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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Soil moisture-atmosphere feedbacks mitigate declining water availability in drylands

Global warming alters surface water availability (precipitation minus evapotranspiration, P–E) and hence freshwater resources. However, the influence of land–atmosphere feedbacks on future P–E changes and the underlying mechanisms remain unclear. Here we demonstrate that soil moisture (SM) strongly impacts future P–E changes, especially in drylands, by regulating evapotranspiration and atmospheric moisture inflow. Using modelling and empirical approaches, we find a consistent negative SM feedback on P–E, which may offset ~60% of the decline in dryland P–E otherwise expected in the absence of SM feedbacks. The negative feedback is not caused by atmospheric thermodynamic responses to declining SM; rather, reduced SM, in addition to limiting evapotranspiration, regulates atmospheric circulation and vertical ascent to enhance moisture transport into drylands. This SM effect is a large source of uncertainty in projected dryland P–E changes, underscoring the need to better constrain future SM changes and improve the representation of SM–atmosphere processes in models.

precipitation↗
NASA NTRS2019

Modeling Phenological Controls on Carbon Dynamics in Dryland Sagebrush Ecosystems

Dryland ecosystems play an important role in determining how precipitation anomalies affect terrestrial carbon fluxes at regional to global scales. Thus, to understand how climate change may affect the global carbon cycle, we must also be able to understand and model its effects on dryland vegetation. Dynamic Global Vegetation Models (DGVMs) are an important tool for modeling ecosystem dynamics, but they often struggle to reproduce seasonal patterns of plant productivity. Because the phenological niche of many plant species is linked to both total productivity and competitive interactions with other plants, errors in how process-based models represent phenology hinder our ability to predict climate change impacts. This may be particularly problematic in dryland ecosystems where many species have developed a complex phenology in response to seasonal variability in both moisture and temperature. Here, we examine how uncertainty in key parameters as well as the structure of existing phenology routines affect the ability of a DGVM to match seasonal patterns of leaf area index (LAI) and gross primary productivity (GPP) across a temperature and precipitation gradient. First, we optimized model parameters using a combination of site-level eddy covariance data and remotely-sensed LAI data. Second, we modified the model to include a semi-deciduous phenology type and added flexibility to the representation of grass phenology. While optimizing parameters reduced model bias, the largest gains in model performance were associated with the development of our new representation of phenology. This modified model was able to better capture seasonal patterns of both leaf area index (R(exp 2) = 0.75) and gross primary productivity (R(exp 2) = 0.84), though its ability to estimate total annual GPP depended on using eddy covariance data for optimization. The new model also resulted in a more realistic outcome of modeled competition between grass and shrubs. These findings demonstrate the importance of improving how DGVMs represent phenology in order to accurately forecast climate change impacts in dryland ecosystems.

Ecosystem model↗
DOE OSTI2022

Increasing sensitivity of dryland vegetation greenness to precipitation due to rising atmospheric CO 2

Water availability plays a critical role in shaping terrestrial ecosystems, particularly in low- and mid-latitude regions. The sensitivity of vegetation growth to precipitation strongly regulates global vegetation dynamics and their responses to drought, yet sensitivity changes in response to climate change remain poorly understood. Here we use long-term satellite observations combined with a dynamic statistical learning approach to examine changes in the sensitivity of vegetation greenness to precipitation over the past four decades. We observe a robust increase in precipitation sensitivity (0.624% yr –1 ) for drylands, and a decrease (–0.618% yr –1 ) for wet regions. Using model simulations, we show that the contrasting trends between dry and wet regions are caused by elevated atmospheric CO 2 (eCO 2 ). eCO 2 universally decreases the precipitation sensitivity by reducing leaf-level transpiration, particularly in wet regions. However, in drylands, this leaf-level transpiration reduction is overridden at the canopy scale by a large proportional increase in leaf area. The increased sensitivity for global drylands implies a potential decrease in ecosystem stability and greater impacts of droughts in these vulnerable ecosystems under continued global change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Size-related decline in dryland shrubs is related to reductions in hydraulic efficiency and carbon assimilation and not nonstructural carbohydrate depletion

