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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.

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NASA NTRS2005

NASA Tech Briefs, January 2005

Topics covered include: Fiber-Optic Sensor Would Monitor Growth of Polymer Film; Sensors for Pointing Moving Instruments Toward Each Other; Pd/CeO2/SiC Chemical Sensors; Microparticle Flow Sensor; Scattering-Type Surface-Plasmon-Resonance Biosensors; Diode-Laser-Based Spectrometer for Sensing Gases; Improved Cathode Structure for a Direct Methanol Fuel Cell; X-Band, 17-Watt Solid-State Power Amplifier; Improved Anode for a Direct Methanol Fuel Cell; Tools for Designing and Analyzing Structures; Interactive Display of Scenes with Annotations; Solving Common Mathematical Problems; Tools for Basic Statistical Analysis; Program Calculates Forces in Bolted Structural Joints; Integrated Structural Analysis and Test Program; Molybdate Coatings for Protecting Aluminum Against Corrosion; Synthesizing Diamond from Liquid Feedstock; Modifying Silicates for Better Dispersion in Nanocomposites; Powder-Collection System for Ultrasonic/Sonic Drill/Corer; Semiautomated, Reproducible Batch Processing of Soy; Hydrogen Peroxide Enhances Removal of NOx from Flue Gases; Subsurface Ice Probe; Real-Time Simulation of Aeroheating of the Hyper-X Airplane; Using Laser-Induced Incandescence To Measure Soot in Exhaust; Method of Real-Time Principal-Component Analysis; Insect-Inspired Flight Control for Unmanned Aerial Vehicles; Domain Compilation for Embedded Real-Time Planning; Semantic Metrics for Analysis of Software; Simulation of Laser Cooling and Trapping in Engineering Applications; Large Fluvial Fans and Exploration for Hydrocarbons; Doping-Induced Interband Gain in InAs/AlSb Quantum Wells; Development of Software for a Lidar-Altimeter Processor; Upgrading the Space Shuttle Caution and Warning System; and Fractal Reference Signals in Pulse-Width Modulation.

Source record↗
NASA NTRS2011

Copolyimide Surface Modifying Agents for Particle Adhesion Mitigation

Marine biofouling, insect adhesion on aircraft surfaces, microbial contamination of sterile environments, and particle contamination all present unique challenges for which researchers have adopted an array of mitigation strategies. Particulate contamination is of interest to NASA regarding exploration of the Moon, Mars, asteroids, etc.1 Lunar dust compromised seals, clogged filters, abraded visors and space suit surfaces, and was a significant health concern during the Apollo missions.2 Consequently, NASA has instituted a multi-faceted approach to address dust including use of sacrificial surfaces, active mitigation requiring the use of an external energy source, and passive mitigation utilizing materials with an intrinsic resistance to surface contamination. One passive mitigation strategy is modification of a material s surface energy either chemically or topographically. The focus of this paper is the synthesis and evaluation of novel copolyimide materials with surface modifying agents (SMA, oxetanes) enabling controlled variation of surface chemical composition.

