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USGS2004

Goals and strategies for estimating trends in landbird abundance

Reliable estimates of trends in population size are critical to effective management of landbirds. We propose a standard for considering that landbird populations are adequately monitored: 80% power to detect a 50% decline occuning within 20 years, using a 2-tailed test and a significance level of 0.10, and incorporating effects of potential bias. Our standard also requires that at least two-thirds of the target region be covered by the monitoring program. We recommend that the standard be achieved for species' entire ranges or for any area one-third the size of the temperate portions of Canada and the United States, whichever is smaller. We applied our approach to North American Breeding Bird Survey (BBS) data. At present, potential annual bias for the BBS is estimated at ??0.008. Further, the BBS achieves the monitoring standard for only about 42% of landbirds for which the BBS is considered the most effective monitoring approach. Achieving the proposed monitoring target for ???80% of these species would require increasing the number of BBS - or similar survey - routes by several-fold, a goal that probably is impractical. We suggest several methods for reducing potential bias and argue that if our methods are implemented, potential bias would fall to ??0.003. The required number of BBS or similar routes would then be 5,106, about 40% more than in the current BBS program. Most of the needed increases are in 15 states or provinces. Developing a comprehensive land-bird monitoring program will require increased support for coordination of the BBS (currently 2 people) and new programs for species that are poorly covered at present. Our results provide a quantitative goal for long-term land-bird monitoring and identify the sample sizes needed, within each state and province, to achieve the monitoring goal for most of the roughly 300 landbird species that are well suited to monitoring with the BBS and similar surveys.

Journal of Wildlife Management↗

USGS2008

Importance of sampling design and analysis in animal population studies: a comment on Sergio et al

1. The use of predators as indicators and umbrellas in conservation has been criticized. In the Trentino region, Sergio et al. (2006; hereafter SEA) counted almost twice as many bird species in quadrats located in raptor territories than in controls. However, SEA detected astonishingly few species. We used contemporary Swiss Breeding Bird Survey data from an adjacent region and a novel statistical model that corrects for overlooked species to estimate the expected number of bird species per quadrat in that region. 2. There are two anomalies in SEA which render their results ambiguous. First, SEA detected on average only 6.8 species, whereas a value of 32 might be expected. Hence, they probably overlooked almost 80% of all species. Secondly, the precision of their mean species counts was greater in two-thirds of cases than in the unlikely case that all quadrats harboured exactly the same number of equally detectable species. This suggests that they detected consistently only a biased, unrepresentative subset of species. 3. Conceptually, expected species counts are the product of true species number and species detectability p. Plenty of factors may affect p, including date, hour, observer, previous knowledge of a site and mobbing behaviour of passerines in the presence of predators. Such differences in p between raptor and control quadrats could have easily created the observed effects. Without a method that corrects for such biases, or without quantitative evidence that species detectability was indeed similar between raptor and control quadrats, the meaning of SEA's counts is hard to evaluate. Therefore, the evidence presented by SEA in favour of raptors as indicator species for enhanced levels of biodiversity remains inconclusive. 4. Synthesis and application. Ecologists should pay greater attention to sampling design and analysis in animal population estimation. Species richness estimation means sampling a community. Samples should be representative for the community studied and the sampling fraction among communities compared should be the same on average, otherwise formal estimation approaches must be applied to avoid misleading inference.

Journal of Applied Ecology↗

USGS2013

Modelling interactions of toxicants and density dependence in wildlife populations

