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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Hot droughts in the Amazon provide a window to a future hypertropical climate

Tropical forests represent the warmest and wettest of Earth’s biomes, but with continued anthropogenic warming, they will be pushed to climate states with no current analogue. Droughts in the tropics are already becoming more intense as they occur at successively higher temperatures. Here, in this study, we synthesize multiple datasets to assess the effects of hot droughts on a central Amazon forest. First, a more than 30-year record of annually resolved forest demographic data from a selective logging experiment showed higher tree mortality during intense droughts, particularly among fast-growing pioneer species with low wood density. Second, analysis of ecophysiological field measurements from the 2015 and 2023 El Niño droughts identified a soil moisture threshold beyond which transpiration rates rapidly declined. As rainless days beyond this threshold continued, drought conditions intensified, increasing the potential for tree mortality from hydraulic failure and carbon starvation. Third, analyses from the Coupled Model Intercomparison Project Phase 6 demonstrated that under high-emission scenarios, a large area of tropical forest will shift to a hotter ‘hypertropical’ climate by 2100. Last, under a hypertropical climate, temperature and moisture conditions during typical dry season months will more frequently exceed identified drought mortality thresholds, elevating the risk of forest dieback. Present-day hot droughts are harbingers of this emerging climate, offering a window for studying tropical forests under expected extreme future conditions.

drought↗
DOE OSTI2021

Predicting Intensive Care Unit Length of Stay and Mortality Using Patient Vital Signs: Machine Learning Model Development and Validation

Background: Patient monitoring is vital in all stages of care. In particular, intensive care unit (ICU) patient monitoring has the potential to reduce complications and morbidity, and to increase the quality of care by enabling hospitals to deliver higher-quality, cost-effective patient care, and improve the quality of medical services in the ICU. Objective: We here report the development and validation of ICU length of stay and mortality prediction models. The models will be used in an intelligent ICU patient monitoring module of an Intelligent Remote Patient Monitoring (IRPM) framework that monitors the health status of patients, and generates timely alerts, maneuver guidance, or reports when adverse medical conditions are predicted. Methods: We utilized the publicly available Medical Information Mart for Intensive Care (MIMIC) database to extract ICU stay data for adult patients to build two prediction models: one for mortality prediction and another for ICU length of stay. For the mortality model, we applied six commonly used machine learning (ML) binary classification algorithms for predicting the discharge status (survived or not). For the length of stay model, we applied the same six ML algorithms for binary classification using the median patient population ICU stay of 2.64 days. For the regression-based classification, we used two ML algorithms for predicting the number of days. We built two variations of each prediction model: one using 12 baseline demographic and vital sign features, and the other based on our proposed quantiles approach, in which we use 21 extra features engineered from the baseline vital sign features, including their modified means, standard deviations, and quantile percentages. Results: We could perform predictive modeling with minimal features while maintaining reasonable performance using the quantiles approach. The best accuracy achieved in the mortality model was approximately 89% using the random forest algorithm. The highest accuracy achieved in the length of stay model, based on the population median ICU stay (2.64 days), was approximately 65% using the random forest algorithm. Conclusions: The novelty in our approach is that we built models to predict ICU length of stay and mortality with reasonable accuracy based on a combination of ML and the quantiles approach that utilizes only vital signs available from the patient’s profile without the need to use any external features. This approach is based on feature engineering of the vital signs by including their modified means, standard deviations, and quantile percentages of the original features, which provided a richer dataset to achieve better predictive power in our models.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRSDate not supplied

Can We Model Forest Demography Globally? Benchmarking of State-of-the-Art Demographic DGVMs

Forests in Dynamic Global Vegetation Models (DGVMs) have historically been simulated as area-averaged plant functional types in each gridcell instead of representing communities of trees of different sizes and ages (demography). Just as the behaviour of a tree differs according to its ontogeny, so the behaviour of forests is known to differ depending on their demography. Accurately simulating demography is therefore key in order to address questions on afforestation and management strategies, as well as assessments of resilience of forests to disturbances such as drought and fire or diversity changes after a disturbance. Ultimately, demography determines the overall forest biomass in natural forests and is a key arbiter of growth and mortality rates. DGVMs are now able to simulate size and age structure of the trees in forests. However, these models have so far not been benchmarked alongside each other. We evaluate 6 DGVMs (BiomeE, CABLE-POP, FATES, LPJ-GUESS, JULES-RED, ORCHIDEE) against observations on regrowth dynamics as well as natural forests at boreal, temperate and tropical sites. We examine whether the models capture observed regrowth dynamics after disturbance, well-known stand size structure and well-established processes such as self-thinning. We outline the planned route forward towards a standardised international benchmarking framework for demographic DGVMs.

