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All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Arizona Water Resources: Utilizing Aerial Imagery and NASA Earth Observations to Assess Pinyon-Juniper Tree Mortality in Flagstaff, AZ

Pinyon-juniper woodlands (PJW) are a vital habitat and food source for several wildlife species and a source of both utility and cultural importance for Indigenous groups. In 2021, amidst a decades-long drought, an extensive juniper mortality event occurred at Wupatki National Monument (WNM) in Arizona. In response, the National Park Service (NPS) is evaluating which land management practices will be beneficial. In partnership with the NPS, the NASA DEVELOP team used remote sensing data to map PJW mortality and analyze the relation of tree mortality to stand density, climate, and topography in north-central Arizona from 2015 to 2021. To identify the extent of PJW, the team performed an unsupervised classification using National Agricultural Imagery Program (NAIP) data with validation sources including NPS-created land cover maps, Landscape Fire and Resource Management Planning Tools (LANDFIRE), NPS and United States Forest Service (USFS) vegetation maps, and Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) data. Terra Moderate Resolution Imaging Spectroradiometer (MODIS), Global Precipitation Measurement (GPM) Integrated Multi-satellite Retrievals for GPM (IMERG), Soil Moisture Active Passive (SMAP), Shuttle Radar Topography Mission (SRTM), and Landsat 8-derived Normalized Difference Vegetation Index (NDVI) and Normalized Difference Moisture Index (NDMI) were used to analyze factors contributing to pinyon-juniper mortality. Although no relationships were found in the broader study region, PJW mortality was weakly correlated to elevation, soil moisture, and land surface temperature within WNM. Results from this study can inform NPS vegetation management that best protects natural and cultural resources.

Margaret Jaenicke↗
NASA NTRS2013

Tree Line Structure and Dynamics at the Northern Limit of the Larch Forest: Anabar Plateau, Siberia, Russia

The goal of the study was to provide an analysis of climate impact before, during, and after the Little Ice Age (LIA) on the larch (Larix gmelinii) tree line at the northern extreme of Siberian forests. Recent decadal climate change impacts on the tree line, regeneration abundance, and age structure were analyzed. The location of the study area was within the forest-tundra ecotone (elevation range 170-450 m) in the Anabar Plateau, northern Siberia. Field studies were conducted along elevational transects. Tree natality/mortality and radial increment were determined based on dendrochronology analyses. Tree morphology, number of living and subfossil trees, regeneration abundance, and age structure were studied. Locations of pre-LIA, LIA, and post-LIA tree lines and refugia boundaries were established. Long-term climate variables and drought index were included in the analysis. It was found that tree mortality from the 16th century through the beginning of the 19th century caused a downward tree line recession. Sparse larch stands experienced deforestation, transforming into tundra with isolated relict trees. The maximum tree mortality and radial growth decrease were observed to have occurred at the beginning of 18th century. Now larch, at its northern boundary in Siberia, is migrating into tundra areas. Upward tree migration was induced by warming in the middle of the 19th century. Refugia played an important role in repopulation of the forest-tundra ecotone by providing a seed source and shelter for recruitment of larch regeneration. Currently this ecotone is being repopulated mainly by tree cohorts that were established after the 1930s. The last two decades of warming did not result in an acceleration of regeneration recruitment because of increased drought conditions. The regeneration line reached (but did not exceed) the pre-LIA tree line location, although contemporary tree heights and stand densities are comparatively lower than in the pre-LIA period. The mean rate of tree line upward migration has been about 0.35 m/yr (with a range of 0.21-0.58), which translates to a tree line response to temperature of about 55 m/deg C.

Northern Limit↗
NASA NTRS1974

Application of ERTS-1 imagery and underflight photography in the detection and monitoring of forest insect infections in the Sierra Nevada Mountains of California

The author has identified the following significant results. Analysis of ERTS-1 imagery with underflight aerial photo support including U-2, in the Sierra Nevada Mountains of California, indicates promising possibilities of detecting and monitoring forest insect outbreaks visually with some mechanical support utilizing the VP-8 image analyzer. Visually, it is possible at a scale of 1:1,000,000 to discriminate between large areas of damaged and undamaged forests; timbered and non-timbered areas; pasture land and cultivated fields; desert and riparian vegetation. At a scale of 1:80,000 it is possible to distinguish among three classes of tree mortality; defoliated and undefoliated areas; non-host mixed conifers; and mountain meadows, rock domes, lakes and glaciers. Machine tests showed significant differences in image densities among various bands and mortality areas.

