Annual Patterns Research Articles

Investigating the Annual Cross-Correlation between HPF, OWF and BUF Ionospheric Parameters over Middle East Region

In this work various correlation methods were employed to investigate the annual cross-correlation patterns among three different ionospheric parameters: Optimum Working Frequency (OWF), Highest Probable Frequency (HPF), and Best Usable Frequency (BUF). The annual predicted dataset for these parameters were generated using VOCAP and ASASPS models based on the monthly Sunspot Numbers (SSN) during two years of solar cycle 24, minimum 2009 and maximum 2014. The investigation was conducted for Thirty-two different transmitter/receiver stations distributed over Middle East. The locations were selected based on the geodesic parameters which were calculated for different path lengths (500, 1000, 1500, and 2000) km and bearings (N, NE, E, SE, S, SW, W, NW) using a Matlab program that was designed and implemented for this purpose. Depending on the investigation results of the cross-correlation, a third order polynomial equation provides a better representation of the correlation between the tested parameters. Also, the annual values of the HPF, OWF, and BUF parameters were predicted using the proposed mathematical correlation equations. These equations were confirmed by comparing their results with the observed datasets for the studied years. Several statistical methods were used to validate the presented data, all of which gave good results for all tested cases. Also, contour plot diagrams were used to visually illustrate the annual average distribution pattern of the tested ionospheric parameters for all geodetic factors for the minimum and maximum years of Solar Cycle 24.

Temporal and spatial dynamics of the non-indigenous bryozoan, Amathia verticillata, and its associated invertebrate community

The widespread non-indigenous bryozoan, Amathia verticillata primarily colonizes in coastal bays and harbors on anthropogenic structures. Although this habitat-forming bryozoan is widely recognized to house a variety of marine invertebrates within its structure, little is known about their spatiotemporal dynamics and their associated invertebrate community in Southern California, USA. Thus, we undertook a comprehensive yearlong study (July 2021-2022) in an urbanized estuary (Mission Bay, San Diego) to quantify A. verticillata percent cover and abiotic conditions at 6 stations with varying environmental conditions. The seasonal and spatial gradients in temperature and salinity within Mission Bay were as expected with seasonal hypersalinity typical of Mediterranean climate regions. The percent cover of A. verticillata was positively correlated with temperature with the highest percent cover found during the warmest periods, and higher average percent cover found in the warmer, eastern parts of Mission Bay. We also collected three replicate A. verticillata colonies to characterize the marine invertebrate community associated with this non-indigenous bryozoan. We identified 25 families, 24 genera, and 19 organisms to species belonging to the taxonomic groups: amphipods, isopods, tanaids, and polychaetes. Furthermore, we identified juvenile stages and ovigerous females living within A. verticillata. None of the identified invertebrate families contributed more than 21 % to the community. The seasonal growth and annual temporal patterns of A. verticillata may prevent competitively dominant species from becoming established within the invertebrate community and allow A. verticillata to harbor a diverse invertebrate community. Sphaeromatidae isopods were the most common family found in the bryozoan colonies, likely reflecting their broad environmental tolerances. Additionally, while some of the invertebrates found within A. verticillata were also non-indigenous species, more work needs to be done to determine if A. verticillata disproportionately supports these species over native species. Collectively, our results imply that A. verticillata functions as a nursery habitat on anthropogenic structures for peracarid crustaceans and polychaetes. Furthermore, A. verticillata assemble analogous communities across their distribution, which may indicate that invasions are homogenizing biota globally.

