Temporal Persistence Research Articles

Macrofaunal Biodiversity and Patch Mosaics on the Deep Gulf of Mexico Seafloor

ABSTRACTThe deep‐sea benthos often exhibit exceptional biodiversity. The patch‐mosaic hypothesis proposes that this deep‐sea diversity arises from varied microhabitats with prolonged temporal persistence filtering for distinctive communities thereby increasing beta‐diversity. This study investigated environmental, community, and macrofaunal species turnover at four deep‐sea sites (~2000 m) in the northern Gulf of Mexico. Using precise small‐scale sampling with a ROV, we analyzed patterns across spatial scales from centimeters to approximately 400 km among 67 sediment cores. We examined the relationships between sedimentary carbon, sediment grain size, and macrofaunal alpha‐ and beta‐diversity. Subsequently, we explored the role of these environmental properties and their spatial arrangement in shaping communities and species distributions. We observed a consistent trend where the overall abundance and diversity of a community increased with higher carbon but decreased with increasing grain size. Substantial faunal turnover was observed among cores, even at centimeter scales, with the contribution of centimeter‐scale spatial distance rivaling that of 100‐km scales in faunal dissimilarity. Similar to alpha‐diversity, beta‐diversity exhibited strong correlations with sediment carbon and grain size. The observed random spatial structure in grain size and carbon appear to translate into randomness in both community and species distribution. These findings align with the patch‐mosaic model, underscoring the complexity of deep‐sea ecosystems. These findings suggest an intricate relationship between sedimentary attributes, faunal composition, and spatial arrangement in the deep‐sea benthos, shedding light on the mechanisms driving biodiversity in seemingly homogeneous environments.

Targeting the high frequency tail of wave spectra for energy harvesting in marine sensor networks

While the conventional philosophy of wave energy conversion is to target the large amounts of power in the peak of the input wave spectrum, this study proposes that for the application of powering marine sensor networks (MSNs), it is advantageous to target the high frequency tail of the wave spectrum. This strategy is predicated on two primary advantages: the spatial and temporal persistence of the wave energy resource in the high-frequency region and its compatibility with the resonance characteristics of smaller MSN devices. To identify the optimal frequency range for energy harvesting, we conducted a detailed analysis of wave spectra across multiple coastal locations. This involved calculating and comparing the power spectra at different frequencies, using data from long-term wave measurements. The high-frequency tail was defined by determining the frequency above which the energy content showed consistent temporal and spatial stability across all study sites. The quantification of available power was achieved by integrating the wave power spectrum over the identified frequency range. Our case study, focusing on the coast of Queensland, Australia, reveals that frequencies above 2.5 rad/s consistently offer a stable and persistent energy resource. The available power in this range is quantified, totalling an average of 60 W/m, with additional analysis provided within narrower sub-bandwidths to address the inherent narrow-bandedness of wave energy harvesters. This research provides critical insights for the design of efficient wave energy harvesters tailored to the needs of diverse marine environments.

Examining contaminant transport hotspots and their predictability across contrasted watersheds.

Hydrobiogeochemical processes governing water quantity and quality are highly variable in space and time. Focusing on thirty river locations in Québec, Canada, three water quality hotness indices were used to classify watersheds as contaminant transport hotspots. Concentration and load data for suspended solids (SS), total nitrogen (TN), and total phosphorous (TP) were used to identify transport hotspots, and results were compared across hotness indices with different data requirements. The role of hydroclimatic and physiographic characteristics on the occurrence and temporal persistence of transport hotspots was examined. Results show that the identification of transport hotspots was dependent on both the type of data and the hotness index used. Relationships between temporal and spatial predictors, however, were generally consistent. Annual transport hotspot occurrence was found to be related to temporal characteristics such as the number of dry days, potential evapotranspiration, and snow water equivalent, while hotspot temporal persistence was correlated to landcover characteristics. Stark differences in the identification of SS, TN, and TP transport hotspots were attributed to differences in mobilization processes and provided insights into dominant water and nutrient flowpaths in the studied watersheds. This study highlighted the importance of comparing contaminant dynamics across watersheds even when high-frequency water quality data or discharge data are not available. Characterizing hotspot occurrence and persistence, among hotness indices and water quality parameters, could be useful for watershed managers when identifying problematic watersheds, exploring legacy effects, and establishing a prioritization framework for areas that would benefit from enhanced routine monitoring or targeted mitigation strategies.