Hall, R. C.↗
DOE OSTI2024

Growth, mortality, wood density, biomass data from BIONTE inventories in Manaus, Brazil

BIONTE (BIOmass and NuTrient Experiment) is a selective logging experiment established at the Experimental Station of Tropical Forestry (EEST, aka “ZF2”) field research station in the mid 1980s in the central Amazon (Higuchi et al. 1997, Amaral et al. 2019). Led by the National Institute for Amazon Research (INPA) in Brazil, the project aimed at assessing the effects of logging intensity on forest dynamics and enabling the creation of a model of forest management for the Central Amazon. The experiment included three levels of increasing selective logging intensity and controls, with 1 hectare sample plots (12 total) located at the center of 4 hectare treatment plots. The site’s Köppen classification is tropical rainforest (Af), characterized by high temperatures and humidity, with mean annual temperatures around 27 ℃ and mean annual precipitation around 2200 mm of rain. The vegetation has a high floristic diversity, the soils of the region are poor in nutrients, and the topography is characterized by plateaus (where BIONTE is located), and also valley bottoms and slopes. The inventory (growth and mortality) and biomass data included here covers the 1990 to 2019 period, with wood density being averaged from existing datasets. This dataset includes a data file in .csv file format and a .txt file, BIONTE_mortality-rates_headers.txt, that provides descriptions for the data file headers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Insights Into Nature-Based Climate Solutions: Managing Forests for Climate Resilience and Carbon Stability

Successful implementation of forest management as a nature-based climate solution is dependent on the durability of management-induced changes in forest carbon storage and sequestration. As forests face unprecedented stability risks in the face of ongoing climate change, much remains unknown regarding how management will impact forest stability, or how interactions with climate might shift the response of forests to management across spatiotemporal scales. Here, we used a process-based model to simulate multidecadal projections of forest dynamics in response to changes in management and climate. Simulations were conducted across gradients in forest type, edaphic factors, and management intensity under two alternate radiative forcing scenarios (RCP4.5 and RCP8.5). This allowed for the quantification of forest stability shifts in response to climate change, and the role of management in modulating that response, where ecosystem stability is characterized as the resilience and temporal stability of net primary production, aboveground biomass, and soil carbon. Our results indicate that forest structure is primarily shaped by management, but the same management strategy often produced divergent structures over time, due to interactions with regional climate change. We found that management can be used to increase stability and minimize the release of stored carbon by reducing mortality, but also highlight the regional dependency of management-induced changes in resilience to climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

What drives forest carbon storage? The ramifications of source–sink decoupling

As the climate changes and scientists seek to project its future course, an important uncertainty lies in the response of forests. Will rising atmospheric carbon dioxide (CO 2 ) and lengthening growing seasons relieve limitations to tree growth, allowing increased carbon (C) sequestration in long-lived woody tissues and providing a negative feedback to climate change? Or will increasing heat and drought stress reduce growth and increase mortality, resulting in a positive feedback to climate change? Furthermore, to answer this question, global C cycle models simulate photosynthesis under future conditions, using simple plant C allocation schemes to estimate the amount of C sequestered in woody growth vs that allocated to short-lived pools that are more rapidly respired back to the atmosphere as CO 2 (Fatichi et al., 2014). However, there is growing evidence that these schemes are too simplistic, as wood production is frequently decoupled from photosynthesis (Delpierre et al., 2016a,b; Etzold et al., 2022), either through the passive limitation of woody tree growth by environmental conditions or active allocation prioritising other sinks. Needed, then, is an understanding of how woody growth is jointly shaped by photosynthesis (i.e. source limitation) and demand from various C sinks (i.e. sink limitation) across species and biomes (Körner, 2015). In this issue of New Phytologist, Martínez-Sancho et al. (2022; pp. 58–70) exemplifies the type of research needed to improve our ability to predict forest C sequestration under climate change, using an innovative approach to describe the seasonal course of C sequestration in tree stem growth and how it is affected by drought.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Machine learning of factors for improving oyster hatchery production

