Patterns Of Temporal Variation Research Articles

Investigation of Near-Infrared Spectroscopy for Assessing the Macroscopic Mechanical Properties of Cross-Linked Polyethylene During Thermal Aging

The present study investigates the relationship between the near-infrared (NIR) spectral characteristics of cross-linked polyethylene (XLPE) insulation materials and their macroscopic properties, with the aim of establishing a reference framework for non-destructive material aging analysis. Accelerated thermal aging tests were conducted on samples of XLPE cables. These samples underwent Fourier-transform infrared spectroscopy (FTIR), elongation at break (EAB), and tensile strength (TS) tests. The temporal variation curves of the carbonyl index (CI), EAB, and TS were obtained at aging temperatures of 105 °C, 135 °C, 155 °C, and 180 °C. Additionally, NIR spectroscopy was performed on the aged XLPE samples, producing absorbance curves corresponding to different aging times at these temperatures. The absorption peaks of ‘C-H (-CH2-)’ (1730 nm/1764 nm) were analyzed to determine their temporal variation patterns. Finally, a correlation analysis was conducted between the NIR results and those of the FTIR, EAB, and TS tests, revealing numerical relationships between NIR characteristic peaks and FTIR, EAB, and TS data. These quantified correlations demonstrate that NIR can effectively represent macroscopic mechanical properties, thereby simplifying the procedures for monitoring material aging and providing valuable results without requiring destructive testing. Results indicate that there is a certain feasibility in replacing traditional cable aging tests with NIR.

Feed efficiency and resilience in dairy ewes subjected to a nutritional challenge.

It is currently uncertain how selection of more efficient animals might impact other traits such as resilience (which, in this context, is defined as the ability of an animal to sustain or revert quickly to its previous production level and health status after a disturbance), especially in small ruminants. However, improving, or at least maintaining, resilience is of utmost importance to ensure livestock production in the face of external perturbances, which are expected to become more prevalent in the near future due to climate change and global instability. This study was conducted to investigate whether a nutritional challenge consisting of animals receiving only 70% of their voluntary feed intake (DMI) for 26 d, might differentially affect the response of high- and low-feed efficiency (FE) sheep. To meet this aim, residual feed intake (RFI), as a proxy of FE, was calculated in 40 lactating ewes fed a total mixed ration ad libitum. Using the RFI values, the ewes with the highest (H-FE; n = 8) and the lowest (L-FE; n = 8) FE were selected and subjected to the nutritional challenge. After the feed restriction, all sheep were again fed ad libitum for a further 25 d. Temporal patterns of variation in animal performance, ruminal fermentation and blood and milk metabolites in response to, and recovery from, the underfeeding were examined in H-FE versus L-FE. More efficient ewes (H-FE) tended to eat less than less efficient ewes (L-FE) for the same level of production. Linear regressions for DMI and milk yield data showed that time-series response to the challenge was comparable in L-FE and H-FE. Despite temporal changes due to underfeeding, both FE divergent groups displayed a similar response to, and recovery from, the challenge with no significant differences in the temporal patterns of variation of the parameters analyzed, except for a tendency to higher plasma glucose in the L-FE ewes. These results challenge the general hypothesis that more efficient animals would be less resilient, but further research is still needed on the relationship and possible trade-offs between high efficiency and resilience.

Trophic diversity of the bloom-forming jellyfish community in the coastal waters of China assessed by stable isotope analysis

