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USGS2012

Quantitative estimation of climatic parameters from vegetation data in North America by the mutual climatic range technique

The mutual climatic range (MCR) technique is perhaps the most widely used method for estimating past climatic parameters from fossil assemblages, largely because it can be conducted on a simple list of the taxa present in an assemblage. When applied to plant macrofossil data, this unweighted approach (MCR un ) will frequently identify a large range for a given climatic parameter where the species in an assemblage can theoretically live together. To narrow this range, we devised a new weighted approach (MCR wt ) that employs information from the modern relations between climatic parameters and plant distributions to lessen the influence of the "tails" of the distributions of the climatic data associated with the taxa in an assemblage. To assess the performance of the MCR approaches, we applied them to a set of modern climatic data and plant distributions on a 25-km grid for North America, and compared observed and estimated climatic values for each grid point. In general, MCR wt was superior to MCR un in providing smaller anomalies, less bias, and better correlations between observed and estimated values. However, by the same measures, the results of Modern Analog Technique (MAT) approaches were superior to MCR wt . Although this might be reason to favor MAT approaches, they are based on assumptions that may not be valid for paleoclimatic reconstructions, including that: 1) the absence of a taxon from a fossil sample is meaningful, 2) plant associations were largely unaffected by past changes in either levels of atmospheric carbon dioxide or in the seasonal distributions of solar radiation, and 3) plant associations of the past are adequately represented on the modern landscape. To illustrate the application of these MCR and MAT approaches to paleoclimatic reconstructions, we applied them to a Pleistocene paleobotanical assemblage from the western United States. From our examinations of the estimates of modern and past climates from vegetation assemblages, we conclude that the MCR un technique provides reliable and unbiased estimates of the ranges of possible climatic conditions that can reasonably be associated with these assemblages. The application of MCR wt and MAT approaches can further constrain these estimates and may provide a systematic way to assess uncertainty. The data sets required for MCR analyses in North America are provided in a parallel publication.

Quaternary Science Reviews↗

USGS2024

Integration of Indigenous Research Methodologies, Traditional Ecological Knowledge and molecular scatology in an assessment of mesocarnivore presence, diet and habitat use on Yurok Ancestral Lands.

Partnerships between Tribes and researchers in wildlife monitoring and application of Traditional Ecological Knowledge (TEK) have taken a variety of forms, and some scholars have noted a need for culturally sensitive approaches. Guided by Indigenous Research Methodologies, this research is coupled with Yurok TEK, or hlkelonah 'ue-megetohl ('to take care of the earth'), enabling an applied, culturally sensitive approach in partnership with the Yurok Tribe. We present results from a molecular scatology study of wildlife within the ancestral territory of the Yurok Tribe. Scats were collected opportunistically on road transects. All samples ( N = 132) were analysed via DNA barcoding and results matched to documented 'Oohl 'we-toh (Yurok language) names to determine the depositor species ( N = 8). Though there were four focal mesocarnivore species in our study, only bobcat ( Chmuuek; Lynx rufus ) and gray fox ( Wergers; Urocyon cinereoargenteus ) were detected as depositor species. Post hoc analyses were conducted to explore distribution, habitat use and selection in a use-availability context, and food habits of these two species. We found almost complete separation of bobcat and gray fox use of transects, as well as indication of partitioning of vegetation cover types and food. We demonstrate an integrated framework of Western and Indigenous sciences that allows the Indigenous researcher to transcend structured academic disciplinary boundaries. Our approach can be modified for partnerships between Tribes, agencies, academics and students for wildlife monitoring in broader geographic regions in various research applications.

California↗

USGS2003

Evidence for chlorine recycling - Hydrosphere, biosphere, atmosphere - In a forested wet zone on the Canadian Shield

The ability to measure environmental levels of 36Cl by Accelerator Mass Spectrometry and 3H by 3He-ingrowth Mass Spectrometry has made it possible to use the pulses of these two isotopes released into the atmosphere during nuclear weapons testing as tracers of Cl and water movement in soils and groundwater. The authors have investigated the movement of these tracers below a forested wet zone, and have found that both are retarded to a differing extent in the near surface because of vegetative uptake and recycling. Adsorption by clay particles, followed by slow release to the groundwater, may also be significant. The data accumulated in this region of near vertical recharge have gone a considerable distance towards explaining the anomalously low concentrations of 36Cl measured in the 5 Laurentian Great Lakes, as well as indicating possible mechanisms for large scale Cl- recycling in the atmosphere and biosphere. Identification of the near-term non-conservative behaviour of the Cl- is significant, since such a phenomenon could introduce errors in many watershed calculations, e.g. water residence times, evaporation rates, and mixing calculations. Published by Elsevier Science Ltd.

