Geology topics

Temuulen T. Sankey

Publications and source records attributed to Temuulen T. Sankey.

At least 19 recordsLinked to original sources

USGS2023

Multi-year tracing of spatial and temporal dynamics of post-fire aeolian sediment transport using rare earth elements provide insights into grassland management

Aeolian sediment transport occurs as a function of, and with feedback to ecosystem changes and disturbances. Many desert grasslands are undergoing rapid changes in vegetation, including the encroachment of woody plants, which alters fire regimes and in turn can change the spatial and temporal patterns of aeolian sediment transport. We investigated aeolian sediment transport and spatial distribution of sediment in the surface soil for 7 years following a prescribed fire using a multiple rare earth element (REE) tracer-based approach in a shrub-encroached desert grassland in the northern Chihuahuan desert. Results indicate that even though the aeolian horizontal sediment mass flux increased approximately three-fold in the first windy season in the burned areas compared to control areas, there were no significant differences after three windy seasons. The soil surface of bare microsites was the major contributor of aeolian sediments in unburned areas (87%), while the shrub microsites contributed the least (<2%) during the observation period. However, after the prescribed fire, the contribution of aeolian sediments from shrub microsites increased considerably (∼40%), indicating post-fire microsite-scale sediment redistribution. The findings of this study, which is the first to use multiple REE tracers for multi-year analysis of the spatial and temporal dynamics of aeolian sediment transport, illustrate how disturbance by prescribed fire can influence aeolian processes and alters dryland soil geomorphology in which distinct soils develop over time at very fine spatial scales of individual plants.

New Mexico↗

USGS2022

Soil moisture response to seasonal drought conditions and post-thinning forest structure

Prolonged drought conditions in semi-arid forests can lead to widespread vegetation stress and mortality. However, the distribution of these effects is not spatially uniform. We measured soil water potential at high spatial and temporal resolution using 112 sensors distributed across a ponderosa pine forest in northern Arizona, USA, during two abnormally dry years with below-average total precipitation. We used the data to assess the effects of fore-summer drought period on the timing, magnitude, and extent of drying throughout the top 100 cm of the soil profile. Additionally, we use high spatial resolution terrestrial lidar measurements of forest structure to develop relationships between soil drying and fine-scale forest structure. We find that increasing drought from 2019 to 2020 caused significantly earlier onset of soil dying at all depths (25, 50 and 100 cm) and more days below a critical drying threshold for ponderosa pine. Additionally, our results show that significantly drier soils are found in areas with higher stand-level basal area, canopy cover and tree density, and shorter trees. Our results from the unprecedented spatial and temporal resolution data suggest that tailored restoration thinning with specific tree density and size parameters can be used to increase and prolong the availability of deep soil water to trees during drought.

Ecohydrology↗

USGS2021

Carbon and ecohydrological priorities in managing woody encroachment: UAV perspective 63 years after a control treatment

Woody encroachment, including both woody species expansion and density increase, is a globally observed phenomenon that deteriorates arid and semi-arid rangeland health, biodiversity, and ecosystem services. Mechanical and chemical control treatments are commonly performed to reduce woody cover and restore ecohydrologic function. While the immediate impacts of woody control treatments are well documented in short-term studies, treatment impacts at decadal scales are not commonly studied. Using a controlled herbicide treatment from 1954 in the Sierra Ancha Experimental Forest in central Arizona, USA, we quantify woody encroachment and associated aboveground carbon accumulation in treated and untreated watersheds. Woody encroachment and aboveground carbon are estimated using high resolution multispectral images and photogrammetric data from a fixed-wing unmanned aerial vehicle (UAV). We then combine the contemporary UAV image-derived estimates with historical records from immediately before and after the treatment to consider long-term trends in woody vegetation cover, aboveground carbon, water yield, and sedimentation. Our results indicate that the treatment has had a lasting impact. More than six decades later, woody cover in two treated watersheds are still significantly lower compared to two control watersheds, even though woody cover increased in all four drainages. Aboveground woody carbon in the treated watersheds is approximately one half that accumulated in the control watersheds. The historical records indicate that herbicide treatment also increased water yield and reduced annual sedimentation. Given the sustained reduction in woody cover and aboveground woody biomass in treated watersheds, we infer that the herbicide treatment has had similarly long lasting impacts on ecohydrological function. Land managers can consider legacy impacts from control treatments to better balance carbon and ecohydrological consequences of woody encroachment and treatment activities.

