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USGS2021

Adaptive monitoring in action: Reconsidering design-based estimators reveals underestimation of whitebark pine disease prevalence in the Greater Yellowstone Ecosystem

Identifying and understanding status and trends in ecological indicators motivates continual monitoring over decades. Many programs rely on probability surveys and their companion design-based estimators for status assessments (e.g. Horvitz–Thompson). Design-based estimators do not easily extend to trend estimation nor situations with observation errors. Field-based monitoring efforts inevitably have turnover of field crew members which may affect consistency and accuracy of data collection over time. Additionally, design-based estimators ignore the complexities of spatial and temporal heterogeneity in an ecological indicator and how this variability may be linked to environmental or biological dynamics. We propose monitoring programs should re-evaluate their prescribed statistical methods, consider model-based approaches and adapt their sampling designs as needed to improve inferences. The Greater Yellowstone Ecosystem, home to two of the most iconic U.S. National Parks, has experienced significant declines in whitebark pine Pinus albicaulis communities due to forest pathogens, insect outbreaks, wildland fires and drought. Whitebark pine is a keystone species found in mountainous environments throughout the Western U.S. and Canada. We assessed the design-based ratio estimator originally recommended for estimating prevalence of white pine blister rust Cronartium ribicola . We compared the design-based estimator to a model-based approach that accounts for the sampling design, imperfect detection and allows for infection probabilities to vary over space and time. Ignoring observation errors led to lower estimated prevalence of white pine blister rust in the general population. Using model-based approaches, we found that the probability of infection has increased since 2004. However, overall prevalence likely has not changed because of the mountain pine beetle Dendroctonus ponderosae -induced shift towards smaller diameter trees that have a lower probability of infection compared to their larger cohorts. Synthesis and Applications . Using a design-based approach to detect change in ecological indicators falls short because of the inability to account for observation errors or to explore environmental or biological factors explaining temporal dynamics. Inherently understanding the mechanisms leading to changes in an ecological indicator over time informs potential management actions. Our assessment underscores the need for continued evaluation and updating of a monitoring program's sampling design and analytical procedures to maintain relevancy.

Wyoming↗

USGS2010

Spatial variation in keystone effects: Small mammal diversity associated with black-tailed prairie dog colonies

Species with extensive geographic ranges may interact with different species assemblages at distant locations, with the result that the nature of the interactions may vary spatially. Black-tailed prairie dogs Cynomys ludovicianus occur from Canada to Mexico in grasslands of the western Great Plains of North America. Black-tailed prairie dogs alter vegetation and dig extensive burrow systems that alter grassland habitats for plants and other animal species. These alterations of habitat justify the descriptor " ecological engineer," and the resulting changes in species composition have earned them status as a keystone species. We examined the impact of black-tailed prairie dogs on small mammal assemblages by trapping at on- and off-colony locations at eight study areas across the species' geographic range. We posed 2 nested hypotheses: 1) prairie dogs function as a keystone species for other rodent species; and 2) the keystone role varies spatially. Assuming that it does, we asked what are the sources of the variation? Black-tailed prairie dogs consistently functioned as a keystone species in that there were strong statistically significant differences in community composition on versus off prairie dog colonies across the species range in prairie grassland. Small mammal species composition varied along both latitudinal and longitudinal gradients, and species richness varied from 4 to 11. Assemblages closer together were more similar; such correlations approximately doubled when including only on- or off-colony grids. Black-tailed prairie dogs had a significant effect on associated rodent assemblages that varied regionally, dependent upon the composition of the local rodent species pool. Over the range of the black-tailed prairie dog, on-colony rodent richness and evenness were less variable, and species composition was more consistent than off-colony assemblages. ?? 2010 The Authors.