Applied Geochemistry↗

USGS2022

Using a vegetation index to assess wetland condition in the Prairie Pothole Region of North America

Wetlands deliver a suite of ecosystem services to society. Anthropogenic activities, such as wetland drainage, have resulted in considerable wetland loss and degradation, diminishing the intrinsic value of wetland ecosystems worldwide. Protecting remaining wetlands and restoring degraded wetlands are common management practices to preserve and reclaim wetland benefits to society. Accordingly, methods for monitoring and assessing wetlands are required to evaluate their ecologic condition and outcomes of restoration activities. We used an established methodology for conducting vegetation-based assessments and describe a case study consisting of a wetland condition assessment in the Prairie Pothole Region of the North American Great Plains. We provide an overview of an existing method for selecting wetlands to sample across broad geographic distributions using a spatially balanced statistical design. We also describe site assessment protocols, including vegetation survey methods, and how field data were applied to a vegetation index that categorized wetlands according to ecologic condition. Results of the case study indicated that vegetation communities in nearly 50% of the surveyed wetlands were in very poor or poor condition, while only about 25% were considered good or very good . Approximately 70% of wetlands in native grasslands were categorized as good or very good compared to only 12% of those in reseeded grasslands (formerly cropland). In terms of informing restoration and management activities, results indicated that improved restoration practices could include a greater focus on establishing natural vegetation communities, and both restored and native prairie wetlands would benefit from enhanced management of invasive species.

Prairie Pothole Region↗

USGS2023

A recruitment niche framework for improving seed-based restoration

As larger tracts of land experience degradation, seed-based restoration (SBR) will be a primary tool to reestablish vegetation and ecosystem function. SBR has advanced in terms of technical and technological approaches, yet plant recruitment remains a major barrier in some systems, notably drylands. There is an unmet opportunity to test science-based approaches to seed mix design and application, based not only on diversity or local provenance, but on the unique recruitment strategies of species. We lay out a framework that uses a quantitative representation of species' recruitment niches to match them to targeted goals (e.g. drought or invasion resistance) and methods (e.g. precision tools and technologies) in SBR. We first describe how to quantify the recruitment niche with seed and seedling traits tied to observed recruitment responses to environmental factors. We then show how a quantified recruitment niche framework can serve as the foundation to address three major restoration challenges: (1) designing forward-looking seed mixes that increase resilience to future climate and disturbance, (2) accounting for natural recovery in SBR planning, and (3) applying precision seeding practices to maximize restoration success. Finally, we demonstrate these ideas with existing data and discuss key challenges to adoption in SBR practice. While the ideas in this framework are based in ecological theory, they will require substantial testing and refinement by scientists engaged in SBR efforts. If this framework is integrated into research agendas, we believe it has the potential to unify and advance diverse elements of seed-based restoration ecology and improve restoration outcomes.

Restoration Ecology↗

USGS2003

Modeling radium and radon transport through soil and vegetation

A one-dimensional flow and transport model was developed to describe the movement of two fluid phases, gas and water, within a porous medium and the transport of 226Ra and 222Rn within and between these two phases. Included in this model is the vegetative uptake of water and aqueous 226Ra and 222Rn that can be extracted from the soil via the transpiration stream. The mathematical model is formulated through a set of phase balance equations and a set of species balance equations. Mass exchange, sink terms and the dependence of physical properties upon phase composition couple the two sets of equations. Numerical solution of each set, with iteration between the sets, is carried out leading to a set-iterative compositional model. The Petrov-Galerkin finite element approach is used to allow for upstream weighting if required for a given simulation. Mass lumping improves solution convergence and stability behavior. The resulting numerical model was applied to four problems and was found to produce accurate, mass conservative solutions when compared to published experimental and numerical results and theoretical column experiments. Preliminary results suggest that the model can be used as an investigative tool to determine the feasibility of phytoremediating radium and radon-contaminated soil. ?? 2003 Elsevier Science B.V. All rights reserved.