1. A major challenge in the conservation of threatened and endangered species is to predict population decline and design appropriate recovery measures. However, anthropogenic impacts on wildlife populations are notoriously difficult to predict due to potentially nonlinear responses and interactions with natural ecological processes like density dependence. 2. Here, we incorporated both density dependence and anthropogenic stressors in a stage-based matrix population model and parameterized it for a density-dependent population of peregrine falcons Falco peregrinus exposed to two anthropogenic toxicants [dichlorodiphenyldichloroethylene (DDE) and polybrominated diphenyl ethers (PBDEs)]. Log-logistic exposure–response relationships were used to translate toxicant concentrations in peregrine falcon eggs to effects on fecundity. Density dependence was modelled as the probability of a nonbreeding bird acquiring a breeding territory as a function of the current number of breeders. 3. The equilibrium size of the population, as represented by the number of breeders, responded nonlinearly to increasing toxicant concentrations, showing a gradual decrease followed by a relatively steep decline. Initially, toxicant-induced reductions in population size were mitigated by an alleviation of the density limitation, that is, an increasing probability of territory acquisition. Once population density was no longer limiting, the toxicant impacts were no longer buffered by an increasing proportion of nonbreeders shifting to the breeding stage, resulting in a strong decrease in the equilibrium number of breeders. 4. Median critical exposure concentrations, that is, median toxicant concentrations in eggs corresponding with an equilibrium population size of zero, were 33 and 46 μg g −1 fresh weight for DDE and PBDEs, respectively. 5. Synthesis and applications. Our modelling results showed that particular life stages of a density-limited population may be relatively insensitive to toxicant impacts until a critical threshold is crossed. In our study population, toxicant-induced changes were observed in the equilibrium number of nonbreeding rather than breeding birds, suggesting that monitoring efforts including both life stages are needed to timely detect population declines. Further, by combining quantitative exposure–response relationships with a wildlife demographic model, we provided a method to quantify critical toxicant thresholds for wildlife population persistence.

California↗

USGS2009

A cautionary note on substituting spatial subunits for repeated temporal sampling in studies of site occupancy

1. Assessing the probability that a given site is occupied by a species of interest is important to resource managers, as well as metapopulation or landscape ecologists. Managers require accurate estimates of the state of the system, in order to make informed decisions. Models that yield estimates of occupancy, while accounting for imperfect detection, have proven useful by removing a potentially important source of bias. To account for detection probability, multiple independent searches per site for the species are required, under the assumption that the species is available for detection during each search of an occupied site. 2. We demonstrate that when multiple samples per site are defined by searching different locations within a site, absence of the species from a subset of these spatial subunits induces estimation bias when locations are exhaustively assessed or sampled without replacement. 3. We further demonstrate that this bias can be removed by choosing sampling locations with replacement, or if the species is highly mobile over a short period of time. 4. Resampling an existing data set does not mitigate bias due to exhaustive assessment of locations or sampling without replacement. 5. Synthesis and applications. Selecting sampling locations for presence/absence surveys with replacement is practical in most cases. Such an adjustment to field methods will prevent one source of bias, and therefore produce more robust statistical inferences about species occupancy. This will in turn permit managers to make resource decisions based on better knowledge of the state of the system.

Journal of Applied Ecology↗

USGS2016

Optimizing selection of training and auxiliary data for operational land cover classification for the LCMAP initiative

The U.S. Geological Survey’s Land Change Monitoring, Assessment, and Projection (LCMAP) initiative is a new end-to-end capability to continuously track and characterize changes in land cover, use, and condition to better support research and applications relevant to resource management and environmental change. Among the LCMAP product suite are annual land cover maps that will be available to the public. This paper describes an approach to optimize the selection of training and auxiliary data for deriving the thematic land cover maps based on all available clear observations from Landsats 4–8. Training data were selected from map products of the U.S. Geological Survey’s Land Cover Trends project. The Random Forest classifier was applied for different classification scenarios based on the Continuous Change Detection and Classification (CCDC) algorithm. We found that extracting training data proportionally to the occurrence of land cover classes was superior to an equal distribution of training data per class, and suggest using a total of 20,000 training pixels to classify an area about the size of a Landsat scene. The problem of unbalanced training data was alleviated by extracting a minimum of 600 training pixels and a maximum of 8000 training pixels per class. We additionally explored removing outliers contained within the training data based on their spectral and spatial criteria, but observed no significant improvement in classification results. We also tested the importance of different types of auxiliary data that were available for the conterminous United States, including: (a) five variables used by the National Land Cover Database, (b) three variables from the cloud screening ‘‘Function of mask” (Fmask) statistics, and (c) two variables from the change detection results of CCDC. We found that auxiliary variables such as a Digital Elevation Model and its derivatives (aspect, position index, and slope), potential wetland index, water probability, snow probability, and cloud probability improved the accuracy of land cover classification. Compared to the original strategy of the CCDC algorithm (500 pixels per class), the use of the optimal strategy improved the classification accuracies substantially (15-percentage point increase in overall accuracy and 4-percentage point increase in minimum accuracy).

