Influence of habitat utilization strategies on trace element signatures in egg contents of green turtles nesting on Xisha Islands, South China Sea.

Habitat utilization significantly influences the accumulation of chemical pollutants, including trace elements (TEs), in the tissues of large marine organisms. Previous research has demonstrated that sea turtles nesting in the same location may employ distinct foraging strategies. This study investigated the influence of habitat use strategies on the concentrations of 16 TEs in the eggs of green turtles (Chelonia mydas) nesting on the Xisha Islands. The analysis incorporated stable carbon (δ13C) and nitrogen (δ15N) isotopes, as well as characteristic elements. Additionally, inter-relationships between TEs were examined. The nesting female green turtles were categorized into two foraging groups based on isotopic signatures, namely oceanic (δ13C values: -21.5 to -17.0 ‰; δ15N values: 7.10 to 12.5 ‰) and neritic (δ13C values: -14.4 to -9.95 ‰ and δ15N values: 5.10 to 10.0 ‰). Different TE patterns were observed in the egg contents of these two groups. The neritic group exhibited elevated levels of V and Cu, which positively corrected with δ13C values. Conversely, the oceanic group displayed higher levels of Zn, Cd, Se, Sn, As and Hg, which positively associated with δ15N values. This distribution pattern is attributed to variations in background TE concentrations in the respective foraging habitats. Additionally, prey items and trophic levels of green turtles may contribute to the observed inter-group differences in TE concentrations (e.g. Zn, As, Se, Sn) found in their eggs, warranting further research. This study provides valuable information about habitat utilization patterns and TE distribution in green turtles nesting on the Xisha Islands. The findings enhance our understanding of TE accumulation mechanisms in turtle tissues and eggs, which is significant for the conservation of this endangered species, the green sea turtle.

Investigation of factors influencing abnormal pulmonary ventilation function in occupational exposed populations and the establishment of a risk prediction model.

The purpose of this study is to investigate the influencing factors of abnormal pulmonary ventilation function in occupational exposed populations and to establish a risk prediction model. The findings will provide a basis for formulating corresponding strategies for the prevention and treatment of occupational diseases. The study focused on workers who underwent occupational health examinations in the year 2020. Statistical analysis was conducted using methods such as t-tests, chi-square tests, and multiple logistic regression analysis. Additionally, machine learning methods were employed to establish multiple models to address classification problems. Among the 7472 workers who participated in the occupational health examination, 1681 cases of abnormal pulmonary ventilation function were detected, resulting in a detection rate of 22.6%. Based on the analysis of occupational hazard data, a risk prediction model was established. Age, work tenure, type of the employing enterprise, and type of dust exposure are all identified as driving factors for abnormal pulmonary function. These factors were used as predictive variables for establishing the risk prediction model. Among the various models evaluated, the logistic regression model was found to be the optimal model for predicting abnormal pulmonary ventilation function.

Snake-like bird hisses induce anti-predator responses in a frog.

Some snakes emit hissing calls which are imitated by birds to deter potential predators. However, the effect of these snake and bird hisses on anuran risk recognition is not yet explored. Here we hypothesize that these hisses may advertise dangers to frogs and evoke their anti-predator responses. We used little torrent frogs (Amolops torrentis) as subjects and conducted sound playbacks to test their anti-predator behaviors. We found that little torrent frogs changed their calling behaviors during sympatric snake hiss playbacks, but showed no response to white noise and allopatric snake hiss playbacks. They did not respond to sympatric avian hiss that has low acoustic similarity with snake sounds. However, they decreased calling activity in response to sympatric avian hiss that has high acoustic similarity with snakes. As compared to other treatments, more individuals ceased calling during the playbacks of the highly similar bird hiss. These results suggest that frogs may recognize risks from snake and snake-like hissing calls and perform anti-predator responses.

Chromosome-level genome of diamondback terrapin provides insight into the genetic basis of salinity adaptation.

