Eddy impacts on abundance and habitat distribution of a large predatory squid off Peru.

The pelagic cephalopod species jumbo flying squid Dosidicus gigas is ecologically and economically important in the Humboldt ecosystem off Peru. This squid species is sensitive to oceanic environmental changes, and regional oceanographical variability is one of the important factors driving its redistribution. Off Peruvian waters, mesoscale eddies are ubiquitous and dominate the biogeochemical processes in this region. This study first explored the role of mesoscale eddies in regulating the environments and their effects on the abundance and habitat distribution of D. gigas off Peru by analyzing squid distribution in eddy-centric coordinates and building a habitat suitability index (HSI) model. Results indicated that the abundance and habitat distribution of D. gigas in mesoscale eddies varied across months, with significant differences observed between anticyclonic eddies (AE) and cyclonic eddies (CE). In AE, a higher abundance and proportion of suitable habitat occurred. While in CE, the abundance was relatively low and the suitable habitat was relatively less, concentrating at the periphery of CE. Based on the HSI model results, sea surface temperature (SST) and 50 m water temperature (T50m) in AE were more favorable for D. gigas, which was 0.3-0.5 °C lower than that in CE, yielding high-quality habitats and higher abundance of D. gigas. Our findings emphasized that mesoscale eddies have a significant impact on water temperature conditions and nutrient concentrations off Peruvian waters.

Engineered DNA molecular machine for ultrasensitive detection of environmental lead pollution.

Dynamic monitoring of environmental Pb2+ is of utmost importance for food safety and personal well-being. Herein, we report a novel, rapid, and practical fluorescence detection platform for Pb2+. The platform comprises two essential components: an engineered DNAzyme probe (EDP) and a responsive functionalized probe (RFP). The EDP demonstrates specific recognition of Pb2+ and the subsequent release of free DNA fragments. The released DNA fragments are then captured using the RFP to form DNA complexes, which undergo multiple cascade amplification reactions involving polymerases and nickases, resulting in the generation of a large number of fluorescence signals. These signals can detect Pb2+ at concentrations as low as 0.114 nmol/L, with a dynamic range spanning from 0.1 nmol/L to 50 nmol/L. Moreover, the platform exhibits excellent sensitivity and selectivity for Pb2+ detection. To further validate its effectiveness, we successfully quantitatively detected lead contamination in water from Chaohu Lake, and the results aligned closely with those obtained using inductively coupled plasma-mass spectrometry (ICP-MS). Moreover, this platform is suitable for detecting Pb2+ in seawater, soil, and fish samples. These findings confirm the suitability of the current detection platform for the dynamic assessment of Pb contamination in ecological environments, thereby contributing to environmental and food safety.

Integrating multi-modal information to detect spatial domains of spatial transcriptomics by graph attention network.

Recent advances in spatially resolved transcriptomic technologies have enabled unprecedented opportunities to elucidate tissue architecture and function in situ. Spatial transcriptomics can provide multimodal and complementary information simultaneously, including gene expression profiles, spatial locations, and histology images. However, most existing methods have limitations in efficiently utilizing spatial information and matched high-resolution histology images. To fully leverage the multi-modal information, we propose a SPAtially embedded Deep Attentional graph Clustering (SpaDAC) method to identify spatial domains while reconstructing denoised gene expression profiles. This method can efficiently learn the low-dimensional embeddings for spatial transcriptomics data by constructing multi-view graph modules to capture both spatial location connectives and morphological connectives. Benchmark results demonstrate that SpaDAC outperforms other algorithms on several recent spatial transcriptomics datasets. SpaDAC is a valuable tool for spatial domain detection, facilitating the comprehension of tissue architecture and cellular microenvironment. The source code of SpaDAC is freely available at Github (https://github.com/huoyuying/SpaDAC.git).

Thermal physiology integrated species distribution model predicts profound habitat fragmentation for estuarine fish with ocean warming.

Species distribution models predict a poleward migration for marine ectotherms with ocean warming. However, a key limitation in current species distribution models (SDM) is that they do not account for population-specific heterogeneity in physiological responses to temperature change resulting from local adaptations and acclimatization. To address this gap, we developed a novel, Physiology Integrated BioClimate Model (PIBCM) that combines habitat-specific metabolic thermal physiological tolerance of a species into a bioclimate envelope model. Using a downscaling approach, we also established a fine-resolution coastal sea-surface temperature data set for 2050-2080, that showed a high degree of location-specific variability in future thermal regimes. Combining predicted temperature data with the PIBCM model, we estimated habitat distribution for a highly eurythermal intertidal minnow, the Atlantic killifish (Fundulus heteroclitus), a species that likely presents a best-case-scenario for coastal vertebrates. We show that the killifish northern boundary shifts southwards, while distinct habitat fragmentation occurs in the southern sub-population (due to migration of adjacent fish populations to the nearest metabolically optimal thermal habitat). When compared to current SDMs (e.g., AquaMaps), our results emphasize the need for thermal physiology integrated range shift models and indicate that habitat fragmentation for coastal fishes may reshape nursery habitats for many commercially and ecologically important species.

Australian fire nourishes ocean phytoplankton bloom.

An unprecedented devastating forest fire occurred in Australia from September 2019 to March 2020. Satellite observations revealed that this rare fire event in Australia destroyed a record amount of more than 202,387 km2 of forest, including 56,471 km2 in eastern Australia, which is mostly composed of evergreen forest. The released aerosols contained essential nutrients for the growth of marine phytoplankton and were transported by westerly winds over the Southern Ocean, with rainfall-induced deposition to the ocean beneath. Here, we show that a prominent oceanic bloom, indicated by the rapid growth of phytoplankton, took place in the Southern Ocean along the trajectory of fire-born aerosols in response to atmospheric deposition. Calculations of carbon released during the fire versus carbon absorbed by the oceanic phytoplankton bloom suggest that they were nearly equal. This finding illustrates the critical role of the oceans in mitigating natural and anthropogenic carbon dioxide releases to the atmosphere, which are a primary driver of climate change.