Journal of Contaminant Hydrology↗

USGS2016

Quantifying pollen-vegetation relationships to reconstruct ancient forests using 19th-century forest composition and pollen data

Mitigation of climate change and adaptation to its effects relies partly on how effectively land-atmosphere interactions can be quantified. Quantifying composition of past forest ecosystems can help understand processes governing forest dynamics in a changing world. Fossil pollen data provide information about past forest composition, but rigorous interpretation requires development of pollen-vegetation models (PVMs) that account for interspecific differences in pollen production and dispersal. Widespread and intensified land-use over the 19th and 20th centuries may have altered pollen-vegetation relationships. Here we use STEPPS, a Bayesian hierarchical spatial PVM, to estimate key process parameters and associated uncertainties in the pollen-vegetation relationship. We apply alternate dispersal kernels, and calibrate STEPPS using a newly developed Euro-American settlement-era calibration data set constructed from Public Land Survey data and fossil pollen samples matched to the settlement-era using expert elicitation. Models based on the inverse power-law dispersal kernel outperformed those based on the Gaussian dispersal kernel, indicating that pollen dispersal kernels are fat tailed. Pine and birch have the highest pollen productivities. Pollen productivity and dispersal estimates are generally consistent with previous understanding from modern data sets, although source area estimates are larger. Tests of model predictions demonstrate the ability of STEPPS to predict regional compositional patterns.

Quaternary Science Reviews↗

USGS2026

Advances and applications of Unoccupied Aerial Systems (UAS) research in landscape ecology

Landscape ecologists have long depended on satellite and aerial remote sensing to address questions about landscape pattern and process, structure, and change (Foody 2023 ). Unoccupied aerial systems/vehicles (UAS/UAV, a.k.a. drones) technology is becoming an increasingly popular research tool in environmental sciences allowing scientists to generate low-cost, high-quality, and high-resolution imagery on demand that can be tailored to specific research questions. While satellite data are of a fixed resolution and temporal interval, UAS offer researchers control and flexibility to design studies and collect data at resolutions and scales that provide ecologically relevant information at finer spatial resolutions (e.g., < 30 cm) than what is currently available from satellite platforms (typically > 3m), thus helping capture objects such as individual plant canopies, micro-topography, and individual animals. Unlike satellites with fixed orbits, UAS can be deployed at more optimal temporal frequencies for ecological monitoring. We organized the special collection “Advances and Applications of Unoccupied Aerial Systems (UAS) Research in Landscape Ecology” to showcase the many ways that UAS tools and technologies are currently applied to advance landscape ecological research. When we announced the collection in 2023, only 11 papers published in the journal Landscape Ecology used UAS data, which was a notably small number compared to many other general ecology, environmental science and remote sensing journals. In an attempt to understand why UAS were not more widely used in landscape ecology and provide possible solutions, we published a review article (Villarreal et al. 2025) that identified the challenges, knowledge gaps, and obstacles for the adoption of UAS technologies in landscape ecology research. The main issues we identified include: (1) an abundance of UAS methods papers in the existing literature, with comparatively few studies demonstrating how UAS can be applied to address ecological questions; (2) a perceived scale mismatch between the geographic extent of UAS data collection (local) compared to larger study areas (landscapes) and a need to design robust scaling approaches to connect fine-scale UAS data with broader ecological patterns; and (3) a need for improved integration of UAS data with other commonly used remote sensing datasets including historical high resolution aerial imagery. Additionally, researchers new to UAS remote sensing may be discouraged or overwhelmed by the general lack of scientific consensus and standardized protocols for typical tasks such as data collection, vegetation classification, and change detection, as well as restrictive and/or confusing policy, regulatory, and legal issues surrounding UAS operations (Villarreal et al. 2025).

