellites, the Skylab Earth resources experiment package, and aircraft to problems in agriculture and the environment were presented. Some of the more important topics that were covered included: range management and resources, environmental monitoring and management, crop growth and inventory, land management, multispectral band scanners, forest management, mapping, marshlands, strip mining, water quality and pollution, ecology.

Source record↗

DOE OSTI2022

Boosts in leaf-level photosynthetic capacity aid Pinus ponderosa recovery from wildfire

Forests mitigate climate change by sequestering massive amounts of carbon, but recent increases in wildfire activity are threatening carbon storage. Currently, our understanding of wildfire impacts on forest resilience and the mechanisms controlling post-fire recovery remains unresolved due to a lack of empirical data on mature trees in natural settings. Here, we quantify the physiological mechanisms controlling carbon uptake immediately following wildfire in mature individuals of ponderosa pine (Pinus ponderosa), a wide-spread and canopy-dominant tree species in fire-prone forests. While photosynthetic capacity was lower in burned than unburned trees due to an overall depletion of resources, we show that within the burned trees, photosynthetic capacity increases with the severity of damage. Our data reveal that boosts in the efficiency of carbon uptake at the leaf-level may compensate for whole-tree damage, including the loss of leaf area and roots. We further show that heightened photosynthetic capacity in remaining needles on burned trees may be linked with reduced water stress and leaf nitrogen content, providing pivotal information about post-fire physiological processes. Our results have implications for Earth system modeling efforts because measurements of species-level physiological parameters are used in models to predict ecosystem and landscape-level carbon trajectories. Finally, current land management practices do not account for physiological resilience and recovery of severely burned trees. Our results suggest premature harvest may remove individuals that may otherwise survive, irrevocably altering forest carbon balance.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1974

Application of ERTS imagery in estimating the environmental impact of a freeway through the Knysna area of South Africa

In the coastal areas north-east and south-west of Knysna, South Africa lie natural forests, lakes and lagoons highly regarded by many for their aesthetic and ecological richness. A freeway construction project has given rise to fears of the degradation or destruction of these natural features. The possibility was investigated of using ERTS imagery to estimate the environmental impact of the freeway and found that: (1) All threatened features could readily be identified on the imagery. (2) It was possible within a short time to provide an area estimate of damage to indigenous forest. (3) In several important respects the imagery has advantages over maps and aerial photos for this type of work. (4) The imagery will enable monitoring of the actual environmental impact of the freeway when completed.

Williamson, D. T.↗

NASA NTRSDate not supplied

Using NASA Earth Observations to Identify Wildfire Impacts on Hydrologic Functions and Recovery in the Gila National Forest

Wildfires can dramatically influence both abiotic and biotic components of a landscape, including soil stability and chemistry; vegetation health, density, and composition; and water flow and quality. In addition to the immediate hazards posed by wildfires, subsequent hazards such as flooding and debris flow can impact the area. In New Mexico’s Gila National Forest, wildfire events have occurred with increasing frequency and severity over recent years, notably including the Whitewater Baldy Complex Fire (2012) and Silver Fire (2013), which burned over 290,000 acres and 138,698 acres, respectively, according to the Burned Area Emergency Response Team Executive Summary reports. Following a significant wildfire, land and resource management decisions are made, including when and where to focus vegetation and stream restoration efforts. This research is the result of a collaboration between the NASA DEVELOP National Program and the US Forest Service, which aimed to utilize NASA Earth observations to help inform those critical land management decisions. The project had two main objectives: 1) assess the efficacy of post-fire vegetation restoration efforts and 2) analyze the impact of burn events on the hydrology at the watershed-scale. To accomplish this first goal, data from Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), and Landsat 8 Operational Land Imager (OLI) were used to study the vegetation health over time of treated and non-treated burn areas. To accomplish the latter, various aspects of stream behavior were examined in relation to burn events, including the runoff coefficient and “flashiness” of streams based on USGS stream gauge data and Integrated Multi-satelllite Retrievals for GPM (IMERG) precipitation data. This will allow land managers to better understand the complex ecological relationship between the cascading effects after wildfire and the greater forest ecosystem.