Dynamic Global Vegetation Models↗
DOE OSTI2023

Carbon stored in live ponderosa pines in the Sierra Nevada will not return to pre-drought (2012) levels during the 21st century due to bark beetle outbreaks

Outbreaks of several bark beetle species can develop rapidly in response to drought and may result in large transfers of carbon (C) stored in live trees to C stored in dead trees (10s of Tg C yr -1 in the western U.S. alone), which over time will be released back to the atmosphere. The western pine beetle (WPB) outbreak incited by the 2012–2015 mega-drought in the Sierra Nevada, California, U.S., could portend more frequent and/or severe bark beetle outbreaks as the temperature warms and drought frequency and intensity increase in the future. However, changes in the frequency and/or severity (resultant levels of host tree mortality) of beetle outbreaks are difficult to predict as outbreaks are complex with non-linear and eruptive processes primarily driven by interactions among beetle populations, the demography of hosts and other tree species, and climate and weather. Using an insect phenology and tree defense model, we projected the future likelihood of WPB outbreaks in the Sierra Nevada with climate drivers from different Earth System Models. Our goal was to understand how host (ponderosa pine, PIPO) recovery and future warming and drought affect the frequency and severity of WPB outbreaks and their C consequences. Our projections suggested that by 2100 the C stored in live PIPO (mean: 1.98 kg C m -2 , 95% CI: 1.74–2.21 kg C m -2 ) will not return to levels that occurred before the 2012–2015 drought (2012: ~2.30 kg C m –2 ) due to future WPB outbreaks. However, differences in climate models indicate a wide range of possible WPB outbreak frequencies and severities. Our results suggest that total plot basal area is the most significant factor in the mortality rate of PIPO by WPB in any given year, followed by drought severity and temperature. High levels of host basal area, higher temperature, and extreme drought all contribute to the frequency and severity of future WPB outbreaks. While PIPO basal area may decline under increased drought and warming, limiting high-stand basal area (>60 m 2 ha -1 ) may reduce the severity of future WPB outbreaks in the Sierra Nevada.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2015

The Legacy of Episodic Climatic Events in Shaping Temperate, Broadleaf Forests

In humid, broadleaf-dominated forests where gap dynamics and partial canopy mortality appears to dominate the disturbance regime at local scales, paleoecological evidence shows alteration at regional-scales associated with climatic change. Yet, little evidence of these broad-scale events exists in extant forests. To evaluate the potential for the occurrence of large-scale disturbance, we used 76 tree-ring collections spanning approx. 840 000 sq km and 5327 tree recruitment dates spanning approx. 1.4 million sq km across the humid eastern United States. Rotated principal component analysis indicated a common growth pattern of a simultaneous reduction in competition in 22 populations across 61 000 km2. Growth-release analysis of these populations reveals an intense and coherent canopy disturbance from 1775 to 1780, peaking in 1776. The resulting time series of canopy disturbance is so poorly described by a Gaussian distribution that it can be described as ''heavy tailed,'' with most of the years from 1775 to 1780 comprising the heavy-tail portion of the distribution. Historical documents provide no evidence that hurricanes or ice storms triggered the 1775-1780 event. Instead, we identify a significant relationship between prior drought and years with elevated rates of disturbance with an intense drought occurring from 1772 to 1775. We further find that years with high rates of canopy disturbance have a propensity to create larger canopy gaps indicating repeated opportunities for rapid change in species composition beyond the landscape scale. Evidence of elevated, regional-scale disturbance reveals how rare events can potentially alter system trajectory: a substantial portion of old-growth forests examined here originated or were substantially altered more than two centuries ago following events lasting just a few years. Our recruitment data, comprised of at least 21 species and several shade-intolerant species, document a pulse of tree recruitment at the subcontinental scale during the late-1600s suggesting that this event was severe enough to open large canopy gaps. These disturbances and their climatic drivers support the hypothesis that punctuated, episodic, climatic events impart a legacy in broadleaf-dominated forests centuries after their occurrence. Given projections of future drought, these results also reveal the potential for abrupt, meso- to large-scale forest change in broadleaf-dominated forests over future decades.

