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USGS2025

The effectiveness of wildfire at meeting restoration goals across a fire severity gradient in the Sierra Nevada

As a consequence of both warming temperatures and over a century of fire suppression, wildfires in the historically frequent-fire forests of the western US have increased both in size and intensity, resulting in large patches of high severity fire that are well outside the historic range of variation. Postfire fuels research has often focused on such high severity patches because of the risk of both type conversion and repeated high severity fire. Yet a substantial portion of any given wildfire will likely still have burned at low to moderate severity. These areas generally retain live mature trees and surface fuels, suggesting that wildfire effects may be in keeping with some forest restoration goals. To better understand the range of postfire fuels conditions across severity classes and how well those conditions align with restoration targets, we sampled three wildfires in mixed conifer forests and giant sequoia groves of the southern Sierra Nevada. These wildfires appear to have met short-term restoration goals for surface fuel reduction, with burned areas having 79.5 % less fuels than unburned areas. Fine woody debris and litter and duff declined with severity, while coarse woody debris was more variable. Small tree density targets were roughly met after low and moderate severity fire, but large tree densities tended to be lower than restoration targets, possibly due to high levels of recent tree mortality. For long-term management, restoration plans set targets for the proportions of the landscape that should be in different fuel load categories, reflecting patterns shaped by many frequent and patchy fires. Observed post-wildfire surface fuels outside of groves were overwhelmingly in the lowest fuels category across severity classes, which is in keeping with short-term goals to reduce surface fuels but is not necessarily contributing to the heterogeneity desired at landscape scales. Surface fuels within giant sequoia groves were higher than those outside groves and therefore more closely matched long-term management targets for variation in fuel loads. However, for a highly valued species that has recently seen substantial losses to high severity fire, managers may find that these higher fuel loads are not desirable even in a landscape context. In summary, low and moderate severity wildfire appear to have beneficial effects in terms of meeting several management goals, however, the large amount of standing postfire fuels, the relative dearth of large trees, and the potential lack of postfire fuel heterogeneity may still pose potential management concerns.

California↗

USGS2014

Evaluation of a model framework to estimate soil and soil organic carbon redistribution by water and tillage using 137 Cs in two U.S. Midwest agricultural fields

Cultivated lands in the U.S. Midwest have been affected by soil erosion, causing soil organic carbon (SOC) redistribution in the landscape and other environmental and agricultural problems. The importance of SOC redistribution on soil productivity and crop yield, however, is still uncertain. In this study, we used a model framework, which includes the Unit Stream Power-based Erosion Deposition (USPED) and the Tillage Erosion Prediction (TEP) models, to understand the soil and SOC redistribution caused by water and tillage erosion in two agricultural fields in the U.S. Midwest. This model framework was evaluated for different digital elevation model (DEM) spatial resolutions (10-m, 24-m, 30-m, and 56-m) and topographic exponents ( m = 1.0–1.6 and n = 1.0–1.3) using soil redistribution rates from 137 Cs measurements. The results showed that the aggregated 24-m DEM, m = 1.4 and n = 1.0 for rill erosion, and m = 1.0 and n = 1.0 for sheet erosion, provided the best fit with the observation data at both sites. Moreover, estimated average SOC redistributions were 1.3 ± 9.8 g C m − 2 yr − 1 in field site 1 and 3.6 ± 14.3 g C m − 2 yr − 1 in field site 2. Spatial distribution patterns showed SOC loss (negative values) in the eroded areas and SOC gain (positive value) in the deposition areas. This study demonstrated the importance of the spatial resolution and the topographic exponents to estimate and map soil redistribution and the SOC dynamics throughout the landscape, helping to identify places where erosion and deposition from water and tillage are occurring at high rates. Additional research is needed to improve the application of the model framework for use in local and regional studies where rainfall erosivity and cover management factors vary. Therefore, using this model framework can help to improve the information about the spatial distribution of soil erosion across agricultural landscapes and to gain a better understanding of SOC dynamics within eroding and previously eroded fields.