Mean sea level, tidal components and surges in Guanabara Bay (Rio de Janeiro) from 1990 to 2021

AbstractGuanabara Bay, located in the Metropolitan Region of Rio de Janeiro, one of the largest urban coastal areas in the Southern Hemisphere, is subject to intense maritime traffic due to the presence of several ports. These facilities are affected by sea level fluctuations, influenced by atmospheric and astronomical forces, which motivates synoptic and climatological analysis, including meteorological and astronomical tidal phenomena. This study aimed to assess the evolution of tidal components and the relative mean sea level (MSL) between 1990 and 2021, as well as the atmospheric influence on extreme meteorological tide events, in which the MSL exceeded ±2 and ±3 (±29.98 and ±44.97 cm) standard deviations. The results have shown that, albeit small, the main tidal components (, , , , , , and ) indicated positive trends in the increase of amplitude and phase, despite the small quantities. For the relative MSL, an increase of 0.30 cm·year−1 was observed in agreement with estimates from global series from satellite altimeters and climate model predictions. Pressure and wind field analyses led to the identification of seasonal variability and the pattern of evolution of atmospheric systems associated with extreme events. In the case of positive surges, very intense winds from the SW, extending along the S/SE Brazilian coast, are caused by the presence of a high‐pressure centre over the continent and low‐pressure centres over the ocean, leading to water piling up. In turn, negative surges are caused by the presence of an anticyclone over the ocean, generating NE winds parallel to the coast of Rio de Janeiro, inducing Ekman transport and lowering the sea level. Therefore, the extreme sea level events in the Guanabara Bay are not triggered by local forces, but rather depend on the temporal persistence and direction of winds along the S/SE Brazilian coast.

Spatial dynamics of mammalian brain development and neuroinflammation by multimodal tri-omics mapping.

The ability to spatially map multiple layers of the omics information over different time points allows for exploring the mechanisms driving brain development, differentiation, arealization, and alterations in disease. Herein we developed and applied spatial tri-omic sequencing technologies, DBiT ARP-seq (spatial ATAC-RNA-Protein-seq) and DBiT CTRP-seq (spatial CUT&Tag-RNA-Protein-seq) together with multiplexed immunofluorescence imaging (CODEX) to map spatial dynamic remodeling in brain development and neuroinflammation. A spatiotemporal tri-omic atlas of the mouse brain was obtained at different stages from postnatal day P0 to P21, and compared to the regions of interest in the human developing brains. Specifically, in the cortical area, we discovered temporal persistence and spatial spreading of chromatin accessibility for the layer-defining transcription factors. In corpus callosum, we observed dynamic chromatin priming of myelin genes across the subregions. Together, it suggests a role for layer specific projection neurons to coordinate axonogenesis and myelination. We further mapped the brain of a lysolecithin (LPC) neuroinflammation mouse model and observed common molecular programs in development and neuroinflammation. Microglia, exhibiting both conserved and distinct programs for inflammation and resolution, are transiently activated not only at the core of the LPC lesion, but also at distal locations presumably through neuronal circuitry. Thus, this work unveiled common and differential mechanisms in brain development and neuroinflammation, resulting in a valuable data resource to investigate brain development, function and disease.

Spatial dynamics of mammalian brain development and neuroinflammation by multimodal tri-omics mapping.

