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Results for “Journal of Applied Statistics”

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At least 145 records · Page 8Linked to original sources
USGS2015

Effects of freezing on white perch Morone americana (Gmelin, 1789): Implications for multivariate morphometrics

This study tested the hypothesis that duration of freezing differentially affects whole-body morphometrics of a derived teleost. Whole-body morphometrics are frequently analyzed to test hypotheses of different species, or stocks within a species, of fishes. Specimens used for morphometric analyses are typically fixed or preserved prior to analysis, yet little research has been done on how fixation or preservation methods or duration of preservation of specimens might affect outcomes of multivariate statistical analyses of differences in shape. To determine whether whole-body morphometrics changed as a result of freezing, 23 whole-body morphometrics of age-1 white perch ( Morone americana ) from western Lake Erie (n = 211) were analyzed immediately after capture, after being held on ice overnight, and after freezing for 100 or 200 days. Discriminant function analysis revealed that all four groups differed significantly from one another (P < 0.0001). The first canonical axis reflected long-axis morphometrics, where there was a clear pattern of positive translation along this axis with duration of preservation. Re-classification analysis demonstrated fish were typically assigned to their original preservation class except for fish frozen 100 days, which assigned mostly to frozen 200 days. Morphometric comparisons using frozen fish must be done on fish frozen for identical periods of time to avoid biases related to the length of time they were frozen. Similar experiments should be conducted on other species and also using formalin- and alcohol-preserved specimens.

Western Lake Erie↗
USGS2012

Tools for quantifying isotopic niche space and dietary variation at the individual and population level.

Ecologists are increasingly using stable isotope analysis to inform questions about variation in resource and habitat use from the individual to community level. In this study we investigate data sets from 2 California sea otter ( Enhydra lutris nereis ) populations to illustrate the advantages and potential pitfalls of applying various statistical and quantitative approaches to isotopic data. We have subdivided these tools, or metrics, into 3 categories: IsoSpace metrics, stable isotope mixing models, and DietSpace metrics. IsoSpace metrics are used to quantify the spatial attributes of isotopic data that are typically presented in bivariate (e.g., δ 13 C versus δ 15 N) 2-dimensional space. We review IsoSpace metrics currently in use and present a technique by which uncertainty can be included to calculate the convex hull area of consumers or prey, or both. We then apply a Bayesian-based mixing model to quantify the proportion of potential dietary sources to the diet of each sea otter population and compare this to observational foraging data. Finally, we assess individual dietary specialization by comparing a previously published technique, variance components analysis, to 2 novel DietSpace metrics that are based on mixing model output. As the use of stable isotope analysis in ecology continues to grow, the field will need a set of quantitative tools for assessing isotopic variance at the individual to community level. Along with recent advances in Bayesian-based mixing models, we hope that the IsoSpace and DietSpace metrics described here will provide another set of interpretive tools for ecologists.

Journal of Mammalogy↗
USGS2001

Processes controlling the episodic streamwater transport of atrazine and other agrichemicals in an agricultural watershed

Episodic streamwater transport of atrazine (a common agricultural herbicide) and nutrients has been observed throughout agricultural watersheds in the United States and poses a serious threat to the quality of its water resources. Catchment-scale atrazine and nutrient transport processes after agricultural application are still poorly understood, and predicting episodic streamwater composition remains an elusive goal. We instrumented a 1.2-km 2 agricultural catchment near Harrisonburg, Virginia, and examined streamwater, overland flow, soil water, groundwater, and rainfall during the summer of 1998. Storm chemographs demonstrated different patterns for constituents derived primarily from weathering (silica and calcium), compared to constituents derived primarily from early spring land applications (nitrate, atrazine, DOC, potassium, chloride, and sulfate). During storms, the concentrations of silica and calcium decreased, the atrazine response was variable, and the concentrations of nitrate, DOC, potassium, chloride, and sulfate increased; the elevated nitrate signal lagged several hours behind the other elevated constituents. Graphical and statistical analyses indicated a relatively stable spring-fed baseflow was modified by a mixture of overland flow and soil water. A rapid, short-duration overland-flow pulse dominated the streamflow early in the event and contributed most of the potassium, DOC, chloride, suspended sediment, and atrazine. A longer-duration soil–water pulse dominated the streamflow later in the event and contributed the nitrate as well as additional potassium, DOC, sulfate, and atrazine. The contributions to the episodic streamflow were quantified using a flushing model in which overland-flow and soil–water concentrations decreased exponentially with time during an episode. Flushing time constants for the overland-flow and soil–water reservoirs were calculated on a storm-by-storm basis using separate tracers for each time-variable reservoir. Initial component concentrations were estimated through regression analyses. Mass-balance calculations were used for flow separations and to predict the observed streamwater composition. Model forecasts indicated that reduced fertilizer and pesticide application (rather than elimination of overland-flow or soil–water contributions) was necessary to improve the episodic streamwater composition. This study provides important additional understanding of the catchment-scale processes by which land-applied pesticides and nutrients can move through agricultural systems.

