Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “vegetation”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Vegetation and location of water inflow affect evaporation in a subtropical wetland as indicated by the deuterium excess method: Evaporation Effects Indicated by Deuterium Excess Method

Evaporation represents a principal form of water loss from water bodies, but quantifying evaporation with transpiring vegetation is challenging, owing to the difficulties in disentangling evaporation from transpiration. As the two processes have different effects on water isotope signatures (i.e., oxygen and hydrogen stable isotope ratios expressed by δ 18 O and δ 2 H), we used both the δ 18 O and δ 2 H values of water samples to calculate their deuterium excess (d) values, which are proportionate to fraction of evaporation loss (E f ) of water being sampled. Comparing with a single isotope method, the d method holds the advantage that it does not require knowledge of the initial isotope ratios of source water. Limitations of the d method, for example, effects of prior-evaporation of water before entering water bodies, can be checked and corrected. The sampling locations throughout our study site differed in vegetation coverage, water depth, and distance to water inflow (or discharge gate of water inflow), which are three important factors in water management. This sampling design offered us a unique opportunity to quantify the influences of the above three factors on E f . We found the following: (1) There was a spatiotemporal pattern in δ 18 O distribution. (2) The E f was negatively related to the vegetation coverage, positively related to distance to the water source inflow but nonsignificantly related to water depth. Therefore, vegetation and distance to the water inflow are two important considerations for the control of evaporative water loss, and evaporation calculated by the d method can lead to more informed water management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Vegetation water sources in California's Sierra Nevada (USA) are young and change over time, a multi-isotope ( δ 18 O, δ 2 H, 3 H) tracer approach.

Sierra Nevada forests transpire a significant amount of California's water resources, sparking interest in applying forest management to improve California's water supply. Determining the source water of evapotranspiration enables forest managers to make informed decisions. To this end, a significant interest in critical zone science is to develop new methods to work across time scales to predict subsurface water storage and use. Here, forest vegetation accessed young water and switched sources depending on availability, suggesting that forest drought vulnerability may depend on the range of water sources available (rain, snowmelt and deeply stored water). This finding also suggests that changes in transpiration rates may have immediate effects on water sources in close proximity to vegetation, and delayed effects on storage and runoff. New δ 18 O, δ 2 H and 3 H data were used to track precipitation, runoff, evapotranspiration and storage through the critical zone seasonally, including seasons where evapotranspiration and snowmelt were in phase (winter snowmelt) and out of phase (seasonally dry summer). The main source of this headwater catchment's runoff is derived from its meadow saturated zone water, which was dominated by snowmelt. Water that originated as snowmelt contributed to transpiration, unless other sources, such as recent rain, became available. In cases where xylem δ 18 O and δ 2 H signatures matched those of deeper saturated zone water, 3 H data showed that xylem water was distinctly younger than the deep saturated zone water. During 2016, which experienced relatively normal snowpack in winter and seasonally dry summer conditions, mean summer saturated zone water and vegetation water were similar in δ 18 O, –12.4 ± 0.04 ‰ and – 12.5 ± 0.3 ‰, respectively, but were distinctly different in 3 H, 5.5 ± 0.2 pCi/L and 13.7 ± 1.1 pCi/L, respectively. While δ 18 O shows that vegetation and meadow saturated zone water have similar origins, 3 H shows they have dissimilar ages.

58 GEOSCIENCES↗
DOE OSTI2021

Is satellite Sun-Induced Chlorophyll Fluorescence more indicative than vegetation indices under drought condition?