ISPRS Journal of Photogrammetry and Remote Sensing↗

USGS2023

Developing a stochastic hydrological model for informing lake water level drawdown management

Winter drawdown (WD) is a common lake management tool for multiple purposes such as flood control, aquatic vegetation reduction, and lake infrastructure maintenance. To minimize adverse impacts to a lake’s ecosystem, regulatory agencies may provide managers with general guidelines for drawdown and refill timing, drawdown magnitude, and outflow limitations. However, there is significant uncertainty associated with the potential to meet management targets due to variability in lake characteristics and hydrometeorology of each lake’s basin, making the use of modeling tools a necessity. In this context, we developed a hydrological modeling framework for lake water level drawdown management (HMF-Lake) and evaluated it at 15 Massachusetts lakes where WDs have been applied over multiple years for vegetation control. HMF-Lake is based on the daily lake water balance, with inflows simulated by a lumped rainfall-runoff model (Cemaneige-GR4J) and outflow rate calculated by a modified Target Storage and Release Based Method (TSRB). The model showed a satisfactory performance of simulating historical water levels (0.53 ≤ NSE ≤ 0.86), however, uncertainties from meteorological inputs and TSRB determined lake outflow rate affected the result accuracy. To account for these uncertainties, the model was executed stochastically to assess the ability of study lakes to follow the Massachusetts’ general WD guidelines: drawdown by Dec 1 and fully refilled by Apr 1. By using the stochastic HMF-Lake, the probabilities of each lake to reach the drawdown level by Dec 1 were calculated for different drawdown magnitudes (1–6 ft). The probability results suggest it was generally less possible for most of study lakes to achieve a drawdown of 3 ft or more by Dec 1. Moreover, we employed the stochastic model to derive the annual latest refill starting dates that ensure a 95 % probability of reaching the normal water level by Apr 1. We found starting a refill in March for drawdowns up to 6 ft was feasible for most of study lakes. These results provide lake managers with a quantitative understanding of the lake’s ability to follow the state guidelines. The model may be used to systematically evaluate current WD management strategies at state or regional scales and support adaptive WD management under changing climates.

Massachusetts↗

USGS2012

The mechanics of ground deformation precursory to dome-building extrusions at Mount St. Helens 1981-1982

Detailed monitoring at Mount St. Helens since 1980 has enabled prediction of the intermittent eruptive activity (mostly dome growth) with unprecedented success. During 1981 and 1982, accelerating deformation of the crater floor around the vent (including radial cracks, thrust faults, and ground tilt) was the earliest indicator of impending activity. Numerical experiments using the finite element method to model the mechanics of the crater floor show that all deformation features can be explained by a uniform shear-stress boundary condition along the conduit wall. The magnitude of the shear stress required to match observed displacements (1–7 MPa) is inversely proportional to the conduit diameter (estimated to be 25–100 m). The most probable source of this shear stress is the flow of viscous magma up the conduit and into the lava dome. We propose a model in which the accelerating deformation, beginning as much as 4 weeks before extrusions, is caused by the increasing velocity of ascending magma in the conduit. This model is examined by using deformation data of the dome before four extrusions in 1981 and 1982 to estimate the volumetric flow rate through the conduit. This flow rate and an estimate of the effective viscosity of the magma enable calculation of an ascent velocity and an applied shear stress that, again, depend on the conduit diameter. The results of these calculations are consistent with the finite element experiments and show that the proposed model is feasible. In light of this model, events observed just before or near the time extrusions began, such as reversals of ground tilt direction from outward to inward and the sudden decrease in the number of shallow earthquakes, may indicate an abrupt decrease of shear stress in the conduit. This could be explained by a decrease in either the ascent velocity, or the effective viscosity of the magma ascending through the shallow conduit, or both, near the time of extrusion. Precursory deformation like that measured at Mount St. Helens should be observable at similar volcanoes elsewhere because it is caused by the fundamental process of magma ascent.

