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At least 793 records · Page 44Linked to original sources

USGS2022

The 2020 Westmorland, California earthquake swarm as aftershocks of a slow slip event sustained by fluid flow

Swarms are bursts of earthquakes without an obvious mainshock. Some have been observed to be associated with transient aseismic fault slip, while others are thought to be related to fluids. However, the association is rarely quantitative due to insufficient data quality. We use high-quality GPS/GNSS, InSAR, and relocated seismicity to study a swarm of >2,000 earthquakes which occurred between 30 September and 6 October 2020, near Westmorland, California. Using 5 min sampled Global Positioning System (GPS) supplemented with InSAR, we document a spontaneous shallow M w 5.2 slow slip event that preceded the swarm by 2–15 hr. The earthquakes in the early phase were predominantly non-interacting and driven primarily by the slow slip event resulting in a nonlinear expansion. A stress-driven model based on the rate-and-state friction successfully explains the overall spatial and temporal evolution of earthquakes, including the time lag between the onset of the slow slip event and the swarm. Later, a distinct back front and a square root of time expansion of clustered seismicity on en-echelon fault structures suggest that fluids helped sustain the swarm. Static stress triggering analysis using Coulomb stress and statistics of interevent times suggest that 45%–65% of seismicity was driven by the slow slip event, 10%–35% by inter-earthquake interactions, and 10%–30% by fluids. Our model also provides constraints on the friction parameter and the pore pressure and suggests that this swarm behaved like an aftershock sequence but with the mainshock replaced by the slow slip event.

California↗

USGS2024

Detecting avalanche path ground cover and vegetation change across multiple scales through time using remote sensing tools

Large-magnitude avalanches often alter vegetation composition, avalanche path dimensions, and subsequent avalanche return periods. Understanding temporal changes in individual avalanche path trimlines, runout zones, and geomorphic characteristics helps forecasters, planners, and engineers estimate potential avalanche destructive size and impact on infrastructure or settlements in the runout zone. Understanding these changes on a large scale also provides information on post-cycle avalanche distribution. Here, we use remote sensing platforms and change detection techniques to examine vegetation change in avalanche paths in Montana and Colorado. In northwest Montana, we implemented a novel approach using lidar, aerial imagery, and a random forest model to classify imagery-observed vegetation within avalanche paths. We calculated spatially explicit avalanche return periods using a physically based spatial interpolation method and characterized the vegetation within those return period zones. In Colorado, we investigated changes in avalanche path vegetation characteristics prior to and after a widespread large-magnitude avalanche cycle. The highest frequency of avalanche return periods was broadly characterized by grassland and shrubland, but topography greatly influences vegetation classes and return periods. Furthermore, statistically significant differences in lidar-derived vegetation canopy height exist between categorical return periods. We used optical sensors from satellite imagery to analyze changes in Normalized Difference Vegetation Index (NDVI) to calculate ground cover change over time. NDVI, a measure of near-infrared and red bands within the imagery, allowed us to distinguish between green vegetation (e.g., trees and shrubs) and non-vegetated ground cover (e.g., dead and downed trees, rocks, and dirt) within avalanche paths. For this study, we calculated changes in NDVI values by comparing imagery from 2018 to imagery from 2019 after a widespread large magnitude avalanche cycle occurred in March 2019 in Colorado, United States. We applied a filtering process to reduce error, classified NDVI change based on the value distribution, and then calculated area change of all areas within each avalanche path. We completed this process for 1633 avalanche paths throughout Colorado. We found that using NDVI difference values pre- and post-avalanche cycle allowed us to identify ground cover change in avalanche paths throughout Colorado. These changes span from a slight expansion of existing avalanche paths to substantial landscape disturbance. For example, a size D5 avalanche caused severe ground cover change in 18% of one single path near Aspen, Colorado. This suggests that large magnitude avalanches can redefine avalanche path dimensions and could impact subsequent avalanche size and frequency. Using NDVI from satellite imagery is a simple way to detect ground cover changes in avalanche paths on a large scale or in remote areas. In general, remote sensing products to detect and examine vegetation and ground cover change in avalanche paths can help inform avalanche distribution and benefit planning efforts.