Seasonal Variations in the Thermal Stratification Responses and Water Quality of the Paldang Lake

We evaluated the thermal and chemical stratifications of Paldang Lake using Schmidt’s stability index (SSI) and the chemical stratification index (IC-i) with weekly data from 2013 to 2022. The temporal trends of stratification were analyzed alongside correlations with meteorological, hydrological, and water quality variables. Thermal stratification intensified with rising air temperature and sunshine duration, while hydrological factors like discharge and retention time affected SSI during periods with less than five days of water retention. During summer, fewer occurrences of intense rainfall or early rainfall before August led to stronger stratification. In fall, nutrient influx from external sources during summer stimulated algal growth, increasing Chlorophyll-α (Chl-α) concentrations. Summer rainfall had a significant impact on the strength and duration of stratification in Paldang Lake. Annual rainfall patterns and subsequent changes in discharge were key factors affecting the physical environment of the lake, which in turn determined water quality and the extent of algal blooms. We provide insights into the seasonal stratification and water quality variations in temperate river-type reservoirs like Paldang Lake. SSI and IC-i from this research can be applied to understand stratification and mixing dynamics in other lakes.

When are you measuring soil β‐glucosidase activities in cropping systems?

AbstractIn situ soil respiration is driven by annual patterns of temperature and soil moisture, but what about extracellular enzyme activities responsible for depolymerizing soil organic matter? We conducted biweekly measurements of potential soil β‐glucosidase activities during a 4‐month period from March soil thawing through July in annually cropped field plots in eastern South Dakota. Our objective was to determine the best sampling time to resolve the effects of crop rotational diversity on soil microbial activities. Potential β‐glucosidase activities were elevated immediately following soil thaw, peaked in May, and declined to their lowest value in mid‐summer. Temperature and precipitation had no value in predicting enzyme activities; however, enzyme activities were affected by crop rotational diversity and responded to current crop and previous crop. These findings are pertinent to the use of soil extracellular enzymes in soil health assessments and as indicators of microbial substrate preference with implications for soil carbon stabilization.

Metamorphosing forex: advancements in volatility forecasting using a modified fuzzy time series framework

The interplay of exchange rates among nations significantly influences both international and domestic trade, underscoring the pivotal role of the foreign exchange market (Forex) in a country's economic landscape. Forex fluctuations have a significant impact on the everyday lives of both government agencies and the public population, directly influencing a country's prosperity or misfortune. This work proposes an advanced fuzzy time series model that incorporates domain universe sub-partitioning, parameter adjustment optimization methodologies, and interval forecasting methods. We utilized this model to examine annual exchange rate patterns between the Pakistani rupee (PKR) and the US dollar (US$), comparing its forecast accuracy to that of other models. Our proposed methodology outperformed existing methodologies in terms of forecasting precision, providing stakeholders with valuable insights for making informed, data-driven business decisions that benefit both individual firms and the country overall.

Сезонная динамика липидов тканей двустворчатого моллюска Cerastoderma glaucum псевдолиторальной зоны

Cerastoderma glaucum is a bivalve mollusk that inhabits the supralittoral zone of the Black Sea. It is a potential object of commercial aquaculture, which makes its lipid profile and adaptation mechanisms a prospective research topic. The authors analyzed the annual patterns in total lipids, phospholipids, polyglycerides, diglycerides, sterols, free fatty acids, and triacylglycerides to obtain the fatty acid profile of C. glaucum, harvested from the supralittoral zone of the upper Kazachya Bay, Sevastopol, Russia. The mollusks were collected in the winter, spring, and autumn of 2021–2022. This research featured their gills, foot, and hepatopancreas. An integrated methodological approach was used to d etermine total lipids, classify them, and study fatty acids. The total lipid level was 2.4–15.1 g/100 g raw weight. During the year, the dynamics of total lipids in the tissues of foot and gills varied from the highest values in the spring (9.6 ± 1.6 and 4.9 ± 1.9 g/100 g raw weight, respectively) to the lowest in the autumn (5.5 ± 0.5 and 2.5 ± 0.4 g/100 g raw weight, respectively). In the hepatopancreas, it peaked the winter and dropped in the autumn (19.4 ± 1.9 and 2.9 ± 0.4 g/100 g raw weight, respectively). In the winter, all tissue samples demonstrated a significant decrease in triacylglycerides. The composition of fatty acids and total lipids in all tissues included 23 types, i.e., nine saturated (35–40%), eight monounsaturated (15–34%), and six polyunsaturated (5.8–29%) from the families of omega-3, 5, 6, 7, 9, 11, and 13. Palmitic and oleic acids were among the dominant fatty acids. Seasonal dynamics of lipids in the samples of foot, gills, and hepatopancreas of C. glaucum revealed some general patterns. In the spring, total lipids peaked while structural and storage lipids had a uniform distribution. In the autumn and winter, total lipids went down whereas structural lipids increased. The fatty acid profile of C. glaucum from the supralittoral zone of the Black Sea differed from those of the same species from o ther regions.

