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At least 973 records · Page 54Linked to original sources

USGS2002

Geodetic imaging: Reservoir monitoring using satellite interferometry

Fluid fluxes within subsurface reservoirs give rise to surface displacements, particularly over periods of a year or more. Observations of such deformation provide a powerful tool for mapping fluid migration within the Earth, providing new insights into reservoir dynamics. In this paper we use Interferometric Synthetic Aperture Radar (InSAR) range changes to infer subsurface fluid volume strain at the Coso geothermal field. Furthermore, we conduct a complete model assessment, using an iterative approach to compute model parameter resolution and covariance matrices. The method is a generalization of a Lanczos-based technique which allows us to include fairly general regularization, such as roughness penalties. We find that we can resolve quite detailed lateral variations in volume strain both within the reservoir depth range (0.4-2.5 km) and below the geothermal production zone (2.5-5.0 km). The fractional volume change in all three layers of the model exceeds the estimated model parameter uncertainly by a factor of two or more. In the reservoir depth interval (0.4-2.5 km), the predominant volume change is associated with northerly and westerly oriented faults and their intersections. However, below the geothermal production zone proper [the depth range 2.5-5.0 km], there is the suggestion that both north- and northeast-trending faults may act as conduits for fluid flow.

Geophysical Journal International↗

USGS2006

Distribution, 14 C chronology, and paleomagnetism of latest Pleistocene and Holocene lava flows at Haleakala volcano, Island of Maui, Hawai'i: A revision of lava flow hazard zones

New mapping and 60 new radiocarbon ages define the age and distribution of latest Pleistocene and Holocene (past 13,000 years) lava flows at Haleakalā volcano, Island of Maui. Paleomagnetic directions were determined for 118 sites, of which 89 are in lava flows younger than 13,000 years. The paleomagnetic data, in conjunction with a reference paleosecular variation (PSV) curve for the Hawaiian Islands, are combined with our knowledge of age limitations based on stratigraphic control to refine age estimates for some of the undated lava flows. The resulting volumetric rate calculations indicate that within analytical error, the extrusion rate has remained nearly constant during the past 13,000 years, in the range 0.05–0.15 km 3 /kyr, only about half the long-term rate required to produce the postshield strata emplaced in the past &sim;1 Myr. Haleakalā's eruptive frequency is similar to that of Hualālai volcano on the Island of Hawai‘i, but its lava flows cover substantially less area per unit time. The reduced rates of lava coverage indicate a lower volcanic hazard than in similar zones at Hualālai.

Hawaii↗

USGS2006

Regional P wave velocity structure of the Northern Cascadia Subduction Zone

This paper presents the first regional three-dimensional, P wave velocity model for the Northern Cascadia Subduction. Zone (SW British Columbia and NW Washington State) constructed through tomographic inversion of first-arrival traveltime data from active source experiments together with earthquake traveltime data recorded at permanent stations. The velocity model images the structure of the subducting Juan de Fuca plate, megathrust, and the fore-arc crust and upper mantle. Beneath southern Vancouver Island the megathrust above the Juan de Fuca plate is characterized by a broad zone (25-35 km depth) having relatively low velocities of 6.4-6.6 km/s. This relative low velocity zone coincides with the location of most of the episodic tremors recently mapped beneath Vancouver Island, and its low velocity may also partially reflect the presence of trapped fluids and sheared lower crustal rocks. The rocks of the Olympic Subduction Complex are inferred to deform aseismically as evidenced by the lack of earthquakes withi the low-velocity rocks. The fore-arc upper mantle beneath the Strait of Georgia and Puget Sound is characterized by velocities of 7.2-7.6 km/s. Such low velocities represent regional serpentinization of the upper fore-arc mantle and provide evidence for slab dewatering and densification. Tertiary sedimentary basins in the Strait of Georgia and Puget Lowland imaged by the velocity model lie above the inferred region of slab dewatering and densification and may therefore partly result from a higher rate of slab sinking. In contrast, sedimentary basins in the Strait of Juan de Fuca lie in a synclinal depression in the Crescent Terrane. The correlation of in-slab earthquake hypocenters M>4 with P wave velocities greater than 7.8 km/s at the hypocenters suggests that they originate near the oceanic Moho of the subducting Juan de Fuca plate. Copyright 2006 by the American Geophysical Union.

