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USGS2025

Avian navigation: Comparing the olfactory navigational “map” and the infrasound direction-finding hypotheses to aeronautics

Animal navigation has long been a fascinating but bewildering subject. Humans and animals might well share similar navigational strategies because they developed within the same physical environments. A “map-and-compass” model has been proposed to explain the two-step avian navigational process, but the “map” step has remained elusive. Although scalar values from bicoordinate geomagnetic or atmospheric olfactory gradients have been considered foundational to the avian map, neither has proved convincing engendering decades of controversy. The olfactory map, and an alternative infrasound direction-finding (IDF) hypothesis, are discussed in this review. The olfactory map hypothesis currently requires extensive stable gradients of trace-odor ratios, but such gradients are highly unlikely within a turbulent and rapidly mixed lower atmosphere. The IDF hypothesis, on the other hand, postulates a two-step navigational model analogous to the maritime and aeronautical radio direction-finding technique. This review was also written to encourage further investigation, and direct testing, of the acoustic navigational process. The IDF hypothesis, at present, appears the better explanation of observed avian navigational behavior and accuracy within the atmosphere’s physical environment.

Journal of Comparative Physiology A↗
USGS2025

Divide and conquer: Separating the two probabilities in seismic phase picking

There are two fundamental probabilities in the seismic phase picking process – the probability of the existence of a seismic phase (detection probability) and the probability of correctly identifying the phase arrival time (timing probability). The nearly ubiquitous approach in developing deep learning phase picking models is to use a kernel, such as a truncated Gaussian, to mask the labeled phase arrival time, and train a segmentation model. Once a model is trained, the times of the peaks in the output are taken as phase arrival times (picks) and the height of the peaks are taken as “probability” of the picks. Here, we show that this “probability” represents neither the detection nor the timing probabilty because this approach forces the output to follow the shape of the kernel. We introduce an approach using two models to estimate these two distinct probabilities. We use a binary classifier with a calibrated confidence to address the detection probability and a multi-class classifier to obtain a probability mass function to address the timing probability. This new approach makes the deep learning-based phase picking process more interpretable and gives us options to logically control seismic monitoring workflows.

Geophysical Journal International↗
USGS2025

Land application of drill waste: A scope analysis

Drilling fluid waste land application, a process where drilling wastes are spread and tilled into the land surface, has become common in some petroleum-producing states, however, the potential benefits and risks of this practice are not well studied. Drilling fluids can be water- or oil-based and can have high concentrations of total soluble salts and total petroleum hydrocarbons. Comprehensive chemical characterization of these fluids is not well documented in the literature, and the extent of land application is largely unknown. We hypothesized that the land application of drill waste would fluctuate over time due to economic factors. To begin to understand the extent of historical and potential future land application, we analyzed data from over 5,800 drilling fluid land application permits collected by the Oklahoma Corporation Commission for years 2000, 2005, 2010, and 2015–2020. During the years studied, drilling fluid wastes were applied to more than 250,000 acres in Oklahoma, with over 54,000 thousand barrels (Mbbl) of liquids and nearly 21,000 Mbbl of solids applied. Land application is widespread (occurring in 59/77 counties), however recent drilling activity, land availability, and the economics of transportation have created conditions favorable for land application specifically in the Anadarko Basin. Land application can co-occur with sensitive areas, such as important groundwater and surface-water drinking sources and agricultural fields used for subsistence or feed crop production. Our approach for quantifying the extent of land application, along with further chemical characterization studies, can aid operators and land managers who are considering this practice in assessing the associated benefits and risks.

