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At least 1,441 records · Page 80Linked to original sources

USGS2026

Finding the (small) cores: Spatial covariance tracks grassland bird community occupancy in fragmented grasslands

Grasslands are an imperiled ecosystem, and grassland bird abundance is declining across North America. One of the strongest drivers for these declines is woody plant encroachment of grasslands. In the Great Plains and Sagebrush biomes of North America, spatial covariance—a remote-sensing metric for tracking boundaries between vegetation types—is emerging as a new method to identify and strategize conservation of grassland cores in the face of woody plant encroachment. However, the relationship between spatial covariance and grassland bird community occupancy is unknown. Here, we used Bayesian multispecies occupancy models to understand how occupancy probability of six declining grassland species responded to spatial covariance at three scales (0.81, 7.29, and 65.61 ha) and tree cover in fragmented grasslands of Arkansas, USA. Model selection revealed that the smallest spatial scale (0.81 ha) best explained grassland bird occupancy. Tree cover alone was a poor predictor of grassland bird occupancy compared to models that included spatial covariance at the 0.81- and 7.29-ha scales. Grassland bird occupancy declined at tree-grass boundaries (negative spatial covariance at the 0.81-ha scale) and increased in grassland cores (near-zero or slightly positive spatial covariance at the 0.81-ha scale). At low tree cover, Dickcissel ( Spiza americana ), Eastern Kingbird ( Tyrannus tyrannus ), Loggerhead Shrike ( Lanius ludovicianus ), Northern Bobwhite ( Colinus virginianus ), and Scissor-tailed Flycatcher ( Tyrannus forficatus ) occupancy probability more than doubled in grassland cores (where spatial covariance approached zero). Eastern Meadowlark ( Sturnella magna ) had the weakest relationship with spatial covariance. Our results suggest that spatial covariance can identify grassland cores and serve as a powerful predictor of grassland bird community occupancy, even in highly fragmented grasslands. Identifying grassland cores empowers defending core grasslands from woody plant encroachment and then growing cores via active restoration.

Arkansas↗

USGS2018

Hierarchical multi-population viability analysis

Population viability analysis (PVA) uses concepts from theoretical ecology to provide a powerful tool for quantitative estimates of population dynamics and extinction risks. However, conventional statistical PVA requires long-term data from every population of interest, whereas many species of concern exist in multiple isolated populations that are only monitored occasionally. We present a hierarchical multi-population viability analysis model that increases inference power from sparse data by sharing information among populations to assess extinction risks while accounting for incomplete detection and sampling biases with explicit observation and sampling sub-models. We present a case study in which we customized this model for historical population monitoring data (1985–2015) from federally threatened Lahontan cutthroat trout populations in the Great Basin, USA. Data were counts of fish captured during backpack electrofishing surveys from locations associated with 155 isolated populations. Some surveys (25%) included multi-pass removal sampling, which provided valuable information about capture efficiency. GIS and remote sensing were used to estimate August stream temperatures, peak flows, and riparian vegetation condition in each population each year. Field data were used to derive an annual index of nonnative trout densities. Results indicated that population growth rates were higher in colder streams and that nonnative trout reduced carrying capacities of native trout. Extinction risks increased with more environmental stochasticity and were also related to population extent, water temperatures, and nonnative densities. We developed a graphical user interface to interact with the fitted model results and to simulate future habitat scenarios and management actions to assess their influence on extinction risks in each population. Hierarchical multi-population viability analysis bridges the gap between site-level field observations and population-level processes, making effective use of existing datasets to support management decisions with robust estimates of population dynamics, extinction risks, and uncertainties.

Ecology↗

USGS2021

Quantifying the demographic vulnerabilities of dry woodlands to climate and competition using rangewide monitoring data

Climate change is expected to alter the distribution and abundance of tree species, impacting ecosystem structure and function. Yet, anticipating where this will occur is often hampered by a lack of understanding of how demographic rates, most notably recruitment, vary in response to climate and competition across a species range. Using large-scale monitoring data on two dry woodland tree species ( Pinus edulis and Juniperus osteosperma ), we develop an approach to infer recruitment, survival, and growth of both species across their range. In doing so, we account for ecological and statistical dependencies inherent in large-scale monitoring data. We find that drying and warming conditions generally lead to declines in recruitment and survival, but the strength of responses varied between species. These climate conditions point to geographic regions of high vulnerability for particular species, such as Pinus edulis in northern Arizona, where both survival and recruitment are low. Our approach provides a path forward for leveraging emerging large-scale monitoring and remotely sensed data to anticipate the impacts of global change on species distributions.