Journal of Geophysical Research B: Solid Earth↗

USGS2021

Long-term carbon sinks in marsh soils of coastal Louisiana are at risk to wetland loss

Coastal marshes are essential habitats for soil carbon accumulation and burial, which can influence the global carbon budget. Coastal Louisiana has extensive marsh habitats (fresh, intermediate, brackish, and saline) where soil cores were collected to a depth of 100 cm at 24 sites to assess long-term carbon accumulation and burial rates. Select soil depth intervals were analyzed for bulk density, total carbon, and radionuclide ( 137 Cs and 210 Pb) dating. Marsh habitat maps (years 1949–2013) were also used to determine the most frequently occurring habitat at each field site. Over 5 decades, half of the sites transitioned between marsh habitats at least once. Saline marshes tended to have lower mean total carbon density (0.04 ± 0.002 g cm −3 ) and lower mean long-term total carbon accumulation rates (211 ± 46 g TC m −2 yr −1 , n = 5, based on 210 Pb) compared to the other marsh habitats. Using marsh habitat specific accumulation rates and area, the total carbon burial rate for coastal Louisiana in year 2013 was estimated at 4.3 Tg TC yr −1 which accounts for about 5%–21% of the estimated tidal wetland burial rate globally. Historically, about 1.0 Tg TC yr −1 was lost due to reduced marsh area from 1949 to 2013. With no coastal restoration activity, the predicted wetland loss over the next 50 years could reduce carbon burial in coastal Louisiana to 2.1 Tg TC yr −1 , a reduction of about 50% from the year 2013 rate, with potential to significantly alter the global carbon budget.

Louisiana↗

USGS2022

Predicted uranium and radon concentrations in New Hampshire (USA) groundwater—Using Multi Order Hydrologic Position as predictors

Two radioactive elements, uranium (U) and radon (Rn), which are of potential concern in New Hampshire (NH) groundwater, are investigated. Exceedance probability maps are tools to highlight locations where the concentrations of undesirable substances in the groundwater may be elevated. Two forms of statistical analysis are used to create exceedance probability maps for U and Rn in NH groundwater. The first, Boosted Regression Tree (BRT), was selected for estimating U exceedance values. It computes exceedance values directly using the Bernoulli distribution function. The second method of statistical analysis used for Rn to determine exceedance probabilities is ordinary least squares (OLS) regression. In the process of determining exceedance probabilities for U and Rn, the utility of a new dataset is investigated. That new predictor dataset is the Multi-Order Hydrologic Position (MOHP) dataset. MOHP raster datasets have been produced nationally for the conterminous United States at a 30-m resolution. The concept behind MOHP is that, for any given point on the earth's surface, there is the potential for a longer groundwater flow path as one goes deeper beneath the land surface. MOHP predictors were tested in both models. Three MOHP predictors were found useful in the BRT model and two in the OLS model. MOHP data were found useful as predictors along with other site characteristics in predicting U and Rn exceedance probabilities in New Hampshire groundwater.

New Hampshire↗

USGS2025

Modelling and mapping burn severity of prescribed and wildfires across the southeastern United States (2000-2022)

Background The southeastern United States (‘Southeast’) experiences high levels of fire activity, but the preponderance of small and prescribed fires means that existing burn severity products are incomplete across the region. Aims We developed and applied a burn severity model across the Southeast to enhance our understanding of regional burn severity patterns. Methods We used Composite Burn Index (CBI) plot data from across the conterminous US (CONUS) to train a gradient-boosted decision tree model. The model was optimised for the Southeast and applied to the annual Landsat Burned Area product for 2000–2022 across the region. Key results The burn severity model had a root mean square error (RMSE) of 0.48 ( R 2 = 0.70) and 0.50 ( R 2 = 0.37) for the CONUS and Southeast, respectively. The Southeast, relative to CONUS, had lower mean absolute residuals in low and moderate burn severity categories. Burn severity was consistently lower in areas affected by prescribed burns relative to wildfires. Conclusions Although regional performance was limited by a lack of high burn severity CBI plots, the burn severity dataset demonstrated patterns consistent with low-severity, frequent fire regimes characteristic of Southeastern ecosystems. Implications More complete data on burn severity will enhance regional management of fire-dependent ecosystems and improve estimates of fuels and fire emissions.