Virginia↗
USGS2010

On the resolution of shallow mantle viscosity structure using post-earthquake relaxation data: Application to the 1999 Hector Mine, California, earthquake

Most models of lower crust/mantle viscosity inferred from postearthquake relaxation assume one or two uniform-viscosity layers. A few existing models possess apparently significant radially variable viscosity structure in the shallow mantle (e.g., the upper 200 km), but the resolution of such variations is not clear. We use a geophysical inverse procedure to address the resolving power of inferred shallow mantle viscosity structure using postearthquake relaxation data. We apply this methodology to 9 years of GPS-constrained crustal motions after the 16 October 1999 M = 7.1 Hector Mine earthquake. After application of a differencing method to isolate the postearthquake signal from the “background” crustal velocity field, we find that surface velocities diminish from ∼20 mm/yr in the first few months to ≲2 mm/yr after 2 years. Viscoelastic relaxation of the mantle, with a time-dependent effective viscosity prescribed by a Burgers body, provides a good explanation for the postseismic crustal deformation, capturing both the spatial and temporal pattern. In the context of the Burgers body model (which involves a transient viscosity and steady state viscosity), a resolution analysis based on the singular value decomposition reveals that at most, two constraints on depth-dependent steady state mantle viscosity are provided by the present data set. Uppermost mantle viscosity (depth ≲ 60 km) is moderately resolved, but deeper viscosity structure is poorly resolved. The simplest model that explains the data better than that of uniform steady state mantle viscosity involves a linear gradient in logarithmic viscosity with depth, with a small increase from the Moho to 220 km depth. However, the viscosity increase is not statistically significant. This suggests that the depth-dependent steady state viscosity is not resolvably different from uniformity in the uppermost mantle.

California↗
USGS2021

Racial, ethnic, and social patterns in the recreation specialization of birdwatchers: An analysis of United States eBird registrants

Although birdwatchers comprise a large and growing proportion of the American public, there is a lack of racial and ethnic diversity in the birdwatching community. Previous research suggests that this homogeneity is self-perpetuating, as ethno-racial minorities are less likely to pursue activities in which no one they know participates. However, it is unclear whether this trend in birdwatching participation also applies to degree of subsequent participant involvement. Using a national online survey of US birdwatchers, we measured the degree of recreation specialization among birdwatchers along affective, cognitive, and behavioral dimensions. We also determined whether respondents had social connections (acquaintances, close friends, or relatives) who birdwatch. We then used logistic regression to determine which ethno-racial groups were more likely to have birdwatcher social connections, and multiple linear regression to investigate how our measures of recreation specialization varied by ethno-racial group. As expected, the ethno-racial composition of the birdwatchers we studied was significantly less diverse than that of the American public. Of the 29,380 respondents who reported their ethno-racial group, 5.2% were Black, Indigenous, and/or people of color (including Native American, Black, Asian, Pacific Islander, Hispanic/Latino, or multiracial), while 94.8% were non-Hispanic White. However, we observed no statistically significant ethno-racial patterns in overall degree of recreation specialization, even when controlling for social connection and demographic characteristics. Considering the three dimensions of specialization individually, we found that some ethno-racial predictors were statistically significant, but coefficients were too small to be practically significant. We conclude that while some ethno-racial groups are underrepresented among birdwatchers, there is insufficient evidence that they are also under-specialized.