Environmental Research Letters↗

USGS2021

Hydrologic and geomorphic effects on riparian plant species occurrence and encroachment: Remote sensing of 360 km of the Colorado River in Grand Canyon

A common impact on riparian ecosystem function following river regulation is the expansion and encroachment of riparian plant species in the active river channels and floodplain, which reduces flow of water and suspended sediment between the river, riparian area, and upland ecosystems. We characterized riparian plant species occurrence and quantified encroachment within the dam-regulated Colorado River in Grand Canyon, Arizona, USA. We mapped 10 riparian species with high-resolution multispectral imagery and examined effects of river hydrology and geomorphology on the spatial distribution of plant species and open sand. Analysis spanned an image time-series from 2002-2009-2013; a period when plant species and sand were spatially dynamic, and operations of Glen Canyon Dam included daily hydro-peaking and small episodic controlled flood releases. Plant species occurrence and encroachment rates varied with hydrology, geomorphology, and local species pool. Encroachment was greatest on surfaces frequently inundated by hydro-peaking. Seep willow ( Baccharis spp .), tamarisk ( Tamarix spp .) and arrowweed ( Pluchea sericea ) were the primary encroaching woody species. Common reed ( Phragmites australis ) and horsetail ( Equisetum xferrissii ) were the primary encroaching herbaceous species. Encroachment composition from 2002 to 2009 was similar to the entire riparian landscape, whereas encroachment from 2009 to 2013 primarily consisted of seep willow and early-colonizing herbaceous species. Emergence of seep willow and arrowweed after burial by sand deposited by controlled floods indicated that those species were resilient to this form of disturbance. Describing patterns of species encroachment is an important step towards designing flow regimes that favor riparian species and ecosystem functions valued by stakeholders.

Arizona↗

USGS2021

UAV-based estimate of snow cover dynamics: Optimizing semi-arid forest structure for snow persistence

Seasonal snow cover in the dry forests of the American West provides essential water resources to both human and natural systems. The structure of trees and their arrangement across the landscape are important drivers of snow cover distribution across these forests, varying widely in both space and time. We used unmanned aerial vehicle (UAV) multispectral imagery and Structure-from-Motion (SfM) models to quantify rapidly melting snow cover dynamics and examine the effects of forest structure shading on persistent snow cover in a recently thinned ponderosa pine forest. Using repeat UAV multispectral imagery (n = 11 dates) across the 76 ha forest, we first developed a rapid and effective method for identifying persistent snow cover with 90.2% overall accuracy. The SfM model correctly identified 98% (n = 1280) of the trees, when compared with terrestrial laser scanner validation data. Using the SfM-derived forest structure variables, we then found that canopy shading associated with the vertical and horizontal metrics was a significant driver of persistent snow cover patches ( R 2 = 0.70). The results indicate that UAV image-derived forest structure metrics can be used to accurately predict snow patch size and persistence. Our results provide insight into the importance of forest structure, specifically canopy shading, in the amount and distribution of persistent seasonal snow cover in a typical dry forest environment. An operational understanding of forest structure effects on snow cover will help drive forest management that can target snow cover dynamics in addition to forest health.

