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At least 433 records · Page 24

Soil evaporation and organic matter turnover in the Sub-Taiga and Forest-Steppe of southwest Siberia

Southwest Siberia encompasses the forest-steppe and sub-taiga climatic zones and has historically been utilized for agriculture. Coinciding with predicted changes in climate for the region is the pressure of agricultural development; however, a characterization of the soil water and carbon dynamics is lacking. We assessed current soil water properties and soil organic carbon turnover in forests and grasslands for two sites that span the forest steppe and sub-taiga bioclimatic zones. Soil evaporation was 0.62±0.17mm d-1 (mean±standard error) in grasslands and 0.45±0.08mm d-1 in the forests of the forest-steppe site. Evaporation at the sub-taiga site was 1.80±1.70mm d-1 in grasslands and 0.96±0.05mm d-1 in forest plots. Evaporation was significantly greater at the sub-taiga site than the forest-steppe site. The density of fine roots explained the soil water isotopic patterns between vegetation types and sites. We found soil organic matter turnover to be three times faster in the sub-taiga site than in the forest-steppe site. Our results show that while climate factors, in particular snow levels, between the two sites are drivers for water and carbon cycles, site level hydrology, soil characteristics, and vegetation directly interact to influence the water and carbon dynamics.

54 ENVIRONMENTAL SCIENCES↗

Estimating the influence of field inventory sampling intensity on forest landscape model performance for determining high-severity wildfire risk

Abstract Historically, fire has been essential in Southwestern US forests. However, a century of fire-exclusion and changing climate created forests which are more susceptible to uncharacteristically severe wildfires. Forest managers use a combination of thinning and prescribed burning to reduce forest density to help mitigate the risk of high-severity fires. These treatments are laborious and expensive, therefore optimizing their impact is crucial. Landscape simulation models can be useful in identifying high risk areas and assessing treatment effects, but uncertainties in these models can limit their utility in decision making. In this study we examined underlying uncertainties in the initial vegetation layer by leveraging a previous study from the Santa Fe fireshed and using new inventory plots from 111 stands to interpolate the initial forest conditions. We found that more inventory plots resulted in a different geographic distribution and wider range of the modelled biomass. This changed the location of areas with high probability of high-severity fires, shifting the optimal location for management. The increased range of biomass variability from using a larger number of plots to interpolate the initial vegetation layer also influenced ecosystem carbon dynamics, resulting in simulated forest conditions that had higher rates of carbon uptake. We conclude that the initial forest layer significantly affects fire and carbon dynamics and is dependent on both number of plots, and sufficient representation of the range of forest types and biomass density.

Science & Technology - Other Topics↗

Vulnerability of Amazon forests to storm-driven tree mortality

Tree mortality is a key driver of forest community composition and carbon dynamics. Strong winds associated with severe convective storms are dominant natural drivers of tree mortality in the Amazon. Why forests vary with respect to their vulnerability to wind events and how the predicted increase in storm events might affect forest ecosystems within the Amazon are not well understood. We found that windthrows are common in the Amazon region extending from northwest (Peru, Colombia, Venezuela, and west Brazil) to central Brazil, with the highest occurrence of windthrows in the northwest Amazon. More frequent winds, produced by more frequent severe convective systems, in combination with well-known processes that limit the anchoring of trees in the soil, help to explain the higher vulnerability of the northwest Amazon forests to winds. Projected increases in the frequency and intensity of convective storms in the Amazon have the potential to increase wind-related tree mortality. A forest demographic model calibrated for the northwestern and the central Amazon showed that northwestern forests are more resilient to increased wind-related tree mortality than forests in the central Amazon. Our study emphasizes the importance of including wind-related tree mortality in model simulations for reliable predictions of the future of tropical forests and their effects on the Earth' system.