Plant growth and survival are fundamentally constrained by water transport from roots to leaves, impacting carbon assimilation and associated labile carbon pools. However, physiological constraints on growth and survival vary with plant age, due to changes in metabolic sinks, and increases in hydraulic path length from rhizosphere to canopy. We investigated crown dieback, growth, hydraulics, carbon assimilation and carbohydrate storage in relation to increasing basal diameter of two dominant shrub species (Caragana korshinskii and Artemisia ordosica) at the southeastern edge of the Tengger Desert, China. The aim was to identify mechanisms of decreased performance with plant size in dryland shrubs. Clear contrasts in stomatal regulation of leaf water potentials were detected between species. Despite these contrasts, radial growth, hydraulic transport efficiency (Ks), and photosynthetic efficiency similarly declined in both species with increasing plant size, while non-structural carbohydrate (NSC) reserves remained unchanged. Xylem embolism (PLC) increased with plant size, resulting in significant reductions in carbon assimilation in both species. Results indicate that hydraulic, and potentially carbon assimilation constraints, rather than reductions in carbohydrate storage, govern growth-related dryland shrub decline. These findings improve our understanding of how population demography impacts dryland forest response to climate change.

Zhang, Hongxia↗
DOE OSTI2021

Enhanced Warming in Global Dryland Lakes and Its Drivers

Lake surface water temperature (LSWT) is sensitive to climate change. Previous studies have found that LSWT warming is occurring on a global scale and is expected to continue in the future. Recently, new global LSWT data products have been generated using satellite remote sensing, which provides an inimitable opportunity to study the LSWT response to global warming. Based on the satellite observations, we found that the warming rate of global lakes is uneven, with apparent regional differences. Indeed, comparing the LSWT warming in different climate zones (from arid to humid), the lakes in drylands experienced more significant warming (0.28 °C decade-1) than those in semi-humid and humid regions (0.19 °C decade-1) during previous decades (1995–2016). By further quantifying the impact factors, it showed that the LSWT warming is attributed to air temperature (74.4%), evaporation (4.1%), wind (9.9%), cloudiness (4.3%), net shortwave (3.1%), and net longwave (4.0%) over the lake surface. Air temperature is the main driving force for the warming of most global lakes, so the first estimate quantification of future LSWT trends can be determined from air temperature projections. By the end of the 21st century, the summer air temperature would warm up to 1.0 °C (SSP1-2.6) and 6.3 °C (SSP5-8.5) over lakes, with a more significant warming trend over the dryland lakes. Combined with their higher warming sensitivity, the excess summer LSWT warming in drylands is expected to continue, which is of great significance because of their high relevance in these water-limited regions.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1980

Dryland pasture and crop conditions as seen by HCMM

Ground truth, aircraft, and satellite data were examined in order to: (1) assess the capability for determining wheat and pasture canopy temperatures in a dryland farming region from HCMM data; (2) assess the capability for determining soil moisture from HCMM data in dryland crops (winter wheat) from adjacent range lands; and (3) determine the relationship of HCMM-derived soil moisture and canopy temperature values with the condition of winter wheat and dryland farming areas during the principal growth stages. The IR data were screened to include areas having greater than 60% pasture and surface temperatures were recalculated using the atmospheric correction factor calculated by the modified RADTRA model, and the July 29, 1978 IR data were analyzed. Screening the IR data improved the relationship for July 24/July 13 and October 7/August 31 temperature/API relationship. However the coefficient of determination was not improved in the July 29/July 13 relationship.

Rosenthal, W. D.↗
NASA NTRS2019

Modeling Phenological Controls on Carbon Dynamics in Dryland Sagebrush Ecosystems

Dryland ecosystems play an important role in determining how precipitation anomalies affect terrestrial carbonfluxes at regional to global scales. Thus, to understand how climate change may affect the global carbon cycle,we must also be able to understand and model its effects on dryland vegetation. Dynamic Global VegetationModels (DGVMs) are an important tool for modeling ecosystem dynamics, but they often struggle to reproduceseasonal patterns of plant productivity. Because the phenological niche of many plant species is linked to bothtotal productivity and competitive interactions with other plants, errors in how process-based models representphenology hinder our ability to predict climate change impacts. This may be particularly problematic in drylandecosystems where many species have developed a complex phenology in response to seasonal variability in bothmoisture and temperature. Here, we examine how uncertainty in key parameters as well as the structure ofexisting phenology routines affect the ability of a DGVM to match seasonal patterns of leaf area index (LAI) andgross primary productivity (GPP) across a temperature and precipitation gradient. First, we optimized modelparameters using a combination of site-level eddy covariance data and remotely-sensed LAI data. Second, wemodified the model to include a semi-deciduous phenology type and added flexibility to the representation ofgrass phenology. While optimizing parameters reduced model bias, the largest gains in model performance wereassociated with the development of our new representation of phenology. This modified model was able to bettercapture seasonal patterns of both leaf area index (R2=0.75) and gross primary productivity (R2=0.84), thoughits ability to estimate total annual GPP depended on using eddy covariance data for optimization. The new modelalso resulted in a more realistic outcome of modeled competition between grass and shrubs. These findingsdemonstrate the importance of improving how DGVMs represent phenology in order to accurately forecastclimate change impacts in dryland ecosystems.