Iowa↗

USGS2008

Application of sedimentary-structure interpretation to geoarchaeological investigations in the Colorado River Corridor, Grand Canyon, Arizona, USA

We present a detailed geoarchaeological study of landscape processes that affected prehistoric formation and modern preservation of archaeological sites in three areas of the Colorado River corridor in Grand Canyon, Arizona, USA. The methods used in this case study can be applied to any locality containing unaltered, non-pedogenic sediments and, thus, are particularly relevant to geoarchaeology in arid regions. Resolving the interaction of fluvial, aeolian, and local runoff processes in an arid-land river corridor is important because the archaeological record in arid lands tends to be concentrated along river corridors. This study uses sedimentary structures and particle-size distributions to interpret landscape processes; these methods are commonplace in sedimentology but prove also to be valuable, though less utilized, in geoarchaeology and geomorphology. In this bedrock canyon, the proportion of fluvial sediment generally decreases with distance away from the river as aeolian, slope-wash, colluvial, and debris-flow sediments become more dominant. We describe a new facies consisting of 'flood couplets' that include a lower, fine-grained fluvial component and an upper, coarser, unit that reflects subaerial reworking at the land surface between flood events. Grain-size distributions of strata that lack original sedimentary structures are useful within this river corridor to distinguish aeolian deposits from finer-grained fluvial deposits that pre-date the influence of the upstream Glen Canyon Dam on the Colorado River. Identification of past geomorphic settings is critical for understanding the history and preservation of archaeologically significant areas, and for determining the sensitivity of archaeological sites to dam operations. Most archaeological sites in the areas studied were formed on fluvial deposits, with aeolian deposition acting as an important preservation agent during the past millennium. Therefore, the absence of sediment-rich floods in this regulated river, which formerly deposited large fluvial sandbars from which aeolian sediment was derived, has substantially altered processes by which the prehistoric, inhabited landscape formed, and has also reduced the preservation potential of many significant cultural sites.

Geomorphology↗

USGS2016

Spatial distribution of thermokarst terrain in Arctic Alaska

In landscapes underlain by ice-rich permafrost, the development of thermokarst landforms can have drastic impacts on ecosystem processes and human infrastructure. Here we describe the distribution of thermokarst landforms in the continuous permafrost zone of Arctic Alaska, analyze linkages to the underlying surficial geology, and discuss the vulnerability of different types of landscapes to future thaw. We identified nine major thermokarst landforms and then mapped their distributions in twelve representative study areas totaling 300-km 2 . These study areas differ in their geologic history, permafrost-ice content, and ground thermal regime. Results show that 63% of the entire study area is occupied by thermokarst landforms and that the distribution of thermokarst landforms and overall landscape complexity varies markedly with surficial geology. Areas underlain by ice-rich marine silt are the most affected by thermokarst (97% of total area), whereas areas underlain by glacial drift are least affected (14%). Drained thermokarst-lake basins are the most widespread thermokarst landforms, covering 33% of the entire study region, with greater prevalence in areas of marine silt (48% coverage), marine sand (47%), and aeolian silt (34%). Thermokarst-lakes are the second most common thermokarst landform, covering 16% of the study region, with highest coverage in areas underlain by marine silt (39% coverage). Thermokarst troughs and pits cover 7% of the study region and are the third most prevalent thermokarst landform. They are most common in areas underlain by deltaic sands and gravels (18% coverage) and marine sand (12%). Alas valleys are widespread in areas of aeolian silt (14%) located in gradually sloping uplands. Areas of marine silt have been particularly vulnerable to thaw in the past because they are ice-rich and have low-gradient topography facilitating the repeated development of thermokarst-lakes. In the future, ice-rich aeolian, upland terrain (yedoma) will be particularly susceptible to thaw because it still contains massive concentrations of ground ice in the form of syngenetic ice-wedges that have remained largely intact since the Pleistocene.