Madeline Allen↗

DOE OSTI2024

Toward a coordinated understanding of hydro‐biogeochemical root functions in tropical forests for application in vegetation models

Summary Tropical forest root characteristics and resource acquisition strategies are underrepresented in vegetation and global models, hampering the prediction of forest–climate feedbacks for these carbon‐rich ecosystems. Lowland tropical forests often have globally unique combinations of high taxonomic and functional biodiversity, rainfall seasonality, and strongly weathered infertile soils, giving rise to distinct patterns in root traits and functions compared with higher latitude ecosystems. We provide a roadmap for integrating recent advances in our understanding of tropical forest belowground function into vegetation models, focusing on water and nutrient acquisition. We offer comparisons of recent advances in empirical and model understanding of root characteristics that represent important functional processes in tropical forests. We focus on: (1) fine‐root strategies for soil resource exploration, (2) coupling and trade‐offs in fine‐root water vs nutrient acquisition, and (3) aboveground–belowground linkages in plant resource acquisition and use. We suggest avenues for representing these extremely diverse plant communities in computationally manageable and ecologically meaningful groups in models for linked aboveground–belowground hydro‐nutrient functions. Tropical forests are undergoing warming, shifting rainfall regimes, and exacerbation of soil nutrient scarcity caused by elevated atmospheric CO 2 . The accurate model representation of tropical forest functions is crucial for understanding the interactions of this biome with the climate.

Plant Sciences↗

DOE OSTI2021

Taxonomic and Functional Diversity of Aquatic Macroinvertebrate Assemblages and Water Quality in Rivers of the Dry Tropics of Costa Rica

One of Costa Rica’s driest areas is the province of Guanacaste, in the Pacific Northwest, with almost no rain during the dry season from November to April. Due to this marked seasonality, the area is covered by dry tropical deciduous forest, considered the most threatened and least known tropical ecosystem in this area. This study analyzes and characterizes the assemblages of aquatic macroinvertebrates in water bodies within the Tempisque basin. Biological water quality was measured using the BMWP′-CR index. Macroinvertebrate assemblages were analyzed using abundance, richness, and functional feeding group approaches (FFG). Partial least square (PLS) analyses were performed, and the relationships between environmental factors and macroinvertebrate assemblages are also discussed. Macroinvertebrate assemblages were dominated numerically by mayflies, caddisflies, flies, and beetles. The BWMP′-CR index showed varying biological water quality, ranging from “very bad” to “excellent,” depending on rainfall and site management. Results suggest that tropical Mesoamerican rivers contradict the “river continuum concept” because predators and scrapers displace shredders in numbers. On the other hand, the study area shows a notable high richness of the Coleoptera genera. The class Rhynchocoela (Nemertea) is reported for the first time in Central America. The results indicate that the dry forest river ecosystem shows staggering biodiversity despite the surrounding agricultural land use, probably because of their older origin concerning tropical rain forests in Central America.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Leaf traits and canopy structure together explain canopy functional diversity: an airborne remote sensing approach

Plant functional diversity is strongly connected to photosynthetic carbon assimilation in terrestrial ecosystems. However, many of the plant functional traits that regulate photosynthetic capacity, including foliar nitrogen concentration and leaf mass per area, vary significantly between and within plant functional types and vertically through forest canopies, resulting in considerable landscape-scale heterogeneity in three dimensions. Hyperspectral imagery has been used extensively to quantify functional traits across a range of ecosystems but is generally limited to providing information for top-of-canopy leaves only. On the other hand, lidar data can be used to retrieve the vertical structure of forest canopies. Because these data are rarely collected at the same time, there are unanswered questions about the effect of forest structure on the 3-D spatial patterns of functional traits across ecosystems. In the United States, the National Ecological Observatory Network's Airborne Observation Platform (NEON AOP) provides an opportunity to address this structure-function relationship by collecting lidar and hyperspectral data together across a variety of ecoregions. With a fusion of hyperspectral and lidar data from the NEON AOP and field-collected foliar trait data, we assessed the impacts of forest structure on spatial patterns of N. In addition, we examine the influence of abiotic gradients and management regimes on top of canopy %N and total canopy N (i.e. the total amount of N (g/m 2 ) within a forest canopy) at a NEON site consisting of a mosaic of open longleaf pine and dense broadleaf deciduous forests. Here, our resulting maps suggest that in contrast with top-of-canopy values, total canopy N variation is dampened across this landscape resulting in relatively homogeneous spatial patterns. At the same time, we found that leaf functional diversity and canopy structural diversity showed distinct dendritic patterns related to the spatial distribution of plant functional types.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

