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At least 181 records · Page 10

Rhodoxanthin synthase from honeysuckle; a membrane diiron enzyme catalyzes the multistep conversation of β-carotene to rhodoxanthin

Rhodoxanthin is a vibrant red carotenoid found across the plant kingdom and in certain birds and fish. It is a member of the atypical retro class of carotenoids, which contain an additional double bond and a concerted shift of the conjugated double bonds relative to the more widely occurring carotenoid pigments, and whose biosynthetic origins have long remained elusive. In this work, we identify LHRS ( Lonicera hydroxylase rhodoxanthin synthase), a variant β-carotene hydroxylase (BCH)–type integral membrane diiron enzyme that mediates the conversion of β-carotene into rhodoxanthin. We identify residues that are critical to rhodoxanthin formation by LHRS. Substitution of only three residues converts a typical BCH into a multifunctional enzyme that mediates a multistep pathway from β-carotene to rhodoxanthin via a series of distinct oxidation steps in which the product of each step becomes the substrate for the next catalytic cycle. We introduce a biosynthetic pathway from β-carotene to rhodoxanthin.

59 BASIC BIOLOGICAL SCIENCES↗

N-Glycolylneuraminic Acid Binding of Avian and Equine H7 Influenza A Viruses

Influenza A viruses (IAV) initiate infection by binding to glycans with terminal sialic acids on the cell surface. Hosts of IAV variably express two major forms of sialic acid, N-acetylneuraminic acid (NeuAc) and N-glycolylneuraminic acid (NeuGc). NeuGc is produced in most mammals, including horses and pigs, but is absent in humans, ferrets, and birds. The only known naturally occurring IAV that exclusively bind NeuGc are extinct highly pathogenic equine H7N7 viruses. We determined the crystal structure of a representative equine H7 hemagglutinin (HA) in complex with NeuGc and observed high similarity in the receptor-binding domain with an avian H7 HA. To determine the molecular basis for NeuAc and NeuGc specificity, we performed systematic mutational analyses, based on the structural insights, on two distant avian H7 HAs and an H15 HA. We found that the A135E mutation is key for binding α2,3-linked NeuGc but does not abolish NeuAc binding. The additional mutations S128T, I130V, T189A, and K193R converted the specificity from NeuAc to NeuGc. We investigated the residues at positions 128, 130, 135, 189, and 193 in a phylogenetic analysis of avian and equine H7 HAs. This analysis revealed a clear distinction between equine and avian residues. The highest variability was observed at key position 135, of which only the equine glutamic acid led to NeuGc binding. These results demonstrate that genetically distinct H7 and H15 HAs can be switched from NeuAc to NeuGc binding and vice versa after the introduction of several mutations, providing insights into the adaptation of H7 viruses to NeuGc receptors.

59 BASIC BIOLOGICAL SCIENCES↗

Avian Activity Classification Using Recurrent Networks to Fuse Videos with Metadata on Imbalanced Datasets

Activity classification plays a crucial role in various real-life scenarios involving both humans and animals. There is an increasing need for precise activity classification focused on avian-solar interactions, as the usage of solar energy facilities, such as photovoltaic array power stations, has been observed to impact bird species richness, behavior, and activity. However, there has been no work to develop an automated system to monitor and classify these avian-solar interactions. All current methods rely on human observers, which is time and human resources costly and subject to errors related to searcher efficiency. With the recent success of Deep Learning models in activity classification problems, this paper develops a recurrent neural network-based model to automatically classify six avian activities around solar energy facilities. Our proposed model integrates critical feature engineering metadata with video frame data, enabling improved learning and more accurate activity classification. Furthermore, we address the challenge of data imbalance during training and demonstrate the efficacy of our model in detecting and classifying different activities within video tracks. Additionally, we analyze the saliency/backpropagation map of the trained proposed model and validate its decision-making rationale.

Avian activity classification; bidirectional LSTM;↗

SSRS (Stochastic Soaring Raptor Simulator)

SSRS (Stochastic Soaring Raptor Simulator) is a generalizable, probabilistic, and predictive tool for wind energy developers, ecologists, wildlife managers and industry consultants to estimate the potential for soaring raptors to interact with operating wind turbines, without the need for site-specific data collection. Rapid expansion of wind energy development across the world has exposed the risk of turbine collisions for birds and bats. The risk to obligate soaring raptors such as golden eagles is of particular concern due to their small population and influence on ecological balance. Golden eagles rely heavily on updrafts to subsidize their flight, putting them in direct conflict with operational wind turbines that utilize the same wind resource. Understanding the behavior of soaring raptors with varying atmospheric conditions is crucial for predicting and mitigating the risk of turbine collision. This software contains a predictive movement model that simulates individual flight paths of golden eagles during updraft-subsidized long-distance flight, including migration. For a given set of atmospheric conditions, the model simulates thousands of eagles at turbine-scale spatial resolution (50m) to produce a relative presence density map. The simulated eagles rely on updrafts to pursue uninterrupted directional flight with minimal energy expenditure, following fluid-flow principles. The simulator includes a stochastic model of eagle behavior and a systematic method of accounting for spatiotemporal variations in atmospheric conditions. This framework only requires publicly available atmospheric data to estimate orographic and thermal updrafts, ensuring general usability.