Arizona↗

USGS2021

Monitoring Tamarix changes using WorldView-2 satellite imagery in Grand Canyon National Park, Arizona

Remote sensing methods are commonly used to monitor the invasive riparian shrub tamarisk ( Tamarix spp. ) and its response to the northern tamarisk beetle ( D. carinulata ), a specialized herbivore introduced as a biocontrol agent to control tamarisk in the Southwest USA in 2001. We use a Spectral Angle Mapper (SAM) supervised classification method with WorldView-2 (2 m spatial resolution) multispectral images from May and August of 2019 to map healthy tamarisk, canopy dieback, and defoliated tamarisk over a 48 km segment of the Colorado River in the topographically complex Grand Canyon National Park, where coarse-resolution satellite images are of limited use. The classifications in May and August produced overall accuracies of 80.0% and 83.1%, respectively. Seasonal change detection between May and August 2019 indicated that 47.5% of the healthy tamarisk detected in May 2019 had been defoliated by August 2019 within the WorldView-2 image extent. When compared to a previously published tamarisk map from 2009, derived from multispectral aerial imagery, we found that 29.5% of healthy tamarisk canopy declined between 2009 and 2019. This implies that tamarisk beetle impacts are continuing to accumulate even though land managers have noted the presence of the beetles in this reach of the river for 7 years since 2012.

Arizona↗

USGS2021

Biocrust and the soil surface: Influence of climate, disturbance, and biocrust recovery on soil surface roughness

Biocrust communities promote soil surface roughness, a key functional characteristic for soil ecology. However, the spatial scales at which biocrust communities contribute to surface roughness are not well understood. To refine our understanding of the spatial dynamics between biocrust and soil surface roughness, we used mm-resolution terrestrial LiDAR to measure micro-topographic roughness at seven sub-meter, 3-dimensional kernels (spatial scales) for undisturbed and disturbed biocrusts within the cool Great Basin and the hot Chihuahuan Deserts of western North America. This multi-scalar approach applied within the different desert regions allowed us to explore two objectives: 1) assess the relative importance of climate and disturbance on biocrust roughness, and 2) evaluate how soil surface roughness evolves with biocrust recovery. For objective 1, we found that undisturbed cool desert biocrust was up to three times rougher than hot desert biocrust. Much of the difference in roughness between the two desert biocrust communities appeared to be from climate or other regional factors. However, positive correlations between roughness and biocrust indicators, including soil chlorophyll-a and the field-based Level of Development (LOD) index, suggested that differences in roughness at spatial scales ≤ 10 cm are directly related to biocrust development. Mechanical disturbance aimed at removing biocrust resulted in significant reductions in roughness and removed much of the observed differences in roughness between cool and hot desert soils. We evaluated biocrust recovery within the cool desert study area two years after mechanical disturbance and found that the disturbed soil increased in roughness up-to 300%. The increased surface roughness at spatial scales ≤ 10 cm were positively correlated with increased aggregate stability and indicators of biocrust reestablishment. We found that topographic change area was also an important contributor to roughness at all spatial scales, particularly at spatial scales ≥ 20 cm where it was the most important factor evaluated. These results provide insight into how biocrust interacts with other biophysical processes to influence soil surface roughness and how soil surfaces evolve at time scales relevant to soil restoration activities.

New Mexico, Utah↗

USGS2021

Quantifying plant-soil-nutrient dynamics in rangelands: Fusion of UAV hyperspectral-LiDAR, UAV multispectral-photogrammetry, and ground-based LiDAR-digital photography in a shrub-encroached desert grassland