Diamondback terrapins (Malaclemys terrapin centrata) exhibit strong environmental adaptability and live in both freshwater and saltwater. However, the genetic basis of this adaptability has not been the focus of research. In this study, we successfully constructed a ∼2.21-Gb chromosome-level genome assembly for M. t. centrata using high-coverage and high-depth genomic sequencing data generated on multiple platforms. The M. t. centrata genome contains 25 chromosomes and the scaffold N50 of ∼143.75 Mb, demonstrating high continuity and accuracy. In total, 53.82% of the genome assembly was composed of repetitive sequences, and 22 435 protein-coding genes were predicted. Our phylogenetic analysis indicated that M. t. centrata was closely related to the red-eared slider turtle (Trachemys scripta elegans), with divergence approximately ∼23.6 million years ago (Mya) during the early Neogene period of the Cenozoic era. The population size of M. t. centrata decreased significantly over the past ∼14 Mya during the Cenozoic era. Comparative genomic analysis indicated that 36 gene families related to ion transport were expanded and several genes (AQP3, solute carrier subfamily, and potassium channel genes) underwent specific amino acid site mutations in the M. t. centrata genome. Changes to these ion transport-related genes may have contributed to the remarkable salinity adaptability of diamondback terrapin. The results of this study not only provide a high-quality reference genome for M. t. centrata but also elucidate the possible genetic basis for salinity adaptation in this species.

MiR-124-3p inhibits cell stemness in glioblastoma via targeting EPHA2 through ALKBH5-mediated m6A modification.

Glioblastoma (GBM) is the most aggressive form of glioma, characterized by high mortality and poor prognosis. Dysregulation of microRNAs (miRNAs) plays a critical role in the progression and metastasis of GBM. This study aimed to investigate the role and molecular mechanism of miR-124-3p in GBM. Levels of miR-124-3p, EPHA2, and ALKBH5 were measured using quantitative real-time polymerase chain reaction (qRT-PCR). Cell proliferation, migration, invasion, and stemness were assessed using the Cell Counting Kit-8 (CCK-8), colony formation, Transwell, and sphere formation assays, respectively. Bioinformatics prediction, dual-luciferase reporter assays, and RNA pull-down experiments were employed to validate the target of miR-124-3p. RNA binding protein immunoprecipitation (RIP) and methylated RNA immunoprecipitation (Me-RIP) were utilized to evaluate the regulation of miR-124-3p maturation by ALKBH5. The results indicated that overexpression of miR-124-3p inhibited the proliferation, migration, invasion, and stemness of GBM cells. EPHA2 was identified as a direct downstream target of miR-124-3p, and its overexpression reversed the inhibitory effects of miR-124-3p on cellular functions. Furthermore, miR-124-3p targeted EPHA2 to inactivate the Wnt/ß-catenin pathway. Additionally, ALKBH5 negatively regulated miR-124-3p by impeding its processing. In conclusion, knockdown of ALKBH5 promoted the processing of pri-miR-124-3p, increasing mature miR-124-3p levels, which inhibited the malignant behaviors of GBM cells by targeting EPHA2. These findings highlight the importance of the ALKBH5/miR-124-3p/EPHA2 axis in GBM.

A hybrid deep learning and clonal selection algorithm-based model for commercial building energy consumption prediction.

In contemporary society, commercial buildings, as a crucial component of urban development, face increasingly prominent energy consumption issues, posing significant challenges to the environment and sustainable development. Traditional energy management methods rely on empirical models and rule-based approaches, which suffer from low prediction accuracy and limited applicability. To address these issues, this study proposes a commercial building energy consumption prediction and energy-saving strategy model based on hybrid deep learning and optimization algorithms. This model integrates convolutional neural networks (CNN), gated recurrent units (GRU), and the clonal selection algorithm (CSA), aiming to enhance the accuracy and efficiency of energy consumption predictions. Experimental results demonstrate that the CNN-GRU-CSA Network (CGC-Net) model achieves mean absolute errors (MAE) of 17.12, 16.73, 16.62, and 15.94 on the Building Data Genome Project (BDGP), Commercial Building Energy Consumption Survey (CBECS), Nonresidential Building Energy Performance Benchmark (NEPB), and Building Energy Efficiency Benchmark (BEBDEE) datasets, respectively, significantly outperforming traditional methods and other models. Additionally, the model exhibits faster inference and training times. These results validate the stability and superiority of the CGC-Net model, providing an innovative solution and essential technical support for commercial building energy management.

Peripheral hearing sensitivity is similar between the sexes in a benthic turtle species despite the larger body size of males.