Montana↗

USGS2018

A new modeling approach to prioritize riparian restoration to reduce sediment loading in two Virginia river basins

Human impact, particularly land cover changes (e.g., agriculture, construction) increase erosion and sediment loading into streams. Benthic species are negatively affected by silt deposition that coats and embeds stream substrate. Given that riparian buffers are effective sediment filters, riparian restoration is increasingly implemented by conservation groups to protect stream habitats. Limited funding and a multitude of impaired streams warrant the need for cost-effective prioritization of potential restoration actions. We created a decision-support framework for conservation agencies and aquatic resource managers to prioritize riparian restoration efforts. Our framework integrates GIS data and field surveys into a statistical model to predict instream silt from estimates of upland soil loss and riparian filtration capacity. We focus specifically on prioritizing sites in upper sections of the Roanoke and Nottoway river basins (Virginia, US) based on observed records of Roanoke logperch ( Percina rex ), an imperiled sediment-sensitive species. Our statistical approach examines soil characteristics, land cover, precipitation, topography, and annual soil loss estimates from the empirically derived Revised Universal Soil Loss Equation, combined with land cover-based riparian filtration capacity as potential stream habitat predictors. We found riparian filtration capacity to be a significant predictor of silt cover, while precipitation was a significant predictor of embeddedness. Spatial scale was also a factor, in that spatial variance in silt cover and embeddedness was more accurately predicted at smaller spatial extents. Ultimately, our model can be used as a prioritization tool for mitigating high siltation areas, or for protecting low soil erosion areas.

North Carolina, Virginia↗

USGS2025

Evidence for nonlocal sediment transport on hillslopes from fault scarp morphology

Hillslope sediment transport processes such as bioturbation, rainsplash, and granular mechanics occur across the entire planet. Yet, it remains uncertain how these small-scale processes act together to shape landscapes. Longstanding hillslope diffusion theory posits that hillslope processes are spatially limited, whereas new concepts of nonlocal sediment transport argue otherwise. However, each theory produces subtly different, but distinct, predictions for the evolution of fault scarps. We use the topographic change of fault scarps to demonstrate that hillslope processes produce nonlocal sediment transport. Analysis of a global compilation of 340 dated single-earthquake scarp profiles reveals a statistically significant ( p < 0.05 ) relationship between scarp age and scarp asymmetry, here defined as the ratio of imaginary to real components of the Fourier transform of absolute slope. Numerical simulations show that nonlocal models predict this relationship, whereas hillslope diffusion models do not. To further investigate this result, we examined the depositional geometry of a well-exposed colluvial wedge along the Wasatch fault in central Utah, United States. Our quantitative comparison between the exposure and numerical simulations reveals better agreement with the nonlocal model. Nonlocal sediment transport theory appears to best capture the physics of how hillslope processes shape fault scarps, yet hillslope diffusion provides a useful approximation in many cases. As the processes that act on fault scarps are nearly identical to those acting on hillslopes, our results provide evidence supporting nonlocality as a generalized model of hillslope sediment transport.

Utah↗

USGS2021

Citizen science data collection for integrated wildlife population analyses

Citizen science, or community science, has emerged as a cost-efficient method to collect data for wildlife monitoring. To inform research and conservation, citizen science sampling designs should collect data that match the robust statistical analyses needed to quantify species and population patterns. Further increasing the contributions of citizen science, integrating citizen science data with other datasets and datatypes can improve population estimates and expand the spatiotemporal extent of inference. We demonstrate these points with a citizen science program called iSeeMammals developed in New York state in 2017 to supplement costly systematic spatial capture-recapture sampling by collecting opportunistic data from one-off observations, hikes, and camera traps. iSeeMammals has initially focused on the growing population of American black bear ( Ursus americanus ), with integrated analysis of iSeeMammals camera trap data with systematic data for a region with a growing bear population. The triumvirate of increased spatial and temporal coverage by at least twofold compared to systematic sampling, an 83% reduction in annual sampling costs, and improved density estimates when integrated with systematic data highlight the benefits of collecting presence-absence data in citizen science programs for estimating population patterns. Additional opportunities will come from applying presence-only data, which are oftentimes more prevalent than presence-absence data, to integrated models. Patterns in data submission and filtering also emphasize the importance of iteratively evaluating patterns in engagement, usability, and accessibility, especially focusing on younger adult and teenage demographics, to improve data quality and quantity. We explore how the development and use of integrated models may be paired with citizen science project design in order to facilitate repeated use of datasets in standalone and integrated analyses for supporting wildlife monitoring and informing conservation.