Sandhu, Rimple↗

3DBFSVBF (3D BatFinder Smart Video BioFilter and Multi-class BatFinder Smart Video BioFilter) [SWR-22-88]

Bats are notoriously difficult to study, therefore, identifying specific behavioral trends and the precise environmental conditions at the time of collision requires a monitoring solution that can reliably collect relevant data. To date, thermal infrared video surveillance has been extensively applied to study bats and has proven to be a powerful yet cumbersome tool. Current analytical approaches are time consuming because data processing data has not been fully automated. In the past, steps have been taken to record avian and bat activity in conjunction with complicated image processing techniques that separate species from other moving objects within the field of view (i.e. clouds and portions of the wind turbine). Once the videos are collected, the post-processing does not allow real time monitoring and identification, leading to a delay in both studying the behavior of these species and determining the effectiveness of any impact reduction strategy being studied. Moreover, object identification capability is lacking, thus limiting the usefulness of video data. To resolve these issues, we are using open source 3D computer vision and machine learning techniques allowing for automatic detection of objects in real-time with the ability to correlate these objects with environmental variables and recording the flight paths of each object. The machine learning has been trained on 3D data and allows for automated real-time data collection, identification and tracking, thereby eliminating the need for long and tedious post-analysis processing of the videos. This machine learning model is an added feature to the previous BatFinder Smart Video BioFilter and increases the accuracy of that systems classification by increasing the accuracy of identifying bats (90% accuracy) and insects (69% accuracy) to a 97% accuracy. There are two object classifier machine learning models, Binary and multi-classification. Binary object classifier labeled BatFinder_Smart_Video_BioFilter.h5 distinguishes between biological objects and non-biological objects. The main goal of this object classifier is to ignore the turbine blades while detecting biological object flying withing the rotor swept area of the turbine. Non-biological objects have a probability of 0 and biological objects have a probability of 1. Multi-classifier labeled Multiclass_BatFinder_Smart_Video_BioFilter.h5 distinguishes between bats, birds, insects and non-biological.

Yarbrough, John↗

PV O&M Cost Model [SWR-21-14]

This tool presents a method for calculating costs associated with the operation and maintenance (O&M) of photovoltaic (PV) systems. The tool compiles details regarding the cost and frequency of multiple O&M services to estimate annual O&M costs ($/year) for each year of an analysis period, the net present value ($) of life cycle costs accumulated over the analysis period, and the reserve account amount ($) that might be required to fund unexpected repairs. The reserve account includes parts inventory and is important for providing a source of funds to make repairs quickly and avoid lost production. This method allows a detailed selection of services to perform based on system size, market served (e.g., residential, commercial, or utility), type and configuration of system components (e.g., micro-, string, or central inverter), and site and environmental conditions (e.g., pollen, bird populations) which is an improvement over simple per unit valuations of O&M costs ($/kW/year). This model also distinguishes costs that vary from year to year and increase at different rates over time as modeled by heuristic failure distributions (e.g., Weibull or Lognormal distribution) based on actuarial data for many of the services.

Walker, Andy↗

ThermalTracker 3D

ThermalTracker-3D is a stereo-vision solution for evaluating flight tracks of birds and bats around offshore wind turbines. Using a pair of thermal video cameras, the technology remotely senses movement of animals and objects, day and night, near critical assets. It generates motion tracks by collapsing a sequence of video frames from each camera into a single image that contains an entire flight track and then applies stereo-vision processing to transform the flight track into three dimensions. The approach allows tracking in near real time and automatically identifies moving objects based on features from the motion track and object size.