Landscape Ecology↗

USGS2021

A novel automatic phenology learning (APL) method of training sample selection using multiple datasets for time-series land cover mapping

The long record of Landsat imagery, which is the cornerstone of Earth observation, provides an opportunity to monitor land use and land cover (LULC) change and understand the interactions between the climate and earth system through time. A few change detection algorithms such as Continuous Change Detection and Classification (CCDC) have been developed to utilize all available Landsat images for change detection and characterization at local or global scales. However, the reliable, rapid, and reproducible collection of training samples have become a challenge for time series land cover classification at a large scale. To meet the challenge, we proposed an automatic phenology learning (APL) method with the assumption that the temporal profiles of samples within the same land cover type are the same or similar at a local scale to generate evenly distributed training samples automatically. We designed the method to build land cover patterns for each category based on consensus samples derived from multiple existing scientific datasets including LANDFIRE's (LF) Existing Vegetation Type (EVT), USGS National Land Cover Database (NLCD), National Agricultural Statistics Service (NASS) Cropland Data Layer (CDL), and National Wetlands Inventory (NWI). Then we calculated the Time-Weighted Dynamic Time Warping (twDTW) distance between any undefined samples and land cover patterns in the same geographical region as prior knowledge. Finally, we selected the optimal land cover category for each undefined sample from the land cover products based on the designed criteria iteratively using the twDTW distance as an indicator. The method was applied in the footprint of 10 selected Landsat Analysis Ready Data (ARD) tiles in the eastern and western conterminous United States (CONUS) to produce annual land cover maps from 1985 to 2017. The accuracy assessment and visual comparison revealed that the APL method can generate reliable training samples without any manual interpretation, producing better land cover results especially for the grass/shrub and wetland land cover classes. Applying the APL method, the overall accuracy of the annual land cover maps was improved by 2% over the accuracy of Land Change Monitoring, Assessment, and Projection (LCMAP) Collection 1.0 Science Products in the research regions. Our results also indicate that the APL method provides an approach for best use of different land cover products and meets the requirement of intensive sampling for training data collection.

Remote Sensing of Environment↗

USGS2021

Long-term ecosystem and biogeochemical research in Loch Vale watershed, Rocky Mountain National Park, Colorado

Loch Vale watershed was instrumented in 1983 with initial support from the National Acid Precipitation Assessment Program to ask whether ecosystems of Rocky Mountain National Park (RMNP) were affected by acidic atmospheric deposition. Research and monitoring activities were expanded in 1991 by the U.S. Geological Survey Water, Energy, and Biogeochemical Budgets program to understand the processes, and their interactions, controlling water, energy, and biogeochemical fluxes. With help from many collaborators we have characterized trends and patterns in atmospheric deposition, climate, and hydrology, including glaciers and other ice features. Instead of acidic deposition, we documented high atmospheric inputs of reactive nitrogen (Nr), and have studied the ecological consequences in soils, surface water, and vegetation. Using paleolimnology, we documented the onset of human-caused change to lake primary producers ca. 1950 in response to increased Nr deposition and warming. Our results provided the basis for the Colorado Nitrogen Deposition Reduction Plan, a state policy that aims to reduce Nr emissions to protect resources in RMNP by 2032. Carbon cycle research revealed mountain wetlands now release more carbon than they store, and respiration and methane flux occurs even during winter through deep snow packs. Trend analyses found export of Nr to be closely tied to atmospheric inputs, but can lag in response to drought. Current research explores consequences of the combination of warming, changes in precipitation dynamics, and atmospheric deposition of Nr and dust on stream and lake CO 2 dynamics, lake biology and trophic state, and soil carbon composition. Dramatic increases in park visitors have prompted studies on the effects of recreational use on water quality. New tools such as remote sensing and high frequency instream water quality sensors are being applied to lake and stream studies. Monitoring, combined with experiments, models, and spatial comparisons is an essential foundation for science-based resource management.

