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1,669 records · Page 93Linked to original sources
USGS2026

Post-fire soil hydrologic response and recovery in northern California (USA)

Background Wildfires abruptly change landscapes by altering soil properties and vegetation cover. These changes are thought to reduce soil infiltration capacity, making landscapes susceptible to runoff and erosion. However, post-fire soil response is complex and likely varies across locations and time. Aims Here, we aim to understand regional post-fire soil response and recovery by tracking changes across different northern California (USA) lithology and vegetation types. Methods We conducted repeat in situ soil infiltration tests for 3 years post-fire at 31 burned and 10 unburned sites spanning the 2021 Dixie, 2020 LNU Lightning Complex, 2020 Walbridge and 2020 Glass fires. Key results Our two main findings are: (1) burned chaparral soils have increased hydraulic conductivity compared with unburned sites, and (2) infiltration rates return to pre-fire conditions within 3 years across most lithologies and vegetations. Conclusions Recovery might be generalizable by vegetation and lithology but differ regionally, making it important to identify meaningful hydrologic response units (HRUs). Multi-year studies with paired burned and unburned measurements can constrain the recovery timeline and provide information missed by observations solely of burned soils. Implications Understanding where, and for how long, soil remains susceptible to runoff and erosion can help prioritize areas and time periods most in need of mitigation.

California↗
USGS2026

Cotton farming pesticides affect ileal microbiota activity expressions of virulome but not resistome or metabolic pathways in a sedentary wild passerine

The increased use of agrochemicals to enhance crop production has had detrimental environmental effects including implication in the sharp decline of North American farmland-breeding birds. Here, using a combination of deep shotgun metatranscriptomics and pesticide exposure data, we sought to assess whether exposure to cotton ( Gossypium spp.) production had a differential effect on ileum multi-kingdom microbial activity, metabolism, anti-microbial resistance, and virulence factors of sedentary northern mockingbirds ( Mimus polyglottos ) sampled from two cotton-producing areas (16 birds in total) and one uncultivated area (7 birds) in Texas, USA. Both Shannon Index values (Adj. r 2 = 0.174, F (1,21) = 5.633, p = 0.027) and a Mantel test (Spearman ρ = 0.184, p = 0.013) supported a relationship between metabolically active microbiota Bray–Curtis dissimilarities and differences in pesticide mixtures among study areas. Virulence factor richness (Adj. r 2 = 0.182, F (1,21) = 5.890, p = 0.024), Shannon Index (Adj. r 2 = 0.231, F (1,21) = 7.612, p = 0.012), and load (sum of virulence factor abundances; Adj. r 2 = 0.160, F (1,21) = 5.194, p = 0.033) were related to total pesticide load (total quantity of pesticides). We found no pesticide effects on expression of either antimicrobial resistance genes or metabolic pathways.

Texas↗
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↗
USGS2025

A spatiotemporal deep learning approach for predicting daily air-water temperature signal coupling and identification of key watershed physical parameters in a montane watershed

Seasonal shifts from runoff to groundwater dominance influence daily headwater stream temperatures, especially where local groundwater input is strong. This input buffers temperature during hot periods, supporting cold-water habitats. Recent studies use air–water temperature signal metrics to identify zones of strong stream–groundwater connectivity. While Previous studies used air–water signal ratios as proxies for groundwater influence but were limited to specific sites and periods, without dynamic forecasting. This study is the first to forecast daily A r as a spatiotemporal signal using a Graph Convolutional Network–Long Short-Term Memory (GCN-LSTM) model. The model was trained using hydroclimate data (air temperature, precipitation, shortwave radiation, streamflow) and watershed physical features (e.g., sand content, slope). Results showed high predictive skill, achieving R 2 (NSE, RMSE) of 0.86 (0.73, 0.0004) for one-day-ahead to 0.52 (0.50, 0.0009) for seven-days ahead forecasts. Prior studies often have not explicitly incorporated spatial hydrogeologic drivers, but this model explicitly incorporates them to assess their impact on A r forecasting and stream-groundwater connectivity. Feature analysis identified mean sand, elevation, slope, clay, and TWI as key predictors of A r . Stronger groundwater signals appeared in hillslopes, elevations, and tributaries, highlighting watershed influence on streamflow. However, limitations include reliance on historical air–water temperature patterns for training and limited representation of extreme climate conditions. Despite these limitations, unlike previous studies relying on measured in-situ stream and air temperature, this study forecasts A r directly from climate and physiographic features after training, avoiding in-situ data requirements. Findings aiding predictions of stream ecosystem resilience.