Ecography↗

USGS2005

Simulation of ground-water flow in coastal Georgia and adjacent parts of South Carolina and Florida-predevelopment, 1980, and 2000

A digital model was developed to simulate steady-state ground-water flow in a 42,155-square-mile area of coastal Georgia and adjacent parts of South Carolina and Florida. The model was developed to (1) understand and refine the conceptual model of regional ground-water flow, (2) serve as a framework for the development of digital subregional ground-water flow and solute-transport models, and (3) serve as a tool for future evaluations of hypothetical pumping scenarios used to facilitate water management in the coastal area. Single-density ground-water flow was simulated using the U.S. Geological Survey finite-difference code MODFLOW-2000 for mean-annual conditions during predevelopment (pre?1900) and the years 1980 and 2000. The model comprises seven layers: the surficial aquifer system, the Brunswick aquifer system, the Upper Floridan aquifer, the Lower Floridan aquifer, and the intervening confining units. A combination of boundary conditions was applied, including a general-head boundary condition on the top active cells of the model and a time-variable fixed-head boundary condition along part of the southern lateral boundary. Simulated heads for 1980 and 2000 conditions indicate a good match to observed values, based on a plus-or-minus 10-foot (ft) calibration target and calibration statistics. The root-mean square of residual water levels for the Upper Floridan aquifer was 13.0 ft for the 1980 calibration and 9.94 ft for the 2000 calibration. Some spatial patterns of residuals were indicated for the 1980 and 2000 simulations, and are likely a result of model-grid cell size and insufficiently detailed hydraulic-property and pumpage data in some areas. Simulated potentiometric surfaces for predevelopment, 1980, and 2000 conditions all show major flow system features that are indicated by estimated peotentiometric maps. During 1980?2000, simulated water levels at the centers of pumping at Savannah and Brunswick rose more than 20 ft and 8 ft, respectively, in response to decreased pumping. Simulated drawdown exceeded 10 ft in the Upper Floridan aquifer across much of the western half of the model area, with drawdown exceeding 20 ft along parts of the western, northern, and southern boundaries where irrigation pumping increased during this period. From predevelopment to 2000 conditions, the simulated water budget showed an increase in inflow from, and decrease in outflow to, the general-head boundaries, and a reversal from net seaward flow to net landward flow across the coastline. Simulated changes in recharge and discharge distribution from predevelopment to 2000 conditions showed an increase in extent and magnitude of net recharge cells in the northern part of the model area, and a decrease in discharge or change to recharge in cells containing major streams and beneath major pumping centers. The model is relatively sensitive to pumping and the controlling head at the fixed-head boundary and less sensitive to the distribution of aquifer properties in general. Model limitations include: (1) its spatial scale and discretization, (2) the extent to which data are available to physically define the flow system, (3) the type of boundary conditions and controlling parameters used, (4) uncertainty in the distribution of pumping, and (5) uncertainty in field-scale hydraulic properties. The model could be improved with more accurate estimates of ground-water pumpage and better characterization of recharge and discharge.

Florida, Georgia, South Carolina↗

USGS2010

Land Disturbance Associated with Oil and Gas Development and Effects of Development-Related Land Disturbance on Dissolved-Solids Loads in Streams in the Upper Colorado River Basin, 1991, 2007, and 2025

