Explore the vast range of titles available.

Space-borne Synthetic Aperture Radar (SAR) Interferometry (InSAR) is now a key geophysical tool for surface deformation studies. The European Commission’s Sentinel-1 Constellation began acquiring data systematically in late 2014. The data, which are free and open access, have global coverage at moderate resolution with a 6 or 12-day revisit, enabling researchers to investigate large-scale surface deformation systematically through time. However, full exploitation of the potential of Sentinel-1 requires specific processing approaches as well as the efficient use of modern computing and data storage facilities. Here we present Looking Into Continents from Space with Synthetic Aperture Radar (LiCSAR), an operational system built for large-scale interferometric processing of Sentinel-1 data. LiCSAR is designed to automatically produce geocoded wrapped and unwrapped interferograms and coherence estimates, for large regions, at 0.001° resolution (WGS-84 coordinate system). The products are continuously updated at a frequency depending on prioritised regions (monthly, weekly or live update strategy). The products are open and freely accessible and downloadable through an online portal. We describe the algorithms, processing, and storage solutions implemented in LiCSAR, and show several case studies that use LiCSAR products to measure tectonic and volcanic deformation. We aim to accelerate the uptake of InSAR data by researchers as well as non-expert users by mass producing interferograms and derived products.

Adaptation in new environments depends on the amount of genetic variation available for evolution, and the efficacy by which natural selection discriminates among this variation. However, whether some ecological factors reveal more genetic variation, or impose stronger selection pressures than others, is typically not known. Here, we apply the enzyme kinetic theory to show that rising global temperatures are predicted to intensify natural selection throughout the genome by increasing the effects of DNA sequence variation on protein stability. We test this prediction by (i) estimating temperature-dependent fitness effects of induced mutations in seed beetles adapted to ancestral or elevated temperature, and (ii) calculate 100 paired selection estimates on mutations in benign versus stressful environments from unicellular and multicellular organisms. Environmental stress per se did not increase mean selection on de novo mutation, suggesting that the cost of adaptation does not generally increase in new ecological settings to which the organism is maladapted. However, elevated temperature increased the mean strength of selection on genome-wide polymorphism, signified by increases in both mutation load and mutational variance in fitness. These results have important implications for genetic diversity gradients and the rate and repeatability of evolution under climate change.

Earthquakes are caused by the release of tectonic strain accumulated between events. Recent advances in satellite geodesy mean we can now measure this interseismic strain accumulation with a high degree of accuracy. But it remains unclear how to interpret short-term geodetic observations, measured over decades, when estimating the seismic hazard of faults accumulating strain over centuries. Here, we show that strain accumulation rates calculated from geodetic measurements around a major transform fault are constant for its entire 250-year interseismic period, except in the ~10 years following an earthquake. The shear strain rate history requires a weak fault zone embedded within a strong lower crust with viscosity greater than ~10 20  Pa s. The results support the notion that short-term geodetic observations can directly contribute to long-term seismic hazard assessment and suggest that lower-crustal viscosities derived from postseismic studies are not representative of the lower crust at all spatial and temporal scales. Accumulation of interseismic strain may now be constrained by satellite observations. Here, the authors show that strain accumulation rates on the North Anatolian Fault are constant for the interseismic period indicating that lower-crustal viscosities from postseismic studies are not representative.

We present a novel algorithm for scheduling the observations of time-domain imaging surveys. Our integer linear programming approach optimizes an observing plan for an entire night by assigning targets to temporal blocks, enabling strict control of the number of exposures obtained per field and minimizing filter changes. A subsequent optimization step minimizes slew times between each observation. Our optimization metric self-consistently weights contributions from time-varying airmass, seeing, and sky brightness to maximize the transient discovery rate. We describe the implementation of this algorithm on the surveys of the Zwicky Transient Facility and present its on-sky performance.

We present average ground‐surface velocities and strain rates for the 1.7 million km2 area of Iran, from the joint inversion of InSAR‐derived displacements and GNSS data. We generate interferograms from 7 years of Sentinel‐1 radar acquisitions, correct for tropospheric noise using the GACOS system, estimate average velocities using LiCSBAS time‐series analysis, tie this into a Eurasia‐fixed reference frame, and perform a decomposition to estimate East and Vertical velocities at 500 m spacing. Our InSAR‐GNSS velocity fields reveal predominantly diffuse crustal deformation, with localized interseismic strain accumulation along the North Tabriz, Main Kopet Dagh, Main Recent, Sharoud, and Doruneh faults. We observe signals associated with recent groundwater subsidence, co‐ and postseismic deformation, active salt diaprism, and sediment motion. We derive high‐resolution strain rate estimates on a country‐ and fault‐scale, and discuss the difficulties of mapping diffuse strain rates in areas with abundant non‐tectonic and anthropogenic signals. Plain Language Summary Across the entire country of Iran, the ongoing convergence of the Arabian and Eurasian tectonic plates at about two cm every year is deforming the Earth's crust, producing earthquakes in this process of continental collision. Accurate measurements of how the ground is moving today are critical to understanding both the county‐scale deformation, and the local‐scale earthquake hazard, where the crust is deforming quickly and building up strain that is likely to be released in future major earthquakes. We combine multiple series of satellite radar images with GPS velocities to estimate East and vertical ground motion across all of Iran, at a higher level of detail than previous GPS‐only studies have been able to capture. Our velocity fields show a complex mix of ground motion signals, from crustal deformation on a country‐scale, to rapid land subsidence caused by the extraction of groundwater from aquifers. Some of the major faults are clearly building up strain for future earthquakes, but other regions are deforming much more diffusely, making it difficult to ascertain the locations of any future seismic hazard and ground shaking. Key Points We generate high‐resolution East and vertical velocity fields for Iran using Sentinel‐1 InSAR and GNSS observations Regional deformation is diffuse, with interseismic strain localized onto the Doruneh, Main Kopet Dagh, North Tabriz, and Sharoud faults Iran contains a wealth of time‐varying, short‐wavelength signals associated with groundwater extraction, salt diaprism, and sediment motion