Journal of Geophysical Research Solid Earth↗

USGS2017

Assessing models of arsenic occurrence in drinking water from bedrock aquifers in New Hampshire

Three existing multivariate logistic regression models were assessed using new data to evaluate the capacity of the models to correctly predict the probability of groundwater arsenic concentrations exceeding the threshold values of 1, 5, and 10 micrograms per liter (µg/L) in New Hampshire, USA. A recently released testing dataset includes arsenic concentrations from groundwater samples collected in 2004–2005 from a mix of 367 public-supply and private domestic wells. The use of this dataset to test three existing logistic regression models demonstrated enhanced overall predictive accuracy for the 5 and 10 μg/L models. Overall accuracies of 54.8, 76.3, and 86.4 percent were reported for the 1, 5, and 10 μg/L models, respectively. The state was divided by counties into northwest and southeast regions. Regional differences in accuracy were identified; models had an average accuracy of 83.1 percent for the counties in the northwest and 63.7 percent in the southeast. This is most likely due to high model specificity in the northwest and regional differences in arsenic occurrence. Though these models have limitations, they allow for arsenic hazard assessment across the region. The introduction of well-type (public or private), well depth, and casing length as explanatory variables may be appropriate measures to improve model performance. Our findings indicate that the original models generalize to the testing dataset, and should continue to serve as an important vehicle of preventative public health that may be applied to other groundwater contaminants in New Hampshire.

New Hampshire↗

USGS2010

Occupancy dynamics in a tropical bird community: Unexpectedly high forest use by birds classified as non‐forest species

1. Worldwide loss of biodiversity necessitates a clear understanding of the factors driving population declines as well as informed predictions about which species and populations are at greatest risk. The biggest threat to the long-term persistence of populations is the reduction and changes in configuration of their natural habitat. 2. Inconsistencies have been noted in the responses of populations to the combined effects of habitat loss and fragmentation. These have been widely attributed to the effects of the matrix habitats in which remnant focal habitats are typically embedded. 3. We quantified the potential effects of the inter-patch matrix by estimating occupancy and colonization of forest and surrounding non-forest matrix (NF). We estimated species-specific parameters using a dynamic, multi-species hierarchical model on a bird community in southwestern Costa Rica. 4. Overall, we found higher probabilities of occupancy and colonization of forest relative to the NF across bird species, including those previously categorized as open habitat generalists not needing forest to persist. Forest dependency was a poor predictor of occupancy dynamics in our study region, largely predicting occupancy and colonization of only non-forest habitats. 5. Our results indicate that the protection of remnant forest habitats is key for the long-term persistence of all members of the bird community in this fragmented landscape, including species typically associated with open, non-forest habitats. 6. Synthesis and applications. We identified 39 bird species of conservation concern defined by having high estimates of forest occupancy, and low estimates of occupancy and colonization of non-forest. These species survive in forest but are unlikely to venture out into open, non-forested habitats, therefore, they are vulnerable to the effects of habitat loss and fragmentation. Our hierarchical community-level model can be used to estimate species-specific occupancy dynamics for focal and inter-patch matrix habitats to identify which species within a community are likely to be impacted most by habitat loss and fragmentation. This model can be applied to other taxa (i.e. amphibians, mammals and insects) to estimate species and community occurrence dynamics in response to current environmental conditions and to make predictions in response to future changes in habitat configurations.

