Changes In Growth Rate Research Articles

Greening in the middle and high latitudes in the Northern Hemisphere is determined by changes in the growth rate of natural vegetation during the growing season

Natural vegetation is an essential component of terrestrial ecosystems, and its growth has a significant impact on the vegetation greening process. However, the growth rate of natural vegetation throughout the growing season in the Northern Hemisphere's middle and high latitudes (NHMHR) (30°N-90°N) is unknown. Additionally, the mechanics underlying how climatic factors drive changes in vegetation growth rates are unclear. Using the GIMMS normalized difference vegetation index (NDVI) dataset from 1982 to 2015, we examined the growth rate of natural vegetation in the NHMHR (VNDVI, NDVI difference for two consecutive months) and the influence of several climatic conditions (temperature, precipitation, solar radiation) on the development and senescence of natural vegetation. The results showed that (1) from 1982 to 2015, the obvious greening of natural vegetation in the NHMHR was caused mainly by significant increases in VNDVI in June and October (1.34 × 10-4/yr and 8.21 × 10-4/yr, p < 0.01). (2) The slowing of vegetation senescence in October, as well as an increase in defoliation in the final month of the growing season (November), resulted in a significant decline in VNDVI in November (−1.42 × 10-3/yr, p < 0.01). (3) Preseason temperature and precipitation had strikingly varied effects on the VNDVI during vegetation growth in different areas. Preseason temperature controlled the fluctuation in the VNDVI from 50°N to 70°N, whereas preseason precipitation had a greater impact in southeastern North America and western Asia. The significant increase in temperature in October was the main factor that slowed the rate of vegetation senescence. Therefore, when simulating the influence of vegetation on climate change, we should consider climate control on the VNDVI in different seasons. Our results are valuable for measuring how climatic conditions affect vegetation growth and senescence and for systematically clarifying the mechanism of vegetation greening in the future.

Calibration of Sr/Ca Ratio and In Situ Temperature Using Hawaiian Corals

AbstractThe Sr/Ca ratio of modern coral skeletons can record local seawater temperature (T) and is an important tool for reconstructing past environments. However, site‐specific calibrations are required to ensure accurate temperature reconstructions. Here, we examine three modern coral skeletons collected at contrasting sites on the island of Oahu, Hawaii to establish the first accurate calibrations for this region and investigate site specific influences on the calibration process. Satellite T data, which is used for many calibrations, may not be able to derive an accurate thermometer. For our shallow lagoonal sites, satellite T had smaller seasonal T ranges, which resulted in significantly higher slopes of Sr/Ca‐T compared to using in situ T. The traditional age model based on aligning only min/max values can lead to errors in the Sr/Ca‐T calibration due to variable growth rates. An enhanced age model which adds midpoint alignments between the min/max peak values can account for seasonal changes in growth rate and reduce the error. On the same island, site‐ and time period specific conditions can cause notable differences in the Sr/Ca‐T calibrations. The coral from an estuarine embayment showed a high Sr/Ca offset, likely due to high Sr/Ca in ambient seawater. For corals which experienced thermal stress, lower slopes were observed probably due to elevated Sr/Ca values during the period of thermal stress.

Testing of rapid vigor method for sorghum (Sorghum bicolor L. Moench) by using radicle emergence

Sorghum has a higher protein nutrient content (11%) than rice (6.8%) per 100 grams of ingredients. However the development and yield of sorghum is still low. One of the causes of low sorghum production yields is because seed deteriorate rapidly. The deterioration of sorghum seeds during storage signals a low seed vigor. So it is necessary to improve seed vigor tests efficiency in order to shorten test time. The objective of this research are determining observation time of Radicle emergence test and determining correlation between Radicle emergence test results with vigor test and seed viability. The results showed that radicula observations using Radicle emergence method can be carried out after the seeds are germinated for 96 hours at 25 + 2 0C temperature. The second result show there is positive correlation between Radicle emergence value to the vigor test and viability seed such as Vigor Index, Speed of Germination, Germination Seed, Maximum Growth Potential. It means the higher value of Vigor Index, Speed of Germination, Germination Seed, Maximum Growth Potential, the higher Radicle emergence value. The correlation between Radicle emergence and Mean Germination Time and Sprout Growth Rate changes shows a negative correlation.