Wohl, Christopher J.↗
NASA NTRS2004

Real-Time Adaptive Color Segmentation by Neural Networks

Artificial neural networks that would utilize the cascade error projection (CEP) algorithm have been proposed as means of autonomous, real-time, adaptive color segmentation of images that change with time. In the original intended application, such a neural network would be used to analyze digitized color video images of terrain on a remote planet as viewed from an uninhabited spacecraft approaching the planet. During descent toward the surface of the planet, information on the segmentation of the images into differently colored areas would be updated adaptively in real time to capture changes in contrast, brightness, and resolution, all in an effort to identify a safe and scientifically productive landing site and provide control feedback to steer the spacecraft toward that site. Potential terrestrial applications include monitoring images of crops to detect insect invasions and monitoring of buildings and other facilities to detect intruders. The CEP algorithm is reliable and is well suited to implementation in very-large-scale integrated (VLSI) circuitry. It was chosen over other neural-network learning algorithms because it is better suited to realtime learning: It provides a self-evolving neural-network structure, requires fewer iterations to converge and is more tolerant to low resolution (that is, fewer bits) in the quantization of neural-network synaptic weights. Consequently, a CEP neural network learns relatively quickly, and the circuitry needed to implement it is relatively simple. Like other neural networks, a CEP neural network includes an input layer, hidden units, and output units (see figure). As in other neural networks, a CEP network is presented with a succession of input training patterns, giving rise to a set of outputs that are compared with the desired outputs. Also as in other neural networks, the synaptic weights are updated iteratively in an effort to bring the outputs closer to target values. A distinctive feature of the CEP neural network and algorithm is that each update of synaptic weights takes place in conjunction with the addition of another hidden unit, which then remains in place as still other hidden units are added on subsequent iterations. For a given training pattern, the synaptic weight between (1) the inputs and the previously added hidden units and (2) the newly added hidden unit is updated by an amount proportional to the partial derivative of a quadratic error function with respect to the synaptic weight. The synaptic weight between the newly added hidden unit and each output unit is given by a more complex function that involves the errors between the outputs and their target values, the transfer functions (hyperbolic tangents) of the neural units, and the derivatives of the transfer functions.

Duong, Tuan A.↗
NASA NTRS2011

Multi-Sensor Remote Sensing of Forest Dynamics in Central Siberia

The forested regions of Siberia, Russia are vast and contain about a quarter of the world's forests that have not experienced harvesting. However, many Siberian forests are facing twin pressures of rapidly changing climate and increasing timber harvest activity. Monitoring the dynamics and mapping the structural parameters of the forest is important for understanding the causes and consequences of changes observed in these areas. Because of the inaccessibility and large extent of this forest, remote sensing data can play an important role for observing forest state and change. In Central Siberia, multi-sensor remote sensing data have been used to monitor forest disturbances and to map above-ground biomass from the Sayan Mountains in the south to the taiga-tundra boundaries in the north. Radar images from the Shuttle Imaging Radar-C (SIR-C)/XSAR mission were used for forest biomass estimation in the Sayan Mountains. Radar images from the Japanese Earth Resources Satellite-1 (JERS-1), European Remote Sensing Satellite-1 (ERS-1) and Canada's RADARSAT-1, and data from ETM+ on-board Landsat-7 were used to characterize forest disturbances from logging, fire, and insect damage in Boguchany and Priangare areas.

Ransom, K. J.↗
NASA NTRS2012

A Project to Map and Monitor Baldcypress Forests in Coastal Louisiana, Using Landsat, MODIS, and ASTER Satellite Data

Cypress swamp forests of Louisiana offer many important ecological and economic benefits: wildlife habitat, forest products, storm buffers, water quality, and recreation. Such forests are also threatened by multiple factors: subsidence, salt water intrusion, sea level rise, persistent flooding, hydrologic modification, hurricanes, insect and nutria damage, timber harvesting, and land use conversion. Unfortunately, there are many information gaps regarding the type, location, extent, and condition of these forests. Better more up to date swamp forest mapping products are needed to aid coastal forest conservation and restoration work (e.g., through the Coastal Forest Conservation Initiative or CFCI). In response, a collaborative project was initiated to develop, test and demonstrate cypress swamp forest mapping products, using NASA supported Landsat, ASTER, and MODIS satellite data. Research Objectives are: Develop, test, and demonstrate use of Landsat and ASTER data for computing new cypress forest classification products and Landsat, ASTER, and MODIS satellite data for detecting and monitoring swamp forest change

