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USGS2019

The effect of stress changes on time-dependent earthquake probabilities for the central Wasatch Fault Zone, Utah, USA

Static and quasi-static Coulomb stress changes produced by large earthquakes can modify the probability of occurrence of subsequent events on neighboring faults. This approach is based on physical (Coulomb stress changes) and statistical (probability calculations) models, which are influenced by the quality and quantity of data available in the study region. Here, we focus on the Wasatch Fault Zone (WFZ), a well-studied active normal fault system having abundant geologic and paleoseismological data. Paleoseismological trench investigations of the WFZ indicate that at least 24 large, surface-faulting earthquakes have ruptured the fault’s five central, 35–59-km long segments since ~7 ka. Our goal is to determine if the stress changes due to the youngest paleoevents have significantly modified the present-day probability of occurrence of large earthquakes on each of the segments. For each segment, we modeled the cumulative (coseismic + postseismic) Coulomb stress changes (∆CFScum) due to earthquakes younger than the most recent event on the segment in question and applied the resulting values to the time-dependent probability calculations. Results from the Coulomb stress modeling suggest that the Brigham City, Salt Lake City, and Provo segments have accumulated ∆CFScum larger than 10 bars, whereas the Weber segment has experienced a stress decrease of 5 bars, in the scenario of recent rupture of the Great Salt Lake fault to the west. Probability calculations predict high probability of occurrence for the Brigham City and Salt Lake City segments, due to their long elapsed times (>1-2 ka) when compared to the Weber, Provo, and Nephi segments (< 1 ka). The range of calculated coefficients of variation (CV) has a large influence on the final probabilities, mostly in the case of the Brigham City segment. Finally, when the Coulomb stress and the probability models are combined, our results indicate that the ∆CFScum resulting from earthquakes postdating the youngest events on each of the five segments significantly affects the probability calculations for three of the segments: Brigham City, Salt Lake City, and Provo. The probability of occurrence of a large earthquake in the next 50 years on these three segments may therefore be underestimated if a time-independent approach, or a time-dependent approach that does not consider ∆CFS, is adopted.

Utah↗

USGS2025

Spatially explicit power analyses to inform occupancy‐based multi‐species wildlife monitoring programmes

1. Current and accurate information on wildlife populations is integral to successful biodiversity management and conservation globally. Nevertheless, many monitoring programs fail in their attempts to accurately monitor populations of interest due to interlinked issues including insufficient sample sizes, inappropriate duration, lack of reproducibility, and lack of clearly stated objectives. These common pitfalls could be avoided through the elicitation of explicit monitoring objectives and the a priori use of simulations to inform minimum sampling design requirements to meet said objectives. 2. Here, we provide a blueprint for using spatially explicit power analyses to inform the design and implementation of multi-species monitoring programs on landscape-scales. As a demonstration, we used spatially explicit simulations to devise a suitable sampling regime to meet clearly specified monitoring objectives in New York State: to use annual occupancy-based monitoring to be able to detect 25% and 50% changes in abundance of populations over five- and ten- year periods for all species of management interest in New York State, USA. We focused our simulation efforts on three challenging focal species (black bear, Ursus americanus, bobcat, Lynx rufus, and American marten, Martes americana) that differ notably in their morphology, life histories, space use, detection probability, habitat suitability, and population sizes/trajectories, and thus provide extremes in the challenges presented when it comes to sampling appropriately to detect changes in abundance. 3. Our simulations demonstrate variable context dependent trade-offs in sampling designs (i.e. number of sites [J] and number of sampling occasions [K]), and identify necessary minimum detection probabilities that must be attained to achieve statistical power to detect changes of varying magnitudes in populations of varying sizes in the three focal species. The simulations also highlight that monitoring population increases is likely beyond the reach of occupancy-based monitoring programs for wide-ranging or locally abundant species. 4. Synthesis and applications : We combine the results from the single-species simulations to produce a multi-species sampling design that meets the specified objectives for all three species. While the case study is centered on developing a multi-species sampling regime for New York State, it provides a reproducible step-by-step framework using established methods for wildlife managers and other practitioners to inform their own context- and objective- specific multi-species occupancy-based monitoring programs.

