Search NASA⌕ Search

SEARCH · Search NASA

Results for “Ecoregions”

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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Prolonged Drought in a Northern California Coastal Region Suppresses Wildfire Impacts on Hydrology

Wildfires naturally occur in many landscapes, however they are undergoing rapid regime shifts. Despite the emphasis in the literature on the most severe hydrological responses to wildfire, there remains a knowledge gap on the thresholds of wildfire (i.e., burned area/drainage area ratio, BAR) required to initiate hydrological responses. We investigated hydrological changes in the Russian River Watershed (RRW) in California, a coastal, Mediterranean, drought-prone, wildfire-adapted ecosystem, following ten wildfires that burned 30% of the watershed. Our findings suggest that sub-watersheds of the RRW have not burned beyond an intrinsic, unknown, threshold required to initiate change. Using paired watersheds, we examined spatiotemporal patterns of pre-and-post wildfire hydrology with a rainfall-runoff hydrological model. Even though these successive wildfires burned 1%–50% of each sub-watershed (1%–30% at moderate/high severity), we found little evidence of wildfire-related shifts in hydrology. As a function of BAR, wildfire imposed limited effects on runoff ratios (runoff/precipitation) and runoff residuals (observations—model simulations). Our findings that post-wildfire runoff enhancements asymptote beyond 30% burn indicate that when a watershed is burned beyond a certain threshold, the magnitude of the hydrologic response no longer increases. Drought and storm conditions explained much of the variability observed in streamflow, whereas wildfire explained only moderate variability in streamflow even when wildfire accounted for >45% BAR. While the BAR in the RRW was sufficiently beyond previously reported minimum disturbance thresholds (>20% burned forest), the lack of hydrological response is attributed to buffering effects of wildfire adaptation and drought factors that are unique to Mediterranean ecoregions.

Newcomer, Michelle E.↗
DOE OSTI2025

Blue Carbon Stocks Along the Pacific Coast of North America Are Mainly Driven by Local Rather Than Regional Factors

Coastal wetlands, including seagrass meadows, emergent marshes, mangroves, and temperate tidal swamps, can efficiently sequester and store large quantities of sediment organic carbon (SOC). However, SOC stocks may vary by ecosystem type and along environmental or climate gradients at different scales. Quantifying such variability is needed to improve blue carbon accounting, conservation effectiveness, and restoration planning. We analyzed SOC stocks in 1,284 sediment cores along >6,500 km of the Pacific coast of North America that included large environmental gradients and multiple ecosystem types. Tidal wetlands with woody vegetation (mangroves and swamps) had the highest mean stocks to 1 m depth (357 and 355 Mg ha −1 , respectively), 45% higher than marshes (245 Mg ha −1 ), and more than 500% higher than seagrass (68 Mg ha −1 ). Unvegetated tideflats, though not often considered a blue carbon ecosystem, had noteworthy stocks (148 Mg ha −1 ). Stocks increased with tidal elevation and with fine (<63 μm) sediment content in several ecosystems. Stocks also varied by dominant plant species within individual ecosystem types. At larger scales, marsh stocks were lowest in the Sonoran Desert region of Mexico, and swamp stocks differed among climate zones; otherwise stocks showed little correlation with ecoregion or latitude. More variability in SOC occurred among ecosystem types, and at smaller spatial scales (such as individual estuaries), than across regional climate gradients. These patterns can inform coastal conservation and restoration priorities across scales where preserving stored carbon and enhancing sequestration helps avert greenhouse gas emissions and maintains other vital ecosystem services.

emergent marsh↗
DOE OSTI2025

AI Improves the Accuracy, Reliability, and Economic Value of Continental‐Scale Flood Predictions

Accurate flood early warnings are critical to minimize damage and loss of life. Current large‐scale operational forecasting systems, however, have limited accuracy, description of uncertainty, and computational efficiency. While Artificial intelligence (AI) can address these limitations in principle, the accuracy and reliability of AI forecasts have thus far proven insufficient. Here we present a novel hybrid framework that integrates AI‐based machinery termed Errorcastnet (ECN) with the National Water Model (NWM) to showcase the potential of ensemble AI flood forecasts over the contiguous U.S. ECN boosts prediction accuracy four‐ to six‐fold across lead times of 1–10 days, while providing uncertainty quantification. It also outperforms Google's state‐of‐the‐art global AI model. ECN‐based forecasts offer superior economic value (up to four‐fold) for decision‐making as compared to those from NWM alone. ECN performs well in varied ecoregions, physiography, and land management conditions. The framework is computationally efficient, enabling national‐scale ensemble forecasts in minutes.

