Multiple Years Research Articles

The Global Forest Fire Emissions Prediction System version 1.0

Abstract. The Global Forest Fire Emissions Prediction System (GFFEPS) is a model that estimates biomass burning in near-real time for global air quality forecasting. The model uses a bottom-up approach, based on remotely sensed hotspot locations, and global databases linking burned area per hotspot to ecosystem-type classification at a 1 km resolution. Unlike other global fire emissions models, GFFEPS provides dynamic estimates of fuel consumption, fire behaviour and fire growth based on the Canadian Forest Fire Danger Rating System, plant phenology as calculated from daily global weather and burned-area estimates using near-real-time Visible Infrared Imaging Radiometer Suite (VIIRS) satellite-detected hotspots and historical burned-area statistics. Combining forecasts of daily fire weather and hourly meteorological conditions with a global land classification, GFFEPS produces fuel consumption and emission predictions in 3 h time steps (in contrast to non-dynamic models that use fixed consumption rates and require a collection of burned area to make post-burn estimates of emissions). GFFEPS has been designed for use in operational forecasting applications as well as historical simulations for which data are available. A study was conducted showing GFFEPS predictions through a 6-year period (2015–2020). Regional annual total smoke emissions, burned area and total fuel consumption per unit area as predicted by GFFEPS were generated to assess model performance over multiple years and regions. The model's fuel consumption per unit area results clearly distinguished regions dominated by grassland (Africa) from those dominated by forests (boreal regions) and showed high variability in regions affected by El Niño and deforestation. GFFEPS carbon emissions and burned area were then compared to other global wildfire emissions models, including the Global Fire Assimilation System (GFAS), the Global Fire Emissions Database (GFED4.1s) and the Fire INventory from NCAR (FINN 1.5 and 2.5). GFFEPS estimated values lower than GFAS and GFED (80 % and 74 %) and had values similar to FINN 1.5 (97 %). This was largely due to the impact of fuel moisture on consumption rates as captured by the dynamic weather modelling. Model evaluation efforts to date are described – an ongoing effort is underway to further validate the model, with further developments and improvements expected in the future.

Optimizing the Allocation of Trials to Sub-regions in Crop Variety Testing with Multiple Years and Locations

AbstractField experiments in crop variety testing are conducted in multiple environments. When the targeted growing area can be stratified into sub-regions (zones), a design problem arises regarding the number of trials to be performed in each sub-region. We propose an analytical solution and a computational approach for optimal allocation of trials to sub-regions in multi-environment crop variety testing for multi-year experiments. For our purpose, we use a linear mixed model and we determine allocations that are optimal for the prediction of pairwise linear contrasts of genotype effects. For computations, we use the OptimalDesign package. The analytical results are illustrated by a real data example.

Temporal and regional trends in Canada for the epidemiology and management of diabetic foot ulcers.

Diabetic foot ulcers (DFUs) are a common downstream consequence of diabetes and pose significant concern to the health of affected individuals. There are currently limited data available that detail the epidemiology and inpatient burden of DFUs in Canada. This study aims to provide updated data on the epidemiological and economic burden of DFUs in Canada between 2015 and 2019. Using the Canadian Institute for Health Information Patient Cost Estimator the authors estimated, as the primary outcome, the number of DFU inpatient cases in Canada, the associated financial burden of these admissions on the Canadian healthcare system, physician compensation, and average patient length of hospitalisation. This analysis covered 12 Canadian jurisdictions and was stratified by age, sex, province and geographical region. The secondary outcome was to highlight temporal trends in the public health burden of DFUs by computing the average annual percentage change (AAPC; the weighted average of several annual percentage changes over multiple years) using Joinpoint (Surveillance Research Program National Cancer Institute, US) regression analysis. The total number of cases, average length of hospitalisation and physician costs across Canada were highest for patients over ≥60 years of age. By region, the total number of cases and standardised physician costs were highest in Central Canada, followed by Western Canada, and subsequently Eastern and Northern Canada. In 2019, there were >1800 patients with DFUs admitted to Canadian acute care hospitals. Despite having the lowest number of inpatient admissions, Northern Canada had the highest associated inpatient costs, followed by Central, then Western and, lastly, Eastern Canada. Overall, mean inpatient costs remained stable over time across all age groups (AAPC 0.61; 95% confidence interval: -1.87-3.15), with an average cost of >$10,000 CAD per case. Average physician cost across all jurisdictions was approximately $1000 CAD per case, with the mean hospitalisation time being nine days. The findings of this study emphasise the dynamic nature of the economic and epidemiological DFU burden in Canada, underscoring the need for targeted interventions, multidisciplinary care and evidence-based resource allocation for the optimal management of diabetes and DFUs.