New York↗

USGS2011

Exploring sensitivity of a multistate occupancy model to inform management decisions

1. Dynamic occupancy models are often used to investigate questions regarding the processes that influence patch occupancy and are prominent in the fields of population and community ecology and conservation biology. Recently, multistate occupancy models have been developed to investigate dynamic systems involving more than one occupied state, including reproductive states, relative abundance states and joint habitat‐occupancy states. Here we investigate the sensitivities of the equilibrium‐state distribution of multistate occupancy models to changes in transition rates. 2. We develop equilibrium occupancy expressions and their associated sensitivity metrics for dynamic multistate occupancy models. To illustrate our approach, we use two examples that represent common multistate occupancy systems. The first example involves a three‐state dynamic model involving occupied states with and without successful reproduction (California spotted owl Strix occidentalis occidentalis ), and the second involves a novel way of using a multistate occupancy approach to accommodate second‐order Markov processes (wood frog Lithobates sylvatica breeding and metamorphosis). 3. In many ways, multistate sensitivity metrics behave in similar ways as standard occupancy sensitivities. When equilibrium occupancy rates are low, sensitivity to parameters related to colonisation is high, while sensitivity to persistence parameters is greater when equilibrium occupancy rates are high. Sensitivities can also provide guidance for managers when estimates of transition probabilities are not available. 4. Synthesis and applications. Multistate models provide practitioners a flexible framework to define multiple, distinct occupied states and the ability to choose which state, or combination of states, is most relevant to questions and decisions about their own systems. In addition to standard multistate occupancy models, we provide an example of how a second‐order Markov process can be modified to fit a multistate framework. Assuming the system is near equilibrium, our sensitivity analyses illustrate how to investigate the sensitivity of the system‐specific equilibrium state(s) to changes in transition rates. Because management will typically act on these transition rates, sensitivity analyses can provide valuable information about the potential influence of different actions and when it may be prudent to shift the focus of management among the various transition rates.

Journal of Applied Ecology↗

USGS2009

A spatial model to assess the effects of hydropower operations on Columbia River fall Chinook Salmon spawning habitat

Priest Rapids Dam on the Columbia River produces large daily and hourly streamflow fluctuations throughout the Hanford Reach during the period when fall Chinook salmon Oncorhynchus tshawytscha are selecting spawning habitat, constructing redds, and actively engaged in spawning. Concern over the detrimental effects of these fluctuations prompted us to quantify the effects of variable flows on the amount and persistence of fall Chinook salmon spawning habitat in the Hanford Reach. Specifically, our goal was to develop a management tool capable of quantifying the effects of current and alternative hydrographs on predicted spawning habitat in a spatially explicit manner. Toward this goal, we modeled the water velocities and depths that fall Chinook salmon experienced during the 2004 spawning season, plus what they would probably have experienced under several alternative (i.e., synthetic) hydrographs, using both one- and two-dimensional hydrodynamic models. To estimate spawning habitat under existing or alternative hydrographs, we used cell-based modeling and logistic regression to construct and compare numerous spatial habitat models. We found that fall Chinook salmon were more likely to spawn at locations where velocities were persistently greater than 1 m/s and in areas where fluctuating water velocities were reduced. Simulations of alternative dam operations indicate that the quantity of spawning habitat is expected to increase as streamflow fluctuations are reduced during the spawning season. The spatial habitat models that we developed provide management agencies with a quantitative tool for predicting, in a spatially explicit manner, the effects of different flow regimes on fall Chinook salmon spawning habitat in the Hanford Reach. In addition to characterizing temporally varying habitat conditions, our research describes an analytical approach that could be applied in other highly variable aquatic systems.