Ecosystem model Phenology Parameter optimization E↗
NASA NTRS2023

Sub-Continental-Scale Carbon Stocks of Individual Trees in African Drylands

The distribution of dryland trees and their density, cover, size, mass and carbon content are not well known at sub-continental to continental scales. This information is important for ecological protection, carbon accounting, climate mitigation and restoration efforts of dryland ecosystems. We assessed more than 9.9 billion trees derived from more than 300,000 satellite images, covering semi-arid sub-Saharan Africa north of the Equator. We attributed wood, foliage and root carbon to every tree in the 0–1,000 mm year −1 rainfall zone by coupling field data, machine learning, satellite data and high-performance computing. Average carbon stocks of individual trees ranged from 0.54 Mg C ha −1 and 63 kg C tree −1 in the arid zone to 3.7 Mg C ha −1 and 98 kg tree −1 in the sub-humid zone. Overall, we estimated the total carbon for our study area to be 0.84 (±19.8%) Pg C. Comparisons with 14 previous TRENDY numerical simulation studies23 for our area found that the density and carbon stocks of scattered trees have been underestimated by three models and overestimated by 11 models, respectively. This benchmarking can help understand the carbon cycle and address concerns about land degradation. We make available a linked database of wood mass, foliage mass, root mass and carbon stock of each tree for scientists, policymakers, dryland-restoration practitioners and farmers, who can use it to estimate farmland tree carbon stocks from tablets or laptops.

Compton Tucker↗
DOE OSTI2021

Climatic Controls on Soil Carbon Accumulation and Loss in a Dryland Ecosystems

Arid and semiarid ecosystems drive year-to-year variability in the strength of the terrestrial carbon (C) sink, yet there is uncertainty about how soil C gains and losses contribute to this variation. For this work, to address this knowledge gap, we embedded C-depleted soil mesocosms, containing litter or biocrust C inputs, within an in situ dryland ecosystem warming experiment. Over the course of one year, changes in microbial biomass and total soil organic C pools were monitored alongside hourly measurements of soil CO 2 flux. We also developed a biogeochemical model to explore the mechanisms that gave rise to observed soil C dynamics. Field data and model simulations demonstrated that water exerted much stronger control on soil biogeochemistry than temperature, with precipitation events triggering large CO 2 pulses and transport of litter- and biocrust-derived C into the soil profile. We expected leaching of organic matter would result in steady accumulation of C within the mineral soil over time. Instead, the size of the total organic C pool fluctuated throughout the year, largely in response to microbial growth: increases in the size of microbial biomass were negatively correlated with the quantity of C residing in the top 2 cm, where most biogeochemical changes were observed. Our data and models suggest that microbial responses to precipitation events trigger rapid metabolism of dissolved organic C inputs, which strongly limit accumulation of autotroph-derived C belowground. Accordingly, changes in the magnitude and/or frequency of precipitation events in this dryland ecosystem could have profound impacts on the strength of the soil C sink.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Continental-scale niche differentiation of dominant topsoil archaea in drylands

Archaea represent a diverse group of microorganisms often associated with extreme environments. However, an integrated understanding of biogeographical patterns of the specialist Haloarchaea and the potential generalist ammonia-oxidizing archaea (AOA) across large-scale environmental gradients remains limited. Here, we hypothesize that niche differentiation determines their distinct distributions along environmental gradients. To test the hypothesis, we use a continental-scale research network including 173 dryland sites across northern China. Our results demonstrate that Haloarchaea and AOA dominate topsoil archaeal communities. As hypothesized, Haloarchaea and AOA show strong niche differentiation associated with two ecosystem types mainly found in China's drylands (i.e. deserts vs. grasslands), and they differ in the degree of habitat specialization. The relative abundance and richness of Haloarchaea are higher in deserts due to specialization to relatively high soil salinity and extreme climates, while those of AOA are greater in grassland soils. Our results further indicate a divergence in ecological processes underlying the segregated distributions of Haloarchaea and AOA. Haloarchaea are governed primarily by environmental-based processes while the more generalist AOA are assembled mostly via spatial-based processes. Our findings add to existing knowledge of large-scale biogeography of topsoil archaea, advancing our predictive understanding on changes in topsoil archaeal communities in a drier world.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Data and scripts associated with the manuscript "Encoding Diel Hysteresis and the Birch Effect in Dryland Soil Respiration Models through Knowledge-Guided Deep Learning"