Study of the Genetic Mechanisms of Siberian Stone Pine (Pinus sibirica Du Tour) Adaptation to the Climatic and Pest Outbreak Stresses Using Dendrogenomic Approach

A joint analysis of dendrochronological and genomic data was performed to identify genetic mechanisms of adaptation and assess the adaptive genetic potential of Siberian stone pine (Pinus sibirica Du Tour) populations. The data obtained are necessary for predicting the effect of climate change and mitigating its negative consequences. Presented are the results of an association analysis of the variation of 84,853 genetic markers (single nucleotide polymorphisms—SNPs) obtained by double digest restriction-site associated DNA sequencing (ddRADseq) and 110 individual phenotypic traits, including dendrophenotypes based on the dynamics of tree-ring widths (TRWs) of 234 individual trees in six natural populations of Siberian stone pine, which have a history of extreme climatic stresses (e.g., droughts) and outbreaks of defoliators (e.g., pine sawfly [Neodiprion sertifer Geoff.]). The genetic structure of studied populations was relatively weak; samples are poorly differentiated and belong to genetically similar populations. Genotype–dendrophenotype associations were analyzed using three different approaches and corresponding models: General Linear Model (GLM), Bayesian Sparse Linear Mixed Model (BSLMM), and Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK), respectively. Thirty SNPs were detected by at least two different approaches, and two SNPs by all three. In addition, three SNPs associated with mean values of recovery dendrophenotype (Rc) averaged across multiple years of climatic stresses were also found by all three methods. The sequences containing these SNPs were annotated using genome annotation of a very closely related species, whitebark pine (P. albicaulis Engelm.). We found that most of the SNPs with supposedly adaptive variation were located in intergenic regions. Three dendrophenotype-associated SNPs were located within the 10 Kbp regions and one in the intron of the genes encoding proteins that play a crucial role in ensuring the integrity of the plant’s genetic information, particularly under environmental stress conditions that can induce DNA damage. In addition, we found a correlation of individual heterozygosity with some dendrophenotypes. Heterosis was observed in most of these statistically significant cases; signs of homeostasis were also detected. Although most of the identified SNPs were not assigned to a particular gene, their high polymorphism and association with adaptive traits likely indicate high adaptive potential that can facilitate adaptation of Siberian stone pine populations to the climatic stresses and climate change.

Cooling down is as important as warming up for a large-bodied tropical reptile.

An ectotherm's performance and physiological function are strongly tied to environmental temperature, and many ectotherms thermoregulate behaviourally to reach optimum body temperatures. Tropical ectotherms are already living in environments matching their thermal tolerance range and may be expected to conform to environmental temperatures. We tracked the body temperatures (Tb) of 163 estuarine crocodiles across 13 years and compared Tb of 39 crocodiles to water temperature gathered using fish-borne sensors (Tw) across 3 years (2015-2018). While Tb largely conformed closely to Tw, we found inter- and intra-individual differences in relative body temperature (Tb-Tw) that depended on sex and body size as well as the time of day and year. Deviations from Tw, especially during the warm parts of the year, suggest that thermoregulatory behaviour was taking place: we found patterns of warming and cooling events that seemed to mediate this variation in Tb. Thermoregulatory behaviour was observed most frequently in larger individuals, with warming events common during winter and cooling events common during summer. By observing free-ranging animals across multiple years, we found that estuarine crocodiles show yearly patterns of active cooling and warming behaviours that modify their body temperature, highlighting their resilience in the face of recent climate warming. Our work also provides the first evidence for thermal type in large-bodied reptiles.