PreciDBPN: A customized deep learning approach for hourly precipitation downscaling in eastern China

Long-term series of high-resolution gridded precipitation datasets are essential for hydrological and meteorological research. Producing high-resolution precipitation data from regional models demands substantial computational resources and labor. Global Reanalyses offer long-term coverage and effectively capture annual and seasonal precipitation patterns. However, they have inadequate resolution and frequently have difficulties depicting extreme conditions. This study proposes an efficient and accurate approach for generating long-term series of high spatial and temporal resolution precipitation. It is achieved by leveraging deep learning techniques to integrate the fifth generation of the European Centre for Medium-Range Weather Forecasts (ECMWF) global climate reanalysis (ERA5, 0.25°, hourly) data with high-resolution precipitation fusion datasets. Considering the heavy-tailed distribution of precipitation, we developed the PreciDBPN model structure, which combines a classification network with a super-resolution network and incorporates physically relevant indices into the model's input. We trained and evaluated the PreciDBPN and baseline models in eastern China using the China Meteorological Administration Land Data Assimilation System (CLDAS) precipitation dataset (0.0625°, hourly, 2017–2022). When compared to baseline methods and ERA5, our model excels in multiple metrics and provides a more precise representation of relative rainfall frequency. Independent verification was performed using station observations during the period of 2010–2015 when CLDAS data were unavailable. During this verification, the PreciDBPN demonstrated exceptional performance and greater robustness compared to the baseline models. Because our method can efficiently downscale precipitation and bias-correct reanalysis data using minimal computational resources, it can be used to generate high-resolution precipitation datasets (0.0625°, hourly) from 1979 to 2022 while correcting for heavy precipitation underestimations in reanalysis data.

Exploring patterns of surface urban heat island intensity: a comparative analysis of three Greek urban areas

One of the most pressing issues of our time is the destabilization of the global climate as a result of rapid urbanization. In Europe, according to United Nations reports, almost 73% of the population lives in cities and this percentage is expected to rise to 85% by 2050 (United Nations and Department of Economic and Social Affairs, ‘World Urbanization Prospects 2018 Highlights’, 2018). This observed urban development and its trends pose significant challenges to our urban environments, therefore it is critical to improve our understanding and assess its impact by measuring and analyzing its patterns. This study presents a comprehensive five-year analysis of microclimatic parameters that can contribute to this analysis, such as land surface temperature (LST) and surface urban heat island (SUHI) intensity, using remotely sensed data over three cities in Greece. Specifically, the selected cities are the city of Thessaloniki, which is the second largest city situated in the northern part of Greece, the city of Larissa on the mainland, and finally the city of Tripoli in the Peloponnese peninsula in southern Greece. Each city represents urban areas with different physical and urban characteristics. For this purpose, the vegetation index-based technique for LST extraction was applied within the Google Earth Engine (GEE) platform. Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) calculations were also performed over a five-year period. The results highlighted the spatio-temporal variations and trends that occur in the studied urban areas, providing valuable insights into the annual patterns of the SUHI phenomenon in different geographical contexts within Greece. This is particularly relevant in countries like Greece, where the density of World Meteorological Organization (WMO) stations providing reliable temperature data is low, usually limited to one per city. Consequently, LST derived from satellite data can provide more accurate intra-urban results of the SUHI effect, demonstrating the value of remotely sensed data as a cost effective and supportive tool for decision-making in environmental and urban planning policies.