Frontiers in Ecology and Evolution↗

USGS2024

Pragmatically mapping Phragmites with unoccupied aerial systems: A comparison of invasive species land cover classification using RGB and multispectral imagery

Unoccupied aerial systems (UASs) are increasingly being deployed in coastal environments to rapidly map and monitor changes to geomorphology, vegetation, and infrastructure, particularly in difficult to access areas. UAS data, relative to airplane or satellite data, typically have higher spatial resolution, sensor customization, and increased flexibility in temporal resolution, which benefits monitoring applications. UAS data have been used to map and monitor invasive species occurrence and expansion, such as Phragmites australis , a reed species in wetlands throughout the eastern United States. To date, the work on this species has been largely opportunistic or ad hoc. Here, we statistically and qualitatively compare results from several sensors and classification workflows to develop baseline understanding of the accuracy of different approaches used to map Phragmites . Two types of UAS imagery were collected in a Phragmites -invaded salt marsh setting—natural color red-green-blue (RGB) imagery and multispectral imagery spanning visible and near infrared wavelengths. We evaluated whether one imagery type provided significantly better classification results for mapping land cover than the other, also considering trade-offs like overall accuracy, financial costs, and effort. We tested the transferability of classification workflows that provided the highest thematic accuracy to another barrier island environment with known Phragmites stands. We showed that both UAS sensor types were effective in classifying Phragmites cover, with neither resulting in significantly better classification results than the other for Phragmites detection (overall accuracy up to 0.95, Phragmites recall up to 0.86 at the pilot study site). We also found the highest accuracy workflows were transferrable to sites in a barrier island setting, although the quality of results varied across these sites (overall accuracy up to 0.97, Phragmites recall up to 0.90 at the additional study sites).

Massachusetts↗

USGS2024

Groundwater hydrology, groundwater and surface-water interactions, aquifer testing, and groundwater-flow simulations for the Fountain Creek alluvial aquifer, near Colorado Springs, Colorado, 2018–20

From 2018 through 2020, the U.S. Geological Survey, in cooperation with the Air Force Civil Engineering Center, conducted an integrated study of the Fountain Creek alluvial aquifer located near Colorado Springs, Colorado. The objective of the study was to characterize hydrologic conditions for the alluvial aquifer pertinent to the potential for transport of solutes. Specific goals of this report were to characterize the groundwater hydrology of the area, to quantify groundwater and surface-water interactions, to estimate hydraulic properties of the aquifer using aquifer testing, and to complete numerical simulations of groundwater flow. Synoptic groundwater-level elevation measurements completed throughout this study, and as part of other U.S. Geological Survey programs between 1994 and 2020, indicate groundwater-level elevations fluctuate on annual and interannual timeframes. Groundwater-level fluctuations likely were caused by temporally variable groundwater recharge and discharge components in the area, with many wells showing maximum groundwater-level elevations during the winter months (November through March). From an interannual perspective, groundwater-level fluctuations appear to have reached maximum values during 2000 to 2003, decreased during 2003 to 2006, and remained relatively constant since that time, with the exception of several wells which have displayed rising groundwater-level elevations since 2018. Spatial evaluation of groundwater-level elevations indicates groundwater flow is generally from northeast to southwest within the vicinity of several alluvial paleochannels occurring along the northeastern margin of the aquifer. Within the center of the aquifer along Fountain Creek, groundwater flow is generally from north to south, approximately paralleling surface-water flow. To quantitatively understand the potential effect of