Matzner, Shari↗

ThermalTracker

This technology was developed to address the need for monitoring bird and bat activity at offshore locations for wind energy

Matzner, Shari [Pacific Northwest National Laborat↗

Ecological Benchmark for Chemicals

The Ecological Benchmark Tool dataset serves as a comprehensive repository of benchmarks designed to assess ecological risks at contaminated sites. This tool facilitates the evaluation of various environmental media and contaminants, supporting regulatory compliance and ecological protection. Benchmarks are available for air, biota, sediment, soil, and surface water. The dataset also provides species-specific benchmarks for fish, plants, birds, mammals, and invertebrates. Users can select benchmark sources, media, individual chemicals, and retrieve results in tabular or spreadsheet formats for analysis. Benchmarks are derived from authoritative sources, including government agencies, scientific councils, and academic publications. The dataset supports ecological risk assessments, regulatory decision-making, and environmental planning, with tools for benchmarking against chemical thresholds, sensitive species protection, and habitat impact evaluations. This structured approach ensures a robust evaluation of ecological risks tailored to site-specific and regulatory needs.

Stewart, Debra [Oak Ridge National Laboratory (ORN↗

Ecological Benchmark for Radionuclides

The Ecological Benchmark Tool for radionuclides dataset serves as a comprehensive repository of benchmarks designed to assess ecological risks at contaminated sites. This tool facilitates the evaluation of various environmental media and contaminants, supporting regulatory compliance and ecological protection. Benchmarks are available for sediment, soil, and surface water. The dataset also provides species-specific benchmarks for fish, plants, birds, mammals, and invertebrates. Users can select benchmark sources, media, individual radionuclides, and retrieve results in tabular or spreadsheet formats for analysis. Benchmarks are derived from authoritative sources, including government agencies, scientific councils, and academic publications. The dataset supports ecological risk assessments, regulatory decision-making, and environmental planning, with tools for benchmarking against radiological thresholds, sensitive species protection, and habitat impact evaluations. This structured approach ensures a robust evaluation of ecological risks tailored to site-specific and regulatory needs.

Stewart, Debra [Oak Ridge National Laboratory (ORN↗

Effective Visualization of Radar Data for Users Impacted by Color Vision Deficiency

Color vision deficiency (CVD) is a decreased ability to discern between particular colors. Eight percent of genetic males and half a percent of genetic females have some form of CVD, with many in the radar community falling into this group. When presenting data on a two-dimensional plane, it is common to use colors to represent values via a colormap. Colormap choice in the radar community is influenced by the ability to highlight scientifically interesting features in data, institutional choices, and domain dominance of legacy colormaps. The problem with these current colormaps is that many do not project well for those with CVD (i.e., green next to red). In working with the CVD community to address this problem, multiple colormaps for moments such as equivalent reflectivity factor and Doppler velocity were created for users with forms of CVD such as deuteranomaly, protanomaly, protanopia, and deuteranopia using Python tools such as colorspacious and viscm. We show how these colormaps can improve interpretability for four cases: a mesoscale convective system, a pyrocumulonimbus storm, a wintertime midlatitude cyclone, and widespread storms with a large bird migration. These new radar equivalent reflectivity factor, Doppler velocity, and polarization colormaps are designed to highlight rain, frozen precipitation, nonmeteorological targets, and velocity-based items, are perceptually uniform, and are visually friendly for those with CVD.

54 ENVIRONMENTAL SCIENCES↗

Delayed access to feed early post-hatch affects the development and maturation of gastrointestinal tract microbiota in broiler chickens

Background: The first two weeks of post-hatch (PH) growth in broilers (meat-type birds) are critical for gut development and microbiota colonization. In the current broiler production system, chicks may not receive feed and water for 24 to 72 h due to variations in hatching time and hatchery management. Post-hatch feed delay affects body weight, feed efficiency, mortality, and gut development. The goal of this study was to investigate changes in the microbiome in broiler chickens early PH and the effect of delayed access to feed on the microbiota. Results: Chicks either received feed and water immediately after hatch or access to feed was delayed for 48 h to mimic commercial hatchery settings (treatment, TRT). Both groups were sampled (n = 6) at -48, 0, 4 h, and 1 (24 h), 2 (48 h), 3 (72 h), 4 (96 h), 6 (144 h), 8 (192 h), 10 (240 h), 12 (288 h) and 14 (336 h) days PH. Ileal (IL) and cecal (CE) epithelial scrapings (mucosal bacteria, M) and digesta (luminal bacteria, L) were collected for microbiota analysis. Microbiota was determined by sequencing the V3-V4 region of bacterial 16S rRNA and analyzed using QIIME2. The microbiota of early ileal and cecal samples were characterized by high abundance of unclassified bacteria. Among four bacterial populations (IL-L, IL-M, CE-L, CE-M), IL-M was the least affected by delayed access to feed early PH. Both alpha and beta diversities were affected by delayed access to feed PH in IL-L, CE-M and CE-L. However, the development effect was more pronounced. In all four bacterial populations, significant changes due to developmental effect (time relative to hatch) was observed in taxonomic composition, with transient changes of bacterial taxa during the first two weeks PH. Delayed access to feed has limited influence on bacterial composition with only a few genera and species affected in all four bacterial populations. Predicted function based on 16S rRNA was also affected by delayed access to feed PH with most changes in metabolic pathway richness observed in IL-L, CE-L and CE-M. Conclusions: These results show transient changes in chicken microbiota biodiversity during the first two weeks PH and indicate that delayed access to feed affects microbiota development. Proper microbiota development could be an important factor in disease prevention and antibiotic use in broiler chickens. Moreover, significant differences in response to delayed access to feed PH between luminal and mucosal bacterial populations strongly suggests the need for separate analysis of these two populations.

