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At least 343 records · Page 19

Global precipitation estimates based on a technique for combining satellite-based estimates, rain gauge analysis, and NWP model precipitation information

The 'satellite-gauge model' (SGM) technique is described for combining precipitation estimates from microwave satellite data, infrared satellite data, rain gauge analyses, and numerical weather prediction models into improved estimates of global precipitation. Throughout, monthly estimates on a 2.5 degrees x 2.5 degrees lat-long grid are employed. First, a multisatellite product is developed using a combination of low-orbit microwave and geosynchronous-orbit infrared data in the latitude range 40 degrees N - 40 degrees S (the adjusted geosynchronous precipitation index) and low-orbit microwave data alone at higher latitudes. Then the rain gauge analysis is brougth in, weighting each field by its inverse relative error variance to produce a nearly global, observationally based precipitation estimate. To produce a complete global estimate, the numerical model results are used to fill data voids in the combined satellite-gauge estimate. Our sequential approach to combining estimates allows a user to select the multisatellite estimate, the satellite-gauge estimate, or the full SGM estimate (observationally based estimates plus the model information). The primary limitation in the method is imperfections in the estimation of relative error for the individual fields. The SGM results for one year of data (July 1987 to June 1988) show important differences from the individual estimates, including model estimates as well as climatological estimates. In general, the SGM results are drier in the subtropics than the model and climatological results, reflecting the relatively dry microwave estimates that dominate the SGM in oceanic regions.

Huffman, George J.↗

Development and Implementation of a Comprehensive Radiometric Validation Protocol for the CERES Earth Radiation Budget Climate Record Sensors

The CERES Flight Models 1 through 4 instruments were launched aboard NASA's Earth Observing System (EOS) Terra and Aqua Spacecraft into 705 Km sun-synchronous orbits with 10:30 a.m. and 1:30 p.m. equatorial crossing times. These instruments supplement measurements made by the CERES Proto Flight Model (PFM) instrument launched aboard NASA's Tropical Rainfall Measuring Mission (TRMM) into a 350 Km, 38-degree mid-inclined orbit. CERES Climate Data Records consist of geolocated and calibrated instantaneous filtered and unfiltered radiances through temporally and spatially averaged TOA, Surface and Atmospheric fluxes. CERES filtered radiance measurements cover three spectral bands including shortwave (0.3 to 5 microns), total (0.3 to 100 microns) and an atmospheric window channel (8 to 12 microns). The CERES Earth Radiation Budget measurements represent a new era in radiation climate data, realizing a factor of 2 to 4 improvement in calibration accuracy and stability over the previous ERBE climate records, while striving for the next goal of 0.3-percent per decade absolute stability. The current improvement is derived from two sources: the incorporation of lessons learned from the ERBE mission in the design of the CERES instruments and the development of a rigorous and comprehensive radiometric validation protocol consisting of individual studies covering different spatial, spectral and temporal time scales on data collected both pre and post launch. Once this ensemble of individual perspectives is collected and organized, a cohesive and highly rigorous picture of the overall end-to-end performance of the CERES instrument's and data processing algorithms may be clearly established. This approach has resulted in unprecedented levels of accuracy for radiation budget instruments and data products with calibration stability of better than 0.2-percent and calibration traceability from ground to flight of 0.25-percent. The current work summarizes the development, philosophy and implementation of the protocol designed to rigorously quantify the quality of the data products as well as the level of agreement between the CERES TRMM, Terra and Aqua climate data records.

Priestley, K. J.↗

Verification and validation of developed short-term forecasting models

Recent advancements in machine learning (ML) and artificial intelligence (AI) technologies provide an opportunity for leveraging data-driven algorithms to predict future nuclear power plant (NPP) operating conditions by using recorded plant process data. Successfully implementing these models can lead to cost-reducing, conditioned-based predictive maintenance through optimized maintenance schedules and a reduction of unnecessary maintenance activities. This report discusses the verification and validation of short-term forecasting processes (i.e., data cleaning, feature selection, model optimization, and forecasting) developed in previous reports. The verification and validation (V&V) process demonstrates the expected precision and accuracy when the ML model encounters new datasets from different systems. Shapley additive explanations were used as the primary means of feature selection across these different data set. Individual models were trained for each data set, then validated through a cross-validation procedure. In this report, two different ML models were tasked to predict variables from three different plant process data sets with varying prediction horizons. The results indicate that support vector regression (SVR) outperformed long short-term memory (LSTM) neural networks in regard to each data set and each prediction horizon in this study, but further tuning and optimization could improve long short-term memory results. However, each forecasting model showed reduced performance as the prediction horizon was extended from 1 hour to 1 day ahead. Research is ongoing to evaluate the optimal input variable space, which is based on a given set of process parameters, to further improve forecasting accuracy.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Comparative analysis of nutrient concentrations in generalist and specialist tree species and soils, Manaus, Brazil