Droughts represent one of the most severe abiotic stress factors that could result in great crop yield loss. Numerous vegetation indices have been proposed for monitoring the vegetation condition under stress and assessing drought impacts on yield loss. However, the understanding and comparison between traditional vegetation indices (VIs) and the newly emerging satellite Sun-Induced Chlorophyll Fluorescence (SIF) for monitoring vegetation condition is still limited especially under drought stress and at multiple spatial scales. In this study, the potential of satellite observation SIF for monitoring corn response to drought was investigated based on the 2012 drought in the US Corn Belt. The standardized precipitation evapotranspiration index (SPEI) was used here to quantify drought. We found that all SPEI were above –1, except for July (–1.27), August (–1.39) and September (–1.14) in 2012, indicating the severity of this drought. We examined the relationship between satellite measurements of SIF, SIF yield , VIs (e.g., NDVI and EVI) and SPEI. Results indicated that SIF yield was sensitive to drought and SIF captured the stress more accurately both at the regional and state scales for the US Corn Belt. Quantitatively, SIF yield had a high correlation with SPEI (r = 0.987, p < 0.05) over the entire Corn Belt, and it indicated losses in response to drought approximately one month earlier than SIF/NDVI/EVI. Furthermore, our results demonstrated that SIF could be trusted as an effective indicator to study the relationship between GPP (R 2 ≥ 0.8664, p < 0.01) under drought conditions across the Corn Belt. Finally, this study highlighted the advantage of using satellite SIF observations to monitor the drought stress on crop growth especially GPP at regional scale.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Vegetation-induced asymmetric diurnal land surface temperatures changes across global climate zones

Unprecedented global vegetation greening during past decades is well known to affect annual and seasonal land surface temperatures (LST). However, the impact of observed vegetation cover change on diurnal LST across global climatic zones is not well understood. In this study, using global climatic time-series datasets, we investigated the long-term growing season daytime and nighttime LST changes globally and explored associated dominant contributors including vegetation and climate factors including air temperature, precipitation, and solar radiation. Results revealed asymmetric growing season mean daytime and nighttime LST warming (0.16 °C/10a and 0.30 °C/10a, respectively) globally from 2003 to 2020, as a result, the diurnal LST range (DLSTR) declined at 0.14 °C/10a. The sensitivity analysis indicated the LST response to changes in LAI, precipitation, and SSRD mainly concentrated during daytime instead of nighttime, however, which showed comparable sensitivities for air temperature. Combining the sensitivities results and the observed LAI and climate trends, we found rising air temperature contributes to 0.24 ± 0.11 °C/10a global daytime LST warming and 0.16 ± 0.07 °C/10a nighttime LST warming, turns to be the dominant contributor to the LST changes. Increased LAI cooled global daytime LST (–0.068 ± 0.096 °C/10a) while warmed nighttime LST (0.064 ± 0.046 °C/10a); hence LAI dominates declines in DLSTR trends (–0.12 ± 0.08 °C/10a), despite some daynight process variations across climate zones. In Boreal regions, reduced DLSTR was due to nighttime warming from LAI increases. In other climatic zones, daytime cooling, and DLSTR decline, was induced by increased LAI. Biophysically, the pathway from air temperature heats the surface through sensible heat and increased downward longwave radiation during day and night, while the pathway from LAI cools the surface by enhancing energy redistribution into latent heat rather than sensible heat during the daytime. These empirical findings of diverse asymmetric responses could help calibrate and improve biophysical models of diurnal surface temperature feedback in response to vegetation cover changes in different climate zones.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Biohydrogen production from hyperthermophilic anaerobic digestion of fruit and vegetable wastes in seawater: Simplification of the culture medium of Thermotoga maritima

Highlights: • H2 production from fruit and vegetable wastes by T. maritima in seawater was studied. • The supply of seawater can replace some components necessary for T. maritima. • Using natural seawater medium recorded similar results to the mineral basal medium. • No H{sub 2} production by T. maritima in absence of nitrogen and sulfur sources. - Abstract: Biohydrogen production by the hyperthermophilic and halophilic bacterium T. maritima, using fruit and vegetable wastes as the carbon and energy sources was studied. Batch fermentation cultures showed that the use of a culture medium containing natural seawater and fruit and vegetable wastes can replace certain components (CaCl{sub 2}, MgCl{sub 2}, Balch's oligo-elements, yeast extract, KH{sub 2}PO{sub 4} and K{sub 2}HPO{sub 4}) present in basal medium. However, a source of nitrogen and sulfur remained necessary for biohydrogen production. When fruit and vegetable waste collected from a wholesale market landfill was used, no decreases in total H{sub 2} production (139 mmol L{sup −1}) or H{sub 2} yield (3.46 mol mol{sup −1}) was observed.