Spruce, Joseph↗
NASA NTRS2012

Applying Biomimetic Algorithms for Extra-Terrestrial Habitat Generation

The objective is to simulate and optimize distributed cooperation among a network of robots tasked with cooperative excavation on an extra-terrestrial surface. Additionally to examine the concept of directed Emergence among a group of limited artificially intelligent agents. Emergence is the concept of achieving complex results from very simple rules or interactions. For example, in a termite mound each individual termite does not carry a blueprint of how to make their home in a global sense, but their interactions based strictly on local desires create a complex superstructure. Leveraging this Emergence concept applied to a simulation of cooperative agents (robots) will allow an examination of the success of non-directed group strategy achieving specific results. Specifically the simulation will be a testbed to evaluate population based robotic exploration and cooperative strategies while leveraging the evolutionary teamwork approach in the face of uncertainty about the environment and partial loss of sensors. Checking against a cost function and 'social' constraints will optimize cooperation when excavating a simulated tunnel. Agents will act locally with non-local results. The rules by which the simulated robots interact will be optimized to the simplest possible for the desired result, leveraging Emergence. Sensor malfunction and line of sight issues will be incorporated into the simulation. This approach falls under Swarm Robotics, a subset of robot control concerned with finding ways to control large groups of robots. Swarm Robotics often contains biologically inspired approaches, research comes from social insect observation but also data from among groups of herding, schooling, and flocking animals. Biomimetic algorithms applied to manned space exploration is the method under consideration for further study.

Birge, Brian↗
NASA NTRS2012

Humanlike Robots - Synthetically Mimicking Humans

Nature inspired many inventions and the field of technology that is based on the mimicking or inspiration of nature is widely known as Biomimetics and it is increasingly leading to many new capabilities. There are numerous examples of biomimetic successes including the copying of fins for swimming, and the inspiration of the insects and birds flight. More and more commercial implementations of biomimetics are appearing and behaving lifelike and applications are emerging that are important to our daily life. Making humanlike robots is the ultimate challenge to biomimetics and, for many years, it was considered science fiction, but such robots are becoming an engineering reality. Advances in producing such robot are allowing them to perform impressive functions and tasks. The development of such robots involves addressing many challenges and is raising concerns that are related to fear of their application implications and potential ethical issues. In this paper, the state-of-the-art of humanlike robots, potential applications and challenges will be reviewed.

sensors↗
NASA NTRS2013

United States Forest Disturbance Trends Observed Using Landsat Time Series

Disturbance events strongly affect the composition, structure, and function of forest ecosystems; however, existing U.S. land management inventories were not designed to monitor disturbance. To begin addressing this gap, the North American Forest Dynamics (NAFD) project has examined a geographic sample of 50 Landsat satellite image time series to assess trends in forest disturbance across the conterminous United States for 1985-2005. The geographic sample design used a probability-based scheme to encompass major forest types and maximize geographic dispersion. For each sample location disturbance was identified in the Landsat series using the Vegetation Change Tracker (VCT) algorithm. The NAFD analysis indicates that, on average, 2.77 Mha/yr of forests were disturbed annually, representing 1.09%/yr of US forestland. These satellite-based national disturbance rates estimates tend to be lower than those derived from land management inventories, reflecting both methodological and definitional differences. In particular the VCT approach used with a biennial time step has limited sensitivity to low-intensity disturbances. Unlike prior satellite studies, our biennial forest disturbance rates vary by nearly a factor of two between high and low years. High western US disturbance rates were associated with active fire years and insect activity, while variability in the east is more strongly related to harvest rates in managed forests. We note that generating a geographic sample based on representing forest type and variability may be problematic since the spatial pattern of disturbance does not necessarily correlate with forest type. We also find that the prevalence of diffuse, non-stand clearing disturbance in US forests makes the application of a biennial geographic sample problematic. Future satellite-based studies of disturbance at regional and national scales should focus on wall-to-wall analyses with annual time step for improved accuracy.

Masek, Jeffrey G.↗
NASA NTRS2013

Monitoring Regional Forest Disturbances across the US with near Real Time MODIS NDVI Products Resident to the ForWarn Forest Threat Early Warning System