A growing realization indicates that the trophic ecology of jellyfish is more diverse than once thought, yet a holistic view reflecting the trophic structure and trophodynamics in bloom-forming jellyfish community remains rare. Based on stable isotope δ13C and δ15N analysis, we estimated the trophic characteristics of common blooms jellyfish Nemopilema nomurai, Cyanea spp., Aurelia coerulea and Aequorea spp. in the coastal waters of China (CWC). Our data indicated that most of the isotopic niche space in the overall planktonic food web was occupied by the bloom-forming jellyfish community. The large spectrum of isotopic niche highlights the diverse ecological roles and potentially broad trophic relevance of these jellyfish in the food web. The substantial trophic diversity of these jellyfish resulted from the various trophic positions occupied by different taxa, complicated niche differentiation and overlap patterns, inconsistent size-based trophic variation, and spatial and temporal variation patterns. Isotopic niche comparisons indicated the presence of niche differentiation, reflecting the difference and individual-specific characteristic in resource exploitation and feeding preference among different jellyfish. Additionally, the inconsistent size-based trophic variation among groups derived from an increase in trophic level with size for Cyanea spp., A. coerulea and Aequorea spp. medusae to no change for N. nomurai medusae, which suggests the complexity in size-related trophic shift patterns within the jellyfish group. Additional diversity also arose from variation in the spatiotemporal structuring of jellyfish trophic ecology, which might be caused by the occurrence of trophic heterogeneity at the base of the planktonic food web. In conclusion, our study characterized the trophic structures of the bloom-forming jellyfish community in the CWC, and revealed their trophic diversity resulting from interspecific, intraspecific (ontogenetic), and spatiotemporal variation. These results hold strong potential to further improve the understanding of the trophic ecology and functional roles of the jellyfish community. Furthermore, this study provides a systematic and valuable isotopic data set, spanning from the food web baseline to zooplanktonic organisms and jellyfish community, against which compare with trophic investigations in future in planktonic food web of the CWC.

Temporal ecological processes have different seasonal influences on multiple dimensions of riverine insect diversity in China

Abstract An understanding of the relative importance of ecological processes affecting biological communities can assist in interpretations of biodiversity patterns. However, the mechanism behind temporal beta diversity, which refers to the dissimilarity between community structures at different times, remains unclear for aquatic insect communities. Therefore, we collected monthly samples of aquatic insects at five sites in streams from July 2011 to June 2012 in Central China. The five sample sites were located in river sections with perennially flowing water, which were subject to little human disturbance. We examined taxonomic‐ and trait‐based temporal beta diversity patterns of riverine insects across seasons in sites. Taxonomic‐ and trait‐based temporal beta diversity demonstrated a decline with species richness but an increase with the time between sampling dates. Taxonomic‐based temporal beta diversity was significantly higher than trait‐based temporal beta diversity. Turnover (i.e. species replacement) was the main driver of taxonomic‐based temporal beta diversity whereas nestedness (i.e. species gain or loss) contributed more to trait‐based temporal beta‐diversity values. In addition, the correlation between taxonomic‐ and trait‐based temporal beta diversity was weak. Deterministic processes (i.e. operating through physico‐chemical factors and climate) and stochastic processes (i.e. operating through temporal variables) are distinct, but they can act together in influencing the temporal beta diversity of riverine insects. Taxonomic‐based temporal beta diversity was more sensitive to environmental changes than trait‐based temporal beta diversity, and taxonomic shift do not necessarily result in trait changes. The main driver of taxonomic‐based temporal beta diversity changed with the location and components analysed. In contrast, stochastic processes were the most dominant influence on trait‐based temporal beta diversity. Results suggest that taxonomic‐ and trait‐based conservation measures should consider both turnover and nestedness patterns in the protection of riverine insects in China and elsewhere. Additionally, the development of integrated monitoring and management protocols that apply across seasons and life stages should be considered.

Links Between Internal Variability and Forced Climate Feedbacks: The Importance of Patterns of Temperature Variability and Change

AbstractUnderstanding the relationships between internal variability and forced climate feedbacks is key for using observations to constrain future climate change. Here we probe and interpret the differences in these relationships between the climate change projections provided by the CMIP5 and CMIP6 experiment ensembles. We find that internal variability feedbacks better predict forced feedbacks in CMIP6 relative to CMIP5 by over 50%, and that the increased predictability derives primarily from the slow (>20 years) response to climate change. A key novel result is that the increased predictability is consistent with the higher resemblance between the patterns of internal and forced temperature changes in CMIP6, which suggests temperature pattern effects play a key role in predicting forced climate feedbacks. Despite the increased predictability, emergent constraints provided by observed internal variability are weak and largely unchanged from CMIP5 to CMIP6 due to the shortness of the observational record.