The ability to spatially map multiple layers of the omics information over different time points allows for exploring the mechanisms driving brain development, differentiation, arealization, and alterations in disease. Herein we developed and applied spatial tri-omic sequencing technologies, DBiT ARP-seq (spatial ATAC-RNA-Protein-seq) and DBiT CTRP-seq (spatial CUT&Tag-RNA-Protein-seq) together with multiplexed immunofluorescence imaging (CODEX) to map spatial dynamic remodeling in brain development and neuroinflammation. A spatiotemporal tri-omic atlas of the mouse brain was obtained at different stages from postnatal day P0 to P21, and compared to the regions of interest in the human developing brains. Specifically, in the cortical area, we discovered temporal persistence and spatial spreading of chromatin accessibility for the layer-defining transcription factors. In corpus callosum, we observed dynamic chromatin priming of myelin genes across the subregions. Together, it suggests a role for layer specific projection neurons to coordinate axonogenesis and myelination. We further mapped the brain of a lysolecithin (LPC) neuroinflammation mouse model and observed common molecular programs in development and neuroinflammation. Microglia, exhibiting both conserved and distinct programs for inflammation and resolution, are transiently activated not only at the core of the LPC lesion, but also at distal locations presumably through neuronal circuitry. Thus, this work unveiled common and differential mechanisms in brain development and neuroinflammation, resulting in a valuable data resource to investigate brain development, function and disease.

Temporal dynamics and persistence of resistance genes to broad spectrum antibiotics in an urban community

The constantly evolving and growing global health crisis, antimicrobial resistance (AMR), endangers progress in medicine, food production, and life expectancy. Limited data on population-level prevalence, including seasonal and temporal variations, hampers accurate risk assessment for AMR transmission, despite its paramount importance on both global and national fronts. In this study, we used quantitative real-time PCR (q-PCR) to analyze 123 antibiotic resistance genes (ARGs) and 13 mobile genetic elements (MGEs) in wastewater of a selected urban community. Sampling was conducted monthly over a 5-month period (December 2021–April 2022) to assess resistance diversity, temporal dynamics, co-abundance of ARGs, MGEs, and resistance mechanisms. Approximately 50% of the tested ARG subtypes were consistently detected in all months, with frequency ranging from 52 to 61% with maximum absolute abundance in the winter months (December and January). In co-abundance analysis, specific genes were clustered into modules, highlighting shared distribution patterns and functional associations among the ARGs and MGEs. Detected clinically significant genes (ndm-1 and cfiA) and other variants (blaoxy, aph, aacC, tet-35, tet M, tet-32) are capable of imparting resistance to 3rd and 4th generation (gen) β-lactam, aminoglycoside, tetracycline, and multidrug classes. These contribute significantly to core/persistent resistance. This study deepens our comprehension of temporal/seasonal fluctuations in ARG and MGE distribution, providing valuable evidence to guide AMR control policies and promote responsible antibiotic/antimicrobial use for preserving effectiveness.

Genetic features of BEL-1-producing and KPC-2-producing E. coli from hospital wastewater: human source or sewages adaptation

Hospital sewage is an ecosystem that facilitates the transfer of antibiotic and heavy metal resistance genes and the interaction of human and environmental bacteria. In this environment, we have detected the presence of 7 KPC-2 and BEL-1 co-producing E. coli isolates of two different clones over a 10-month period in the same hospital. All isolates carried blaKPC-2 and the operon mer on the same IncP plasmid of similar size and an IncN plasmid of different size each clone carrying blaBEL-1. Both IncN-blaBEL-1 plasmids shared a 77 kb region containing blaBEL-1 alongside with fosE, blaOXA-10 and aac(6’)-1b genes in a class 3 integron within a Tn3 transposon. The major IncN plasmid contained in addition a region homolog to P1-like bacteriophage RCS47, including the lytic RepL and lysogenic proteins, but other phage regions were incomplete. The characters such as the temporal persistence in sewage, the absence of colonized patients in the hospital or in the region, the presence of a p1 phage-plasmid fusion and the infrequent class 3 integron as genetic platform would indicate that BEL-1-producing isolates could have been generated in situ by adaptation to human sewage. Part of the microbiota in these discharges could be explained by the interactions of sewage ecosystems and not derive directly from the hospital.