Alaska↗

USGS2019

The effects of topographic surveying technique and data resolution on the detection and interpretation of geomorphic change

Change detection of high resolution topographic data is commonly used in river valleys to quantify reach- and site-scale sediment budgets by estimating the erosion/deposition volume, and to interpret the geomorphic processes driving erosion and deposition. Field survey data are typically collected as point clouds that are often converted to gridded raster datasets and the ultimate choice of grid resolution is left to the user. This choice may have important implications for both the quantification and interpretation of geomorphic change. Here we used concurrent topographic data collected by terrestrial laser scanning (TLS) and structure-from-motion (SfM) photogrammetry to quantify the influence of grid resolution and sampling technique on (a) the sediment budget and (b) the presence and role of geomorphic processes (i.e., alluvial, colluvial, aeolian, and fluvial transport) driving topographic change at four sites along the Colorado River in Grand Canyon, Arizona, USA. We found that while both techniques produced similar estimates for site-scale sediment budgets, the magnitude of detected topographic change was dampened at coarser pixel resolutions. An overall decrease in the areal extent of erosion and deposition were observed, respectively, when coarsening pixel size from 5 cm to 1 m among all sites. Coarser resolution data tended to affect interpretation of landscape change along the margins of river valleys. For example, when changing from 5 cm to 1 m pixel resolution, the inferred contribution of aeolian changes to total site-scale geomorphic change increased in area by 7.9%, whereas the inferred contribution of alluvial and colluvial processes decreased in area by 97.9% and 88.2%, respectively. More generally, we found that coarsening pixel sizes disproportionately attributed geomorphic change to one or more of the most common processes operating at a site. We also found that coarsening pixel resolution amplified the net sediment imbalance at the site scale, driving the imbalance at erosional sites further into erosion and vice versa for depositional sites. Our results have implications both for point cloud data collection and for raster dataset processing. We argue that selecting the finest obtainable resolution is not always warranted to accurately quantify and interpret geomorphic change, because remote sensing technique, topographic data resolution, and analysis procedure can be optimized to capture the spatial scale of those processes driving landscape change. However, in landscapes at or near sediment equilibrium (i.e., equal amounts of erosion and deposition), the finest obtainable topographic data resolution is warranted to avoid amplifying sediment imbalance and erroneously inferring that sites are trending toward erosion or deposition.

Arizona↗

USGS2022

Using near–surface temperature data to vicariously calibrate high-resolution thermal infrared imagery and estimate physical surface properties

Thermal response of the surface to solar insolation is a function of the topography and the thermal physical characteristics of the landscape, which include bulk density, heat capacity, thermal conductivity and surface albedo and emissivity. Thermal imaging is routinely used to constrain thermal physical properties by characterizing or modeling changes in the diurnal temperature profiles. Images need to be acquired throughout the diurnal cycle – typically this is done twice during a diurnal cycle, but we suggest multiple times. Comparison of images acquired over 24 hours requires that either the data be calibrated to surface temperature, or the response of the thermal camera is linear and stable over the image acquisition period. Depending on the type and age of the thermal instrument, imagery may be self-calibrated in radiance, corrected for atmospheric effects, and pixels converted to surface temperature. We used an experimental instrumentation where the calibration should be stable, but calibration coefficients are unknown. Cases may occur where one wishes to validate the camera's calibration. We present a method to validate and calibrate the instrument and characterize the thermal physical properties for areas of interest. Finally, in situ high-temporal-resolution oblique thermal imaging can be invaluable in preparation for conducting overflight missions. We present the following: • The use of oblique thermal high temporal resolution thermal imaging over diurnal or multiday periods for the characterization of landscapes has not been widespread but poses great potential. • A method of collecting and analyzing thermal data that can be used to either determine or validate thermal camera calibration coefficients. • An approach to characterize thermophysical properties of the landscape using oblique temporally high-resolution thermal imaging, combined with in situ ground measurements.

MethodsX↗

USGS2018

Aeolian stratigraphy describes ice-age paleoenvironments in unglaciated Arctic Alaska