This package contains the data and scripts used in "Encoding Diel Hysteresis and the Birch Effect in Dryland Soil Respiration Models through Knowledge-Guided Deep Learning" (Jiang et al., 2022). The data.zip file contains the flux tower and automated chamber observations used for developing the deep learning model for modeling soil respiration. The scripts.zip file contains the Jupyter notebooks and python scripts for preprocessing the data, training the deep learning models, and postprocessing the results. The src.zip contains the source code for training the deep learning model, performing mutual information analysis, and plotting functions. The trained_models.zip contains multiple folders used for hosting the trained deep-learning models and the associated soil respiration predictions. The whole process is performed using python. We include the REAMD.md to document the python package requirements.Soil respiration in dryland ecosystems is challenging to model due to its complex interactions with environmental drivers. Knowledge-guided deep learning provides a much more effective means of accurately representing these complex interactions than traditional Q10-based models. Mutual information analysis revealed that future soil temperature shares more information with soil respiration than past soil temperature, consistent with their clockwise diel hysteresis. We explicitly encoded diel hysteresis, soil drying, and soil rewetting effects on soil respiration dynamics in a newly designed Long Short Term Memory (LSTM) model. The model takes both past and future environmental drivers as inputs to predict soil respiration. The new LSTM model substantially outperformed three Q10-based models and the Community Land Model when reproducing the observed soil respiration dynamics in a semi-arid ecosystem. The new LSTM model clearly demonstrated its superiority for temporally extrapolating soil respiration dynamics, such that the resulting correlation with observational data is up to 0.7 while the correlations of both Q10-based models and the Community Land Model (CLM) are less than 0.4. Our results underscore the high potential for knowledge-guided deep learning to replace Q10-based soil respiration modules in Earth system models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Genetic variation in nitrogen‐use efficiency and its associated traits in dryland winter wheat ( Triticum aestivum L.) cultivars released from the 1940s to the 2010s in Shaanxi Province, China

Abstract BACKGROUND Improving the nitrogen‐use efficiency (NUE) of wheat can help mitigate the problems of poor soil fertility under dryland conditions. We conducted field experiments using three nitrogen (N) fertilization levels (0, 120, and 180 kg ha −1 ) applied to eight dryland wheat cultivars to assess NUE and its associated traits. RESULTS The grain yield significantly increased with the improvement in variety, mainly as a result of a substantial increase in 1000‐grain weight and harvest index. Modern wheat varieties have stabilized at an optimal plant height and exhibited improved performance in terms of NUE, partial N productivity, N harvest index, and grain protein content compared to older varieties. The NUE of wheat gradually increased with variety replacement. The net photosynthesis rate of the flag leaves in the filling stage improved with the year of cultivar release; Increasing soil–plant analysis development (SPAD) values of flag leaves in the flowering and filling stages were observed over time, with the flag leaves of modern varieties showing a high chlorophyll content in the filling stage. Additionally, the principal component analysis showed that the SPAD value, grain number per unit area, transpiration rate, leaf area, and grain protein content positively contributed to the clustering of the N180 and modern cultivars (from the 2000s to 2010s). CONCLUSION Overall, high levels of N application did not significantly improve the NUE of wheat. However, modern wheat varieties can optimize N distribution, increase flag leaf photosynthetic capacity, and improve photosynthesis ability, thus enhancing NUE to achieve high yields under a suitable level of N supply. © 2022 Society of Chemical Industry.

Lian, Huida↗
DOE OSTI2023

Adaptation to climate change through strategic integration of long fallow into cropping system in a dryland Mediterranean-type environment