Quantifying Sub‐Seasonal Growth Rate Changes in Fossil Giant Clams Using Wavelet Transformation of Daily Mg/Ca Cycles

AbstractShells of the giant clam Tridacna can provide decade‐long records of past environmental conditions via their geochemical composition and structurally through growth banding. Counting the daily bands can give an accurate internal age model with high temporal resolution, but daily banding is not always visually retrievable, especially in fossil specimens. We show that daily geochemical cycles (e.g., Mg/Ca) are resolvable via highly spatially resolved laser‐ablation inductively coupled plasma mass spectrometry (LA‐ICPMS; 3 × 33 μm laser slit) in our Miocene (∼10 Ma) specimen, even in areas where daily banding is not visually discernible. By applying wavelet transformation on the measured daily geochemical cycles, we quantify varying daily growth rates throughout the shell. These growth rates are thus used to build an internal age model independent of optical daily band countability. Such an age model can be used to convert the measured elemental ratios from a function of distance to a function of time, which helps evaluate paleoenvironmental proxy data, for example, regarding the timing of sub‐seasonal events. Furthermore, the quantification of daily growth rates across the shell facilitates the evaluation of (co)dependencies between growth rates and corresponding elemental compositions.

Multi-Level Modelling of Global Warming Based on Machine Learning Algorithms

Today, abnormally high temperatures around the world are a wake-up call for global warming. Global warming is a problem that needs to be addressed urgently. In order to assess past temperature changes, this paper constructs indicators of data growth rates over a certain period of time. Firstly, this paper analyses the changes in growth rates after 1800. In addition, this study uses the Mann-Kendall method to determine the trend of the growth rate, and the ridge regression model, ARIMA model, and LSTM model are constructed to predict the future temperature change, respectively. The results show that the LSTM model is the most reliable, whereas the ARIMA model is only suitable for short-term forecasts due to the lack of a follow-up dataset and is less effective in predicting global temperatures below 20°C. The results of the ARIMA model are summarised as follows, with polynomial fitting results being affected by the extremes of the data, and performing the worst. The results show that the temperature will reach 20°C around 2310 and within 2398~2439 according to the ridge regression model and LSTM model, respectively.

Detection, Identification and Diagnostic Characterization of the Staphylococcal Small Colony-Variant (SCV) Phenotype.

While modern molecular methods have decisively accelerated and improved microbiological diagnostics, phenotypic variants still pose a challenge for their detection, identification and characterization. This particularly applies if they are unstable and hard to detect, which is the case for the small-colony-variant (SCV) phenotype formed by staphylococci. On solid agar media, staphylococcal SCVs are characterized by tiny colonies with deviant colony morphology. Their reduced growth rate and fundamental metabolic changes are the result of their adaptation to an intracellular lifestyle, regularly leading to specific auxotrophies, such as for menadione, hemin or thymidine. These alterations make SCVs difficult to recognize and render physiological, biochemical and other growth-based methods such as antimicrobial susceptibility testing unreliable or unusable. Therefore, diagnostic procedures require prolonged incubation times and, if possible, confirmation by molecular methods. A special approach is needed for auxotrophy testing. However, standardized protocols for SCV diagnostics are missing. If available, SCVs and their putative parental isolates should be genotyped to determine clonality. Since their detection has significant implications for the treatment of the infection, which is usually chronic and relapsing, SCV findings should be specifically reported, commented on, and managed in close collaboration with the microbiological laboratory and the involved clinicians.

Prenatal ambient air pollution exposure and child weight trajectories from the 3rd trimester of pregnancy to 2 years of age: a cohort study