Oil and gas resource development in the Upper Colorado River Basin (UCRB) has increased substantially since the year 2000. The UCRB encompasses several significant oil and gas producing areas that have the potential for continued oil and gas resource development. Land disturbance associated with oil and gas resource development is caused by activities related to constructing drill pads to contain drilling and well maintenance equipment and roads to access the drill pad. Land disturbed by oil and gas development has the potential to cause increased erosion, stream degradation, habitat fragmentation and alteration, and increase public use of areas that may be environmentally sensitive. Land disturbance resulting from oil and gas resource development has not been monitored and mapped on a regional scale in the UCRB. However, information on the location and age of oil and gas wells in the UCRB is available. These data combined with geographic data analysis and modeling techniques were used to estimate the total area of disturbed land associated with oil and gas resource development in 1991 and in 2007 in the UCRB. Additional information about anticipated oil and gas development in the UCRB was used to project land disturbance to the year 2025. Results of the analysis indicate that approximately 117,500 acres (183 mi2) of total land disturbance was associated with drill pads and related roads in the UCRB in 1991. The estimated area of disturbed land associated with oil and gas development increased 53 percent to 179,400 acres (280 mi2) in 2007. Projecting oil and gas development through 2025 results in a potential near doubling of the land surface disturbance to approximately 319,300 acres (500 mi2). Estimated land disturbance for 1991 and 2007 were input to a contaminant transport model developed for the UCRB to assess the statistical significance of energy-related land disturbance to contributing dissolved solids to basin streams. The statistical assessment was an observational study based on an existing model and available water-quality monitoring data for the basin. No new data were collected for the analysis. The source coefficient calibrated for the disturbed lands associated with oil and gas development in 2007 was zero, which indicated that estimated land disturbance from oil and gas development is not statistically significant in explaining dissolved solids in UCRB streams. The lack of significance in the contaminant transport modeling framework may be due to the amount of available monitoring data, the spatial distribution of monitoring sites with respect to land disturbance, or the overall quantity of land disturbance associated with oil and gas development basin wide. Finally, dissolved-solids loads derived from natural landscapes may be similar to loads derived from lands disturbed by oil and gas resource development. The model recalibration done for this study confirms calibration results from Kenney and others (2009): the most significant contributor to dissolved solids in the UCRB is irrigated agricultural land, which covers an area substantially larger than the estimated area disturbed by oil and gas development and is subjected to artificially applied water.

Scientific Investigations Report↗

USGS2013

Investigation of the structure and lithology of bedrock concealed by basin fill, using ground-based magnetic-field-profile data acquired in the San Rafael Basin, southeastern Arizona

Data on the Earth’s total-intensity magnetic field acquired near ground level and at measurement intervals as small as 1 m include information on the spatial distribution of nearsurface magnetic dipoles that in many cases are unique to a specific lithology. Such spatial information is expressed in the texture (physical appearance or characteristics) of the data at scales of hundreds of meters to kilometers. These magnetic textures are characterized by several descriptive statistics, their power spectrum, and their multifractal spectrum. On the basis of a graphical comparison and textural characterization, ground-based magnetic-field profile data can be used to estimate bedrock lithology concealed by as much as 100 m of basin fill in some cases, information that is especially important in assessing and exploring for concealed mineral deposits. I demonstrate that multifractal spectra of ground-based magnetic-field-profile data can be used to differentiate exposed lithologies and that the shape and position of the multifractal spectrum of the ground-based magnetic-field-profile of concealed lithologies can be matched to the upward-continued multifractal spectrum of an exposed lithology to help distinguish the concealed lithology. In addition, ground-based magnetic-field-profile data also detect minute differences in the magnetic susceptibility of rocks over small horizontal and vertical distances and so can be used for precise modeling of bedrock geometry and structure, even when that bedrock is concealed by 100 m or more of nonmagnetic basin fill. Such data contain valuable geologic information on the bedrock concealed by basin fill that may not be so visible in aeromagnetic data, including areas of hydrothermal alteration, faults, and other bedrock structures. Interpretation of these data in the San Rafael Basin, southeastern Arizona, has yielded results for estimating concealed lithologies, concealed structural geology, and a concealed potential mineral-resource target.

Arizona↗

USGS2013

Influence of estuarine processes on spatiotemporal variation in bioavailable selenium

Dynamic processes (physical, chemical and biological) challenge our ability to quantify and manage the ecological risk of chemical contaminants in estuarine environments. Selenium (Se) bioavailability (defined by bioaccumulation), stable isotopes and molar carbon-tonitrogen ratios in the benthic clam Potamocorbula amurensis, an important food source for predators, were determined monthly for 17 yr in northern San Francisco Bay. Se concentrations in the clams ranged from a low of 2 to a high of 22 μg g -1 over space and time. Little of that variability was stochastic, however. Statistical analyses and preliminary hydrodynamic modeling showed that a constant mid-estuarine input of Se, which was dispersed up- and down-estuary by tidal currents, explained the general spatial patterns in accumulated Se among stations. Regression of Se bioavailability against river inflows suggested that processes driven by inflows were the primary driver of seasonal variability. River inflow also appeared to explain interannual variability but within the range of Se enrichment established at each station by source inputs. Evaluation of risks from Se contamination in estuaries requires the consideration of spatial and temporal variability on multiple scales and of the processes that drive that variability.