Oklahoma↗
USGS2025

Impact of gas/liquid phase change of CO2 during injection for sequestration

CO 2 sequestration in deep saline formations is an effective and important process to control the rapid rise in CO 2 emissions. The process of injecting CO 2 requires reliable predictions of the stress in the formation and the fluid pressure distributions – particularly since monitoring of the CO 2 migration is difficult – to mitigate leakage, prevent induced seismicity, and analyze wellbore stability. A key aspect of CO 2 is the gas–liquid phase transition at the temperatures and pressures of relevance to leakage and sequestration, which has been recognized as being critical for accurate predictions but has been challenging to model without ad hoc empiricisms. This paper presents a robust multiphase thermodynamics-based poromechanics model to capture the complex phase transition behavior of CO 2 and predict the stress and pressure distribution under super- and sub- critical conditions during the injection process. A finite element implementation of the model is applied to analyze the behavior of a multiphase porous system with CO 2 as it displaces the fluid brine phase. We find that if CO 2 undergoes a phase transition in the geologic reservoir, the spatial variation of the density is significantly affected, and the migration mobility of CO 2 decreases in the reservoir. A key feature of our approach is that we do not a priori assume the location of the CO 2 gas/liquid interface – or even if it occurs at all – but rather, this is a prediction of the model, along with the spatial variation of the phase of CO 2 and the change of the saturation profile due to the phase change.

Journal of the Mechanics and Physics of Solids↗
USGS2000

Storm impact scale for barrier islands

A new scale is proposed that categorizes impacts to natural barrier islands resulting from tropical and extra-tropical storms. The proposed scale is fundamentally different than existing storm-related scales in that the coupling between forcing processes and the geometry of the coast is explicitly included. Four regimes, representing different levels of impact, are defined. Within each regime, patterns and relative magnitudes of net erosion and accretion are argued to be unique. The borders between regimes represent thresholds defining where processes and magnitudes of impacts change dramatically. Impact level 1 is the 'swash' regime describing a storm where runup is confined to the foreshore. The foreshore typically erodes during the storm and recovers following the storm; hence, there is no net change. Impact level 2 is the 'collision' regime describing a storm where the wave runup exceeds the threshold of the base of the foredune ridge. Swash impacts the dune forcing net erosion. Impact level 3 is the 'overwash' regime describing a storm where wave runup overtops the berm or, if present, the foredune ridge. The associated net landward sand transport contributes to net migration of the barrier landward. Impact level 4 is the 'inundation' regime describing a storm where the storm surge is sufficient to completely and continuously submerge the barrier island. Sand undergoes net landward transport over the barrier island; limited evidence suggests the quantities and distance of transport are much greater than what occurs during the 'overwash' regime.

Journal of Coastal Research↗
USGS2024

Field evidence and indicators of rockfall fragmentation and implications for mobility

Rockfall fragmentation can play an important role in hazard studies and the design of protective measures. However, the current lack of modeling tools that incorporate rock fragmentation mechanics is a limitation to enhancing studies and design. This research investigates the fragmentation patterns of rockfalls and analyzes the resulting distribution of fragment sizes within corresponding rockfall deposits. We focus on small rock fragments, which provide insights into the dynamics of the rockfall event and can be used as input for numerical modeling. We analyzed multiple rockfall events from locations worldwide, each exhibiting different degrees of fragmentation. Using image analysis techniques, we mapped all visible blocks, determined their volumes, and measured the distances they travelled from the initial point of impact. A key finding is the identification of three indicators of fragmentation. First, in cases where fragmentation was largely absent, we observed a trend of increasing block size with distance from the impact point or source area, which aligns with previously published findings. However, for energetic rockfall events characterized by intense fragmentation, we observed that small fragments exhibited longer travel distances compared to larger fragments. This distinction allowed us to differentiate blocks primarily resulting from the disaggregation process from those primarily resulting from dynamic fragmentation, with implications for rockfall mobility. Second, although the size distribution of rockfall deposits exhibits a power-law scaling for volumes larger than a minimum size threshold corresponding to a rollover of the distribution, in some case studies a deviation from power-law scaling is observed, indicating a process of larger block comminution due to fragmentation. Third, we found that rockfalls with fragmentation experience reduced mobility, indicated by higher reach angles, and higher lateral dispersion showing a wider distribution of trajectories. We interpret these findings as being directly related to the energy-consuming nature of fragmentation, which prevents farther deposition of fragmented rock blocks.