This dataset was collected near Manaus, Brazil, at ZF-2 site, inside the North-South transect plots from 20221011 to 20221020. Measurements were made on specialists and generalist tree species along topographic gradient (in upland high-clay content soils of plateaus and high sandy content and partially flooded soils of valleys). We selected nine species (with four replicates each, totaling 35 individuals) occurring in different topographic positions: three plateau specialists, three valley specialists, and three generalists, where leaf and trunk samples were collected from each individual, and soil samples for carbon and nutrient analysis and quantification. Three soil pits were opened around each sample tree, about one meter apart (total of 105 soil pits each 60-cm deep), where soil samples were collected at four depths: 0-5, 5-10, 10-30 and 30-50 cm. In each of the three pits around each tree, one single sample was taken at each depth and combined to obtain a composite sample per depth per individual tree (35 trees × 4 depths = 140 soil samples). The files “Plant_Nutrient_Concentrations_NS_Transect_Manaus.csv” and “Soil_Nutrient_Concentrations_NS_Transect_Manaus.csv” contain the nutrient concentration data from plant and soil material, respectively. Additionally, the file “Sample_Info.csv” contains details about each variable including units and data type. The file “Species_Info.csv” includes information about each sampled individual, such as species, family, diameter at the breast height (DBH), and more. The dataset is ready to be used in any programming language like python or R. This dataset was originally published on the NGEE Tropics Archive and is being mirrored on ESS-DIVE for long-term archival Acknowledgement: Funding for NGEE-Tropics data resources was provided by the U.S. Department of Energy Office of Science, Office of Biological and Environmental Research.

54 ENVIRONMENTAL SCIENCES↗

The statistical magnetic signature of magnetospheric substorms

Daily magnetograms from a midlatitude network of geomagnetic observatories were used in the analysis of approximately 1800 substorm events, and the characteristic magnetic signatures of magnetospheric substorms both on the ground and in space were determined. Auroral electrojet (AE) indices and individual magnetograms at different local times in the auroral zone and at midlatitudes were analyzed with reference to onsets, and superposed epoch averages of individual magnetograms and AE indices confirm the local time magnetic substorm signatures. Superposed epoch averages of the interplanetary magnetic field (IMF) associated with the onsets demonstrates both a distinct southward component prior to the onsets and a dependence of the substorm amplitude on the integrated preceding southward IMF flux. Superposed epoch averages of the tail lobe magnetic field magnitude and vector components are discussed.

Caan, M. N.↗

Proteomic analysis of hair shafts from monozygotic twins: Expression profiles and genetically variant peptides

Forensic association of hair shaft evidence with individuals is currently assessed by comparing mitochondrial DNA haplotypes of reference and casework samples, primarily for exclusionary purposes. Present work tests and validates more recent proteomic approaches to extract quantitative transcriptional and genetic information from hair samples of monozygotic twin pairs, which would be predicted to partition away from unrelated individuals if the datasets contain identifying information. Protein expression profiles and polymorphic, genetically variant hair peptides were generated from ten pairs of monozygotic twins. Profiling using the protein tryptic digests revealed that samples from identical twins had typically an order of magnitude fewer protein expression differences than unrelated individuals. The data did not indicate that the degree of difference within twin pairs increased with age. In parallel, data from the digests were used to detect genetically variant peptides that result from common nonsynonymous single nucleotide polymorphisms in genes expressed in the hair follicle. Compilation of the variants permitted sorting of the samples by hierarchical clustering, permitting accurate matching of twin pairs. The results demonstrate that genetic differences are detectable by proteomic methods and provide a framework for developing quantitative statistical estimates of personal identification that increase the value of hair shaft evidence.