08 HYDROGEN↗
DOE OSTI2022

Bioprocessing, Recovery, and Mass Balance of Vegetative Lipids from Metabolically Engineered “Oilcane” Demonstrates Its Potential as an Alternative Feedstock for Drop-In Fuel Production

Plant oils are increasingly in demand as renewable feedstocks for biodiesel and biochemicals. Currently, oilseeds are the primary source of plant oils. Although the vegetative tissues of plants express lipid metabolism pathways, they do not hyper- accumulate lipids. Elevated synthesis, storage, and accumulation of lipids in vegetative tissues have been achieved by metabolic engineering of sugarcane to produce “oilcane”. This study evaluates the potential of oilcane as a renewable feedstock for the co- production of lipids and fermentable sugars. Oilcane was grown under favorable climatic and field conditions in Florida (FLOC) as well as during an abbreviated growing season, outside its typical growing region, in Illinois (ILOC). The potential lipid yield of 0.35 tons/ha was projected from the hyperaccumulation of fatty acids in the stored vegetative biomass of FLOC, which is approaching the lipid yield of soybean (0.44 tons/ha). Processing of the vegetative tissues of oilcane recovered 0.20 tons/ha, which represents the recovery of 55% of the total lipids from FLOC. Chemical-free hydrothermal bioprocessing of ILOC and FLOC bagasse and leaves at 180 °C for 10 min prevented the degeneration of in situ plant lipids. Here, this allowed the recovery of lipids at the end of the bioprocess with a major fraction of lipids remaining in the biomass residues after pretreatment and saccharification. Improvements through refined biomass processing, crop management, and metabolic engineering are expected to boost lipid yields and make oilcane a prime feedstock for the production of biodiesel.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Vegetation Functional Properties Determine Uncertainty of Simulated Ecosystem Productivity: A Traceability Analysis in the East Asian Monsoon Region

Global and regional projections of climate change by Earth system models are limited by their uncertain estimates of terrestrial ecosystem productivity. At the middle to low latitudes, the East Asian monsoon region has higher productivity than forests in Europe–Africa and North America, but its estimate by current generation of terrestrial biosphere models (TBMs) has seldom been systematically evaluated. Here, we developed a traceability framework to evaluate the simulated gross primary productivity (GPP) by 15 TBMs in the East Asian monsoon region. The framework links GPP to net primary productivity, biomass, leaf area and back to GPP via incorporating multiple vegetation functional properties of carbon–use efficiency (CUE), vegetation C turnover time ( τ veg ), leaf C fraction (F leaf ), specific leaf area (SLA), and leaf area index (LAI)–level photosynthesis (P LAI ), respectively. We then applied a relative importance algorithm to attribute intermodel variation at each node. The results showed that large intermodel variation in GPP over 1901–2010 were mainly propagated from their different representation of vegetation functional properties. For example, SLA explained 77% of the intermodel difference in leaf area, which contributed 90% to the simulated GPP differences. In addition, the models simulated higher CUE (18.1 ± 21.3%), τ veg (18.2 ± 26.9%), and SLA (27.4±36.5%) than observations, leading to the overestimation of simulated GPP across the East Asian monsoon region. Furthermore, these results suggest the large uncertainty of current TBMs in simulating GPP is largely propagated from their poor representation of the vegetation functional properties and call for a better understanding of the covariations between plant functional properties in terrestrial ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Metabolic engineering of sugarcane to accumulate energy-dense triacylglycerols in vegetative biomass