Southeastern United States↗

USGS2016

Illuminating wildfire erosion and deposition patterns with repeat terrestrial lidar

Erosion following a wildfire is much greater than background erosion in forests because of wildfire-induced changes to soil erodibility and water infiltration. While many previous studies have documented post-wildfire erosion with point and small plot-scale measurements, the spatial distribution of post-fire erosion patterns at the watershed scale remains largely unexplored. In this study lidar surveys were collected periodically in a small, first-order drainage basin over a period of 2 years following a wildfire. The study site was relatively steep with slopes ranging from 17° to > 30°. During the study period, several different types of rain storms occurred on the site including low-intensity frontal storms (2.4 mm h −1 ) and high-intensity convective thunderstorms (79 mm h −1 ). These storms were the dominant drivers of erosion. Erosion resulting from dry ravel and debris flows was notably absent at the site. Successive lidar surveys were subtracted from one another to obtain digital maps of topographic change between surveys. The results show an evolution in geomorphic response, such that the erosional response after rain storms was strongly influenced by the previous erosional events and pre-fire site morphology. Hillslope and channel roughness increased over time, and the watershed armored as coarse cobbles and boulders were exposed. The erosional response was spatially nonuniform; shallow erosion from hillslopes (87% of the study area) contributed 3 times more sediment volume than erosion from convergent areas (13% of the study area). However, the total normalized erosion depth (volume/area) was highest in convergent areas. From a detailed understanding of the spatial locations of erosion, we made inferences regarding the processes driving erosion. It appears that hillslope erosion is controlled by rain splash (for detachment) and overland flow (for transport and quasi-channelized erosion), with the sites of highest erosion corresponding to locations with the lowest roughness. By contrast, in convergent areas we found erosion caused by overland flow. Soil erosion was locally interrupted by immobile objects such as boulders, bedrock, or tree trunks, resulting in a patchy erosion network with increasing roughness over time.

Colorado↗

USGS2005

Estimating discharge in rivers using remotely sensed hydraulic information

A methodology to estimate in-bank river discharge exclusively from remotely sensed hydraulic data is developed. Water-surface width and maximum channel width measured from 26 aerial and digital orthophotos of 17 single channel rivers and 41 SAR images of three braided rivers were coupled with channel slope data obtained from topographic maps to estimate the discharge. The standard error of the discharge estimates were within a factor of 1.5-2 (50-100%) of the observed, with the mean estimate accuracy within 10%. This level of accuracy was achieved using calibration functions developed from observed discharge. The calibration functions use reach specific geomorphic variables, the maximum channel width and the channel slope, to predict a correction factor. The calibration functions are related to channel type. Surface velocity and width information, obtained from a single C-band image obtained by the Jet Propulsion Laboratory's (JPL's) AirSAR was also used to estimate discharge for a reach of the Missouri River. Without using a calibration function, the estimate accuracy was +72% of the observed discharge, which is within the expected range of uncertainty for the method. However, using the observed velocity to calibrate the initial estimate improved the estimate accuracy to within +10% of the observed. Remotely sensed discharge estimates with accuracies reported in this paper could be useful for regional or continental scale hydrologic studies, or in regions where ground-based data is lacking. ?? 2004 Elsevier B.V. All rights reserved.