59 BASIC BIOLOGICAL SCIENCES↗

Integrating Predictions for Improving Defect Classification Accuracy in NDT-based Assessment of Concrete - 20229

There is an increasing need to create predictive models for defect classification in concrete using the output of non-destructive testing (NDT) techniques. Recent advancement of machine-learning algorithms has offered several techniques for developing classification models for different types of data sets. However, the performance of these algorithms is very uncertain, mainly when applied to small and noisy datasets. For example, when human access is limited (e.g., nuclear facility), robot-based NDT is preferred. But compared to manual tests with humans present on site, the data sets are small, and more noise can exist. Therefore, it is imperative to develop new approaches to ensure a consistently high classification accuracy for inadequate data sets. This study explores the classification performance on NDT dataset using classifiers from different machine-learning algorithms, namely k-Nearest Neighbor (kNN), Decision Tree, Naive Bayes, Logistic Regression, and Support Vector Machine (SVM). The authors further integrated the predictions from these classifiers using proposed methods. The integration strategy combines the output of the classifiers based on two different measures, accuracy, and performance (ACC and PERF), using equations such as sum, average, and square-root-of-sums-of-squares (SRSS). Our results reveal varying classification accuracies across individual classifiers with different misclassifications across the test data set. The integration strategy provided significant improvement in the classification accuracy compared to the individual classifiers. Furthermore, the results indicate minimal variation across the integration methods as compared to the variation across the individual classifiers. To conclude, prediction integration offers a unique approach for combining the output of multiple classifiers to create redundancies with the potential of achieving high classification performance and improved reliability in predictive models for defect detection in concrete. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Generative Representations for Evolving Families of Designs

Since typical evolutionary design systems encode only a single artifact with each individual, each time the objective changes a new set of individuals must be evolved. When this objective varies in a way that can be parameterized, a more general method is to use a representation in which a single individual encodes an entire class of artifacts. In addition to saving time by preventing the need for multiple evolutionary runs, the evolution of parameter-controlled designs can create families of artifacts with the same style and a reuse of parts between members of the family. In this paper an evolutionary design system is described which uses a generative representation to encode families of designs. Because a generative representation is an algorithmic encoding of a design, its input parameters are a way to control aspects of the design it generates. By evaluating individuals multiple times with different input parameters the evolutionary design system creates individuals in which the input parameter controls specific aspects of a design. This system is demonstrated on two design substrates: neural-networks which solve the 3/5/7-parity problem and three-dimensional tables of varying heights.

Hornby, Gregory S.↗

Human ocular torsion during parabolic flights: an analysis with scleral search coil

Rotation of the eyes about the visual axis is known as ocular torsion. A lateral inclination (a "roll") of the head induces ocular torsion in the opposite direction, a response known as ocular counterrolling. For six subjects, we recorded the static (head still) and dynamic (head in oscillatory roll motion) ocular torsion in normal 1 g condition and also during the microgravity and hypergravity periods of parabolic flight, using the electromagnetic scleral search coil technique. With the head still, the direction and magnitude of torsion that occurred in response to microgravity and hypergravity differed substantially from one individual to another, but there was a significant difference in torsional magnitude between the microgravity and hypergravity periods, for all static head positions including the upright position. Under normal 1 g conditions, counterrolling compensated for about 16% of (voluntary) static head roll, while dynamic counterroll was much larger, up to 36% of head roll at 0.55 Hz. With increasing frequency of head oscillation between 0.33 Hz and 0.55 Hz, the gain of counterrolling increased and there was no change in the phase relationship. The gain of dynamic counterroll (in response to voluntary head rolling) was not significantly less in hypogravity, suggesting that on the ground at these frequencies the contribution of gravity and gravity receptors to this reflex is redundant: this reflex is probably driven by the semicircular canals. In some subjects, the torsional displacement in microgravity is accompanied by micro-torsional oscillatory motion.

Non-NASA Center↗

The Influence of Contrasting Microbial Lifestyles on the Pre-symbiotic Metabolite Responses of Eucalyptus grandis Roots