Intercomparison of multisource actual evapotranspiration satellite products in Bilate watershed, Ethiopia

Recent advancements in satellite remote sensing have led to increased spatial and temporal resolution of actual evapotranspiration (AET) estimates across scales. Yet, the accuracy of AET products remains unknown for many regions, prompting further investigation to guide selection. This study intercompares five AET products within Ethiopia’s Bilate watershed, focusing on the 2009-2018 period. The products assessed include TerraClimate, Food and Agriculture Organization Water Productivity (FAO WaPOR), Moderate Resolution Imaging Spectroradiometer Operational Simplified Surface Energy Balance (ModisSSEBop), and Synthesis of Global AET. Reference evapotranspiration estimated using ground station climate data served as a basis for comparing the Satellite Products (SP). The intercomparison was conducted using descriptive statistics, scatter plots and Pearson’s Correlation Coefficient to assess correlation, standard deviation, and root mean square error. Additional error statistics were also considered. Findings reveal higher AET values in the highlands compared to the lowlands of the Bilate watershed. A weak correlation (<0.35) exists between ETo and satellite-derived AET, potentially due to the averaging of AET values across diverse land cover classes, contrasting with point-scale reference measurements. The variance among AET products was varied across seasons and elevation ranges. While the annual patterns of AET were consistent across the products, large discrepancies in magnitude (average AET varies from 25 to 83 mm per month in the lower part) were detected. The ModisSSEBop global and continental products showed minimal mismatches, whereas the Synthesis of Global and FAO WaPOR products displayed slight differences. Notably, the FAO WaPOR’s AET estimates showed relatively closer agreement with many products in terms of magnitude and variability of AET. In conclusion, the study highlights significant random and systematic differences between the AET products. The substantial mismatch between the products underscores the necessity for continued research to refine AET product accuracy through improved input dataset and revisiting the algorithms.

An annual result of outdoor and indoor PM 2.5 analysis in two different building types in Ulaanbaatar, Mongolia.

Air pollution has been a significant environmental and public health concern in Ulaanbaatar, the capital city of Mongolia, for many years. The city experiences severe air pollution, particularly during the winter months. This study investigated the annual trends of outdoor and indoor PM2.5 concentrations at two neighboring sites in Ulaanbaatar: an office and a household, using low-cost sensors. Both locations exhibited similar fluctuations in outdoor PM2.5 concentrations over time, with ambient PM2.5 levels beginning to rise in October and declining in April. During the mid-term of the heating season (November to February), hourly averaged PM2.5 concentrations were exceptionally high, with peak pollution events exceeding ~ 1000µg/m3. Notably, PM2.5 concentrations were elevated during this heating season period. Time-activity patterns showed a decrease in PM2.5 concentrations during the periods of 06:00-08:00 and 14:00-18:00. Furthermore, the study found that the indoor environment could remain safe when windows were well-sealed, even under severe outdoor pollution conditions. Overall, this study provided accurate insights into the annual patterns of PM2.5 concentrations and demonstrated their fluctuations during the heating season when pollution levels were particularly high. The findings offer valuable recommendations for individuals to consider when going outside and for taking actions to improve indoor air quality in Ulaanbaatar.