Ecology↗

USGS2021

Poor relationships between NEON Airborne Observation Platform data and field-based vegetation traits at a mesic grassland

Understanding spatial and temporal variation in plant traits is needed to accurately predict how communities and ecosystems will respond to global change. The National Observatory Ecological Network (NEON) Airborne Observation Platform (AOP) provides hyperspectral images and associated data products at numerous field sites at 1 m spatial resolution, potentially allowing high-resolution trait mapping. We tested the accuracy of NEON’s readily available AOP derived data products – Leaf Area Index, Total biomass, Ecosystem structure (Canopy height model; CHM), and Canopy Nitrogen by comparing them to spatially extensive field measurements from a mesic tallgrass prairie. Correlations with AOP data products exhibited generally weak or no relationships with corresponding field measurements. The strongest relationships were between AOP LAI and ground-measured LAI (r = 0.32) and AOP Total biomass and ground-measured biomass (r = 0.23). We also examined how well the full reflectance spectra (380-2500 nm), as opposed to derived products, could predict vegetation traits using partial least-squares regression models. Only one of the eight traits examined, Nitrogen, had a validation R2 of more than 0.25. For all vegetation traits, validation R2 ranged from 0.08-0.29 and the root mean square error of prediction ranged from 14-64%. Our results suggest that currently available AOP derived data products should not be used without extensive ground-based validation. Relationships using the full reflectance spectra may be more promising, although careful consideration of field and AOP data mismatches in space and/or time, biases in field-based measurements or AOP algorithms, and model uncertainty are needed. Finally, grassland sites may be especially challenging for airborne spectroscopy because of their high species diversity within a small area, mixed functional types of plant communities, and heterogenous mosaics of disturbance and resource availability. Remote sensing observations are one of the most promising approaches to understanding ecological patterns across space and time, yet the opportunity to engage a diverse community of NEON data users will depend on establishing rigorous links with in-situ field measurements across a diversity of sites.

Ecology↗

USGS2024

Going with the floe: Sea-ice movement affects distance and destination during Adélie penguin winter movements

Seasonal migration, driven by shifts in annual climate cycles and resources, is a key part of the life history and ecology of species across taxonomic groups. By influencing the amount of energy needed to move, external forces such as wind and ocean currents are often key drivers of migratory pathways exposing individuals to varying resources, environmental conditions, and competition pressures impacting individual fitness and population dynamics. Although wildlife movements in connection with wind and ocean currents are relatively well understood, movements within sea-ice fields have been much less studied, despite sea ice being an integral part of polar ecology. Adélie penguins ( Pygoscelis adeliae ) in the southern Ross Sea, Antarctica, currently exist at the southernmost edge of their range and undergo the longest (~12,000 km) winter migration known for the species. Within and north of the Ross Sea, the Ross Gyre drives ocean circulation and the large-scale movement of sea ice. We used remotely sensed sea-ice movement data together with geolocation-based penguin movement data to test the hypothesis that penguins use gyre-driven sea-ice movement to aid their migration. We found that penguins traveled greater distances when their movement vectors were aligned with those of sea ice (i.e., ice support) and the amount of ice support received depended on which route a penguin took. We also found that birds that took an eastern route traveled significantly further north in two of the 3 years we examined, coinciding with higher velocities of sea ice in those years. We compare our findings to patterns observed in migrating species that utilize air or water currents for their travel and with other studies showing the importance of ocean/sea-ice circulation patterns to wildlife movement and life history patterns within the Ross Sea. Changes in sea ice may have consequences not only for energy expenditure but, by altering migration and movement pathways, to the ecological interactions that exist in this region.