North American Journal of Fisheries Management↗

USGS2021

Eagle fatalities are reduced by automated curtailment of wind turbines

Collision‐caused fatalities of animals at wind power facilities create a ‘green versus green’ conflict between wildlife conservation and renewable energy. These fatalities can be mitigated via informed curtailment whereby turbines are slowed or stopped when wildlife are considered at increased risk of collision. Automated monitoring systems could improve efficacy of informed curtailment, yet such technology is undertested. We test the efficacy of an automated curtailment system—a camera system that detects flying objects, classifies them and decides whether to curtail individual turbines to avoid potential collision—in reducing counts of fatalities of eagles, at Top of the World Windpower Facility (hereafter, the treatment site) in Wyoming, USA. We perform a before–after–control–impact study, comparing the number of eagle fatalities observed at the treatment site with those at a nearby (15 km) control site without automated curtailment, both before and after the implementation of automated curtailment at the treatment site. After correcting for carcass detection probability and scaling fatality estimates to turbine‐years, we estimate that the number of fatalities at the treatment site declined by 63% (95% CI = 59%–66%) between before and after periods while increasing at the control site by 113% (51%–218%). In total, there was an 82% (75%–89%) reduction in the fatality rate at the treatment site relative to the control site. Synthesis and applications . Automated curtailment of wind turbine operation substantially reduced eagle fatalities. This technology therefore has the potential to lessen the conflict between wind energy and raptor conservation. Although automated curtailment reduced fatalities, they were not fully eliminated. Therefore, automated curtailment, as implemented here, is not a panacea and its efficacy could be improved if considered in conjunction with other mitigation actions.

Wyoming↗

USGS2006

A robust design mark-resight abundance estimator allowing heterogeneity in resighting probabilities

This article introduces the beta-binomial estimator (BBE), a closed-population abundance mark-resight model combining the favorable qualities of maximum likelihood theory and the allowance of individual heterogeneity in sighting probability (p). The model may be parameterized for a robust sampling design consisting of multiple primary sampling occasions where closure need not be met between primary occasions. We applied the model to brown bear data from three study areas in Alaska and compared its performance to the joint hypergeometric estimator (JHE) and Bowden's estimator (BOWE). BBE estimates suggest heterogeneity levels were non-negligible and discourage the use of JHE for these data. Compared to JHE and BOWE, confidence intervals were considerably shorter for the AICc model-averaged BBE. To evaluate the properties of BBE relative to JHE and BOWE when sample sizes are small, simulations were performed with data from three primary occasions generated under both individual heterogeneity and temporal variation in p. All models remained consistent regardless of levels of variation in p. In terms of precision, the AICc model-averaged BBE showed advantages over JHE and BOWE when heterogeneity was present and mean sighting probabilities were similar between primary occasions. Based on the conditions examined, BBE is a reliable alternative to JHE or BOWE and provides a framework for further advances in mark-resight abundance estimation. ?? 2006 American Statistical Association and the International Biometric Society.

Journal of Agricultural, Biological, and Environme↗

USGS1997

Excavation of red squirrel middens by grizzly bears in the whitebark pine zone

Whitebark pine seeds Pinus albicaulis are an important food of grizzly Ursus arctos horribilis bears wherever whitebark pine is abundant in the contiguous United States of America; availability of seeds affects the distribution of bears, and the level of conflict between bears and humans. Almost all of the seeds consumed by bears are excavated from middens where red squirrels Tamiasciurus hudsonicus have cached whitebark pine cones. Relationships among the occupancy of middens by squirrels, the excavation of middens by bears, and site features were investigated in this study. Data were collected from radio-marked bears and from middens located from line transects on two study sites in the Yellowstone ecosystem. Densities of active middens were positively related to lodgepole pine Pinus contorta basal area and negatively related to steepness of slope. The probability that a midden was occupied by a squirrel (i.e. active) was positively related to lodgepole pine basal area in the surrounding stand, size of the midden and size of the whitebark pine cone crop, and negatively related to elevation and to bear excavation during the previous 2-12 months. The probability that a midden had been excavated by a bear during the previous 12 months was positively related to size of the midden, and to whitebark pine basal area and cone crop, and negatively related to nearness of roads and town sites. The influence of midden size on bear use was attributable to a positive relationship with the number of excavated cones. The positive association between bear excavations and whitebark pine basal area or cone crops was attributable to availability of pine seeds. Grizzly bears would benefit from the minimization of roads and other human facilities in the whitebark pine zone and from increases in the availability of whitebark pine seeds, potentially achieved by increasing the numbers of cone-producing whitebark pine trees, especially in lower elevations of the whitebark pine zone where red squirrels are more abundant.