Increased global warming potential during freeze-thaw cycle is primarily due to the contribution of N2O rather than CO2

While freeze-thaw cycle (FTC) can influence greenhouse gas emissions, the specific greenhouse gas that responds most strongly to FTC, as well as the underlying mechanisms, remain unclear. Here, we conducted a meta-analysis to explore the responses of global warming potential (GWP) and the fluxes of CO2 and N2O to FTC. Our results showed that FTC treatment significantly increased GWP, N2O flux, cumulative GWP, and cumulative N2O emissions by 23.1 %, 53.2 %, 14.5 %, and 164.6 %, respectively, but did not affect CO2 flux, indicating that the enhanced GWP during the FTC period may be primarily due to the contribution of N2O flux rather than CO2 flux. The responses of GWP (+68.6 %), CO2 (+21.0 %), and N2O fluxes (+136.3 %) in croplands was higher than those in other ecosystems, exhibiting a strong dependence on ecosystem types. The effect size of FTC treatment on greenhouse gas emissions escalated with decreasing freezing temperature and diminished with increasing FTC frequency. Moreover, mean annual temperature (MAT) and FTC patterns were key factors influencing GWP during the FTC period. These findings provide critical insights into the variations in greenhouse gas emissions due to FTC and its influencing factors, allowing for more accurate predictions of the future impact of global climate change on GWP.

Annual patterns of body, tissue, and organ mass variation in long-tailed ducks Clangula hyemalis

Temporal variation in resource availability, physiological demands, and other factors are associated with many phenotypic changes in organisms. For example, there are often predictable stages of atrophy and hypertrophy in animals’ organs to accommodate changes in diet. Timing of stages may differ by sex given differences in life histories (e.g., egg-laying versus male–male competition). In this context, we quantified changes over the annual cycle in 153 long-tailed duck ( Clangula hyemalis) carcasses. We also tested whether timing of changes differed by sex. Total body mass was lowest in February and highest in November, whereas livers, spleens, kidneys, and salt glands were lightest in the middle of breeding seasons. Reductions in kidney and salt gland masses coincided with switches to using freshwater from marine habitats. Generally, timing in patterns of body mass change did not differ by sex. This was unexpected, and could arise from the compressed breeding season. We were also interested in evaluating whether changes in masses of tissues or organs were more dramatic for a species that breeds at such high latitudes than for species that breed at lower latitudes, but were unable to glean this information from the literature. We present coefficients of variation to facilitate future comparisons.

Quantifying urban climate response to large-scale forcing modified by local boundary layer effects

Over the past two decades, the joint manifestation of global warming and rapid urbanization has significantly increased the occurrence of heatwaves and the formation of urban heat islands in temperate cities. Consequently, this synergy has amplified the frequency and duration of periods with tropical nights (TNs) in these urban areas. While the occurrences of such extreme events demonstrate irregular and nonlinear annual patterns, they consistently manifest a discernible rising decadal trend in local or regional climatic data. In urban regions situated amidst hilly or mountainous landscapes, changing wind directions—often associated with uphill or downhill thermal flows—profoundly impact the spread and dispersion of heat-related pollution, creating unique natural ventilation patterns. Using the Lausanne/Pully urban area in Switzerland as examples of hilly and lakeshore temperate cities, this study explores the influence of wind patterns and natural urban ventilation on the nonlinearity of recorded climatic data within an urban environment. This study integrates a mesoscale numerical weather prediction model (COSMO-1), a microscale Computational Fluid Dynamics (CFD) model, field observations, variational mode decomposition technique, and statistical analysis to investigate how wind speed and direction critically influence the nonlinearity of recorded long-term trends of extreme events, specifically focusing on the frequency and duration of TNs in lakeshore and hilly cities. The results strongly indicate a direct correlation between the frequency of TNs and the occurrence of specific moderate wind patterns. These wind patterns are exclusively captured by the microscale CFD model, unlike the mesoscale model, which neglects both urban morphology and complex hilly terrains. The impact of temporal and spatial variability of the wind field on long-term observations at fixed measurement stations suggests that caution should be exercised when relying on limited spatial measurement points to monitor and quantify long-term urban climate trends, particularly in cities located in complex terrains.