AmeriFlux US-xTR NEON Treehaven (TREE)

This is the AmeriFlux version of the carbon flux data for the site US-xTR NEON Treehaven (TREE). Site Description - Treehaven, situated between Rhinelander and Tomahawk, WI, is one of two relocatable sites located in NEON’s Great Lakes Domain. The Treehaven property spans 1400 acres and is owned and operated by the University of Wisconsin-Stevens Point (UWSP), College of Natural Resources. UWSP uses the property and conference center for summer field techniques courses but welcomes other educators, researchers, and the public to use and enjoy their forests, trails, and facility.

Network), NEON (National Ecological Observatory↗

DOE OSTI2023

AmeriFlux FLUXNET-1F US-xTR NEON Treehaven (TREE)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-xTR NEON Treehaven (TREE). This is the FLUXNET version of the carbon flux data for the site US-xTR NEON Treehaven (TREE) produced by applying the standard ONEFlux (1F) software. Site Description - Treehaven, situated between Rhinelander and Tomahawk, WI, is one of two relocatable sites located in NEON’s Great Lakes Domain. The Treehaven property spans 1400 acres and is owned and operated by the University of Wisconsin-Stevens Point (UWSP), College of Natural Resources. UWSP uses the property and conference center for summer field techniques courses but welcomes other educators, researchers, and the public to use and enjoy their forests, trails, and facility.

Network), NEON (National Ecological Observatory↗

NASA NTRS2019

Effects of Topography on Tropical Forest Structure Depend on Climate Context

Topography affects abiotic conditions which can influence the structure, function, and dynamics of ecological communities. An increasing number of studies have demonstrated biological consequences of fine-scale topographic heterogeneity but we have a limited understanding of how We merged high-resolution (1 sq. meter) data on topography and canopy height derived from airborne lidar with ground-based data from 15 forest plots in Puerto Rico distributed along a precipitation gradient spanning ca. 800 to 3,500 mm yr(exp -1). Ground-based data included species composition, estimated above-ground biomass (AGB), and two key functional traits (wood density and leaf mass per area, LMA) that reflect resource-use strategies and a trade-off between hydraulic safety and hydraulic efficiency. We used hierarchical Bayesian models to evaluate how the interaction between topography climate is related to metrics of forest structure (i.e., canopy height and AGB), as well as taxonomic and functional alpha- and beta-diversity. Fine-scale topography (characterized with the topographic wetness index, TWI) significantly affected forest structure and the strength (and in some cases direction) of these effects varied across the precipitation gradient. In all plots, canopy height increased with topographic wetness but the effect was much stronger in dry compared to wet forest plots. In dry forest plots, topographically wetter microsites also had higher levels of AGB but in wet forest plots, topographically drier microsites had higher AGB. Fine-scale topography influenced functional composition but had only weak or non-significant effects on taxonomic and functional alpha- and beta-diversity. For instance, community-weighted wood density followed a similar pattern to AGB across plots. We also found a marginally significant association between variation of wood density and topographic heterogeneity that depended on climate context. Synthesis: The effects of fine-scale topographic heterogeneity on tropical forest structure and composition depend on the climate context. Our study demonstrates how a stronger integration of topographic heterogeneity across precipitation gradients could improve estimates of forest structure and biomass, and may provide insight to the ways that topography might mediate species responses to drought and climate change.