Sexually dimorphic hearing sensitivity has evolved in many vertebrate species, and the sex with a larger body size typically shows more sensitive hearing. However, generalizing this association is controversial. Research on sexually dimorphic hearing sensitivity contributes to an understanding of auditory sense functions, adaptations, and evolution among species. Therefore, the hypothesized association between body size and hearing needs further validation, especially in specific animal groups. In this study, we assessed hearing sensitivity by measuring auditory brainstem responses (ABRs) in both sexes of 3-year-old Chinese softshell turtles (Pelodiscus sinensis). In this species, male bodies are larger than those of female, and individuals spend most of their lives in the mud at the bottom of freshwater habitats. We found that for both sexes, the hearing sensitivity bandwidth was 0.2-0.9 kHz. Although males were significantly larger than females, no significant differences in ABR thresholds or latencies were found between males and females at the same stimulus frequency. These results indicate that P. sinensis hearing is only sensitive to low-frequency (typically <0.9 kHz) sound signals and that sexually dimorphic hearing sensitivity is not a trait that has evolved in P. sinensis. Physiological and environmental reasons may account for P. sinensis acoustic communication via low-frequency sound signals and the lack of sexually dimorphic hearing sensitivity in these benthic turtles. The results of this study refine our understanding of the adaptation and evolution of the vertebrate auditory system.

Altered regional neural activity and functional connectivity in patients with non-communicating hydrocephalus: a resting-state functional magnetic resonance imaging study.

Introduction: Cognitive impairment is a frequent clinical symptom of non-communicating hydrocephalus (NCH) involving multiple domains, including executive function, working memory, visual-spatial function, language, and attention. Functional magnetic resonance imaging (fMRI) can be used to obtain information on functional activity in local brain areas and functional connectivity (FC) across multiple brain regions. However, studies on the associated cognitive impairment are limited; further, the pathophysiological mechanisms of NCH with cognitive impairment remain unclear. Here, we aimed to explore alterations in regional neural activity and FC, as well as the mechanisms of cognitive impairment, in patients with NCH. Methods: Overall, 16 patients with NCH and 25 demographically matched healthy controls (HCs) were assessed using the Mini-Mental State Examination (MMSE) and fMRI. Changes in regional homogeneity (ReHo), degree centrality (DC), and region of interest-based FC were analyzed in both groups. The relationship between fMRI metrics (ReHo, DC, and FC) and MMSE scores in patients with NCH was also investigated. Results and discussion: Compared with the HC group, the NCH group exhibited significantly lower ReHo values in the left precentral and postcentral gyri, and significantly higher ReHo values in the left medial prefrontal cortex (MPFC). The NCH group also showed significantly higher DC values in the bilateral MPFC compared with the HC group. Regarding seed-based FC, the MPFC showed reduced FC values in the right superior parietal and postcentral gyrus in the NCH group compared with those in the HC group. Moreover, within the NCH group, MMSE scores were significantly negatively correlated with the ReHo value in the left MPFC and the DC value in the bilateral MPFC, whereas MMSE scores were significantly positively correlated with FC values. To conclude, regional neural activity and FC are altered in patients with NCH and are correlated with cognitive impairment. These results advance our understanding of the pathophysiological mechanisms underlying the association between NCH and cognitive impairment.

A bibliometric analysis and visualization of normal pressure hydrocephalus.

Background: Normal pressure hydrocephalus (NPH) has drawn an increasing amount of attention over the last 20 years. At present, there is a shortage of intuitive analysis on the trends in development, key contributors, and research hotspots topics in the NPH field. This study aims to analyze the evolution of NPH research, evaluate publications both qualitatively and quantitatively, and summarize the current research hotspots. Methods: A bibliometric analysis was conducted on data retrieved from the Web of Science Core Collection (WoSCC) database between 2003 and 2023. Quantitative assessments were conducted using bibliometric analysis tools such as VOSviewer and CiteSpace software. Results: A total of 2,248 articles published between 2003 and 2023 were retrieved. During this period, the number of publications steadily increased. The United States was the largest contributor. The University of Gothenburg led among institutions conducting relevant research. Eide P. K. was the most prolific author. The Journal of Neurosurgery is the leading journal on NPH. According to the analysis of the co-occurrence of keywords and co-cited references, the primary research directions identified were pathophysiology, precise diagnosis, and individualized treatment. Recent research hotspots have mainly focused on epidemiology, the glymphatic system, and CSF biomarkers. Conclusion: The comprehensive bibliometric analysis of NPH offers insights into the main research directions, highlights key countries, contributors, and journals, and identifies significant research hotspots. This information serves as a valuable reference for scholars to further study NPH.