Marine Ecology Progress Series↗

USGS2021

Integrating thermal infrared stream temperature imagery and spatial stream network models to understand natural spatial thermal variability in streams

Under a warmer future climate, thermal refuges could facilitate the persistence of species relying on cold-water habitat. Often these refuges are small and easily missed or smoothed out by averaging in models. Thermal infrared (TIR) imagery can provide empirical water surface temperatures that capture these features at a high spatial resolution (<1 m) and over tens of kilometers. Our study examined how TIR data could be used along with spatial stream network (SSN) models to characterize thermal regimes spatially in the Middle Fork John Day (MFJD) River mainstem (Oregon, USA). We characterized thermal variation in seven TIR longitudinal temperature profiles along the MFJD mainstem and compared them with SSN model predictions of stream temperature (for the same time periods as the TIR profiles). TIR profiles identified reaches of the MFJD mainstem with consistently cooler temperatures across years that were not consistently captured by the SSN prediction models. SSN predictions along the mainstem identified ~80% of the 1-km reach scale temperature warming or cooling trends observed in the TIR profiles. We assessed whether landscape features (e.g., tributary junctions, valley confinement, geomorphic reach classifications) could explain the fine-scale thermal heterogeneity in the TIR profiles (after accounting for the reach-scale temperature variability predicted by the SSN model) by fitting SSN models using the TIR profile observation points. Only the distance to the nearest upstream tributary was identified as a statistically significant landscape feature for explaining some of the thermal variability in the TIR profile data. When combined, TIR data and SSN models provide a data-rich evaluation of stream temperature captured in TIR imagery and a spatially extensive prediction of the network thermal diversity from the outlet to the headwaters.

Oregon↗

USGS2003

Ground-water-quality assessment of shallow aquifers in the Front Range Urban Corridor, Colorado, 1954-98

Historical (1954-98) water-quality data for major ions, trace elements, major plant nutrients, and organic constituents collected in 3,870 sampling events at 2,138 shallow wells represent ground-water quality in shallow aquifers that underlie the Front Range Urban Corridor in Colorado. Nonparametric summary statistics and maps of concentrations across the study area indicate that ground water in the study area included fresh to saline water. Sulfate concentrations were elevated in the north and northeast parts of the study area, possibly due to Pierre Shale and Laramie Formation shale outcrops in those areas. Apart from isolated areas of known contamination, chloride concentrations were generally less than 100 milligrams per liter across the study area. Wells with elevated nitrate concentrations usually were located near rivers and streams downgradient from metropolitan areas. Elevated nitrate concentrations in wells that were not along the South Platte River were possibly from individual sewage disposal system usage or from fertilizer application to land. Spatial distribution for organic compounds for which more than 40 percent of the data were above the detection limit (atrazine, methyl-tert-butylether, and prometon) is not widespread across the study area, but this may reflect limitations of data availability. Summary statistics calculated or estimated by decade are influenced by the temporal variability of data across the study area. The median values of specific conductance, chloride, and nitrate from the 1970?s are less than values from the 1980?s and 1990?s, which, because most samples from the l970?s were collected in the western part of the study area, indicates that water quality in the western part of the study area is generally different than the rest of the study area. Chloride may be introduced to ground water from runoff of road deicers or chlorinated organics in transportation/transitional areas, where the median concentration is the greatest (85.0 milligrams per liter). Nitrate median concentrations are several times greater where the land is cultivated or used for agricultural business, which may reflect use of nitrogen fertilizers and the presence of animal feeding operations. Most inorganic and organic constituents exceeded drinking-water standards in only a small percentage of samples. Exceptions to this include sulfate; nitrate; trace elements aluminum, cadmium, iron, and manganese; and organic compounds 1,1-dichloroethylene, tetrachloroethylene, trichloroethylene, benzene, and dichloromethane.