Journal of Applied Ecology↗

USGS2018

Estimating fluvial discharges coincident with 21st century coastal storms modeled with CoSMoS

On the open coast, flooding is largely driven by tides, storm surge, waves, and in areas near coastal inlets, the magnitude and co-occurrence of high fluvial discharges. Statistical methods are typically used to estimate the individual probability of coastal storm and fluvial discharge occurrences for use in sophisticated flood hazard models. A challenge arises when considering possible future climate changes and the relation between the intensity of extreme coastal water levels and high fluvial discharges. In this study, the Coastal Storm Modeling System (CoSMoS) is used to dynamically downscale global climate projections to local-scale storm-driven coastal water levels, including associated fluvial discharges. An efficient approach to derive 21st century projected fluvial discharges for rivers within San Francisco Bay was developed, leveraging a readily-available time-series of projected (2010 – 2100) discharge rates of the predominant river system (the “Delta”). Delta projections were used to estimate flow rates of 8 Bay rivers for the IPCC's CMIP5 RCP4.5 climate scenario. Relationships describing discharge rates, normalized by respective watershed areas, were developed and applied to projected data to generate 21st century fluvial discharge time-series for each river. Results indicate decreasing discharge rates throughout the 21 st century with the exception of extreme flows.

California↗

USGS2018

Managing individual nests promotes population recovery of a top predator

Threatened species are managed using diverse conservation tactics implemented at multiple scales ranging from protecting individuals, to populations, to entire species. Individual protection strives to promote recovery at the population‐ or species‐level, although this is seldom evaluated. After decades of widespread declines, bald eagles, Haliaeetus leucocephalus , are recovering throughout their range due to legal protection and pesticide bans. However, like other raptors, their recovery remains threatened by human activities. Bald eagle nests are commonly managed using buffer zones to minimize human disturbance, but the benefits of this practice remain unquantified. Within Voyageurs National Park (VNP), Minnesota, USA, managers have monitored bald eagle populations for over 40 years, and since 1991, have protected at‐risk nests from human disturbance using buffer zones (200 and 400 m radius). We aimed to (1) quantify the recovery of bald eagles in VNP (1973–2016), and (2) provide a first‐ever evaluation of the individual‐ and population‐level effects of managing individual nests. To do so, we developed Bayesian Integrated Population Models combining observations of nest occupancy and reproductive output (metrics commonly collected for raptors) to estimate nest‐level probabilities of occupancy, nest success, and high productivity (producing ≥2 nestlings), as well as population‐level estimates of abundance and growth. The breeding population of bald eagles at VNP increased steadily from <10 pairs in the late 1970s to 48 pairs by 2016. At the nest‐level, management significantly improved occupancy and success. At the population‐level, management led to 8% and 13% increases in nest success and productivity rates, respectively, resulting in a 37% increase in breeding pair abundance. Synthesis and applications . There is a clear need to evaluate how management approaches at multiple scales assist in species recovery. Our study uses an Integrated Population Model to reveal the population‐level benefits of a widely used, individual‐based management action (protecting nests using buffer zones) on a recovering raptor.

Minnesota↗

USGS2024

Perceived constraints to participating in wildlife-related recreation

Wildlife-related recreationists play an important role in conservation. Understanding constraints to wildlife-related activities is critical for maintaining or increasing participation in activities like birdwatching and hunting. A mail-out survey was administered to a generalized sample representative of U.S. residents (i.e., not specific to birdwatching or hunting) in early 2017 to determine what would limit them from participating in birdwatching and hunting (n = 1030). We employed a concurrent nested mixed-methods design: open-ended responses were thematically coded qualitatively in two distinct cycles (i.e., inductive, and then mixed inductive-deductive coding), and then the probability of expressing the second cycle codes was quantitatively modeled using multinomial logit models for the respective activities. Doing so empirically determined various groups’ constraints that are important to recruitment, retention, and reactivation (R 3 ) efforts for birdwatching and hunting. We found that the likelihood of experiencing unique constraints varied based on sociodemographic characteristics, and these relationships differed between birdwatching and hunting. Gender had a limited effect on constraints to birdwatching but was a strong indicator of intrapersonal constraints and limitations to involvement in hunting. The likelihood of expressing structural constraints decreased with age for both activities. Possessing strong social ties to the activities tended to reduce the likelihood of expressing constraints overall but this was especially true for hunting. Our findings inform R 3 efforts for wildlife-related recreation and provide direct results that organizations can apply in seeking to help Americans negotiate constraints and increase and diversify participation in wildlife-related recreation and conservation behavior.