Bifurcation Analysis and Spatiotemporal Dynamics in a Diffusive Predator–Prey System Incorporating a Holling Type II Functional Response

This study aims to investigate a diffusive predator–prey system incorporating additional food for predators, prey refuge, fear effect, and its carry-over effects. For the temporal model, the well-posedness and persistence of the system have been discussed. We investigated the existence and the stability behavior of the various equilibria. Furthermore, we explored the bifurcations of codimension-1 including transcritical, saddle-node, and Hopf, concerning the crucial parameters. The system also presents codimension-2 bifurcations such as Bogdanov–Takens and cusp bifurcation along with the global homoclinic bifurcation. We observed the bubbling phenomena, which illustrate the fluctuations in the amplitudes of the periodic oscillations. For the spatiotemporal system, we established the non-negativity and boundedness of the solutions. We derived the conditions for the diffusion-driven instabilities in a confined region with Neumann boundary conditions. Extensive numerical simulations have been conducted to depict the various stationary patterns in Turing space. It is observed that incorporating cross-diffusion divides the bi-parametric plane into various sub-regions and dynamic patterns are analyzed in these different regions. The intricate spatiotemporal dynamics exhibited by prey–predator interactions are crucial for unraveling the intricacies within ecological systems.

Growth couples temporal and spatial fluctuations of tissue properties during morphogenesis

Living tissues display fluctuations-random spatial and temporal variations of tissue properties around their reference values-at multiple scales. It is believed that such fluctuations may enable tissues to sense their state or their size. Recent theoretical studies developed specific models of fluctuations in growing tissues and predicted that fluctuations of growth show long-range correlations. Here, we elaborated upon these predictions and we tested them using experimental data. We first introduced a minimal model for the fluctuations of any quantity that has some level of temporal persistence or memory, such as concentration of a molecule, local growth rate, or mechanical property. We found that long-range correlations are generic, applying to any such quantity, and that growth couples temporal and spatial fluctuations, through a mechanism that we call "fluctuation stretching"-growth enlarges the length scale of variation of this quantity. We then analyzed growth data from sepals of the model plant Arabidopsis and we quantified spatial and temporal fluctuations of cell growth using the previously developed cellular Fourier transform. Growth appears to have long-range correlations. We compared different genotypes and growth conditions: mutants with lower or higher response to mechanical stress have lower temporal correlations and longer-range spatial correlations than wild-type plants. Finally, we used theoretical predictions to merge experimental data from all conditions and developmental stages into a unifying curve, validating the notion that temporal and spatial fluctuations are coupled by growth. Altogether, our work reveals kinematic constraints on spatiotemporal fluctuations that have an impact on the robustness of morphogenesis.

On the persistence and related mechanisms for day–night compound humid heat extremes in the Northern Hemisphere

Hot extremes pose adverse impacts on human health and ecosystem, leading to aggravated damage when they combine high-humidity and occur in the both daytime and nighttime. Although considerable studies have focused on hot extremes, understandings about day–night Compound humid heat (quantified by Moist Enthalpy) Extremes (CMEEs) are still lacking. This work investigates their frequency, linear trends and temporal persistence in the Northern Hemisphere, and two typical vulnerable regions are selected as Central Europe (CE) and the Arabian Peninsula (AP), both exhibiting high frequency and positive trends, but with contrasting persistence, which is quantified by the bivariate Dynamical System method. Results reveal their regional dependence and physical processes: the dual importance of sensible and latent heat in CE is attributed to the combination of an anomalous anticyclone and evaporation, whereas the dominance of latent heat in AP is largely owing to the convective precipitation. CMEEs in AP can be further divided into two groups with distinct persistence, and this disparity actually depends on the preceding precipitation duration and its associated water vapor supply.