groundwater recharge and groundwater pumping on fluctuations in groundwater-level elevation, a statistical transfer-function-noise model was applied. Results of the statistical model indicate throughout most of the aquifer, fluctuations were primarily the result of recharge seasonality. In the main stem of the aquifer where groundwater pumping wells were more concentrated, however, groundwater-level elevation fluctuations were also attributable to groundwater pumping through time. Three-dimensional evaluation of the aquifer geometry near Fountain Creek was combined with synoptic streamflow measurement and accounting of stream gains and losses to evaluate groundwater and surface-water interactions in the study area. Streamflow gain or loss calculations indicate Fountain Creek both gains from and loses flow to the alluvial aquifer, and gaining or losing reaches of the stream may be partially controlled by the depth to bedrock near the stream. Reaches with streamflow gains tend to coincide with areas where the estimated depth to bedrock is decreasing, meaning the alluvial aquifer is likely thinning in these areas and groundwater-flow paths may be converging and discharging groundwater to the stream. Losing reaches tended to coincide with locally greater depth to bedrock where the alluvial aquifer is likely thicker and has greater storage potential for surface water lost from Fountain Creek. Results of aquifer testing indicate hydraulic conductivity, estimated from slug tests and single-well pumping tests, ranged from 0.32 to 1,410 feet per day (ft/d) and 4.13 to 664 ft/d, respectively. These results are similar to the range of values from previous aquifer tests in the study area. Hydraulic conductivities from aquifer testing for this study were generally greater than the estimates of previous slug tests and had a mean value less than the estimates from previous pumping tests. Spatial evaluation of aquifer testing results indicates hydraulic conductivity tends to be greater in the main stem of the alluvial aquifer and lower in paleochannels upgradient from the main stem of the aquifer. The spatial variation in hydraulic conductivity may be attributed to the geomorphologic processes that formed the alluvial aquifer. Compacted sediment in the paleochannels has not been potentially transported sufficient distance to cause grain-size sorting, resulting in a poorly sorted deposit and lower hydraulic conductivities. In the central portion of the alluvial aquifer, near Fountain Creek, the sediments have been transported farther from their source areas and are likely better sorted, removing finer grained sediments that would cause lower hydraulic conductivity. A numerical groundwater-flow model was calibrated for the Fountain Creek alluvial aquifer for 2000–19 to simulate water-budget components, groundwater-flow directions, and groundwater-flow paths. The model simulated precipitation recharge, groundwater and surface-water interactions, evapotranspiration, high-volume groundwater pumping by pumping wells, and external inflows and outflows occurring along the boundaries of the alluvial aquifer. Model calibration was completed using manual and automated approaches, the latter of which assisted in quantifying model results sensitivity to input parameters. The calibrated model corresponds well with groundwater-level elevation observations, with a mean residual (observed minus simulated groundwater-level elevation) equal to −0.60 feet. Simulated groundwater base flow to streams was typically within 10 percent of base flow estimated by independent methods. Groundwater and surface-water interactions represented the largest water-budget components of the aquifer, with the second largest groundwater discharge component coming from pumping wells. Groundwater and surface-water interactions represent both the largest gain and loss terms in the water budget, because these interactions differ spatially, meaning in some areas of the model domain groundwater is being recharged by streams, whereas in other areas, groundwater is discharged to streams. Estimates of advective groundwater-flow paths indicate pumping wells may capture groundwater recharged from losing streams and groundwater that flows into the main stem of the alluvial aquifer from paleochannels.