Occurrence, residency, and habitat characterization of leopard seals in Chile

Leopard seals have traditionally been considered Antarctic predators with a Southern Ocean distribution. Historically, sightings north of the Antarctic Polar Front were considered extralimital. However, recent studies suggest a significant presence of leopard seals in subantarctic regions. Here, we assess the spatial occurrence, residency status, and temporal trends of leopard seals in Chile using historical records, stranding reports, standardized monitoring data, photo-identification (photo ID) catalogs, and sightings from four research expeditions. We also characterize glaciers where sightings are concentrated, identifying glaciological and geomorphic attributes that prolong iceberg residency time, which is linked to high leopard seal concentrations. Based on these attributes, we evaluated other potential suitable glacial habitats in Patagonia. We obtained 438 sighting records of leopard seals from 1927 to 2023. Over the last 15 years, we documented a 4-18% annual increase in stranding events reported to national authorities. Most sightings (75%) were concentrated in two hotspots: National Park San Rafael Lagoon, located in Northern Patagonia, and Parry Fjord in Tierra del Fuego. Using photo ID catalogs, we identified 19 resident leopard seals, including 16 multi-year residents observed between 2010-2023 (10 in San Rafael, 6 in Tierra del Fuego) and 3 potential residents (observed multiple months in the same year in Tierra del Fuego). San Rafael monitoring data showed no inter-annual trend, but seasonal trends were observed. We also provide evidence of breeding in Chile, with records of at least 14 pups born and at least two females giving birth in multiple years. Our habitat characterization suggests that calving flux, fjord sinuosity, and fjord width variation are crucial for prolonging iceberg residency in hotspot areas. Based on these attributes, we identified 13 additional fjords in Patagonia as “very likely” suitable for leopard seals. Our study confirms that Patagonia is part of the species’ breeding distribution, shifting the paradigm that leopard seals are merely visitors north of the Antarctic Polar Front. Given the limited number of suitable glaciers in Chile and the potential impacts of climate change, our assessment highlights glacial retreat as a major threat for the ecosystem of this pagophilic marine apex predator in South America.

An improved framework for mapping and assessment of dynamics in cropping pattern and crop calendar from NDVI time series across a heterogeneous agro-climatic region.

The absence of spatial and temporal cropping information in semi-arid regions poses a significant challenge in assessing the dynamics of agricultural systems at river basin scales. Satellite remote sensing provides qualitative and quantitative information to derive vegetation dynamics over extensive areas of inherent complexities due to limitations in the availability of field data and the diverse nature of agricultural cropping practices. Utilizing phenological information derived from MODIS Normalized Difference Vegetation Index (NDVI) time series data from 2003-2004 to 2021-2022, this study derives major crop types, and cropping calendar (sowing, maturity, and harvest dates) for each season and year at 250-m resolution. This study introduces an integrated function-fitting model based on the Fast Fourier Transform (FFT) and a Lagrangian 3-point derivative-based approach to extract phenological events from the NDVI time series automatically. The derived phenological information is used in a hybrid crop classification algorithm that combines a rule-based decision tree approach (using the phenological events/dates) and a random forest classifier (using the phenological metrics) to generate the classified crop map at a river basin scale for multiple seasons and years. The implemented approach successfully captured sowing and harvesting dates for every crop growing season over 19years, with an RMSE of 9days, as observed with the available field survey data from 2015 to 2021. The classification results from this hybrid approach demonstrate an overall 82% accuracy. The proposed method shows a substantial improvement in cropping area estimation with a 60% reduction in MAE and RMSE compared to the existing algorithm. From the long time series of derived seasonal crop data (19-year analysis period), the influence of monsoonal activities and shifts on the spatial and temporal dynamics of sowing time and cropping patterns are assessed for a large river basin, demonstrating the utility of this continuous crop calendar. Further, an extensive analysis of results highlights farmers' adaptive strategies in response to dry and wet years, providing foundational insights for future studies on assessing the impacts of climate change. Hence, the hybrid framework adopted in this study for deriving a continuous crop calendar holds immense relevance for parameterizing and utilizing such information for developing river basin scale hydrologic and crop growth models for water resources planning and assessment.

Dissemination of Information on Investor Attention, Firm Size, and Year-End Market Dynamics: An Empirical Study of the Indian Stock Market

This paper investigates the dissemination and presence of the “Year-End Market Surge”, commonly referred to as the “Christmas Rally”, in the Indian stock market. In developed nations, this phenomenon describes a notable increase in stock prices typically observed during the last week of December and the first two trading days of January. Recent reports in the popular press suggest that a similar trend has been witnessed in the Indian stock market over recent years. However, there remains a lack of systematic research on this subject. Therefore, this study rigorously examines whether this market surge, which poses a potential challenge to the Efficient Market Hypothesis (EMH), is observable in the Indian context. Furthermore, the paper explores the dissemination of firm-specific trading patterns to identify characteristics of companies that have consistently delivered positive returns during this period over multiple years. The findings reveal that larger stock portfolios in the Indian market consistently benefit from the Year-End Market Surge effect, delivering higher abnormal returns compared to smaller portfolios. These results provide important insights into the role of firm size in capturing the benefits of this seasonal market anomaly.

Effects of soil acidification on humus, electric charge, and bacterial community diversity.