Evaluation of the PM2.5 concentrations in South America: Climatological patterns and trend analysis

This study assessed the concentration of particulate matter with an aerodynamic diameter of 2.5 (PM2.5) over South America (SA) based on climatological patterns and trend analysis. This study used monthly PM2.5 data from the Copernicus Atmosphere Monitoring Service (CAMS) at the European Centre for Medium-range Weather Forecasts from 2003 to 2022. The bilinear interpolation method was applied to the data resampling from 0.75° × 0.75°–0.25° × 0.25° spatial resolution, and subsequently, the climatological analysis was performed on seasonal and annual scales of PM2.5 concentrations for the 20-year series. The assessment comprised three main stages: 1) descriptive statistics, 2) seasonal and annual climatology patterns, and 3) trend analysis (Mann-Kendall - MK and Pettitt tests). Results indicated that the largest annual PM2.5 concentrations were found in the Amazon region and northern Paraguay due the El-Niño South Oscillation events (2003–2005, 2007, 2010, 2020, and 2022). The annual average PM2.5 concentrations exceeded the WHO recommended limit (5 μg m−3), ranging from 15.57 μg m−3 (1999) and 22.74 μg m−3 (2007 and 2010). The highest PM2.5 concentrations were observed in the Amazon and Chile (Santiago), reaching 160.4 μg m−3 annually and 177.8 μg m−3 seasonally (spring). Elevated seasonal PM2.5 concentrations were attributed to increased deforestation and wildfires associated with meteorological systems such as the Bolivian high and subtropical jets during dry periods (winter and spring). The MK test revealed a significant reduction in PM2.5 concentrations between 2003 and 2022, observed in Argentina (north), Brazil (arc of reforestation), Bolivia (south), and Chile (north). Reduction values varied between 0.5 and 10 μg m−3.year−1 annually and during winter, attributed to no-tillage practices in regions cultivating commodities. The Pettitt test also identified significant structural changes occurring in 2006–2008 and 2010–2011, aligning with areas highlighted in the MK test. This study provides valuable insights for air quality and environmental monitoring managers to mitigate PM2.5 pollution in SA.

Annual and Seasonal Patterns of Dietary Intake in Australian Adults: A Prospective Cohort Study.

Poor diet is a major risk factor for non-communicable disease. The aims of this study were to describe temporal patterns and seasonal changes in diet across the year in Australian adults. A total of 375 adults from a prospective cohort study conducted between 1 December 2019 and 31 December 2021 in Adelaide, Australia, were asked to complete the Dietary Questionnaire for Epidemiological Studies at eight timepoints over a year. Average intakes over the previous month of total energy, macronutrients, healthy food groups, and discretionary foods and beverages were derived. Temporal patterns in diet were analysed descriptively. Multilevel linear regression modelling was used to assess seasonal differences in diet. Of the 375 participants recruited, 358 provided sufficient data for analysis. Intake of total energy, all macronutrients, and most discretionary foods and beverages peaked in December. Total energy intake was higher in summer than in autumn, winter, and spring. Fruit intake was higher in summer than in winter. Consumption of alcoholic beverages was higher in summer than in autumn, winter, and spring. Consumption of non-alcoholic beverages was higher in summer than in autumn and winter. This study identified temporal differences in dietary intake among Australian adults. Seasonal effects appear to be driven largely by increases in consumption of foods and beverages over the December (summer) holiday period. These findings can inform the design and timing of dietary interventions.

Using quantile mapping and random forest for bias‐correction of high‐resolution reanalysis precipitation data and CMIP6 climate projections over Iran