Oyster aquaculture and restoration in the Chesapeake Bay are vital, yet hatcheries frequently struggle with inconsistent larval growth and sudden mass mortality events. Unpredictable disruptions in larval production cause large economic losses, represent a perceived risk to growers, and impede industry expansion. To better understand associations between production yield and its potential predictors, we applied machine learning (random forest, and neural network) and statistical (generalized additive model) models to a comprehensive dataset of environmental, water quality, and operational parameters from a Maryland oyster hatchery, aiming to identify key yield predictors and develop a robust forecasting tool. We used recursive Boruta algorithm for variable selection, pinpointing critical predictors, and employed cross-validation to fine-tune model settings. Shapley value analysis offered crucial insights into model interpretations, highlighting week number, Normalized Difference Vegetation Index, salinity, turbidity, and fecundity as primary drivers of yield variability. For low-yield cases, salinity-related variables were particularly important. Our findings provide an early warning system for potential production downturns, empowering hatchery operators to make data-driven decisions for optimizing water conditions, feeding schedules, and broodstock management. By boosting predictability and efficiency, this research directly supports economic stability of the oyster industry and ecological health of the Chesapeake Bay.

Vishwakarma, Srishti [Oak Ridge National Laborator↗
DOE OSTI2022

Drivers and ecological impacts of a wildfire outbreak in the southern Appalachian Mountains after decades of fire exclusion

During one of the warmest and driest droughts of the last century, the southern Appalachian Mountains experienced a regional outbreak of over a dozen large wildfires in late fall of 2016. We provide a synthesis of long-term forest changes leading up to the 2016 wildfires, examine the climatic setting and patterns of burn severity in relationship to topography, and discuss the ecological and management implications of these and future fires. During the pre- and post-European settlement periods, frequent low- and mixed-severity wildfires interacted with complex topographic gradients and maintained heterogenous landscapes dominated by several species of oak (Quercus spp.), pine (Pinus spp.), and the American chestnut (Castanea dentata). Land-use changes associated with European settlement, loss of the American chestnut, and 20th century fire exclusion resulted in large scale shifts towards mesic, fire-intolerant species (i.e. mesophication). Wildfire activity began increasing in the early 1980s, but most fires in the region are small (<1,000 ha). In Fall of 2016, deciduous tree leaf fall occurred concurrently with a period of anomalously dry and warm weather, creating ideal conditions for fire ignition and spread. Thousands of ignitions across the region strained suppression resources and eight fires grew to greater than 5,000 ha. The 2016 fires were larger and burned more area than in the previous three decades combined. In one unique landscape setting, the Chimney Tops 2 Fire, a synoptic wind event drove extreme fire behavior and burned large, high-severity patches resulting in devastating effects in the wildland urban interface. However, immediate post-fire burn severity mosaics for other fires were composed primarily of low- (73 %) and moderate-severity (21 %) fire effects. High-severity fire comprised only 6 % of the area burned, and occurred mostly on steep upper slopes and ridges on south-facing aspects, reflecting the importance of bottom-up topographic drivers in this region. Although the fires will likely enhance biodiversity by restoring fire-dependent species and creating early seral habitat, invasions of non-native plant species, delayed mortality of mature pines and oaks, and rapid re-sprouting of pyrophyllic shrubs pose significant management challenges. Although similar large fire outbreaks may become more common under future climatic conditions, they are unlikely to reverse the effects of mesophication and significantly alter forest dynamics at broad spatial scales. Furthermore, the 2016 fires exposed the vulnerability of the region to wildfire during acute fall drought and demonstrate the potential ecological effects of future wildfires in mixed pine-hardwood landscapes of the southern Appalachians.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2021

Storm Surge and Ponding Explain Mangrove Dieback in Southwest Florida Following Hurricane Irma

Mangroves buffer inland ecosystems from hurricane winds and storm surge. However, their ability to withstand harsh cyclone conditions depends on plant resilience traits and geomorphology. Using airborne lidar and satellite imagery collected before and after Hurricane Irma, we estimated that 62% of mangroves in southwest Florida suffered canopy damage, with largest impacts in tall forests (>10 m). Mangroves on well-drained sites (83%) resprouted new leaves within one year after the storm. By contrast, in poorly-drained inland sites, we detected one of the largest mangrove diebacks on record (10,760 ha), triggered by Irma. We found evidence that the combination of low elevation (median = 9.4 cm asl), storm surge water levels (>1.4 m above the ground surface), and hydrologic isolation drove coastal forest vulnerability and were independent of tree height or wind exposure. Our results indicated that storm surge and ponding caused dieback, not wind. Tidal restoration and hydrologic management in these vulnerable, low-lying coastal areas can reduce mangrove mortality and improve resilience to future cyclones.