Soil acidification due to the long-term application of nitrogenous fertilizers and the consequent impact on crop growth have been frequently reported. The effects of acidification on soil humus, charge, and microbial communities need to be studied. In this experiment, fertilizer drenching was used to simulate the effects of multiple years of fertilizer application on the black soil. The results showed that 25years of soil acidification treatment resulted in a decrease of 8.97% in the content of stable humus and led to a decrease of 58% and 51.18% in the humic acid (HA) content and degree of humification (PQ) value in stable humus, respectively. In addition, soil acidification leads to a significant decrease in total negative charge (CEC8.2) and variable negative charge (CECv), with both decreasing by 63.28% and 88.67%, respectively, at 25years. Acidification treatments affected both soil microbial community abundance and diversity, with a significant decrease in Acidobacteriota and Gemmatimonadota abundance and an increase in Bacteroidia abundance and Acidobacteriota abundance at 25years.

Edoxaban for stroke prevention in routine practice patients with atrial fibrillation with and without atherosclerotic disease: a post-hoc sub-study of ETNA-AF-Europe

Abstract Background Patients with atrial fibrillation (AF) and concomitant coronary and peripheral artery disease (CAD and/or PAD) have an increased risk of adverse health events compared to those without such atherosclerotic disease. The annual risks of major adverse cardiovascular outcomes for these patients treated with edoxaban in routine clinical practice remain uncertain. Purpose To determine the clinical characteristics and rates of key adverse events over multiple years of follow-up in patients with and without atherosclerotic disease (defined as CAD and/or PAD). Methods This is a post-hoc sub-study of ETNA-AF-Europe, a multinational, prospective cohort study on unselected patients with AF treated with edoxaban. In total, 13,164 (97%) of the 13,632 patients who provided informed consent were included in this substudy. The included patients were followed for a total of 48 months. Data were collected at baseline and yearly thereafter (±2 months). The present analysis compared baseline clinical characteristics (n [%] or mean [SD]) and clinical outcomes (events per 100 patient-years [%/year] with 95% confidence intervals [95% CI]) by CAD/PAD status at baseline. Results Of the 13,164 patients included in the analysis, 2973 had CAD and/or PAD (n=2762 CAD only). Patients with atherosclerotic disease were older (75.3 years vs 73.2 years), had higher CHA2DS2-VASc scores (3.8 vs 3.0) and HAS-BLED scores (2.8 vs 2.4), and more frequently received the reduced dose of 30 mg edoxaban than those without CAD/PAD (30.2% vs 21.0%) (Table). Cardiovascular comorbidities were in general more prevalent in those with atherosclerotic disease vs those without. Rates of stroke or systemic embolism (0.89%/year, 95%-CI 0.72–1.09 vs 0.59%/year, 95%-CI 0.52–0.68), myocardial infarction (0.73%/year, 95%-CI 0.58–0.92 vs 0.25%/year, 95%-CI 0.20–0.30), and cardiovascular (1.56%/year, 95%-CI 1.33–1.83 vs 0.85%/year, 95%-CI 0.76–0.95) as well as all-cause death (5.96%/year, 95%-CI 5.50–6.46 vs 3.56%/year, 95%-CI 3.37–3.77) were higher for patients with CAD/PAD vs those without such atherosclerotic disease (Figure). Conclusion Annual rates of thromboembolic and bleeding events were low for AF patients treated with edoxaban in routine practice. The higher rates of thrombotic and bleeding events in patients with CAD/PAD are most likely caused by differences in baseline intrinsic risks. Nonetheless, these differences, particularly the threefold higher rate of myocardial infarction, warrants further investigation.Baseline Characteristics

Disability during the last ten years of life: Evidence from a register-based study in Austria

Abstract Background Many older adults experience disability in activities of daily living during the last years of life, but survey-based analyses suffer from non-representative samples due to selective participation and attrition. Here, we use individual-level register data on the receipt of the Austrian long-term care allowance (ALTCA) as a proxy for late-life disability. Methods In this retrospective mortality follow-back study, we analyse receipt of ALTCA, a cash benefit based on physician assessed disability during the last 10 years of life, among all decedents aged 65 years and over from 2020 in Austria (n = 76,781). The impact of sex, age of death, and cause of death on the duration and probability of receipt of ALTCA was assessed with regression models. Results 10 years before death 10% of older men and 25% of older women received ALTCA, which increased to 27% and 51% at 5 years, 56% and 77% at 1 year, and finally to 70% and 87% at 1 month before death. On average, ALTCA was received for 3.2 years in men and 4.5 years in women. The probability to receive ALTCA and its duration increased sharply with age at death and varied by underlying causes of death: those who died from cancer, myocardial infarction, and external causes of death were less likely to receive ALTCA and experienced shorter durations of it, while those who died from dementia, Parkinson’s disease, chronic heart disease, or chronic obstructive lung disease were more likely to receive ALTCA and longer so. Conclusions Most older adults received ALTCA for multiple years before death, and this increased strongly with age at death and varied across causes of death. Our register-based estimates of late-life disability were twice as high as survey-based estimates, which points to an underestimation in previous studies. Policy-makers should be aware that costs of long-term care will likely increase as life expectancy rises and deaths from dementia and organ failure increase in ageing European societies. Key messages • A large majority of older adults in Austria experience late-life disability. On average, older men were disabled for 3.2 and older women for 4.5 years. • Probability and duration of late-life disability increased steeply with age at death and was higher for those who died from dementia, Parkinson’s disease, or chronic heart or lung disease.