Albacete province, Lombardy and Aosta Valley, Yose↗
USGS2026

Nonstationary demographic state-space models using unreplicated counts for species undergoing environmental stressors

A fundamental task in ecological statistics is to estimate abundance and growth rate distributions from wildlife monitoring data to inform conservation management. Modeling time series of wildlife populations presents a number of challenges from both statistical and ecological perspectives, including discreteness; lack of replication; nonstationarity; and observation, demographic, and other phenomenological processes. Nonstationary dynamics are often exhibited by populations undergoing environmental stressors. Models must account for these characteristics to produce reliable estimates of abundance and trends, yet estimation can be challenging with unreplicated data. We propose nonstationary demographic state-space models using unreplicated counts for populations undergoing environmental stressors. A reduced growth rate model matches the complexity of the unreplicated count data, and a fecundity bound on growth rate distributions allows the separation of processes affecting growth rates like environmental stressors from those affecting abundance external to growth rates like migration. NDSSMs allow for the embedding of nonstationary model components, and we explore the use of changepoints, volatility clustering, and migration processes. We apply the proposed nonstationary models in case studies of herons affected by predator/competitor reestablishment and three bat species affected by a fungal pathogen causing white-nose syndrome. Nonstationary models outperform stationary models and generalized linear mixed effects models according to model scoring and visual inspection of predictions, and provide estimates more consistent with published values. Incorporating migration improves model fit universally, even with approximate one-way immigration, most likely because populations are extirpated, recolonized, and increase multiple-fold over the upper bound set by species fecundity. In addition, estimates of the timing and severity of the environmental stressor differed for models with migration. Including nonstationary and demographic components in a fecundity-bounded growth rate model improves inference and benefits interpretability of hyperparameters. In turn, this adjusts uncertainties in predictions of abundance and growth rates over time, providing the ingredients needed for informed conservation analysis and for directing future monitoring of at-risk species.

Journal of Agricultural, Biological and Environmen↗
USGS2026

Remote compositional analyses of space-weathered lunar maria

Visible-to-shortwave infrared (VSWIR) reflectance spectroscopy has revolutionized our understanding of planetary surface compositions. However, space-weathering processes on airless bodies complicate quantitative compositional analyses. Here, we present a framework to isolate the signatures of space weathering in VSWIR spectra of lunar maria by leveraging radiative transfer modeling under the assumptions that (i) a space-weathered target can be expressed as a mixture of fresh and fully space-weathered components and (ii) remaining signatures can be modeled by including agglutinates as an end-member component. We first validate this approach against laboratory spectra of space-weathered Apollo mare soils of known mineral compositions using a probabilistic Markov Chain Monte Carlo implementation of the Hapke radiative transfer model. Second, we illustrate how this approach can be applied to orbital Moon Mineralogy Mapper data. The proposed space-weathering correction workflow for lunar maria could be expanded to other lunar lithologies and applied to existing and future data sets.

Planetary Science Journal↗
USGS2026

HyFlood: A surrogate-model-based framework for compound coastal flooding

Compound coastal flooding is a major threat to low-lying coastal regions and is expected to intensify under future climate change projections. However, modeling the joint interaction of waves, storm surge, tides, and rainfall remains computationally demanding, limiting the development of fast and reliable forecast tools. Here we present HyFlood, a hybrid statistical-numerical downscaling framework capable of computing and mapping high-resolution compound flood hazards while substantially reducing the computational cost compared with fully process-based hydrodynamic modeling. HyFlood combines statistical sampling and selection algorithms with a cascade of reduced-complexity surrogate models that emulate nearshore wave transformation, surf-zone hydrodynamics, and coastal, fluvial, and pluvial flooding. The surrogate models employ machine-learning and regression algorithms applied to a low-dimensional representation of the flooding outputs, obtained through statistical dimensionality reduction. The framework is demonstrated in southern O'ahu, Hawai'i, a region exposed to elevated sea levels driven by tides, waves, and storm surge along with frequent precipitation-driven flash flooding. Validation of the surrogates against the physics-based model outputs demonstrates that HyFlood accurately reproduces daily maxima of spatially distributed flooding depths. This hybrid approach offers a scalable and efficient tool to better quantify how changes in flooding drivers translate into hazard and impact assessments, and to support compound-flood risk assessments and climate-change adaptation planning.