Forest threats across the US have become increasingly evident in recent years. Sometimes these have resulted in regionally evident disturbance progressions (e.g., from drought, bark beetle outbreaks, and wildfires) that can occur across multiyear durations and have resulted in extensive forest overstory mortality. In addition to stand replacement disturbances, other forests are subject to ephemeral, sometimes yearly defoliation from various insects and varying types and intensities of ephemeral damage from storms. Sometimes, after prolonged severe disturbance, signs of recovery in terms of Normalized Difference Vegetation Index (NDVI) can occur. The growing prominence and threat of forest disturbances in part have led to the formation and implementation of the 2003 Healthy Forest Restoration Act which mandated that national forest threat early warning system be developed and deployed. In response, the US Forest Service collaborated with NASA, DOE Oakridge National Laboratory, and the USGS Eros Data Center to build and roll-out the near real time ForWarn early warning system for monitoring regionally evident forest disturbances. Given the diversity of disturbance types, severities, and durations, ForWarn employs multiple historical baselines that are used with current NDVI to derive a suite of six forest change products that are refreshed every 8 days. ForWarn employs daily quarter kilometer MODIS NDVI data from the Aqua and Terra satellites, including MOD13 data for deriving historical baseline NDVIs and eMODIS 7 NDVI for compiling current NDVI. In doing so, the Time Series Product Tool and the Phenological Parameters Estimation Tool are used to temporally de-noise, fuse, and aggregate current and historical MODIS NDVIs into 24 day composites refreshed every 8 days with 46 dates of products per year. The 24 day compositing interval enables disturbances to be detected, while minimizing the frequency of residual atmospheric contamination. Forest change products are computed versus the previous 1, previous 3, and all previous years in the MODIS record for a given 24 day interval. Other "weekly" forest change products include one computed using an adaptive length compositing method for quicker detection of disturbances, two others that adjust for seasonal fluctuations in normal vegetation phenology (e.g., early versus late springs). This overall approach enables forest disturbance dynamics from a variety of regionally evident biotic and abiotic forest disturbances to be viewed and assessed through the calendar year. The change products are also being utilized for forest change trend analysis and for developing regional forest overstory mortality products. ForWarn's forest change products are used to alert forest health specialists about new forest disturbances. Such alerts are also typically based on available Landsat, aerial, and ground data as well as communications with forest health specialists and previous experience. ForWarn products have been used to detect and track many types of regional disturbances to multiple forest types, including defoliation from caterpillars and severe storms, as well as mortality from both biotic and abiotic agents (e.g., bark beetles, drought, fire, anthropogenic clearing). ForWarn offers products that could be combined with other geospatial data on forest biomass to assess forest disturbance carbon impacts within the conterminous US.

Spruce, Joseph P.↗
NASA NTRS2014

Potential of Pest and Host Phenological Data in the Attribution of Regional Forest Disturbance Detection Maps According to Causal Agent

Near real time forest disturbance detection maps from MODIS NDVI phenology data have been produced since 2010 for the conterminous U.S., as part of the on-line ForWarn national forest threat early warning system. The latter has been used by the forest health community to identify and track many regional forest disturbances caused by multiple biotic and abiotic damage agents. Attribution of causal agents for detected disturbances has been a goal since project initiation in 2006. Combined with detailed cover type maps, geospatial pest phenology data offer a potential means for narrowing the candidate causal agents responsible for a given biotic disturbance. U.S. Aerial Detection Surveys (ADS) employ such phenology data. Historic ADS products provide general locational data on recent insect-induced forest type specific disturbances that may help in determining candidate causal agents for MODIS-based disturbance maps, especially when combined with other historic geospatial disturbance data (e.g., wildfire burn scars and drought maps). Historic ADS disturbance detection polygons can show severe and extensive regional forest disturbances, though they also can show polygons with sparsely scattered or infrequent disturbances. Examples will be discussed that use various historic disturbance data to help determine potential causes of MODIS-detected regional forest disturbance anomalies.

Spruce, Joseph↗
NASA NTRS2014

Potential for Expanding the Near Real Time ForWarn Regional Forest Monitoring System to Include Alaska

The on-line near real time (NRT) ForWarn system is currently deployed to monitor regional forest disturbances within the conterminous United States (CONUS), using daily MODIS Aqua and Terra NDVI data to derive monitoring products. The Healthy Forest Restoration Act of 2003 mandated such a system. Work on ForWarn began in 2006 with development and validation of retrospective MODIS NDVI-based forest monitoring products. Subsequently, NRT forest disturbance monitoring products were demonstrated, leading to the actual system deployment in 2010. ForWarn provides new CONUS forest disturbance monitoring products every 8 days, using USGS eMODIS data for current NDVI. ForWarn currently does not cover Alaska, which includes extensive forest lands at risk to multiple biotic and abiotic threats. This poster discusses a case study using Alaska eMODIS Terra data to derive ForWarn like forest change products during the 2010 growing season. The eMODIS system provides current MODIS Terra NDVI products for Alaska. Resulting forest change products were assessed with ground, aerial, and Landsat reference data. When cloud and snow free, these preliminary products appeared to capture regional forest disturbances from insect defoliation and fires; however, more work is needed to mitigate cloud and snow contamination, including integration of eMODIS Aqua data.