Comparative analysis of the liver transcriptome in the red-eared slider (Trachemys scripta elegans) post exposure to noise.

Exposure to noise can cause non-auditory health problems and has been widely studied in mammals such as rats and rabbits. However, the non-auditory effects of noise exposure on reptiles (such as red-eared sliders) remain unclear. In this study, we determined the noise exposure-induced transcriptomic changes in the liver of red-eared slider (Trachemys scripta elegans) using Illumina Novaseq6000 sequencing technology. The transcriptome analysis identified 176 differentially expressed genes (DEGs), which were mainly enriched in lipid metabolism. KEGG analysis showed that by affecting the peroxisome proliferator activated receptor (PPAR) signaling pathway these DEGs increased lipid synthesis and decreased lipid oxidation. The Oil Red O staining results validated our data that noise exposure increased hepatic lipid deposition. Thus, noise exposure may lead to lipid accumulation and toxicity, mitochondrial damage, and accelerated oxidative stress. Our findings provide insights into the molecular process underlying non-auditory damage caused by noise exposure in T. scripta elegans.

Visible-Light-Driven Reduction of CO2 to CO with Highly Active and Selective Earth-Abundant Metal Porphyrin-Conjugated Organic Polymers.

The field of artificial photosynthesis, which focuses on harnessing solar light for the conversion of CO2 to economically valuable chemical products, remains a captivating area of research. In this study, we developed a series of photocatalysts based on Earth abundant elements (Fe, Co, Ni, Cu, and Zn) incorporated into 2D metalloporphyrin-conjugated organic polymers known as MTBPP-BEPA-COPs. These photocatalysts were utilized for the photoreduction of CO2 employing only H2O as the electron donor, without the need for any sacrificial agents or precious-metal cocatalysts. Remarkably, all of the synthesized MTBPP-BEPA-COPs exhibited an exceptional CO2 photoreduction performance only irradiated by visible light. Particularly, upon optimizing the metal ion coordinated with porphyrin units, ZnTBPP-BEPA-COP outperformed the other MTBPP-BEPA-COPs in terms of photocatalytic activity, achieving an impressive CO reduction yield of 152.18 µmol g-1 after just 4 h of irradiation. The electrostatic potential surfaces calculated by density functional theory suggest the potential involvement of metal centers as binding and catalytic sites for the binding of CO2. The calculated adsorption energy of CO2 with ZnTBPP-BEPA-COP exhibited one of the two smallest values. This may be the reason for the excellent catalytic effect of ZnTBPP-BEPA-COP. Thus, the present study not only demonstrates the potential of porphyrin-based conjugated polymers as highly efficient photocatalysts for CO2 reduction but also offers valuable insights into the rational design of such materials in the future.

Enhanced Electrochemical Performance of NiMn Layered Double Hydroxides/Graphene Oxide Composites Synthesized by One-Step Hydrothermal Method for Supercapacitors.

This study aims to enhance the performance of supercapacitors, focusing particularly on optimizing electrode materials. While pure NiMn layered double hydroxides (LDHs) exhibit excellent electrochemical properties, they have limitations in achieving high specific capacitance. Therefore, this paper successfully synthesized composite materials of NiMn LDHs with varying loadings of graphene oxide (GO) using a hydrothermal method. Systematic physicochemical characterization of the synthesized materials, such as powder X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), field-emission scanning electron microscopy (FE-SEM), and Raman spectroscopy, revealed the influence of GO doping on the microstructure and electrochemical performance of NiMn LDHs. Electrochemical tests demonstrated that the NiMn LDHs/GO electrode material exhibited optimal electrochemical performance with a specific capacitance of 2096 F g-1 at 1 A g-1 current density and 1471 F g-1 at 10 A g-1, when GO doping level was 0.45 wt %. Furthermore, after 1000 cycles of stability testing, the material retained 53.3 % capacitance at 5 A g-1, indicating good cyclic stability. This study not only provides new directions for research on supercapacitor electrode materials but also offers new strategies for developing low-cost and efficient electrode materials.

A Novel Electrochemical Sensor Based on Pd Confined Mesoporous Carbon Hollow Nanospheres for the Sensitive Detection of Ascorbic Acid, Dopamine, and Uric Acid.