Climatology↗
NASA NTRS2016

Fir Decline and Mortality in the Southern Siberian Mountains

Increased dieback and mortality of dark needle conifer (DNC) stands (composed of fir (Abies sibirica),Siberian pine (Pinus sibirica) and spruce (Picea obovata)) were documented in Russia during recent decades. Here we analyzed spatial and temporal patterns of fir decline and mortality in the southern Siberian Mountains based on satellite, in situ and dendrochronological data. The studied stands are located within the boundary between DNC taiga to the north and forest-steppe to the south. Fir decline and mortality were observed to originate where topographic features contributed to maximal water-stress risk, i.e., steep (18 deg to 25 deg), convex, south-facing slopes with a shallow well-drained root zone. Fir regeneration survived droughts and increased stem radial growth, while upper canopy trees died. Tree ring width (TRW) growth negatively correlated with vapor pressure deficit (VPD), drought index and occurrence of late frosts, and positively with soil water content. Previous year growth conditions (i.e., drought index, VPD, soil water anomalies) have a high impact on current TRW (r = 0.60 to 0.74). Fir mortality was induced by increased water stress and severe droughts (as a primary factor) in synergy with bark-beetles and fungi attacks (as secondary factors). Dendrochronology data indicated that fir mortality is a periodic process. In a future climate with increased aridity and drought frequency, fir (and Siberian pine) may disappear from portions of its current range (primarily within the boundary with the forest- steppe) and is likely to be replaced by drought-tolerant species such as Pinus sylvestris and Larix sibirica.

conifer mortality↗
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.↗
NASA NTRS2016

Fir Decline and Mortality in the Southern Siberian Mountains

Increased dieback and mortality of dark needle conifer (DNC) stands (composed of fir (Abies sibirica),Siberian pine (Pinus sibirica) and spruce (Picea obovata))were documented in Russia during recent decades. Here we analyzed spatial and temporal patterns of fir decline and mortality in the southern Siberian Mountains based on satellite, in situ and dendrochronological data. The studied stands are located within the boundary between DNC taiga to the north and forest-steppe to the south. Fir decline and mortality were observed to originate where topographic features contributed to maximal water-stress risk, i.e., steep (1825),convex, south-facing slopes with a shallow well-drained root zone. Fir regeneration survived droughts and increased stem radial growth, while upper canopy trees died. Tree ring width(TRW) growth negatively correlated with vapor pressure deficit (VPD), drought index and occurrence of late frosts, and positively with soil water content. Previous year growth conditions (i.e., drought index, VPD, soil water anomalies)have a high impact on current TRW (r 0.600.74). Fir mortality was induced by increased water stress and severe droughts (as a primary factor) in synergy with bark-beetles and fungi attacks (as secondary factors). Dendrochronology data indicated that fir mortality is a periodic process. In a future climate with increased aridity and drought frequency, fir (and Siberian pine) may disappear from portions of its current range (primarily within the boundary with the forest steppe)and is likely to be replaced by drought-tolerant species such as Pinus sylvestris and Larix sibirica.

Kharuk, Viacheslav I.↗
NASA NTRS1972

Remote sensing applications to forest vegetation classification and conifer vigor loss due to dwarf mistletoe

Criteria was established for practical remote sensing of vegetation stress and mortality caused by dwarf mistletoe infections in black spruce subboreal forest stands. The project was accomplished in two stages: (1) A fixed tower-tramway site in an infected black spruce stand was used for periodic multispectral photo coverage to establish basic film/filter/scale/season/weather parameters; (2) The photographic combinations suggested by the tower-tramway tests were used in low, medium, and high altitude aerial photography.

Douglass, R. W.↗
DOE OSTI2024

Attributing human mortality from fire PM 2.5 to climate change

Climate change intensifies fire smoke, emitting hazardous air pollutants that impact human health. However, the global influence of climate change on fire-induced health impacts remains unquantified. Here, in this study, we used three well-tested fire-vegetation models in combination with a chemical transport model and health risk assessment framework to attribute global human mortality from fire fine particulate matter (PM 2.5 ) emissions to climate change. Of the 46401 (1960s) –to 98748 (2010s) annual fire PM 2.5 mortalities, 669 (1.2%, 1960s) –to 12566 (12.8%, 2010s) were attributed to climate change. The most substantial influence of climate change on fire mortality occurred in South America, Australia, and Europe, coinciding with decreased relative humidity, and in boreal forests with increased air temperature. Increasing relative humidity lowered fire mortality in other regions, like South Asia. Our study highlights the role of climate change in fire mortality, aiding public health authorities in spatial targeting adaptation measures for sensitive fire-prone areas.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Demography, dynamics and data: building confidence for simulating changes in the world's forests