Water-Resources Investigations Report↗

USGS2005

Statistical characterization of a large geochemical database and effect of sample size

The authors investigated statistical distributions for concentrations of chemical elements from the National Geochemical Survey (NGS) database of the U.S. Geological Survey. At the time of this study, the NGS data set encompasses 48,544 stream sediment and soil samples from the conterminous United States analyzed by ICP-AES following a 4-acid near-total digestion. This report includes 27 elements: Al, Ca, Fe, K, Mg, Na, P, Ti, Ba, Ce, Co, Cr, Cu, Ga, La, Li, Mn, Nb, Nd, Ni, Pb, Sc, Sr, Th, V, Y and Zn. The goal and challenge for the statistical overview was to delineate chemical distributions in a complex, heterogeneous data set spanning a large geographic range (the conterminous United States), and many different geological provinces and rock types. After declustering to create a uniform spatial sample distribution with 16,511 samples, histograms and quantile-quantile (Q-Q) plots were employed to delineate subpopulations that have coherent chemical and mineral affinities. Probability groupings are discerned by changes in slope (kinks) on the plots. Major rock-forming elements, e.g., Al, Ca, K and Na, tend to display linear segments on normal Q-Q plots. These segments can commonly be linked to petrologic or mineralogical associations. For example, linear segments on K and Na plots reflect dilution of clay minerals by quartz sand (low in K and Na). Minor and trace element relationships are best displayed on lognormal Q-Q plots. These sensitively reflect discrete relationships in subpopulations within the wide range of the data. For example, small but distinctly log-linear subpopulations for Pb, Cu, Zn and Ag are interpreted to represent ore-grade enrichment of naturally occurring minerals such as sulfides. None of the 27 chemical elements could pass the test for either normal or lognormal distribution on the declustered data set. Part of the reasons relate to the presence of mixtures of subpopulations and outliers. Random samples of the data set with successively smaller numbers of data points showed that few elements passed standard statistical tests for normality or log-normality until sample size decreased to a few hundred data points. Large sample size enhances the power of statistical tests, and leads to rejection of most statistical hypotheses for real data sets. For large sample sizes (e.g., n > 1000), graphical methods such as histogram, stem-and-leaf, and probability plots are recommended for rough judgement of probability distribution if needed. ?? 2005 Elsevier Ltd. All rights reserved.

Applied Geochemistry↗

USGS2019

An integrative GIS approach to analyzing the impacts of septic systems on the coast of Florida, USA

An estimated 2.7 million septic systems in Florida, USA are potential ground and surface water contaminant sources that may affect environmental and human health. This study examined the spatial distribution of septic systems, coastal surface water contamination, and related environmental factors of coastal Florida watersheds at the 8-digit hydrologic unit code level. Hydrology, in situ sampling data, and other ancillary data were combined in a geographic information system to examine spatial relationships. Spatial distribution data were correlated to nitrogen, Enterococci counts, and beach closures tabulated since 2000, 2007, and 2012. Significant positive correlations (α = 0.05) with nitrogen and Enterococci counts were consistent for percent agricultural cover, percent combined urban and agricultural cover, septic tank density, population density, and septic tank density in poorly drained soils. Beach closures since 2012 were significantly positively correlated (α = 0.05) to average impervious cover (IC) and percent urbanization. Statistics indicated that Enterococci counts, nitrogen, and beach closures may be related to specific environmental factors and septic tank densities. The combination of septic tanks in urban regions with high IC prone to elevated runoff could also be a factor in surface water contamination. Data availability was also highlighted as a limitation due to infrequent spatial and temporal sampling.