The crop-growing region of Western Australia characterized by a Mediterranean-type climate is projected to become warmer and drier. Appropriate selection of crop sequences will be of importance to cope with these climatic changes for this largest grain-producing region of Australia. Through linking a widely used crop model (APSIM), 26 General Circulation Models (GCMs) with one Shared Socioeconomic Pathway (SSP585) and economic analysis, we explored how the climate change would affect dryland wheat cropping and whether/how long fallow (the practice of leaving a field out of production for an entire growing season) could be integrated into wheat cropping system in Western Australia. The potential adaptation of long fallow into wheat system was assessed with four fixed rotations (fallow-wheat, fallow-wheat-wheat, fallow-wheat-wheat-wheat, and fallow-wheat-wheat-wheat-wheat) and four flexible sowing rule-based rotations (the land was fallowed if sowing rule was not met), compared with continuous wheat. The simulation results at four representing locations show that climate change would have negative impacts on both yield and economic return of continuous wheat cropping in Western Australia. Wheat after fallow out-yielded and out-profited wheat after wheat under future climate. But integrating fallow into wheat cropping systems with the above fixed rotations would lead to yield and economic loss. By contrast, cropping systems in which fallowing took place when sowing condition could not be met at a certain time would achieve comparable yield and economic return to continuous wheat, with wheat yield being only 5% less than continuous wheat and the gross margin being $12ha -1 more than continuous wheat averaged across locations. We highlight strategic integration of long fallow into cropping system in a dryland Mediterranean-type environment would have a great potential to cope with future climate change. These findings can be extended into other Mediterranean-type cropping regions in Australia and beyond.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Soil carbon storage capacity of drylands under altered fire regimes

The determinants of fire-driven changes in soil organic carbon (SOC) across broad environmental gradients remains unclear, especially in global drylands. Here we combined datasets and field sampling of fire-manipulation experiments to evaluate where and why fire changes SOC and compared our statistical model to simulations from ecosystem models. Drier ecosystems experienced larger relative changes in SOC than humid ecosystems—in some cases exceeding losses from plant biomass pools—primarily explained by high fire-driven declines in tree biomass inputs in dry ecosystems. Many ecosystem models underestimated the SOC changes in drier ecosystems. Upscaling our statistical model predicted that soils in savannah–grassland regions may have gained 0.64 PgC due to net-declines in burned area over the past approximately two decades. Consequently, ongoing declines in fire frequencies have probably created an extensive carbon sink in the soils of global drylands that may have been underestimated by ecosystem models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

New-generation geostationary satellite reveals widespread midday depression in dryland photosynthesis during 2020 western U.S. heatwave

Emerging new-generation geostationary satellites have broadened the scope for studying the diurnal cycle of ecosystem functions. We exploit observations from the Geostationary Operational Environmental Satellite-R series to examine the effect of a severe U.S. heatwave in 2020 on the diurnal variations of ecosystem photosynthesis. We find divergent responses of photosynthesis to the heatwave across vegetation types and aridity gradients, with drylands exhibiting widespread midday and afternoon depression in photosynthesis. The diurnal centroid and peak time of dryland gross primary production (GPP) substantially shift toward earlier morning times, reflecting notable water and heat stress. Our geostationary satellite-based method outperforms traditional radiation-based upscaling methods from polar-orbiting satellite snapshots in estimating daily GPP and GPP loss during heatwaves. These findings underscore the potential of geostationary satellites for diurnal photosynthesis monitoring and highlight the necessity to consider the increased diurnal asymmetry in GPP under stress when evaluating carbon-climate interactions.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2015

Reductions in Productivity Due to Land Degradation in the Drylands of the Southwestern United States

Dryland degradation has long been recognized at regional, national, and global scales, yet there are no objective assessments of its location and severity. An assessment of reductions in net primary production (NPP) due to dryland degradation in the southwestern United States is reported. The local NPP scaling (LNS) approach was applied to map the extent and magnitude of degradation. LNS seeks to identify reference sites in which there is no degradation that can be used as a standard for comparison with other sites that share the same environment, except for degradation. Twelve years were analyzed (2000–2011), using Normalized Difference Vegetation Index (NDVI) data (250 m) from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite‐borne multispectral sensor. The results indicated that the total NPP reductions in the study area were about 35.9 ± 4.7 Tg C/yr, which equates to 0.31 ± 0.04 Mg C/ha·y. The NPP reductions in grassland‐savanna and livestock grazing areas were large and mostly consistent between years in spite of large variations in overall NPP caused by differences in land‐use, interannual variations in rainfall, and other aspects of weather. In comparison with other cover types, forested land generally had higher NPP reduction per unit area. The maps also enable attribution of degradation from the finest management units to entire agencies, such as the Bureau of Land Management, which had 50% less production per unit area than the U.S. Forest Service. The degradation within Native American land was low with total NPP reduction of about 2.41 ± 0.24 Tg C/yr and unit area reduction of productivity of just 0.21 ± 0.02 Mg C/ha·yr, yet the percent reduction from potential was in equivalence with other land management agencies.