Plant roots co-inhabit the soil with a diverse consortium of microbes of which a number attempt to enter symbiosis with the plant. These microbes may be pathogenic, mutualistic, or commensal. Hence, the health and survival of plants is heavily reliant on their ability to perceive different microbial lifestyles and respond appropriately. Emerging research suggests that there is a pivotal role for plant root secondary metabolites in responding to microbial colonization. However, it is largely unknown if plants are able to differentiate between microbes of different lifestyles and respond differently during the earliest stages of pre-symbiosis (i.e., prior to physical contact). In studying plant responses to a range of microbial isolates, we questioned: (1) if individual microbes of different lifestyles and species caused alterations to the plant root metabolome during pre-symbiosis, and (2) if these early metabolite responses correlate with the outcome of the symbiotic interaction in later phases of colonization. We compared the changes of the root tip metabolite profile of the model tree Eucalyptus grandis during pre-symbiosis with two isolates of a pathogenic fungus (Armillaria luteobubalina), one isolate of a pathogenic oomycete (Phytophthora cinnamomi), two isolates of an incompatible mutualistic fungus (Suillus granulatus), and six isolates of a compatible mutualistic fungus (Pisolithus microcarpus). Untargeted metabolite profiling revealed predominantly positive root metabolite responses at the pre-symbiosis stage, prior to any observable phenotypical changes of the root tips. Metabolite responses in the host tissue that were specific to each microbial species were identified. A deeper analysis of the root metabolomic profiles during pre-symbiotic contact with six strains of P. microcarpus showed a connection between these early metabolite responses in the root with later colonization success. Further investigation using isotopic tracing revealed a portion of metabolites found in root tips originated from the fungus. RNA-sequencing also showed that the plant roots undergo complementary transcriptomic reprogramming in response to the fungal stimuli. Taken together, our results demonstrate that the early metabolite responses of plant roots are partially selective toward the lifestyle of the interacting microbe, and that these responses can be crucial in determining the outcome of the interaction.

59 BASIC BIOLOGICAL SCIENCES↗

Improving coastal water level estimation by merging nadir-only satellite altimetry data into a hydrodynamic model

Providing robust real time flood warnings is of paramount importance to coastal communities. Although state-of-the-art hydrodynamic models are capable of robustly predicting Coastal Water Levels (CWL), unresolved drivers affecting level fluctuations are often not represented by the model governing equations. This work evaluates a novel method to improve the performance of the ADvanced CIRCulation (ADCIRC) hydrodynamic model by assimilating observations from four nadir-only satellite altimetry missions against a set of National Oceanic and Atmospheric Administration (NOAA) gauge stations located across the entire U.S. East Coast. Two different types of simulations were performed – Open Loop (OL) and Data Assimilation (DA). Five different simulations were performed where four different satellite altimetry observations were assimilated individually and combined with two different scenarios – with and without considering the data quality flags. Results indicate that, despite their limited spatial coverage, merging nadir-only observations into ADCIRC from the newly launched Surface Water and Ocean Topography (SWOT)’s nadir altimeter can improve the model performance at 76% of the gauge locations, whereas Sentinel-6 improves 73% of the total locations, Jason-3 74%, and SARAL 21%. Furthermore, combining observations from SWOT-nadir, Jason-3, and Sentinel-6 can improve the ADCIRC performance at more than 80% of the gauge locations for 107-day simulation. Nadir-only satellite altimetry observations can be useful for improving the model performance even if flagged as “poor quality” near the coast. When the flagged data are disregarded, SWOT can improve ADCIRC at 78%, Sentinel-6 at 73%, Jason-3 at 53%, and SARAL at 21% of the gauge locations. The ability to improve the model simulations largely depends on the availability of a satellite overpass nearby. Therefore, model performance can be further enhanced if satellite observations are available during a storm surge event, stressing the importance of frequent satellite overpasses.

Aafnan Bhuiyan, Soelem↗

Melatonin concentrations in the sudden infant death syndrome

To examine a possible relationship between pineal function and the sudden infant death syndrome (SIDS), samples of whole blood, ventricular cerebrospinal fluid (CSF) and/or vitreous humor (VH) were obtained at autopsy from 68 infants (45 male, 23 female) whose deaths were attributed to either SIDS (n = 32, 0.5-5.0 months of age; mean plus or minus S.E.M., 2.6 plus or minus 0.2 months) or other causes (non-SIDS, n = 36, 0.3-8.0 months of age 4.3 plus or minus 0.3 months). The melatonin concentrations were measured by radioimmunoassay. A significant correlation was observed for melatonin levels in different body fluids from the same individual. After adjusting for age differences, CSF melatonin levels were significantly lower among the SIDS infants (91 plus or minus 29 pmol/l; n = 32) than among those dying from other causes (180 plus or minus 27; n = 35, P less than 0.05). A similar, but non-significant trend was also noted in blood (97 plus or minus 23, n = 30 vs. 144 plus or minus 22 pmol/l, n = 33) and vitreous humor (68 plus or minus 21, n = 10 vs. 81 plus or minus 17 pmol/l, n = 15). These differences do not appear to be explainable in terms of the interval between death and autopsy, gender, premortem infection, or therapeutic measures instituted prior to death. Diminished melatonin production may be characteristic of SIDS and could represent an impairment in the maturation of physiologic circadian organization.