The ability to rapidly access optical satellite imagery is now an intrinsic component of managing the disaster response that follows a major earthquake. These images provide synoptic data on the impacts, extent, and intensity of damage, which is essential for mitigating further losses by feeding into the response coordination. However, whilst the efficiency of the response can be hampered when cloud cover limits image availability, spatio-temporal variations in cloud cover have never been considered as part of the design of effective disaster mapping. Here we show how annual variations in cloud cover may affect our capacity to respond rapidly throughout the year and consequently contribute to overall earthquake risk. We find that on a global scale when accounting for cloud, the worst time of year for an earthquake disaster is between June and August. During these months, 40% of the global population at risk from earthquakes are obscured from optical satellite view for >3 consecutive days. Southeastern Asia is particularly strongly affected, accounting for the majority of the population at risk from earthquakes that could be obscured by cloud in every month. Our results demonstrate the importance of the timing of earthquakes in terms of our capacity to respond effectively, highlighting the need for more intelligent design of disaster response that is not overly reliant on optical satellite imagery.

General relativity 1 predicts that short-orbital-period binaries emit considerable amounts of gravitational radiation. The upcoming Laser Interferometer Space Antenna 2 (LISA) is expected to detect tens of thousands of such systems 3 but few have been identified 4 , of which only one 5 is eclipsing—the double-white-dwarf binary SDSS J065133.338+284423.37, which has an orbital period of 12.75 minutes. Here we report the discovery of an eclipsing double-white-dwarf binary system, ZTF J153932.16+502738.8, with an orbital period of 6.91 minutes. This system has an orbit so compact that the entire binary could fit within the diameter of the planet Saturn. The system exhibits a deep eclipse, and a double-lined spectroscopic nature. We see rapid orbital decay, consistent with that expected from general relativity. ZTF J153932.16+502738.8 is a strong source of gravitational radiation close to the peak of LISA’s sensitivity, and we expect it to be detected within the first week of LISA observations, once LISA launches in approximately 2034. Observations of an eclipsing double-white-dwarf binary with an orbital period of 6.91 minutes that is decaying as predicted by general relativity are reported; once launched, the Laser Interferometer Space Antenna (LISA) should swiftly detect this binary.

Although the potential to adapt to warmer climate is constrained by genetic trade-offs, our understanding of how selection and mutation shape genetic (co)variances in thermal reaction norms is poor. Using 71 isofemale lines of the fly Sepsis punctum, originating from northern, central, and southern European climates, we tested for divergence in juvenile development rate across latitude at five experimental temperatures. To investigate effects of evolutionary history in different climates on standing genetic variation in reaction norms, we further compared genetic (co)variances between regions. Flies were reared on either high or low food resources to explore the role of energy acquisition in determining genetic trade-offs between different temperatures. Although the latter had only weak effects on the strength and sign of genetic correlations, genetic architecture differed significantly between climatic regions, implying that evolution of reaction norms proceeds via different trajectories at high latitude versus low latitude in this system. Accordingly, regional genetic architecture was correlated to region-specific differentiation. Moreover, hot development temperatures were associated with low genetic variance and stronger genetic correlations compared to cooler temperatures. We discuss the evolutionary potential of thermal reaction norms in light of their underlying genetic architectures, evolutionary histories, and the materialization of trade-offs in natural environments.

Diversified farming systems, for example those that incorporate agroforestry elements, have been proposed as a solution that could maintain and improve multiple ecosystem services. However, habitat diversification in and around arable fields has complex and inconsistent effects on invertebrate crop pests and their natural enemies. This hinders the development of policy recommendations to promote the adoption of such management strategies for the provision of natural pest control services. Here, for the first time, we conducted a trait-based approach to investigate the effect of farming system on plant, invertebrate herbivore, and invertebrate natural enemy communities. We then evaluated this approach by comparing the results to those generated using a traditional taxonomic approach. At each of three working farms, we sampled within an agroforestry field (a diverse farming system comprising alleys of arable crops separated by tree rows), and within a paired non-diversified area of the farm (arable control field). Each of 96 sample points was sampled between 8 and 10 times, yielding 393,318 invertebrate specimens from 344 taxonomic groups. Diet specialization or granivory, lack of a pupal stage, and wing traits in invertebrates, along with late flowering, short flowering duration, creeping habit, and perenniality in plants, were traits more strongly associated with agroforestry crop alleys than the arable control fields. We hypothesize that this is a result of reduced habitat disturbance and increased habitat complexity in the agroforestry system. Taxonomic richness and diversity were higher in the agroforestry crop alleys compared to the arable control fields, but these effects were stronger at lower trophic levels. However, functional trait diversity of natural enemies was significantly higher in the agroforestry crop alleys than the arable control fields, suggesting an improved level of biocontrol, which was not detected by traditional diversity metrics. Of eight key pest taxa, three were significantly suppressed in the agroforestry system, while two were more abundant, compared to the arable control fields. Trait-based approaches can provide a better mechanistic understanding of farming system effects on pests and their natural enemies, therefore we recommend their application and testing in future studies of diversified farming systems.