BackgroundPrenatal air pollution exposure may increase risk for childhood obesity. However, few studies have evaluated in utero growth measures and infant weight trajectories. This study will evaluate the associations of prenatal exposure to ambient air pollutants with weight trajectories from the 3rd trimester through age 2 years.MethodsWe studied 490 pregnant women who were recruited from the Maternal and Development Risks from Environmental and Social Stressors (MADRES) cohort, which comprises a low-income, primarily Hispanic population in Los Angeles, California. Nitrogen dioxide (NO2), particulate matter < 10 µm (PM10), particulate matter < 2.5 µm (PM2.5), and ozone (O3) concentrations during pregnancy were estimated from regulatory air monitoring stations. Fetal weight was estimated from maternal ultrasound records. Infant/child weight measurements were extracted from medical records or measured during follow-up visits. Piecewise spline models were used to assess the effect of air pollutants on weight, overall growth, and growth during each period.ResultsThe mean (SD) prenatal exposure concentrations for NO2, PM2.5, PM10, and O3 were 16.4 (2.9) ppb, 12.0 (1.1) μg/m3, 28.5 (4.7) μg/m3, and 26.2 (2.9) ppb, respectively. Comparing an increase in prenatal average air pollutants from the 10th to the 90th percentile, the growth rate from the 3rd trimester to age 3 months was significantly increased (1.55% [95%CI 1.20%, 1.99%] for PM2.5 and 1.64% [95%CI 1.27%, 2.13%] for NO2), the growth rate from age 6 months to age 2 years was significantly decreased (0.90% [95%CI 0.82%, 1.00%] for NO2), and the attained weight at age 2 years was significantly lower (− 7.50% [95% CI − 13.57%, − 1.02%] for PM10 and − 7.00% [95% CI − 11.86%, − 1.88%] for NO2).ConclusionsPrenatal ambient air pollution was associated with variable changes in growth rate and attained weight from the 3rd trimester to age 2 years. These results suggest continued public health benefits of reducing ambient air pollution levels, particularly in marginalized populations.

Shifts in intra-annual growth dynamics drive a decline in productivity of temperate trees in Central European forest under warmer climate

Climate change shifts tree growth phenology and dynamics in temperate forests. However, there is still little information on how warming climate changes intra-annual growth patterns and how these changes affect the productivity and carbon uptake of temperate trees. To address this knowledge gap, we used high-precision growth data from automatic dendrometers to quantify the impacts of unusually warm weather in 2022 (hot year) on growth phenology, dynamics and aboveground biomass (AGB) production in eight common temperate species (both conifers and broadleaved) in the Czech Republic. Mixed-effect models were used to investigate inter-annual changes in the start, end, and length of the growing season and intra-annual growth dynamics. We also modelled how changes in growth phenology, growth rates, and tree size affected yearly AGB production of individual trees. In the hot year, the growth started 5 days earlier, peaked 22 days earlier and ended 20 days earlier than in the climatically normal year, resulting in a shorter growing season with fewer growing days. AGB production decreased 36 % in the hot year, mainly due to fewer growing days and lower maximum growth rates, but with significant variation among tested species. The decline in AGB production in the hot year was most significant in the most productive species, which were also the species with the greatest reduction in the number of growing days. Tree size strongly enhanced AGB production, but its effect did not change with climate variation. Our findings suggest that climate change is likely to advance but also shorten the growing season of temperate trees, resulting in lower biomass production and carbon uptake. The results also indicate that the fast-growing and highly productive temperate tree species will have their growth reduced most by climate change, which will increasingly limit their high carbon sequestration potential.

Spatial biology of Ising-like synthetic genetic networks

BackgroundUnderstanding how spatial patterns of gene expression emerge from the interaction of individual gene networks is a fundamental challenge in biology. Developing a synthetic experimental system with a common theoretical framework that captures the emergence of short- and long-range spatial correlations (and anti-correlations) from interacting gene networks could serve to uncover generic scaling properties of these ubiquitous phenomena.ResultsHere, we combine synthetic biology, statistical mechanics models, and computational simulations to study the spatial behavior of synthetic gene networks (SGNs) in Escherichia coli quasi-2D colonies growing on hard agar surfaces. Guided by the combined mechanisms of the contact process lattice simulation and two-dimensional Ising model (CPIM), we describe the spatial behavior of bi-stable and chemically coupled SGNs that self-organize into patterns of long-range correlations with power-law scaling or short-range anti-correlations. These patterns, resembling ferromagnetic and anti-ferromagnetic configurations of the Ising model near critical points, maintain their scaling properties upon changes in growth rate and cell shape.ConclusionsOur findings shed light on the spatial biology of coupled and bistable gene networks in growing cell populations. This emergent spatial behavior could provide insights into the study and engineering of self-organizing gene patterns in eukaryotic tissues and bacterial consortia.

Falling Behind: The Growing Gap in Life Expectancy Between the United States and Other Countries, 1933-2021.