Rangelands cover 70% of the world's land surface, and provide critical ecosystem services of primary production, soil carbon storage, and nutrient cycling. These ecosystem services are governed by very fine-scale spatial patterning of soil carbon, nutrients, and plant species at the centimeter-to-meter scales, a phenomenon known as “islands of fertility”. Such fine-scale dynamics are challenging to detect with most satellite and manned airborne platforms. Remote sensing from unmanned aerial vehicles (UAVs) provides an alternative option for detecting fine-scale soil nutrient and plant species changes in rangelands tn0020 smaller extents. We demonstrate that a model incorporating the fusion of UAV multispectral and structure-from-motion photogrammetry classifies plant functional types and bare soil cover with an overall accuracy of 95% in rangelands degraded by shrub encroachment and disturbed by fire. We further demonstrate that employing UAV hyperspectral and LiDAR fusion greatly improves upon these results by classifying 9 different plant species and soil fertility microsite types (SFMT) with an overall accuracy of 87%. Among them, creosote bush and black grama, the most important native species in the rangeland, have the highest producer's accuracies at 98% and 94%, respectively. The integration of UAV LiDAR-derived plant height differences was critical in these improvements. Finally, we use synthesis of the UAV datasets with ground-based LiDAR surveys and lab characterization of soils to estimate that the burned rangeland potentially lost 1474 kg/ha of C and 113 kg/ha of N owing to soil erosion processes during the first year after a prescribed fire. However, during the second-year post-fire, grass and plant-interspace SFMT functioned as net sinks for sediment and nutrients and gained approximately 175 kg/ha C and 14 kg/ha N, combined. These results provide important site-specific insight that is relevant to the 423 Mha of grasslands and shrublands that are burned globally each year. While fire, and specifically post-fire erosion, can degrade some rangelands, post-fire plant-soil-nutrient dynamics might provide a competitive advantage to grasses in rangelands degraded by shrub encroachment. These novel UAV and ground-based LiDAR remote sensing approaches thus provide important details towards more accurate accounting of the carbon and nutrients in the soil surface of rangelands.

New Mexico↗

USGS2019

UAV-derived estimates of forest structure to inform ponderosa pine forest restoration

Restoring forest ecosystems has become an increasingly high priority for land managers across the American West. Millions of hectares of forest are in need of drastic yet strategic reductions in density (e.g., basal area). Meeting the restoration and management goals requires quantifying metrics of vertical and horizontal forest structure, which has relied upon field‐based measurements, manned airborne or satellite remote sensing datasets. We used unmanned aerial vehicle (UAV ) image‐derived Structure‐from‐Motion (SfM) models and high‐resolution multispectral orthoimagery in this study to quantify vertical and horizontal forest structure at both the fine‐ (<4 ha) and mid‐scales (4–400 ha) across a forest density gradient. We then used these forest structure estimates to assess specific objectives of a forest restoration treatment. At the fine‐scale, we found that estimates of individual tree height and canopy diameter were most accurate in low‐density conditions, with accuracies degrading significantly in high‐density conditions. Mid‐scale estimates of canopy cover and forest density followed a similar pattern across the density gradient, demonstrating the effectiveness of UAV image‐derived estimates in low‐ to medium‐density conditions as well as the challenges associated with high‐density conditions. We found that post‐treatment conditions met a majority of the prescription objectives and demonstrate the UAV image application in quantifying changes from a mechanical thinning treatment. We provide a novel approach to forest restoration monitoring using UAV ‐derived data, one that considers varying density conditions and spatial scales. Future research should consider a more spatially extensive sampling design, including different restoration treatments, as well as experimenting with different combinations of equipment, flight parameters, and data processing workflows.

Western United States↗

USGS2019

Invasive buffelgrass detection using high-resolution satellite and UAV imagery on Google Earth Engine

Methods to detect and monitor the spread of invasive grasses are critical to avoid ecosystem transformations and large economic costs. The rapid spread of non‐native buffelgrass (Pennisetum ciliare) has intensified fire risk and is replacing fire intolerant native vegetation in the Sonoran Desert of the southwestern US. Coarse‐resolution satellite imagery has had limited success in detecting small patches of buffelgrass, whereas ground‐based and aerial survey methods are often cost prohibitive. To improve detection, we trained 2 m resolution DigitalGlobe WorldView‐2 satellite imagery with 12 cm resolution unmanned aerial vehicle (UAV) imagery and classified buffelgrass on Google Earth Engine, a cloud computing platform, using Random Forest (RF) models in Saguaro National Park, Arizona, USA. Our classification models had an average overall accuracy of 93% and producer's accuracies of 94–96% for buffelgrass, although user's accuracies were low. We detected a 2.92 km 2 area of buffelgrass in the eastern Rincon Mountain District (1.07% of the total area) and a 0.46 km 2 area (0.46% of the total area) in the western Tucson Mountain District of Saguaro National Park. Buffelgrass cover was significantly greater in the Sonoran Paloverde‐Mixed Cacti Desert Scrub vegetation type, on poorly developed Entisols and Inceptisol soils and on south‐facing topographic aspects compared to other areas. Our results demonstrate that high‐resolution imagery improve on previous attempts to detect and classify buffelgrass and indicate potential areas where the invasive grass might spread. The methods demonstrated in this study could be employed by land managers as a low‐cost strategy to identify priority areas for control efforts and continued monitoring.