artificial intelligence↗
DOE OSTI2025

Peatland fires in Alaska will double by the end of the century

During recent summers, warm and dry conditions have increased the occurrence of wildfires and potentially peat-fires across Alaska. Limitations in resolving the fine-scale distribution of peatlands and climate observations have constrained our ability to accurately predict peat-fire dynamics. Using a new high-resolution peatland map of Alaska, we evaluated the climate and environmental controls of past and future peat-fire activity. Ensemble machine learning models identified reduced soil moisture, higher temperatures, and evapotranspiration as key predictors of annual total burned peatland area (tenfold CV R 2 = 0.62, RMSE = 221.1 km 2 ). By the end of the twenty-first century, models forced with climate datasets from representative concentration pathways (RCPs) 4.5, 6.0, and 8.5 emission scenarios project a statewide doubling of burned peatlands (increasing 61–121%), with regional increases ranging from 25–165% in polar, 61–95% in boreal, and 102–106% in maritime ecoregions. These projections indicate that wildfires will progressively encroach further into organic-rich moist and wet peaty soils, potentially amplifying soil carbon release across Alaska.

climate-change ecology↗
DOE OSTI2025

Nature-based climate solutions can help mitigate the radiative forcing that follows deforestation

Widespread expansion of agriculture and forestry has altered the surface of the Earth, the composition of the atmosphere, and as a result, the climate. Here we quantify the radiative forcing caused by the historical deforestation of an ecoregion in the U.S. Upper Midwest and the adoption of eight nature-based climate solutions. We combined regional forest inventory data with over three decades of remote sensing and in situ data from a replicated land use change experiment. Deforestation of the region caused net global warming (1626 ± 44 µW m -2 ), mainly from the 76 % reduction of ecosystem carbon stocks, but also from the 84 % reduction of the soil methane sink and the 115 % increase in soil nitrous oxide emissions. The associated albedo increase offset 24 % of this greenhouse gas induced warming. For the adoption of nature-based climate solutions, we found that conservation agriculture can provide -39 to -76 ± 31 µW m -2 of climate mitigation over a 100-year time period while short/medium length forestry rotations can provide more at -296 to -881 ± 44 µW m -2 and natural forest regeneration can provide the most at -1555 ± 44 µW m -2 . As the impacts of climate change on nature and society intensify, consideration should be given to the climate mitigation, habitat, and ecosystem services that nature-based climate solutions can provide.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Meta-analysis of North American Arctic and boreal aboveground biomass datasets: assessing accuracy, dynamics, and similarities

The North American arctic and boreal regions (ABRs) are rapidly warming and experiencing intensifying disturbances. Accurately quantifying aboveground biomass (AGB) is critical for understanding the impacts of these changes on the carbon cycle and for designing climate change mitigation strategies. Several AGB maps have been developed for the North American ABRs, including recent contributions from National Aeronautics and Space Administration’s Arctic-Boreal Vulnerability Experiment (ABoVE) campaign. However, these maps differ widely in training data, methodology, and resulting AGB density estimates. Presently, a comprehensive comparative evaluation is lacking, making it difficult for users to select datasets suited to their research or management needs. Here, in this study, we conducted a comparative analysis of nine AGB density datasets across North American ABRs, specifically for Alaska and Canada. We (1) summarized AGB by ecoregion and Canadian provinces, (2) evaluated their accuracy against field-based measurements, (3) analyzed spatial and temporal similarities among datasets, and (4) assessed their ability to capture disturbance (fire and harvest) impacts on AGB. We found substantial variation in regional and local AGB estimates across datasets, with overall accuracy ranging from R 2 = 0.25–0.62 and Bias% from −47.8% to 69.9% when validated against field plots. Despite these differences, most datasets have comparatively consistent spatial patterns in AGB (r > 0.8 for most cases). In contrast, agreement on the temporal patterns of AGB change is generally low. We found datasets with spatial resolutions ⩽300 m are capable of capturing disturbance impacts on AGB dynamics, though sensitivity varies across products. Our findings and dataset summary provide guidance for selecting appropriate AGB datasets for different applications within our study area. Our analysis also highlights the need to decrease map bias and increase capability to detect temporal change to decrease uncertainty of AGB datasets potentially by using training data which is representative of major plant functional types within the mapped area.