Spruce, Joseph P.↗
NASA NTRS2012

Correction Technique for Raman Water Vapor Lidar Signal-Dependent Bias and Suitability for Water Wapor Trend Monitoring in the Upper Troposphere

The MOHAVE-2009 campaign brought together diverse instrumentation for measuring atmospheric water vapor. We report on the participation of the ALVICE (Atmospheric Laboratory for Validation, Interagency Collaboration and Education) mobile laboratory in the MOHAVE-2009 campaign. In appendices we also report on the performance of the corrected Vaisala RS92 radiosonde measurements during the campaign, on a new radiosonde based calibration algorithm that reduces the influence of atmospheric variability on the derived calibration constant, and on other results of the ALVICE deployment. The MOHAVE-2009 campaign permitted the Raman lidar systems participating to discover and address measurement biases in the upper troposphere and lower stratosphere. The ALVICE lidar system was found to possess a wet bias which was attributed to fluorescence of insect material that was deposited on the telescope early in the mission. Other sources of wet biases are discussed and data from other Raman lidar systems are investigated, revealing that wet biases in upper tropospheric (UT) and lower stratospheric (LS) water vapor measurements appear to be quite common in Raman lidar systems. Lower stratospheric climatology of water vapor is investigated both as a means to check for the existence of these wet biases in Raman lidar data and as a source of correction for the bias. A correction technique is derived and applied to the ALVICE lidar water vapor profiles. Good agreement is found between corrected ALVICE lidar measurments and those of RS92, frost point hygrometer and total column water. The correction is offered as a general method to both quality control Raman water vapor lidar data and to correct those data that have signal-dependent bias. The influence of the correction is shown to be small at regions in the upper troposphere where recent work indicates detection of trends in atmospheric water vapor may be most robust. The correction shown here holds promise for permitting useful upper tropospheric water vapor profiles to be consistently measured by Raman lidar within NDACC (Network for the Detection of Atmospheric Composition Change) and elsewhere, despite the prevalence of instrumental and atmospheric effects that can contaminate the very low signal to noise measurements in the UT.

MOHAVE-2009↗
NASA NTRS2016

Nanotechnology: From Science Fiction to Reality

Nanotechnology promises unconventional solutions to challenging problems because of expectations that matter can be manipulated at the atomic scale to yield properties that exceed those predicted for bulk materials. The excitement at this possibility has been fueled by significant investments in this technology area. This talk will focus on three examples of where advances are being made to exploit unique properties made possible by nanoscale features for aerospace applications. The first two topics will involve the development of carbon nanotubes for (a) lightweight structural applications and (b) net shape fabricated multifunctional components. The third topic will highlight lessons learned from the demonstration of the effect of nanoengineered surfaces on insect residue adhesion. In all three cases, the approaches used to mature these emerging technologies are based on the acceleration of technology development through multidisciplinary collaborations.

Siochi, Mia↗
NASA NTRS2016

NASAs VESGEN: Systems Analysis of Vascular Phenotypes from Stress and Other Signaling Pathways Using GeneLab.