Journal of Outdoor Recreation and Tourism↗
USGS2022

NABat ML: Utilizing deep learning to enable crowdsourced development of automated, scalable solutions for documenting North American bat populations

Bats play crucial ecological roles and provide valuable ecosystem services, yet many populations face serious threats from various ecological disturbances. The North American Bat Monitoring Program (NABat) aims to use its technology infrastructure to assess status and trends of bat populations, while developing innovative and community-driven conservation solutions. Here, we present NABat ML , an automated machine-learning algorithm that improves the scalability and scientific transparency of NABat acoustic monitoring. This model combines signal processing techniques and convolutional neural networks (CNNs) to detect and classify recorded bat echolocation calls. We developed our CNN model with internet-based computing resources (‘cloud environment’), and trained it on >600,000 spectrogram images. We also incorporated species range maps to improve the robustness and accuracy of the model for future ‘unseen’ data. We evaluated model performance using a comprehensive, independent, holdout dataset. NABat ML successfully distinguished 31 classes (30 species and a noise class) with overall weighted-average accuracy and precision rates of 92%, and ≥90% classification accuracy for 19 of the bat species. Using a single cloud-environment computing instance, the entire model training process took <16 h. Synthesis and applications . Our convolutional neural network (CNN)-based model, NABat ML , classifies 30 North American bat species using their recorded echolocation calls with an overall accuracy of 92%. In addition to providing highly accurate species-level classification, NABat ML and its outputs are compatible with Bayesian and other statistical techniques for measuring uncertainty in classification. Our model is open-source and reproducible, enabling future implementations as software on end-user devices and cloud-based web applications. These qualities make NABat ML highly suitable for applications ranging from grassroots community science initiatives to big-data methods developed and implemented by researchers and professional practitioners. We believe the transparency and accessibility of NABat ML will encourage broad-scale participation in bat monitoring, and enable development of innovative solutions needed to conserve North American bat species.

Journal of Applied Ecology↗
USGS2015

Effects of climate and land cover on hydrology in the southeastern U.S.: Potential impacts on watershed planning

The hydrologic response to statistically downscaled general circulation model simulations of daily surface climate and land cover through 2099 was assessed for the Apalachicola-Chattahoochee-Flint River Basin located in the southeastern United States. Projections of climate, urbanization, vegetation, and surface-depression storage capacity were used as inputs to the Precipitation-Runoff Modeling System to simulate projected impacts on hydrologic response. Surface runoff substantially increased when land cover change was applied. However, once the surface depression storage was added to mitigate the land cover change and increases of surface runoff (due to urbanization), the groundwater flow component then increased. For hydrologic studies that include projections of land cover change (urbanization in particular), any analysis of runoff beyond the change in total runoff should include effects of stormwater management practices as these features affect flow timing and magnitude and may be useful in mitigating land cover change impacts on streamflow. Potential changes in water availability and how biota may respond to changes in flow regime in response to climate and land cover change may prove challenging for managers attempting to balance the needs of future development and the environment. However, these models are still useful for assessing the relative impacts of climate and land cover change and for evaluating tradeoffs when managing to mitigate different stressors.

Alabama, Florida, Georgia↗
USGS2015

Microscopical characterization of carbon materials derived from coal and petroleum and their interaction phenomena in making steel electrodes, anodes and cathode blocks for the Microscopy of Carbon Materials Working Group of the ICCP

This paper describes the evaluation of petrographic textures representing the structural organization of the organic matter derived from coal and petroleum and their interaction phenomena in the making of steel electrodes, anodes and cathode blocks. This work represents the results of the Microscopy of Carbon Materials Working Group in Commission III of the International Committee for Coal and Organic Petrology between the years 2009 and 2013. The round robin exercises were run on photomicrograph samples. For textural characterization of carbon materials the existing ASTM classification system for metallurgical coke was applied. These round robin exercises involved 15 active participants from 12 laboratories who were asked to assess the coal and petroleum based carbons and to identify the morphological differences, as optical texture (isotropic/anisotropic), optical type (punctiform, mosaic, fibre, ribbon, domain), and size. Four sets of digital black and white microphotographs comprising 151 photos containing 372 fields of different types of organic matter were examined. Based on the unique ability of carbon to form a wide range of textures, the results showed an increased number of carbon occurrences which have crucial role in the chosen industrial applications. The statistical method used to evaluate the results was based on the “raw agreement indices”. It gave a new and original view on the analysts' opinion by not only counting the correct answers, but also all of the knowledge and experience of the participants. Comparative analyses of the average values of the level of overall agreement performed by each analyst in the exercises during 2009–2013 showed a great homogeneity in the results, the mean value being 90.36%, with a minimum value of 83% and a maximum value of 95%.