ABoVE↗
DOE OSTI2023

The drivers and predictability of wildfire re-burns in the western United States (US)

Evidence is mounting that the effectiveness of using prescribed burns as a management tactic may be diminishing due to the higher incidence of wildfire re-burns. The development of predictive models of re-burns is thus essential to better understand their primary drivers so that forest management practices can be updated to account for these events. First, we assess the potential for human activity as a driver of re-burns by evaluating re-burn trends both within and outside of the wildland–urban interface (WUI) of the western US. Next, we investigate the predictability of re-burns through the application of both random forest and the explanatory machine learning non-negative matrix factorization using k-means clustering (NMFk) algorithms to predict re-burn occurrence over California based on a number of climate factors. Our findings indicate that while most states showed increasing trends within the WUI when trends were conducted over longer moving windows (e.g. 20 years), California was the only state where the rate of increase was consistently higher in the WUI, indicating a stronger potential for human activity as a driver in that location. Furthermore, we find model performance was found to be robust over most of California (Testing F1 scores = 0.688), although results were highly variable based on EPA level III Ecoregion (F1 scores = 0.0–0.778). Insights provided from this study will lead to a better understanding of climate and human activity drivers of re-burns and how these vary at broad spatial scales so that improvements in forest management practices can be tuned according to the level of change that is expected for a given region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Geographic patterns of genomic diversity and structure in the C4 grass Panicum hallii across its natural distribution

Abstract Geographic patterns of within-species genomic diversity are shaped by evolutionary processes, life history and historical and contemporary factors. New genomic approaches can be used to infer the influence of such factors on the current distribution of infraspecific lineages. In this study, we evaluated the genomic and morphological diversity as well as the genetic structure of the C4 grass Panicum hallii across its complex natural distribution in North America. We sampled extensively across the natural range of P. hallii in Mexico and the USA to generate double-digestion restriction-associated DNA (ddRAD) sequence data for 423 individuals from 118 localities. We used these individuals to study the divergence between the two varieties of P. hallii, P. hallii var. filipes and P. hallii var. hallii as well as the genetic diversity and structure within these groups. We also examined the possibility of admixture in the geographically sympatric zone shared by both varieties, and assessed distribution shifts related with past climatic fluctuations. There is strong genetic and morphological divergence between the varieties and consistent genetic structure defining seven genetic clusters that follow major ecoregions across the range. South Texas constitutes a hotspot of genetic diversity with the co-occurrence of all genetic clusters and admixture between the two varieties. It is likely a recolonization and convergence point of populations that previously diverged in isolation during fragmentation events following glaciation periods.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Aboveground Biomass Estimation Using NISAR Simulated ALOS-2 Time Series Data

Aboveground biomass (AGB) is a critical parameter to better understand the global carbon cycle and to develop sustainable forest management. However, a large uncertainty prevails. L-band SAR data have demonstrated strong potential to accurately retrieve AGB over low-biomass regions (<100 Mg ha-1). The upcoming NASA-ISRO Synthetic Aperture Radar mission will collect data at L- and S-band over earth’s landmass with a repeat period of 12 days, allowing us to have ample data for monitoring biomass and its dynamics. One of the key science requirements of the mission is to produce annual AGB maps at 1-ha resolution with RMS accuracy of 20 Mg/ha for 80 percentage of area over low-biomass regions in Calibration/Validation sites. The NISAR biomass algorithm will generate AGB maps based on the parameterization of semi-empirical model along with NISAR time-series dual pol data (HH and HV). To calibrate and validate the model for mission requirements, the mission will use reference estimates of AGB produced from ground inventory plots and airborne LiDAR data collected over selected sites distributed across different global ecoregions. This paper presents the initial results of the calibration/validation of the NISAR AGB retrieval algorithm over the Lenoir Landing (LENO), Alabama, USA site using NISAR simulated ALOS-2 time series data. Five multi-temporal dual-pol HH and HV NISAR Simulated ALOS 2 data collections were used as input to assess the performance of the model. The model AGB retrieval results shows that the NISAR model was able to achieve RMS accuracy within 20 Mg/ha.