Florida↗

USGS2021

Mapping biological soil crusts in a Hawaiian dryland

Historical and ongoing land use patterns in the Hawaiian Islands have degraded the Islands’ drylands, causing erosion and detrimentally affecting adjacent coastal marine ecosystems. Biological soil crust (biocrust) communities have been shown to increase soil stability in drylands worldwide, but their efficacy in mitigating soil erosion in Hawaiian drylands is largely unknown. Using a combination of field data and imagery collected by small unmanned aerial systems (sUAS), we mapped biocrusts and examined their influence on soil stability in the Kawaihae watershed, an erosion-prone dryland on leeward Hawai`i Island. We created classified maps of biocrust cover from imagery collected at three spatial resolutions (1.2, 2.1 and 2.8 cm/pixel) using the pixel-based Support Vector Machine (SVM) classifier and investigated the impacts of spatial resolution and biocrust level of development on classification accuracy. Our medium (2.1 cm) resolution image produced the highest overall classification accuracy when biocrust was treated as a single class (82.1%). We explored the spatial impacts of biocrusts on soil loss via sUAS-derived measurements of elevation change over a four-year time span. We found differences in soil loss among land cover types, but robustly quantifying these was a challenge, as much of the change fell below statistically significant limits of detection. We investigated the relationship between biocrust development and soil stability by conducting soil aggregate stability testing at the three biocrust levels of development (LODs) present at the study site. We found a significant increase in soil stability from soils without surface biocrusts (LOD score of 0) to those with biocrusts at any development level (LOD 1–3). Our research adds to the body of biocrust knowledge by presenting new information about biocrust distribution and soil stabilization capabilities in Hawaiian drylands. We also provide insights into the trade-offs between spatial resolution and classification accuracy for biocrust classification and land cover analysis.

Hawaii↗

USGS2020

Fishing for food: Quantifying recreational fisheries harvest in Wisconsin lakes

Recreational fisheries have high economic worth, valued at US$190 billion globally. An important, but underappreciated, secondary value of recreational catch is its role as a source of food. This contribution is poorly understood due to difficulty in estimating recreational harvest at spatial scales beyond a single system, as traditionally estimated from individual creel surveys. Here, we address this gap using 28‐year creel surveys of ~300 Wisconsin inland lakes. We develop a statistical model of recreational harvest for individual lakes and then scale‐up to unsurveyed lakes (3,769 lakes; 73% of statewide lake surface area). We generate a statewide estimate of recreational lake harvest of ~4,200 metric tons and an estimated annual angler consumption rate of ~1.1 kg, nearly equal to the total estimated United States per capita freshwater fish consumption. An important ecosystem service, recreational harvest makes significant contributions to human diets and plays an often‐unheralded role in food security.

Wisconsin↗

USGS2002

The National Vegetation Classification Standard applied to the remote sensing classification of two semiarid environments

The National Vegetation Classification Standard (NVCS) was implemented at two US National Park Service (NPS) sites in Texas, the Padre Island National Seashore (PINS) and the Lake Meredith National Recreation Area (LM-NRA), to provide information for NPS oil and gas management plans. Because NVCS landcover classifications did not exist for these two areas prior to this study, we created landcover classes, through intensive ground and aerial reconnaissance, that characterized the general landscape features and at the same time complied with NVCS guidelines. The created landcover classes were useful for the resource management and were conducive to classification with optical remote sensing systems, such as the Landsat Thematic Mapper (TM). In the LMNRA, topographic elevation data were added to the TM data to reduce confusion between cliff, high plains, and forest classes. Classification accuracies (kappa statistics) of 89.9% (0.89) and 88.2% (0.87) in PINS and LMNRA, respectively, verified that the two NPS landholdings were adequately mapped with TM data. Improved sensor systems with higher spectral and spatial resolutions will ultimately refine the broad classes defined in this classification; however, the landcover classifications created in this study have already provided valuable information for the management of both NPS lands. Habitat information provided by the classifications has aided in the placement of inventory and monitoring plots, has assisted oil and gas operators by providing information on sensitive habitats, and has allowed park managers to better use resources when fighting wildland fires and in protecting visitors and the infrastructure of NPS lands.