Elevating the lipid content in vegetative tissues has emerged as a new strategy for increasing energy density and biofuel yield of crops. Storage lipids in contrast to structural and signaling lipids are mainly composed of glycerol esters of fatty acids, also known as triacylglycerol (TAG). TAGs are one of the most energy-rich and abundant forms of reduced carbon available in nature. Therefore, altering the carbon-partitioning balance in favour of TAG in vegetative tissues of sugarcane, one of the highest yielding biomass crops, is expected to drastically increase energy yields. We report metabolic engineering to elevate TAG accumulation in vegetative tissues of sugarcane. Constitutive co-expression of WRINKLED1 (WRI1), diacylglycerol acyltransferase1-2 (DGAT1-2) and oleosin1 (OLE1) and simultaneous cosuppression of ADP-glucose pyrophosphorylase (AGPase) and a subunit of the peroxisomal ABC transporter1 (PXA1) in transgenic sugarcane elevated TAG accumulation in leaves or stems by 95- or 43-fold to 1.9% or 0.9% of dry weight (DW), respectively, while expression or suppression of one to three of the target genes increased TAG levels by 1.5- to 9.5-fold. Accumulation of TAG in vegetative progeny plants was consistent with the results from primary transgenics and contributed to a total fatty acid content of up to 4.7% or 1.7% of DW in mature leaves or stems, respectively. We saw lipid droplets in mesophyll cells of transgenic leaves by confocal fluorescence microscopy. These results provide the basis for optimizations of TAG accumulation in sugarcane and other high yielding biomass grasses and will open new prospects for biofuel applications.

09 BIOMASS FUELS↗
DOE OSTI2018

Validation of a Statistical Methodology for Extracting Vegetation Feedbacks: Focus on North African Ecosystems in the Community Earth System Model

Generalized equilibrium feedback assessment (GEFA) is a potentially valuable multivariate statistical tool for extracting vegetation feedbacks to the atmosphere in either observations or coupled Earth system models. The reliability of GEFA at capturing the terrestrial impacts on regional climate is demonstrated here using the National Center for Atmospheric Research Community Earth System Model (CESM), with focus on North Africa. The feedback is assessed statistically by applying GEFA to output from a fully coupled control run. To reduce the sampling error caused by short data records, the traditional or full GEFA is refined through stepwise GEFA by dropping unimportant forcings. Two ensembles of dynamical experiments are developed for the Sahel or West African monsoon region against which GEFA-based vegetation feedbacks are evaluated. In these dynamical experiments, regional leaf area index (LAI) is modified either alone or in conjunction with soil moisture, with the latter runs motivated by strong regional soil moisture–LAI coupling. Stepwise GEFA boasts higher consistency between statistically and dynamically assessed atmospheric responses to land surface anomalies than full GEFA, especially with short data records. GEFA-based atmospheric responses are more consistent with the coupled soil moisture–LAI experiments, indicating that GEFA is assessing the combined impacts of coupled vegetation and soil moisture. Both the statistical and dynamical assessments reveal a negative vegetation–rainfall feedback in the Sahel associated with an atmospheric stability mechanism in CESM versus a weaker positive feedback in the West African monsoon region associated with a moisture recycling mechanism in CESM.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Impact of Vegetation Assimilation on Flash Drought Characteristics across the Continental United States

Predicting and managing the impacts of flash droughts is difficult owing to their rapid onset and intensification. Flash drought monitoring often relies on assessing changes in root-zone soil moisture. However, the lack of widespread soil moisture measurements means that flash drought assessments often use process-based model data like that from the North American Land Data Assimilation System (NLDAS). Such reliance opens flash drought assessment to model biases, particularly from vegetation processes. Here, we examine the influence of vegetation on NLDAS-simulated flash drought characteristics by comparing two experiments covering 1981–2017: open loop (OL), which uses NLDAS surface meteorological forcing to drive a land surface model using prognostic vegetation, and data assimilation (DA), which instead assimilates near-real-time satellite-derived leaf area index (LAI) into the land surface model. The OL simulation consistently underestimates LAI across the United States, causing relatively high soil moisture values. Both experiments produce similar geographic patterns of flash droughts, but OL produces shorter duration events and regional trends in flash drought occurrence that are sometimes opposite to those in DA. Across the Midwest and Southern United States, flash droughts are 4 weeks (about 70%) longer on average in DA than OL. Moreover, across much of the Great Plains, flash drought occurrence has trended upward according to the DA experiment, opposite to the trend in OL. This sensitivity of flash drought to the representation of vegetation suggests that representing plants with greater fidelity could aid in monitoring flash droughts and improve the prediction of flash drought transitions to more persistent and damaging long-term droughts.