Hawaii↗
USGS2026

Deep subsurface organic-rich shale supports abundant, diverse, and novel fungi

As Earth’s principal reservoir of organic carbon and microbial biomass, the deep subsurface hosts microorganisms capable of mobilizing this once-sequestered carbon. Contrary to standard assumptions of eukaryotic scarcity, this study documents abundant fungal communities, ranging from 4.2 × 10 3 to 6.8 × 10 3 fungal cells mL −1 , across a methane-producing organic-rich shale 247–556 meters below the surface. Although fungal:bacterial cell ratios ranged from 1:7028 to 1:713, application of biomass conversion factors developed for oceanic systems yielded a median fungal:bacterial biomass ratio of 1:4.7. 16S rRNA gene amplicons revealed bacterial and archaeal communities mirroring those found in well-characterized extremophilic, carbon-degrading environments, while sequencing of 18S rRNA gene and ITS rRNA spacer amplicons collectively identified a eukaryotic hotspot with 689 fungal OTUs across six phyla. The dominant fungal classes, Agaricomycetes and Dothideomycetes, are well-established degraders of recalcitrant carbon compounds at the surface, suggesting they may similarly contribute to organic matter degradation and ecosystem maintenance in the subsurface. Cultivation and isolation efforts yielded 205 fungal strains, including 13 candidate novel taxa, underscoring the deep subsurface as an underexplored eukaryotic habitat. Stable carbon isotopes indicate methane is predominantly generated via microbial conversion of the fossil carbon, while water isotopes suggest in situ geochemical conditions have been relatively stable since the Late Pleistocene, with subglacial recharge as a plausible mechanism for microbial introduction. Collectively, these findings suggest that fungi are underrecognized contributors to organic matter transformation and functional diversity in the deep biosphere, revealing a critical gap in our understanding of deep subsurface ecosystem processes.

Indiana, Michigan, Ohio↗
USGS2026

Upper Triassic igneous rocks of the southern Kenai Peninsula, Alaska – Prelude to Early Jurassic subduction along the western Wrangellia composite terrane margin

New U–Pb zircon geochronology identifies a latest Triassic (ca 214–201 Ma) igneous suite of tuff, hypabyssal dikes, and a pluton on the southern Kenai Peninsula, Alaska. The igneous suite was emplaced within Upper Triassic sedimentary rocks along the southern margin of Western Wrangellia, the western-most fragment of the Wrangellia composite terrane. The igneous rocks range from mafic (50.6% SiO 2 ) to felsic (78.3% SiO 2 ), characteristically have less than 1.55% K 2 O, and generally have low trace element abundances. The tonalitic and trondhjemitic magmas were largely sourced in mafic-rich lower crust and incompletely assimilated quartz and other mineral xenocrysts are common. Fractionation involving plagioclase and amphibole is indicated for some magmas and composite intrusions and igneous xenoliths indicate magma mixing was possible. Paleozoic and Precambrian inherited zircons and initial 87 Sr/ 86 Sr (0.704103–0.705609) and 143 Nd/ 144 Nd (0.512396–0.512777) ratios indicate that the Western Wrangellia crustal sources are heterogeneous and contain sialic components. The latest Triassic magmatism reflects processes that preceded Early Jurassic subduction along the Wrangellia composite terrane and Pacific Ocean plate boundary. These processes involved heating and melting of mantle lithosphere and lower crust as mantle instabilities accompanied the breaking of the plate boundary linkages. The Late Triassic transition to subduction along the Wrangellia composite terrane margin coincided with the transition to subduction cessation in the Late Triassic arcs of the western Intermontane terranes of Canada. The shift to subduction along the outboard Wrangellia composite terrane margin marks the beginning of the Pacific Ocean–Cordillera plate interactions that came to dominate the tectonic evolution of the northern Cordillera from the Early Jurassic to today.