Journal of Hydrology↗

USGS2007

Generation and validation of characteristic spectra from EO1 Hyperion image data for detecting the occurrence of the invasive species, Chinese tallow

Chinese tallow (Triadica sebifera) is an invasive tree that is spreading throughout the south-eastern United States and now into the west, and in many places causing extensive change to native habitat and associated wildlife. Detecting and mapping the relative distribution of this species is important to its control and eradication. To map the relative distribution of Chinese tallow within a southwestern Louisiana coastal wetland to upland environment, Earth Observing 1 (EO1) satellite Hyperion sensor hyperspectral image data were combined with a subpixel extraction method that modelled characteristic spectra from the image data without requiring a priori characteristic spectra. Because of the low percentage occurrences of Chinese tallow and high spectral covariation in the environment, unique validation and verification methods were implemented, relying on simultaneous collection of field canopy reflectance spectra and subsequent classification of canopy compositions. The subpixel extraction method produced five characteristic spectra, which we further refined to four that adequately represented the field spectra, as well as the Hyperion imaged canopy reflectance datasets. Characteristic spectra were designated as senescing foliage, cypress-tupelo trees, and trees without leaves; shadows and green vegetation; senescing Chinese tallow with yellow leaves and yellowing foliage; and senescing Chinese tallow with red leaves ('red tallow'). About 81% (n=34) of the field and 78% (n=33) of the Hyperion imaged characteristic spectra associated with 'red tallow' were explained by the compositions generated in the field slide classifications. ?? 2005 US Government.

International Journal of Remote Sensing↗

USGS2010

Predicting species distributions from checklist data using site-occupancy models

Aim: (1) To increase awareness of the challenges induced by imperfect detection, which is a fundamental issue in species distribution modelling; (2) to emphasize the value of replicate observations for species distribution modelling; and (3) to show how 'cheap' checklist data in faunal/floral databases may be used for the rigorous modelling of distributions by site-occupancy models. Location: Switzerland. Methods: We used checklist data collected by volunteers during 1999 and 2000 to analyse the distribution of the blue hawker, Aeshna cyanea (Odonata, Aeshnidae), a common dragonfly in Switzerland. We used data from repeated visits to 1-ha pixels to derive 'detection histories' and apply site-occupancy models to estimate the 'true' species distribution, i.e. corrected for imperfect detection. We modelled blue hawker distribution as a function of elevation and year and its detection probability of elevation, year and season. Results: The best model contained cubic polynomial elevation effects for distribution and quadratic effects of elevation and season for detectability. We compared the site-occupancy model with a conventional distribution model based on a generalized linear model, which assumes perfect detectability (p = 1). The conventional distribution map looked very different from the distribution map obtained using site-occupancy models that accounted for the imperfect detection. The conventional model underestimated the species distribution by 60%, and the slope parameters of the occurrence-elevation relationship were also underestimated when assuming p = 1. Elevation was not only an important predictor of blue hawker occurrence, but also of the detection probability, with a bell-shaped relationship. Furthermore, detectability increased over the season. The average detection probability was estimated at only 0.19 per survey. Main conclusions: Conventional species distribution models do not model species distributions per se but rather the apparent distribution, i.e. an unknown proportion of species distributions. That unknown proportion is equivalent to detectability. Imperfect detection in conventional species distribution models yields underestimates of the extent of distributions and covariate effects that are biased towards zero. In addition, patterns in detectability will erroneously be ascribed to species distributions. In contrast, site-occupancy models applied to replicated detection/non-detection data offer a powerful framework for making inferences about species distributions corrected for imperfect detection. The use of 'cheap' checklist data greatly enhances the scope of applications of this useful class of models. ?? 2010 Blackwell Publishing Ltd.