Arizona↗

USGS2019

Using oblique imagery to measure hypsometric changes in sandbar volume following controlled floods in the Grand Canyon

Measuring changes in the elevation distribution of sub-aerial fine (< 2 mm ) sediment and estimating sandbar volume multiple times per year can improve sediment budget calculations in fluvial systems. In the Grand Canyon of the Colorado River, effects of dam operations on sandbar size and distribution is of long-term management interest. Bar-building controlled floods have been implemented in 1996, 2004, 2008, 2012, 2013, 2014, 2016, and 2018 to mitigate sandbar erosion. Annual topographic surveys provide a single measurement of sandbar change caused by the integrated effects of all flows in one year (both controlled floods and normal dam releases), but do not measure erosion and deposition caused by specific operations or individual floods. On one sandbar monitoring site in Grand Canyon, we demonstrate that imagery from autonomous digital cameras can be used to provide quantitative measures of sandbar hypsometry several times per year without costly and labor-intensive surveys. We describe methods for measuring changes in the storage of fine sediment at monthly or seasonal timescales by constructing hypsometric (area-elevation relation) curves. These curves are created and updated with sandbar area measurements from georectified images taken multiple times each day. As the water surface elevation fluctuates with daily, seasonal, and monthly discharge patterns, sandbar area and volume can be estimated using known stage-discharge relationships. We present parameters extracted from image-derived hypsometries to estimate sandbar volume and elevation relief ratio, which provides a new way to quantitatively measure monthly or seasonal changes in fine sediment storage.

Arizona↗

USGS2018

Examining forest structure with terrestrial lidar: Suggestions and novel techniques based on comparisons between scanners and forest treatments

Terrestrial laser scanners (TLSs) provide a tool to assess and monitor forest structure across forest landscapes. We present TLS methods, suggestions, and mapped guidelines for planning TLS acquisitions at varying scales and forest densities. We examined rates of point‐density decline with distance from two TLS that acquire data at relatively high and low point density and found that the rates were nearly identical between scanners ( p value <0.01), suggesting that our findings are applicable to a range of TLS types. Using unique, TLS‐adapted processing methods, we determined the relative accuracy of TLS‐derived plot‐scale estimates of tree height, diameter‐at‐breast‐height, height‐to‐canopy, tree counts, as well as treatment‐scale tree density and patch metrics, using both high point density and low point density TLS among thinned and nonthinned forest treatments. The high‐density TLS consistently provides more accurate estimates of plot‐level metrics ( R 2 = 0.46 to 0.87) than the low‐density TLS (R 2 = −0.14 to 0.53). At treatment scales, tree density estimates are similar among scanners ( R 2 = 0.95 vs. 0.71), as are canopy cover and patch metrics. We develop and present the normalized density‐distance index (NDDI), which can account for up to 59% of the variance in estimate error and can be used to guide TLS‐data acquisition plans. This index indicates whether a given location has generally higher point density (higher NDDI) relative to the distance from the scanner and can be used as a proxy for uncertainty. Using NDDI as a guide for fair comparison between scanners, both plot‐ and treatment‐scale estimates improved.