Sturner, W. Q.↗

Geologic Structures in Crater Walls on Vesta

The Framing Camera (FC) on the Dawn spacecraft has imaged most of the illuminated surface of Vesta with a resolution of apporpx. 20 m/pixel through different wavelength filters that allow for identification of lithologic units. The Visible and Infrared Mapping Spectrometer (VIR) has imaged the surface at lower spatial resolution but high spectral resolution from 0.25 to 5 micron that allows for detailed mineralogical interpretation. The FC has imaged geologic structures in the walls of fresh craters and on scarps on the margin of the Rheasilvia basin that consist of cliff-forming, competent units, either as blocks or semi-continuous layers, hundreds of m to km below the rims. Different units have different albedos, FC color ratios and VIR spectral characteristics, and different units can be juxtaposed in individual craters. We will describe different examples of these competent units and present preliminary interpretations of the structures. A common occurrence is of blocks several hundred m in size of high albedo (bright) and low albedo (dark) materials protruding from crater walls. In many examples, dark material deposits lie below coherent bright material blocks. In FC Clementine color ratios, bright material is green indicating deeper 1 m pyroxene absorption band. VIR spectra show these to have deeper and wider 1 and 2 micron pyroxene absorption bands than the average vestan surface. The associated dark material has subdued pyroxene absorption features compared to the average vestan surface. Some dark material deposits are consistent with mixtures of HED materials with carbonaceous chondrites. This would indicate that some dark material deposits in crater walls are megabreccia blocks. The same would hold for bright material blocks found above them. Thus, these are not intact crustal units. Marcia crater is atypical in that the dark material forms a semi-continuous, thin layer immediately below bright material. Bright material occurs as one or more layers. In one region, there is an apparent angular unconformity between the bright material and the dark material where bright material layers appear to be truncated against the underlying dark layer. One crater within the Rheasilvia basin contains two distinct types of bright materials outcropping on its walls, one like that found elsewhere on Vesta and the other an anomalous block ~200 m across. This material has the highest albedo; almost twice that of the vestan average. Unlike all other bright materials, this block has a subdued 1 micron pyroxene absorption band in FC color ratios. These data indicate that this block represents a distinct vestan lithology that is rarely exposed.

Mittlefehldt, David W.↗

Associations between SARS-CoV-2 Infection or COVID-19 Vaccination and Human Milk Composition: A Multi-Omics Approach

Background: The risk of contracting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) via human milk-feeding is virtually nonexistent. Adverse effects of coronavirus disease 2019 (COVID-19) vaccination for lactating individuals are not different from the general population, and no evidence has been found that their infants exhibit adverse effects. Yet, there remains substantial hesitation among this population globally regarding the safety of these vaccines. Objectives: Herein, we aimed to determine if compositional changes in milk occur following SARS-CoV-2 infection or COVID-19 vaccination, including any evidence of vaccine components. Methods: An extensive multiomics approach was taken using a subset of milk samples obtained as part of our broad studies examining the effects on milk of SARS-CoV-2 infection and COVID-19 vaccination. Results: We found that compared with unvaccinated individuals, SARS-CoV-2 infection was associated with significant compositional differences in 67 proteins, 385 lipids, and 13 metabolites. In contrast, COVID-19 vaccination was not associated with any changes in lipids or metabolites, although it was associated with changes in 13 or fewer proteins. Compositional changes in milk differed by vaccine. Changes following vaccination were greatest after 1–6 h for the mRNA-based Moderna vaccine (8 changed proteins), 3 d for the mRNA-based Pfizer (4 changed proteins), and adenovirus-based Johnson and Johnson (13 changed proteins) vaccines. Proteins that changed after both natural infection and Johnson and Johnson vaccine were associated mainly with systemic inflammatory responses. In addition, no vaccine components were detected in any milk sample. Conclusions: Together, our data provide evidence of only minimal changes in milk composition because of COVID-19 vaccination, with much greater changes after natural SARS-CoV-2 infection.