David Lagomasino↗
DOE OSTI2025

Hot Droughts and Forest Tree Dynamics in the Amazon - Statistical Models, Scripts, Data, and Outputs

This package contains data, outputs, equations, and R scripts for analyses for manuscript entitled "Hot droughts in the Amazon: A window to a future hypertropical climate" by J. Chambers et al., in particular it contains statistical models and analyses for the INPA BIONTE tree mortality study. The Models folder contains details for all statistical models in PDF files. The Scripts folder contains the R scripts for Bayesian Hierarchical Models (two text files) and SEMs (one text file) are separate and reasonably annotated. All data associated with these scripts are in the data folder. The Data folder contains two of the three CSV files used for the analyses and are called by the R scripts. Two of them are part of published datasets (`BIONTE_mortality-rates.csv` from Lima et al. 2024, DOI:10.15486/ngt/1898910 and `SPEI.csv` from Pastorello et al. 2023 DOI:10.15486/ngt/1958257) and also provided in this package for convenience (please see the corresponding datasets for usage and citation terms). The third dataset (`BIONTE_gapfilled_wd.csv`) contains sensitive information and can be obtained by contacting the manuscript lead author. The Outputs folder contains the two output files that provide extra information about the analyses. The file `figuresFeb2025d.pdf` contains all the figures from the manuscript - captions are in the manuscript. The file `ChambersMS.pdf` contains primary results from Bayesian statistical models, regression analyses, and validation steps applied to the tree mortality data from the INPA experiments. The document includes visual summaries, model diagnostics, and leave-one-out (LOO) validation results. A breakdown of file contents can be found in the README file that is part of this package.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2020

Cherokee Water Resources Project Summary - Mapping Forest Composition and Health in the Southern Appalachians Using NASA Earth Observations to Enhance Drought and Watershed Health-Related Forest Management for the Eastern Band of the Cherokee Indians

The Eastern Band of Cherokee Indians (EBCI) owns and manages more than 55,000 acres of land in the Southern Appalachian Mountains of western North Carolina. Most of these lands reside within the Oconaluftee River watershed. In this region and watershed, hemlock trees are a culturally significant foundation species that contribute to habitat biodiversity, regulate temperature and evapotranspiration of riparian environments, and provide economic value for tourism and recreation. The hemlock woolly adelgid (HWA), an invasive insect, has caused widespread hemlock mortality in recent decades, raising concerns about hemlock decline. Hemlock mortality leads to standing dead trees and increased evapotranspiration which can abet the spread of wildfires, especially during periods of drought. The DEVELOP team used satellite imagery from Landsat 5 Thematic Mapper (TM) to quantify and map possible hemlock decline by comparing changes in the normalized difference vegetation index (NDVI) values of winter season between 2003 and 2010. The project utilized the Shuttle Radar Topography Mission (SRTM) along with imagery from Landsat 8 Operational Land Imager (OLI) to create a weighted suitability analysis that maps topographic and environmental conditions favorable for hemlock habitat. This study found that 67%of evergreen and mixed forest cover in the Oconaluftee River valley exhibited a decrease in winter NDVI from 2003 to 2010. Additionally, the two-example weighted suitability analyses showed 4.5-9.5% of hemlock suitable land in 2018 in the Oconaluftee. The partners of this project can use the outputs to identify the extent of potential hemlock decline in the Oconaluftee and establish benchmark metrics for assessing changes in hemlock suitable areas over time.

DEVELOP Project Summary↗
NASA NTRS2020

Cherokee Water Resources - Mapping Hemlock Tree Composition and Health in the Southern Appalachians Using NASA Earth Observations to Enhance Drought and Watershed Health-Related Forest Management for the Eastern Band of the Cherokee Indians

The Eastern Band of Cherokee Indians (EBCI) owns and manages more than 55,000 acres of land in the Southern Appalachian Mountains of western North Carolina. Most of these lands reside within the Oconaluftee River watershed. In this region and watershed, hemlock trees are a culturally significant foundation species that contribute to habitat biodiversity, regulate temperature and evapotranspiration of riparian environments, and provide economic value for tourism and recreation. The hemlock woolly adelgid (HWA), an invasive insect, has caused widespread hemlock mortality in recent decades, raising concerns about hemlock decline. Hemlock mortality leads to standing dead trees and increased evapotranspiration which can abet the spread of wildfires, especially during periods of drought. The DEVELOP team used satellite imagery from Landsat 5 Thematic Mapper (TM) to quantify and map possible hemlock decline by comparing changes in the normalized difference vegetation index (NDVI) values of winter season between 2003 and 2010. The project utilized the Shuttle Radar Topography Mission (SRTM) along with imagery from Landsat 8 Operational Land Imager (OLI) to create a weighted suitability analysis that maps topographic and environmental conditions favorable for hemlock habitat. This study found that 67% of evergreen and mixed forest cover in the Oconaluftee River valley exhibited a decrease in winter NDVI from 2003 to 2010. Additionally, the two-example weighted suitability analyses showed 4.5-9.5% of hemlock suitable land in 2018 in the Oconaluftee. The partners of this project can use the outputs to identify the extent of potential hemlock decline in the Oconaluftee and establish benchmark metrics for assessing changes in hemlock suitable areas over time.