Ramachandran, Naveen [Jet Propulsion Laboratory, C↗
DOE OSTI2022

Mutually promoting or constraining? Disentangling the superimposed effect of velocity and illuminance on fish motion in low-velocity flows with a novel metric

Global climate change, species invasion, and human activities such as the construction of hydraulic facilities are contributing to the worldwide degradation of fish stocks. As a pivotal environmental factor that affects fish migration and population distribution, low-velocity flow has not drawn enough attention despite its extensive presence in various ecoregions. Herein, to understand the behavioural profiles of fish in low-velocity flow, we examined the motility and swimming performance of two representative cyprinids, grass carp (GC, Ctenopharyngodon idella) and silver carp (SC, Hypophthalmichthys molitrix), under the combined effect of different flow velocities and illuminance ranges. The two species were exposed to two flow velocities (0.15 and 0.25 m/s) and three illuminance ranges (100.0 – 0.9 lx, 300.0 – 2.5 lx, and 700.0 – 4.9 lx). A novel behavioural metric, composed of light preference, cruising swimming speed, rheotaxis index (RI), swimming stability (SS), and the probability of moving forwards/backwards over a certain distance (PM f -0.1 and PM b -0.1), was developed to depict the motion strategy of fish fully. By investigating the individual distribution of the fish in light gradient, we confirmed the scototaxis of GC and found the oscillating light preference in SC that changed from 84.4 – 10.2 lx to 6.0 – 2.1 lx and disappeared with increasing illuminance. At the given velocities, the RI and SS increased in both species with a faster flow, and SC was more forward-prone and stable than GC. Despite its fluctuating light preference, the higher illuminances heightened the RI and SS in SC; while in GC, higher illuminances inhibited the SS and had no impact on the RI. The results of PM f -0.1 and PM b -0.1 indicated that a higher flow velocity could facilitate temporary upstream swimming in both species, while illuminance could promote the same effect in SC only. Finally, our study proposed possible moving manoeuvres in fine-scale spatio-temporal scenarios such as attraction flow and untraditional passages and provides valuable insights into fish community dynamics, laying the groundwork for alleviating the threat from invasive species and for future fish population recovery.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Salinization and sedimentation drive contrasting assembly mechanisms of planktonic and sediment‐bound bacterial communities in agricultural streams

Abstract Agriculture is the most dominant land use globally and is projected to increase in the future to support a growing human population but also threatens ecosystem structure and services. Bacteria mediate numerous biogeochemical pathways within ecosystems. Therefore, identifying linkages between stressors associated with agricultural land use and responses of bacterial diversity is an important step in understanding and improving resource management. Here, we use the Mississippi Alluvial Plain (MAP) ecoregion, a highly modified agroecosystem, as a case study to better understand agriculturally associated drivers of stream bacterial diversity and assembly mechanisms. In the MAP, we found that planktonic bacterial communities were strongly influenced by salinity. Tolerant taxa increased with increasing ion concentrations, likely driving homogenous selection which accounted for ~90% of assembly processes. Sediment bacterial phylogenetic diversity increased with increasing agricultural land use and was influenced by sediment particle size, with assembly mechanisms shifting from homogenous to variable selection as differences in median particle size increased. Within individual streams, sediment heterogeneity was correlated with bacterial diversity and a subsidy‐stress relationship along the particle size gradient was observed. Planktonic and sediment communities within the same stream also diverged as sediment particle size decreased. Nutrients including carbon, nitrogen, and phosphorus, which tend to be elevated in agroecosystems, were also associated with detectable shifts in bacterial community structure. Collectively, our results establish that two understudied variables, salinity and sediment texture, are the primary drivers of bacterial diversity within the studied agroecosystem, whereas nutrients are secondary drivers. Although numerous macrobiological communities respond negatively, we observed increasing bacterial diversity in response to agricultural stressors including salinization and sedimentation. Elevated taxonomic and phylogenetic bacterial diversity likely increases the probability of detecting community responses to stressors. Thus, bacteria community responses may be more reliable for establishing water quality goals within highly modified agroecosystems that have experienced shifting baselines.

DeVilbiss, Stephen E.↗
DOE OSTI2020

Foliar functional traits from imaging spectroscopy across biomes in eastern North America

Summary Foliar functional traits are widely used to characterize leaf and canopy properties that drive ecosystem processes and to infer physiological processes in Earth system models. Imaging spectroscopy provides great potential to map foliar traits to characterize continuous functional variation and diversity, but few studies have demonstrated consistent methods for mapping multiple traits across biomes. With airborne imaging spectroscopy data and field data from 19 sites, we developed trait models using partial least squares regression, and mapped 26 foliar traits in seven NEON (National Ecological Observatory Network) ecoregions (domains) including temperate and subtropical forests and grasslands of eastern North America. Model validation accuracy varied among traits (normalized root mean squared error, 9.1–19.4%; coefficient of determination, 0.28–0.82), with phenolic concentration, leaf mass per area and equivalent water thickness performing best across domains. Across all trait maps, 90% of vegetated pixels had reasonable values for one trait, and 28–81% provided high confidence for multiple traits concurrently. Maps of 26 traits and their uncertainties for eastern US NEON sites are available for download, and are being expanded to the western United States and tundra/boreal zone. These data enable better understanding of trait variations and relationships over large areas, calibration of ecosystem models, and assessment of continental‐scale functional diversity.