60 APPLIED LIFE SCIENCES↗

A determination of meteor mass distribution from meteor echoes

Meteor counts from observations at four magnitudes in the range of about +9 to +15 in the visual scale were used to determine the exponent of the mass distribution law under certain assumptions. Since for these data no range measures were available, and since the pattern of the transmitting/receiving antennas was very broad, the same range and radiant distribution were assumed for all counts within the same half hour during which individual counts at different magnitudes were obtained. These echo counts, covering in five successive days 24 hr with overlapping periods, yielded for the exponent a value of 1.95 + or - 0.02, close to other determinations. Individual values, however, presented a considerable scatter, probably reflecting changes in radiant and mass distribution over the year. From the same data, it appeared that the mass exponent changed during the day, yielding generally a higher value for the evening hours.

Forti, G.↗

SAGE 2-Umkehr case study of ozone differences and aerosol effects from October 1984 to April 1989

A comparison of 1262 cases of coincident ozone profiles derived from 666 Umkehrs at 17 different stations and 901 SAGE 2 profiles within 1000 km and 12 hours between October 1984 and April 1989 indicates the following layer percentage differences with 2-sigma error bars: layer three 14.6 plus/minus 3.3 percent, layer four 17.6 plus/minus 1.1 percent, layer five -1.3 plus/minus 0.5 percent, layer six -5.7 plus/minus 0.7 percent, layer seven -1.0 plus/minus 0.7 percent, layer eight 4.2 plus/minus 0.7 percent, and layer nine 6.8 plus/minus 1.2 percent. Comparing SAGE 2-Umkehr differences to SAGE 1 version 5.5-Umkehr differences shows SAGE 2 higher than or equal to SAGE 1 relative to Umkehr in all layers except layer three. Adjustment for this bias would produce trends derived from SAGE 2-SAGE 1 differences and Umkehr observations in the 1980s more nearly equal to each other in layers six, seven, and eight. A possible explanation of these differences is a systematic shift in the reference altitude between SAGE 1 and SAGE 2, but there is no independent evidence of this. While the shape of the vertical profile of differences at 17 individual Umkehr stations (mostly in mid-latitudes) is generally consistent at all stations except at Poker Flat, Seoul, and Lauder, significant variation does exists among the stations. The profile of mean difference is similar to previously observed differences between Umkehr and both SAGE 2 and SBUV and also to an eigenvector analysis, but with site-dependent amplitude discrepancies. Because of the close correspondence of stratospheric aerosol optical depth at the SAGE 2-measured 0.525 micron wavelength and the extrapolated 0.32 Umkehr wavelength determined in this study, we use the 0.525 micron data to determine the aerosol effect of Umkehr profiles. The aerosol errors to the Umkehr ozone amounts in percent ozone amount per 0.01 stratospheric aerosol optical depth range from plus 2 percent in layer six to minus 3 percent in layer nine. These results agree with previous theoretical and empirical studies within their respective error bounds in layers nine, eight, and five. The result in layer six differs significantly from previous works. In view of the fact that SAGE 2 and Umkehr produce different ozone retrievals in layers eight and nine and because the intra-layer correlation of SAGE 2 ozone and aerosol in layers eight and nine in non-zero, one must exercise some caution in attributing the entire SAGE 2-Umkehr differences in the upper layers to an aerosol effect.

Newchurch, M. J.↗

Modelling individual variability in growth of bull trout in the Walla Walla River Basin using a hierarchical von Bertalanffy growth model

Abstract We examined growth in length of fluvial bull trout ( Salvelinus confluentus ) in the Walla Walla River Basin, Washington and Oregon. Our objectives were to quantify individual variability in growth; examine growth within and among years, life history forms, life stages and sexes; and estimate von Bertalanffy growth parameters. Individual variability was evaluated by modelling asymptotic length ( L ∞ ) and the growth coefficient ( k ) as random variables. All models were fit with Bayesian methods and were evaluated for fit by the deviance information criterion. By incorporating individual variability, population‐level estimates of L ∞ and k appeared appropriate and estimated growth trajectories for specific bull trout fit individual observed patterns in growth. Growth trajectories and positive correlation between individual estimates of L ∞ and k suggest that some individuals grow at a faster rate and reach a larger maximum size than other individuals and those differences are maintained throughout life. Selected models suggest that fluvial migrants have higher estimates of L ∞ and k than residents, but there were only slight differences in parameter estimates among migrants from two adjacent spawning populations in the Walla Walla River Basin, as well as between males and females. Growth rates increased for fluvial migrants after subadult emigration. Individual variability in growth is consistent with the life history diversity assumed essential for bull trout population persistence. Quantifying this variability is important for modelling population dynamics and viability to conserve this threatened species.

Harris, Julianne E.↗