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Sedimentary landforms on Earth and other planetary bodies are built through scour, transport, and deposition of sediment. Sediment connectivity refers to the hypothesis that pathways of sediment transport do not occur in isolation, but rather are mechanistically linked. In dryland river systems, one such example of sediment connectivity is the transport of fluvially deposited sediment by wind. However, predictive tools that can forecast fluvial‐aeolian sediment connectivity at meaningful scales are rare. Here we develop a suite of models for quantifying the availability of river‐sourced sediment for aeolian transport as a function of river flow, wind regime, and land cover across 168 km of the Colorado River in Grand Canyon, USA. We compare and validate these models using topographic changes observed over 10 years in a coupled river sandbar‐aeolian dunefield setting. The models provide a path forward for directly linking fluvial hydrology with the management and understanding of aeolian landscapes. Plain Language Summary: Landscapes on Earth are built from sediment, which is deposited by a variety of processes, especially water and wind. In rivers located in dry regions, sediment is deposited by flowing water during river floods. Once this sediment dries, it is often then moved by wind across the landscape. Although we frequently observe this sediment connectivity between water and wind, we are not currently able to predict when and where windblown transport of river‐deposited sediment may occur. We used maps of sand in Grand Canyon along 168 km of the Colorado River, along with records of river flow, wind speed, and vegetation cover, to develop four models that predict how much sediment is available for wind to move. We compared the results of these models to actual windblown sediment transport at a study site in Grand Canyon, finding that when models predicted more sand was available at the site, we also observed more landscape changes there which were due to wind. Our research makes it possible to understand how changes in river flows affect the amount of sediment moved by wind. Key Points: We developed four methods for modeling the extent of exposed, bare sand available for windblown transport in river valleysOur models employ data on river flow, land cover, wind velocity, and vegetation to predict exposed, bare sand extent at corridor scalesWhere models predict increased areal extent of bare sand, we also observe a greater volume of topographic changes driven by wind [ABSTRACT FROM AUTHOR]

Rivers and their adjacent riparian zones are model ecosystems for observing cross‐ecosystem energy transfers. Aquatic insects emerging from streams, for example, are resource subsidies that support riparian consumers such as birds, spiders, lizards, and bats. We collaborated with recreational river runners in Grand Canyon, Arizona, USA, to record acoustic bat activity and sample riparian insects using light traps at dusk from April through October 2017–2020. River runners collected these data on 1,428 events over 611 sampling nights at 410 sites throughout a 470‐km segment of the Colorado River. We documented 71 insect taxa in light traps and recorded 19 bat species with acoustic detectors. We hypothesized that bat activity along this highly regulated river segment would be influenced primarily by variation in prey availability, as compared to other habitat descriptors. We predicted that bat activity would be positively related to aquatic insect catch rates and unrelated to terrestrial insect abundance. We fit Bayesian regression models to test these hypotheses and to quantify the relationship between bat activity and a suite of environmental variables: time of year, time of day, distance from perennial tributaries, distance from rapids, channel width, geomorphic reach, tall vegetation cover, air temperature, and lunar phase. Bat activity was positively related to the abundance of aquatic flies (Diptera), which outcompeted all other prey categories and structural habitat descriptors in our models. Within our dusk sampling period, activity of small myotis (California myotis [Myotis californicus] and Yuma myotis [M. yumanensis]) was high late in the evening and canyon bats (Parastrellus hesperus), conversely, were more active early in the evening. Activity of canyon bats varied seasonally, with peak activity in August. Our results support the hypothesis that aquatic prey, specifically aquatic flies, are key predictors of bat activity along a large, regulated river corridor and demonstrate the power of community science as a tool for ecosystem monitoring. [ABSTRACT FROM AUTHOR]

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 characterised 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 to 2009 to 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 colonising 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 favour riparian species and ecosystem functions valued by stakeholders. [ABSTRACT FROM AUTHOR]