AbstractClimate change is expected to cause important changes in precipitation patterns in Iran until the end of 21st century. This study aims at evaluating projections of climate change over Iran by using five climate model outputs (including ACCESS‐ESM1‐5, BCC‐CSM2‐MR, CanESM5, CMCC‐ESM2 and MRI‐ESM2‐0) of the Coupled Model Intercomparison Project phase 6 (CMIP6), and performing bias‐correction using a novel combination of quantile mapping (QM) and random forest (RF) between the years 2015 and 2100 under three shared socioeconomics pathways (SSP2‐4.5, SSP3‐7.0 and SSP5‐8.5). First, bias‐correction was performed on ERA5‐Land reanalysis data as reference period (1990–2020) using the QM method, then the corrected ERA5‐Land reanalysis data was considered as measured data. Based on the corrected ERA5‐Land reanalysis data (1990–2020) and historical simulations (1990–2014), the future projections (2015–2100) were also bias‐corrected utilizing the QM method. Next, the accuracy of the QM method was validated by comparing the corrected ERA5‐Land reanalysis data with model outputs for overlapping years between 2015 and 2020. This comparison revealed persistent biases; hence, a combination of QM‐RF method was applied to rectify future climate projections until the end of the 21st century. Based on the QM result, CMCC‐ESM2 revealed the highest RMSE in both SSP2‐4.5 and SSP3‐7.0 amounting to 331.74 and 201.84 mm·year−1, respectively. Particularly, the exclusive use of the QM method displayed substantial errors in projecting annual precipitation based on SSP5‐8.5, notably in the case of ACCESS‐ESM1‐5 (RMSE = 431.39 mm·year−1), while the RMSE reduced after using QM‐RF method (197.75 mm·year−1). Obviously, a significant enhancement in results was observed upon implementing the QM‐RF combination method in CMCC‐ESM2 under both SSP2‐4.5 (RMSE = 139.30 mm·year−1) and SSP3‐7.0 (RMSE = 151.43 mm·year−1) showcasing approximately reduction in RMSE values by 192.43 and 50.41 mm·year−1, respectively. Although each bias‐corrected model output was evaluated individually, multi‐model ensemble (MME) was also created to project the annual future precipitation pattern in Iran. By considering that combination of QM‐RF method revealed the lower errors in correcting model outputs, we used the QM‐RF technique to create the MME. Based on SSP2‐4.5, the MME climate projections highlight imminent precipitation reductions (>10%) across large regions of Iran, conversely projecting increases ranging from 10% to over 20% in southern areas under SSP3‐7.0. Moreover, MME projected dramatic declines under SSP5‐8.5, especially impacting central, eastern, and northwest Iran. Notably, the most pronounced possibly decline patterns are projected for arid regions (central plateau) and eastern areas under SSP2‐4.5, SSP3‐7.0 and SSP5‐8.5.

Bacterial ecology and evolution converge on seasonal and decadal scales.

Ecology and evolution are often viewed as distinct processes, which interact on contemporary time scales in microbiomes. To observe these processes in a natural system, we collected a two-decade, 471-sample freshwater lake time series, creating the longest metagenome dataset to date. Among 2,855 species-representative genomes, diverse species and strains followed cyclical seasonal patterns, and one in five species experienced decadal shifts in strain composition. The most globally abundant freshwater bacterium had constant species-level abundance, but environmental extremes appeared to trigger a shift in strain composition and positive selection of amino acid and nucleic acid metabolism genes. These genes identify organic nitrogen compounds as potential drivers of freshwater responses to global change. Seasonal and long-term strain dynamics could be regarded as ecological processes or equivalently as evolutionary change. Rather than as distinct processes that interact, we propose a conceptualization where ecology and evolution converge along a continuum to better describe change in diverse microbial communities.

The evolution of financial technology: A comprehensive bibliometric review of robo-advisors