In this study, we designed a novel electrochemical sensor by modifying a glass carbon electrode (GCE) with Pd confined mesoporous carbon hollow nanospheres (Pd/MCHS) for the simultaneous detection of ascorbic acid (AA), dopamine (DA), and uric acid (UA). The structure and morphological characteristics of the Pd/MCHS nanocomposite and the Pd/MCHS/GCE sensor are comprehensively examined using SEM, TEM, XRD and EDX. The electrochemical properties of the prepared sensor are investigated through CV and DPV, which reveal three resolved oxidation peaks for AA, DA, and UA, thereby verifying the simultaneous detection of the three analytes. Benefiting from its tailorable properties, the Pd/MCHS nanocomposite provides a large surface area, rapid electron transfer ability, good catalytic activity, and high conductivity with good electrochemical behavior for the determination of AA, DA, and UA. Under optimized conditions, the Pd/MCHS/GCE sensor exhibited a linear response in the concentration ranges of 300-9000, 2-50, and 20-500 µM for AA, DA, and UA, respectively. The corresponding limit of detection (LOD) values were determined to be 51.03, 0.14, and 4.96 µM, respectively. Moreover, the Pd/MCHS/GCE sensor demonstrated outstanding selectivity, reproducibility, and stability. The recovery percentages of AA, DA, and UA in real samples, including a vitamin C tablet, DA injection, and human urine, range from 99.8-110.9%, 99.04-100.45%, and 98.80-100.49%, respectively. Overall, the proposed sensor can serve as a useful reference for the construction of a high-performance electrochemical sensing platform.

Network analysis reveals context-dependent structural complexity of social calls in serrate-legged small treefrogs.

Vocal communication plays an important role in survival, reproduction, and animal social association. Birds and mammals produce complex vocal sequence to convey context-dependent information. Vocalizations are conspicuous features of the behavior of most anuran species (frogs and toads), and males usually alter their calling strategies according to ecological context to improve the attractiveness/competitiveness. However, very few studies have focused on the variation of vocal sequence in anurans. In the present study, we used both conventional method and network analysis to investigate the context-dependent vocal repertoire, vocal sequence, and call network structure in serrate-legged small treefrogs Kurixalus odontotarsus. We found that male K. odontotarsus modified their vocal sequence by switching to different call types and increasing repertoire size in the presence of a competitive rival. Specifically, compared with before and after the playback of advertisement calls, males emitted fewer advertisement calls, but more aggressive calls, encounter calls, and compound calls during the playback period. Network analysis revealed that the mean degree, mean closeness, and mean betweenness of the call networks significantly decreased during the playback period, which resulted in lower connectivity. In addition, the increased proportion of one-way motifs and average path length also indicated that the connectivity of the call network decreased in competitive context. However, the vocal sequence of K. odontotarsus did not display a clear small-world network structure, regardless of context. Our study presents a paradigm to apply network analysis to vocal sequence in anurans and has important implications for understanding the evolution and function of sequence patterns.

Behavioral responses to predator and heterospecific alarm calls are habitat-specific in Eurasian tree sparrows.

Acoustic communication plays a vital role in predator-prey interactions. Although habitat structure has been shown to affect anti-predator tactics, little is known about how animals vary their behaviors in response to predator calls or heterospecific alarm calls in different environments. Here we used sound playbacks to test the responses of Eurasian tree sparrows (Passer montanus) foraging in harvested/unharvested rice paddy and open residential area. In the first experiment, we tested their behavioral responses to dove calls, male common cuckoo (Cuculus canorus) calls, hawk-like calls mimicked by female common cuckoo, sparrowhawk (Accipiter nisus) calls, and human yell calls produced to scare birds (predator signal playbacks). In the second experiment, we tested their behavioral responses to the Japanese tit's (Parus minor) territorial songs and alarm calls (heterospecific alarm signal playbacks). Results showed that the tree sparrows had less fleeing in unharvested ripe rice paddy than in harvested rice paddy and open residential area. In predator signal playbacks, call type affected the escape behavior of sparrows in unharvested rice paddy and open residential area but not harvested rice paddy. In alarm signal playbacks, tit alarm calls evoked more fleeing than territorial songs in harvested rice paddy and open residential area but not unharvested rice paddy. These results suggest that anthropogenic habitat changes may influence avian anti-predator tactics.

A Machine learning model for predicting sepsis based on an optimized assay for microbial cell-free DNA sequencing.