Environmental Management↗

USGS2010

Ecological hierarchies and self-organisation - Pattern analysis, modelling and process integration across scales

A continuing discussion in applied and theoretical ecology focuses on the relationship of different organisational levels and on how ecological systems interact across scales. We address principal approaches to cope with complex across-level issues in ecology by applying elements of hierarchy theory and the theory of complex adaptive systems. A top-down approach, often characterised by the use of statistical techniques, can be applied to analyse large-scale dynamics and identify constraints exerted on lower levels. Current developments are illustrated with examples from the analysis of within-community spatial patterns and large-scale vegetation patterns. A bottom-up approach allows one to elucidate how interactions of individuals shape dynamics at higher levels in a self-organisation process; e.g., population development and community composition. This may be facilitated by various modelling tools, which provide the distinction between focal levels and resulting properties. For instance, resilience in grassland communities has been analysed with a cellular automaton approach, and the driving forces in rodent population oscillations have been identified with an agent-based model. Both modelling tools illustrate the principles of analysing higher level processes by representing the interactions of basic components.The focus of most ecological investigations on either top-down or bottom-up approaches may not be appropriate, if strong cross-scale relationships predominate. Here, we propose an 'across-scale-approach', closely interweaving the inherent potentials of both approaches. This combination of analytical and synthesising approaches will enable ecologists to establish a more coherent access to cross-level interactions in ecological systems. ?? 2010 Gesellschaft f??r ??kologie.

Basic and Applied Ecology↗

USGS2007

Consistency of L4 TM absolute calibration with respect to the L5 TM sensor based on near-simultaneous image acquisition

The Landsat archive provides more than 35 years of uninterrupted multispectral remotely sensed data of Earth observations. Since 1972, Landsat missions have carried different types of sensors, from the Return Beam Vidicon (RBV) camera to the Enhanced Thematic Mapper Plus (ETM+). However, the Thematic Mapper (TM) sensors on Landsat 4 (L4) and Landsat 5 (L5), launched in 1982 and 1984 respectively, are the backbone of an extensive archive. Effective April 2, 2007, the radiometric calibration of L5 TM data processed and distributed by the U.S. Geological Survey (USGS) Center for Earth Resources Observation and Science (EROS) was updated to use an improved lifetime gain model, based on the instrument's detector response to pseudo-invariant desert site data and cross-calibration with the L7 ETM+. However, no modifications were ever made to the radiometric calibration procedure of the Landsat 4 (L4) TM data. The L4 TM radiometric calibration procedure has continued to use the Internal Calibrator (IC) based calibration algorithms and the post calibration dynamic ranges, as previously defined. To evaluate the "current" absolute accuracy of these two sensors, image pairs from the L5 TM and L4 TM sensors were compared. The number of coincident image pairs in the USGS EROS archive is limited, so the scene selection for the cross-calibration studies proved to be a challenge. Additionally, because of the lack of near-simultaneous images available over well-characterized and traditionally used calibration sites, alternate sites that have high reflectance, large dynamic range, high spatial uniformity, high sun elevation, and minimal cloud cover were investigated. The alternate sites were identified in Yuma, Iraq, Egypt, Libya, and Algeria. The cross-calibration approach involved comparing image statistics derived from large common areas observed eight days apart by the two sensors. This paper summarizes the average percent differences in reflectance estimates obtained between the two sensors. The work presented in this paper is a first step in understanding the current performance of L4 TM absolute calibration and potentially serves as a platform to revise and improve the radiometric calibration procedures implemented for the processing of L4 TM data.

Conference Paper↗

USGS2019

State-space analysis of power to detect regional brook trout population trends over time

Threats to aquatic biodiversity are expressed at broad spatial scales, but identifying regional trends in abundance is challenging owing to variable sampling designs, and temporal and spatial variation in abundance. We compiled a regional dataset of brook trout Salvelinus fontinalis counts across their southern range representing 326 sites from eight states between 1982-2014, and conducted a statistical power analysis using Bayesian state-space models to evaluate the ability to detect temporal trends by characterizing posterior distributions with three approaches. A combination of monitoring periods, number of sites and electrofishing passes, decline magnitude and different revisit patterns were tested. Power increased with monitoring periods and decline magnitude. Trends in adults were better detected than young-of-the-year fish, which showed greater inter-annual variation in abundance. The addition of weather covariates to account for the temporal variation increased power only slightly. Single- and three-pass electrofishing methods were similar in power. Finally, power was higher for sampling designs with more frequent revisits over the duration of the monitoring program. Our results provide guidance for broad-scale monitoring designs for temporal trend detection.