54 ENVIRONMENTAL SCIENCES↗

Effects of topography on tropical forest structure depend on climate context

Abstract Topography affects abiotic conditions which can influence the structure, function and dynamics of ecological communities. An increasing number of studies have demonstrated biological consequences of fine‐scale topographic heterogeneity but we have a limited understanding of how these effects depend on the climate context. We merged high‐resolution (1 m 2 ) data on topography and canopy height derived from airborne lidar with ground‐based data from 15 forest plots in Puerto Rico distributed along a precipitation gradient spanning c . 800–3,500 mm/year. Ground‐based data included species composition, estimated above‐ground biomass (AGB), and two key functional traits (wood density and leaf mass per area, LMA) that reflect resource‐use strategies and a trade‐off between hydraulic safety and hydraulic efficiency. We used hierarchical Bayesian models to evaluate how the interaction between topography × climate is related to metrics of forest structure (i.e. canopy height and AGB), as well as taxonomic and functional alpha‐ and beta‐diversity. Fine‐scale topography (characterized with the topographic wetness index, TWI) significantly affected forest structure and the strength (and in some cases direction) of these effects varied across the precipitation gradient. In all plots, canopy height increased with topographic wetness but the effect was much stronger in dry compared to wet forest plots. In dry forest plots, topographically wetter microsites also had higher levels of AGB but in wet forest plots, topographically drier microsites had higher AGB. Fine‐scale topography influenced functional composition but had only weak or non‐significant effects on taxonomic and functional alpha‐ and beta‐diversity. For instance, community‐weighted wood density followed a similar pattern to AGB across plots. We also found a marginally significant association between variation of wood density and topographic heterogeneity that depended on climate context. Synthesis . The effects of fine‐scale topographic heterogeneity on tropical forest structure and composition depend on the climate context. Our study demonstrates how a stronger integration of topographic heterogeneity across precipitation gradients could improve estimates of forest structure and biomass, and may provide insight to the ways that topography might mediate species responses to drought and climate change.

Muscarella, Robert↗

Landscape‐scale lidar analysis of aboveground biomass distribution in secondary Brazilian Atlantic Forest

Abstract Secondary forests account for more than half of tropical forests and represent a growing carbon sink, but rates of biomass accumulation vary by a factor of two or more even among plots in the same landscape. To better understand the drivers of this variability, we used airborne lidar to measure forest canopy height and estimate biomass over 4529 ha at Serra do Conduru Park in Southern Bahia, Brazil. We measured trees in 30 georeferenced field plots (0.25‐ha each) to estimate biomass using allometry. Then we estimated aboveground biomass density ( ABD ) across the lidar study area using a statistical model developed from our field plots. This model related the 95th percentile of the distribution of lidar return heights to ABD . We overlaid this map of ABD on a Landsat‐derived forest age map to determine rates of biomass accumulation. We found rapid initial biomass regeneration (~6 Mg/ha yr), which slowed as forests aged. We also observed high variability in both height and biomass across the landscape within forests of similar age. Nevertheless, a regression model that accounted for spatial autocorrelation and included forest age, slope, and distance to roads or open areas explained 62 and 77 percent of the landscape variation in ABD and canopy height, respectively. Thus, while there is high spatial heterogeneity in forest recovery, and the drivers of this heterogeneity warrant further investigation, we suggest that a relatively simple set of predictor variables is sufficient to explain the majority of variance in both height and ABD in this landscape.

Becknell, Justin M.↗

CTFS-ForestGEO: a worldwide network monitoring forests in an era of global change

Global change is impacting forests worldwide, threatening biodiversity and ecosystem services, including climate regulation. Understanding how forests respond is critical to forest conservation and climate protection. This review describes an international network of 59 long-term forest dynamic research sites useful for characterizing forest responses to global change. The broad suite of measurements made at the CTFS-ForestGEO sites make it possible to investigate the complex ways in which global change is impacting forest dynamics. ongoing research across the network is yielding insights into how and why the forests are changing, and continued monitoring will provide vital contributions to understanding worldwide forest diversity and dynamics in a era of global change

54 ENVIRONMENTAL SCIENCES↗

Forest carbon sequestration on the west coast, USA: Role of species, productivity, and stockability