Climate warming and temporal variation in reproductive strategies in the endangered meadow viper.

Anthropogenic climate change poses a significant threat to species on the brink of extinction. Many non-avian reptiles are endangered, but uncovering their vulnerability to climate warming is challenging, because this requires analyzing the climate sensitivity of different life stages and modeling population growth rates. Such efforts are currently hampered by a lack of long-term life-history data. In this study, we used over 3 decades of mark-recapture data from a natural population of the endangered meadow viper (Vipera ursinii ursinii) to unravel the patterns of temporal variation in reproductive traits, the local climatic determinants of inter-annual variation in reproduction, and the potential buffering effects of life cycle on population growth rate. We found significant inter-annual variation in body growth, gestation length, post-parturition body condition, clutch success, and offspring traits at birth, while reproductive effort showed little temporal variation. Temperature during gestation was the most critical factor, reducing gestation length and increasing both clutch success and post-parturition body condition. In contrast, neither air humidity nor global radiation affected reproductive outcomes. This population had a negative growth rate with minimal temporal variation, indicating a rapid decline largely independent of climatic conditions. Overall, the viper's life-history traits appeared to be buffered against temporal variation in climatic conditions, with this declining population potentially benefiting on the short term from rising local temperatures.

Individual Variability in the Structural Connectivity Architecture of the Human Brain.

The human brain exhibits high degree of individual variability in both its structure and function, which underlies inter-subject differences in cognition and behavior. It was previously shown that functional connectivity is more variable in the hetero-modal association cortex but less variable in the unimodal cortices. Structural connectivity is the anatomical substrate of functional connectivity, but the spatial and temporal patterns of individual variability in structural connectivity (IVSC) remain largely unknown. In the present study, we discovered a detailed and robust chart of IVSC obtained by applying diffusion MRI and tractography techniques to 1724 adults (770 males and 954 females) from multiple imaging datasets. Our results showed that the structural connectivity exhibited the highest and lowest variability in the limbic regions and the unimodal sensorimotor regions, respectively. With increased age, higher IVSC was observed across most brain regions. Moreover, the specific spatial distribution of IVSC is related to the cortical laminar differentiation and myelination content. Finally, we proposed a modified ridge regression model to predict individual cognition and generated idiographic brain mapping, which was significantly correlated with the spatial pattern of IVSC. Overall, our findings further contribute to the understanding of the mechanisms of individual variability in brain structural connectivity and link to the prediction of individual cognitive function in adult subjects.Significance Statement White matter connectivity between grey matter regions plays an important role in integrating information from distributed regions when individuals performing complex cognitive functions. Unique white matter connectivity is the neuroanatomical identity of each individual. The authors systematically explored the spatio-temporal pattern of individual variability in structural connectivity, and the results show higher variability in structural connectivity relates to higher neuroplasticity. In addition, this study reveals that structural connectivity involved in executive function and attention task is different among individuals and highlights the importance of individualized statistical methods for mapping neural pathway of complex cognition.