Predictability of B cell clonal persistence and immunosurveillance in breast cancer

B cells and T cells are important components of the adaptive immune system and mediate anticancer immunity. The T cell landscape in cancer is well characterized, but the contribution of B cells to anticancer immunosurveillance is less well explored. Here we show an integrative analysis of the B cell and T cell receptor repertoire from individuals with metastatic breast cancer and individuals with early breast cancer during neoadjuvant therapy. Using immune receptor, RNA and whole-exome sequencing, we show that both B cell and T cell responses seem to coevolve with the metastatic cancer genomes and mirror tumor mutational and neoantigen architecture. B cell clones associated with metastatic immunosurveillance and temporal persistence were more expanded and distinct from site-specific clones. B cell clonal immunosurveillance and temporal persistence are predictable from the clonal structure, with higher-centrality B cell antigen receptors more likely to be detected across multiple metastases or across time. This predictability was generalizable across other immune-mediated disorders. This work lays a foundation for prioritizing antibody sequences for therapeutic targeting in cancer.

Controlling inter-particle distances in crowds of motile, cognitive, active particles

Distance control in many-particle systems is a fundamental problem in nature. This becomes particularly relevant in systems of active agents, which can sense their environment and react by adjusting their direction of motion. We employ agent-based simulations to investigate the complex interplay between agent activity, characterized by Péclet number Pe\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\hbox{Pe}$$\\end{document}, reorientation maneuverability Ω\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\Omega$$\\end{document}, vision angle θ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ heta$$\\end{document} and vision range R0\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$R_0$$\\end{document}, and agent density, which determines agent distancing and dynamics. We focus on semi-dense crowds, where the vision range is much larger than the particle size. The minimal distance to the nearest neighbors, exposure time, and persistence of orientation direction are analyzed to characterize the behavior. With increasing particle speed at fixed maneuverability, particles approach each other more closely, and exhibit shorter exposure times. The temporal persistence of motion decreases with increasing Pe\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\hbox{Pe}$$\\end{document}, reflecting the impact of activity and maneuverability on direction changes. For a vision angle θ=π/4\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ heta =\\pi /4$$\\end{document}, we observe the emergence of flocking aggregates with a band-like structure, somewhat reminiscent of the bands in the Vicsek model. Additionally, for vision angles θ≥π/2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ heta \\ge \\pi /2$$\\end{document}, several quantities are found to display a universal scaling behavior with scaling variable Pe3/2/Ω\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\hbox{Pe}^{3/2}/\\Omega$$\\end{document}. Our results are in good agreement with recent experiments of pedestrians in confined spaces.

Interannual Variability of August Precipitation in China Associated With the Antarctic Sea Ice Anomaly

AbstractThrough observational analysis and atmospheric simulation experiments, the relationship between sea ice in the region of South Pole and August precipitation in China was determined. Results indicate that the leading mode of August precipitation in China is significantly correlated with July sea ice concentration (SIC) in South Pole, specifically in eastern Indian Ocean (EIO) region. Typically, the SIC growth is followed by positive rainfall anomalies in the middle and lower reaches of Yangtze River Basin (YRB) and Northeast China (NEC), while South China (SC) is under the control of negative rainfall anomalies. Precisely, owing to the temporal persistence of sea ice in the South Polar region from May to August, sea ice anomalies exert a strong influence on August atmospheric stability in EIO of Southern Hemisphere via regulating turbulent heat flux and air temperature anomalies. As SIC increases, the atmospheric circulation in horizontal exhibits the characteristics of the Antarctic Oscillation (AAO) positive phase, affecting the zonal wind anomalies. Subsequently, the anomalous circulation with a barotropic structure propagates to Australia and the East Asian via the strengthened vertical meridional cells and zonal winds. Moreover, numerical simulations confirm that due to the growth of South Polar sea ice in EIO, abnormal cyclone and anticyclone appear over North China and SC respectively, together with the moisture converging anomalies in the middle and lower reaches of YRB, and diverging anomalies in SC. Accordingly, these atmospheric circulation anomalies triggered by Antarctic sea ice conducive to a wet (dry) August in northern (southern) China.