Noojipady, Praveen↗
DOE OSTI2020

Reducing nitrous oxide emissions and optimizing nitrogen-use efficiency in dryland crop rotations with different nitrogen rates

Recent interests in improving agricultural production while minimizing environmental footprints emphasized the need for research on management strategies that reduce nitrous oxide (N 2 O) emissions and increase nitrogen-use efficiency (NUE) of cropping systems. This study aimed to evaluate N 2 O emissions, annualized crop grain yield, emission factor, and yield-scaled- and NUE-scaled N 2 O emissions under continuous spring wheat (Triticum aestivum L.) (CW) and spring wheat-pea (Pisum sativum L.) (WP) rotations with four N fertilization rates (0, 50, 100, and 150 kg N ha(-1)). The N 2 O fluxes peaked immediately after N fertilization, intense precipitation, and snowmelt, which accounted for 75-85% of the total annual flux. Cumulative N 2 O flux usually increased with increased N fertilization rate in all crop rotations and years. Annualized crop yield and NUE were greater in WP than CW for 0 kg N ha(-1) in all years, but the trend reversed with 100 kg N ha(-1) in 2013 and 2015. Crop yield maximized at 100 kg N ha(-1), but NUE declined linearly with increased N fertilization rate in all crop rotations and years. As N fertilization rate increased, N fertilizer-scaled N2O flux decreased, but NUE-scaled N 2 O flux increased non-linearly in all years, regardless of crop rotations. The yield-scaled N 2 O flux decreased from 0 to 50 kg N ha -1 and then increased with increased N fertilization rate. Because of non-significant difference of N 2 O fluxes between 50 and 100 kg N ha(-1), but increased crop yield, N 2 O emissions can be minimized while dryland crop yields and NUE can be optimized with 100 kg N ha -1 , regardless of crop rotations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Chronostratigraphy of talus flatirons and piedmont alluvium along the Book Cliffs, Utah – Testing models of dryland escarpment evolution

Research on the evolution of dryland escarpments and what drives and controls their erosional retreat have been limited by a lack of chronologically constrained records. Prior investigations of escarpments in the southwestern U.S. and globally garner two endmember conceptual models -- one focused on bottom-up baselevel drivers and autogenic variations in piedmont and toeslope erosion processes, the other focused on the role of climate as a top-down forcing mechanism on sediment production and transport from cliffs. In this work, we test these conceptual models along a section of the Book Cliffs in central Utah, where climate has varied strongly and baselevel has fallen significantly over the late Quaternary. Four generations of talus flatirons and piedmont terraces are preserved in the study area we date them by optically stimulated luminescence and 10Be-exposure techniques. OSL depositional ages cluster into four generations of deposits with mean ages and mean standard errors of 117.8 ± 6.7 ka, 83.4 ± 3.3 ka, 52.4 ± 1.8 ka, and 5.6 ± 0.3 ka. 10Be-exposure results from talus boulders protruding from flatirons confirm that the youngest generation of talus is Holocene, with recent rock-fall boulders still being received on the landform top. Older flatiron generations produce incoherent, minimum exposure ages reflecting an increasing dominance of in situ boulder weathering and a steady-state denudation rate of ~45 mm/ky after tens of thousands of years. Based on the chronostratgraphy and correlation of talus and piedmont deposits, we interpret climate as the primary control on escarpment evolution. Depositional ages do not correspond to glacial epochs as historically presumed, but instead to episodes of intermediate and unstable or variable Pleistocene climate during Marine Isotope Stage-3 and 5 a/b. Results support the significance of high climate variability at millennial timescales in driving both sediment production by mass wasting from the cliff as well as sediment storage and reworking along the piedmont. In contrast, wetter climates of glacial epochs apparently caused greater erosion and sediment transport to trunk drainages. Our chronology also reveals a systematic decrease in deposit age with increasing distance up the piedmont from the regional baselevel of the Price River, consistent with transient fluvial incision and terrace abandonment. The Book Cliffs record notably does not correlate with similarly constrained records in Spain or the contrasting record from the Negev, yet they all share the feature of enhanced talus deposition and cliff retreat corresponding to climate instability rather than in response to steady glacial-climate conditions. Thus, we outline a model of escarpment evolution and retreat governed largely by top-down climate-forcing of sediment production and transport during climate variability, with local changes in baselevel and erosional processes on the piedmont being a modifying, secondary factor.

58 GEOSCIENCES↗