International Journal of Coal Geology↗
USGS2009

Disease, predation and demography: Assessing the impacts of bovine tuberculosis on African buffalo by monitoring at individual and population levels

Summary Understanding the effects of disease is critical to determining appropriate management responses, but estimating those effects in wildlife species is challenging. We used bovine tuberculosis (BTB) in the African buffalo Syncerus caffer population of Kruger National Park, South Africa, as a case study to highlight the issues associated with estimating chronic disease effects in a long‐lived host. We used known and radiocollared buffalo, aerial census data, and a natural gradient in pathogen prevalence to investigate if: (i) at the individual level, BTB infection reduces reproduction; (ii) BTB infection increases vulnerability to predation; and (iii) at the population level, increased BTB prevalence causes reduced population growth. There was only a marginal reduction in calving success associated with BTB infection, as indexed by the probability of sighting a known adult female with or without a calf ( P = 0·065). Since 1991, BTB prevalence increased from 27 to 45% in the southern region and from 4 to 28% in the central region of Kruger National Park. The prevalence in the northern regions was only 1·5% in 1998. Buffalo population growth rates, however, were neither statistically different among regions nor declining over time. Lions Panthera leo did not appear to preferentially kill test‐positive buffalo. The best (Akaike's Information Criterion corrected for small sample size) AIC c model with BTB as a covariate [exp(β) = 0·49; 95% CI = (0·24–1·02)] suggested that the mortality hazard for positive individuals was no greater than for test‐negative individuals. Synthesis and applications . Test accuracy, time‐varying disease status, and movement among populations are some of the issues that make the detection of chronic disease impacts challenging. For these reasons, the demographic impacts of bovine tuberculosis in the Kruger National Park remain undetectable despite 6 years of study on known individuals and 40 years of population counts. However, the rainfall and forage conditions during this study were relatively good and the impacts of many chronic diseases may be a non‐linear function of environmental conditions such that they are only detectable in stressful periods.

Kruger National Park↗
USGS2025

Concentration-discharge relations and transient metal loads reveal spatiotemporal variability in solute-generation mechanisms in a mine-affected watershed

Concentration-discharge (CQ) relations are commonly used to understand geochemical and hydrologic controls on the generation of solutes in watersheds. Despite the widespread application of CQ relations, this technique has been infrequently applied to acid mine drainage (AMD) sites, but the CQ framework may allow mechanistic understanding of remedial outcomes such as impoundment of water within underground mines. Results of CQ analyses and changes in metal loads in an AMD affected watershed in Colorado, USA indicate that dissolved loads increased at many individual locations following water impoundment within mine workings. Although increased loads were observed at most individual locations, these increases were offset by a large decrease in loading from the largest mine. A loading analysis that included data from an instream monitoring location showed a statistically significant decrease in Fe and Zn after bulkhead emplacement, indicating a net positive effect of bulkheads. Streams generally displayed dilution CQ patterns whereas mines and springs showed either flushing or chemostatic patterns prior to bulkheading, which transitioned to chemostatic patterns following bulkheading, indicating a transition from dynamic to equilibrium geochemical processes. Saturation indices for sulfide and secondary minerals indicated that mines and springs were near equilibrium for phases including schwertmannite, fluorite, and gypsum. Saturation indices vary through time for mines suggesting progressive leaching of sulfide minerals as the mass of available minerals in the mine workings decreases. Together, these diverse analyses provide an integrated understanding of the variability in solute generating processes in this watershed and may inform remediation plans for similarly affected sites by indicating the nature of mineralogic controls on water quality.