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 (R2 = 0.46 to 0.87) than the low‐density TLS (R2 = −0.14 to 0.53). At treatment scales, tree density estimates are similar among scanners (R2 = 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. Plain Language Summary: We compared two ground‐based lidar instruments, an expensive unit that captures dense data and a constructed, inexpensive unit that produces relatively low‐density data. We wanted to understand how well these units capture forest structure, including tree heights, diameters, and canopy cover as well as how to better place these scanners on a landscape to capture better data. We found that the more expensive lidar better captures forest attributes at small landscape scales, but the difference between the two diminishes as you reach larger spatial scales. We also found that the rate at which the point density declines is approximately the same between the two lidars, suggesting that these findings are applicable across a range of ground‐based lidar instruments. Finally, we came up with suggestions and some mapped guidelines on how to best arrange lidar instruments across a landscape in which the density of trees is variable. The methods we use here are applicable many types of forest‐related questions, including biomass, carbon capture, and growth through time. Key Points: TLS can provide accurate forest structure metrics below the canopy across a range of spatial extentsHigh‐density TLS is needed for most metrics, while low‐density TLS provides reasonable estimates of canopy height and tree densityMultiple lines of evidence are used to determine optimal scanner‐location schemes for data collection among variable forest density [ABSTRACT FROM AUTHOR]

The aerodynamic roughness length (Z0m) serves an important role in the flux exchange between the land surface and atmosphere. In this study, airborne lidar (ALS), terrestrial lidar (TLS), and imaging spectroscopy data were integrated to develop and test two approaches to estimate Z0m over a shrub dominated dryland study area in south-central Idaho, USA. Sensitivity of the two parameterization methods to estimate Z0m was analyzed. The comparison of eddy covariance-derived Z0m and remote sensing-derived Z0m showed that the accuracy of the estimated Z0m heavily depends on the estimation model and the representation of shrub (e.g., Artemisia tridentata subsp. wyomingensis) height in the models. The geometrical method (RA1994) led to 9 percent (~0.5 cm) and 25% (~1.1 cm) errors at site 1 and site 2, respectively, which performed better than the height variability-based method (MR1994) with bias error of 20 percent and 48 percent at site 1 and site 2, respectively. The RA1994 model resulted in a larger range of Z0m than the MR1994 method. We also found that the mean, median and 75th percentiles of heights (H75) from ALS provides the best Z0m estimates in the MR1994 model, while the mean, median, and MLD (Median Absolute Deviation from Median Height), as well as AAD (Mean Absolute Deviation from Mean Height) heights from ALS provides the best Z0m estimates in the RA1994 model. In addition, the fractional cover of shrub and grass, distinguished with ALS and imaging spectroscopy data, provided the opportunity to estimate the frontal area index at the pixel-level to assess the influence of grass and shrub on Z0m estimates in the RA1994 method. Results indicate that grass had little effect on Z0m in the RA1994 method. The Z0m estimations were tightly coupled with vegetation height and its local variance for the shrubs. Overall, the results demonstrate that the use of height and fractional cover from remote sensing data are promising for estimating Z0m, and thus refining land surface models at regional scales in semiarid shrublands. [ABSTRACT FROM AUTHOR]