Colorado↗

USGS2003

A Framework for Long-term Ecological Monitoring in Olympic National Park: Prototype for the Coniferous Forest Biome

This report is the result of a five-year collaboration between scientists of the U.S. Geological Survey Forest and Rangeland Ecosystem Science Center, Olympic Field Station, and the natural resources staff of Olympic National Park to develop a comprehensive strategy for monitoring natural resources of Olympic National Park. Olympic National Park is the National Park Serviceʼs prototype monitoring park, representing parks in the coniferous forest biome. Under the umbrella of the National Park Serviceʼs prototype parks program, U.S. Geological Survey and Olympic National Park staffs are obligated to: develop strategies and designs for monitoring the long-term health and integrity of national park ecosystems with a significant coniferous forest component. design exportable monitoring protocols that can be used by other parks within the coniferous forest biome (i.e., parks having similar environments), and create a demonstration area and ʻcenter of excellenceʼ for assisting other parks in developing ecological monitoring programs. Olympic National Park is part of the North Coast and Cascades Network, a network of seven Pacific Northwestern park units created recently by the National Park Serviceʼs Inventory and Monitoring Program to extend the monitoring of ʻvital signsʼ of park health to all National Park Service units. It is our intent and hope that the monitoring strategies and conceptual models described here will meet the overall purpose of the prototype parks monitoring program in proving useful not only to Olympic National Park, but also to parks within the North Coast and Cascades Network and elsewhere. Part I contains the conceptual design and sampling framework for the prototype long-term monitoring program in Olympic National Park. In this section, we explore key elements of monitoring design that help to ensure the spatial, ecological, and temporal integration of monitoring program elements and discuss approaches used to design an ecosystem-based monitoring program. Basic monitoring components include ecosystem drivers, (e.g., climate, atmospheric inputs, human pressures), indicators of ecosystem integrity (e.g., biogeochemical indicators), known threats (e.g., impacts of introduced mountain goats), and focal or ʻkeyʼ species (e.g., rare or listed species, Roosevelt elk). Monitoring system drivers and key indicators of ecosystem integrity provide the long-term baseline needed to judge what constitutes ʻunnaturalʼ variation in park resources and provide the earliest possible warning of unacceptable change. Monitoring effects of known threats and the status of focal species will provide information useful to park managers for dealing with current park issues. In Part I we describe the process of identifying potential indicators of ecological condition and present conceptual models of park ecosystems. In addition we report results from several workshops held in conjunction with Olympic National Park aimed at identifying potential indicators of change in the parkʼs ecosystem. First, we describe the responses of Olympic National Park staff to the generic question, “What is the most important resource to monitor in Olympic National Park and why?” followed by the responses from resource and land managers from areas adjoining the park. We also catalogue the responses of various expert groups that we asked to help identify the most appropriate system drivers and indicators of change in the Olympic National Park ecosystems. Results of the workshops provided the justification for selecting basic indicators of ecosystem integrity, effects of current threats to park resources, and focal resources of parks to detect both the currently evident and unforeseeable changes in park resources. We conclude Part I by exploring several generic statistical issues relevant to monitoring natural resources in Olympic National Park. Specifically we discuss trade-offs associated with sampling extensively versus sampling intensively in smaller geographic regions and describe a conceptual framework to guide development of a generic sampling frame for monitoring. We recommend partitioning Olympic National Park into three zones of decreasing accessibility to maximize monitoring efficiency. We present examples of how the generic sampling frame could be used to help ensure spatial integration of individual monitoring projects. Part II of the report is a record of the potential monitoring questions and indicators identified to date in our workshops. The presentation is organized according to the major system drivers, components, and processes identified in the intermediate-level working model of the Olympic National Park ecosystem. For each component of the park system, we develop the need and justification for monitoring, articulate park management issues, and describe key resources and ecosystem functions. We also present a pictorial conceptual model of each ecological subsystem, identify monitoring questions, and list potential indicators for each monitoring question. We conclude each section by identifying linkages of indicators to other ecological subsystems in our general ecosystem model, spatial and temporal contexts for monitoring (where and how often to monitor), and research and development needs. Part II represents the most current detailed listing of potential indicators—the material for subsequent discussions of monitoring priorities and selection of indicators for protocol development. Collectively, the sections of this report contain a comprehensive list of the important monitoring questions and potential indicators as well as recommendations for designing an integrated monitoring program. In Part I, Chapter 6 we provide recommendations on how to proceed with the important next steps in the design process: establishing priorities among the many possible monitoring questions and indicators, and beginning to research and design effective long-term monitoring protocols.

Information and Technology Report↗

USGS2025

False positives in the identification of dynamic earthquake triggering

Dynamic earthquake triggering is commonly identified through the temporal correlation between increased seismicity rates and global earthquakes that are possible triggering events. However, correlation does not imply causation. False positives may occur when unrelated seismicity rate changes coincidently occur at around the time of candidate triggers. We investigate the expected false positive rate in Southern California with global M ≥ 6 earthquakes as candidate triggers. We compute the false positive rate by applying the statistical tests used by DeSalvio and Fan (2023), https://doi.org/10.1029/2023jb026487 to synthetic earthquake catalogs with no real dynamic triggering. We find a false positive rate of ∼3.5%–8.5% when realistic earthquake clustering is present, consistent with the 95% confidence typically used in seismology. However, when this false positive rate is applied to the tens of thousands of spatial-temporal windows in Southern California tested in DeSalvio and Fan (2023), https://doi.org/10.1029/2023jb026487 , thousands of false positives are expected. The expected false positive occurrence is large enough to explain the observed apparent triggering following 70% of large global earthquakes (DeSalvio & Fan, 2023, https://doi.org/10.1029/2023jb026487 ), without requiring any true dynamic triggering. Aside from the known triggering from the nearby El Mayor-Cucapah, Mexico, earthquake, the spatial and temporal characteristics of the reported triggering are indistinguishable from random false positives. This implies that best practice for dynamic triggering studies that depend on temporal correlation is to estimate the false positive rate and investigate whether the observed apparent triggering is distinguishable from the correlations that may occur by chance.