Individual-based eco-evolutionary models for understanding adaptation in changing seas.

As climate change threatens species' persistence, predicting the potential for species to adapt to rapidly changing environments is imperative for the development of effective conservation strategies. Eco-evolutionary individual-based models (IBMs) can be useful tools for achieving this objective. We performed a literature review to identify studies that apply these tools in marine systems. Our survey suggested that this is an emerging area of research fuelled in part by developments in modelling frameworks that allow simulation of increasingly complex ecological, genetic and demographic processes. The studies we identified illustrate the promise of this approach and advance our understanding of the capacity for adaptation to outpace climate change. These studies also identify limitations of current models and opportunities for further development. We discuss three main topics that emerged across studies: (i) effects of genetic architecture and non-genetic responses on adaptive potential; (ii) capacity for gene flow to facilitate rapid adaptation; and (iii) impacts of multiple stressors on persistence. Finally, we demonstrate the approach using simple simulations and provide a framework for users to explore eco-evolutionary IBMs as tools for understanding adaptation in changing seas.

A Sixteen-year Decline in Dissolved Oxygen in the Central California Current.

A potential consequence of climate change is global decrease in dissolved oxygen at depth in the oceans due to changes in the balance of ventilation, mixing, respiration, and photosynthesis. We present hydrographic cruise observations of declining dissolved oxygen collected along CalCOFI Line 66.7 (Line 67) off of Monterey Bay, in the Central California Current region, and investigate likely mechanisms. Between 1998 and 2013, dissolved oxygen decreased at the mean rate of 1.92 µmol kg-1 year-1 on σθ 26.6-26.8 kg m-3 isopycnals (250-400 m), translating to a 40% decline from initial concentrations. Two cores of elevated dissolved oxygen decline at 130 and 240 km from shore, which we suggest are a California Undercurrent and a California Current signal respectively, occurred on σθ ranges of 26.0-26.8 kg m-3 (100-400 m). A box model suggests that small annual changes in dissolved oxygen in source regions are sufficient to be the primary driver of the mid-depth declines. Variation in dissolved oxygen at the bottom of the surface mixed layer suggests that there is also a signal of increased local remineralization.

Probing an Individual Electron Spin State in a Quantum Dot with Spin Bias.

A quantum dot coupled to two electrodes with spin-dependent splitting of chemical potentials (spin bias) is proposed as a detector of an individual electron spin. Spin polarized transport properties through the quantum dot have been investigated theoretically by means of the nonequilibrium Green's function formalism. We found that the direction of current flow is dependent on the electronic spin state in quantum dot. Measuring the direction of the current flow through the devices, we can determine the direction of the electronic spin state in quantum dot. This proposed detector provides a practical and all electrical approach to detect the electronic spin state in quantum dot structure.

Persistent and energetic bottom-trapped topographic Rossby waves observed in the southern South China Sea.

Energetic fluctuations with periods of 9-14 days below a depth of 1400 m were observed in the southern South China Sea (SCS) from 5 years of direct measurements. We interpreted such fluctuations as topographic Rossby waves (TRWs) because they obey the dispersion relation. The TRWs persisted from May 24, 2009 to August 23, 2013, and their bottom current speed with a maximum of ~10 cm/s was one order of magnitude greater than the mean current and comparable to the tidal currents near the bottom. The bottom-trapped TRWs had an approximate trapping depth of 325 m and reference wavelength of ~82 km, which were likely excited by eddies above. Upper layer current speed that peaked approximately every 2 months could offer the energy sources for the persistent TRWs in the southern SCS. Energetic bottom-trapped TRWs may have a comparable role in deep circulation to tides in areas with complex topography.

Observed deep energetic eddies by seamount wake.

Despite numerous surface eddies are observed in the ocean, deep eddies (a type of eddies which have no footprints at the sea surface) are much less reported in the literature due to the scarcity of their observation. In this letter, from recently collected current and temperature data by mooring arrays, a deep energetic and baroclinic eddy is detected in the northwestern South China Sea (SCS) with its intensity, size, polarity and structure being characterized. It remarkably deepens isotherm at deep layers by the amplitude of ~120 m and induces a maximal velocity amplitude about 0.18 m/s, which is far larger than the median velocity (0.02 m/s). The deep eddy is generated in a wake when a steering flow in the upper layer passes a seamount, induced by a surface cyclonic eddy. More observations suggest that the deep eddy should not be an episode in the area. Deep eddies significantly increase the velocity intensity and enhance the mixing in the deep ocean, also have potential implication for deep-sea sediments transport.

Proton irradiation damage mechanism of PANDA-type polarization-maintaining optical fibers.

The effects of proton irradiation with energies of 3.5 and 5 MeV on the optical properties of PANDA (polarization-maintaining and absorption-reducing) optical fiber were investigated. The displacement and the ionization damage in the fiber induced by proton irradiation at 3.5, 5, and 10 MeV were calculated, respectively, using a Stopping and Range of Ions in Matter code. The irradiation-induced defects were analyzed by means of x-ray photoelectron spectroscopy, electron paramagnetic resonance, Fourier-transform infrared spectrometry, and broadband optical spectrum analysis. The results show that the proton irradiation leads to an increase of optical loss around 1310 nm and that the effect of 3.5 MeV protons is more severe than that of 5 MeV.