This bibliometric study delves into the rapidly evolving domain of robo-advisors—digital platforms that offer automated, algorithm-driven financial planning services with minimal human intervention. Utilizing a robust dataset extracted from Scopus, the research employs the PRISMA flow chart methodology for meticulous screening, inclusion, and exclusion of relevant studies. Advanced bibliometric analysis tools such as Biblioshiny, VOSviewer, and CiteSpace are employed to conduct the analysis, facilitating a multifaceted examination of the literature. The findings of this study are extensive and informative, covering various aspects of the research on robo-advisors. It highlights the annual scientific production, identifying trends and growth patterns within the field. The study also spotlights the most productive authors and sources, shedding light on the leading contributors to the discourse on robo-advisors. Furthermore, it provides insights into the most globally cited documents, author cocitations, and keyword co-occurrences, revealing the core themes and discussions shaping this area of study. Significantly, the research identifies keywords with the strongest citation bursts and offers network visualizations of cited authors, showcasing the dynamic interactions within the academic community. Timezone and timeline views of cited journals and country collaborations offer a geographical and temporal perspective on the research landscape. Through these analyses, the study uncovers identified research gaps and practical implications, guiding future investigations and the practical application of robo-advisors in the financial industry.

A diagnostic approach to modeling watersheds with human interference

Most watersheds have human impacts that modify hydrological responses differently over a range of timescales. However, these impacts are not accounted for in most hydrological models. Human impacts in watersheds are diverse and case specific, unlike natural hydrologic processes. Incorporating all plausible human impacts comes at a high data acquisition and modeling cost. This raises the question, which human impacts do we need to incorporate to represent observed streamflow patterns at different timescales? To answer this question, we develop a diagnostic approach to modeling watersheds with human interference. This mixed methods approach is informed by the case history and builds on the top-down hydrological modeling approach where process complexity is incrementally added with changing timescales to identify and respond to changing dominant hydrological processes in a given watershed. Here we implement this modeling approach in the East Fork watershed in California, USA for which data on changes in water imports, withdrawals, irrigation and agriculture land cover is available from the early 1940′s, making it an ideal demonstration case. In the East Fork watershed, we find that incorporation of water imports and rights are sufficient to replicate annual patterns of runoff variability, and that adding crop water demand and irrigation enables replication of monthly and daily patterns, while incorporation of groundwater pumping results in negligible improvements. To demonstrate the capabilities of the diagnostic approach in and beyond this case we conducted two computational experiments: checking for needed model structural change and exploring a counterfactual scenario of intensified agriculture.

Care Patterns and Barriers to Outpatient Care for Adults With AML Following Intensive Chemotherapy at NCCN Member Institutions.

Prolonged hospitalization following intensive (re)induction chemotherapy for acute myeloid leukemia (AML), while standard, is costly and resource intense, limits inpatient bed capacity, and negatively impacts quality of life. Early hospital discharge (EHD) following completion of chemotherapy has proven safe as an alternative at select institutions, but is not widely implemented. From February 2023 through May 2023, the NCCN Best Practices Committee conducted a survey evaluating AML hospitalization patterns, care models, and barriers to EHD at its 33 member institutions. A total of 30 (91%) institutions completed the survey; two-thirds treat >100 patients with AML annually and 45% treat more than half of these with intensive chemotherapy. In the (re)induction setting, 80% of institutions keep patients hospitalized until blood count recovery, whereas 20% aim to discharge patients after completion of chemotherapy if medically stable and logistically feasible. The predominant reasons for the perceived need for ongoing hospitalization were high risk of infection, treatment toxicities, and lack of nearby/accessible housing. There was no significant association between ability to practice EHD and annual AML volume or treatment intensity patterns (P=.60 and P=.11, respectively). In contrast, in the postremission setting, 87% of centers support patients following chemotherapy in the outpatient setting unless toxicities arise requiring readmission. Survey responses showed that 80% of centers were interested in exploring EHD after (re)induction but noted significant barriers, including accessible housing (71%), transportation (50%), high toxicity/infection rate (50%), high transfusion burden (50%), and limited bed availability for rehospitalization (50%). Hospitalization and care patterns following intensive AML therapy vary widely across major US cancer institutions. Although only 20% of surveyed centers practice EHD following intensive (re)induction chemotherapy, 87% do so following postremission therapy. Given the interest in exploring the EHD approach given potential advantages of EHD for both patients and health care systems, strategies to address identified medical and logistical barriers should be explored.