The solar radiation induced spatiotemporal temperature distribution and time-varying temperature effect in long-span ballastless track continuous beam-arch bridge

The influence of a time-varying temperature environment on the mechanical performance and geometric alignment of long-span ballastless track continuous beam-arch bridge is significant. However, the structural temperature loads are often simplified into a single mode, making it difficult to accurately simulate the evolution of geometric alignment of long-span ballastless track continuous beam-arch bridge under time-varying temperature effects. To explore the spatiotemporal distribution characteristics of temperature fields and the evolution patterns of track geometric alignment in long-span ballastless track continuous beam-arch bridge, a refined analysis model for the time-varying temperature field is established incorporating ray tracing methods and real-time shadow techniques. Combining the temperature experiment results, the spatiotemporal distribution characteristic and evolution patterns of temperature across the bridge system and key sections are explored. Building on this foundation, the evolution of track geometric alignment on the bridge is analyzed, and the measures for controlling track geometric alignment are proposed. The research findings indicate that the surface temperature of the structure undergoes periodic changes throughout the day, and the orientation of the bridge significantly influences the temperature field of the beam-track structure. The vertical displacement extremes of the ballastless track on the bridge are positively correlated with the structural temperature. The track maintenance moments affect the track alignment on the bridge, but the extreme deformation of the ballastless track and the temporal variation pattern of the structural system temperature remain consistent. To minimize irregularities in the ballastless track geometric alignment on the bridge, adjustments to the track position during high-speed railway maintenance window should choose the moments close to the daily average temperature, aiming to decrease the effects of time-varying temperature on track irregularity.

Research on Climate Drivers of Ecosystem Services’ Value Loss Offset in the Qinghai–Tibet Plateau Based on Explainable Deep Learning

As one of the highest and most ecologically vulnerable regions in the world, the Qinghai–Tibet Plateau (QTP) presents significant challenges for the application of existing ecosystem service value (ESV) assessment models due to its extreme climate changes and unique plateau environment. Current models often fail to adequately account for the complex climate variability and topographical features of the QTP, making accurate assessments of ESV loss deviations difficult. To address these challenges, this study focuses on the QTP and employs a modified ESV loss deviation model, integrated with explainable deep learning techniques (LSTM-SHAP), to quantify and analyze ESV loss deviations and their climate drivers from 1990 to 2030. The results show that (1) between 1990 and 2020, the offset index in the eastern QTP consistently remained low, indicating significant deviations. Since 2010, low-value clusters in the western region have significantly increased, reflecting a widening range of ecological damage caused by ESV losses, with no marked improvement from 2020 to 2030. (2) SHAP value analysis identified key climate drivers, including temperature seasonality, diurnal temperature variation, and precipitation patterns, which exhibit nonlinear impacts and threshold effects on ESV loss deviation. (3) In the analysis of nonlinear relationships among key climate drivers, the interaction between diurnal temperature range and precipitation in wet seasons demonstrated significant effects, indicating that the synergistic action of temperature variation and precipitation patterns is critical to ecosystem stability. Furthermore, the complex nonlinear interactions between climate factors exacerbated the volatility of ESV loss deviations, particularly under extreme climate conditions. The 2030 forecast highlights that wet season precipitation and annual rainfall will become key factors driving changes in ESV loss deviation. By combining explainable deep learning methods, this study advances the understanding of the relationship between climate drivers and ecosystem service losses, providing scientific insights for ecosystem protection and sustainable management in the Qinghai–Tibet Plateau.

The sacred and the wild: Unpacking human-wildlife interaction in Indian part of Kailash Sacred Landscape

The negative interaction between humans and wildlife in the Indian Himalayas has increased in recent decades. Studies on human-wildlife negative interactions have primarily focused on protected areas. However, research on such interactions is limited in regions like the Indian part of Kailash Sacred Landscape (KSL), where wildlife and humans share a common space. This study examined the patterns of crop damage, livestock depredation, human fatalities, seasonal and temporal variations, location-specific factors, and critical variables contributing to negative humanwildlife interactions in KSL India. We examined 574 incidences of livestock depredation, 123 incidences of human injury/death between 1984-2016, and 560 crop damage incidences between 2002-2017. Most incidences of human injury/death and livestock depredation were by common leopards, followed by Asiatic black bears. Maize was the highest raided crop (n=202), followed by wheat (n=190) and paddy (n=168). Maximum incidences of crop loss were reported in 2017 (n=76), and the lowest was in 2002 (n=5). The hotspot maps of crop damage and livestock depredation revealed that the negative interaction between humans and wildlife was highest in the southern part of the landscape. The result predicted 195 villages as hotspots in the Indian part of KSL. Villages were identified at the forest range level. We found that 11 villages in Askot, 12 in Munshiyari, 17 in Berinag, 15 in Dharchula, 36 in Didihat, 61 in Gangolihat, and 43 in Pithoragarh forest ranges are severely affected by negative interaction with wildlife.

