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Scientific Reports

Scientific Reports: explore 6 source-linked works published from 2025 to 2026, with original documents and citations.

This collection is a preview while coverage and quality are evaluated.

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Includes records with this source-supplied label or an explicit phrase match in their metadata. Matches indicate a mention, not proof that a paper uses a method or tests a material. Source versions are consolidated by DOI.

Sources: usgs. Collection updated 2026-09-15. Counts describe this index, not the complete source archives.

USGS2026

Rewilding the upper Klamath River Basin: Rapid recolonization of Chinook salmon following the world’s largest dam removal

Habitat fragmentation is a global driver of decline in biodiversity, yet evaluations of ecological response following re-connection remain rare. In 2024, four hydroelectric dams on the Klamath River were removed, reconnecting over 640 km of anadromous habitat and marking the largest dam removal project completed to date. We used a stationary high-resolution multi-beam imaging SONAR to quantify adult Chinook salmon ( Oncorhynchus tshawytscha ) passage into newly reopened reaches during the first two migratory seasons following dam removal. An estimated 7,742 (95% CI: 7,702–7,778) Chinook salmon migrated upstream in 2024 and 13,310 (95% CI: 12,876–13,733) in 2025, representing 18–19% of fish returning to the Klamath River Basin. Within this period, Chinook salmon recolonized 88% of their documented historical distribution, expanding into 345 km of reconnected habitats and reaching elevations of up to 1,250 m. Recolonization required fish to swim through dam removal sites, complex hydraulic corridors and engineered fishways, demonstrating the propensity for rapid recolonization at basin scale despite these challenges. These findings provide the first quantitative assessment of salmon response to the world’s largest dam removal and demonstrate how reconnection can catalyze large-scale recolonization in historically fragmented river networks.

California, Oregon↗

USGS2026

Bayesian belief network model to predict human-wildlife conflict in protected areas

Human-wildlife conflict (HWC) poses a pervasive global challenge, affecting livelihoods and threatening biodiversity. To better anticipate and mitigate HWC risk, we developed a large-scale predictive model using a Bayesian Belief Network (BBN). We surveyed 1,011 park rangers across 135 terrestrial protected areas in three Andean countries, documenting recent HWC incidents involving wildlife persecution or killing, livestock depredation, crop damage, or threats to human safety and property. We identified key drivers of HWC risk, including governance, wildlife acceptance, participation, and habitat quality. A sensitivity analysis revealed that enhancing governance and improving wildlife acceptance could reduce HWC risk by > 85%. The BBN model demonstrated scalability, effectively identifying strategies to reduce HWC risk at multiple scales, from individual protected areas to national networks. Our findings highlight the importance of strengthening governance, increasing wildlife acceptance, and enhancing community participation in conservation efforts. BBNs provide a flexible, cost-effective, and data-driven tool to guide protected areas and wildlife managers in monitoring, anticipating, and making informed decisions to mitigate conflict and promote coexistence.

Scientific Reports↗

USGS2026

Influence of new residential construction varying in housing density on bird species, human tolerance guilds, and communities

Human population growth and changing settlement patterns fuel the development of urban fringe lands worldwide, with implications for biodiversity. We conducted a 12-year study of birds in the fast-developing urban fringe lands of the central Puget Sound region, Washington, USA, to examine the effect of development configuration on birds. We hypothesized that lower-intensity conservation developments, compared to higher-intensity planned community developments, would benefit the overall bird community, as well as native forest birds (avoiders of human development) and avian generalist species (adapters to human development), but that higher-intensity planned community developments would benefit synanthropic species (exploiters of human development). We fit single-species and multi-species occupancy models to test these hypotheses. Consistent with our hypotheses, we found that a greater proportion of the overall community, avoiders, and adapters occupied lower-intensity conservation developments compared to higher-intensity planned community developments. However, we did not detect an effect of development type on the exploiter guild, and we found that species in the exploiter guild are variable in their response to the configuration of suburban developments. We also hypothesized that human tolerance guilds would be a useful predictor of individual species responses to development type. This hypothesis was somewhat supported: we found that, for avoiders, 87% of species in the guild had the same response to development type as the overall guild; for adapters, 63% had the same response as the overall guild, and for exploiters, only 44% had the same response as the overall guild. Our results indicate that the configuration of suburban developments can have a meaningful impact on bird communities, particularly on those species that are most sensitive to any level of development.