Canadian Journal of Fisheries and Aquatic Sciences↗

USGS2023

A population-based performance evaluation of the ShakeAlert earthquake early warning system for M 9 megathrust earthquakes in the Pacific Northwest, U.S.A.

We evaluate the potential performance of the ShakeAlert earthquake early warning system for M 9 megathrust earthquakes in the Pacific Northwest (PNW) using synthetic seismograms from 30 simulated M 9 earthquake scenarios on the Cascadia subduction zone. The timeliness and accuracy of source estimates and effectiveness of ShakeAlert alert contours are evaluated with a station‐based alert classification scheme using an alert threshold equal to the target threshold. We develop a population‐based alert classification method by aligning a population grid with Voronoi diagrams computed from the station locations for each scenario. Using raster statistics, we estimate the PNW population that would receive timely accurate alerts during an offshore M 9 earthquake. We also examine the range of expected warning times with respect to the spatial distribution of the population. Results show that most of the population in our evaluation region could receive alerts with positive warning times for an alert threshold of modified Mercalli intensity (MMI) III, but that late and missed alerts increase because the alert threshold is increased. An average of just under 60% of the population would be alerted for MMI V prior to the arrival of threshold level shaking. Large regions of late and missed alerts for thresholds MMI IV and V are caused by delays in alert updates, inaccurate FinDer source estimates, and undersized alert contours due to magnitude underestimation. We also investigate an alerting strategy where ShakeAlert sends out an alert to the entire evaluation region when the system detects at least an M 8 earthquake along the coast. Because large magnitude offshore earthquakes are rare in Cascadia, overalerting is most likely to occur from an overestimated M 7+ on the Gorda plate. With appropriate criteria to minimize overalerting, this strategy may eliminate all missed and late alerts except at sites close to the epicenter.

California, Oregon, Washington↗

USGS2023

Trends in environmental, anthropogenic, and water-quality characteristics in the upper White River Basin, Indiana

The U.S. Geological Survey (USGS), in cooperation with The Nature Conservancy, undertook a study to update and extend results from a previous study (Koltun, 2019, https://doi.org/10.3133/sir20195119 ), using data from 3 additional years and newer estimation methods. Koltun (2019) assessed trends in streamflow, precipitation, and estimated annual mean concentrations and flux of nitrate plus nitrite, total Kjeldahl nitrogen, total phosphorus, and total suspended solids (TSS) for USGS streamflow gages on the upper White River at Muncie, near Nora, and near Centerton, Indiana. Annual mean and maximum daily streamflows had statistically significant upward trends at all study gages between water years 1978 and 2020. An abrupt increase in streamflow occurred around water year 2001. Annual total precipitation at the Indianapolis International Airport increased between calendar years 1932 and 2020 at an average rate of 0.089 inches per year. The current study assessed the magnitude, direction, and likelihood of change in flow-normalized concentrations and flux of TSS, total phosphorus, nitrate plus nitrite, and total Kjeldahl nitrogen between water years 1997 and 2019. With two exceptions, concentration and flux changes that were statistically significant in Koltun (2019, https://doi.org/10.3133/sir20195119 ), which reported changes between water years 1997 and 2017, still have the same statistically significant change directions. The reliability of the current trend result for TSS is uncertain because of a large gap in the TSS record for the Centerton gage. For each constituent, spatial patterns were examined in the sampled distribution of nutrient and TSS concentration data from 20 mainstem, tributary, and distributary locations in the upper White River Basin. The largest median concentrations of TSS, total phosphorus, and total Kjeldahl nitrogen were associated with mainstem upper White River sites downstream from Indianapolis. The median total phosphorus and total Kjeldahl nitrogen concentrations were elevated relative to bracketing upstream/downstream mainstem sites at the upper White River site immediately downstream from Muncie. Data on several anthropogenic factors that could influence the concentrations and fluxes of nutrients and TSS were gathered and analyzed to better understand the factors’ spatial and temporal variations. Those anthropogenic factors included population, land cover, cropping and operational tillage practices, fertilizer application, and upgrades to wastewater treatment systems and delivery processes.

Indiana↗