Habitat Stability Modulates Temporal β-Diversity Patterns of Seagrass-Associated Amphipods Across a Temperate-Subtropical Transition Zone.

Identifying drivers that shape biodiversity across biogeographical regions is important to predict ecosystem responses to environmental changes. While β-diversity has been widely used to describe biodiversity patterns across space, the dynamic assembly of species over time has been comparatively overlooked. Insights from terrestrial and marine studies on temporal β-diversity has mostly considered environmental drivers, while the role of biotic mechanisms has been largely ignored. Here, we investigated patterns of temporal variation in β-diversity of seagrass-associated amphipods. We conducted a study in three biogeographical regions across a temperate to subtropical latitudinal gradient (approximately 2000 km, 13° of latitude in total). In each region, we randomly selected three Cymodocea nodosa meadows, totaling nine meadows sampled seasonally (i.e., four times per year) from 2016 to 2018. We partitioned temporal β-diversity into its turnover (i.e., species replacement) and nestedness (i.e., differences in species composition caused by species losses) components and addressed the relative influence of both temporal variation in habitat structure (i.e., biotic driver) and environmental conditions on the observed β-diversity patterns. Our study revealed high temporal β-diversity of amphipod assemblages across the three biogeographical regions, denoting significant fluctuations in species composition over time. We identified species turnover as the primary driver of temporal β-diversity, strongly linked to temporal variability in local habitat structure rather than to regional climatic drivers. Subtropical Atlantic meadows with high structural stability over time exhibited the largest turnover rates compared with temperate Mediterranean meadows, under lower structural stability, where nestedness was a more relevant component of temporal β-diversity. Our results highlight the crucial role of habitat stability in modulating temporal β-diversity patterns on animals associated with seagrasses, stressing the importance of monitoring variations in habitat structure over time for developing management plans and restoration actions in the context of diversity loss and fragmentation of ecosystems.

A conceptual model explaining spatial variation in soil nitrous oxide emissions in agricultural fields

Soil emissions of nitrous oxide contribute substantially to global warming from agriculture. Spatiotemporal variation in nitrous oxide emissions within agricultural fields leads to uncertainty in the benefits of climate-smart agricultural practices. Here, we present a conceptual model explaining spatial variation in temporal patterns of soil nitrous oxide emissions developed from high spatial resolution measurements of soil nitrous oxide emissions, gross nitrous oxide fluxes, and soil physicochemical properties in two maize fields in Illinois, USA. In sub-field locations with consistently low nitrous oxide emissions, soil nitrate and dissolved organic carbon constrained nitrous oxide production irrespective of changes in soil moisture. In sub-field locations where high emissions occurred episodically, soil nitrate and dissolved organic carbon availability were higher, and increases in soil moisture stimulated nitrous oxide production. These findings form the ‘cannon model’ which conceptualizes how sub-field scale variation in soil nitrate and dissolved organic carbon determines where increases in soil moisture can trigger high soil nitrous oxide emissions within agricultural fields.