Colorado↗
USGS1985

Three-dimensional trend mapping from wire-line logs

Mapping of lithofacies and porosities of stratigraphic units is complicated because these properties vary in three dimensions. The method of moments was proposed by Krumbein and Libby (1957) as a technique to aid in resolving this problem. Moments are easily computed from wireline logs and are simple statistics which summarize vertical variation in a log trace. Combinations of moment maps have proved useful in understanding vertical and lateral changes in lithology of sedimentary rock units. Although moments have meaning both as statistical descriptors and as mechanical properties, they also define polynomial curves which approximate lithologic changes as a function of depth. These polynomials can be fitted by least-squares methods, partitioning major trends in rock properties from finescale fluctuations. Analysis of variance yields the degree of fit of any polynomial and measures the proportion of vertical variability expressed by any moment or combination of moments. In addition, polynomial curves can be differentiated to determine depths at which pronounced expressions of facies occur and to determine the locations of boundaries between major lithologic subdivisions. Moments can be estimated at any location in an area by interpolating from log moments at control wells. A matrix algebra operation then converts moment estimates to coefficients of a polynomial function which describes a continuous curve of lithologic variation with depth. If this procedure is applied to a grid of geographic locations, the result is a model of variability in three dimensions. Resolution of the model is determined largely by number of moments used in its generation. The method is illustrated with an analysis of lithofacies in the Simpson Group of south-central Kansas; the three-dimensional model is shown as cross sections and slice maps. In this study, the gamma-ray log is used as a measure of shaliness of the unit. However, the method is general and can be applied, for example, to suites of neutron, density, or sonic logs to produce three-dimensional models of porosity in reservoir rocks. ?? 1985 Plenum Publishing Corporation.

Journal of the International Association for Mathe↗
USGS1965

Effects of field applications of heptachlor on bobwhite quail and other wild animals

A study of the effects of field applications of heptachlor on bobwhite quail ( Colinus uirginianus ) and other animals was conducted on three similar areas, two in Decatur County, Georgia, and one in Escambia County, Alabama, from February, 1958, to March, 1962. Heptachlor in granules was applied by aircraft on the Georgia areas for eradication of the imported fire ant ( Solenopsis saevissima ). Applications were directed by personnel of the U. S. Department of Agriculture, Plant Pest Control Division. The Alabama area remained untreated. Transects where whistling cocks were counted were superimposed on areas where coveys were counted. Size of areas varied from 14,000 to 20,000 acres. Each area had six transects, totaling 11,000 acres. Whistling cock bobwhites and coveys averaged 28 and 20 per 1,000 acres, respectively, the year before treatment on a Georgia area, and cocks and coveys averaged 25 per 1,000 acres for the duration of the study on the untreated Alabama area. Where portions of an area were treated at 2 pounds of heptachlor per acre, whistling cocks and coveys were reduced significantly, with a greater reduction where a greater amount of land was treated on the area or its transects. A decline of cocks and coveys also followed 1/2-pound applications (approaching statistical significance for coveys). Three years after treatment, cock and covey numbers were below those recorded before treatment. Whistling cocks and coveys also declined on adjoining land which remained untreated (significant for cocks, approaching significance for coveys). This decline was attributed to movements of bobwhites from untreated land to repopulate treated land. There is evidence that some loss occurred in bobwhites after they moved from untreated to treated land; the decrease in each instance was ascribed to the application of heptachlor. Songbirds were listed on the two Georgia areas. The first summer, eight more species and 458 more individuals of permanent resident birds were listed on the untreated area than on the treated area. After half of the originally untreated area was treated with heptachlor at 2 pounds per acre the following winter, the number of resident birds declined 37 percent. Some species of summer resident birds could not be found on treated land after heptachlor was applied. A small plot of 4 acres was intensively searched for dead and dying animals, and observations were made on living animals. Forty-seven days after treatment, no live animals were seen or heard on the plot, and a total of 38 dead animals had been found. Soils were sampled twice after treatment, and residues had declined in the second lot of samples. Twice animals also were obtained for analysis, and residues declined in the second group. Numbers of birds increased in the same period.