Terrestrial paleoenvironmental records with high dating resolution extending into the last ice age are rare from the western Arctic. Such records can test the synchronicity and extent of ice-age climatic events and define how Arctic landscapes respond to rapid climate changes. Here we describe the stratigraphy and sedimentology of a yedoma deposit in Arctic Alaska (the Carter Section) dating to between 37,000 and 9000 calibrated radiocarbon years BP (37–9 ka) and containing detailed records of loess and sand-sheet sedimentation, soil development, carbon storage, and permafrost dynamics. Alternation between sand-sheet and loess deposition provides a proxy for the extent and activity of the Ikpikpuk Sand Sea (ISS), a large dune field located immediately upwind. Warm, moist interstadial times (ca. 37, 36.3–32.5, and 15–13 ka) triggered floodplain aggradation, permafrost thaw, reduced loess deposition, increased vegetation cover, and rapid soil development accompanied by enhanced carbon storage. During the Last Glacial Maximum (LGM, ca. 28–18 ka), rapid loess deposition took place on a landscape where vegetation was sparse and non-woody. The most intense aeolian activity occurred after the LGM between ca. 18 and 15 ka when sand sheets fringing the ISS expanded over the site, possibly in response to increasingly droughty conditions as summers warmed and active layers deepened. With the exception of this lagged LGM response, the record of aeolian activity at the Carter Section correlates with other paleoenvironmental records from unglaciated Siberia and Alaska. Overall, rapid shifts in geomorphology, soils, vegetation, and permafrost portray an ice-age landscape where, in contrast to the Holocene, environmental change was chronic and dominated by aeolian processes.

Alaska↗

USGS2021

Spatiotemporal patterns of northern lake formation since the last glacial maximum

The northern mid- to high-latitudes have the highest total number and area of lakes on Earth. Lake origins in these regions are diverse, but to a large extent coupled to glacial, permafrost, and peatland histories. The synthesis of 1207 northern lake initiation records presented here provides an analog for rapid landscape-level change in response to climate warming, and its subsequent attenuation by physical and biological feedback mechanisms. Our compilation reveals two peaks in northern lake formation, 13,200 and 10,400 years ago, both following rapid increases in North Atlantic air temperature. Placing our findings within the context of existing paleoenvironmental records, we suggest that solar insolation-driven changes in climate (temperature and water balance) that led to deglaciation and permafrost thaw likely contributed to high rates of northern lake formation during the last Deglacial period. However, further landscape development and stabilization dramatically reduced rates of lake formation beginning ∼10,000 years ago. This suggests that temperature alone may not control future lake development; rather, multiple factors must align to enable a landscape to respond with an increase in lake area. We propose that land surfaces strongly geared toward increased lake formation were highly conditioned by glaciation. Thus, it is unlikely that warming this century will cause lake formation as rapid or as widespread as that during the last Deglacial period.

Quaternary Science Reviews↗

USGS2018

Land use diversification and intensification on elk winter range in Greater Yellowstone: A framework and agenda for social-ecological research

Amenity migration describes the movement of peoples to rural landscapes and the transition toward tourism and recreation and away from production-oriented land uses (ranching, timber harvesting). The resulting mosaic of land uses and community structures has important consequences for wildlife and their management. This research note examines amenity-driven changes to social-ecological systems in the Greater Yellowstone Ecosystem, specifically in lower elevations that serve as winter habitat for elk. We present a research agenda informed by a preliminary and exploratory mixed-methods investigation: the creation of a “social-impact” index of land use change on elk winter range and a focus group with wildlife management experts. Our findings suggest that elk are encountering an increasingly diverse landscape with respect to land use, while new ownership patterns increase the complexity of social and community dynamics. These factors, in turn, contribute to increasing difficulty meeting wildlife management objectives. To deal with rising complexity across social and ecological landscapes of the Greater Yellowstone Ecosystem, future research will focus on property life cycle dynamics, as well as systems approaches.

Rangeland Ecology and Management↗

USGS2020

Post-fire management-scale trials of bacterial soil amendment MB906 show inconsistent control of invasive annual grasses