Vegetation demographic models (VDMs) are advanced tools for simulating forest responses to climate and land-use changes, and are essential for projecting carbon cycling and large-scale forest management strategies. Despite their increasing incorporation into Earth System Models, VDMs differ in their demographic assumptions, with no prior quantitative comparison of their performance. We benchmarked nine VDMs against observational data from boreal, temperate and tropical sites, assessing their accuracy in predicting tree growth, carbon turnover, biomass stocks and size distributions. Models were simulated under consistent climate conditions with postdisturbance recovery monitored for at least 420 yr. Postdisturbance carbon recovery trajectories showed significant variability while remaining within observational ranges. Initial regrowth rates varied substantially (0.03-0.60, 0.18-0.70 and 0.35-1.10 kgCm-2 yr-1 for boreal, temperate and tropical sites, respectively), influenced by each model's initial forest state. Models captured mature forest carbon content but showed compensating effects between overestimated growth and underestimated mortality rates. This first multi-model benchmarking identifies growth and mortality rates as critical calibration targets and highlights the need to refine postdisturbance establishment conditions for model development. We outline specific benchmarking variables needed to improve predictions of forest responses to environmental change.

demographic vegetation model benchmarking↗
DOE OSTI2023

Salinity exposure affects lower-canopy specific leaf area of upland trees in a coastal deciduous forest

Sea level rise and increasing storm surges are likely to affect the canopy physiology, ecology, and structure of coastal forests, even well in advance of tree mortality. Laboratory and greenhouse studies have documented that saltwater exposure can trigger changes in leaf-level physiology and morphology, but few in situ studies have examined how tree-specific leaf area (SLA), the ratio of leaf area to mass and a crucial trait and model parameter, is affected by saline soils. We conducted an observational study of SLA in a mid-Atlantic (USA) coastal deciduous forest, taking advantage of a natural gradient in salinity along a tidal creek. Measured SLA of the 239 trees and seven species sampled ranged from Carya glabra (N = 6 trees, mean SLA = 277.9±36.3cm 2 /g) to Fagus grandifolia (N=60, 321.9±62.9cm 2 g); as expected, trees species and canopy position (sun versus shade) significantly affected SLA. For trees (N=100) directly exposed to the tidal creek, salinity was highly significant after accounting for species (P<0.001), with trees in the lower reaches of the creek having lower SLA. Leaf area index (LAI), computed from SLA and litter traps, ranged from 4.8 to 15.8 and was inversely related to salinity exposure; the spatial variability in leaf litter production contributed much more to LAI uncertainty than did SLA variability. These in situ results are correlative but consistent with the hypothesis, based on previous greenhouse studies, that the stress of chronic salinity exposure changes species’ leaf morphology. Our findings are useful for understanding the growing effects of saltwater intrusion into upland forests, as well as parameterizing and testing ecosystem-scale models simulating forest stressors and disturbances at the terrestrial-aquatic interface.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Basin-wide variation in tree hydraulic safety margins predicts the carbon balance of Amazon forests

Abstract Tropical forests face increasing climate risk 1,2 , yet our ability to predict their response to climate change is limited by poor understanding of their resistance to water stress. Although xylem embolism resistance thresholds (for example, $$\varPsi $$ Ψ 50 ) and hydraulic safety margins (for example, HSM 50 ) are important predictors of drought-induced mortality risk 3–5 , little is known about how these vary across Earth’s largest tropical forest. Here, we present a pan-Amazon, fully standardized hydraulic traits dataset and use it to assess regional variation in drought sensitivity and hydraulic trait ability to predict species distributions and long-term forest biomass accumulation. Parameters $$\varPsi $$ Ψ 50 and HSM 50 vary markedly across the Amazon and are related to average long-term rainfall characteristics. Both $$\varPsi $$ Ψ 50 and HSM 50 influence the biogeographical distribution of Amazon tree species. However, HSM 50 was the only significant predictor of observed decadal-scale changes in forest biomass. Old-growth forests with wide HSM 50 are gaining more biomass than are low HSM 50 forests. We propose that this may be associated with a growth–mortality trade-off whereby trees in forests consisting of fast-growing species take greater hydraulic risks and face greater mortality risk. Moreover, in regions of more pronounced climatic change, we find evidence that forests are losing biomass, suggesting that species in these regions may be operating beyond their hydraulic limits. Continued climate change is likely to further reduce HSM 50 in the Amazon 6,7 , with strong implications for the Amazon carbon sink.