Characterizing Long-term Astroclimate Parameters at the Muztagh-Ata Site in the Pamir Plateau with ERA5 and MERRA-2 Data

Abstract The Muztagh-Ata site, an excellent high-altitude ground-based astronomical observing site was discovered and monitored in the eastern part of the Pamir Plateau in the southwestern Xinjiang Uygur Autonomous Region of China. This site has been systematically monitored using various observational parameters since the spring of 2017. Yet, the site lacks long-term monitoring and statistical characterization of key variables such as: precipitable water vapour (PWV) and air temperature. These factors directly influence whether a site is suitable for hosting large ground-based telescopes across optical, infrared, submillimeter, and millimeter wavelengths in later stages. In this study, we utilized atmospheric reanalysis datasets from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) and ERA5, the fifth edition of the European Centre for Medium-Range Weather Forecasts (ECMWF). These datasets were combined with local observations from the weather station at the Muztagh-Ata site. Following the validation of ground-based and satellite data, we conducted a comparative analysis of PWV and temperature trends at the Muztagh-Ata site over a period of 24 years. The weighted annual mean nighttime temperature and PWV increase at rates of 0.18 ∼ 0.38 ○C decade−1 and 0.02 ∼ 0.15 mm decade−1, respectively. The nighttime PWV slightly decrease during the winter with rates of −0.01 ∼ −0.03 mm decade−1. This findings reveal that the PWV and temperature variation patterns at the Muztagh-Ata site are consistently stable, particularly in the results derived from the ERA5 dataset. The comprehensive conditions at this site are highly suitable and advantageous for hosting large optical, infrared, submillimeter, and millimeter wavelengths telescope installations.

Spatial and Temporal Patterns of Grassland Species Diversity and Their Driving Factors in the Three Rivers Headwater Region of China from 2000 to 2021

Biodiversity loss will lead to a serious decline for ecosystem services, which will ultimately affect human well-being and survival. Monitoring the spatial and temporal dynamics of grassland biodiversity is essential for its conservation and sustainable development. This study integrated ground monitoring data, Landsat remote sensing, and environmental variables in the Three Rivers Headwater Region (TRHR) from 2000 to 2021. We established a reliable model for estimating grassland species diversity, analyzed the spatial and temporal patterns, trends of change, and the driving factors of changes in grassland species diversity over the past 22 years. Among models based on diverse variable selection and machine learning methods, the random forest (RF) combined stepwise regression (STEP) model was found to be the optimal model for estimating grassland species diversity in this study, which had an R2 of 0.44 and an RMSE of 2.56 n/m2 on the test set. The spatial distribution of species diversity showed a pattern of abundance in the southeast and scarcity in the northwest. Trend analysis revealed that species diversity was increasing in 80.46% of the area, whereas 16.59% of the area exhibited a decreasing trend. The analysis of driving factors indicated that the changes in species diversity were driven by both climate change and human activities over the past 22 years in the study area, of which temperature was the most significant driving factor. This study effectively monitors grassland species diversity on a large scale, thereby supporting biodiversity monitoring and grassland resource management.

Developmental dynamics of brain network modularity and temporal co-occurrence diversity in childhood

ObjectiveBrain development during childhood involves significant structural, functional, and connectivity changes, reflecting the interplay between modularity, information interaction, and functional segregation. This study aims to understand the dynamic properties of brain connectivity and their impact on cognitive development, focusing on temporal co-occurrence diversity patterns. MethodsWe recruited 481 children aged 6 to 12 years from the Healthy Brain Network database. Functional MRI data were used to construct dynamic functional connectivity matrices with a sliding window approach. Modular structures were identified using multilayer network community detection, and the Dagum Gini coefficient decomposition technique, which uniquely allows for multi-faceted exploration of modular temporal co-occurrence diversities, quantified these diversities. Mediation analysis assessed the impact on small-world properties. ResultsTemporal co-occurrence diversity in brain networks increased with age, especially in the default mode, frontoparietal, and salience networks. These changes were driven by disparities within and between communities. The small-world coefficient increased with age, indicating improved information processing efficiency. To validate the impact of changes in spatiotemporal interaction disparities during childhood on information transmission within brain networks, we used mediation analysis to verify its effect on alterations in small-world properties. ConclusionThis study highlights the critical developmental changes in brain modularity and spatiotemporal interaction patterns during childhood, emphasizing their role in cognitive maturation. These insights into neural mechanisms can inform the diagnosis and intervention of developmental disorders.