Earth and Space Science↗

USGS2018

Remote sensing of tamarisk beetle (Diorhabda carinulata) impacts along 412 km of the Colorado River in the Grand Canyon, Arizona, USA

Tamarisk ( Tamarix spp.) is an invasive plant species that is rapidly expanding along arid and semi-arid rivers in the western United States. A biocontrol agent, tamarisk beetle ( Diorhabda carinulata ), was released in 2001 in California, Colorado, Utah, and Texas. In 2009, the tamarisk beetle was found further south than anticipated in the Colorado River ecosystem within the Grand Canyon National Park and Glen Canyon National Recreation Area. Our objectives were to classify tamarisk stands along 412 km of the Colorado River from the Glen Canyon Dam through the Grand Canyon National Park using 2009 aerial, high spatial resolution multispectral imagery, and then quantify tamarisk beetle impacts by comparing the pre-beetle images from 2009 with 2013 post-beetle images. We classified tamarisk presence in 2009 using the Mahalanobis Distance method with a total of 2500 training samples, and assessed the classification accuracy with an independent set of 7858 samples across 49 image quads. A total of 214 ha of tamarisk were detected in 2009 along the Colorado River, where each image quad, on average, included an 8.4 km segment of the river. Tamarisk detection accuracies varied across the 49 image quads, but the combined overall accuracy across the entire study region was 74%. Using the Normalized Difference Vegetation Index (NDVI) from 2009 and 2013 with a region-specific ratio of >1.5 decline between the two image dates (2009NDVI/2013NDVI), we detected tamarisk defoliation due to beetle herbivory. The total beetle-impacted tamarisk area was 32 ha across the study region, where tamarisk defoliation ranged 1–86% at the local levels. Our tamarisk classification can aid long-term efforts to monitor the spread and impact of the beetle along the river and the eventual mortality of tamarisk due to beetle impacts. Identifying areas of tamarisk defoliation is a useful ecological indicator for managers to plan restoration and tamarisk removal efforts.

Arizona↗

USGS2018

Mapping and measuring aeolian sand dunes with photogrammetry and LiDAR from unmanned aerial vehicles (UAV) and multispectral satellite imagery on the Paria Plateau, AZ, USA

The Paria Plateau is a potentially important but relatively unstudied aeolian sand source area in the Grand Canyon region of Arizona, USA. This study used unmanned aerial vehicle(UAV) - based LiDAR and structure-from-motion (SfM) photogrammetry to produce high-resolution topographic models of aeolian dunes on the plateau. We combined the dune topography data with a high-resolution satellite image maximum likelihood classification (producer's accuracy = 87.2%) to quantify potential aeolian sand source areas across the 958 km 2 plateau. We mapped all the unvegetated active aeolian dunes on the plateau and estimate they contain 24 Tg of sand, and could, therefore, be a proportionately important regional sand source considering the annual sand loads of the downwind Paria River at its confluence with the Colorado River are generally <1 Tg. The results and data from this study could be useful for future investigations that wish to explicitly link aeolian sand on the Paria Plateau to downwind sediment dynamics in the region. The methodology for UAV and satellite remote sensing that we demonstrate could be applied to quantify sand at large geographic extents in other aeolian environments around the world.

Arizona↗

USGS2017

Climate, wildfire, and erosion ensemble foretells more sediment in western USA watersheds

The area burned annually by wildfires is expected to increase worldwide due to climate change. Burned areas increase soil erosion rates within watersheds, which can increase sedimentation in downstream rivers and reservoirs. However, which watersheds will be impacted by future wildfires is largely unknown. Using an ensemble of climate, fire, and erosion models, we show that post-fire sedimentation is projected to increase for nearly nine-tenths of watersheds by > 10% and for more than one-third of watersheds by > 100% by the 2041 to 2050 decade in the western USA. The projected increases are statistically significant for more than eight-tenths of the watersheds. In the western USA, many human communities rely on water from rivers and reservoirs that originates in watersheds where sedimentation is projected to increase. Increased sedimentation could negatively impact water supply and quality for some communities, in addition to affecting stream channel stability and aquatic ecosystems.