Alabama, Georgia↗
USGS2009

An improved procedure for detection and enumeration of walrus signatures in airborne thermal imagery

In recent years, application of remote sensing to marine mammal surveys has been a promising area of investigation for wildlife managers and researchers. In April 2006, the United States and Russia conducted an aerial survey of Pacific walrus (Odobenus rosmarus divergens) using thermal infrared sensors to detect groups of animals resting on pack ice in the Bering Sea. The goal of this survey was to estimate the size of the Pacific walrus population. An initial analysis of the U.S. data using previously-established methods resulted in lower detectability of walrus groups in the imagery and higher variability in calibration models than was expected based on pilot studies. This paper describes an improved procedure for detection and enumeration of walrus groups in airborne thermal imagery. Thermal images were first subdivided into smaller 200 x 200 pixel "tiles." We calculated three statistics to represent characteristics of walrus signatures from the temperature histogram for each the. Tiles that exhibited one or more of these characteristics were examined further to determine if walrus signatures were present. We used cluster analysis on tiles that contained walrus signatures to determine which pixels belonged to each group. We then calculated a thermal index value for each walrus group in the imagery and used generalized linear models to estimate detection functions (the probability of a group having a positive index value) and calibration functions (the size of a group as a function of its index value) based on counts from matched digital aerial photographs. The new method described here improved our ability to detect walrus groups at both 2 m and 4 m spatial resolution. In addition, the resulting calibration models have lower variance than the original method. We anticipate that the use of this new procedure will greatly improve the quality of the population estimate derived from these data. This procedure may also have broader applicability to thermal infrared surveys of other wildlife species. Published by Elsevier B.V.

International Journal of Applied Earth Observation↗
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↗
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↗
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↗
USGS2006

Methodology and results of calculating central California surface temperature trends: Evidence of human-induced climate change?

A procedure is described to construct time series of regional surface temperatures and is then applied to interior central California stations to test the hypothesis that century-scale trend differences between irrigated and nonirrigated regions may be identified. The procedure requires documentation of every point in time at which a discontinuity in a station record may have occurred through (a) the examination of metadata forms (e.g., station moves) and (b) simple statistical tests. From this "homogeneous segments" of temperature records for each station are defined. Biases are determined for each segment relative to all others through a method employing mathematical graph theory. The debiased segments are then merged, forming a complete regional time series. Time series of daily maximum and minimum temperatures for stations in the irrigated San Joaquin Valley (Valley) and nearby nonirrigated Sierra Nevada (Sierra) were generated for 1910-2003. Results show that twentieth-century Valley minimum temperatures are warming at a highly significant rate in all seasons, being greatest in summer and fall (> +0.25??C decade-1). The Valley trend of annual mean temperatures is +0.07?? ?? 0.07??C decade-1. Sierra summer and fall minimum temperatures appear to be cooling, but at a less significant rate, while the trend of annual mean Sierra temperatures is an unremarkable -0.02?? ?? 0.10??C decade-1. A working hypothesis is that the relative positive trends in Valley minus Sierra minima (>0.4??C decade-1 for summer and fall) are related to the altered surface environment brought about by the growth of irrigated agriculture, essentially changing a high-albedo desert into a darker, moister, vegetated plain. ?? 2006 American Meteorological Society.

Journal of Climate↗
USGS2023

Conserving habitat for migratory ungulates: How wide is a migration corridor?

Conserving migratory ungulates relies on the analysis of GPS collar data and associated maps of migration corridors to inform management and policy actions. Current methods for identifying migratory corridors use complex statistical models designed to account for movement uncertainty rather than estimating the amount of space required by animals to migrate. Furthermore, such methods can complicate conservation efforts by producing highly variable corridor widths and non-contiguous corridors that do not fully connect seasonal ranges. To remedy, we propose an intuitive line buffer approach for delineating individual migration corridors that is simple to implement and focuses on the functional corridor widths needed by migratory ungulates. By buffering a line that connects successive GPS locations, we can delineate individual migration corridors with consistent widths that are robust to variable parameters (GPS fix rate, travel speed, tortuosity) and provide contiguous connection between seasonal ranges. Using a combination of expert knowledge, simulation and 10-min GPS collar data collected from mule deer ( Odocoileus hemionus ) and pronghorn ( Antilocapra americana ), we suggest 400–600 m are reasonable estimates of functional migration corridor widths for individuals of those species. Synthesis and applications . Our line buffer approach is intended to simplify migration corridor delineation, improve transparency and encourage a broader discussion of functional corridor widths. These considerations help advance efforts to conserve habitat within migration corridors and prioritize conservation efforts within a single corridor or across multiple corridors.

Journal of Applied Ecology↗