Ecology↗

USGS2026

DRIFteRS: A dataset of drift invertebrate densities in streams and rivers across western North America, 1997–2024

Prey availability is among the most influential and highly variable determinants of fish growth and freshwater habitat carrying capacity, yet it remains understudied compared to physical habitat variables (Ouellet et al., 2025; Rosenfeld et al., 2014; Weber et al., 2017). We often lack a clear understanding of how much food is available to fishes, how it varies spatially and temporally, and how it influences responses to restoration (Ouellet et al., 2025; Rossi et al., 2024; Wipfli et al., 2010). Drift invertebrates—the primary food source for juvenile salmonids and other drift-foraging fishes—play a pivotal role in these dynamics. To better understand the spatiotemporal variability of drift invertebrate abundance and biomass across the freshwater range of drift-feeding salmonids in western North America, we compiled the DRift Invertebrates For salmonids in River Systems (DRIFteRS) dataset. The dataset encompasses 6125 samples of drift invertebrates, and, for a subset of drift samples, associated benthic invertebrate density data, collected from 1360 reaches on 459 unique rivers and streams spanning 55 river basins considered hydrologically independent (i.e., not nested within the same larger watershed) across British Columbia, Canada, and the U.S. states of Alaska, Arizona, California, Colorado, Idaho, Nevada, New Mexico, Oregon, Utah, Washington, and Wyoming. Sample sites represent a diverse array of river and stream habitats (e.g., headwater, mainstem, side channel), in watersheds with diverse land uses (e.g., urban, wilderness, agricultural), and disturbance histories (e.g., fire, restoration). Collected between 1997 and 2024, the data span the full calendar year and capture daily and seasonal patterns in drift abundance and biomass densities. When paired with water quality and quantity data as well as remotely sensed environmental landscape data, such as land use/land cover, climate, and disturbance history, channel morphology, and riparian vegetation composition, the DRIFteRS dataset can aid in identifying key drivers of drift invertebrate densities and mean body size and support predictive modeling in unsampled locations and times. The dataset may also be used to analyze aquatic-terrestrial resource flows, derive prey-encounter rates and profitability (mean prey size), and inform broader investigations of sit-and-wait foraging ecology, especially when paired with data on drift-foraging predators. For salmonid-focused applications, the dataset can be integrated into habitat evaluation models, including bioenergetic (e.g., Naman et al., 2019) and life cycle models (e.g., Beechie et al., 2023), to improve estimates of habitat capacity and population dynamics for river- and stream-rearing salmonids. Understanding prey availability dynamics is increasingly important, because rising water temperatures increase salmonid metabolic demands (Crozier et al., 2010). Flow regime transitions (i.e., snow or glacier dominated to rain dominated; Beechie et al., 2013), wildfire frequency and intensity (Hessburg et al., 2021), as well as plant community and phenology shifts (Cleland et al., 2007; Franklin et al., 2016) are all predicted to change with rising temperatures and are potential drivers of terrestrial and aquatic invertebrate prey quality and availability in lotic systems. These insights can ultimately inform restoration prioritization and design, helping managers consider food resource implications when evaluating restoration priorities and match habitat improvement to food supply. The data are released under the Creative Commons Attribution 4.0 International license and may be reused with attribution.

Alaska, Arizona, British Columbia, California, Col↗

USGS2017

Functional integrity of freshwater forested wetlands, hydrologic alteration, and climate change

Climate change will challenge managers to balance the freshwater needs of humans and wetlands. The Intergovernmental Panel on Climate Change predicts that most regions of the world will be exposed to higher temperatures, CO 2 , and more erratic precipitation, with some regions likely to have alternating episodes of intense flooding and mega-drought. Coastal areas will be exposed to more frequent saltwater inundation as sea levels rise. Local land managers desperately need intra-regional climate information for site-specific planning, management, and restoration activities. Managers will be challenged to deliver freshwater to floodplains during climate change-induced drought, particularly within hydrologically altered and developed landscapes. Assessment of forest health, both by field and remote sensing techniques, will be essential to signal the need for hydrologic remediation. Studies of the utility of the release of freshwater to remediate stressed forested floodplains along the Murray and Mississippi Rivers suggest that brief episodes of freshwater remediation for trees can have positive health benefits for these forests. The challenges of climate change in forests of the developing world will be considered using the Tonle Sap of Cambodia as an example. With little ecological knowledge of the impacts, managing climate change will add to environmental problems already faced in the developing world with new river engineering projects. These emerging approaches to remediate stressed trees will be of utmost importance for managing worldwide floodplain forests with predicted climate changes.