Objectives. To document the evolution of the US life expectancy disadvantage and regional variation across the US states. Methods. I obtained life expectancy estimates in 2022 from the United Nations, the Human Mortality Database, and the US Mortality Database, and calculated changes in growth rates, US global position (rank), and state-level trends. Results. Increases in US life expectancy slowed from 1950 to 1954 (0.21 years/annum) and 1955 to 1973 (0.10 years/annum), accelerated from 1974 to 1982 (0.34 years/annum), and progressively deteriorated from 1983 to 2009 (0.15 years/annum), 2010 to 2019 (0.06 years/annum), and 2020 to 2021 (-0.97 years/annum). Other countries experienced faster growth in each phase except 1974 to 1982. During 1933 to 2021, 56 countries on 6 continents surpassed US life expectancy. Growth in US life expectancy was slowest in Midwest and South Central states. Conclusions. The US life expectancy disadvantage began in the 1950s and has steadily worsened over the past 4 decades. Dozens of globally diverse countries have outperformed the United States. Causal factors appear to have been concentrated in the Midwest and South. Public Health Implications. Policies that differentiate the United States from other countries and circumstances associated with the Midwest and South may have contributed. (Am J Public Health. 2023;113(9):970-980. https://doi.org/10.2105/AJPH.2023.307310).

Assessing future climate trends and implications for managed forests across Canadian ecozones

Climate change interacts with ecological processes leading to changes in tree and forest growth rate, biome shifts and species composition, all of which are influenced by disturbances. This study explores future overarching climate trends of eight of Canada's ecozones containing managed forests. For the 2071 to 2100 period, climate projections indicate a warming trend of up to an additional 5.5 °C and an overall increase in annual precipitation. Future trends suggest marked contrast between coastal and interior forests and polarization between western and eastern forests. Warmer temperatures, accumulating degree-days above 5 °C and frost-free days suggest longer and drier growing seasons and greater risk of drought particularly in moisture-limited areas such as montane cordillera, taiga shield and boreal shield ecozones. Warmer temperatures and rising precipitation combined with less snow suggest shorter and wetter future winters. This indicates greater risk of rain-on-snow and freeze-thaw events, flooding and landslides particularly in coastal ecozones. We discuss how these projections are likely to result in shifts in dominant species and abundance, which when coupled with the cumulative effects of future disturbances, is likely to alter future forest dynamics and impact harvestable wood volumes for Canada's forestry industry.

Unveiling the impact of short-term polyethylene microplastics exposure on metabolomics and gut microbiota in earthworms (Eudrilus euganiae)

Microplastics (MPs) pose a significant environmental concern, particularly for terrestrial fauna. In this study, earthworms were used as a model organism to investigate the ecotoxicological effects of short-term exposure to virgin MPs on changes in metabolome and gut microbiota. High-throughput untargeted metabolomics showed significant internal reactions in the earthworms' metabolic processes due to MPs exposure, even when no visible stress signs, such as changes in growth or mortality rates, were present. Earthworms exposed to different concentrations of polyethylene (PE) MP exhibited significant disruption in 39 and 199 molecular features related to energy and lipid metabolism, anti-inflammatory, cell signaling, and membrane integrity. The activities of enzymes and transport proteins in earthworms were dysregulated when exposed to PE. Changes in the gut microbiota's community structure and complexity were observed in response to PE MPs exposure. Despite the relative stability in alpha-diversity and relative abundance, shifts in beta-diversity and network analysis in the PE-exposed group were indicative of an adaptive response to MPs. Earthworms exhibited resilience or adaptation in response to MPs exposure, potentially maintaining their functionality. This study provides preliminary insights into the impact of MPs on soil invertebrates like earthworms and highlights the need for further exploration of long-term effects and underlying molecular mechanisms.