Alaska↗
USGS2025

Rare earth element-mineralized carbonatite in the Bear Lodge Alkaline Complex, USA—Ore genesis implications from fluid inclusion characterization

Rare earth element (REE) resources of the Bear Lodge Alkaline Complex, Wyoming, are hosted in variably leached carbonatite spatially related to diatreme breccia pipes. We investigated the genesis of REE and lesser-known gold resources through fluid inclusion analysis of carbonatite, fluorite breccia, and smoky quartz vein samples. Physicochemical characteristics of inclusion-trapped fluids were evaluated using petrography, microthermometry, Raman spectroscopy, decrepitate mound analysis, energy-dispersive spectroscopy, laser ablation inductively coupled plasma mass spectrometry, and noble gas isotope analysis. Microthermometry results reveal three fluid types that affected carbonatite dikes within deeper zones that escaped near-surface, ore-grade REE enrichment: (1) high-temperature (330–432°C) magmatic fluid captured in fine-grained calcite; (2) REE-enriched alkali bicarbonate-sulfate brine; and (3) low-temperature (117–182°C) diluted magmatic or meteoric water. Multiphase brine-like inclusions contain burbankite, nahcolite, strontianite, celestine and alkali sulfate daughter crystals, linking them to early burbankite mineralization. Peripheral smoky quartz and fluorite occurrences at Smith Ridge, 1.5 km from the central carbonatite dike swarm, contain primary inclusions that are Cl-poor and rich in Na-HCO 3 -SO 4 , similar to secondary and pseudosecondary inclusions in carbonatites. Helium isotopes reveal a MORB-like source for carbonatite samples and an older crust signature at Smith Ridge, consistent with the proximal ridge-top exposures of Archean granite. Results from this fluid inclusion study coupled with previous studies of carbonatite mineral paragenesis, show that light REEs (LREEs) were not mobilized great distances. Instead, burbankite crystallized within carbonatite from alkali bicarbonate fluids. With sodium retained in early burbankite, outward-emanating fluids enriched in potassium relative to sodium (higher K:Na) resulted in potassium–ferric iron metasomatism of silicate host rocks. This alkali fractionation was accompanied by fractionation of LREEs and heavy REEs (HREEs), with LREEs dominating the central carbonatite resources. In contrast, areas of peripheral REE mineralization at Bear Lodge are commonly characterized by higher HREE:LREE ratios. The K:Na ratio of associated fenites or alteration assemblages could be indicative of early crystallized burbankite in carbonatites and REE fractionation processes potentially leading to areas of concentrated HREEs with greater supply vulnerabilities.

South Dakota, Wyoming↗
USGS2025

Per- and polyfluoroalkyl substances (PFAS) mass flux and mass balance at an aqueous film-forming foam release site in semiarid eastern New Mexico, USA

Passive flux meters (PFMs) directly measure groundwater chemistry mass flux and Darcy flux, providing insight into contaminant source-zone architecture and transport properties. This study uses PFMs to characterize PFAS flux in groundwater at a semiarid site with a thick (greater than 90-m) unsaturated zone where groundwater has been contaminated with per - and polyfluoroalkyl substances (PFAS) related to the use of aqueous film-forming foam (AFFF) for fire training and fire suppression. PFAS mass discharge (PFAS mass flux integrated over a control plane) in groundwater downgradient from several PFAS release areas is calculated using PFM results. In groundwater downgradient from fire-training areas, total PFAS mass discharge (summed across 14 compounds) was estimated to be between 6.0 and 31 g per day in 2020 and between 5.9 and 23 g per day in 2021. Site-specific documentation, generic information on AFFF properties, and literature values of PFAS concentration in AFFF are used to estimate site-specific PFAS-application rates at fire-training areas. These PFAS-application rates are compared to groundwater PFAS-discharge rates. Results suggest that transformation processes (exact pathways unknown) have led to increased discharge of measured PFAS in groundwater relative to initial AFFF formulations. The mass balance approach has broad applicability as a high-level approach that can provide insight into PFAS transport at AFFF sites.