Journal of Outdoor Recreation and Tourism↗

USGS2008

Coupled semivariogram uncertainty of hydrogeological and geophysical data on capture zone uncertainty analysis

This study investigates capture zone uncertainty that relates to the coupled semivariogram uncertainty of hydrogeological and geophysical data. Semivariogram uncertainty is represented by the uncertainty in structural parameters (range, sill, and nugget). We used the beta distribution function to derive the prior distributions of structural parameters. The probability distributions of structural parameters were further updated through the Bayesian approach with the Gaussian likelihood functions. Cokriging of noncollocated pumping test data and electrical resistivity data was conducted to better estimate hydraulic conductivity through autosemivariograms and pseudo-cross-semivariogram. Sensitivities of capture zone variability with respect to the spatial variability of hydraulic conductivity, porosity and aquifer thickness were analyzed using ANOVA. The proposed methodology was applied to the analysis of capture zone uncertainty at the Chicot aquifer in Southwestern Louisiana, where a regional groundwater flow model was developed. MODFLOW-MODPATH was adopted to delineate the capture zone. The ANOVA results showed that both capture zone area and compactness were sensitive to hydraulic conductivity variation. We concluded that the capture zone uncertainty due to the semivariogram uncertainty is much higher than that due to the kriging uncertainty for given semivariograms. In other words, the sole use of conditional variances of kriging may greatly underestimate the flow response uncertainty. Semivariogram uncertainty should also be taken into account in the uncertainty analysis. ?? 2008 ASCE.

Journal of Hydrologic Engineering↗

USGS2014

Deep permeability of the San Andreas Fault from San Andreas Fault Observatory at Depth (SAFOD) core samples

The San Andreas Fault Observatory at Depth (SAFOD) scientific borehole near Parkfield, California crosses two actively creeping shear zones at a depth of 2.7 km. Core samples retrieved from these active strands consist of a foliated, Mg-clay-rich gouge containing porphyroclasts of serpentinite and sedimentary rock. The adjacent damage zone and country rocks are comprised of variably deformed, fine-grained sandstones, siltstones, and mudstones. We conducted laboratory tests to measure the permeability of representative samples from each structural unit at effective confining pressures, P e up to the maximum estimated in situ P e of 120 MPa. Permeability values of intact samples adjacent to the creeping strands ranged from 10 −18 to 10 −21 m 2 at P e = 10 MPa and decreased with applied confining pressure to 10 −20 –10 −22 m 2 at 120 MPa. Values for intact foliated gouge samples (10 −21 –6 × 10 −23 m 2 over the same pressure range) were distinctly lower than those for the surrounding rocks due to their fine-grained, clay-rich character. Permeability of both intact and crushed-and-sieved foliated gouge measured during shearing at P e ≥ 70 MPa ranged from 2 to 4 × 10 −22 m 2 in the direction perpendicular to shearing and was largely insensitive to shear displacement out to a maximum displacement of 10 mm. The weak, actively-deforming foliated gouge zones have ultra-low permeability, making the active strands of the San Andreas Fault effective barriers to cross-fault fluid flow. The low matrix permeability of the San Andreas Fault creeping zones and adjacent rock combined with observations of abundant fractures in the core over a range of scales suggests that fluid flow outside of the actively-deforming gouge zones is probably fracture dominated.

Journal of Structural Geology↗

USGS2001

Estimation of brood and nest survival: Comparative methods in the presence of heterogeneity

The Mayfield method has been widely used for estimating survival of nests and young animals, especially when data are collected at irregular observation intervals. However, this method assumes survival is constant throughout the study period, which often ignores biologically relevant variation and may lead to biased survival estimates. We examined the bias and accuracy of 1 modification to the Mayfield method that allows for temporal variation in survival, and we developed and similarly tested 2 additional methods. One of these 2 new methods is simply an iterative extension of Klett and Johnson's method, which we refer to as the Iterative Mayfield method and bears similarity to Kaplan-Meier methods. The other method uses maximum likelihood techniques for estimation and is best applied to survival of animals in groups or families, rather than as independent individuals. We also examined how robust these estimators are to heterogeneity in the data, which can arise from such sources as dependent survival probabilities among siblings, inherent differences among families, and adoption. Testing of estimator performance with respect to bias, accuracy, and heterogeneity was done using simulations that mimicked a study of survival of emperor goose ( Chen canagica ) goslings. Assuming constant survival for inappropriately long periods of time or use of Klett and Johnson's methods resulted in large bias or poor accuracy (often >5% bias or root mean square error) compared to our Iterative Mayfield or maximum likelihood methods. Overall, estimator performance was slightly better with our Iterative Mayfield than our maximum likelihood method, but the maximum likelihood method provides a more rigorous framework for testing covariates and explicity models a heterogeneity factor. We demonstrated use of all estimators with data from emperor goose goslings. We advocate that future studies use the new methods outlined here rather than the traditional Mayfield method or its previous modifications.