Wang, Zhihui↗
DOE OSTI2026

Multi-ignition fire complexes drive extreme fire years and impacts

Climate change is intensifying fire behavior, with the largest and fastest-spreading fires causing the greatest impacts on people and ecosystems. Yet the mechanisms driving variability and trends in large fires remain poorly understood. Using 12-hour satellite-derived fire tracking data from 2012 to 2023, we show that the merging of separate ignitions into multi-ignition complexes is a key process amplifying fire size and destructive potential across temperate and boreal ecoregions. Multi-ignition fires account for 31% of the burned area in California and 59% in the Arctic-boreal domain, spread faster and persist longer than single-ignition fires, and disproportionately contribute to extreme fire years in California, Canada, and Siberia. They also generate stronger atmospheric feedbacks, produce more pyrocumulonimbus events, and strain firefighting capacity by dispersing suppression resources. Recognizing and accounting for fire-merging dynamics are critical for improving wildfire prediction, risk assessment, and management.

Environmental sciences↗
DOE OSTI2022

An experimental approach for crown to whole-canopy defoliation in forests

Canopy defoliation is an important source of disturbance in forest ecosystems that has rarely been represented in large-scale manipulation experiments. Scalable crown to canopy level experimental defoliation is needed to disentangle the effects of variable intensity, timing, and frequency on forest structure, function, and mortality. We present a novel pressure-washing-based defoliation method that can be implemented at the canopy-scale, throughout the canopy volume, targeted to individual leaves or trees, and completed within a timeframe of hours or days. Pressure washing proved successful at producing consistent leaf-level and whole-canopy defoliation, with 10%–20% reduction in leaf area index and consistent leaf surface area removal across branches and species. This method allows for stand-scale experimentation on defoliation disturbance in forested ecosystems and has the potential for broad application. Studies utilizing this standardized method could promote mechanistic understanding of defoliation effects on ecosystem structure and function and development of synthetic understanding across forest types, ecoregions, and defoliation sources.

Forestry↗
DOE OSTI2021

Raw Data published in PeerJ, 2021 for Crested Butte decomposition field study 2017-2019.

This data package contains text files that describe geochemical measurements collected from 2017-2019 during isolated conifer needle decomposition field studies in Crested Butte, Colorado. The geochemical measurements were collected across three elevations (2,800–3,500 m) ranging from montane to subalpine ecoregions. The data sets within include total carbon and nitrogen content and fourier-transform infrared spectroscopy (FTIR) results for the initial needles collected in 2016 and after decomposition in 2019. Data collection results from August 2020 are also included from when the experimental plots were removed to understand final concentrations of soil extractable carbon and nitrogen content as well as mass balances from litter bag deployments. Soil porewater results are also provided from 2017-2019 for DOC, TN, UV254, and specific UV absorbance (SUVA) analyses at 15 cm soil depth. Gas flux raw data provides CO2, CH4, N2O, and NH3 measurements above needle decomposition over the three study years. Finally, soil samples for microbial DNA extractions were collected from the upper soil depth. This raw data is available in the NCBI SRA database under SRA accession numbers PRJNA605259 and PRJNA715914. These data sets were generated to investigate the isolated decomposition of spruce and lodgepole conifer needles. The goal of this work was to determine the roles of elevation, soil type, seasonal changes in soil moisture, and snowmelt timing on litter decomposition processes. Results from this work are detailed in the reference paper "Effect of elevation, season and accelerated snowmelt on biogeochemical processes during isolated conifer needle litter decomposition. DOI: 10.7717/peerj.11926."