Forest ecosystems store large amounts of carbon and can be important sources, or sinks, of the atmospheric carbon dioxide that is contributing to global warming. Understanding the carbon storage potential of different forests and their response to management and disturbance events are fundamental to developing policies and scenarios to partially offset greenhouse gas emissions. Projections of live tree carbon accumulation are handled differently in different models, with inconsistent results. We developed growth-and-yield style models to predict stand-level live tree carbon density as a function of stand age in all vegetation types of the coastal Pacific region, US (California, Oregon, and Washington), from 7,523 national forest inventory plots. We incorporated site productivity and stockability within the Chapman-Richards equation and tested whether intensively managed private forests behaved differently from less managed public forests. We found that the best models incorporated stockability in the equation term controlling stand carrying capacity, and site productivity in the equation terms controlling the growth rate and shape of the curve. RMSEs ranged from 10 to 137 Mg C/ha for different vegetation types. There was not a significant effect of ownership over the standard industrial rotation length (~50 yrs) for the productive Douglas-fir/western hemlock zone, indicating that differences in stockability and productivity captured much of the variation attributed to management intensity. Our models suggest that doubling the rotation length on these intensively managed lands from 35 to 70 years would result in 2.35 times more live tree carbon stored on the landscape. These findings are at odds with some studies that have projected higher carbon densities with stand age for the same vegetation types, and have not found an increase in yields (on an annual basis) with longer rotations. We suspect that differences are primarily due to the application of yield curves developed from fully-stocked, undisturbed, single-species, “normal” stands without accounting for the substantial proportion of forests that don’t meet those assumptions. The carbon accumulation curves developed here can be applied directly in growth-and-yield style projection models, and used to validate the predictions of ecophysiological, cohort, or single-tree style models being used to project carbon futures for forests in the region. Our approach may prove useful for developing robust models in other forest types.

Chisholm, Paul J. (ORCID:0000000238784707)↗

Prospects for silvicultural enhancement of fire resistance in mesic westside forests of the Pacific Northwest

Increasing wildfire activity in mesic, temperate Pacific Northwest forests west of the Cascade Range crest has stimulated interest in understanding whether alternative forest management practices could reduce risk of stand-replacing fire. To explore how management can enhance fire resistance in these forests and assess tradeoffs among resistance enhancement, carbon sequestration and storage, and economic returns, we conducted 40-year simulations of stand development with BioSum, a framework for conducting landscape analysis with the Forest Vegetation Simulator (FVS), utilizing a statistically representative and spatially balanced sample of Forest Inventory and Analysis (FIA) plots. Simulation outcomes under business-as-usual silviculture were contrasted with fire-aware silviculture, and treatment optimization logic was developed and applied to represent landscape-scale outcomes under business-as-usual and fire-focused management scenarios. Simulation results indicate that fire-aware prescriptions and fire-focused management can meaningfully enhance stand- and landscape-scale fire resistance of westside forests under less than extreme fire weather, but at the cost of lower economic returns and reduced net carbon storage and sequestration over the 40-year analysis window. Shifting from business-as-usual regeneration harvests with short rotations to fire-aware, episodic selection harvest improved fire resistance the most, especially in young privately-owned forests, and with only modest tradeoffs in carbon and economic outcomes. While fire-aware treatments generally reduced net present value from forest operations over business-as-usual, most treatments still generated positive net present value and could be implemented without subsidy. Fire-aware prescriptions that removed and utilized non-merchantable harvest residues instead of burning them, via either pile or broadcast burning, partially mitigated carbon emissions associated with fire-aware treatments, with about the same improvement in fire resistance. Given the currently limited institutional and financial capacity to implement fire resistance enhancing treatments at scale, the insights from this analysis may aid managers seeking to elevate fire resistance to prioritize where and how to manage.

Science & Technology - Other Topics↗

AmeriFlux US-Bar Bartlett Experimental Forest

This is the AmeriFlux version of the carbon flux data for the site US-Bar Bartlett Experimental Forest. Site Description - The Bartlett Experimental Forest (448170 N, 71830 W) is located within the White Mountains National Forest in north-central New Hampshire, USA. The 1050 ha forest extends across an elevational range from 200 to 900 m a.s.l. It was established in 1931 and is managed by the USDA Forest Service Northeastern Research Station in Durham, NH. The climate is humid continental with short, cool summers (mean July temperature, 19.8C) and long, cold winters (mean January temperature, 9.8C). Annual precipitation averages 130 cm and is distributed evenly throughout the year. Soils are developed from glacial till and are predominantly shallow, well-drained spodosols. At lowto mid-elevation, vegetation is dominated by northern hardwoods (American beech, Fagus grandifolia; sugar maple, Acer saccharum; yellow birch, Betula alleghaniensis; with some red maple, Acer rubrum and paper birch, Betula papyrifera). Conifers (eastern hemlock, Tsuga canadensis; eastern white pine, Pinus strobus; red spruce, Picea rubens) are occasionally found intermixed with the more abundant deciduous species but are generally confined to the highest (red spruce) and lowest (hemlock and pine) elevations. In 2003, the site was adopted as a NASA North American Carbon Program (NACP) Tier-2 field research and validation site. A 26.5 m high tower was installed in a low-elevation northern hardwood stand in November, 2003, for the purpose of making eddy covariance measurements of the forest–atmosphere exchange of CO2, H2O and radiant energy. Continuous flux and meteorological measurements began in January, 2004, and are ongoing. Average canopy height in the vicinity of the tower is approximately 20–22 m. In the tower footprint, the forest is predominantly classified into red maple, sugar maple, and American beech forest types. Leaf area index in the vicinity of the tower is 3.6 as measured by seasonal litterfall collection, and 4.5 as measured by the optically based Li-Cor LAI-2000 instrument. Further site information: http://www.fs.fed.us/ne/durham/4155/bartlett.htm