Temporal Variation and Persistence of Methane Emissions from Shallow Water Oil and Gas Production in the Gulf of Mexico.

Methane emissions from the oil and gas supply chain can be intermittent, posing challenges for monitoring and mitigation efforts. This study examines shallow water facilities in the US Gulf of Mexico with repeat atmospheric observations to evaluate temporal variation in site-specific methane emissions. We combine new and previous observations to develop a longitudinal study, spanning from days to months to almost five years, evaluating the emissions behavior of sites over time. We also define and determine the chance of subsequent detection (CSD): the likelihood that an emitting site will be observed emitting again. The average emitting central hub in the Gulf has a 74% CSD at any time interval. Eight facilities contribute 50% of total emissions and are over 80% persistent with a 96% CSD above 100 kg/h and 46% persistent with a 42% CSD above 1000 kg/h, indicating that large emissions are persistent at certain sites. Forward-looking infrared (FLIR) footage shows many of these sites exhibiting cold venting. This suggests that for offshore, a low sampling frequency over large spatial coverage can capture typical site emissions behavior and identify targets for mitigation. We further demonstrate the preliminary use of space-based observations to monitor offshore emissions over time.

Time-varying causalities from the COVID-19 media coverage to the dynamic spillovers among the cryptocurrency, the clean energy, and the crude oil

This paper aims to explore the time-varying causalities from the COVID-19 media coverage (MCI) to the dynamic spillovers among the cryptocurrency, the clean energy, and the crude oil. To achieve this goal, the dynamic spillovers among the three elements are estimated by employing the TVP-VAR extended joint connectedness approach in the first stage, while the temporal heterogeneity and persistence of causalities from MCI to the dynamic spillovers among the three elements are examined in the second stage by using the novel time-varying causality technique. We find that the dynamic spillovers among the three elements have been strengthened during the turmoil periods, i.e., the COVID-19 pandemic. Moreover, the averaged joint connectedness results show that the cryptocurrency and the clean energy seem to be the net receivers of spillovers, whereas the crude oil is the net transmitter of spillovers. However, the net spillovers roles of the three elements shift between transmitter and receiver dynamically. The causality results demonstrate that MCI has a significant causal effect on the dynamic total spillovers, the dynamic net total directional spillovers, and the dynamic net pairwise directional spillovers during certain periods. Specifically, long-lasting causal effects of MCI on the dynamic total spillovers are identified during the periods of December 2020–January 2021 and March 2021–October 2021. The causalities from MCI to the dynamic net total directional spillovers for the clean energy and the crude oil exist from September 2020 to the end of the sample period, more persistent than those for the cryptocurrency. Moreover, the causalities from MCI to the dynamic net total pairwise directional spillovers for the cryptocurrency-clean energy and the cryptocurrency-crude oil are found to be similar, which last for a shorter period than those for the clean energy-crude oil. These causal relationships can be fundamentally explained by the fact that investors' sentiments are susceptible to the COVID-19 media coverage, thus triggering changes in investors' decision-making.

Interaction network structure explains species' temporal persistence in empirical plant-pollinator communities.

Despite clear evidence that some pollinator populations are declining, our ability to predict pollinator communities prone to collapse or species at risk of local extinction is remarkably poor. Here, we develop a model grounded in the structuralist approach that allows us to draw sound predictions regarding the temporal persistence of species in mutualistic networks. Using high-resolution data from a six-year study following 12 independent plant-pollinator communities, we confirm that pollinator species with more persistent populations in the field are theoretically predicted to tolerate a larger range of environmental changes. Persistent communities are not necessarily more diverse, but are generally located in larger habitat patches, and present a distinctive combination of generalist and specialist species resulting in a more nested structure, as predicted by previous theoretical work. Hence, pollinator interactions directly inform about their ability to persist, opening the door to use theoretically informed models to predict species' fate within the ongoing global change.