• Sediment budgets are fundamentally important for planetary geomorphology. • Two methods, remote sensing and in-situ, used on Earth, but only the former on Mars. • What is effect of only one available method without a second for validation on Mars? • Terrestrial analog case study revealed 3 to 138 relative % difference between methods. • Many more analog studies will improve sediment budgets on Mars, other planets. Sediment budgets are fundamentally important for planetary science. However, only one primary method, based on remote sensing, is currently available for determining extraterrestrial sediment budgets. For determining sediment budgets on Earth, both in-situ and remote sensing methods are available. Despite the widespread use of the two methods, there has been surprisingly little research on how well the sediment budgets produced by these two approaches reconcile with one another, which highlights the lack of quantitative understanding of errors for sediment budgets measured with remote sensing in planetary research. Therefore, there is a general need to expand our knowledge of sediment budgets. Here we use a background review and analog case study of an aeolian dunefield in Grand Canyon, Earth to frame a path forward for addressing shortcomings of remote sensing sediment budgets on Mars. We estimate a 53% percent difference in the sediment budget determined with remote sensing relative to in-situ methods for a simple endmember scenario of a dunefield within a unimodal wind directional regime and no external sediment supply. However, when we incorporated key sources of uncertainty in remote sensing change detection following methods commonly used by geomorphologists on Earth, the estimates of sediment budget differences relative to the in-situ method spanned a much larger range, from 3% to 138%. Our case study also suggests that sediment budget errors could be much larger under more complex wind direction, sediment supply, and physiographic settings, and that variability in those landscape characteristics might be used to better estimate errors for dunefield sediment budgets. We conclude that by comparing sediment budgets derived from in-situ measurements of sediment fluxes and from remote sensing measurements at many more analog sites on Earth, the aeolian research community, and the geomorphology discipline, could gain an understanding of the errors of the remote sensing method, which is used by investigators on other planetary bodies such as Mars. This could improve the ability to quantify sediment budgets on Mars – and, in the future, other planetary environments where high-resolution topographic data are available – as well as directly improve our ability to interpret extraterrestrial landscape evolution related to climate, weather, and geologic history. [ABSTRACT FROM AUTHOR]

Processes contributing to development of ephemeral gully channels are of great importance to landscapes worldwide, and particularly in dryland regions where soil loss and land degradation from gully erosion pose long-term land-management problems. Whereas gully formation has been relatively well studied, much less is known of the processes that anneal gullies and impede their growth. This study of gully annealing by aeolian sediment, spanning 95km along the Colorado River corridor in Glen, Marble, and Grand Canyon, Arizona, USA, employed field and remote sensing observations, including digital topographic modelling. Results indicate that aeolian sediment activity can be locally effective at counteracting gully erosion. Gullies are less prevalent in areas where surficial sediment undergoes active aeolian transport, and have a greater tendency to terminate in active aeolian sand. Although not common, examples exist in the record of historical imagery of gullies that underwent infilling by aeolian sediment in past decades and evidently were effectively annealed. We thus provide new evidence for a potentially important interaction of aeolian-hillslope-fluvial processes, which could affect dryland regions substantially in ways not widely recognized. Moreover, because the biologic soil crust plays an important role in determining aeolian sand activity, and so in turn the extent of gully development, this study highlights a critical role of geomorphic-ecologic interactions in determining arid-landscape evolution. [ABSTRACT FROM AUTHOR]

Abstract: Wildland fire activity has increased in many parts of the world in recent decades. Ecological disturbance by fire can accelerate ecosystem degradation processes such as erosion due to combustion of vegetation that otherwise provides protective cover to the soil surface. This study employed a novel ecological indicator based on remote sensing of vegetation greenness dynamics (phenology) to estimate variability in the window of time between fire and the reemergence of green vegetation. The indicator was applied as a proxy for short-term, post-fire disturbance windows in rangelands; where a disturbance window is defined as the time required for an ecological or geomorphic process that is altered to return to pre-disturbance levels. We examined variability in the indicator determined for time series of MODIS and AVHRR NDVI remote sensing data for a database of ∼100 historical wildland fires, with associated post-fire reseeding treatments, that burned 1990–2003 in cold desert shrub steppe of the Great Basin and Columbia Plateau of the western USA. The indicator-based estimates of disturbance window length were examined relative to the day of the year that fires burned and seeding treatments to consider effects of contemporary variability in fire regime and management activities in this environment. A key finding was that contemporary changes of increased length of the annual fire season could have indirect effects on ecosystem degradation, as early season fires appeared to result in longer time that soils remained relatively bare of the protective cover of vegetation after fires. Also important was that reemergence of vegetation did not occur more quickly after fire in sites treated with post-fire seeding, which is a strategy commonly employed to accelerate post-fire vegetation recovery and stabilize soil. Future work with the indicator could examine other ecological factors that are dynamic in space and time following disturbance – such as nutrient cycling, carbon storage, microbial community composition, or soil hydrology – as a function of disturbance windows, possibly using simulation modeling and historical wildfire information. [Copyright &y& Elsevier]