Journal of Wildlife Management↗

USGS2015

Probabilistic 3-D time-lapse inversion of magnetotelluric data: Application to an enhanced geothermal system

Surface-based monitoring of mass transfer caused by injections and extractions in deep boreholes is crucial to maximize oil, gas and geothermal production. Inductive electromagnetic methods, such as magnetotellurics, are appealing for these applications due to their large penetration depths and sensitivity to changes in fluid conductivity and fracture connectivity. In this work, we propose a 3-D Markov chain Monte Carlo inversion of time-lapse magnetotelluric data to image mass transfer following a saline fluid injection. The inversion estimates the posterior probability density function of the resulting plume, and thereby quantifies model uncertainty. To decrease computation times, we base the parametrization on a reduced Legendre moment decomposition of the plume. A synthetic test shows that our methodology is effective when the electrical resistivity structure prior to the injection is well known. The centre of mass and spread of the plume are well retrieved.We then apply our inversion strategy to an injection experiment in an enhanced geothermal system at Paralana, South Australia, and compare it to a 3-D deterministic time-lapse inversion. The latter retrieves resistivity changes that are more shallow than the actual injection interval, whereas the probabilistic inversion retrieves plumes that are located at the correct depths and oriented in a preferential north-south direction. To explain the time-lapse data, the inversion requires unrealistically large resistivity changes with respect to the base model. We suggest that this is partly explained by unaccounted subsurface heterogeneities in the base model from which time-lapse changes are inferred.

Geophysical Journal International↗

USGS2003

Spring hunting changes the regional movements of migrating greater snow geese

1. Human-induced disturbance such as hunting may influence the migratory behaviour of long-distance migrants. In 1999 and 2000 a spring hunt of greater snow geese Anser caerulescens atlanticus occurred for the first time in North America since 1916, aimed at stopping population growth to protect natural habitats. 2. We evaluated the impact of this hunt on the staging movements of geese along a 600-km stretch of the St Lawrence River in southern Quebec, Canada. 3. We tracked radio-tagged female geese in three contiguous regions of the staging area from the south-west to the north-east: Lake St Pierre, Upper Estuary and Lower Estuary, in spring 1997 (n = 37) and 1998 (n = 70) before the establishment of hunting , and in 1999 (n = 60) and 2000 (n = 59) during hunting . 4. We used multi-state capture-recapture models to estimate the movement probabilities of radio-tagged females among these regions. To assess disturbance level, we tracked geese during their feeding trips and estimated the probability of completing a foraging bout without being disturbed. 5. In the 2 years without hunting , migration was strongly unidirectional from the south-west to the north-east, with very low westward movement probabilities. Geese gradually moved from Lake St Pierre to Upper Estuary and then from Upper Estuary to Lower Estuary. 6. In contrast, during the 2 years with hunting westward movement was more than four times more likely than in preceding years. Most of these backward movements occurred shortly after the beginning of the hunt, indicating that geese moved back to regions where they had not previously experienced hunting . 7. Overall disturbance level increased in all regions in years with hunting relative to years without hunting . 8. Synthesis and applications. We conclude that spring hunting changed the stopover scheduling of this long-distance migrant and might further impact population dynamics by reducing prenuptial fattening. The spring hunt may also have increased crop damage. We propose that staggered hunt opening dates could attenuate secondary effects of such management actions.