Ecosystem Health and Sustainability↗

USGS2011

Expansion rate and geometry of floating vegetation mats on the margins of thermokarst lakes, northern Seward Peninsula, Alaska, USA

Investigations on the northern Seward Peninsula in Alaska identified zones of recent (<50 years) permafrost collapse that led to the formation of floating vegetation mats along thermokarst lake margins. The occurrence of floating vegetation mat features indicates rapid degradation of near‐surface permafrost and lake expansion. This paper reports on the recent expansion of these collapse features and their geometry is determined using geophysical and remote sensing measurements. The vegetation mats were observed to have an average thickness of 0.57 m and petrophysical modeling indicated that gas content of 1.5–5% enabled floatation above the lake surface. Furthermore, geophysical investigation provides evidence that the mats form by thaw and subsidence of the underlying permafrost rather than terrestrialization. The temperature of the water below a vegetation mat was observed to remain above freezing late in the winter. Analysis of satellite and aerial imagery indicates that these features have expanded at maximum rates of 1–2 m yr ‐1 over a 56 year period. Including the spatial coverage of floating ‘thermokarst mats’ increases estimates of lake area by as much as 4% in some lakes.

Alaska↗

USGS2012

Rock fall dynamics and deposition: an integrated analysis of the 2009 Ahwiyah Point rock fall, Yosemite National Park, USA.

We analyzed a combination of airborne and terrestrial LiDAR, high-resolution photography, seismic, and acoustic data in order to gain insights into the initiation, dynamics, and talus deposition of a complex rock fall. A large (46 700 m3) rock fall originated from near Ahwiyah Point in eastern Yosemite Valley and fell a total of 730 m to the valley floor on 28 March 2009. Analyses of remote sensing, seismic, and acoustic data were integrated to reconstruct the rock fall, which consisted of (1) the triggering of a 25 400 m3 rock block in an area of intersecting and sometimes highly weathered joint planes, (2) the sliding and subsequent ballistic trajectory of the block from a steeply dipping ledge, (3) dislodging of additional rock from the cliff surface from beneath the rock fall source area, (4) a mid-cliff ledge impact that detached a volume of rock nearly equivalent in volume to the initial block, (5) sliding of the deteriorating rock mass down the remainder of the cliff, and (6) final impact at the base of the cliff that remobilized the existing talus downward and outward and produced an airblast that knocked down hundreds of trees. The depositional geomorphology indicates that the porosity of the fresh talus is significantly lower than that expected for typical blocky talus slopes, likely because the rock debris from this event was pulverized into smaller, more poorly sorted fragments and densified via dynamic compaction when compared to less energetic, fragmental-type rock falls. These results suggest that accumulation of individual rock-fall boulders tends to steepen talus slopes, whereas large, energetic rock falls tend to flatten them. Detachment and impact signals were recorded by seismic and acoustic instruments and highlight the potential use of this type of instrumentation for generalized rock fall monitoring, while LiDAR and photography data were able to quantify the cliff geometry, rock fall volume, source and impact locations, and geomorphological changes to the cliff and talus.

California↗

USGS2017

Camera system considerations for geomorphic applications of SfM photogrammetry

The availability of high-resolution, multi-temporal, remotely sensed topographic data is revolutionizing geomorphic analysis. Three-dimensional topographic point measurements acquired from structure-from-motion (SfM) photogrammetry have been shown to be highly accurate and cost-effective compared to laser-based alternatives in some environments. Use of consumer-grade digital cameras to generate terrain models and derivatives is becoming prevalent within the geomorphic community despite the details of these instruments being largely overlooked in current SfM literature. This article is protected by copyright. All rights reserved. A practical discussion of camera system selection, configuration, and image acquisition is presented. The hypothesis that optimizing source imagery can increase digital terrain model (DTM) accuracy is tested by evaluating accuracies of four SfM datasets conducted over multiple years of a gravel bed river floodplain using independent ground check points with the purpose of comparing morphological sediment budgets computed from SfM- and lidar-derived DTMs. Case study results are compared to existing SfM validation studies in an attempt to deconstruct the principle components of an SfM error budget. This article is protected by copyright. All rights reserved. Greater information capacity of source imagery was found to increase pixel matching quality, which produced 8 times greater point density and 6 times greater accuracy. When propagated through volumetric change analysis, individual DTM accuracy (6–37 cm) was sufficient to detect moderate geomorphic change (order 100,000 m 3 ) on an unvegetated fluvial surface; change detection determined from repeat lidar and SfM surveys differed by about 10%. Simple camera selection criteria increased accuracy by 64%; configuration settings or image post-processing techniques increased point density by 5–25% and decreased processing time by 10–30%. This article is protected by copyright. All rights reserved. Regression analysis of 67 reviewed datasets revealed that the best explanatory variable to predict accuracy of SfM data is photographic scale. Despite the prevalent use of object distance ratios to describe scale, nominal ground sample distance is shown to be a superior metric, explaining 68% of the variability in mean absolute vertical error.