Importance of the memory effect for assessing interannual variation in net ecosystem exchange

Terrestrial carbon flux shows greater interannual variation (IAV) than the ocean and drives most temporal changes in the atmospheric CO2 growth rate. Accurate estimation of the interannual variation in the terrestrial carbon budget is crucial for predicting changes in the carbon balance of ecosystems and atmospheric CO2 concentrations in the context of climate change. However, the interannual variation simulation of the terrestrial carbon budget has considerable uncertainty. One of the important reasons is the neglect of the memory effect of the ecosystem on climate change, namely the potential lagged impact of climate change. In the present work, we integrated meteorological and remote sensing vegetation data and introduced the memory effect into a deep learning model to simulate the global terrestrial net ecosystem exchange (NEE). The conclusions were as follows: (a) Considering the memory effect not only improved the simulation accuracy of the global terrestrial NEE, R2 increased by 0.37–0.55, RMSE decreased by 38.97%–52.42%, and MAE decreased by 39.77%–52.38%, but also improved the simulation accuracy of the interannual variation of NEE, R2 increased by 0.50–0.84, RMSE decreased by 37.13%–72.07%, and MAE decreased by 40.72%–66.49%. (b) The memory effect of NEE varied by ecosystem type, environmental factors, and plant development phase. The response of NEE to precipitation in most ecosystems was slower than that to temperature and radiation. The length of the comprehensive memory effect of NEE on antecedent environmental variables in the non-growth season was longer than that in the growth season. (c) NEE in the tropics has shown greater interannual variation than that in the high latitudes and dominated interannual variation in global terrestrial NEE. The tropical savanna exceeded tropical forest and contributed the largest fraction of the interannual variation of NEE in the tropics.

How plant roots respond to waterlogging.

Plant submergence is a major abiotic stress that impairs plant performance. Under water, reduced gas diffusion exposes submerged plant cells to an environment that is enriched in gaseous ethylene and is limited in oxygen (O2) availability (hypoxia). The capacity for plant roots to avoid and/or sustain critical hypoxia damage is essential for plants to survive waterlogging. Plants use spatiotemporal ethylene and O2 dynamics as instrumental flooding signals to modulate potential adaptive root growth and hypoxia stress acclimation responses. However, how non-adapted plant species modulate root growth behaviour during actual waterlogged conditions to overcome flooding stress has hardly been investigated. Here we discuss how changes in the root growth rate, lateral root formation, density, and growth angle of non-flood adapted plant species (mainly Arabidopsis) could contribute to avoiding and enduring critical hypoxic conditions. In addition, we discuss current molecular understanding of how ethylene and hypoxia signalling control these adaptive root growth responses. We propose that future research would benefit from less artificial experimental designs to better understand how plant roots respond to and survive waterlogging. This acquired knowledge would be instrumental to guide targeted breeding of flood-tolerant crops with more resilient root systems.

The Placenta: A Maternofetal Interface.

The placenta is the gatekeeper between the mother and the fetus. Over the first trimester of pregnancy, the fetus is nourished by uterine gland secretions in a process known as histiotrophic nutrition. During the second trimester of pregnancy, placentation has evolved to the point at which nutrients are delivered to the placenta via maternal blood (hemotrophic nutrition). Over gestation, the placenta must adapt to these variable nutrient supplies, to alterations in maternal physiology and blood flow, and to dynamic changes in fetal growth rates. Numerous questions remain about the mechanisms used to transport nutrients to the fetus and the maternal and fetal determinants of this process. Growing data highlight the ability of the placenta to regulate this process. As new technologies and omics approaches are utilized to study this maternofetal interface, greater insight into this unique organ and its impact on fetal development and long-term health has been obtained.

Trends in Medicare Reimbursement for Interventional Radiology Procedures: 2007-2020.

Declining physician reimbursement has been occurring across multiple specialties due to changes in Medicare legislation, including theDeficit Reduction Omnibus Reconciliation Act (DRA),the Balanced Budget Act, and the Sustainable Growth Rate. The purpose of this study was to evaluate trends in Medicare reimbursement rates for various procedural classes in interventional radiology from 2007 to 2020. Common interventional radiology procedures were selected across multiple procedural classes: gastrointestinal, biliary, urinary, fallopian dilatation, other injection/change/removal, iliac vascular, femoral/popliteal vascular, tibial/peroneal vascular, hepatobiliary, and vascular emergency. The Physician Fee Schedule Look-Up Tool from the Centers for Medicare & Medicaid Services was queried for current procedural terminology (CPT) codes to extract reimbursement data. All monetary data were adjusted for inflation using the United States consumer price index (CPI). The compound annual growth rate (CAGR) and average annual change in reimbursement were calculated based on these adjusted trends. Aside from urinary and vascular emergency procedures, all other procedural classes experienced decreases in inflation-adjusted Medicare reimbursement from 2007 to 2020. The greatest mean decrease in reimbursement rates was observed in biliary procedures (-$21.25), while the largest mean increase in reimbursement rates was observed in vascular emergency procedures ($3.23). All procedures with increases in reimbursement rates and 36.8% of procedures with decreases in reimbursement rates have a CPT code change between 2007 and 2020. After accounting for inflation, reimbursement rates were shown to decline for all procedural classes except for urinary and vascular emergencies. Congressional policies, such as the Deficit Reduction Act (DRA) and the Medicare Access and Children's Health Insurance Program (CHIP) Reauthorization Act of 2015, may clarify some of these trends.