Rangeland managers need tools to control invasive annual grasses, particularly following wildfire. We assessed responses of native and invasive/exotic grasses to the MB906 soil amendment containing live cultures of a purportedly weed-suppressive strain of the bacterium Pseudomonas fluorescens (“WSB”). MB906 was applied alone and in combination with the pre-emergent herbicide imazapic on >3000 ha across three sagebrush-steppe landscapes burned several months prior. Replicate plots of each treatment type were established and plant cover was measured in the following three years. Cover of invasive-annual grasses (“IAG”) was not responsive to MB906 when all IAG species were considered (“IAG-All”). However, MB906 led to a 54% reduction in the IAG's that were previously reported to be controlled by WSB (“IAG-Target”) in the second year following application (IAG-Target = cheatgrass, Bromus tectorum and medusahead, Taeniatherum caput-medusae; IAG-All also includes Vulpia myuros and Bromus arvensis ). MB906 reduced the effectiveness of co-applied imazapic: Imazapic alone reduced IAG-All by 83% and 68% in years 1 and 2, respectively, while imazapic+MB906 reduced IAG-All by 48% and 38% in years 1 and 2, respectively, across all landscapes, and a similar response pattern was observed for IAG-Target. Perennial grass cover was unaffected by the treatments except where it increased 4-fold in response to imazapic applied at a high rate (0.140 kg a.i. ha −1 ) in one of the landscapes. Tank mixing MB906 and herbicide may have lessened the biological activity of the herbicide by altering the pH or mineral content of the spray solution or by direct metabolism of the herbicide by the bacteria. These results do not provide strong support for MB906 as a tool for annual grass control, though they suggest further investigation may be warranted.

Rangeland Ecology and Management↗

USGS2026

Long-term effects of rangeland improvements on cattle distribution: A ranch-scale case study

Resource matching can be a common assumption that underlies anthropogenic rangeland improvements for wildlife or livestock. Countless resources are spent on targeted vegetation manipulations for both livestock and wildlife, but selection for improved areas has not been well quantified in livestock. This case study investigates whether cattle exhibit preferential use of historically improved rangeland sites within sagebrush steppe ecosystems, and whether these effects are relevant long-term compared with inherent landscape heterogeneity. We used a generalized linear mixed-effects resource selection function on Global Positioning System points collected at a fix rate of 2 h from a subset of animals grazing throughout 14 pastures (totaling 13 079 ha) over 3 yr to investigate cattle distribution in relation to historical rangeland improvements. These consisted of various methods for reducing woody plant cover and increasing forage production, most followed by grass and legume reseeding. Overall selection for treated areas was positive (0.16, P < 0.0 0 01), but highly variable (pasture estimates range from-1.81 to 0.77). Differences in enhanced vegetation index (EVI) accounted for 25% of the variation in treatment selection, whereas herbaceous production did not have an appreciable effect on treatment selection. Within individual pastures, the effects of landscape variables (distance to water, slope, herbaceous production, EVI, tree cover, and shrub cover) were more variable than treatment effects and on average 2.4-fold more influential to selection than anthropogenic treatments. Still, the combined effects of all landscape variables accounted for only 8% of the variation in site selection. The observed inconsistency among selection patterns underscores the complexity of large herbivore resource selection behavior, and the statistical challenges to modeling that behavior. These results provide limited and inconsistent support for the hypothesis that large herbivores select long-term (5–20 yr post establishment) for range improvements in relation to their forage quality/quantity in a resource-matching manner.

Utah↗

USGS2026

Habitat restoration efforts increase patch retention times in migratory mule deer (Odocoileus hemionus)

Mule deer ( Odocoileus hemionus ) populations have been declining across much of their range, often due to habitat alteration. Habitat alterations, including the introduction of non-native annual grasses and the expansion of pinyon–juniper (PJ) forests on sagebrush ecosystems, are changing resource availability compared to historical conditions. Extensive habitat restoration has been completed across the State of Utah to foster plant communities that better reflect historical conditions and optimal mule deer habitat. We investigated how patch retention times differ on eight different habitat restoration treatment types and random locations during summer and winter across the State of Utah, to evaluate the efficacy of restoration treatments for migratory mule deer, as retention time is expected to reflect resource availability. We developed seasonal moving-window Brownian Bridge Movement Models for individual mule deer ( n = 593 animals), and intersected occurrence distributions (OD) with habitat restoration treatments and randomly generated background landscape polygons. We quantified patch retention time as the number of days individuals’ OD overlapped treatment or random polygons during each season, using a Poisson regression. In winter sites treated to remove PJ, both with (56.5 days, 95% CI [29.3, 108.0]) and without seeding (55.3 days, 95% CI [29.1, 105.8]), as well as sagebrush restoration sites (59.0 days, 95% CI [30.6, 114.8]), had increased retention times when compared to the landscape average (41.9 days, 95% CI [20.7, 84.1]), with effects decreasing 5+ years post-treatment. Retention times in summer were longer across all treatment types in the 2–4-year post-treatment age class (37.5 days, 95% CI [26.3, 53.1]) compared to the landscape average (28.6 days, 95% CI [25.7, 31.8]). Our results demonstrate the positive effects of habitat restoration through increased patch retention times on mule deer winter and summer range and may suggest follow-up treatment 5+ years after initial treatment to maximize mule deer use.