Richardson, Andrew↗

AmeriFlux CA-AF1 Acadia Research Forest

This is the AmeriFlux version of the carbon flux data for the site CA-AF1 Acadia Research Forest. Site Description - The site is located in the Acadia Research Forest (managed by the Canadian Forest Service). The research forest is representative of the Acadian Forest Region in New Brunswick and Nova Scotia and comprises of mixed forest containing softwood, hardwood, and mixed-wood stands. The forest is managed and features different forest composition depending on management history.

Helbig, Manuel [Dalhousie University]↗

Effects of Warming on Tree Species’ Recruitment in Deciduous Forests of the Eastern United States

Climate change is restructuring forests of the United States, although the details of this restructuring are currently uncertain. Rising temperatures of 2 to 8oC and associated changes in soil moisture will shift the competitive balance between species that compete for light and water, and so change their abilities to produce seed, germinate, grow, and survive. We have used large-scale experiments to determine the effects of warming on the most sensitive stage of species distributions, i.e., recruitment, in mixed deciduous forests in southern New England and in the Piedmont region of North Carolina. Two questions organized our research: (1) Might temperate tree species near the “warm” end of their range in the eastern United States decline in abundance during the coming century due to projected warming? and (2) Might trees near the “cool” end of their range in the eastern United States increase in abundance, or extend their range, during the coming 100 years because of projected warming? To explore these questions, we exposed seedlings to air and soil warming experiments in two eastern deciduous forest sites; one at the Harvard Forest (HF) in central Massachusetts, and the other at the Duke Forest (DF) in the Piedmont region of North Carolina. We focused on tree species common to both Harvard and Duke Forests (such as red, black, and white oaks), those near northern range limits (black oak, flowing dogwood, tulip poplar), and those near southern range limits (yellow birch, sugar maple, Virginia pine). At each site, we planted seeds and seedlings in common gardens established in temperature-controlled, open-top chambers. The experimental design was replicated and fully factorial and involved three temperature regimes (ambient, +3oC and +5oC) and two light regimes (closed forest canopy (low light) and gap conditions (high light)). Measured variables included Winter/Spring responses to temperature and mid-Summer responses to low soil moisture. This research will advance our understanding of how the abundances and geographic distributions of several important eastern tree species near the cool and warm ends of their ranges will change during the century because of projected warming. Warming-induced changes in eastern tree abundances and distributions have the potential to affect both the quality and quantity of goods and services provided by eastern forests, and will therefore be of importance to society.

59 BASIC BIOLOGICAL SCIENCES↗

Synergy between land use and climate change increases future fire risk in Amazon forests

Tropical forests have been a permanent feature of the Amazon basin for at least 55 million years, yet climate change and land use threaten the forest's future over the next century. Understory forest fires, which are common under the current climate in frontier forests, may accelerate Amazon forest losses from climate-driven dieback and deforestation. Far from land use frontiers, scarce fire ignitions and high moisture levels preclude significant burning, yet projected climate and land use changes may increase fire activity in these remote regions. Here, we used a fire model specifically parameterized for Amazon understory fires to examine the interactions between anthropogenic activities and climate under current and projected conditions. In a scenario of low mitigation efforts with substantial land use expansion and climate change – Representative Concentration Pathway (RCP) 8.5 – projected understory fires increase in frequency and duration, burning 4–28 times more forest in 2080–2100 than during 1990–2010. In contrast, active climate mitigation and land use contraction in RCP4.5 constrain the projected increase in fire activity to 0.9–5.4 times contemporary burned area. Importantly, if climate mitigation is not successful, land use contraction alone is very effective under low to moderate climate change, but does little to reduce fire activity under the most severe climate projections. These results underscore the potential for a fire-driven transformation of Amazon forests if recent regional policies for forest conservation are not paired with global efforts to mitigate climate change.