Science & Technology - Other Topics↗
NASA NTRS2011

Contribution of Near Real Time MODIS-Based Forest Disturbance Detection Products to a National Forest Threat Early Warning System

This presentation discusses an effort to compute and post weekly MODIS forest change products for the conterminous US (CONUS), as part of national forest threat early warning system (EWS) known as the U.S. Forest Change Assessment Viewer (FCAV). The US Forest Service, NASA, USGS, and ORNL are working collaboratively to contribute weekly change products to this EWS. Large acreages of the nation's forests are being disturbed by a growing multitude of biotic and abiotic threats that can act either singularly or in combination. When common at regional scales, such disturbances can pose hazards and threats to floral and faunal bio-diversity, ecosystem sustainability, ecosystem services, and human settlements across the conterminous US. Regionally evident forest disturbances range from ephemeral periodic canopy defoliation to stand replacement mortality events due to insects, disease, fire, hurricanes, tornadoes, ice, hail, and drought. Mandated by the Healthy Forest Restoration Act of 2003, this forest threat EWS has been actively developed since 2006 and on-line since 2010. This FCAV system employs 250-meter MODIS NDVI-based forest change products as a key element of the system, providing regional and CONUS scale products in near real time every 8 days. Each forest change product in FCAV is based on current versus historical 24 day composite NDVI data gridded at 231.66 meter resolution. Current NDVI is derived from USGS eMODIS expedited products. MOD13 NDVI is used for constructing historical baselines. CONUS change products are computed for all forests as % change in the current versus historical NDVI. Change products are computed according to previous year, previous 3 years and previous 8 year historical baselines. The use of multiple baselines enables disturbance anomaly phenology to be more fully assessed. CONUS forest change products are posted each week on the FCAV, a web mapping service maintained by the National Environmental Modeling and Analysis Center. The FCAV EWS has been used to aid multiple Federal and State agency forest management activities, including aerial disturbance detection surveys, as well as rapid response preliminary assessments of timber loss due to tornadoes, regional drought studies, and fire damage assessments. The FCAV allows end-users to assess the context of apparent forest vegetation change with respect to ancillary data, such as land cover, topography, hydrology, climate variables, and administrative boundaries. Such change products are being evaluated through case studies involving comparison with higher spatial resolution satellite, aerial, and field data. The presentation will include multiple examples in which regionally evident forest disturbances were successfully detected and monitored with the MODIS-based change products, as part of the FCAV. FCAV's MODIS forest change products enable end-users (e.g., resource managers) to monitor forest hazards at regional scales throughout the year and across the nation.

Spruce, Joseph P.↗
NASA NTRS2009

Developing New Coastal Forest Restoration Products Based on Landsat, ASTER, and MODIS Data

This paper discusses an ongoing effort to develop new geospatial information products for aiding coastal forest restoration and conservation efforts in coastal Louisiana and Mississippi. This project employs Landsat, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data in conjunction with airborne elevation data to compute coastal forest cover type maps and change detection products. Improved forest mapping products are needed to aid coastal forest restoration and management efforts of State and Federal agencies in the Northern Gulf of Mexico (NGOM) region. In particular, such products may aid coastal forest land acquisition and conservation easement procurements. This region's forests are often disturbed and subjected to multiple biotic and abiotic threats, including subsidence, salt water intrusion, hurricanes, sea-level rise, insect-induced defoliation and mortality, altered hydrology, wildfire, and conversion to non-forest land use. In some cases, such forest disturbance has led to forest loss or loss of regeneration capacity. In response, a case study was conducted to assess and demonstrate the potential of satellite remote sensing products for improving forest type maps and for assessing forest change over the last 25 years. Change detection products are needed for assessing risks for specific priority coastal forest types, such as live oak and baldcypress-dominated forest. Preliminary results indicate Landsat time series data are capable of generating the needed forest type and change detection products. Useful classifications were obtained using 2 strategies: 1) general forest classification based on use of 3 seasons of Landsat data from the same year; and 2) classification of specific forest types of concern using a single date of Landsat data in which a given targeted type is spectrally distinct compared to adjacent forested cover. When available, ASTER data was useful as a complement to Landsat data. Elevation data helped to define areas in which targeted forest types occur, such as live oak forests on natural levees. MODIS Normalized Difference Vegetation Index time series data aided visual assessments of coastal forest damage and recovery from hurricanes. Landsat change detection products enabled change to be identified at the stand level and at 10- year intervals with the earliest date preceding available change detection products from the National Oceanic and Atmospheric Administration and from the U.S. Geological Survey. Additional work is being done in collaboration with State and Federal agency partners in a follow-on NASA ROSES project to refine and validate these new, promising products. The products from the ROSES project will be available for aiding NGOM coastal forest restoration and conservation.