JGR Solid Earth↗

USGS2010

Integrating physiology, population dynamics and climate to make multi-scale predictions for the spread of an invasive insect: The Argentine ant at Haleakala National Park, Hawaii

Mechanistic models for predicting species’ distribution patterns present particular advantages and challenges relative to models developed from statistical correlations between distribution and climate. They can be especially useful for predicting the range of invasive species whose distribution has not yet reached equilibrium. Here, we illustrate how a physiological model of development for the invasive Argentine ant can be connected to differences in micro-site suitability, population dynamics and climatic gradients; processes operating at quite different spatial scales. Our study is located in the subalpine shrubland of Haleakala National Park, Hawaii, where the spread of Argentine ants Linepithema humile has been documented for the past twenty-five years. We report four main results. First, at a microsite level, the accumulation of degree-days recorded in potential ant nest sites under bare ground or rocks was significantly greater than under a groundcover of grassy vegetation. Second, annual degree-days measured where population boundaries have not expanded (456-521 degree-days), were just above the developmental requirements identified from earlier laboratory studies (445 degree-days above 15.98C). Third, rates of population expansion showed a strong linear relationship with annual degree-days. Finally, an empirical relationship between soil degree-days and climate variables mapped at a broader scale predicts the potential for future range expansion of Argentine ants at Haleakala, particularly to the west of the lower colony and the east of the upper colony. Variation in the availability of suitable microsites, driven by changes in vegetation cover and ultimately climate, provide a hierarchical understanding of the distribution of Argentine ants close to their cold-wet limit of climatic tolerances. We conclude that the integration of physiology, population dynamics and climate mapping holds much promise for making more robust predictions about the potential spread of invasive species.

Hawaii↗

USGS2005

Fractured-aquifer hydrogeology from geophysical logs; the passaic formation, New Jersey

The Passaic Formation consists of gradational sequences of mudstone, siltstone, and sandstone, and is a principal aquifer in central New Jersey. Ground‐water flow is primarily controlled by fractures interspersed throughout these sedimentary rocks and characterizing these fractures in terms of type, orientation, spatial distribution, frequency, and transmissivity is fundamental towards understanding local fluid‐transport processes. To obtain this information, a comprehensive suite of geophysical logs was collected in 10 wells roughly 46 m in depth and located within a .05 km 2 area in Hopewell Township, New Jersey. A seemingly complex, heterogeneous network of fractures identified with an acoustic televiewer was statistically reduced to two principal subsets corresponding to two distinct fracture types: (1) bedding‐plane partings and (2) high‐angle fractures. Bedding‐plane partings are the most numerous and have an average strike of N84°W and dip of 20° N. The high‐angle fractures are oriented subparallel to these features, with an average strike of N79° E and dip of 71° S, making the two fracture types roughly orthogonal. Their intersections form linear features that also retain this approximately east‐west strike. Inspection of fluid temperature and conductance logs in conjunction with flow meter measurements obtained during pumping allows the transmissive fractures to be distinguished from the general fracture population. These results show that, within the resolution capabilities of the logging tools, approximately 51 (or 18 percent) of the 280 total fractures are water producing. The bedding‐plane partings exhibit transmissivities that average roughly 5 m 2 /day and that generally diminish in magnitude and frequency with depth. The high‐angle fractures have average transmissivities that are about half those of the bedding‐plane partings and show no apparent dependence upon depth. The geophysical logging results allow us to infer a distinct hydrogeologic structure within this aquifer that is defined by fracture type and orientation. Fluid flow near the surface is controlled primarily by the highly transmissive, subhorizontal bedding‐plane partings. As depth increases, the high‐angle fractures apparently become more dominant hydrologically.

Ground Water↗

USGS2016

An assessment of the cultivated cropland class of NLCD 2006 using a multi-source and multi-criteria approach

We developed a method that analyzes the quality of the cultivated cropland class mapped in the USA National Land Cover Database (NLCD) 2006. The method integrates multiple geospatial datasets and a Multi Index Integrated Change Analysis (MIICA) change detection method that captures spectral changes to identify the spatial distribution and magnitude of potential commission and omission errors for the cultivated cropland class in NLCD 2006. The majority of the commission and omission errors in NLCD 2006 are in areas where cultivated cropland is not the most dominant land cover type. The errors are primarily attributed to the less accurate training dataset derived from the National Agricultural Statistics Service Cropland Data Layer dataset. In contrast, error rates are low in areas where cultivated cropland is the dominant land cover. Agreement between model-identified commission errors and independently interpreted reference data was high (79%). Agreement was low (40%) for omission error comparison. The majority of the commission errors in the NLCD 2006 cultivated crops were confused with low-intensity developed classes, while the majority of omission errors were from herbaceous and shrub classes. Some errors were caused by inaccurate land cover change from misclassification in NLCD 2001 and the subsequent land cover post-classification process.