Drought↗
DOE OSTI2018

Vegetation and Wildlife Surveys at the National Renewable Energy Laboratory, National Wind Technology Center: July 2010-May 2011

This year-long wildlife and vegetation study was conducted to update the National Wind Technology Center (NWTC) vegetation and wildlife baseline conditions. These updated baseline conditions will be used to support future National Environmental Policy Act (NEPA) analyses. NWTC is a laboratory center of the National Renewable Energy Laboratory (NREL), a national laboratory of the U.S. Department of Energy (DOE), Office of Energy Efficiency and Renewable Energy, and operated by the Alliance for Sustainable Energy, LLC. The current effort involved conducting four seasons of vegetation and wildlife surveys beginning in July 2010 and ending in May 2011. This report presents the results of these surveys. Concurrent avian monitoring studies by Tetra Tech, Inc. were conducted beginning January 2010 to September 2011. The results of these surveys are presented in a separate report. Prior to the current study, Plantae (2000) completed a site characterization of vegetation communities and noxious weeds, Monahan (1996) conducted a raptor study, and Schmidt et al. (2003) conducted a bird and bat use and fatality study. More recently, Walsh conducted a bat study in 2010.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Vegetation and Wildlife Surveys at the National Renewable Energy Laboratory, South Table Mountain: June 2010-May 2011

This year-long wildlife and vegetation study was conducted by Walsh Environmental Scientists and Engineers, LLC (Walsh) to update previous vegetation and wildlife baseline reports for the South Table Mountain Site (STM). This baseline report will be used to support future National Environmental Policy Act (NEPA) analyses. STM is located on the southeastern corner of South Table Mountain in Jefferson County and is home to a laboratory center of the National Renewable Energy Laboratory (NREL), a national laboratory of the U.S. Department of Energy (DOE), Office of Energy Efficiency and Renewable Energy, and operated by the Alliance for Sustainable Energy, LLC. For the current effort, Walsh conducted four seasons of vegetation and wildlife surveys beginning in June, 2010 and ending in May, 2011. This report presents the results of these surveys. Prior to the current study, Plantae (2002) completed a site characterization of vegetation communities and noxious weeds, and FORUM (1987) and Science Applications International Corporation (SAIC 2005) conducted wildlife surveys including migratory birds and raptors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

SPRUCE S1 Bog Vegetation Allometric and Biomass Data: 2010-2011

This data set reports the results of measurements on sampled aboveground tissues of trees (Picea mariana and Larix laricina), shrubs (Ledum, Chamaedaphne, and Vaccinium), and ground layer vegetation (all species) of the S1 Bog located in areas adjacent to planned experimental study plots. Ground layer vegetation was sampled from both hummocks and hollows, within a 0.25 m2 plot, to evaluate total standing biomass of bog vegetation at or near the peak of annual production. Vegetation was harvested, processed, and measured in July of 2010 and again in June of 2011.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2013

Daily MODIS 500 m Reflectance Anisotropy Direct Broadcast (DB) Products for Monitoring Vegetation Phenology Dynamics