Geophysical Research Letters↗

USGS2017

UAV lidar and hyperspectral fusion for forest monitoring in the southwestern USA

Forest vegetation classification and structure measurements are fundamental steps for planning, monitoring, and evaluating large-scale forest changes including restoration treatments. High spatial and spectral resolution remote sensing data are critically needed to classify vegetation and measure their 3-dimensional (3D) canopy structure at the level of individual species. Here we test high-resolution lidar, hyperspectral, and multispectral data collected from unmanned aerial vehicles (UAV) and demonstrate a lidar-hyperspectral image fusion method in treated and control forests with varying tree density and canopy cover as well as in an ecotone environment to represent a gradient of vegetation and topography in northern Arizona, U.S.A. The fusion performs better (88% overall accuracy) than either data type alone, particularly for species with similar spectral signatures, but different canopy sizes. The lidar data provides estimates of individual tree height ( R 2 = 0.90; RMSE = 2.3 m) and crown diameter ( R 2 = 0.72; RMSE = 0.71 m) as well as total tree canopy cover ( R 2 = 0.87; RMSE = 9.5%) and tree density ( R 2 = 0.77; RMSE = 0.69 trees/cell) in 10 m cells across thin only, burn only, thin-and-burn, and control treatments, where tree cover and density ranged between 22 and 50% and 1–3.5 trees/cell, respectively. The lidar data also produces highly accurate digital elevation model (DEM) ( R 2 = 0.92; RMSE = 0.75 m). In comparison, 3D data derived from the multispectral data via structure-from-motion produced lower correlations with field-measured variables, especially in dense and structurally complex forests. The lidar, hyperspectral, and multispectral sensors, and the methods demonstrated here can be widely applied across a gradient of vegetation and topography for monitoring landscapes undergoing large-scale changes such as the forests in the southwestern U.S.A.

Arizona↗

USGS2016

Four-band image mosaic of the Colorado River corridor downstream of Glen Canyon Dam in Arizona, derived from the May 2013 airborne image acquisition

In May 2013, the U.S. Geological Survey’s Grand Canyon Monitoring and Research Center acquired airborne multispectral high-resolution data for the Colorado River in the Grand Canyon, Arizona. The image data, which consist of four color bands (blue, green, red, and near-infrared) with a ground resolution of 20 centimeters, are available to the public as 16-bit geotiff files at http://dx.doi.org/10.5066/F7TX3CHS . The images are projected in the State Plane map projection, using the central Arizona zone (202) and the North American Datum of 1983. The assessed accuracy for these data is based on 91 ground-control points and is reported at the 95-percent confidence level as 0.64 meter (m) and a root mean square error of 0.36 m. The primary intended uses of this dataset are for maps to support field data collection and simple river navigation; high-spatial-resolution change detection of sandbars, other geomorphic landforms, riparian vegetation, and backwater and nearshore habitats; and other ecosystem-wide mapping.

Arizona↗

USGS2016

Decadal shifts in grass and woody plant cover are driven by prolonged drying and modified by topo‐edaphic properties

Woody plant encroachment and overall declines in perennial vegetation in dryland regions can alter ecosystem properties and indicate land degradation, but the causes of these shifts remain controversial. Determining how changes in the abundance and distribution of grass and woody plants are influenced by conditions that regulate water availability at a regional scale provides a baseline to compare how management actions alter the composition of these vegetation types at a more local scale and can be used to predict future shifts under climate change. Using a remote‐sensing‐based approach, we assessed the balance between grasses and woody plants and how climate and topo‐edaphic conditions affected their abundances across the northern Sonoran Desert from 1989 to 2009. Despite widespread woody plant encroachment in this region over the last 150 years, we found that leguminous trees, including mesquite ( Prosopis spp.), declined in cover in areas with prolonged drying conditions during the early 21st century. Creosote bush ( Larrea tridentata ) also had moderate decreases with prolonged drying but was buffered from changes on soils with low clay that promote infiltration and high available water capacity that allows for retention of water at depth. Perennial grasses have expanded and contracted over the last two decades in response to summer precipitation and were especially dynamic on shallow soils with high clay that have large fluctuations in water availability. Our results suggest that topo‐edaphic properties can amplify or ameliorate climate‐induced changes in woody plants and perennial grasses. Understanding these relationships has important implications for ecosystem function under climate change in the southwestern USA and can inform management efforts to regulate grass and woody plant abundances.

Arizona↗