Colorado↗

USGS2008

Quantitative estimation of bioclimatic parameters from presence/absence vegetation data in North America by the modern analog technique

The method of modern analogs is widely used to obtain estimates of past climatic conditions from paleobiological assemblages, and despite its frequent use, this method involved so-far untested assumptions. We applied four analog approaches to a continental-scale set of bioclimatic and plant-distribution presence/absence data for North America to assess how well this method works under near-optimal modern conditions. For each point on the grid, we calculated the similarity between its vegetation assemblage and those of all other points on the grid (excluding nearby points). The climate of the points with the most similar vegetation was used to estimate the climate at the target grid point. Estimates based the use of the Jaccard similarity coefficient had smaller errors than those based on the use of a new similarity coefficient, although the latter may be more robust because it does not assume that the "fossil" assemblage is complete. The results of these analyses indicate that presence/absence vegetation assemblages provide a valid basis for estimating bioclimates on the continental scale. However, the accuracy of the estimates is strongly tied to the number of species in the target assemblage, and the analog method is necessarily constrained to produce estimates that fall within the range of observed values. We applied the four modern analog approaches and the mutual overlap (or "mutual climatic range") method to estimate bioclimatic conditions represented by the plant macrofossil assemblage from a packrat midden of Last Glacial Maximum age from southern Nevada. In general, the estimation approaches produced similar results in regard to moisture conditions, but there was a greater range of estimates for growing-degree days. Despite its limitations, the modern analog technique can provide paleoclimatic reconstructions that serve as the starting point to the interpretation of past climatic conditions.

Quaternary Science Reviews↗

USGS2013

Woody vegetation communities of tidal freshwater swamps in South Carolina, Georgia and Florida (US) with comparisons to similar systems in the US and South America

Questions What are the general tree communities found in tidal freshwater swamps along four large coastal rivers in the southeastern United States (US)? How do these communities compare to other tidal freshwater swamps in the US and South America? Locations Tidal floodplains of major rivers along the Atlantic and Gulf coasts of the southeastern US: Savannah, Altamaha, Suwannee and Apalachicola Rivers. Methods An extensive survey of trees and shrubs was conducted to describe the communities from a range of tidal freshwater swamps. River basins studied include micro-tidal (Gulf coast) and meso-tidal (Atlantic coast) regimes, and study areas were located both near and distant to primary channels. A total of 128 plots (100 m2 each) were inventoried, distributed evenly over the Savannah and Altamaha Rivers along the Atlantic coast, and the Suwannee and Apalachicola Rivers along the Gulf coast. Multivariate statistics helped discern communities and the significant indicator species in each. Results Four general communities were characterized and named according to the strongest individual indicator species in each: Water Tupelo (Nyssa aquatica) Community, Swamp Tupelo (Nyssa biflora) Community, Dwarf Palmetto (Sabal minor) Community and Cabbage Palm (Sabal palmetto) Community. Conclusions Descriptions of most tidal freshwater swamps in the southeastern US fit within the communities described in this study. Because studies that make inferences between environmental drivers (e.g. salinity, hydroperiod, hurricanes) and specific community types are best applied to the same communities (but perhaps different river systems), this work provides a framework by which tidal freshwater forested wetlands can be accurately compared based on their tree communities. We suggest that, within the broad range of our inventories, the four communities described identify the primary associations that should be tracked within most tidal freshwater swamps of the US. However, we identify some river basins in the US that do not fit this construct. Diversity of major tree communities in tidal freshwater swamps outside the US is generally much lower (with the notable exception of Amazonian hardwood tidal várzea), as are basal area values.

Georgia;Florida;South Carolina↗

USGS2013

Advanced and applied remote sensing of environmental conditions

"Remote sensing” is a general term for monitoring techniques that collect information without being in physical contact with the object of study. Overhead imagery from aircraft and satellite sensors provides the most common form of remotely sensed data and records the interaction of electromagnetic energy (usually visible light) with matter, such as the Earth’s surface. Remotely sensed data are fundamental to geographic science. The U.S. Geological Survey’s (USGS) Eastern Geographic Science Center (EGSC) is currently conducting and promoting the research and development of several different aspects of remote sensing science in both the laboratory and from overhead instruments. Spectroscopy is the science of recording interactions of energy and matter and is the bench science for all remote sensing. Visible and infrared analysis in the laboratory with special instruments called spectrometers enables the transfer of this research from the laboratory to multispectral (5–15 broad bands) and hyperspectral (50–300 narrow contiguous bands) analyses from aircraft and satellite sensors. In addition, mid-wave (3–5 micrometers, µm) and long-wave (8–14 µm) infrared data analysis, such as attenuated total reflectance (ATR) spectral analysis, are also conducted. ATR is a special form of vibrational infrared spectroscopy that has many applications in chemistry and biology but has recently been shown to be especially diagnostic for vegetation analysis.