Utah↗

USGS2009

Using LiDAR and quickbird data to model plant production and quantify uncertainties associated with wetland detection and land cover generalizations

Spatiotemporal data from satellite remote sensing and surface meteorology networks have made it possible to continuously monitor global plant production, and to identify global trends associated with land cover/use and climate change. Gross primary production (GPP) and net primary production (NPP) are routinely derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard satellites Terra and Aqua, and estimates generally agree with independent measurements at validation sites across the globe. However, the accuracy of GPP and NPP estimates in some regions may be limited by the quality of model input variables and heterogeneity at fine spatial scales. We developed new methods for deriving model inputs (i.e., land cover, leaf area, and photosynthetically active radiation absorbed by plant canopies) from airborne laser altimetry (LiDAR) and Quickbird multispectral data at resolutions ranging from about 30??m to 1??km. In addition, LiDAR-derived biomass was used as a means for computing carbon-use efficiency. Spatial variables were used with temporal data from ground-based monitoring stations to compute a six-year GPP and NPP time series for a 3600??ha study site in the Great Lakes region of North America. Model results compared favorably with independent observations from a 400??m flux tower and a process-based ecosystem model (BIOME-BGC), but only after removing vapor pressure deficit as a constraint on photosynthesis from the MODIS global algorithm. Fine-resolution inputs captured more of the spatial variability, but estimates were similar to coarse-resolution data when integrated across the entire landscape. Failure to account for wetlands had little impact on landscape-scale estimates, because vegetation structure, composition, and conversion efficiencies were similar to upland plant communities. Plant productivity estimates were noticeably improved using LiDAR-derived variables, while uncertainties associated with land cover generalizations and wetlands in this largely forested landscape were considered less important.

Remote Sensing of Environment↗

USGS2016

Perspectives on monitoring gradual change across the continuity of Landsat sensors using time-series data

There are many types of changes occurring over the Earth's landscapes that can be detected and monitored using Landsat data. Here we focus on monitoring “within-state,” gradual changes in vegetation in contrast with traditional monitoring of “abrupt” land-cover conversions. Gradual changes result from a variety of processes, such as vegetation growth and succession, damage from insects and disease, responses to shifts in climate, and other factors. Despite the prevalence of gradual changes across the landscape, they are largely ignored by the remote sensing community. Gradual changes are best characterized and monitored using time-series analysis, and with the successful launch of Landsat 8 we now have appreciable data continuity that extends the Landsat legacy across the previous 43 years. In this study, we conducted three related analyses: (1) comparison of spectral values acquired by Landsats 7 and 8, separated by eight days, to ensure compatibility for time-series evaluation; (2) tracking of multitemporal signatures for different change processes across Landsat 5, 7, and 8 sensors using anniversary-date imagery; and (3) tracking the same type of processes using all available acquisitions. In this investigation, we found that data representing natural vegetation from Landsats 5, 7, and 8 were comparable and did not indicate a need for major modification prior to use for long-term monitoring. Analyses using anniversary-date imagery can be very effective for assessing long term patterns and trends occurring across the landscape, and are especially good for providing insights regarding trends related to long-term and continuous trends of growth or decline. We found that use of all available data provided a much more comprehensive level of understanding of the trends occurring, providing information about rate, duration, and intra- and inter-annual variability that could not be readily gleaned from the anniversary date analyses. We observed that using all available clear Landsat 5–8 observations with the new Continuous Change Detection and Classification (CCDC) algorithm was very effective for illuminating vegetation trends. There are a number of potential challenges for assessing gradual changes, including atmospheric impacts, algorithm development and visualization of the changes. One of the biggest challenges for studying gradual change will be the lack of appropriate data for validating results and products.