Comparative bone histology of two thalattosaurians (Diapsida: Thalattosauria): Askeptosaurus italicus from the Alpine Triassic (Middle Triassic) and a Thalattosauroidea indet. from the Carnian of Oregon (Late Triassic)

Here, we present the first bone histological and microanatomical study of thalattosaurians, an enigmatic group among Triassic marine reptiles. Two taxa of thalattosaurians, the askeptosauroid Askeptosaurus italicus and one as yet undescribed thalattosauroid, are examined. Both taxa have a rather different microanatomy, tissue type, and growth pattern. Askeptosaurus italicus from the late Anisian middle Besano Formation of the southern Alpine Triassic shows very compact tissue in vertebrae, rib, a gastralium, and femora, and all bones are without medullary cavities. The tissue shows moderate to low vascularization, dominated by highly organized and very coarse parallel-fibred bone, resembling interwoven tissue. Vascularization is dominated by simple longitudinal vascular canals, except for the larger femur of Askeptosaurus, where simple vascular canals dominate in a radial arrangement. Growth marks stratify the cortex of femora. The vertebrae and humeri from the undescribed thalattosauroid from the late Carnian of Oregon have primary and secondary cancellous bone, resulting in an overall low bone compactness. Two dorsal vertebral centra show dominantly secondary trabeculae, whereas a caudal vertebral centrum shows much primary trabecular bone, globuli ossei, and cartilage, indicating an earlier ontogenetic stage of the specimens or paedomorphosis. The humeri of the thalattosauroid show large, simple vascular canals that are dominantly radially oriented in a scaffold of woven and loosely organized parallel-fibred tissue. Few of the simple vascular canals are thinly but only incompletely lined by parallel-fibered tissue. In the Oregon material, changes in growth rate are only indicated by changes in vascular organization but no distinct growth marks were identified. The compact bone of Askeptosaurus is best comparable to some pachypleurosaurs, whereas its combination of tissue and vascularity is similar to eosauropterygians in general, except for the coarse nature of its parallel-fibred tissue. The cancellous bone of the Oregon thalattosauroid resembles what is documented in ichthyosaurs and plesiosaurs. However, in contrast to these its tissue does not consist of fibro-lamellar bone type. Tissue types of both thalattosaurian taxa indicate rather different growth rates and growth patterns, associated with different life history strategies. The microanatomy reflects different life styles that fit to the different environments in which they had been found (intraplatform basin vs. open marine). Both thalattosaurian taxa differ from each other but in sum also from all other marine reptile taxa studied so far. Thalattosaurian bone histology documents once more that bone histology provides for certain groups (i.e., Triassic Diapsida) only a poor phylogenetic signal and is more influenced by exogenous factors. Differences in lifestyle, life history traits, and growth rate and pattern enabled all these Triassic marine reptiles to live contemporaneously in the same habitat managing to avoid substantial competition.

The genome-scale metabolic model for the purple non-sulfur bacterium Rhodopseudomonas palustris Bis A53 accurately predicts phenotypes under chemoheterotrophic, chemoautotrophic, photoheterotrophic, and photoautotrophic growth conditions.