Tropical dry forest↗

NASA NTRS1994

Overview of the Oregon Transect Ecosystem Research Project

The Oregon Transect Ecosystem Research (OTTER) project is a study of ecosystem functions in coniferous forests using the methods of computer modeling, experimental and theoretical remote sensing, and ecological field and laboratory techniques. The study is focused on predicting the major fluxes of carbon, nitrogen, and water, and the factors that dynamically regulate them. The OTTER project was conceived to test two major questions: (1) Can a generalized ecosystem simulation model, designed to use mainly parameters available from remote sensing, predict the functioning of forests across an environmentally variable region? and (2) To what extent can the variables required by this model be derived from remotely sensed data? The scientific objectives and scope of the project demanded that a coordinated effort be made to link ground measurements with remote sensing and modeling requirements. OTTER was selected as a focus for a National Aeronautics and Space Administration (NASA)-sponsored Multi-sensor Aircraft Campaign (MAC; combining NASA aircraft and sensors with those of others) on the basis of experience gained in past ecosystem studies and remote-sensing projects, and the importance of the OTTER objectives to NASA's long-range science goals and plans. Having several independent approaches available, both on the ground and from various remote-sensing platforms, proved valuable in estimating and validating many of the critical variables. This experience and cross comparison should help simplify future studies of a similar nature. Edited data sets from the OTTER project are now available to the scientific community on optical disks or via on-line data banks at NASA (Washington, D.C., USA) and Oregon State University (Corvallis, Oregon, USA).

Peterson, David L.↗

DOE OSTI2021

Machine learning feature analysis illuminates disparity between E3SM climate models and observed climate change

In September of 2020, Arctic sea ice extent was the second-lowest on record. State of the art climate prediction uses Earth system models (ESMs), driven by systems of differential equations representing the laws of physics. Previously, these models have tended to underestimate Arctic sea ice loss. The issue is grave because accurate modeling is critical for economic, ecological, and geopolitical planning. We use machine learning techniques, including random forest regression and Gini importance, to show that the Energy Exascale Earth System Model (E3SM) relies too heavily on just one of the ten chosen climatological quantities to predict September sea ice averages. Furthermore, E3SM gives too much importance to six of those quantities when compared to observed data. Finally, identifying the features that climate models incorrectly rely on should allow climatologists to improve prediction accuracy.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

The Latent Dirichlet Allocation model applied to airborne LiDAR data: A case study on mapping forest degradation associated with fragmentation and fire in the Amazon region

1. LiDAR data are being increasingly used to provide a detailed characterization of the vertical profile of forests. This characterization enables the generation of new insights on the influence of environmental drivers and anthropogenic disturbances on forest structure as well as on how forest structure influences important ecosystem functions and services. Unfortunately, extracting information from LiDAR data in a way that enables the spatial visualization of forest structure, as well as its temporal changes, is challenging due to the high dimensionality of these data. 2. In this study, we show how the Latent Dirichlet Allocation model applied to LiDAR data (LidarLDA) can be used to identify forest structural types and how the relative abundance of these forest types changes throughout the landscape. The code to fit this model is made available through the open-source r package LidarLDA in github. We illustrate the use of LidarLDA both with simulated data and data from a large-scale fire experiment in the Brazilian Amazon region. 3. Using simulated data, we demonstrate that LidarLDA accurately identifies the number of forest types as well as their spatial distribution and absorptance probabilities. For the empirical data, we found that LidarLDA detects both landscape-level patterns in forest structure as well as the strong interacting effect of fire and forest fragmentation on forest structure based on the experimental fire plots. More specifically, LidarLDA reveals that proximity to forest edge exacerbates the impact of fires, and that burned forests remain structurally different from unburned areas for at least 7 years, even when burned only once. Importantly, LidarLDA generates insights on the 3D structure of forest that cannot be obtained using more standard approaches that just focus on top-of-the-canopy information (e.g. canopy height models based on LiDAR data). 4. By enabling the mapping of forest structure and its temporal changes, we believe that LidarLDA will be of broad utility to the ecological research community.

54 ENVIRONMENTAL SCIENCES↗