New York↗
USGS2025

RioM-1: A new calcite reference material for U-Pb LA-ICP-MS geochronology

Determining absolute ages of carbonate diagenesis, faulting, fossil formation, speleothem growth, carbonate-hosted hydrocarbon deposits, vein mineralisation and hydrothermal alteration has become increasingly accessible through LA-ICP-MS U-Pb dating of calcite, complementing traditional isotope dilution methods still applicable to certain materials (e.g., speleothems via micro-drilling). However, well-calibrated reference materials for LA-ICP-MS calcite geochronology remain scarce. Here, we characterise the Rio Maior calcite, designated ‘RioM-1’, as a potential reference material for U-Pb dating by LA-ICP-MS. Fragments (0.1 to 1 cm 3 ) from a single scalenohedral crystal were analysed by ID-TIMS (U-Pb), LA-ICP-MS (U-Pb and 87 Sr/ 86 Sr), and SIMS (O isotopes). RioM-1 displays high U mass fraction and low, though variable, proportions of common Pb. Combined ID-TIMS analyses from two independent laboratories yielded a Tera-Wasserburg lower intercept date of 63.93 ± 0.11 Ma (2 s , MSWD = 1.3, n = 16). LA-ICP-MS U-Pb data from three independent laboratories are concordant with the TIMS age, producing a pooled date of 64.10 ± 0.12/1.2 Ma (2 s , MSWD = 7.7, n = 708) and an initial 207 Pb/ 206 Pb ratio of 0.85 ± 0.01. Other calcite reference materials, when normalised to RioM-1, yielded dates within uncertainty of their published values. SIMS measurements returned a mean 18 O/ 16 O of 0.002044450 ± 181 (1 s ) and δ 18 O SMOW of 19.57 ± 0.92‰ (1 s ), while LA-ICP-MS strontium isotope measurement yielded a mean 87 Sr/ 86 Sr of 0.708177 ± 9 (2 s ).

Geostandards and Geoanalytical Research↗
USGS2026

Seasonal and hydrologic variation influences habitat and functional structure of stream fish assemblages

Introduction: Hydrologic variability is a key driver of ecological structure in lotic systems, shaping habitat conditions, taxonomic diversity, and the functional traits that mediate species’ persistence and performance (e.g., reproductive success). While many studies examine taxonomic responses to variation in flows, few evaluate how spatiotemporal hydrologic variation influences the functional organization within stream fish communities. Methods: We quantified seasonal habitat structure and functional trait diversity of fish assemblages across six Ozark Plateau headwater streams representing two contrasting flow regimes: Groundwater Flashy and Runoff/Intermittent Flashy. Fish and habitat data were collected seasonally during a dry year (2002) and a wet year (2003). Functional space was constructed using PCoA of morphological, ecological, and life-history traits, and functional diversity was measured using community weighted means (CWMs), functional richness (FRic), functional evenness (FEve), and functional divergence (FDiv). Results: We found that habitat structure differed strongly by flow regime and season, with Runoff/Intermittent streams exhibiting pronounced reductions in depth, area, and velocity, while groundwater streams remained structurally stable. Functional identity of assemblages was similar across flow regimes, dominated by benthic, hydrodynamic taxa with opportunistic and periodic life-history strategies. However, functional structure differed significantly: FEve and FDiv were consistently lower in Runoff/Intermittent Flashy streams in both years, indicating assemblage dominance of species with similar trait combinations and reduced trait partitioning under variable flow. FRic and taxonomic richness remained stable across seasons and flow regimes, suggesting high functional redundancy despite species turnover. Discussion: Together, results show that flow regime mediates both habitat structural stability and functional organization. As climatic warming and extreme drought increase hydrologic instability in headwaters, functional trait approaches provide a sensitive tool for detecting losses of functional roles that may not be evident by using taxonomic metrics alone.