Remote Sensing↗

USGS2020

Climate change: Flowering time may be shifting in surprising ways

Climate change is known to affect regional weather patterns and phenology; however, we lack under-standing of how climate drives phenological change across local spatial gradients. This spatial variation is critical for determining whether subpopulations and metacommunities are changing in unison or diverging in phenology. Divergent responses could reduce synchrony both within species (disrupting gene flow among subpopulations) and among species (disrupting interspecific interactions in communities). We also lack understanding of phenological change in environments where life history events are frequently aseasonal, such as the tropical, arid,and semi-arid ecosystems that cover vast areas.Using a 33-year-long dataset spanning a 1,267-m semi-arid elevational gradient in the southwestern United States, we test whether flowering phenology diverged among subpopulations within species and among five communities comprising 590 species. Applying circular statistics to test for changes in year-round flowering, we show flowering has become earlier for all communities except at the highest elevations. However, flowering times shifted at different rates across elevations likely because of elevation-specific changes in temperature and precipitation, indicating diverging phenologies of neighboring communities. Subpopulations of individual species also diverged at mid-elevation but converged in phenology at high elevation. These changes in flowering phenology among communities and subpopulations are undetectable when data are pooled across the gradient. Furthermore, we show that nonlinear changes in flowering times over the 33-year record are obscured by traditional calculations of long-term trends. These findings reveal greater spatiotemporal complexity in phenological responses than previously recognized and indicate climate is driving phenological reshuffling acrosslocal spatial gradients.

Current Biology↗

USGS2005

A regional classification scheme for estimating reference water quality in streams using land-use-adjusted spatial regression-tree analysis

Various approaches are used to subdivide large areas into regions containing streams that have similar reference or background water quality and that respond similarly to different factors. For many applications, such as establishing reference conditions, it is preferable to use physical characteristics that are not affected by human activities to delineate these regions. However, most approaches, such as ecoregion classifications, rely on land use to delineate regions or have difficulties compensating for the effects of land use. Land use not only directly affects water quality, but it is often correlated with the factors used to define the regions. In this article, we describe modifications to SPARTA (spatial regression-tree analysis), a relatively new approach applied to water-quality and environmental characteristic data to delineate zones with similar factors affecting water quality. In this modified approach, land-use-adjusted (residualized) water quality and environmental characteristics are computed for each site. Regression-tree analysis is applied to the residualized data to determine the most statistically important environmental characteristics describing the distribution of a specific water-quality constituent. Geographic information for small basins throughout the study area is then used to subdivide the area into relatively homogeneous environmental water-quality zones. For each zone, commonly used approaches are subsequently used to define its reference water quality and how its water quality responds to changes in land use. SPARTA is used to delineate zones of similar reference concentrations of total phosphorus and suspended sediment throughout the upper Midwestern part of the United States. ?? 2006 Springer Science+Business Media, Inc.

Environmental Management↗

USGS2016

Surface-air mercury fluxes across Western North America: A synthesis of spatial trends and controlling variables

Mercury (Hg) emission and deposition can occur to and from soils, and are an important component of the global atmospheric Hg budget. This paper focuses on synthesizing existing surface-air Hg flux data collected throughout the Western North American region and is part of a series of geographically focused Hg synthesis projects. A database of existing Hg flux data collected using the dynamic flux chamber (DFC) approach from almost a thousand locations was created for the Western North America region. Statistical analysis was performed on the data to identify the important variables controlling Hg fluxes and to allow spatiotemporal scaling. The results indicated that most of the variability in soil-air Hg fluxes could be explained by variations in soil-Hg concentrations, solar radiation, and soil moisture. This analysis also identified that variations in DFC methodological approaches were detectable among the field studies, with the chamber material and sampling flushing flow rate influencing the magnitude of calculated emissions. The spatiotemporal scaling of soil-air Hg fluxes identified that the largest emissions occurred from irrigated agricultural landscapes in California. Vegetation was shown to have a large impact on surface-air Hg fluxes due to both a reduction in solar radiation reaching the soil as well as from direct uptake of Hg in foliage. Despite high soil Hg emissions from some forested and other heavily vegetated regions, the net ecosystem flux (soil flux + vegetation uptake) was low. Conversely, sparsely vegetated regions showed larger net ecosystem emissions, which were similar in magnitude to atmospheric Hg deposition (except for the Mediterranean California region where soil emissions were higher). The net ecosystem flux results highlight the important role of landscape characteristics in effecting the balance between Hg sequestration and (re-)emission to the atmosphere.