Remote Sensing of Environment↗

USGS2016

Mapping changing distributions of dominant species in oil-contaminated salt marshes of Louisiana using imaging spectroscopy

The April 2010 Deepwater Horizon (DWH) oil spill was the largest coastal spill in U.S. history. Monitoring subsequent change in marsh plant community distributions is critical to assess ecosystem impacts and to establish future coastal management priorities. Strategically deployed airborne imaging spectrometers, like the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), offer the spectral and spatial resolution needed to differentiate plant species. However, obtaining satisfactory and consistent classification accuracies over time is a major challenge, particularly in dynamic intertidal landscapes. Here, we develop and evaluate an image classification system for a time series of AVIRIS data for mapping dominant species in a heavily oiled salt marsh ecosystem. Using field-referenced image endmembers and canonical discriminant analysis (CDA), we classified 21 AVIRIS images acquired during the fall of 2010, 2011 and 2012. Classification results were evaluated using ground surveys that were conducted contemporaneously to AVIRIS collection dates. We analyzed changes in dominant species cover from 2010 to 2012 for oiled and non-oiled shorelines. CDA discriminated dominant species with a high level of accuracy (overall accuracy = 82%, kappa = 0.78) and consistency over three imaging dates (overall 2010 = 82%, overall 2011 = 82%, overall 2012 = 88%). Marshes dominated by Spartina alterniflora were the most spatially abundant in shoreline zones (≤ 28 m from shore) for all three dates (2010 = 79%, 2011 = 61%, 2012 = 63%), followed by Juncus roemerianus (2010 = 11%, 2011 = 19%, 2012 = 17%) and Distichlis spicata (2010 = 4%, 2011 = 10%, 2012 = 7%). Marshes that were heavily contaminated with oil exhibited variable responses from 2010 to 2012. Marsh vegetation classes converted to a subtidal, open water class along oiled and non-oiled shorelines that were similarly situated in the landscape. However, marsh loss along oil-contaminated shorelines doubled that of non-oiled shorelines. Only S. alterniflora dominated marshes were extensively degraded, losing 15% (354,604 m 2 ) cover in oiled shoreline zones, suggesting that S. alterniflora marshes may be more vulnerable to shoreline erosion following hydrocarbon stress, due to their landscape position.

Louisiana↗

USGS2020

Estimating wildfire fuel consumption with multitemporal airborne laser scanning data and demonstrating linkage with MODIS-derived fire radiative energy

Characterizing pre- and post-fire fuels remains a key challenge for estimating biomass consumption and carbon emissions from wildfires. Airborne laser scanning (ALS) data have demonstrated effectiveness for estimating canopy, and to a lesser degree, surface fuel components at fine-scale (i.e., 30 m) across landscapes. Using pre- and post-fire ALS data and corresponding field data, this study estimated consumption of canopy fuel (ΔCF), understory fuel (ΔUF), total fuel (ΔTF), and canopy bulk density (ΔCBD) for the 2012 Pole Creek fire in Oregon, USA (10,760 ha), and portions of the 2011 Las Conchas fire in New Mexico, USA (4,934 ha). Additionally, the feasibility of predicting fuel consumption was tested using separate pre- and post-fire models (PrePost), models combining all pre- and post-fire data (Pooled), and models using all data from both fires (Global). Estimates of ΔTF were then compared to fire radiative energy (FRE, units: MJ) derived from Fire Radiative Power (FRP, units: MW) observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard NASA Terra and Aqua satellites to mechanistically derive a biomass combustion coefficient (BCC, units: kg MJ −1 ). The PrePost and Pooled approaches yielded similar results at Las Conchas, but at Pole Creek insufficient pre-fire field data resulted in erroneous fuel consumption estimates outside the fire perimeter using the PrePost models. These results demonstrated that pre-fire field data were less important for these models than having field data which represent the full range of fuel conditions likely to exist across the landscape. Estimated total biomass consumed for the PrePost, Pooled, and Global models were 226 Gg, 224 Gg, and 224 Gg at Las Conchas, and 581 Gg, 713 Gg, and 552 Gg at Pole Creek. Comparisons between estimated ΔTF and FRE yielded an average BCC for both fires of 0.367 (s.d. ± 0.049) kg MJ −1 based on pixels with at least five MODIS observations. Both higher MODIS observations per pixel and accounting for canopy occlusion of FRE improved the relationship between ΔTF and MODIS-FRE. This study suggested a practical modelling approach for future efforts using only post-fire field observations and quantified a landscape-scale relationship between MODIS-derived FRE and fine-scale fuel consumption consistent with prior experiments.