Earth Surface Processes and Landforms↗

USGS2020

Measuring channel planform change from image time series: A generalizable, spatially distributed, probabilistic method for quantifying uncertainty

Channels change in response to natural or anthropogenic fluctuations in streamflow and/or sediment supply and measurements of channel change are critical to many river management applications. Whereas repeated field surveys are costly and time‐consuming, remote sensing can be used to detect channel change at multiple temporal and spatial scales. Repeat images have been widely used to measure long‐term channel change, but these measurements are only significant if the magnitude of change exceeds the uncertainty. Existing methods for characterizing uncertainty have two important limitations. First, while the use of a spatially variable image co‐registration error avoids the assumption that errors are spatially uniform, this type of error, as originally formulated, can only be applied to linear channel adjustments, which provide less information on channel change than polygons of erosion and deposition. Second, previous methods use a level‐of‐detection (LoD) threshold to remove non‐significant measurements, which is problematic because real changes that occurred but were smaller than the LoD threshold would be removed. In this study, we present a new method of quantifying uncertainty associated with channel change based on probabilistic, spatially varying estimates of co‐registration error and digitization uncertainty that obviates a LoD threshold. The spatially distributed probabilistic (SDP) method can be applied to both linear channel adjustments and polygons of erosion and deposition, making this the first uncertainty method generalizable to all metrics of channel change. Using a case study from the Yampa River, Colorado, we show that the SDP method reduced the magnitude of uncertainty and enabled us to detect smaller channel changes as significant. Additionally, the distributional information provided by the SDP method allowed us to report the magnitude of channel change with an appropriate level of confidence in cases where a simple LoD approach yielded an indeterminate result.

Earth Surface Processes and Landforms↗

USGS2021

Past, present and future of a meandering river in the Bolivian Amazon basin

Field observations on small rivers of the Amazon basin are less common due to their remote location and difficult accessibility. Here we show, through remote sensing analysis and field works, the planform evolution and riverbed topography of a small river located in the upper foreland Amazon basin, the Ichilo River. By tracking planform changes over 30 years, we identified the factors that control meander migration rates in the Ichilo River: cutoffs, climate and human interventions. The data suggest that neck cutoffs are the main controls in the Ichilo River, with an annual density of 0.022 cutoffs/km. In addition, climate controls have been identified in the form of high-precipitation events that may have promoted cutoffs, an increase in meander migration rate and channel widening. The width distribution of the Ichilo River is well represented by general extreme value and inverse Gaussian distributions. The spatiotemporal variability of meandering migration rates in the Ichilo River is analysed in two locations where neck cutoffs are expected. Analysing the distance across the neck in these two points, we predict the occurrence of a new cutoff. The combined methodology of bathymetric surveys and structure from motion photogrammetry shows us the Ichilo riverbed topography and banks at high resolution, where two scour holes were identified. Finally, we discuss the impact of planform changes of the Ichilo River on communities that are established along its riverbanks.

Earth Surface Processes and Landforms↗

USGS2017

Biological soil crusts: Diminutive communities of potential global importance

Biological soil crusts (biocrusts) are widespread, diverse communities of cyanobacteria, fungi, lichens, and mosses living on soil surfaces, primarily in drylands. Biocrusts can locally govern primary production, soil fertility, hydrology, and surface energy balance, with considerable variation in these functions across alternate community states. Further, these communities have been implicated in Earth system functioning via potential influences on global biogeochemistry and climate. Biocrusts are easily destroyed by disturbances and appear to be exceptionally vulnerable to warming temperatures and altered precipitation inputs, signaling possible losses of dryland functions with global change. Despite these concerns, we lack sufficient spatiotemporal data on biocrust function, cover, and community structure to confidently assess their ecological roles across the extensive dryland biome. Here, we present the case for cross-scale research and restoration efforts coupled with remote-sensing and modeling approaches that improve our collective understanding of biocrust responses to global change and the ecological roles of these diminutive communities at global scales.