Richard Murray↗
NASA NTRS1972

Investigation of the detection and monitoring of forest insect infestations in the Sierra Nevada Mountains of California

The author has identified the following significant results. Due to the fact that all of the ERTS-1 imagery has not been received, evaluation of this imagery will be delayed until all of it is at hand. It has been determined that the arbitrary classification of tree mortality into dead, dying, and light damage is sound in that each class is significatly different in terms of number and volume of trees killed. It has likewise been determined that the different classes of defoliation of light, medium, and heavy are significantly different in terms of the needles per tip. It has been found that all classes of tree mortality and degrees of defoliation are readily and accurately identified from underflight photos in color and color IR in both scales of 1/5000 and 1/18,500. Evaluation of U-2 imagery is incomplete. It has been determined, however, that through the use of RC-10 color IR it is expected to be able to detect all three classes of tree mortality and probably at least two extreme levels of defoliation.

Hall, R. C.↗
NASA NTRS1973

Investigation of the detection and monitoring of forest insect infestation in the Sierra Nevada Mountains of California

The author has identified the following significant results. Significant progress has been made in detecting insect outbreaks from ERTS-1 data during this period. It is possible to differentiate forested areas with heavy damage from those with little or no damage. The analysis is made with color infrared positive transparencies and prints. Enlargement of the transparencies makes it possible to detect and map areas of three degrees of tree mortality into heavy, medium, and light. It was also noted that shadows cast by massive rock domes closely resemble natural lakes.

Hall, R. C.↗
NASA NTRS2014

Evaluating an Automated Approach for Monitoring Forest Disturbances in the Pacific Northwest from Logging, Fire and Insect Outbreaks with Landsat Time Series Data

Forests are the largest aboveground sink for atmospheric carbon (C), and understanding how they change through time is critical to reduce our C-cycle uncertainties. We investigated a strong decline in Normalized Difference Vegetation Index (NDVI) from 1982 to 1991 in Pacific Northwest forests, observed with the National Ocean and Atmospheric Administration's (NOAA) series of Advanced Very High Resolution Radiometers (AVHRRs). To understand the causal factors of this decline, we evaluated an automated classification method developed for Landsat time series stacks (LTSS) to map forest change. This method included: (1) multiple disturbance index thresholds; and (2) a spectral trajectory-based image analysis with multiple confidence thresholds. We produced 48 maps and verified their accuracy with air photos, monitoring trends in burn severity data and insect aerial detection survey data. Area-based accuracy estimates for change in forest cover resulted in producer's and user's accuracies of 0.21 +/- 0.06 to 0.38 +/- 0.05 for insect disturbance, 0.23 +/- 0.07 to 1 +/- 0 for burned area and 0.74 +/- 0.03 to 0.76 +/- 0.03 for logging. We believe that accuracy was low for insect disturbance because air photo reference data were temporally sparse, hence missing some outbreaks, and the annual anniversary time step is not dense enough to track defoliation and progressive stand mortality. Producer's and user's accuracy for burned area was low due to the temporally abrupt nature of fire and harvest with a similar response of spectral indices between the disturbance index and normalized burn ratio. We conclude that the spectral trajectory approach also captures multi-year stress that could be caused by climate, acid deposition, pathogens, partial harvest, thinning, etc. Our study focused on understanding the transferability of previously successful methods to new ecosystems and found that this automated method does not perform with the same accuracy in Pacific Northwest forests. Using a robust accuracy assessment, we demonstrate the difficulty of transferring change attribution methods to other ecosystems, which has implications for the development of automated detection/attribution approaches. Widespread disturbance was found within AVHRR-negative anomalies, but identifying causal factors in LTSS with adequate mapping accuracy for fire and insects proved to be elusive. Our results provide a background framework for future studies to improve methods for the accuracy assessment of automated LTSS classifications.