Journal of Applied Ecology↗

USGS2013

Complex resistivity signatures of ethanol in sand-clay mixtures

We performed complex resistivity (CR) measurements on laboratory columns to investigate changes in electrical properties as a result of varying ethanol (EtOH) concentration (0% to 30% v/v) in a sand–clay (bentonite) matrix. We applied Debye decomposition, a phenomenological model commonly used to fit CR data, to determine model parameters (time constant: τ, chargeability: m, and normalized chargeability: m n ). The CR data showed a significant (P ≤ 0.001) time-dependent variation in the clay driven polarization response (~ 12 mrad) for 0% EtOH concentration. This temporal variation probably results from the clay–water reaction kinetics trending towards equilibrium in the sand–clay–water system. The clay polarization is significantly suppressed (P ≤ 0.001) for both measured phase (ϕ) and imaginary conductivity (σ″) with increasing EtOH concentration. Normalized chargeability consistently decreases (by up to a factor of ~ 2) as EtOH concentration increases from 0% to 10% and 10 to 20%, respectively. We propose that such suppression effects are associated with alterations in the electrical double layer (EDL) at the clay–fluid interface due to (a) strong EtOH adsorption on clay, and (b) complex intermolecular EtOH–water interactions and subsequent changes in ionic mobility on the surface in the EDL. Changes in the CR data following a change of the saturating fluid from EtOH 20% to plain water indicate strong hysteresis effects in the electrical response, which we attribute to persistent EtOH adsorption on clay. Our results demonstrate high sensitivity of CR measurements to clay–EtOH interactions in porous media, indicating the potential application of this technique for characterization and monitoring of ethanol contamination in sediments containing clays.

Journal of Contaminant Hydrology↗

USGS2018

Persistence-based area prioritization for conservation: Applying occupancy and habitat threats and risks analyses

Effective habitat conservation is predicated on maintaining high levels or increasing local persistence probability of the species it purports to protect. Thus, methodological approaches that improve the inferential value of local persistence are of utmost value to guide conservation planning as they inform area selection processes. Herein we used the painted bunting Passerina ciris, a species of conservation interest in North Carolina, as an illustrative case that combined single-season, single-species occupancy analyses and a threats and risk decision support tool to rank five areas of conservation interest in terms of local persistence probability. We used survey data from two seasons (2008–2009) grouped into 21 natal dispersal sampling units and land-cover data from 12 habitat classes to establish the relationship between local occupancy probability and habitat. Occupancy increased most strongly with increasing amount of maritime forest. Projections to year 2050, relative to year 2000, indicated that a potential loss of maritime forest of 200–1,300 ha, depending on the area of interest. Projected loss was lowest at Bald Head Island–Wilmington (2%) and highest at Camp Lejune (27%). Bald Head Island–Wilmington ranked highest in projected local persistence probability (0.91; 95% confidence interval [CI] = 0.53–0.99), whereas Top Sail–Hammocks Beach Park ranked lowest (0.28; 95% CI = 0.03–0.82). Estimates of local persistence offer decision-makers another criterion to prioritize areas for conservation and help guide efforts aimed at maintaining or enhancing local persistence. These include in situ habitat management, expanding or connecting existing areas of interest. In the future, we recommend the use of multiseason occupancy models, coupled with measures of uncertainty of land-cover projections, to strengthen inferences about local persistence, particularly useful in nonstationary landscapes driven by human activities.

North Carolina↗

USGS1983

The saltwater-freshwater interface in the Tertiary limestone aquifer, southeast Atlantic outer-continental shelf of the U.S.A.