The purple non-sulfur bacterium Rhodopseudomonas palustris is recognized as a critical microorganism in the nitrogen and carbon cycle and one of the most common members in wastewater treatment communities. This bacterium is metabolically extremely versatile. It is capable of heterotrophic growth under aerobic and anaerobic conditions, but also able to grow photoautotrophically as well as mixotrophically. Therefore R. palustris can adapt to multiple environments and establish commensal relationships with other organisms, expressing various enzymes supporting degradation of amino acids, carbohydrates, nucleotides, and complex polymers. Moreover, R. palustris can degrade a wide range of pollutants under anaerobic conditions, e.g., aromatic compounds such as benzoate and caffeate, enabling it to thrive in chemically contaminated environments. However, many metabolic mechanisms employed by R. palustris to breakdown and assimilate different carbon and nitrogen sources under chemoheterotrophic or photoheterotrophic conditions remain unknown. Systems biology approaches, such as metabolic modeling, have been employed extensively to unravel complex mechanisms of metabolism. Previously, metabolic models have been reconstructed to study selected capabilities of R. palustris under limited experimental conditions. Here, we developed a comprehensive metabolic model (M-model) for R. palustris Bis A53 (iDT1294) consisting of 2,721 reactions, 2,123 metabolites, and comprising 1,294 genes. We validated the model using high-throughput phenotypic, physiological, and kinetic data, testing over 350 growth conditions. iDT1294 achieved a prediction accuracy of 90% for growth with various carbon and nitrogen sources and close to 80% for assimilation of aromatic compounds. Moreover, the M-model accurately predicts dynamic changes of growth and substrate consumption rates over time under nine chemoheterotrophic conditions and demonstrated high precision in predicting metabolic changes between photoheterotrophic and photoautotrophic conditions. This comprehensive M-model will help to elucidate metabolic processes associated with the assimilation of multiple carbon and nitrogen sources, anoxygenic photosynthesis, aromatic compound degradation, as well as production of molecular hydrogen and polyhydroxybutyrate.

Effects of ambient temperature and wind speed on icing characteristics and anti-icing energy demand of a blade airfoil for wind turbine

The icing on wind turbines causes liability issues in cold and humid climate regions with extreme climatic conditions. Accordingly, in this study, numerical simulation is employed to investigate the icing characteristics and anti-icing energy demand of a blade airfoil for wind turbines under various icing conditions. The findings indicate that the distribution range of ice accretion at 268 K is broader than that at 253 K. The maximum water film thickness experiences a significant increase at 6–8 m/s, while exhibiting a slight change at 8–14 m/s for an ambient temperature of 268 K. As the wind speed rises (6–14 m/s), the maximum heat flux demanded for anti-icing increases by 2717 W/m2 and 745 W/m2 for 253 K and 268 K, respectively. The heat flux demanded for anti-icing on the positions (0–0.02 m) of the blade airfoil declines sharply, as the latent heat released by solidification elevates the blade surface temperature. The heat flux demanded for anti-icing on the positions (0.06–0.18 m) of the blade airfoil rises at 6–8 m/s and diminishes at 14 m/s due to the change in growth rate of water film caused by airflow. This research contributes to the development of anti-icing method design for wind turbines.

Partitioning variance in population growth for models with environmental and demographic stochasticity.

How demographic factors lead to variation or change in growth rates can be investigated using life table response experiments (LTRE) based on structured population models. Traditionally, LTREs focused on decomposing the asymptotic growth rate, but more recently decompositions of annual 'realized' growth rates using 'transient' LTREs have gained in popularity. Transient LTREs have been used particularly to understand how variation in vital rates translate into variation in growth for populations under long-term study. For these, complete population models may be constructed to investigate how temporal variation in environmental drivers affect vital rates. Such investigations have usually come down to estimating covariate coefficients for the effects of environmental variables on vital rates, but formal ways of assessing how they lead to variation in growth rates have been lacking. We extend transient LTREs to further partition the contributions from vital rates into contributions from temporally varying factors that affect them. The decomposition allows one to compare the resultant effect on the growth rate of different environmental factors, as well as density dependence, which may each act via multiple vital rates. We also show how realized growth rates can be decomposed into separate components from environmental and demographic stochasticity. The latter is typically omitted in LTRE analyses. We illustrate these extensions with an integrated population model (IPM) for data from a 26 years study on northern wheatears (Oenanthe oenanthe), a migratory passerine bird breeding in an agricultural landscape. For this population, consisting of around 50-120 breeding pairs per year, we partition variation in realized growth rates into environmental contributions from temperature, rainfall, population density and unexplained random variation via multiple vital rates, and from demographic stochasticity. The case study suggests that variation in first year survival via the unexplained random component, and adult survival via temperature are two main factors behind environmental variation in growth rates. More than half of the variation in growth rates is suggested to come from demographic stochasticity, demonstrating the importance of this factor for populations of moderate size.