Frontiers in Ecology and the Environment↗

USGS2020

Oases of the future? Evaluating springs as potential hydrologic refugia in drying climates

Springs in water-limited landscapes are biodiversity hotspots and keystone ecosystems, disproportionately influencing surrounding landscapes despite their often small areas. Some springs served as evolutionary refugia during previous climate drying, supporting relict species in isolated habitats. Understanding whether springs will provide hydrologic refugia from future climate change is important to biodiversity conservation but complicated by hydrologic variability among springs, data limitations, and multiple non-climate threats to groundwater-dependent ecosystems. Here, we present a conceptual framework for categorizing springs as potentially stable, relative, or transient hydrologic refugia in a drying climate. Clues about refugial capacity of springs can be assembled from diverse approaches, including citizen-science-powered ecohydrologic monitoring, remote sensing, landowner interviews, and environmental tracer analysis. Managers can integrate multiple lines of evidence to predict which springs may become future refugia for species of concern, strengthening the long-term effectiveness of springs conservation and restoration and informing climate adaptation for terrestrial and freshwater species.

Frontiers in Ecology and the Environment↗

USGS2015

Rethinking the longitudinal stream temperature paradigm: region-wide comparison of thermal infrared imagery reveals unexpected complexity of river temperatures

Prevailing theory suggests that stream temperature warms asymptotically in a downstream direction, beginning at the temperature of the source in the headwaters and leveling off downstream as it converges to match meteorological conditions. However, there have been few empirical examples of longitudinal patterns of temperature in large rivers due to a paucity of data. We constructed longitudinal thermal profiles (temperature versus distance) for 53 rivers in the Pacific Northwest (USA) using an extensive dataset of remotely sensed summertime river temperatures and classified each profile into one of five patterns of downstream warming: asymptotic (increasing then flattening), linear (increasing steadily), uniform (not changing), parabolic (increasing then decreasing), or complex (not fitting other classes). We evaluated (1) how frequently profiles warmed asymptotically downstream as expected, and (2) whether relationships between river temperature and common hydroclimatic variables differed by profile class. We found considerable diversity in profile shape, with 47% of rivers warming asymptotically, and 53% having alternative profile shapes. Water temperature did not warm substantially over the course of the river for coastal parabolic and uniform profiles, and for some linear and complex profiles. Profile classes showed no clear geographical trends. The degree of correlation between river temperature and hydroclimatic variables differed among profile classes, but there was overlap among classes. Water temperature in rivers with asymptotic or parabolic profiles was positively correlated with August air temperature, tributary temperature and velocity, and negatively correlated with elevation, August precipitation, gradient, and distance upstream. Conversely, associations were less apparent in rivers with linear, uniform, or complex profiles. Factors contributing to the unique shape of parabolic profiles differed for coastal and inland rivers, where downstream cooling was influenced locally by climate or cool water inputs, respectively. Potential drivers of shape for complex profiles were specific to each river. These thermal patterns indicate diverse thermal habitats that may promote resilience of aquatic biota to climate change. Without this spatial context, climate change models may incorrectly estimate loss of thermally suitable habitat.

California, Idaho, Oregon, Washington↗

USGS2015

Regional variability in dust-on-snow processes and impacts in the Upper Colorado River Basin

