Search for: All records

Abstract Marine heatwaves (MHWs) are increasing in frequency and intensity globally and are among the greatest threats to marine ecosystems. However, limited studies have characterized subsurface MHWs, particularly in shallow waters. We utilized nearly two decades of full water-column (~ 10 m) observations from a unique automated profiler in central California to characterize, for the first time, the vertical structure of MHWs in a shallow nearshore upwelling system. We found MHWs have similar average durations and intensities across all depths, but there were ~ 17% more bottom MHW days than surface MHW days. Nearly one third of bottom MHWs occurred independently of surface MHWs, indicating that satellites miss a significant fraction of events. MHWs showed distinct seasonality with more frequent and intense events during the fall/winter when weak stratification allowed for MHWs to occupy a larger portion of the water column and persist longer. During summer, strong stratification limited the vertical extent of MHWs, leading to surface- and bottom-trapped events with shorter durations and intensities. Additionally, MHW initiation and termination across depths was consistently linked to anomalously low and high coastal upwelling, respectively. This study highlights the need for expansion of subsurface monitoring of MHWs globally amid a warming planet. 

Abstract Theoretical understanding of the upward vertical motion into the surface layer during coastal upwelling is often based on steady linear Ekman dynamics. In steady linear theory, the divergence of surface transport that leads to upwelling is associated with either overlap of the frictional boundary layers over the inner shelf or wind stress curl farther offshore. However, the alongshore current associated with a coastal upwelling front is associated with relative vorticity which modifies surface transport. A new nonlinear theory shows that, under spatially uniform wind forcing, the fraction of Ekman transport upwelled over the inner shelf tends to decrease with increasing slope Burger numberSas the baroclinic alongshore jet strengthens and cyclonic vorticity increases. Similar patterns are shown in a set of idealized numerical experiments. Unsteadiness in the alongshore flow, neglected in the theory, strongly influences the cross-shelf distribution of upwelling in the numerical model at locations offshore of the inner shelf and near the core of the upwelling jet. The theory and numerical modeling are extended to explore the effect of a large-scale alongshore pressure gradient force (PGF) that forms in response to alongshore variations in wind stress. At highS, a baroclinic PGF is associated with a shallow onshore return flow, but the fraction of modeled upwelling that occurs over the inner shelf is not strongly affected. The results emphasize that the strength and location of the alongshore jet strongly influence the cross-shelf distribution of coastal upwelling in the presence of stratification and a sloping bottom. Significance StatementWind-driven coastal upwelling is important for supplying nutrients to phytoplankton at the base of marine ecosystems. This study uses simple models to investigate factors that determine where upwelling of water into the surface layer occurs when wind blows along the coastline. With a larger difference in density between the surface and bottom layers, a steeply sloping seafloor, and at latitudes closer to the equator, the upwelling region shifts farther offshore because of the strength and location of faster ocean currents that flow along the coastline. 

The relationship between genotype and phenotype remains an outstanding question for organism-level traits because these traits are generallycomplex. The challenge arises from complex traits being determined by a combination of multiple genes (or loci), which leads to an explosion of possible genotype–phenotype mappings. The primary techniques to resolve these mappings are genome/transcriptome-wide association studies, which are limited by their lack of causal inference and statistical power. Here, we develop an approach that combines transcriptional data endowed with causal information and a generative machine learning model designed to strengthen statistical power. Our implementation of the approach—dubbed transcriptome-wide conditional variational autoencoder (TWAVE)—includes a variational autoencoder trained on human transcriptional data, which is incorporated into an optimization framework. Given a trait phenotype, TWAVE generates expression profiles, which we dimensionally reduce by identifying independently varying generalized pathways (eigengenes). We then conduct constrained optimization to find causal gene sets that are the gene perturbations whose measured transcriptomic responses best explain trait phenotype differences. By considering several complex traits, we show that the approach identifies causal genes that cannot be detected by the primary existing techniques. Moreover, the approach identifies complex diseases caused by distinct sets of genes, meaning that the disease is polygenicandexhibits distinct subtypes driven by different genotype–phenotype mappings. We suggest that the approach will enable the design of tailored experiments to identify multigenic targets to address complex diseases. 

See also the Commentary on this article bySalomon & Watts-Williams, 246: 811–813. 

ABSTRACT Fire is a common ecological disturbance that structures terrestrial ecosystems and biological communities. The ability of fires to contribute to ecosystem heterogeneity has been termed pyrodiversity and has been directly linked to biodiversity (i.e., the pyrodiversity–biodiversity hypothesis). Since climate change models predict increases in fire frequency, understanding how fire pyrodiversity influences soil microbes is important for predicting how ecosystems will respond to fire regime changes. Here we tested how fire frequency‐driven changes in burn patterns (i.e., pyrodiversity) influenced soil microbial communities and diversity. We assessed pyrodiversity effects on soil microbes by manipulating fire frequency (annual vs. biennial fires) in a tallgrass prairie restoration and evaluating how changes in burn patterns influenced microbial communities (bacteria and fungi). Annual burns produced more heterogeneous burn patterns (higher pyrodiversity) that were linked to shifts in fungal and bacterial community composition. While fire frequency did not influence microbial (bacteria and fungi) alpha diversity, beta diversity did increase with pyrodiversity. Changes in fungal community composition were not linked to burn patterns, suggesting that pyrodiversity effects on other ecosystem components (e.g., plants and soil characteristics) influenced fungal community dynamics and the greater beta diversity observed in the annually burned plots. Shifts in bacterial community composition were linked to variation in higher severity burn pattern components (grey and white ash), suggesting that thermotolerance contributed to the observed changes in bacterial community composition and lower beta diversity in the biennially burned plots. This demonstrates that fire frequency‐driven increases in pyrodiversity augment biodiversity and may influence productivity in fire‐prone ecosystems. 

Massive scalar fields are promising candidates for addressing many unresolved problems in fundamental physics. We report the first model-agnostic Bayesian search of massive scalar fields that are nonminimally coupled to gravity in LIGO/Virgo/KAGRA gravitational-wave data. We find no evidence for such fields and place the most stringent upper limits on their coupling for scalar masses $\lesssim 2\times {10}^{-12}\mathrm{eV}$. We exemplify the strength of these bounds by applying them to massive scalar-Gauss-Bonnet gravity, finding the tightest constraints on the coupling constant to date, $\sqrt{{\alpha }_{\mathrm{GB}}}\lesssim 1\mathrm{km}$for scalar masses $\lesssim {10}^{-13}\mathrm{eV}$to 90% credible level. Published by the American Physical Society2025 

Abstract This work describes the apparatus for NIST-F4, an updated cesium atomic fountain at the National Institute of Standards and Technology (NIST), and presents an accuracy evaluation of the fountain as a primary frequency standard. The fountain uses optical molasses to laser cool a cloud of cesium atoms and launch it vertically in a fountain geometry. In high-density mode, the fractional frequency stability of NIST-F4 is ${\sigma }_y\left(\tau \right)=1.5\times {10}^{-13}/\sqrt{\tau }$, whereτis the measurement time in seconds. The short-term stability is limited by quantum projection noise and by phase noise from the local oscillator, an oven-controlled crystal oscillator operating at 5 MHz. Systematic frequency shifts and their uncertainties have been evaluated, resulting in a systematic (type B) fractional frequency uncertainty ${\sigma }_{\mathrm{B}}=2.2\times {10}^{-16}$.