Land surface vegetation phenology is an efficient bio-indicator for monitoring ecosystem variation in response to changes in climatic factors. The primary objective of the current article is to examine the utility of the daily MODIS 500 m reflectance anisotropy direct broadcast (DB) product for monitoring the evolution of vegetation phenological trends over selected crop, orchard, and forest regions. Although numerous model-fitted satellite data have been widely used to assess the spatio-temporal distribution of land surface phenological patterns to understand phenological process and phenomena, current efforts to investigate the details of phenological trends, especially for natural phenological variations that occur on short time scales, are less well served by remote sensing challenges and lack of anisotropy correction in satellite data sources. The daily MODIS 500 m reflectance anisotropy product is employed to retrieve daily vegetation indices (VI) of a 1 year period for an almond orchard in California and for a winter wheat field in northeast China, as well as a 2 year period for a deciduous forest region in New Hampshire, USA. Compared with the ground records from these regions, the VI trajectories derived from the cloud-free and atmospherically corrected MODIS Nadir BRDF (bidirectional reflectance distribution function) adjusted reflectance (NBAR) capture not only the detailed footprint and principal attributes of the phenological events (such as flowering and blooming) but also the substantial inter-annual variability. This study demonstrates the utility of the daily 500 m MODIS reflectance anisotropy DB product to provide daily VI for monitoring and detecting changes of the natural vegetation phenology as exemplified by study regions comprising winter wheat, almond trees, and deciduous forest.

Vegetation↗
NASA NTRS2015

Estimation of Crop Gross Primary Production (GPP): Do Scaled (MODIS) Vegetation Indices Improve Performance? - 2

Satellite remote sensing estimates of Gross Primary Production (GPP) have routinely been made using spectral Vegetation Indices (VIs) over the past two decades. The Normalized Difference Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI), the green band Wide Dynamic Range Vegetation Index (WDRVIgreen), and the green band Chlorophyll Index (CIgreen) have been employed to estimate GPP under the assumption that GPP is proportional to the product of VI and photosynthetically active radiation (PAR) (where VI is one of four VIs: NDVI, EVI, WDRVIgreen, or CIgreen). However, the empirical regressions between VI*PAR and GPP measured locally at flux towers do not pass through the origin (i.e., the zero X-Y value for regressions). Therefore they are somewhat difficult to interpret and apply. This study investigates (1) what are the scaling factors and offsets (i.e., regression slopes and intercepts) between the fraction of PAR absorbed by chlorophyll of a canopy (fAPARchl) and the VIs, and (2) whether the scaled VIs developed in (1) can eliminate the deficiency and improve the accuracy of GPP estimates. Three AmeriFlux maize and soybean fields were selected for this study, two of which are irrigated and one is rainfed. The four VIs and fAPARchl of the fields were computed with the MODerate resolution Imaging Spectroradiometer (MODIS) satellite images. The GPP estimation performance for the scaled VIs was compared to results obtained with the original VIs and evaluated with standard statistics: the coefficient of determination (R2), the root mean square error (RMSE), and the coefficient of variation (CV). Overall, the scaled EVI obtained the best performance. The performance of the scaled NDVI, EVI and WDRVIgreen was improved across sites, crop types and soil/background wetness conditions. The scaled CIgreen did not improve results, compared to the original CIgreen. The scaled green band indices (WDRVIgreen, CIgreen) did not exhibit superior performance to either the scaled EVI or NDVI in estimating crop daily GPP at these agricultural fields. The scaled VIs are more physiologically meaningful than original un-scaled VIs, but scaling factors and offsets may vary across crop types and surface conditions.

Vegetation Index↗
NASA NTRS2016

Application of Satellite Solar-Induced Chlorophyll Fluorescence to Understanding Large-Scale Variations in Vegetation Phenology and Function Over Northern High Latitude Forests