New Mexico↗
USGS2026

Subsurface water ice mapping on Mars: A probabilistic approach

Subsurface water ice deposits on Mars are an important resource for potential future human exploration. They are also an indicator of the planet’s past climate. However, the distribution of subsurface water ice in Mars’s midlatitudes is uncertain because spacecraft imagery cannot directly observe subsurface ice in most cases. Various spacecraft remote sensing instruments are sensitive to subsurface water ice, including thermal imaging spectrometers, radar sounders, and neutron spectrometers. Geomorphic analyses of images can also implicate subsurface ice. Building upon the data products from the Mars Subsurface Water Ice Mapping project, we provide a probabilistic framework to jointly interpret existing data and estimate the likelihood of subsurface water ice in the Martian midlatitudes between 60 ∘ S and 60 ∘ N with uncertainty. Broadly, we find that near-surface ice is likely present poleward of ∼45 ∘ in both the northern and southern hemispheres. However, closer to the equator, existing remote sensing data cannot uniquely constrain the presence of subsurface water ice. Our probabilistic results provide a framework for quantifying the abundance of ice on Mars, and our uncertainty estimates allow future analysis and exploration to target regions of high uncertainty.

Planetary Science Journal↗
USGS2026

Keeping pace: Migrating sea lampreys adjust swim speed in response to shifting water velocity to maintain a constant ground speed

Upstream migrating fish must balance energetic costs with environmental and ecological constraints. Theoretical models predict that fish can conserve energy by adjusting swim speed in response to changing water velocity, but detailed field tests of these predictions remain rare. We used fine-scale acoustic telemetry and hydrodynamic modeling to track adult sea lamprey (Petromyzon marinus) migrating through a river and evaluated how movement speeds varied with environmental conditions and individual traits. Swim speed increased with faster water velocities, while ground speed remained constant, supporting the hypothesis that lampreys regulate swim effort to maintain a fixed migration pace. The average ground speed aligned with a predicted optimum of ∼1 body length per second. Both swim and ground speeds declined slightly in deeper water, suggesting a trade-off between movement efficiency and predator avoidance. These findings provide field-based support for a theoretical model of energy optimization and underscore how migratory fish adaptively adjust behavior to local hydrodynamic conditions. Our results highlight the value of using high-resolution tracking and environmental modeling to reveal behavioral tactics that underlie efficient migration strategies.

Michigan↗
USGS2026

Long-term monotonic trends in water budget components in the contiguous United States: Insights from two hydrologic models

Characterizing changes to water availability for domestic, industrial, agricultural, and other uses is essential to support water management. To better quantify these changes, the U.S. Geological Survey and National Science Foundation National Center for Atmospheric Research produced two hydrologic models simulating water budget components from 1980 to 2021 over the contiguous United States (CONUS). Both hydrologic models were driven by a common atmospheric forcing dataset and aggregated to common spatial and temporal scales, which enables a novel evaluation of congruency between the models. We present annual and seasonal trends in six water budget components (precipitation, evapotranspiration, streamflow, groundwater recharge, soil saturation, and snow water equivalent) based on the Mann–Kendall test for monotonic trend and Theil-Sen slope estimate for the water year 1983–2021 period for ~86,000 catchments in CONUS. Additional components and metrics from our analysis pipeline are available in an associated published dataset, which contains more than 46 million trend results. The water budget trends showed broad agreement with prior observational and modeling studies that indicate increasing trends in the northeast and decreasing trends in southwestern CONUS. We found the seasonal variability in water budget trends was greatest in the southern, central, and northwest CONUS. These findings support integrated trend assessments when coupled with trends in water quality and use.