Chilling and Forcing Requirements of Wintersweet (Chimonanthus praecox L.) Flowering in China

Numerous studies have reported phenological changes and their driving mechanisms in spring flowering plants. However, there is little research on the shifts of winter flowering phenology and its response to forcing and chilling requirements. Based on the China Phenological Observation Network (CPON) ground observation data from nine sites over the past 20 years, we explored the spatial and temporal variation patterns of flowering plants and their response to chilling and forcing in wintersweet (Chimonanthus praecox L.), a common winter flowering plant species in temperate and subtropical zones of China. We used three chilling models (chilling hour, Utah, and dynamic models) and the growing degree hours (GDHs) model to calculate each site’s daily chilling and forcing. Using the partial least squares (PLSs) regression approach, we established the relationship between the first flowering date (FFD) and pre-season chilling and forcing in wintersweet, based on which we identified chilling and forcing periods and calculated chilling and forcing requirements. This study found that the FFD of wintersweet in China showed an overall advancement trend during the last 20 years. Still, there were temporal and spatial differences in the FFD of wintersweet among different sites. The PLS results showed that wintersweet also had periods of chilling and forcing, both of which co-regulated wintersweet flowering. We found the forcing and chilling requirements of wintersweet varied significantly from site to site. The higher the latitude is, the more chilling requirements are needed. The chilling requirements for wintersweet were about 6.9–34.9 Chill Portions (CPs) and 1.4–21.6 CP in the temperate and subtropical zones, respectively, with corresponding forcing requirements of 3.2–1922.9 GDH and 965.3–8482.6 GDH, respectively. In addition, we found that the temperature requirements of wintersweet were correlated by a negative exponential relationship, suggesting that chilling and forcing requirements have an antagonistic effect on initiating flowering phenology. Our results could help us understand how flowering dates of winter flowering plants respond to climate change.

Application of Sentinel-2 imagery for total suspended solids mapping off the Bodri River, Kendal Regency, Indonesia

Total suspended solids (TSS) is one of the key parameters in water quality monitoring. TSS dynamics off the seas of Bodri River can be observed using Sentinel-2. This research validates Wirasatriya and Laili's algorithm and redevelops a TSS retrieval algorithm based on in situ TSS and Sentinel-2 reflectance (Rrs). During the satellite's passing time, water sampling for TSS was conducted at 64 stations at a depth of 0.5m in October 2023. Bottom of Atmosphere (BoA) Rrs data were obtained from SNAP software, which had previously performed image cropping and resampling. Rrs data from all bands were initially correlated with in situ TSS. The validation results of Wirasatriya and Laili's algorithms obtained very high of RMSE values reaching 272.23 mg/L and 33.08 mg//L. While the results of generating the algorithm produced better the performance of the algorithmic model with RMSE = 7.34 mg/L, MAPE = 14.24%, and bias = 0.99. The development of the algorithms in the study based on the green band (B3) resulted in the equation: TSS (mg/L) = 4.6698exp10.609∗B3, which was further used for temporal mapping. High TSS was found in nearshore areas and river mouths influenced by shallow waters. Temporally, high TSS was found in October (55.65 mg/L) and low in May (11 mg/L). The temporal variation pattern is influenced by precipitation and tides. The findings of this algorithm are very important for analyzing the evolution of land accretion in the Bodri River estuary and as a review for land management in upland areas and can be used to monitor other shallow areas.