Arkansas, Kansas, Missouri, Oklahoma↗
USGS2026

Advancing outreach effectiveness to improve conservation practice adoption

Agricultural conservation practices are central to achieving Chesapeake Bay watershed restoration goals, yet long-term adoption remains challenging even when practices are technically effective and financial assistance is available. Adoption is not a single decision, but a staged and context-dependent process. Awareness and willingness to commitment, implementation, and persistence, are all important. Progress along this pathway is influenced by interacting factors such as knowledge, attitudes, beliefs, social norms, trust, perceived risk, farm characteristics, and practical constraints. Improving adoption requires outreach strategies that respond to the specific factors limiting progress at each stage rather than relying on a one-size-fits-all approach.

Chesapeake Bay watershed↗
USGS2025

A global database of soil microbial phospholipid fatty acids and enzyme activities

Soil microbes drive ecosystem function and play a critical role in how ecosystems respond to global change. Research surrounding soil microbial communities has rapidly increased in recent decades, and substantial data relating to phospholipid fatty acids (PLFAs) and potential enzyme activity have been collected and analysed. However, studies have mostly been restricted to local and regional scales, and their accuracy and usefulness are limited by the extent of accessible data. Here we aim to improve data availability by collating a global database of soil PLFA and potential enzyme activity measurements from 12,258 georeferenced samples located across all continents, 5.1% of which have not previously been published. The database contains data relating to 113 PLFAs and 26 enzyme activities, and includes metadata such as sampling date, sample depth, and soil pH, total carbon, and total nitrogen. This database will help researchers in conducting both global- and local-scale studies to better understand soil microbial biomass and function.

Scientific Data↗
USGS2025

Improved prediction of postfire debris flows through rainfall anomaly maps

Predicting where runoff-generated debris flows might occur during rainfall on steep, recently burned terrain is challenging. Studies of mass-movement processes in unburned areas indicate that event locations are well-predicted by rainfall anomaly, R* , in which peak observed rainfall is normalized by local rainfall climatology. Here, we use remote and field methods to map debris flows triggered within the 2020 Dolan Fire burn area in coastal California, demonstrate that a short-duration R* metric predicts debris-flow occurrence more effectively than absolute peak intensity or longer-duration rainfall metrics, and show that incorporating an R* criterion into an existing debris-flow likelihood model can reduce false positive predictions and improve accuracy. We test R * at three other climatically distinct fires in California, demonstrating its utility for mapping likely debris-flow locations in different climates. We also consider how R* can benefit postfire debris-flow prediction given recent increases in climatological variability within individual burn perimeters.

Callifornia↗
USGS2025

Preferential groundwater discharges along stream corridors are disregarded sources of greenhouse gases

Groundwater delivery of greenhouse gases (GHGs) to stream banks and riparian areas, before mixing with surface waters, has not been well quantified. We measured preferential groundwater delivery of GHGs to stream banks within three stream reaches, and found that stream banks with discharging groundwater emitted more CO 2 and were sources of N 2 O compared to stream banks without actively discharging groundwater, which emitted less CO 2 and were N 2 O sinks. At one of our stream reaches, groundwater CO 2 and N 2 O concentrations were 1.4–19.2 and 1.1–40.6 times higher than those in surface water, respectively, and groundwater delivery rates of CO 2 and N 2 O were 1.5 and 1.6 times higher than surface water emissions per unit area. On average, 21% (range 0%–100%) of CO 2 and N 2 O were emitted at the stream bank before mixing with surface waters. Preferential groundwater GHG emissions may contribute substantially to stream corridor emissions and may be underestimated when using a channel-centric approach to estimate riverine GHG budgets.