Fact Sheet↗

USGS2005

Species frequency dynamics in an old-field succession: Effects of disturbance, fertilization and scale

Question: Can patterns of species frequency in an old-field be explained within the context of a metapopulation model? Are the patterns observed related to time, spatial scale, disturbance, and nutrient availability? Location: Upland and lowland old-fields in Illinois, USA. Method: Species richness was recorded annually for seven years following plowing of an upland and lowland old-field subject to crossed fertilizer and disturbance treatments (mowing and rototilling). Species occupancy distributions were assessed with respect to the numbers of core and satellite species. Results: In both fields, species richness became higher in disturbed plots than in undisturbed plots over time, and decreased in fertilized plots irrespective of time. A bimodal pattern of species richness consistent with the Core-satellite species (CSS) hypothesis occurred in the initial seed bank and through the course of early succession. The identity of native and exotic core species (those present in > 90% of blocks) changed with time. Some core species from the seed bank became core species in the vegetation, albeit after several years. At the scale of individual plots, a bimodal fit consistent with the CSS hypothesis applied only in year 1 and rarely thereafter. Conclusions: The CSS hypothesis provides a metapopulation perspective for understanding patterns of species richness but requires the assessment of spatial and temporal scaling effects. Regional processes (e.g. propagule availability) at the largest scale have the greatest impact influencing community structure during early secondary succession. Local processes (e.g., disturbance and soil nutrients) are more important at smaller scales and place constraints on species establishment and community structure of both native and exotic species. Under the highest intensity of disturbance, exotic species may be able to use resources unavailable to, or unused by, native species.

Journal of Vegetation Science↗

USGS2023

Riparian vegetation response amid variable climate conditions across the Upper Gila River watershed: Informing Tribal restoration priorities

Riparian systems across the Southwest United States are extremely valuable for the human and ecological communities that engage with them. However, they have experienced substantial changes and stresses over the past century, including non-native vegetation expansion, vegetation die-offs, and increased fire activity. Vegetation management approaches, such as ecological restoration, may address some of these stressors as well as reduce the risk of future impacts. We apply remote sensing to inform restoration priorities along the upper Gila River within the San Carlos Apache Reservation and Upper Gila River watershed. First, we develop a spatially and temporally explicit trend analysis across three observed climate periods (1985–1993, 1993–2014, 2014–2021) using the Landsat-derived indices to quantify changes in riparian vegetation conditions. These maps can be used to identify areas potentially more at risk for degradation. Second, we analyze changes in riparian vegetation within a climate framework to better understand trends and the potential effect of climate change. Vegetation greenness has largely increased throughout the watershed despite intensifying drought conditions across our study period, though areas within the lower watershed have shown increased stress and higher rates of wildfire and other disturbances over the past 5-years. Nevertheless, small-scale restoration activities appear to show improving vegetation conditions, suggesting efficacy of these restoration activities. Results from this study may be integrated with restoration objectives to develop a restoration plan that will help riparian vegetation communities adapt to change.

Arizona↗

USGS2003

Imaging spectroscopy: Earth and planetary remote sensing with the USGS Tetracorder and expert systems