Hydrologic testing in an offshore oil well abandoned by Tenneco, Inc., determined the position of the saltwater-freshwater interface in Tertiary limestones underlying the Florida-Georgia continental shelf of the U.S.A. Previous drilling (JOIDES and U.S.G.S. AMCOR projects) established the existence of freshwater far offshore in this area. At the Tenneco well 55 mi. (∼88 km) east of Fernandina Beach, Florida, drill-stem tests made in the interval 1050–1070 ft. (320–326 m) below sea level in the Ocala Limestone recovered a sample with a chloride concentration of 7000 mg l −1 . Formation water probably is slightly fresher. Pressure-head measurements indicated equivalent freshwater heads of 24–29 ft. (7.3–8.8 m) above sea level. At the coast (Fernandina Beach), a relatively thin transition zone separating freshwater and saltwater occurs at a depth of 2100 ft. (640 m) below sea level. Fifty-five miles (∼88 km) offshore, at the Tenneco well, the base of freshwater is ∼1100 ft. (∼335 m) below sea level. The difference in approximate depth to the freshwater-saltwater transition at these two locations suggests an interface with a very slight landward slope. Assuming the Hubbert interface equation applies here (because the interface and therefore freshwater flow lines are nearly horizontal) the equilibrium depth to the interface should be 40 times the freshwater head above sea level. Using present-day freshwater heads along the coast in the Hubbert equation results in depths to the interface of less than the observed 2100 ft. (640 m). Substituting predevelopment heads in the equation yields depths greater than 2100 ft. (640 m). Thus the interface appears to be in a transient position between the position that would be compatible with present-day heads and the position that would be compatible with predevelopment heads. This implies that some movement of the interface from the predevelopment position has occurred during the past hundred years. The implied movement is incompatible with the hypothesis that the freshwater occurring far offshore in this area is trapped water remaining since the Pleistocene Epoch.

Florida, Georgia↗

USGS2015

Limited role for thermal erosion by turbulent lava in proximal Athabasca Valles, Mars

The Athabasca Valles flood lava is among the most recent (<50 Ma) and best preserved effusive lava flows on Mars and was probably emplaced turbulently. The Williams et al. (2005) model of thermal erosion by lava has been applied to what we term “proximal Athabasca,” the 75 km long upstream portion of Athabasca Valles. For emplacement volumes of 5000 and 7500 km 3 and average flow thicknesses of 20 and 30 m, the duration of the eruption varies between ~11 and ~37 days. The erosion of the lava flow substrate is investigated for three eruption temperatures (1270°C, 1260°C, and 1250°C), and volatile contents equivalent to 0–65 vol % bubbles. The largest erosion depths of ~3.8–7.5 m are at the lava source, for 20 m thick and bubble-free flows that erupted at their liquidus temperature (1270°C). A substrate containing 25 vol % ice leads to maximum erosion. A lava temperature 20°C below liquidus reduces erosion depths by a factor of ~2.2. If flow viscosity increases with increasing bubble content in the lava, the presence of 30–50 vol % bubbles leads to erosion depths lower than those relative to bubble-free lava by a factor of ~2.4. The presence of 25 vol % ice in the substrate increases erosion depths by a factor of 1.3. Nevertheless, modeled erosion depths, consistent with the emplacement volume and flow duration constraints, are far less than the depth of the channel (~35–100 m). We conclude that thermal erosion does not appear to have had a major role in excavating Athabasca Valles.

Journal of Geophysical Research E: Planets↗

USGS2016

Application of a hybrid model to reduce bias and improve precision in population estimates for elk (Cervus elaphus) inhabiting a cold desert ecosystem

Accurately estimating the size of wildlife populations is critical to wildlife management and conservation of species. Raw counts or “minimum counts” are still used as a basis for wildlife management decisions. Uncorrected raw counts are not only negatively biased due to failure to account for undetected animals, but also provide no estimate of precision on which to judge the utility of counts. We applied a hybrid population estimation technique that combined sightability modeling, radio collar-based mark-resight, and simultaneous double count (double-observer) modeling to estimate the population size of elk in a high elevation desert ecosystem. Combining several models maximizes the strengths of each individual model while minimizing their singular weaknesses. We collected data with aerial helicopter surveys of the elk population in the San Luis Valley and adjacent mountains in Colorado State, USA in 2005 and 2007. We present estimates from 7 alternative analyses: 3 based on different methods for obtaining a raw count and 4 based on different statistical models to correct for sighting probability bias. The most reliable of these approaches is a hybrid double-observer sightability model (model M H ), which uses detection patterns of 2 independent observers in a helicopter plus telemetry-based detections of radio collared elk groups. Data were fit to customized mark-resight models with individual sighting covariates. Error estimates were obtained by a bootstrapping procedure. The hybrid method was an improvement over commonly used alternatives, with improved precision compared to sightability modeling and reduced bias compared to double-observer modeling. The resulting population estimate corrected for multiple sources of undercount bias that, if left uncorrected, would have underestimated the true population size by as much as 22.9%. Our comparison of these alternative methods demonstrates how various components of our method contribute to improving the final estimate and demonstrates why each is necessary.