54 ENVIRONMENTAL SCIENCES↗

ERTS-1 data applications to Minnesota forest land use classification

The author has identified the following significant results. Color-combined ERTS-1 MSS spectral slices were analyzed to determine the maximum (repeatable) level of meaningful forest resource classification data visually attainable by skilled forest photointerpreters for the following purposes: (1) periodic updating of the Minnesota Land Management Information System (MLMIS) statewide computerized land use data bank, and (2) to provide first-stage forest resources survey data for large area forest land management planning. Controlled tests were made of two forest classification schemes by experienced professional foresters with special photointerpretation training and experience. The test results indicate it is possible to discriminate the MLMIS forest class from the MLMIS nonforest classes, but that it is not possible, under average circumstances, to further stratify the forest classification into species components with any degree of reliability with ERTS-1 imagery. An ongoing test of the resulting classification scheme involves the interpretation, and mapping, of the south half of Itasca County, Minnesota, with ERTS-1 imagery. This map is undergoing field checking by on the ground field cooperators, whose evaluation will be completed in the fall of 1973.

Sizer, J. E.↗

Interpreting forest biome productivity and cover utilizing nested scales of image resolution and biogeographical analysis

The objective was to relate spectral imagery of varying resolution with ground-based data on forest productivity and cover, and to create models to predict regional estimates of forest productivity and cover with a quantifiable degree of accuracy. A three stage approach was outlined. In the first stage, a model was developed relating forest cover or productivity to TM surface reflectance values (TM/FOREST models). The TM/FOREST models were more accurate when biogeographic information regarding the landscape was either used to stratigy the landscape into more homogeneous units or incorporated directly into the TM/FOREST model. In the second stage, AVHRR/FOREST models that predicted forest cover and productivity on the basis of AVHRR band values were developed. The AVHRR/FOREST models had statistical properties similar to or better than those of the TM/FOREST models. In the third stage, the regional predictions were compared with the independent U.S. Forest Service (USFS) data. To do this regional forest cover and forest productivity maps were created using AVHRR scenes and the AVHRR/FOREST models. From the maps the county values of forest productivity and cover were calculated. It is apparent that the landscape has a strong influence on the success of the approach. An approach of using nested scales of imagery in conjunction with ground-based data can be successful in generating regional estimates of variables that are functionally related to some variable a sensor can detect.

Iverson, Louis R.↗

AVHRR-LAC estimates of forest area in Madagascar, 1990

Three AVHRR-LAC data sets acquired in September 1990 and January 1991 were used to map the forest resources of Madagascar. The island was partitioned into four strata to include: (1) the western hardwoods, (2) the central grasslands, (3) the eastern rainforest, and (4) spiny forest. Each stratum was classified separately using AVHRR-LAC data in conjunction with 1984-1988 Landsat-MSS photoproducts. The results of AVHRR classification indicate that approximately 11 percent of the island is covered by forest. Estimates of forest area, by stratum, are as follows: western hardwoods, 6697 sq km; central grasslands, 2830 sq km; eastern rainforest 34,167 sq km; and spiny forest, 17,224 sq km. The total forest area on the 587,041 sq km island is estimated to be 60,918 sq km. The AVHRR forest map was compared to a mid-1970s land cover map which was developed using Landsat-MSS photoproducts. The average class agreement between the mid 1970s ground reference map and the 1990 AVHRR-LAC map was 78.2 percent, the overall accuracy was 81.1 percent. Much of the per-pixel disagreement between the ground reference and AVHRR maps involved areas identified as forest in the 1970s and as nonforest in 1990.

Nelson, R.↗

Toward unbiased determination of the redshift evolution of Lyman-alpha forest clouds