Imaging spectroscopy is a tool that can be used to spectrally identify and spatially map materials based on their specific chemical bonds. Spectroscopic analysis requires significantly more sophistication than has been employed in conventional broadband remote sensing analysis. We describe a new system that is effective at material identification and mapping: a set of algorithms within an expert system decision‐making framework that we call Tetracorder. The expertise in the system has been derived from scientific knowledge of spectral identification. The expert system rules are implemented in a decision tree where multiple algorithms are applied to spectral analysis, additional expert rules and algorithms can be applied based on initial results, and more decisions are made until spectral analysis is complete. Because certain spectral features are indicative of specific chemical bonds in materials, the system can accurately identify and map those materials. In this paper we describe the framework of the decision making process used for spectral identification, describe specific spectral feature analysis algorithms, and give examples of what analyses and types of maps are possible with imaging spectroscopy data. We also present the expert system rules that describe which diagnostic spectral features are used in the decision making process for a set of spectra of minerals and other common materials. We demonstrate the applications of Tetracorder to identify and map surface minerals, to detect sources of acid rock drainage, and to map vegetation species, ice, melting snow, water, and water pollution, all with one set of expert system rules. Mineral mapping can aid in geologic mapping and fault detection and can provide a better understanding of weathering, mineralization, hydrothermal alteration, and other geologic processes. Environmental site assessment, such as mapping source areas of acid mine drainage, has resulted in the acceleration of site cleanup, saving millions of dollars and years in cleanup time. Imaging spectroscopy data and Tetracorder analysis can be used to study both terrestrial and planetary science problems. Imaging spectroscopy can be used to probe planetary systems, including their atmospheres, oceans, and land surfaces.

Journal of Geophysical Research E: Planets↗

USGS2007

Loess sedimentation in Tibet: provenance, processes, and link with Quaternary glaciations

Well-preserved loess deposits are found on the foothills of mountains along the middle reaches of the Yarlung Zangbo River in southern Tibet. Optically stimulated luminescence (OSL) dating is used to determine loess ages by applying the single-aliquot regeneration technique. Geochemical, mineralogical, and granulometric measurements were carried out to allow a comparison between loess from Tibet and the Chinese Loess Plateau. Our results demonstrate that (i) the loess deposits have a basal age of 13-11 ka, suggesting they accumulated after the last deglaciation, (ii) loess in southern Tibet has a "glacial" origin, resulting from eolian sorting of glaciofluvial outwash deposits from braided river channels or alluvial fans by local near-surface winds, and (iii) the present loess in the interior of Tibet has accumulated since the last deglaciation when increased monsoonal circulation provided an increased vegetation cover that was sufficient for trapping eolian silt. The lack of full-glacial loess is either due to minimal vegetation cover or possibly due to the erosion of loess as glaciofluvial outwash during the beginning of each interglacial. Such processes would have been repeated during each glacial-interglacial cycle of the Quaternary. ?? 2007 Elsevier Ltd. All rights reserved.

Quaternary Science Reviews↗

USGS2008

Soil texture drives responses of soil respiration to precipitation pulses in the sonoran desert: Implications for climate change

Climate change predictions for the desert southwestern U.S. are for shifts in precipitation patterns. The impacts of climate change may be significant, because desert soil processes are strongly controlled by precipitation inputs ('pulses') via their effect on soil water availability. This study examined the response of soil respiration-an important biological process that affects soil carbon (C) storage-to variation in pulses representative of climate change scenarios for the Sonoran Desert. Because deserts are mosaics of different plant cover types and soil textures-which create patchiness in soil respiration-we examined how these landscape characteristics interact to affect the response of soil respiration to pulses. Pulses were applied to experimental plots of bare and vegetated soil on contrasting soil textures typical of Sonoran Desert grasslands. The data were analyzed within a Bayesian framework to: (1) determine pulse size and antecedent moisture (soil moisture prior to the pulse) effects on soil respiration, (2) quantify soil texture (coarse vs. fine) and cover type (bare vs. vegetated) effects on the response of soil respiration and its components (plant vs. microbial) to pulses, and (3) explore the relationship between long-term variation in pulse regimes and seasonal soil respiration. Regarding objective (1), larger pulses resulted in higher respiration rates, particularly from vegetated fine-textured soil, and dry antecedent conditions amplified respiration responses to pulses (wet antecedent conditions dampened the pulse response). Regarding (2), autotrophic (plant) activity was a significant source (???60%) of respiration and was more sensitive to pulses on coarse- versus fine-textured soils. The sensitivity of heterotrophic (microbial) respiration to pulses was highly dependent on antecedent soil water. Regarding (3), seasonal soil respiration was predicted to increase with both growing season precipitation and mean pulse size (but only for pulses between 7 and 25 mm). Thus, the heterogeneity of the desert landscape and the timing or the number of medium-sized pulses is expected to significantly impact desert soil C loss with climate change. ?? 2008 Springer Science+Business Media, LLC.

Ecosystems↗