Colorado↗

USGS2020

Causes of variability in suspended‐sand concentration evaluated using measurements in the Colorado River in Grand Canyon

Rivers commonly exhibit substantial variability in suspended‐sand concentration, even at constant water discharge. Here we derive an approach for evaluating how much of this variability arises from mean bed‐sand grain size. We apply this approach to the Colorado River in Grand Canyon, where discharge‐independent concentration of suspended sand varies by more than a factor of 23 ( N = 1.4 × 10 6 ). Theory predicts that where concentration is controlled by bed‐sand grain size, concentration and grain size in suspension will be inversely correlated (i.e., coarsening of the bed causes suspended sand to become coarser in grain size and lower in concentration). Although the observed correlation is negative, riverbed grain size accounts for only 40% of the variability in concentration. The residuals vary by an order of magnitude; they arise from other processes, such as changes in topography or distribution of sand that cause shear stress to change at constant discharge, changes in the fine tail of bed‐sand grain sizes or changing bedforms. Both bed sand and the other factors influence concentration for durations from less than 1 day to several years. Predictions of concentration based on bed‐sand grain size ( N = 4 × 10 4 ) are less accurate than predictions based on suspended‐sand grain size, probably because suspended sand is a natural integrator of sand‐transporting processes, giving more weight to those areas of the bed that exchange more sand with the flow. Although the causes of variability vary from one river to another, the approach illustrated here is applicable to any river in which concentration varies at constant water discharge.

Arizona↗

USGS2009

Incorporating uncertainty into the ranking of SPARROW model nutrient yields from Mississippi/Atchafalaya River basin watersheds

Excessive loads of nutrients transported by tributary rivers have been linked to hypoxia in the Gulf of Mexico. Management efforts to reduce the hypoxic zone in the Gulf of Mexico and improve the water quality of rivers and streams could benefit from targeting nutrient reductions toward watersheds with the highest nutrient yields delivered to sensitive downstream waters. One challenge is that most conventional watershed modeling approaches (e.g., mechanistic models) used in these management decisions do not consider uncertainties in the predictions of nutrient yields and their downstream delivery. The increasing use of parameter estimation procedures to statistically estimate model coefficients, however, allows uncertainties in these predictions to be reliably estimated. Here, we use a robust bootstrapping procedure applied to the results of a previous application of the hybrid statistical/mechanistic watershed model SPARROW (Spatially Referenced Regression On Watershed attributes) to develop a statistically reliable method for identifying “high priority” areas for management, based on a probabilistic ranking of delivered nutrient yields from watersheds throughout a basin. The method is designed to be used by managers to prioritize watersheds where additional stream monitoring and evaluations of nutrient-reduction strategies could be undertaken. Our ranking procedure incorporates information on the confidence intervals of model predictions and the corresponding watershed rankings of the delivered nutrient yields. From this quantified uncertainty, we estimate the probability that individual watersheds are among a collection of watersheds that have the highest delivered nutrient yields. We illustrate the application of the procedure to 818 eight-digit Hydrologic Unit Code watersheds in the Mississippi/Atchafalaya River basin by identifying 150 watersheds having the highest delivered nutrient yields to the Gulf of Mexico. Highest delivered yields were from watersheds in the Central Mississippi, Ohio, and Lower Mississippi River basins. With 90% confidence, only a few watersheds can be reliably placed into the highest 150 category; however, many more watersheds can be removed from consideration as not belonging to the highest 150 category. Results from this ranking procedure provide robust information on watershed nutrient yields that can benefit management efforts to reduce nutrient loadings to downstream coastal waters, such as the Gulf of Mexico, or to local receiving streams and reservoirs.