Abstract: The reduction of vegetation by wildfire can subject stable soil surfaces to increased aeolian transport. Vegetation and associated microtopography function as surface roughness elements that influence the entrainment, transport, and deposition of sediment by wind in burned and unburned semiarid shrublands. We examined whether surface roughness derived from LiDAR can explain variability in aeolian surface change following wildfire in loess soils of a cold desert shrub steppe in SE Idaho, USA. Erosion bridges were installed in Fall 2007, following a late summer wildfire to monitor soil surface change at sites in burned and downwind unburned areas. Surface elevation measurements were made when the erosion bridges were installed and again in Fall 2008. Surface change was determined from the difference in relative elevation between the two dates. Airborne LiDAR data were acquired in Fall 2007 following erosion bridge installation. Surface roughness was calculated at 2-m raster resolution using the standard deviation of all LiDAR elevations within the 2-m cells, after elevations were detrended to remove the effects of topographic slope. Surface change varied as a function of surface roughness among burned and unburned surfaces, with net erosion occurring on the relatively smooth, burned surfaces and net deposition occurring on the rough, unburned surfaces. Site mean surface change decreased linearly as a function of the inverse of site mean surface roughness (r 2 =0.77, p <0.00). Quantile regression analysis indicated that changes in surface roughness were related to proportionally greater changes in erosion compared to deposition. Analysis of surface change at finer spatial scales suggested that aeolian processes occurred with strong spatial patterns on burned, but not unburned surfaces. Future research to examine relationships between aeolian transport and fine spatial resolution topographic variability, for example from ground-based LiDAR systems, is recommended. [Copyright &y& Elsevier]

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. [ABSTRACT FROM AUTHOR]

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. • Rangeland function is influenced by fine-scale patterns of species & soil nutrients. • Range plant-soil-nutrient dynamics require very high spatial & spectral resolution. • UAV multispectral-photogrammetry fusion excels at functional cover classification. • UAV hyperspectral-LiDAR fusion excels at species & soil fertility classification. • LiDAR data detect soil fertility changes from ecological disturbance of fire. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The Upper Verde River in northern Arizona, USA is a vital resource for the wildlife and humans that rely on its waters. We characterize the riparian corridor topography using terrestrial laser scanner (TLS) data from 2021 to 2022. We also quantify geomorphic changes associated with human and climate-driven alterations in river flow and vegetation changes by combining the contemporary lidar surveys with legacy measurements from single line geomorphology transects measured by the United States Forest Service (USFS) in 2009. Seventeen plots along the Upper Verde River were surveyed with the TLS and the data were coregistered within individual plots with a Root Mean Square Error of <0.03 m among scan positions. Digital Elevation Models (DEM) were derived for each plot from the TLS data at 10 cm resolution and compared to the 2009 USFS cross-section data to quantify elevation changes. In areas with statistically significant change, we detected maximum changes in elevation due to erosion and deposition of −0.37 m and + 0.97 m, respectively. Topographic changes over the 13-year period were predominately aggradation and associated with sediment deposition, which we hypothesize might have resulted from altered river flow and vegetation encroachment. This study also demonstrates a quantitative and statistical methodology to fuse traditional single line cross-section data with contemporary lidar data to quantify geomorphic change. The novel approach demonstrated here is broadly applicable to natural resource managers for integrating and contextualizing legacy topographic data for understanding past, present, and future landscape and habitat changes. [ABSTRACT FROM AUTHOR]

• Undisturbed biocrust was 2–3 times rougher in cool deserts than hot deserts. • Disturbed biocrust was up-to 70% smoother than undisturbed biocrust. • Biocrust roughness increased with recovery at spatial scales up-to 30 cm. • Increased roughness was linked to soil stability, biocrust, and topographic change. 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. [ABSTRACT FROM AUTHOR]