Journal of Biogeography↗

USGS2009

Three‐dimensional model of Hellenic Arc deformation and origin of the Cretan uplift

[1] The Hellenic Arc of Greece is the most seismically active part of Europe, but little is know about its mechanics. We modeled deformation along the arc using a finite element model. The model was intended to capture large‐scale 3‐D structure of Nubian plate subduction beneath the Aegean block and its deformational consequences. The shape of the interface was developed using mapped traces at the surface and earthquake hypocenters at depth. Model block motions were constrained by recent compilations of GPS velocity vectors. We simulated a 10 ka period of convergence between Nubia and the Aegean and calculated the strain field in the overriding plate as well as the spatial distribution and orientation of differential stress (∣ σ 1 − σ 3 ∣). From these calculations we derived testable quantities such as the expected seismic moment rate on the interplate contact, uplift pattern, and distribution of strain modes. Our relatively simple model broadly reproduced observed uplift patterns, earthquake activity, and loci of extension and contraction. The model showed a localization of uplift near the island of Crete, where the fastest Aegean uplift rates are well documented. Comparison of calculated expected seismic moment and observed earthquake catalogs implies a nearly fully coupled interplate contact. On the basis of our modeling results, we suggest that south Aegean deformation is driven primarily by the fast moving (∼33 mm a −1 ) Aegean upper plate overriding a nearly stalled (∼5 mm a −1 ) Nubian lower plate. This tectonic setting thus more closely resembles a continental thrust than it does a typical oceanic subduction zone.

Aegean Sea, Hellenic Arc↗

USGS2015

Spatial occupancy models for predicting metapopulation dynamics and viability following reintroduction

The reintroduction of a species into its historic range is a critical component of conservation programmes designed to restore extirpated metapopulations. However, many reintroduction efforts fail, and the lack of rigorous monitoring programmes and statistical models have prevented a general understanding of the factors affecting metapopulation viability following reintroduction. Spatially explicit metapopulation theory provides the basis for understanding the dynamics of fragmented populations linked by dispersal, but the theory has rarely been used to guide reintroduction programmes because most spatial metapopulation models require presence–absence data from every site in the network, and they do not allow for observation error such as imperfect detection. We develop a spatial occupancy model that relaxes these restrictive assumptions and allows for inference about metapopulation extinction risk and connectivity. We demonstrate the utility of the model using six years of data on the Chiricahua leopard frog Lithobates chiricahuensis , a threatened desert-breeding amphibian that was reintroduced to a network of sites in Arizona USA in 2003. Our results indicate that the model can generate precise predictions of extinction risk and produce connectivity maps that can guide conservation efforts following reintroduction. In the case of L. chiricahuensis , many sites were functionally isolated, and 82% of sites were characterized by intermittent water availability and high local extinction probabilities (0·84, 95% CI: 0·64–0·99). However, under the current hydrological conditions and spatial arrangement of sites, the risk of metapopulation extinction is estimated to be <3% over a 50-year time horizon. Low metapopulation extinction risk appears to result from the high dispersal capability of the species, the high density of sites in the region and the existence of predator-free permanent wetlands with low local extinction probabilities. Should management be required, extinction risk can be reduced by either increasing the hydroperiod of existing sites or by creating new sites to increase connectivity. Synthesis and applications . This work demonstrates how spatio-temporal statistical models based on ecological theory can be applied to forecast the outcomes of conservation actions such as reintroduction. Our spatial occupancy model should be particularly useful when management agencies lack the funds to collect intensive individual-level data.

Arizona, New Mexico↗

USGS2021

Principles for collaborative risk communication: Reducing landslide losses in Puerto Rico

Landslides are frequent and damaging natural hazards that threaten the people and the natural and built environments of Puerto Rico. In 2017, more than 70,000 landslides were triggered across the island by heavy rainfall from Hurricane María, prompting requests by local professionals for landslide education and outreach materials. This article describes a novel collaborative risk communication framework that was developed to meet those requests and shaped the creation of a Spanish- and English-language Landslide Guide for Residents of Puerto Rico. Collaborative risk communication is defined here as an iterative process guided by a set of principles for the interdisciplinary coproduction of hazards information and communication products by local and external stakeholders. The process that supports this form of risk communication involves mapping out the risk communication stakeholders in the at-risk or disaster-affected location—in this case Puerto Rico—and collaborating over time to address a shared challenge, such as landslide hazards. The approach described in this article involved the formation of a core team of government and university partners that expanded in membership to conduct collaborative work with an informal network of hazards professionals from diverse sectors in Puerto Rico. The following principles guided this process: cultural competence, ethical engagement, listening, inclusive decision making, empathy, convergence research, nested mentoring, adaptability, and reciprocity. This article contributes to the field of risk communication and emergency management by detailing these principles and the associated process in order to motivate collaborative risk communication efforts in different geographic and cultural contexts. While the work described here focuses on addressing landslides, the principles and process are transferable to other natural, technological, and willful human-caused hazards. They may also serve as a roadmap for future partnerships among government agencies and university researchers to inform the cocreation of science education and outreach tools.