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Soil organic matter, tree communities, and fungal communities across mycorrhizal gradients in the Eastern United States

We collected these data to investigate how mycorrhizal associations are related to soil C and N across four sites in the eastern U.S. broadleaf forest biome, which capture broad variability in climate and tree species. Our sites represented each of the four ecoregions in the eastern United States temperate forest—warm continental (New Hampshire), hot continental (Wisconsin), Prairie (Illinios), and subtropical (Georgia). This breadth naturally provided tree species diversity and allowed us to also investigate how soil C and N are related to canopy tree and EcM fungal community composition. Specifically, we analyzed the effects of mycorrhizal association, canopy tree family, and EcM fungal taxa on the proportion of C and N associated with soil minerals (MAOM) and bulk soil C:N. These are plot level data from forests in New Hampshire, Georgia, Wisconsin, and Illinois. The plots are 10 m in radius and vary across gradients of ectomycorrhizal tree basal area. Within each plot, data include the basal area of all trees >2 cm in diameter identified to species, the abundance of different fungal taxa based on ITS sequences, and the %C, %N, C:N of bulk soil and of soil density fractions (free light, occluded light, and particulate) as well as the proportion of soil C and N within each fraction. The soil data (both organic matter and fungal communities) are from the top 10 cm of the mineral soil. This also includes a meta-analysis of leaf litter k and C:N values for the tree species present in the forests.The "Tree_BA_ALL.csv" files include the basal area of all trees >2 cm in diameter at breast height within our 10 cm radii plots. The "Soil_Data_Final.csv" file contains the soil carbon and nitrogen in bulk and density fractions (concentrations as well as proportion for free light fraction (fLF), occluded light fraction (oLF), and heavy or dense fraction (HF), oxalate extractable iron and aluminum concentrations, as well as the geographic coordinates of each plot's location. The "FungiNonRelative.csv" file contains the abundances of fungal taxa identified via ITS sequencing for each plot (with the exception of 4 plots from GA where there was not enough quality DNA to extract).The "R_ReadyK.csv" and "R_Ready_CN.csv" files contain leaf litter decomposition constant (k) and C:N values from the literature for the tree species found at our sites.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Storm and Annual Time Scale Hydrological Data for the Russian River Watershed 1996-2022

These files contains observed and simulated hydrological data (discharge, precipitation) that have been aggregated to the storm-event scale and to the annual time scale for the Russian River Watershed (RRW), California. Observed data are obtained from 12 different USGS hydrological stations located throughout the watershed, and discharge is simulated using the GR5H hourly hydrological model. Precipitation data are obtained from the NASA NLDAS NOAH Community Land Surface Model. All simulated and observed discharge are aggregated to the storm and annual time scales. We investigated changes in watershed hydrological conditions in the Russian River Watershed, a Mediterranean, drought prone, wildfire-adapted ecosystem, following eleven wildfires that occurred from 2017-2020. We ask two research questions: 1) How do interacting wildfire events, drought, and atmospheric rivers impact hydrological conditions of the watershed and in particular streamflow?, and 2) What percentage of new and/or cumulative wildfire disturbance is required to initiate hydrological change? We hypothesize that sub-watersheds of the RRW Mediterranean ecoregion have not burned beyond an intrinsic, and still unknown, threshold required to initiate change. Using a series of paired burned/unburned catchments nested within the larger watershed, we examined temporal and spatial patterns of pre-and-post wildfire water hydrology using a rainfall runoff hydrological model compared with data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

AmeriFlux FLUXNET-1F CA-Gro Ontario - Groundhog River, Boreal Mixedwood Forest

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site CA-Gro Ontario - Groundhog River, Boreal Mixedwood Forest. This is the FLUXNET version of the carbon flux data for the site CA-Gro Ontario - Groundhog River, Boreal Mixedwood Forest produced by applying the standard ONEFlux (1F) software. Site Description - Groundhog River (FCRN or CCP site "ON-OMW") is situated in a typical boreal mixedwood forest in northeastern Ontario (48.217 degrees north and 82.156 degrees west) about 80 km southwest of Timmins in Reeves Twp. near the Groundhog River. Rowe (1972) places the site in the Missinaibi-Cabonga Section of the Boreal Forest Region. In terms of ecoregion and ecozone, the site is in the Lake Timiskaming Lowlands of the Boreal Shield. The forest developed after high-grade logging in the 1930's. The average age in 2013 is estimated at beteen 75 and 80 years. The forest is dominated by five species characteristic of Ontario boreal mixedwoods: trembling aspen (Populus tremuloides Michx.), black spruce (Picea mariana (Mill.) B.S.P.), white spruce (Picea glauca (Moench.) Voss.), white birch (Betula papyrifera Marsh.), and balsam fir (Abies balsamea (L.) Mill.). The surficial geology is a lacustrine deposit of varved or massive clays, silts and silty sands. The soil is an orthic gleysol with a soil moisture regime classified as fresh to very fresh. Plonski (1974) rates it as a site class 1. The topography is simple and flat with an overall elevation of 340 m ASL.

McCaughey, Harry↗