Numerical investigation on the combustion characteristics and NOx emission of non-premixed H2/NH3/air in vase-shaped micro combustor

Hydrogen and ammonia, as currently popular zero carbon fuels, have received widespread attention. These two fuels have complementary advantages in combustion characteristics, cost, safety, etc. Based on the vase shaped micro combustor, a new structure proposed for application in micro thermophotovoltaic systems in our previous work. This article numerically investigated the combustion characteristics and NOx emission of non-premixed H2/NH3/Air in vase shaped micro combustor which proposed in our previous work. The variation patterns of flame temperature, wall temperature, flammability limit, and NOx emission with the blended ratio of NH3 and equivalence ratio were obtained. It was found that the flame cannot move and stabilize when the mixing ratio is 0.6. The rate of production (ROP) and sensitivity of NO and N2O were analyzed. Four precursors of NO, HNO, NH, N, N2 have been discovered. Under the conditions of this article, HNO is the key component affecting NO emissions. When the blending ratio is greater than 0.3, the lower reaction rate of HNO leaded to a decrease in NO. The elementary reaction R63: NH + NON2O + H is the key elementary reaction that affects NO consumption and N2O generation. The blending ratio of 0.4 and the equivalence ratio of 1.2 are the optimized operating conditions with the highest comprehensive performance.

Impacts of counting protocols for light microscopy on estimates of biodiversity and algal density of phytoplankton

AbstractKnowledge on the biodiversity and abundance of phytoplankton is key for many ecological and societal (e.g., blue growth) questions. Gathering temporal variation and spatial patterns on key indicators requires reliable and standardized protocols on sampling, species identification and counting. Numerous methods are used but consequences for comparing the biodiversity and abundance of phytoplankton of these different techniques are not well known. We evaluated the consequences of different counting protocols using light microscopy (i.e., subsampling transects or wedges within counting chambers) for these indices using samples collected weekly to bi‐weekly (n = 398, 2009–2018) from the Wadden Sea (southern North Sea). Phytoplankton cells were counted (by one person under similar conditions) in a fixed number of viewing fields (58, 70, and 29) at three respective magnifications (10 × 100, 10 × 40, and 10 × 10). Patterns in the spatial distribution of phytoplankton cells varied among species and clustering of cells occurred in more than one‐fifth of the samples. This will induce error in the conversion from counts (per viewing field) to abundance (cells mL−1). Our present effort resulted in a high accuracy (95%) in overall cell abundances. This was not the case for species richness, for example, capturing 90% of all species present in the sample would require an almost threefold increase in effort for the 10 × 40 and 10 × 10 magnifications. We recommend that counting methods be tailored to the main research objectives and that counting protocols should quantify uncertainty as well as potential bias to provide an estimation of the error in phytoplankton abundance and species composition.

Comparative Study of Temperature and Pressure Variation Patterns in Hydrogen and Natural Gas Storage in Salt Cavern

Clarifying the distribution of temperature and pressure in the wellbore and cavern during hydrogen injection and extraction is crucial for quantitatively assessing cavern stability and wellbore integrity. This paper establishes an integrated flow and heat transfer model for the cavern and wellbore during hydrogen injection and withdrawal, analyzing the variations in temperature and pressure in both the wellbore and the cavern. The temperature and pressure parameters of hydrogen and natural gas within the chamber and wellbore were compared. The specific conclusions are as follows. (1) Under identical injection and withdrawal conditions, the temperature of hydrogen in the chamber was 10 °C higher than that of natural gas, and 16 °C higher in the wellbore. The pressure of hydrogen in the chamber was 2.9 MPa greater than that of natural gas, and 2.6 MPa higher in the wellbore. (2) A comparative analysis was conducted on the impact of surrounding rock’s horizontal and numerical distance on temperature during hydrogen and natural gas injection processes. As the distance from the cavity increases, from 5 to 15 m, the temperature fluctuation in the surrounding rock diminishes progressively, with the temperature effect in the hydrogen storage chamber extending to at least 10 m. (3) The influence of rock thermal conductivity parameters on temperature during the processes of hydrogen injection and natural gas extraction is also compared. The better the thermal conductivity, the deeper the thermal effects penetrate the rock layers, with the specific heat capacity having the most significant impact.