Dust deposition onto mountain snow cover in the Upper Colorado River Basin frequently occurs in the spring when wind speeds and dust emission peaks on the nearby Colorado Plateau. Dust loading has increased since the intensive settlement in the western USA in the mid 1880s. The effects of dust-on-snow have been well studied at Senator Beck Basin Study Area (SBBSA) in the San Juan Mountains, CO, the first high-altitude area of contact for predominantly southwesterly winds transporting dust from the southern Colorado Plateau. To capture variability in dust transport from the broader Colorado Plateau and dust deposition across a larger area of the Colorado River water sources, an additional study plot was established in 2009 on Grand Mesa, 150 km to the north of SBBSA in west central, CO. Here, we compare the 4-year (2010–2013) dust source, deposition, and radiative forcing records at Grand Mesa Study Plot (GMSP) and Swamp Angel Study Plot (SASP), SBBSA's subalpine study plot. The study plots have similar site elevations/environments and differ mainly in the amount of dust deposited and ensuing impacts. At SASP, end of year dust concentrations ranged from 0.83 mg g −1 to 4.80 mg g −1 , and daily mean spring dust radiative forcing ranged from 50–65 W m −2 , advancing melt by 24–49 days. At GMSP, which received 1.0 mg g −1 less dust per season on average, spring radiative forcings of 32–50 W m −2 advanced melt by 15–30 days. Remote sensing imagery showed that observed dust events were frequently associated with dust emission from the southern Colorado Plateau. Dust from these sources generally passed south of GMSP, and back trajectory footprints modelled for observed dust events were commonly more westerly and northerly for GMSP relative to SASP. These factors suggest that although the southern Colorado Plateau contains important dust sources, dust contributions from other dust sources contribute to dust loading in this region, and likely account for the majority of dust loading at GMSP.

Hydrological Processes↗

USGS2015

Wide-area estimates of evapotranspiration by red gum ( Eucalyptus camaldulensis ) and associated vegetation in the Murray-Darling River Basin, Australia

Floodplain red gum forests ( Eucalyptus camaldulensis plus associated grasses, reeds and sedges) are sites of high biodiversity in otherwise arid regions of southeastern Australia. They depend on periodic floods from rivers, but dams and diversions have reduced flood frequencies and volumes, leading to deterioration of trees and associated biota. There is a need to determine their water requirements so environmental flows can be administered to maintain or restore the forests. Their water requirements include the frequency and extent of overbank flooding, which recharges the floodplain soils with water, as well as the actual amount of water consumed in evapotranspiration (ET). We estimated the flooding requirements and ET for a 38 134 ha area of red gum forest fed by the Murrumbidgee River in Yanga National Park, New South Wales. ET was estimated by three methods: sap flux sensors placed in individual trees; a remote sensing method based on the Enhanced Vegetation Index from MODIS satellite imagery and a water balance method based on differences between river flows into and out of the forest. The methods gave comparable estimates yet covered different spatial and temporal scales. We estimated flood frequency and volume requirements by comparing Normalized Difference Vegetation Index values from Landsat images with flood history from 1995 to 2014, which included both wet periods and dry periods. ET during wet years is about 50% of potential ET but is much less in dry years because of the trees' ability to control stomatal conductance. Based on our analyses plus other studies, red gum trees at this location require environmental flows of 2000 GL yr −1 every other year, with peak flows of 20 000 ML d −1 , to produce flooding sufficient to keep them in good condition. However, only about 120–200 GL yr −1 of river water is consumed in ET, with the remainder flowing out of the forest where it enters the Murray River system.

Murray-Darling River Basin↗

USGS2015

Effect of permafrost thaw on the dynamics of lakes recharged by ice-jam floods: case study in Yukon Flats, Alaska

Large river floods are a key water source for many lakes in fluvial periglacial settings. Where permeable sediments occur, the distribution of permafrost may play an important role in the routing of floodwaters across a floodplain. This relationship is explored for lakes in the discontinuous permafrost of Yukon Flats, interior Alaska, using an analysis that integrates satellite-derived gradients in water surface elevation, knowledge of hydrogeology, and hydrologic modeling. We observed gradients in water surface elevation between neighboring lakes ranging from 0.001 to 0.004. These high gradients, despite a ubiquitous layer of continuous shallow gravel across the flats, are consistent with limited groundwater flow across lake basins resulting from the presence of permafrost. Permafrost impedes the propagation of floodwaters in the shallow subsurface and constrains transmission to “fill-and-spill” over topographic depressions (surface sills), as we observed for the Twelvemile-Buddy Lake pair following a May 2013 ice-jam flood on the Yukon River. Model results indicate that permafrost table deepening of 1–11 m in gravel, depending on watershed geometry and subsurface properties, could shift important routing of floodwater to lakes from overland flow (fill-and-spill) to shallow groundwater flow (“fill-and-seep”). Such a shift is possible in the next several hundred years of ground surface warming, and may bring about more synchronous water level changes between neighboring lakes following large flood events. This relationship offers a potentially useful tool, well-suited to remote sensing, for identifying long-term changes in shallow groundwater flow resulting from thawing of permafrost.

Alaska↗