Landsat↗
DOE OSTI2020

Mechanistic and predictive understanding of needle litter decay in semi-arid mountain ecosystems experiencing unprecedented vegetation mortality. Final report

This research compared needle litter decay rates and underlying mechanisms between litter released from insect-killed trees to that of naturally senesced litter from healthy trees across climate variables with elevation and snowmelt rates as variables. Our research was designed to address questions of whether there is a significant impact to C and N cycling at the terrestrial-atmospheric interface in association with pine needle decomposition and the role of changes in soil moisture and temperature as a function of these processes. Field activities were primarily conducted within the Rocky Mountain Biological Laboratory’s (RMBL) East River watershed across a spectrum of ecoregions that spanned approximately 700 vertical meters. Forested catchments at these elevations in southwestern Colorado are threatened by heat-induced drought, altered snowmelt patterns, and invasive insect infestation that have all been associated with climate change. Needle litter from two members of the Pinaceae family experiencing large-scale insect infestations (spruce and lodgepole pine) were collected, redeployed and then sampled over the course of three years. We experimentally tested three tractable parameters that are known to impact litter decay and biogeochemical cycling and are relevant to bark beetle-induced tree mortality: (1) moisture content, (2) temperature by using elevation as a surrogate, and (3) changes to litter compositional chemistry that result from beetle infestation. We examined decay processes and monitored the migration of soluble and gaseous nitrogen and carbon species as well as microbiological signatures of decay such as biodegradable fractions, metal availability and the temporal succession of associated microorganisms at the terrestrial interface.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2021

Climate drives modeled forest carbon cycling resistance and resilience in the Upper Great Lakes Region, USA

Forests dominate the global terrestrial carbon budget, but their ability to continue doing so in the face of a changing climate is uncertain. A key uncertainty is how forests will respond to (resistance) and recover from (resilience) rising levels of disturbance of varying intensities. This knowledge gap can optimally be addressed by integrating manipulative field experiments with ecophysiological modeling. We used the Ecosystem Demography-2.2 (ED-2.2) model to project carbon fluxes for a northern temperate deciduous forest subjected to a real-world disturbance severity manipulation experiment. ED-2.2 was run for 150 years, starting from near bare ground in 1900 (approximating the clear-cut conditions at the time), and subjected to three disturbance treatments under an ensemble of climate conditions. Both disturbance severity and climate strongly affected carbon fluxes such as gross primary production (GPP), and interacted with one another. We then calculated resistance and resilience, two dimensions of ecosystem stability. Modeled GPP exhibited a two-fold decrease in mean resistance across disturbance severities of 45%, 65%, and 85% mortality; conversely, resilience increased by a factor of two with increasing disturbance severity. This pattern held for net primary production and net ecosystem production, indicating a trade-off in which greater initial declines were followed by faster recovery. Notably, however, heterotrophic respiration responded more slowly to disturbance, and its highly variable response was affected by different drivers. This work provides insight into how future conditions might affect the functional stability of mature forests in this region under ongoing climate change and changing disturbance regimes.

Kalyn Dorheim↗
NASA NTRS2021

Climate drives modeled forest carbon cycling resistance and resilience in the Upper Great Lakes Region, USA

Forests dominate the global terrestrial carbon budget, but their ability to continue doing so in the face of a changing climate is uncertain. A key uncertainty is how forests will respond to (resistance) and recover from (resilience) rising levels of disturbance of varying intensities. This knowledge gap can optimally be addressed by integrating manipulative field experiments with ecophysiological modeling. We used the Ecosystem Demography-2.2 (ED-2.2)model to project carbon fluxes for a northern temperate deciduous forest subjected to a real-world disturbance severity manipulation experiment. ED-2.2 was run for 150 years, starting from near bare ground in 1900(approximating the clear-cut conditions at the time),and subjected to three disturbance treatments under an ensemble of climate conditions. Both disturbance severity and climate strongly affected carbon fluxes such as gross primary production (GPP),and interacted with one another. We then calculated resistance and resilience, two dimensions of ecosystem stability. Modeled GPP exhibited a two-fold decrease in mean resistance across disturbance severities of 45%, 65%, and 85% mortality; conversely, resilience increased by a factor of two with increasing disturbance severity. This pattern held for net primary production and net ecosystem production, indicating a trade-off in which greater initial declines were followed by faster recovery. Notably, however, heterotrophic respiration responded more slowly to disturbance, and its highly variable response was affected by different drivers. This work provides insight into how future conditions might affect the functional stability of mature forests in this region under ongoing climate change and changing disturbance regimes.

Kalyn Dorheim↗