Spruce, Joseph P.↗
NASA NTRS2017

Satellite Image Mapping of Tree Mortality in the Sierra Nevada Region of California from 2013 to 2016

Extreme drought from 2013 to 2015 has been linked to extensive tree dieback in the Sierra-Nevada region of California. Landsat satellite imagery was analysed for the region from Lake Tahoe to the southern Sequoia National Forest with the objective of understanding the patterns of tree mortality in the years of 2013 to 2015 and into the near-normal precipitation year of 2016. The main mapping results for Landsat moisture index differences from year-to-year showed that the highest coverage of tree dieback was located in the Sierra and Sequoia National Forests, at four to five times greater area each year than within any other National Park or National Forest unit. Since 2013, over 50% of the Sierra Nevada forest dieback area was detected in the mid elevation zone of 1000-2000 m. The total area of tree mortality in the lower elevation zone of 500-1000 m did not grow notably from 2015 to 2016. Within the largest California river drainages in the Sierra region, new tree mortality in 2015 was detected mainly below 1200 m elevation, whereas new tree mortality in 2016 was detected mainly at higher elevations, up to about 2200 m. In three out of the four years studied, results showed that about 60% of all new tree mortality areas were located on north-facing hill slopes.

Satellite↗
DOE OSTI2021

Adding Tree Rings to North America's National Forest Inventories: An Essential Tool to Guide Drawdown of Atmospheric CO 2

Tree-ring time series provide long-term, annually resolved information on the growth of trees. When sampled in a systematic context, tree-ring data can be scaled to estimate the forest carbon capture and storage of landscapes, biomes, and—ultimately—the globe. A systematic effort to sample tree rings in national forest inventories would yield unprecedented temporal and spatial resolution of forest carbon dynamics and help resolve key scientific uncertainties, which we highlight in terms of evidence for forest greening (enhanced growth) versus browning (reduced growth, increased mortality). We describe jump-starting a tree-ring collection across the continent of North America, given the commitments of Canada, the United States, and Mexico to visit forest inventory plots, along with existing legacy collections. Failing to do so would be a missed opportunity to help chart an evidence-based path toward meeting national commitments to reduce net greenhouse gas emissions, urgently needed for climate stabilization and repair.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2011

Fire Return Interval Within the Northern Boundary of the Larch Forest

Larch (Larix spp.) dominant forests compose a large proportion of the forests of Russia (i.e., about 40% of forested areas). These forests range from the Yenisei ridge on the west to the Pacific Ocean on the east, and from Lake Baikal on the south to the 73rd parallel in the north. Larch stands comprise the world s northern most forest at Ary-Mas (72 deg 28' N, 102 deg 15' E). Larch dominated forests occupy about 70% of the permafrost areas in Siberia. Larch forms high closure stands as well as open forests, and is found mainly over permafrost, where other tree species barely survive. Wildfires are typical for this territory with the majority occurring as ground fires due to low crown closure. Due to the thin active layer in permafrost soils and a dense lichen-moss cover, ground fires may cause stand mortality. The vast areas of larch-dominant forests is generally considered as a "carbon sink"; however, positive long-term temperature trends at higher latitudes are expected to result in an increase of fire frequency, and thus may convert this area to a source for greenhouse gases. There are recent observations regarding the increase of fire frequency within non-protected territories. Surprisingly, there are few publications on fire chronoseqences for the huge forested territory between the Ural Mountains and the Pacific Ocean. Also there is a general understanding that bimodal (late spring -- early summer and late summer-beginning of fall) fire seasonal distribution in the south becomes uni-modal (late spring -- early summer) in the north. The purpose of this study is to investigate the wildfire history at the northern edge of the zone of larch dominance.

Kharuk, V. I.↗