16S↗

Supranutrition of microalgal docosahexaenoic acid and calcidiol improved growth performance, tissue lipid profiles, and tibia characteristics of broiler chickens

Abstract Background Docosahexaenoic acid (DHA) and calcidiol could be enriched in chicken for improving public nutrition and health. It remains unclear if supranutritional levels of DHA and calcidiol impair growth performance or metabolism of broiler chickens. This study was to determine singular and combined effects of high levels of supplemental DHA-rich microalgal biomass or oil and calcidiol on growth performance, concentrations of triglycerides, cholesterol, and nonesterfied fatty acids in plasma, liver, breast, and thigh, and biophysical properties of tibia. Methods In Exp. 1, 144 day-old Cornish chicks were divided into 4 groups (6 cages/treatment, 6 birds/cage), and were fed a corn-soybean meal basal diet (BD), BD + 10,000 IU calcidiol/kg (BD + Cal), BD + 1% DHA-rich Aurantiochytrium (1.2 g DHA/kg; BD + DHA), and BD + Cal + DHA for 6 weeks. In Exp. 2, 180 day-old chicks were divided into 5 groups, and were fed: BD, BD + DHA (0.33% to 0.66% oil, 1.5 to 3.0 g DHA/kg), BD + DHA + EPA (1.9% to 3.8% eicosapentaenoic acid-rich Nannochloropsis sp. CO18, 0.3 to 0.6 g EPA/kg), BD + DHA + calcidiol (6000 to 12,000 IU/kg diet), and BD + DHA + EPA + Cal for 6 weeks. Results Birds fed BD + Cal diet in Exp. 1 and BD + DHA + EPA diet in Exp. 2 had higher ( P < 0.05) body weight gain (10%–11%) and gain:feed ratio (7%), and lower ( P < 0.05) total cholesterol and triglyceride concentrations in plasma (18%–54%), liver (8%–26%), breast (19%–26%), and thigh (10%–19%), respectively, over the controls. The two diets also improved ( P < 0.05) tibial breaking strength (8%–24%), total bone volume (2%–13%), and (or) bone mineral density (3%–19%) of chickens. Conclusion Supranutrition of dietary calcidiol and DHA alone or together did not produce adverse effects, but led to moderate improvements of growth performance, lipid profiles of plasma and muscle, and bone properties of broiler chickens.

60 APPLIED LIFE SCIENCES↗

Central-place foraging poses variable constraints year-round in a neotropical migrant

Background: “Central-place foragers” are constrained in their habitat selection and foraging range by the frequency with which they need to return to a central place. For example, chick-rearing songbirds that must feed their offspring hourly might be expected to have smaller foraging ranges compared to non-breeding songbirds that return nightly to a roost. Methods: We used GPS units to compare the foraging behaviour of an aerial insectivorous bird, the purple martin (Progne subis), during the breeding season in three regions across North America, as well as the non-breeding season in South America. Specifically, we tested foraging range size and habitat selection. Results: Foraging range did not vary among regions during breeding (14.0 ± 39.2 km 2 ) and was larger during the nonbreeding period (8840 ± 8150 km 2 ). Purple martins strongly preferred aquatic habitats to other available habitats year-round and in the Amazon commuted from night roosts in low productivity sediment-poor water, where risk of predation was probably low, to daytime foraging sites in productive sediment-rich water sites. Conclusions: We provide the first estimates for foraging range size in purple martins and demonstrate foraging preference for aquatic habitats throughout two stages of the annual cycle. Understanding foraging constraints and habitat of aerial insectivores may help plan conservation actions throughout their annual cycle. Future research should quantify foraging behaviour during the post-breeding period and during migration.