Puerto Rico↗

USGS2011

Upscaling carbon fluxes over the Great Plains grasslands: Sinks and sources

Previous studies suggested that the grasslands may be carbon sinks or near equilibrium, and they often shift between carbon sources in drought years and carbon sinks in other years. It is important to understand the responses of net ecosystem production (NEP) to various climatic conditions across the U.S. Great Plains grasslands. Based on 15 grassland flux towers, we developed a piecewise regression model and mapped the grassland NEP at 250 m spatial resolution over the Great Plains from 2000 to 2008. The results showed that the Great Plains was a net sink with an averaged annual NEP of 24 ± 14 g C m −2 yr −1 , ranging from a low value of 0.3 g C m −2 yr −1 in 2002 to a high value of 47.7 g C m −2 yr −1 in 2005. The regional averaged NEP for the entire Great Plains grasslands was estimated to be 336 Tg C yr −1 from 2000 to 2008. In the 9 year period including 4 dry years, the annual NEP was very variable in both space and time. It appeared that the carbon gains for the Great Plains were more sensitive to droughts in the west than the east. The droughts in 2000, 2002, 2006, and 2008 resulted in increased carbon losses over drought-affected areas, and the Great Plains grasslands turned into a relatively low sink with NEP values of 15.8, 0.3, 20.1, and 10.2 g C m −2 yr −1 for the 4 years, respectively.

Journal of Geophysical Research: Biogeosciences↗

USGS2005

Quaternary geomorphology and modern coastal development in response to an inherent geologic framework: An example from Charleston, South Carolina

Coastal landscapes evolve over wide-ranging spatial and temporal scales in response to physical and biological processes that interact with a wide range of variables. To develop better predictive models for these dynamic areas, we must understand the influence of these variables on coastal morphologies and ultimately how they influence coastal processes. This study defines the influence of geologic framework variability on a classic mixed-energy coastline, and establishes four categorical scales of spatial and temporal influence on the coastal system. The near-surface, geologic framework was delineated using high-resolution seismic profiles, shallow vibracores, detailed geomorphic maps, historical shorelines, aerial photographs, and existing studies, and compared to the long- and short-term development of two coastal compartments near Charleston, South Carolina. Although it is clear that the imprint of a mixed-energy tidal and wave signal (basin-scale) dictates formation of drumstick barriers and that immediate responses to wave climate are dramatic, island size, position, and longer-term dynamics are influenced by a series of inherent, complex near-surface stratigraphic geometries. Major near-surface Tertiary geometries influence inlet placement and drainage development (island-scale) through multiple interglacial cycles and overall channel morphology (local-scale). During the modern marine transgression, the halo of ebb-tidal deltas greatly influence inlet region dynamics, while truncated beach ridges and exposed, differentially erodable Cenozoic deposits in the active system influence historical shoreline dynamics and active shoreface morphologies (block-scale). This study concludes that the mixed-energy imprint of wave and tide theories dominates general coastal morphology, but that underlying stratigraphic influences on the coast provide site-specific, long-standing imprints on coastal evolution.