The possibility of using D(sub A), the mean depression of a quasar spectrum due to Ly-alpha forest absorption, to study the number density evolution of the Ly-alpha forest clouds is examined in some detail. Current D(sub A) measurements are made against a continuum that is a power-law extrapolation from the continuum longward of Ly-alpha emission. Compared to the line-counting approach, the D(sub A)-method has the advantage that the D(sub A) measurements are not affected by line-blending effects. However, we find using low-redshift quasar spectra obtained with the Hubble Space Telescope (HST), where the true continuum in the Ly-alpha forest can be estimated fairly reliably because of the much lower density of the Ly-alpha forest lines, that the extrapolated continuum often deviates systematically from the true continuum in the forest region. Such systematic continuum errors introduce large errors in the D(sub A) measurements. The current D(sub A) measurements may also be significantly biased by the possible presence of the Gunn-Peterson absorption. We propose a modification to the existing D(sub A)-method, namely, to measure D(sub A) against a locally established continuum in the Ly-alpha forest. Under conditions that the quasar spectrum has good resolution and S/N to allow for a reliable estimate of the local continuum in the Ly-alpha forest, the modified D(sub A) measurements should be largely free of the systematic uncertainties suffered by the existing D(sub A) measurements. We also introduce a formalism based on the work of Zuo (1993) to simplify the application of the D(sub A)-method(s) to real data. We discuss the merits and limitations of the modified D(sub A)-method, and conclude that it is a useful alternative. Our findings that the extrapolated continuum from longward of Ly-alpha emission often deviates systematically from the true continuum in the Ly-alpha forest present a major problem in the study of the Gunn-Peterson absorption.

Lu, Limin↗

Predicting Fire Susceptibility in the Forests of Amazonia

Although fire is the single greatest threat to the ecological integrity of Amazon forests, our ability to predict the occurrence of Amazon forest fires is rudimentary. Part of the difficulty encountered in making such predictions is the remarkable capacity of Amazon forests to tolerate drought by tapping moisture stored in deep soil. These forests can avoid drought-induced leaf shedding by withdrawing moisture to depths of 8 meters and more. Hence, the absorption of deep soil moisture allows these forests to maintain their leaf canopies following droughts of several months duration, thereby maintaining the deep shade and high relative humidity of the forest interior that prevents these ecosystems from burning. But the drought- and fire-avoidance that is conferred by this deep-rooting phenomenon is not unlimited. During successive years of drought, such as those provoked by El Nino episodes, deep soil moisture can be depleted, and drought-induced leaf shedding begins. The goal of this project was to incorporate this knowledge of Amazon forest fire ecology into a predictive model of forest flammability.

Nepstad, Daniel C.↗

Effect of Forest Canopy on Remote Sensing Soil Moisture at L-band

Global maps of soil moisture are needed to improve understanding and prediction of the global water and energy cycles. Accuracy requirements imply the use of lower frequencies (L-band) to achieve adequate penetration into the soil and to minimize attenuation by the vegetation canopy and effects of surface roughness. Success has been demonstrated over agricultural areas, but canopies with high biomass (e.g. forests) still present a challenge. Examples from recent measurements over forests with the L-band radiometer, 2D-STAR, and its predecessor, ESTAR, will be presented to illustrate the problem. ESTAR and 2D-STAR are aircraft-based synthetic aperture radiometers developed to help resolve both the engineering and algorithm issues associated with future remote sensing of soil moisture. ESTAR, which does imaging across track, was developed to demonstrate the viability of aperture synthesis for remote sensing. The instrument has participated several soil moisture experiments (e.g. at the Little Washita Watershed in 1992 and the Southern Great Plains experiments in 1997 and 1999). In addition, measurements have been made at a forest site near Waverly, VA which contains conifer forests with a variety of biomass. These data have demonstrated the success of retrieving soil moisture at L-band over agricultural areas and the response of passive observations at L-band to biomass over forests. 2D-STAR is a second generation instrument that does aperture synthesis in two dimensions (along track and cross track) and is dual polarized. This instrument has the potential to provide measurements at L-band that simulate the measurements that will be made by the two L-band sensors currently being developed for future remote sensing of soil moisture from space: Hydros (conical scan and real aperture) and SMOS (multiple incidence angle and synthetic aperture). 2D-STAR participated in the SMEX-03 soil moisture experiment, providing images from the NASA P-3 aircraft. Preliminary results include images of the experiment site area near Huntsville, AL that included a mixture of forest and agriculture. Changes during a rain event further illustrate the issues presented by forests. Work is continuing to reduce the 2D-STAR data and to support the two future remote sensing missions. Among the goals is to process the 2D-STAR data to create multiple looks (at the same pixel) with different incidence angles. Data in this format can be used to test algorithms for retrieving soil moisture and biomass such as are planned for SMOS. Also, the data are being processed to provide images at constant incidence angles such as will be obtained by Hydros. Although Hydros will have only one incidence angle, it will also carry an L-band radar, The goal is to use the radar to improve spatial resolution, an issue for remote sensing from space at the long wavelengths. Simultaneous observations with active and passive sensors also offers interesting prospects for treating areas of high biomass (forests) and irregular terrain and may be the challenge for the future.

LeVine, D. M.↗