Quebec↗

USGS1983

Statistical evaluation of oil and gas prospects in the outer continental shelf of the U.S. Gulf Coast

Areas of the U.S. Gulf Coast, both onshore and offshore, are among the petroliferous regions of the United States. In offshore Louisiana and Texas, most oil and gas is associated with structurally controlled traps on the crest or flanks of domes created by the diapiric movement of salt. These structures can be detected and mapped by seismic techniques that directly indicate favorable prospective areas. The characteristics of seismically defined structures provide information in advance of drilling about the probable size of reservoirs contained within these structures. Simple statistical relationships can be determined between the size, shape, and other attributes of structures detected by seismic mapping and the presence and size of petroleum and natural gas reservoirs. Gulf Coast OCS lease tracts presently are evaluated by the U.S. government using a Monte Carlo simulation procedure adapted from reservoir analysis. Specification of the parameters of the Monte Carlo model are obtained subjectively in advance of drilling and thus are highly uncertain. Comparisons of predrill predictions with postdiscovery reservoir evaluations show very low correlations. In contrast, predrill predictions based on regressions between seismic structural properties and reservoir volumes show highly significant correlations. In addition, statistical analysis of seismic structure is much simpler than the Monte Carlo procedure, and can be applied rapidly and inexpensively. A statistical analysis of the "Pleistocene Trend" of offshore Louisiana and Texas, an area of about 3 million acres, yielded results that are sufficiently encouraging to suggest that similar evaluations be made of the remaining Gulf Coast OCS and of OCS regions off of other coasts of the United States. ?? 1983 Plenum Publishing Corporation.

Journal of the International Association for Mathe↗

USGS2024

Constraining mean landslide occurrence rates for non-temporal landslide inventories using high-resolution elevation data

Constraining landslide occurrence rates can help to generate landslide hazard models that predict the spatial and temporal occurrence of landslides. However, most landslide inventories do not include any temporal data due to the difficulties of dating landslide deposits. Here we introduce a method for estimating the mean landslide occurrence rate of deep-seated rotational and translational slides derived solely from high-resolution (≤3 m) elevation data and globally available estimates of the diffusion coefficient for sediment flux. The method applies a linear diffusion model to the roughest landslide deposits until they reach a representative non-landslide roughness distribution. This estimates the time for a landslide deposit to be unrecognizable in high-resolution digital elevation data, which we term the mean lifetime of the landslide. Using the mean lifetime and number of landslides within an area of interest, we can estimate the mean occurrence rate of landslides over that domain. We validate this approach using a comprehensive temporal inventory of landslides in western Oregon created using age-roughness curves that are calibrated with high-resolution elevation data and radiocarbon data. We find good agreement between our diffusion method and the existing age-roughness-derived estimates, producing mean lifetimes of 4500 and 5200 years (4% difference), respectively. Hazard maps produced using the two methodologies generally agree, with the maximum differences in landslide probability reaching 0.1. Due to the relative abundance of high-resolution elevation data compared with age-dated landslides, our method could help constrain landslide occurrence rates in areas previously considered unfeasible.

Oregon↗

USGS2022

Mapping the probability of freshwater algal blooms with various spectral indices and sources of training data

Algal blooms are pervasive in many freshwater environments and can pose risks to the health and safety of humans and other organisms. However, monitoring and tracking of potentially harmful blooms often relies on in-person observations by the public. Remote sensing has proven useful in augmenting in situ observations of algal concentration, but many hurdles hinder efficient application by end users. First, numerous approaches to estimate aquatic chlorophyll-a are available and can produce inconsistent results. Second, lack of quantitative in situ observations limits opportunities to train models for specific waterbodies, such that models developed for other systems must be used instead. We (1) implement univariate and multivariate logistic regression models to estimate the probability that aquatic chlorophyll-a concentrations exceed an accepted threshold beyond which harmful effects become likely and (2) evaluate the use of visually classified bloom/no-bloom satellite imagery to augment in situ training data. Using a binary classification of aquatic chlorophyll-a exceeding 10 μg / L, we found that (1) logistic regression models were ∼80 % accurate, (2) univariate models trained with visually classified data produce nearly the same accuracy (79%) as models trained with in situ observations (80%), and (3) augmenting in situ chlorophyll-a observations with visual classifications outperformed (82% accuracy) models trained on in situ observations alone (80% accuracy). These results provide a framework for evaluating multiple spectral indices in retrieving algal bloom presence or absence and illustrate that training data derived directly from satellite imagery can be useful in augmenting in situ observations.

Idaho, Oregon↗