One fundamental requirement shared by humans with all higher terrestrial life forms, including insect wings, higher land plants and other vertebrates, is a complex, fractally branching vascular system. NASA's VESsel GENeration Analysis (VESGEN) software maps and quantifies vascular trees, networks, and tree-network composites according to weighted physiological rules such as vessel connectivity, tapering and bifurcational branching. According to fluid dynamics, successful vascular transport requires a complex distributed system of highly regulated laminar flow. Microvascular branching rules within vertebrates, dicot leaves and the other organisms therefore display many similarities. One unifying perspective is that vascular patterning offers a useful readout that necessarily integrates complex molecular signaling pathways. VESGEN has elucidated changes in vascular pattern resulting from inflammatory, stress response, developmental and other signaling within numerous tissues and major model organisms studied for Space Biology. For a new VESGEN systems approach, we analyzed differential gene expression in leaves of Arabidopsis thaliana reported by GeneLab (GLDS-7) for spaceflight. Vascular-related changes in leaf gene expression were identified that can potentially be phenocopied by mutants in ground-based experiments. To link transcriptional, protein and other molecular change with phenotype, alterations in the Euclidean and dynamic dimensions (x,y,t) of vascular patterns for Arabidopsis leaves and other model species are being co-localized with signaling patterns of single molecular expression analyzed as information dimensions (i,j,k,...). Previously, Drosophila microarray data returned from space suggested significant changes in genes related to wing venation development that include EGF, Notch, Hedghog, Wingless and Dpp signaling. Phenotypes of increasingly abnormal ectopic wing venation in the (non-spaceflight) Drosophila wing generated by overexpression of a Notch antagonist were analyzed by VESGEN. Other VESGEN research applications include the mouse retina, GI and coronary vessels, avian placental analogs and translational studies in the astronaut retina related to health challenges for long-duration missions.

Venation↗
NASA NTRS2016

Using NASA's GeneLab for VESGEN Systems Analysis of Vascular Phenotypes from Stress and Other Signaling Pathways

One fundamental requirement shared by humans with all higher terrestrial life forms, including other vertebrates, insects, and higher land plants, is a complex, fractally branching vascular system. NASA's VESsel GENeration Analysis (VESGEN) software maps and quantifies vascular trees, networks, and tree-network composites according to weighted physiological rules such as vessel connectivity, tapering and bifurcational branching. According to fluid dynamics, successful vascular transport requires a complex distributed system of highly regulated laminar flow. Microvascular branching rules within vertebrates, dicot leaves and the other organisms therefore display many similarities. A unifying perspective is that vascular patterning offers a useful readout of molecular signaling that necessarily integrates these complex pathways. VESGEN has elucidated changes in vascular pattern resulting from inflammatory, developmental and other signaling within numerous tissues and major model organisms studied for Space Biology. For a new VESGEN systems approach, we analyzed differential gene expression in leaves of Arabidopsis thaliana reported by GeneLab (GLDS-7) for spaceflight. Vascularrelated changes in leaf gene expression were identified that can potentially be phenocopied by mutants in ground-based experiments. To link transcriptional, protein and other molecular change with phenotype, alterations in the spatial and dynamic dimensions of vascular patterns for Arabidopsis leaves and other model species are being co-localized with signaling patterns of single molecular expression analyzed as information dimensions. Previously, Drosophila microarray data returned from space suggested significant changes in genes related to wing venation development that include EGF, Notch, Hedghog, Wingless and Dpp signaling. Phenotypes of increasingly abnormal ectopic wing venation in the (non-spaceflight) Drosophila wing generated by overexpression of a Notch antagonist were analyzed by VESGEN. Other VESGEN research applications include the mouse retina, GI and coronary vessels, avian placental analogs and translational studies in the astronaut retina related to health challenges for long-duration missions.

Venation↗
NASA NTRS2016

Climate-Induced Mortality of Siberian Pine and Fir in the Lake Baikal Watershed, Siberia

Siberian pine (Pinus sibirica) and fir (Abies sibirica) (so called ''dark needle conifers", DNC) showed decreased radial growth increment within the Lake Baikal watershed since the 1980s with increasing mortality recorded since the year 2000. Tree ring width was strongly correlated with vapor pressure deficit, aridity and root zone moisture. Water stress from droughts made trees more susceptible to insect attacks causing mortality in about 10% of DNC stands within the Lake Baikal watershed. Within Siberia DNC mortality increased in the southern part of the DNC range. Biogeographically, tree mortality was located within the DNC - forest-steppes transition. Tree mortality was significantly correlated with drought and soil moisture anomalies. Within the interior of the DNC range mortality occurred within relief features with high water stress risk (i.e., steep convex south facing slopes with shallow well-drained soils). In general, DNC mortality in Siberia was induced by increased aridity and severe drought (inciting factors) in synergy with biotic attacks (contributing factor). In future climate scenarios with predicted increase in aridity DNC could be eliminated from the southern part of its current range and will be replaced by drought-resistant conifers and broadleaf species (e.g., Larix sibirica, Pinus silvestris, and Betula pubescence).