Science of the Total Environment↗

USGS2007

Natal location influences movement and survival of a spatially structured population of snail kites

Despite the accepted importance of the need to better understand how natal location affects movement decisions and survival of animals, robust estimates of movement and survival in relation to the natal location are lacking. Our study focuses on movement and survival related to the natal location of snail kites in Florida and shows that kites, in addition to exhibiting a high level of site tenacity to breeding regions, also exhibit particular attraction to their natal region. More specifically, we found that estimates of movement from post-dispersal regions were greater toward natal regions than toward non-natal regions (differences were significant for three of four regions). We also found that estimates of natal philopatry were greater than estimates of philopatry to non-natal regions (differences were statistically significant for two of four regions). A previous study indicated an effect of natal region on juvenile survival; in this study, we show an effect of natal region on adult survival. Estimates of adult survival varied among kites that were hatched in different regions. Adults experienced mortality rates characteristic of the region occupied at the time when survival was measured, but because there is a greater probability that kites will return to their natal region than to any other regions, their survival was ultimately influenced by their natal region. In most years, kites hatched in southern regions had greater survival probabilities than did kites hatched in northern regions. However, during a multiregional drought, one of the northern regions served as a refuge from drought, and during this perturbation, survival was greater for birds hatched in the north. Our study shows that natal location may be important in influencing the ecological dynamics of kites but also highlights the importance of considering temporal variation in habitat conditions of spatially structured systems when attempting to evaluate the conservation value of habitats.

Oecologia↗

USGS2020

Sample-size considerations for a study of shorebird nest survival in the 1002 Area, Arctic National Wildlife Refuge, Alaska

Authorization of lease sales for oil development in the 1002 Area of the Arctic National Wildlife Refuge has highlighted gaps in information about biological communities in the area. The U.S. Fish and Wildlife Service, which is planning a study to evaluate spatial variation in the nest survival of tundra-breeding shorebirds to identify hotspots with high nest survival, sought advice from the U.S. Geological Survey on how to predict which sampling designs might be successful in achieving the study goals. I used previously obtained data on nest survival from Alaska’s North Slope to develop a simulation study that explored the statistical consequences of various sampling designs in the context of expected ranges of values of biological parameters. Of all sampling parameters, the number of nests per plot had the strongest influence on the ability to detect hotspots, followed by number of years of monitoring and the age at which nests were found. The benefit of sampling 98 plots instead of 68 was relatively small. Ages of nests cannot be predicted a priori, so I developed a field reference chart to identify when further nest-searching would be useful for a given plot. This simulation study used the best available information, but values of biological parameters will become better defined following subsequent data collection in the 1002 Area. Data from upcoming field seasons could be used to refine this analysis and improve estimation of the expected results of the field study, thus maximizing the likelihood that data from the 1002 Area nest survival study will meet the monitoring goals.

Alaska↗

USGS2002

Grizzly bear denning and potential conflict areas in the Greater Yellowstone Ecosystem

Increasing winter use of steep, high-elevation terrain by backcountry recreationists has elevated concern about disturbance of denning grizzly bears (Ursus arctos) in the Greater Yellowstone Ecosystem (GYE). To help identify areas where such conflicts might occur, we developed a spatially explicit model to predict potential denning areas in the GYE. Using a scan area of 630 m around each location, we assigned site attributes to 344 den locations of radio-trackedg rizzly bears from 1975-99. Attributesi dentified as predictorsf or the analysis included elevation, slope, an index of solar radiation, and forest cover. We used the Mahalanobis distance statistic to model the similarity between sites used by denning bears and each cell in the data layers. We used the final Mahalanobis distance model to produce maps of the study area. Potential denning habitat, based upon the model, is abundantw ithin the GYE. Ourr esultsc an be used by land managementa gencies to identifyp otentialc onflict sites and minimize effects of regulated activities on denning grizzly bears. We illustrate how the Gallatin National Forest (GNF) used the model to examine the overlap between potential snowmobile use areas and potential denning habitat as part of a Biological Assessment submitted to the U.S. Fish and Wildlife Service.

Wyoming↗