OBJECTIVE: To integrate an enhanced molecular diagnostic technique to develop and validate a machine-learning model for diagnosing sepsis. METHODS: We prospectively enrolled patients suspected of sepsis from August 2021 to August 2023. Various feature selection algorithms and machine learning models were used to develop the model. The best classifier was selected using 5-fold cross validation set and then was applied to assess the performance of the model in the testing set. Additionally, we employed the Shapley Additive exPlanations (SHAP) method to illustrate the effects of the features. RESULTS: We established an optimized mNGS assay and proposed using the copies of microbe-specific cell-free DNA per milliliter of plasma (CPM) as the detection signal to evaluate the real burden, with strong precision and high accuracy. In total, 237 patients were eligible for participation, which were randomly assigned to either the training set (70 %, n = 165) or the testing set (30 %, n = 72). The random forest classifier achieved accuracy, AUC and F1 scores of 0.830, 0.918 and 0.856, respectively, outperforming other machine learning models in the training set. Our model demonstrated clinical interpretability and achieved good prediction performance in differentiating between bacterial sepsis and non-sepsis, with an AUC value of 0.85 and an average precision of 0.91 in the testing set. Based on the SHAP value, the top nine features of the model were PCT, CPM, CRP, ALB, SBPmin, RRmax, CREA, PLT and HRmax. CONCLUSION: We demonstrated the potential of machine-learning approaches for predicting bacterial sepsis based on optimized mcfDNA sequencing assay accurately.

Accumulation rate and sources of plastic marine litter at nesting grounds of green turtles on the North Island of Qilianyu, Xisha Islands, South China Sea.

In this study, the accumulation rate of plastic litter was investigated by sampling quadrats placed on the North Island of Qilianyu, and the composition was analyzed and identified to determine its source. The results showed that the annual average accumulation rate of plastic litter on North Island was 0.64 ± 0.32 pieces·m-2·month-1, with a mass accumulation rate of 11.30 ± 7.73 g·m-2·month-1. The accumulation rate of plastic litter was mainly influenced by wind speed and direction, with higher accumulation rates occurring during the southwest monsoon season and tropical cyclones. ATR-FTIR analysis indicated that polyethylene (44 %) and polypropylene (41 %) were the most abundant types of polymers. This study reveals the current status of plastic litter pollution in green turtle nesting grounds on North Island in Qilianyu, which can be used as a reference for management strategies that mitigate plastic litter pollution.

Genomic analysis reveals deep population divergence in the water snake Trimerodytes percarinatus (Serpentes, Natricidae).

Although several phylogeographic studies of Asian snakes have been conducted, most have focused on pitvipers, with non-venomous snakes, such as colubrids or natricids, remaining poorly studied. The Chinese keelback water snake (Trimerodytes percarinatus Boulenger) is a widespread, semiaquatic, non-venomous species occurring in China and southeastern Asia. Based on mitochondrial DNA (mtDNA) and single nucleotide polymorphism (SNP) data, we explored the population genetic structure, genetic diversity, and evolutionary history of this species. MtDNA-based phylogenetic analysis showed that T. percarinatus was composed of five highly supported and geographically structured lineages. SNP-based phylogenetic analysis, principal component analysis, and population structure analysis consistently revealed four distinct, geographically non-overlapping lineages, which was different from the mtDNA-based analysis in topology. Estimation of divergence dates and ancestral area of origin suggest that T. percarinatus originated ~12.68 million years ago (95% highest posterior density: 10.36-15.96 Mya) in a region covering southwestern China and Vietnam. Intraspecific divergence may have been triggered by the Qinghai-Xizang Plateau uplift. Population demographics and ecological niche modeling indicated that the effective population size fluctuated during 0.5 Mya and 0.002 Mya. Based on the data collected here, we also comment on the intraspecific taxonomy of T. percarinatus and question the validity of the subspecies T. p. suriki.

Collective effects of rising average temperatures and heat events on oviparous embryos.