Conifer Mortality↗
NASA NTRS2016

Climate-Induced Mortality of Siberian Pine and Fir in the Lake Baikal Watershed, Siberia

Siberian pine (Pinus sibirica) and fir (Abies sibirica) (so called "dark needle conifers", DNC) showed decreased radial growth increment within the Lake Baikal watershed since the 1980s with increasing mortality recorded since the year 2000. Tree ring width was strongly correlated with vapor pressure deficit, aridity and root zone moisture. Water stress from droughts made trees more susceptible to insect attacks causing mortality in about 10% of DNC stands within the Lake Baikal watershed. Within Siberia DNC mortality increased in the southern part of the DNC range. Biogeographically, tree mortality was located within the DNC - forest-steppes transition. Tree mortality was significantly correlated with drought and soil moisture anomalies. Within the interior of the DNC range mortality occurred within relief features with high water stress risk (i.e., steep convex south facing slopes with shallow well-drained soils). In general, DNC mortality in Siberia was induced by increased aridity and severe drought (inciting factors) in synergy with biotic attacks (contributing factor). In future climate scenarios with predicted increase in aridity DNC could be eliminated from the southern part of its current range and will be replaced by drought-resistant conifers and broadleaf species (e.g., Larix sibirica, Pinus silvestris, and Betula pubescence).

Viacheslav I Kharuk↗
NASA NTRS2015

Forest Disturbance Across the Conterminous United States from 1985-2012: The Emerging Dominance of Forest Decline

Evidence of shifting dominance among major forest disturbance agent classes regionally to globally has been emerging in the literature. For example, climate-related stress and secondary stressors on forests (e.g., insect and disease, fire) have dramatically increased since the turn of the century globally, while harvest rates in the western US and elsewhere have declined. For shifts to be quantified, accurate historical forest disturbance estimates are required as a baseline for examining current trends. We report annual disturbance rates (with uncertainties) in the aggregate and by major change causal agent class for the conterminous US and five geographic subregions between 1985 and 2012. Results are based on human interpretations of Landsat time series from a probability sample of 7200 plots (30 m) distributed throughout the study area. Forest disturbance information was recorded with a Landsat time series visualization and data collection tool that incorporates ancillary high-resolution data. National rates of disturbance varied between 1.5% and 4.5% of forest area per year, with trends being strongly affected by shifting dominance among specific disturbance agent influences at the regional scale. Throughout the time series, national harvest disturbance rates varied between one and two percent, and were largely a function of harvest in the more heavily forested regions of the US (Mountain West, Northeast, and Southeast). During the first part of the time series, national disturbance rates largely reflected trends in harvest disturbance. Beginning in the mid-90s, forest decline-related disturbances associated with diminishing forest health (e.g., physiological stress leading to tree canopy cover loss, increases in tree mortality above background levels), especially in the Mountain West and Lowland West regions of the US, increased dramatically. Consequently, national disturbance rates greatly increased by 2000, and remained high for much of the decade. Decline-related disturbance rates reached as high as 8% per year in the western regions during the early-2000s. Although low compared to harvest and decline, fire disturbance rates also increased in the early- to mid-2000s. We segmented annual decline-related disturbance rates to distinguish between newly impacted areas and areas undergoing gradual but consistent decline over multiple years. We also translated Landsat reflectance change into tree canopy cover change information for greater relevance to ecosystem modelers and forest managers, who can derive better understanding of forest-climate interactions and better adapt management strategies to changing climate regimes. Similar studies could be carried out for other countries where there are sufficient Landsat data and historic temporal snapshots of high-resolution imagery.

Cohen, Warren B.↗