Co‐Occurring Extremes of Fine Particulate Matter (PM2.5) and Ground‐Level Ozone in the Summer of Southern China

AbstractConcurrent pollution of fine particulate matter (PM2.5) and ozone has been increasingly reported in China recently. Here, we further confirm widespread co‐occurring summertime PM2.5‐ozone extremes in southern China. Annual‐average frequency of co‐occurrence is above 50% from 2015 to 2022, especially in Pearl River Delta region (72 ± 12%). The spatial extent (city numbers) and temporal persistence (co‐occurrence days) for cities with co‐occurrence frequency >50% increase at a rate of two cities/year and 14 days/year, respectively. We further identify typical synoptic conditions (e.g., typhoon periphery circulation, West Pacific subtropical high) conducive to widespread co‐occurrence. Through combining multi‐source data, Random Forest model well predicts PM2.5‐ozone co‐occurrence and identifies common precursors (e.g., volatile organic compounds) as important variables. Finally, we postulate co‐occurrence is linked to synoptic conditions and secondary generation of PM2.5‐ozone from shared precursors. Our results suggest high potentials for co‐occurring PM2.5‐ozone extremes in southern China and control strategies on common precursors to mitigate concurrent pollution.

Electrotaxis of Dictyostelium discoideum, Migration in an Electric Field.

Living cells have the ability to detect electric fields and respond to them with directed migratory movements. Many proteomic approaches have been adopted in the past to identify the molecular mechanism behind this cellular phenomenon. However, how the cells sense the electric stimulus and transduce it into directed cell migration is still under discussion. Many eukaryotic cells react to applied electric stimulation, including Dictyostelium discoideum cells. We use them as model system for studying cell migration in electric fields, also known as electrotaxis. Here we report the protocols that we developed for our experiments. Our experimental outcomes helped us to characterize: (i) the memory that cells have in a varying electric field, which we defined as temporal electric persistence; and (ii) the accelerating motion of cells along their paths over the electric exposure time. We also report on the analysis of the role that conditioned medium factor (CMF), a protein secreted by cells when they begin to starve, plays in the mechanism of electric sensing. The results of this study can contribute to the understanding of the electrical sensing of cells and its transduction into directed cell migration.

Identifying important habitat for northern bottlenose and Sowerby's beaked whales in the western North Atlantic

Abstract Understanding habitat requirements for species at risk is crucial for effective conservation management, even though the location and extent of vital habitats may be unknown for rare or elusive species. In the case of marine species, determining important habitat often relies on limited occurrence data or extrapolation from species distribution models (SDMs). SDMs predict habitat by associating species records with environmental variables, assuming a functional ecological relationship. This study focuses on northern bottlenose whales (NBW; Hyperoodon ampullatus) and Sowerby's beaked whales (SBW; Mesoplodon bidens) in the western North Atlantic. As both NBW and SBW are at risk in Canada, the objective was to identify the extent and function of important habitats to guide conservation efforts. The analysis mapped all available geographic occurrence data and used passive acoustic monitoring (PAM) data to inform the development of ensemble SDMs to predict potential habitat and assess the persistence of realized habitat use. Important habitats for NBW and SBW were found primarily concentrated along the continental shelf edges, at an average depth of 1200 m ± 460 SD. All habitat areas support foraging and movement and critical life history functions for both species. The Gully and other submarine canyons off eastern Nova Scotia emerged as important areas for both species, validating the existing Critical Habitat for NBW. However, spatial–temporal patterns diverged on either side of this region. North‐eastern Newfoundland was identified as the next closest area of near‐year‐round presence for NBW, whereas the south‐western Scotian Shelf region, Georges Bank and the Fundian Channel supported persistent foraging by SBW. By integrating multiple data sources (sightings, acoustic detections and SDMs) and demonstrating the temporal persistence of habitat use by NBW and SBW, this study provides valuable insights for identifying, protecting and managing important habitat for beaked whales.