JGR Biogeosciences↗
USGS2025

Detection of viral, bacterial, and protozoan pathogens and microbial source tracking markers in paired large- and small-volume water samples

When sampling for waterborne microbes, researchers may need to diverge from recommended sample volumes due to logistical constraints, novel targets, or challenging matrices, with little guidance about the potential impact on results. In field studies, we measured bacteria, viruses, and protozoa (15 quantitative polymerase chain reaction assays) in paired large- and small-volume samples to evaluate method performance and relevant factors. Concordance between methods was low. Large-volume ultrafiltration yielded more detections than small-volume sampling, especially for pathogens in groundwater. Greater microbial concentrations were associated with more frequent detections in small-volume samples and greater concordance between paired samples. Large-volume samples appeared to be more susceptible to diminished sensitivity from complex sample matrices. In laboratory studies, recovery of microbes was poorer for large- than small-volume methods, although large-volume methods more reliably detected low-concentration targets. Large-volume samples were less stable than small-volume samples during storage. Overall, large-volume sampling was superior for detecting pathogens but may underestimate concentrations; small-volume sampling was more prone to false negatives but was adequate when concentrations were relatively high, like we observed for microbial source tracking in surface waters.

Wisconsin↗
USGS2025

Gaps in water quality modeling of hydrologic systems

This review assesses gaps in water quality modeling, emphasizing opportunities to improve next-generation models that are essential for managing water quality and are integral to meeting goals of scientific and management agencies. In particular, this paper identifies gaps in water quality modeling capabilities that, if addressed, could support assessments, projections, and evaluations of management alternatives to support ecosystem health and human beneficial use of water resources. It covers surface water and groundwater quality modeling, dealing with a broad suite of physical, biogeochemical, and anthropogenic drivers. Modeling capabilities for six constituents (or constituent categories) are explored: water temperature, salinity, nutrients, sediment, geogenic constituents, and contaminants of emerging concern. Each constituent was followed through the coupled atmospheric-hydrologic-human system, with prominent modeling gaps described for a diverse array of relevant inputs, processes, and human activities. Commonly identified modeling gaps primarily fall under three types: (1) model gaps, (2) data gaps, and (3) process understanding gaps. In addition to potential solutions for addressing specific individual modeling limitations, some broad approaches (e.g., enhanced data collection and compilation, machine learning, reduced-complexity modeling) are discussed as ways forward for tackling multiple gaps. This gap analysis establishes a framework of diverse approaches that may support improved process representation, scale, and accuracy of models for a wide range of water quality issues.

Water↗
USGS2026

Non-destructive sampling of larval amphibians shows tail tissues reflect whole-body methylmercury concentrations and trophic-related differences in bioaccumulation

Mercury (Hg), and specifically methylmercury (MeHg), is a contaminant of global concern to humans and wildlife, but there is still limited understanding of its effects on many taxa. Amphibians are closely associated with water, where Hg is converted to MeHg, and high concentrations of MeHg can reduce survival of amphibians in the wild. However, limited non-lethal proxies exist for estimating MeHg bioaccumulation in amphibian larvae, which could be used to reduce destructive sampling and allow sampling of imperiled species. We evaluated whether tail clips were indicative of whole-body MeHg concentrations of larval amphibians, whether dragonflies were an effective bioindicator of Hg concentrations of larval amphibians, and compared MeHg bioaccumulation in predatory caudate (salamanders, newts) and non-predatory anuran (frogs, toads) larvae. Tail-clip and whole-body MeHg concentrations were strongly correlated, especially for caudates. There was high variability among sites and species, but caudates had higher MeHg than anurans, and MeHg concentrations of caudates and anurans were strongly correlated. Dragonflies were a weak indicator of MeHg for anurans but strong indicators for larval caudates, likely because caudates and dragonflies are carnivorous and occupy similar trophic positions. Our study revealed that sampling tails can be an effective non-destructive index of whole-body MeHg for larval amphibians and demonstrates differences in MeHg bioaccumulation related to trophic position in larval amphibians and dragonflies. All post-embryo life stages for a broad suite of amphibian species can now be sampled non-lethally for MeHg, allowing for a broader examination of population-level effects and focus on imperiled species that cannot be sampled destructively.

conterminous United States↗