This study evaluates the large-scale seasonal phenology and physiology of vegetation over northern high latitude forests (40 deg - 55 deg N) during spring and fall by using remote sensing of solar-induced chlorophyll fluorescence (SIF), normalized difference vegetation index (NDVI) and observation-based estimate of gross primary productivity (GPP) from 2009 to 2011. Based on GPP phenology estimation in GPP, the growing season determined by SIF time-series is shorter in length than the growing season length determined solely using NDVI. This is mainly due to the extended period of high NDVI values, as compared to SIF, by about 46 days (+/-11 days), indicating a large-scale seasonal decoupling of physiological activity and changes in greenness in the fall. In addition to phenological timing, mean seasonal NDVI and SIF have different responses to temperature changes throughout the growing season. We observed that both NDVI and SIF linearly increased with temperature increases throughout the spring. However, in the fall, although NDVI linearly responded to temperature increases, SIF and GPP did not linearly increase with temperature increases, implying a seasonal hysteresis of SIF and GPP in response to temperature changes across boreal ecosystems throughout their growing season. Seasonal hysteresis of vegetation at large-scales is consistent with the known phenomena that light limits boreal forest ecosystem productivity in the fall. Our results suggest that continuing measurements from satellite remote sensing of both SIF and NDVI can help to understand the differences between, and information carried by, seasonal variations vegetation structure and greenness and physiology at large-scales across the critical boreal regions.

Australia↗
NASA NTRS2021

Disentangling the Regional Climate Impacts of Competing Vegetation Responses to Elevated Atmospheric CO2

Biophysical vegetation responses to elevated atmospheric carbon dioxide (CO2) affect regional hydroclimate through two competing mechanisms. Higher CO2 increases leaf area (LAI), thereby increasing transpiration and water losses. Simultaneously, elevated CO2 reduces stomatal conductance and transpiration, thereby increasing rootzone soil moisture. Which mechanism dominates in the future is highly uncertain, partly because these two processes are difficult to explicitly separate within dynamic vegetation models. We address this challenge by using the GISS ModelE global climate model to conduct a novel set of idealized 2×CO2 sensitivity experiments to: evaluate the total vegetation biophysical contribution to regional climate change under high CO2; and quantify the separate contributions of enhanced LAI and reduced stomatal conductance to regional hydroclimate responses. We find that increased LAI exacerbates soil moisture deficits across the sub‐tropics and more water‐limited regions, but also attenuates warming by ∼0.5–1°C in the US Southwest, Central Asia, Southeast Asia, and northern South America. Reduced stomatal conductance effects contribute ∼1°C of summertime warming. For some regions, enhanced LAI and reduced stomatal conductance produce nonlinear and either competing or mutually amplifying hydroclimate responses. In northeastern Australia, these effects combine to exacerbate radiation‐forced warming and contribute to year‐round water limitation. Conversely, at higher latitudes these combined effects result in less warming than would otherwise be predicted due to nonlinear responses. These results highlight substantial regional variation in CO2‐driven vegetation responses and the importance of improving model representations of these processes to better quantify regional hydroclimate impacts.

Regional climate impacts↗
NASA NTRSDate not supplied

Vegetation Heights for Landsat Land Cover Classes in the Interior Boreal Forest Region of Alaska

Accurate determination and mapping of vegetation height is a prerequisite for regional estimations of above ground biomass, carbon pool dynamics, and improved modeling of future climate-vegetation-soil interactions. This study combined land cover class maps (at 30-m pixel resolution) derived from Landsat image bands with canopy vegetation heights detected at 1-m resolution from NASA G-LiHT Lidar flights, both from the year 2014 for the Middle Tanana Valley near Fairbanks, Alaska. The statistical distributions and structural attributes from Lidar plant heights were derived and refined for all Landsat vegetation classes. Results showed that the tallest cover classes in this region were deciduous forests (dominated by birch and aspen), followed by evergreen spruce and wooded wetlands. Open shrubland and herbaceous cover areas were determined to be 2 - 5 m shorter, on average, than these boreal forest stands. Tall shrubland cover areas were slightly shorter than most spruce-dominated evergreen forest areas. Nearly 60% of all low shrubland and herbaceous wetland pixels were detected with at least one tree crown greater than 10 m tall. This was in contrast to evergreen and deciduous forest classes that showed 88% of stands with at least one tree crown greater than 10 m tall.

Vegetation↗