Washington↗

USGS2026

Per- and polyfluoroalkyl substances in waters associated with oil and gas development in the Denver Basin

Use of per- and polyfluoroalkyl substances (PFAS) in the petroleum industry could be a cause for concern due to the large volumes of produced water (PW) generated during oil and gas extraction, the reuse of these wastes in water-stressed regions, and adverse health outcomes related to PFAS exposures. However, PW PFAS characterization is nearly absent in the literature, and hydraulic fracturing (HF) chemical disclosures often omit the identities of additives as proprietary. Here we evaluate PFAS in PW samples from three petroleum wells in the Denver Basin during their first year of production. Total concentrations of targeted PFAS (Σ 40 PFAS) were < 35 ng/L in PW samples, with short-chain PFAS like perfluorobutanoic acid persisting throughout the sampled duration. Analysis of freshwater inputs for hydraulic fracturing (Σ 40 PFAS ~ 113 ng/L) and mixed fracture fluid (Σ 40 PFAS ~ 69 ng/L) indicated much of the targeted PFAS content was derived from the input water, and not from HF additives, however samples subjected to oxidation indicated the presence of PFAS precursors that would not be detected by targeted analysis. This study highlights that while PFAS content is low in the studied PWs, the potential for redistribution of PFAS in the environment may be a consideration for reuse applications.

Colorado, Nebraska, Wyoming↗

USGS2026

Rapid hydrothermal triggering of induced seismicity at the Coso Geothermal Field

The long-term producing Coso Geothermal Field (CGF) in California operates over 100 wells tapping into a reservoir characterized by an extensive fracture network, complex fluid pathways, and regular seismic activity. Understanding the interaction between seismicity and injection can shed important light on the hydrothermal characteristics of the field. Here, we analyze 15 years of local seismic and daily operational data from the CGF, identifying a strong correlation between short-term increase in seismicity rate and seasonal volumetric and temperature variations in the reinjected fluid. Furthermore, the seismic footprint during peak injection of colder fluids reveals a near-instantaneous response up to 2 km away from the injection well, too rapid for pore pressure diffusion alone. This short-term and distant response is observed to have directional preference, indicating structural or permeability anisotropy within the reservoir. Additionally, the seismic response correlates with the initial volumetric increase of colder fluids, but also with temperature decrease during stable injection periods, suggesting thermal effects alone can play an important role in triggering distant seismicity.

California↗

USGS2025

Modeling seawater intrusion along the Alabama coastline using physical and machine learning models to evaluate the effects of multiscale natural and anthropogenic stresses

Seawater intrusion threatens groundwater resources in coastal regions, including southern Baldwin County, Alabama, where the freshwater-saltwater interface dynamics remain poorly understood. To address this gap, this study uses combined physics-based and machine-learning models to quantify seawater intrusion caused by natural (storm surges) and anthropogenic (human activities) perturbations. The long short-term memory network and wavelet analysis were used to assess vertical aquifer vulnerabilities, revealing that the shallow part of the Coastal lowlands aquifer system (CL1) in the southern Baldwin County region is more susceptible to sea level rise and groundwater extraction than deeper aquifers. Based on these findings, a cross-sectional numerical model (physics approach) for the CL1 aquifer was developed to evaluate tidal and storm surge effects, using Tropical Storm Claudette (June 2021) as a case study. Results showed that tidal fluctuations had a minimal impact on the saltwater-freshwater interface location, whereas storm surges caused substantial inland movement, with effects lasting for nine months. The steady-state version of the three-dimensional (3D) physical model predicted seawater intrusion across the entire area, and convolutional neural network-based modeling further validated the model results. The 3D physical model was also applied to a smaller area to assess human impact on the saltwater interface due to two groundwater pumping scenarios (± 50% of the baseline pumping rate). Results revealed that a 50% increase in groundwater withdrawals caused seawater to advance ~ 320 m inland, whereas a 50% reduction led to a ~ 270-meter retreat. This study highlights the vulnerability of Alabama’s shallow coastal aquifers to seawater intrusion due to storm surges and human activities, and demonstrates that combining physics-based models with machine learning approaches can improve groundwater predictions, though its accuracy depends on the availability of site-specific data.

Alabama↗

Compare source metadata on this page

Work	Published	Source identifier	Source
Rewilding the upper Klamath River Basin: Rapid recolonization of Chinook salmon following the world’s largest dam removal	2026-08-27	70279535	usgs
Bayesian belief network model to predict human-wildlife conflict in protected areas	2026-06-19	70278884	usgs
Influence of new residential construction varying in housing density on bird species, human tolerance guilds, and communities	2026-05-31	70279520	usgs
Per- and polyfluoroalkyl substances in waters associated with oil and gas development in the Denver Basin	2026-02-07	70273904	usgs
Rapid hydrothermal triggering of induced seismicity at the Coso Geothermal Field	2026-02-03	70275362	usgs
Modeling seawater intrusion along the Alabama coastline using physical and machine learning models to evaluate the effects of multiscale natural and anthropogenic stresses	2025-07-01	70270114	usgs

These are bibliographic comparisons, not experimental rankings. Follow the original document for methods and conditions.