Contiguous United States↗
USGS2025

Manipulation of the Symbiodiniaceae microbiome confers multigenerational impacts on symbioses and reproductive ecology of its Exaiptasia diaphana host

Symbiodiniaceae-associated microbiota strongly influence cnidarian symbioses. We systematically reduced the bacterial and fungal communities associated with Symbiodiniaceae to study potential effects on the cnidarian holobiont Exaiptasia diaphana (Aiptasia). Clonal anemones were inoculated with xenic Breviolum minutum (SSB01) and microbiome-manipulated cultures after antibacterial or antifungal treatment. The asexual reproduction of pedal laceration allowed for three generations of clonal aposymbiotic Aiptasia to be utilised in this study, from the initial adult generation (G0), to the first (G1), and second (G2) generation. We inoculated small and large G1 Aiptasia with SSB01 algae and monitored onset of symbiosis, rate of algal proliferation, and holobiont characteristics. Sequencing the 16S and 18S rRNA gene regions identified significant differences in the bacterial and fungal communities of the G0 and G1 generations, alongside differences between the size classes of small and large G1 anemones. The microbiome of larger G1 individuals was distinct to the smaller G1 anemones, suggesting a microbiome maturation process. Control Breviolum minutum cultures exhibited a significantly greater proliferation rate in large G1 anemones when compared to antibacterial or antifungal treated cultures, whereas the opposite trend was documented in the small G1 anemones. Although no differences were observed between algal photochemical parameters, or the growth and polyp activity of G1 juveniles, we observed a significant influence in the production of G2 clones between treatments. Overall, we provide strong ecological implications of manipulating Symbiodiniaceae microbiome, not for the algae themselves, but for the maturation of the host Aiptasia, as well as for the cnidarian holobiont over multiple generations.

The ISME Journal↗
USGS2025

Laboratory assessment for recovery of porcine circovirus 2 and porcine reproductive and respiratory syndrome virus using two types of commercially available hollow-fiber ultrafilters

Groundwater near swine farms is an uninvestigated reservoir for porcine reproductive and respiratory syndrome virus (PRRSV) and porcine circoviruses (PCVs). Enteric microorganisms are often collected from groundwater via dead-end ultrafiltration, but recovery of PRRSV and PCV with this method has not been assessed. We recovered PRRSV2 and PCV2 by dead-end ultrafiltration followed by polyethylene glycol (PEG) precipitation, nucleic acid extraction, and reverse-transcription quantitative real-time PCR. We also compared 2 commercial hemodialysis ultrafilters (Asahi Kasei Rexeed-25A, Nipro Elisio-25H) and compared PRRSV2 recovery in these filters to other waterborne microorganisms. On average, 8 ± 1% of PRRSV2 was recovered by dead-end ultrafiltration and PEG precipitation, compared to 25 ± 6% for adenovirus 41. Full-process recovery of bacteria in the same filters was 5–15%; Cryptosporidium parvum recovery was 42 ± 12%. PCV2 was detected in 4 of 12 replicate filters, but low stock concentrations precluded quantitative recovery estimates. Elisio-25H ultrafilters performed similarly to Rexeed-25A filters for all organisms tested and is an effective replacement for the Rexeed-25A, which is no longer available in the United States. Our recovery of PRRSV2 and PCV2 by dead-end ultrafiltration in the laboratory suggests that PRRSV2 detection limits are as low as 3–50 genomic copies/L in sample volumes of 100–1,500 L. Based on quantitative microbial risk assessment, these concentrations are relevant to PRRSV2 infection rates in the U.S. swine herd.

Journal of Veterinary Diagnostic Investigation↗