Journal of Coastal Research↗

USGS2013

Geologic effects on groundwater salinity and discharge into an estuary

Submarine groundwater discharge (SGD) can be an important pathway for transport of nutrients and contaminants to estuaries. A better understanding of the geologic and hydrologic controls on these fluxes is critical for their estimation and management. We examined geologic features, porewater salinity, and SGD rates and patterns at an estuarine study site. Seismic data showed the existence of paleovalleys infilled with estuarine mud and peat that extend hundreds of meters offshore. A low-salinity groundwater plume beneath this low-permeability fill was mapped with continuous resistivity profiling. Extensive direct SGD measurements with seepage meters ( n = 551) showed fresh groundwater discharge patterns that correlated well with shallow porewater salinity and the hydrogeophysical framework. Small-scale variability in fresh and saline discharge indicates influence of meter-scale geologic heterogeneity, while site-scale discharge patterns are evidence of the influence of the paleovalley feature. Beneath the paleovalley fill, fresh groundwater flows offshore and mixes with saltwater before discharging along paleovalley flanks. On the adjacent drowned interfluve where low-permeability fill is absent, fresh groundwater discharge is focused at the shoreline. Shallow saltwater exchange was greatest across sandy sediments and where fresh SGD was low. The geologic control of groundwater flowpaths and discharge salinity demonstrated in this work are likely to affect geochemical reactions and the chemical loads delivered by SGD to coastal surface waters. Because similar processes are likely to exist in other estuaries where drowned paleovalleys commonly cross modern shorelines, the existence and implications of complex hydrogeology are important considerations for studies of groundwater fluxes and related management decisions.

Delaware↗

USGS2014

Investigating organic matter in Fanno Creek, Oregon, Part 2 of 3: sources, sinks, and transport of organic matter with fine sediment

Organic matter (OM) is abundant in Fanno Creek, Oregon, USA, and has been tied to a variety of water-quality concerns, including periods of low dissolved oxygen downstream in the Tualatin River, Oregon. The key sources of OM in Fanno Creek and other Tualatin River tributaries have not been fully identified, although isotopic analyses from previous studies indicated a predominantly terrestrial source. This study investigates the role of fine sediment erosion and deposition (mechanisms and spatial patterns) in relation to OM transport. Geomorphic mapping within the Fanno Creek floodplain shows that a large portion (approximately 70%) of the banks are eroding or subject to erosion, likely as a result of the imbalance caused by anthropogenic alteration. Field measurements of long- and short-term bank erosion average 4.2 cm/year and average measurements of deposition for the watershed are 4.8 cm/year. The balance between average annual erosion and deposition indicates an export of 3,250 metric tons (tonnes, t) of fine sediment to the Tualatin River—about twice the average annual export of 1,880 t of sediment at a location 2.4 km from the creek’s mouth calculated from suspended sediment load regressions from continuous turbidity data and suspended sediment samples. Carbon content from field samples of bank material, combined with fine sediment export rates, indicates that about 29–67 t of carbon, or about 49–116 t of OM, from bank sediment may be exported to the Tualatin River from Fanno Creek annually, an estimate that is a lower bound because it does not account for the mass wasting of organic-rich O and A soil horizons that enter the stream.

Oregon↗

USGS2007

Characterizing the spatial structure of endangered species habitat using geostatistical analysis of IKONOS imagery

Our study used geostatistics to extract measures that characterize the spatial structure of vegetated landscapes from satellite imagery for mapping endangered Sonoran pronghorn habitat. Fine spatial resolution IKONOS data provided information at the scale of individual trees or shrubs that permitted analysis of vegetation structure and pattern. We derived images of landscape structure by calculating local estimates of the nugget, sill, and range variogram parameters within 25 ?? 25-m image windows. These variogram parameters, which describe the spatial autocorrelation of the 1-m image pixels, are shown in previous studies to discriminate between different species-specific vegetation associations. We constructed two independent models of pronghorn landscape preference by coupling the derived measures with Sonoran pronghorn sighting data: a distribution-based model and a cluster-based model. The distribution-based model used the descriptive statistics for variogram measures at pronghorn sightings, whereas the cluster-based model used the distribution of pronghorn sightings within clusters of an unsupervised classification of derived images. Both models define similar landscapes, and validation results confirm they effectively predict the locations of an independent set of pronghorn sightings. Such information, although not a substitute for field-based knowledge of the landscape and associated ecological processes, can provide valuable reconnaissance information to guide natural resource management efforts.

Arizona↗