Survival of the immobile embryo in response to rising temperature is important to determine a species' vulnerability to climate change. However, the collective effects of 2 key thermal characteristics associated with climate change (i.e., rising average temperature and acute heat events) on embryonic survival remain largely unexplored. We used empirical measurements and niche modeling to investigate how chronic and acute heat stress independently and collectively influence the embryonic survival of lizards across latitudes. We collected and bred lizards from 5 latitudes and incubated their eggs across a range of temperatures to quantify population-specific responses to chronic and acute heat stress. Using an embryonic development model parameterized with measured embryonic heat tolerances, we further identified a collective impact of embryonic chronic and acute heat tolerances on embryonic survival. We also incorporated embryonic chronic and acute heat tolerance in hybrid species distribution models to determine species' range shifts under climate change. Embryos' tolerance of chronic heat (T-chronic) remained consistent across latitudes, whereas their tolerance of acute heat (T-acute) was higher at high latitudes than at low latitudes. Tolerance of acute heat exerted a more pronounced influence than tolerance of chronic heat. In species distribution models, climate change led to the most significant habitat loss for each population and species in its low-latitude distribution. Consequently, habitat for populations across all latitudes will shift toward high latitudes. Our study also highlights the importance of considering embryonic survival under chronic and acute heat stresses to predict species' vulnerability to climate change.

Efectos colectivos del aumento de las temperaturas promedio y los eventos de calor en embriones ovíparos Resumen La supervivencia de los embriones inmóviles en respuesta al incremento de temperatura es importante para determinar la vulnerabilidad de las especies al cambio climático. Sin embargo, los efectos colectivos de dos características térmicas claves asociadas con el cambio climático (i. e., aumento de temperatura promedio y eventos de calor agudo) sobre la supervivencia embrionaria permanecen en gran parte inexplorados. Utilizamos mediciones empíricas y modelos de nicho para investigar cómo el estrés térmico crónico y agudo influye de forma independiente y colectiva en la supervivencia embrionaria de los lagartos en todas las latitudes. Recolectamos y criamos lagartos de cinco latitudes e incubamos sus huevos en un rango de temperaturas para cuantificar las respuestas específicas de la población al estrés por calor crónico y agudo. Posteriormente, mediante un modelo de desarrollo embrionario parametrizado con mediciones de tolerancia embrionaria al calor, identificamos un impacto colectivo de las tolerancias embrionarias al calor agudo y crónico en la supervivencia embrionaria. También incorporamos la tolerancia embrionaria crónica y aguda al calor en modelos de distribución de especies híbridas para determinar los cambios de distribución de las especies bajo el cambio climático. La tolerancia embrionaria al calor crónico (T­crónico) permaneció constante, mientras que la tolerancia al calor agudo (T­agudo) fue mayor en latitudes altas que en latitudes bajas. La tolerancia al calor agudo ejerció una influencia más pronunciada que la tolerancia al calor crónico. En los modelos de distribución de especies, el cambio climático provocó la pérdida de hábitat más significativa para cada población y especie en su distribución de latitudes bajas. En consecuencia, el hábitat para poblaciones en todas las latitudes se desplazará a latitudes altas. Nuestro estudio también resalta la importancia de considerar la supervivencia embrionaria bajo estrés térmico crónico y agudo para predecir la vulnerabilidad de las especies al cambio climático.

Microplastic Distribution Characteristics and Sources on Beaches That Serve as the Largest Nesting Ground for Green Turtles in China.

The threat of microplastics to marine animals and habitats is increasing, which may affect sea turtle nesting grounds. The Qilianyu Islands are the largest remaining green turtle (Chelonia mydas) nesting grounds in China. Despite being far from the mainland, microplastic pollution cannot be ignored. In this study, the level of microplastic pollution in surface sediments from three different zones, namely, the bottom, intertidal, and supratidal zone, was investigated on North Island, Qilianyu Islands. The results showed that the abundance of microplastics in the supratidal zone was significantly higher than that in the bottom zone and intertidal zone (r = 3.65, p = 0.011), with the highest average abundance of microplastics located on the southwest coast of North Island. In the bottom zone, only plastic blocks (88%) and fibers (12%) were found. The main types of microplastics in the intertidal and supratidal zones were plastic blocks (48%) and foam (42%), with polyethylene (PE) (40%) and polystyrene (PS) (34%) being the predominant components. These types and components of microplastics differed from those in the surrounding seawater, but corresponding types and components were found in the plastic debris on the beach. Meanwhile, it was also observed that there were multiple instances of fragmented plastic on the beach. Thus, we suggest that the microplastics on the beach in North Island were mainly derived from the fragmentation of microplastic debris, indicating secondary microplastics. It is recommended to further strengthen the regular cleaning of plastic debris on the beach, especially the removal of small plastic debris, in order to reduce the pollution from secondary microplastics generated by the fragmentation of beach plastic debris and to better protect China's most important sea turtle nesting site in the South China Sea.