New Mexico, Oregon↗

USGS2022

Monitoring and characterizing multi-decadal variations of urban thermal condition using time-series thermal remote sensing and dynamic land cover data

Urban development and associated land cover and land use change alter the thermal, hydrological, and physical properties of the land surface. Assessments of surface urban heat island (UHI) usually focused on using remote sensing and land cover data to quantify UHI intensity and spatial distribution within a certain period. However, the mechanisms and complex interactions in landscape dynamics and land surface thermal features are still being assessed. In this study, we developed and implemented a novel approach to characterize landscape thermal conditions by focusing on UHI intensity and its spatiotemporal variation using the recently available time series of Landsat land surface temperature and land cover change products. We analyzed land surface temperature changes in urban and surrounding non-urban lands to quantify the UHI intensity and landscape thermal conditions in the Atlanta and Minneapolis metropolitan areas of the United States. Our results revealed that UHI intensities had averages of 3.4 °C and 3.3 °C in the Atlanta and Minneapolis metropolitan areas, respectively. The dominant land cover type in rural areas and urban imperviousness cover determines the UHI intensity. Increasing trends of 0.04 °C/year and 0.01 °C/year in UHI intensity between 1985 and 2018 were found in Atlanta and Minneapolis, respectively. The UHI intensity variations in 1985 and 2018 suggest that the magnitudes and temporal variations of UHI intensity averaged from all urban land cover classes are close to the UHI intensity estimated from the low intensity urban area only while the UHI intensities are more than 2 °C larger in medium to high and high intensity urban areas. The UHI intensities estimated from the maximum temperature that have statistically significant increasing trends suggest that the maximum temperature is a good element for measuring UHI effect. Urban land cover dynamics play an important role in controlling temporal variation of UHI and the UHI hotspots. Our findings support the scientific value of implementing the prototype approach as an objective framework to quantify and monitor UHI intensity at a large geographic extent.

Remote Sensing of Environment↗

USGS2016

Mercury in western North America: A synthesis of environmental contamination, fluxes, bioaccumulation, and risk to fish and wildlife

Western North America is a region defined by extreme gradients in geomorphology and climate, which support a diverse array of ecological communities and natural resources. The region also has extreme gradients in mercury (Hg) contamination due to a broad distribution of inorganic Hg sources. These diverse Hg sources and a varied landscape create a unique and complex mosaic of ecological risk from Hg impairment associated with differential methylmercury (MeHg) production and bioaccumulation. Understanding the landscape-scale variation in the magnitude and relative importance of processes associated with Hg transport, methylation, and MeHg bioaccumulation requires a multidisciplinary synthesis that transcends small-scale variability. The Western North America Mercury Synthesis compiled, analyzed, and interpreted spatial and temporal patterns and drivers of Hg and MeHg in air, soil, vegetation, sediments, fish, and wildlife across western North America. This collaboration evaluated the potential risk from Hg to fish, and wildlife health, human exposure, and examined resource management activities that influenced the risk of Hg contamination. This paper integrates the key information presented across the individual papers that comprise the synthesis. The compiled information indicates that Hg contamination is widespread, but heterogeneous, across western North America. The storage and transport of inorganic Hg across landscape gradients are largely regulated by climate and land-cover factors such as plant productivity and precipitation. Importantly, there was a striking lack of concordance between pools and sources of inorganic Hg, and MeHg in aquatic food webs. Additionally, water management had a widespread influence on MeHg bioaccumulation in aquatic ecosystems, whereas mining impacts where relatively localized. These results highlight the decoupling of inorganic Hg sources with MeHg production and bioaccumulation. Together the findings indicate that developing efforts to control MeHg production in the West may be particularly beneficial for reducing food web exposure instead of efforts to simply control inorganic Hg sources.

Science of the Total Environment↗