54 ENVIRONMENTAL SCIENCES↗

Comparing western (Megascops kennicottii) and whiskered (M. trichopsis) screech-owl microbiomes in southern Arizona using a novel 16S rRNA sequencing method

Microbiomes are essential to a host’s physiology and health. Despite the overall importance of microbiomes to animal health, they remain understudied in wildlife. Microbiomes function as physical barriers to invading pathogens, and changes in the diversity or composition of microbes within a host may disrupt this barrier. In order to use microbiomes in wildlife ecology, knowledge of the natural variation within and among species is essential. We compare the diversity and composition of two avian species that share the same habitat and niche in our study area, the western screech-owl (Megascops kennicottii) and the whiskered screech-owl (M. trichopsis). We used a targeted 16S sequencing method to improve the taxonomic resolution of microbiomes. We found similar measures of alpha diversity between species and sample types (cloacal samples vs. fecal samples). However, there were significant differences in bacterial species richness among nestlings from different nest boxes, and the composition differed between the two bird species and among nestlings from different nest boxes. Western screech-owls had more variation in alpha diversity and composition and had fewer bacterial species in their core microbiome than whiskered screech-owls. Siblings are likely to yield similar findings for microbiomes; thus, sampling nestlings from different nests may be most informative for monitoring population-level changes.

59 BASIC BIOLOGICAL SCIENCES↗

Observations of marine animal interactions with a small tidal turbine

The risk of collisions between animals and operating tidal turbines remains a concern in the scientific and regulatory communities. A sensor package including optical cameras was deployed to monitor animal interactions with a small-scale (1 m 2 ) cross-flow tidal turbine. The turbine was deployed in Washington State, USA for 141 days at a site with peak flow speeds of 2.5 m/s. We analyze optical camera imagery spanning 109 days of turbine operation. The analyzed images contain 1044 observations of fish, fish schools, seabirds, or seals in the vicinity of the turbine. No instances of collision with seabirds or seals were observed. Seabirds were only observed during daylight hours and while the turbine was stationary. Both seals and fish were observed during both day and night and while the turbine was stationary and rotating. Four fish were observed colliding with the moving turbine and in all but one case the animals swam away following the collision. Over the same period of time, over fifty times more fish (224 individual fish and 5 fish schools) were observed passing the moving turbine without collision. Fish encounters were likely under counted due to the difficulty in discerning small fish from plant matter in the water column. These observations represent the first optical camera imagery showing fish, bird, and marine mammal interactions with a tidal turbine in North America. In addition to quantitative and qualitative discussion of the implications of our observations for collision risk, we discuss lessons learned on sampling schemes and deployment of machine learning for detection of animals to inform future data collection strategies in future monitoring campaigns.

16 TIDAL AND WAVE POWER↗

The Monkeys and Parrots of Gold Rush-era California

As immigrant gold miners migrated en masse to San Francisco and northern California during the Gold Rush-era (ca. 1849–1855), they experienced new animals. Stopping in ports throughout Central and South America, these argonauts saw, felt, smelled, heard, and occasionally consumed, mammals, birds, reptiles, and many more creatures, which were wholly exotic to those species found at home. Two types of animals that the Gold Rush populace encountered during this era include parrots and monkeys. Although found throughout tropical environments in areas far distant from northern California, these animals became quickly imported to San Francisco during the early 1850s. A wild, turbulent Gold Rush-era helped facilitate the importation of these exotic animal types, both for comfort and entertainment, as they helped provide a source of companionship for miners unaccustomed to the shock of 1850s northern California.

59 BASIC BIOLOGICAL SCIENCES↗

AmeriFlux FLUXNET-1F CA-TPD Ontario - Turkey Point Mature Deciduous

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site CA-TPD Ontario - Turkey Point Mature Deciduous. This is the FLUXNET version of the carbon flux data for the site CA-TPD Ontario - Turkey Point Mature Deciduous produced by applying the standard ONEFlux (1F) software. Site Description - The forest is approximately 90 years old. Naturally regenerated on sandy terrain and abandoned agricultural land. Predominantly hardwood species with a few scattered conifers. Site has been managed (thinned) in the past. It has a high biodiversity with 573 tree and plant species, 102 bird species, 23 mamal species and 22 reptile and amphibian species (SWALSREP Report, 1999). The dominant tree species is white oak (Quercus alba), with other scattered broadleaf Carolinian species including sugar and red maple (Acer saccharum, A. rubrum), American beech (Fagus grandifolia), black and red oak (Q. velutina, Q. rubra) and white ash (Fraxinus americana) . There are also scattered conifers, mostly white and red pine (Pinus strobes, P. resinosa), comprising about 5% of the trees. Average tree height is 25.7 m with a stand density of 504 ± 18 trees per hectare. Average tree diameter at breast height is 22.3 cm and basal area is 0.06 m2 or approximately 29 square meters per hectare.

Arain, M. Altaf↗