Atchafalaya River;Gulf Of Mexico;Mississippi River↗

USGS2008

Correlation of the Deccan and Rajahmundry Trap lavas: Are these the longest and largest lava flows on Earth?

We propose that the Rajahmundry Trap lavas, found near the east coast of peninsular India , are remnants of the longest lava flows yet recognized on Earth (∼ 1000 km long). These outlying Deccan-like lavas are shown to belong to the main Deccan Traps. Several previous studies have already suggested this correlation, but have not demonstrated it categorically. The exposed Rajahmundry lavas are interpreted to be the distal parts of two very-large-volume pāhoehoe flow fields, one each from the Ambenali and Mahabaleshwar Formations of the Wai Sub-group in the Deccan Basalt Group. Eruptive conditions required to emplace such long flows are met by plausible values for cooling and eruption rates, and this is shown by applying a model for the formation of inflated pāhoehoe sheet flow lobes. The model predicts flow lobe thicknesses similar to those observed in the Rajahmundry lavas. For the last 400 km of flow, the lava flows were confined to the pre-existing Krishna valley drainage system that existed in the basement beyond the edge of the gradually expanding Deccan lava field, allowing the flows to extend across the subcontinent to the eastern margin where they were emplaced into a littoral and/or shallow marine environment. These lavas and other individual flow fields in the Wai Sub-group may exceed eruptive volumes of 5000 km 3 , which would place them amongst the largest magnitude effusive eruptive units yet known. We suggest that the length of flood basalt lava flows on Earth is restricted mainly by the size of land masses and topography. In the case of the Rajahmundry lavas, the flows reached estuaries and the sea, where their advance was perhaps effectively terminated by cooling and/or disruption. However, it is only during large igneous province basaltic volcanism that such huge volumes of lava are erupted in single events, and when the magma supply rate is sufficiently high and maintained to allow the formation of very long lava flows. The Rajahmundry lava fields were emplaced around 65 Ma during the later times of Deccan volcanism, probably just after the K/T environmental crisis. However, many lava-forming eruptions of similar magnitude and style straddled the K/T boundary.

Rajahmundry Trap↗

USGS2026

Testing the efficacy of industrial mitigation measures for caribou in the Arctic

1. Mitigation measures are commonly employed to reduce the negative effects of industrial development on wildlife but are not often evaluated for their efficacy. For example, oil fields in the Arctic typically incorporate design features intended to increase permeability for migratory, barren-ground caribou ( Rangifer tarandus) , even though there is limited empirical evidence of the effectiveness of some of these features. 2. Given expected increases in energy development in the North American Arctic, we examined whether two mitigation measures commonly used for migratory caribou, elevating pipelines and separating roads and pipelines, were effective at increasing the probability caribou would cross infrastructure. 3. We conducted our investigation on adult female caribou in the Central Arctic Herd of Alaska during summer, analyzing movement data from telemetry collars (2015-2020) in conjunction with spatial data on oil field infrastructure. To evaluate whether caribou would cross infrastructure as a function of the mitigation measures, we employed a generalized additive modeling framework capable of detecting non-linear and threshold responses. 4. We found that caribou were more likely to cross a pipeline when the nearest pipeline was elevated (≥1.9-m), a result that supports current mitigation recommendations. We also found that caribou were more likely to cross both a road and pipeline when they were directly adjacent to one another, as opposed to being spatially separated, a result that contradicts recommended mitigation strategies. 5. Synthesis and applications . As new energy projects are designed and implemented in environments around the globe, it is important to ensure that mitigation efforts for wildlife are scientifically validated for their efficacy. In the North American Arctic, such efforts will be critical for minimizing the impacts of expanding industrial development on migratory caribou and on the human communities that rely on them for subsistence.

Alaska↗