Infection-Associated Flares in Systemic Lupus Erythematosus

Systemic lupus erythematosus (SLE) is characterised by generalised immune dysfunction, including infection susceptibility. Infection-associated flares (IAFs) are common and might rapidly self-resolve, paralleling infection resolution, but their specific clinical phenotype is poorly understood. Therefore, we screened 2039 consecutive visits and identified 134 flares, defined as a loss of the lupus low disease activity state (LLDAS), from 1089 visits at risk spanning over multiple follow-up years, yielding an average yearly LLDAS deterioration rate of 17%. Thirty-eight IAFs were isolated from the total flares and were mostly related to bacterial and herpesvirus infections. When compared to other flares (OFs; n = 98), IAFs showed no milder patterns of organ involvement and similar rates of long-term damage accrual, as estimated by conventional clinimetrics. Arthritis in IAFs was more severe than that in OFs [median (interquartile range) DAS-28 2.6 (2.3–4.1) vs. 2.0 (1.6–2.7); p = 0.02]. Viral IAFs were characterised by atypically lower levels of anti-DNA antibodies (p < 0.001) and possibly abnormally high complement levels when compared to flares of different origin. These data suggest that IAFs are of comparable or even higher severity than OFs and may subtend distinct pathophysiological mechanisms that are poorly tackled by current treatments. Further research is needed to confirm these data.

Serotype-specific epidemiological patterns of inapparent versus symptomatic primary dengue virus infections: a 17-year cohort study in Nicaragua.

Dengue is the most prevalent mosquito-borne viral disease and a major public health problem worldwide. Most primary infections with the four dengue virus serotypes (DENV1-4) are inapparent; nonetheless, whether the distribution of symptomatic versus inapparent infections by serotype varies remains unknown. Here, we present (1) the evaluation of a DENV1-4 envelope domain III multiplex microsphere-based assay (EDIII-MMBA) to serotype inapparent primary infections and (2) its application leveraging 17 years of prospective sample collection from the Nicaraguan Pediatric Dengue Cohort Study (PDCS). We analysed primary DENV infections in the PDCS from 2004 to 2022 detected by inhibition ELISA (iELISA) or RT-PCR. First, we evaluated the performance of the EDIII-MMBA for serotyping with samples characterised by RT-PCR or focus reduction neutralisation test. Next, we analysed a subset of inapparent primary DENV infections in the PDCS with the EDIII-MMBA to evaluate the epidemiology of inapparent infections. Remaining infections were inferred using stochastic imputation, taking year and neighbourhood into account. Infection incidence and percentage of inapparent, symptomatic, and severe infections were analysed by serotype. Between Aug 30, 2004, and March 10, 2022, a total of 5931 DENV-naive participants were followed in the PDCS. There were 1626 primary infections (382 symptomatic, 1244 inapparent) detected by iELISA or RT-PCR over the study period. The EDIII-MMBA demonstrated excellent overall accuracy (100%, 95% CI 95·8-100) for serotyping inapparent primary DENV infections when evaluated against gold-standard serotyping methods. Of the 1244 inapparent infections, we analysed 574 (46%) using the EDIII-MMBA. We found that the majority of primary infections were inapparent, with DENV3 exhibiting the highest likelihood of symptomatic (pooled odds ratio compared with DENV1: 2·13, 95% CI 1·28-3·56) and severe (6·75, 2·01-22·62) primary infections, whereas DENV2 was similar to DENV1 in both analyses. Considerable within-year and between-year variation in serotype distribution between symptomatic and inapparent infections and circulation of serotypes undetected in symptomatic cases were observed in multiple years. Our study indicates that case surveillance skews the perceived epidemiological footprint of DENV. We reveal a more complex and intricate pattern of serotype distribution in inapparent infections. The substantial differences in infection outcomes by serotype emphasises the need for vaccines with balanced immunogenicity and efficacy across serotypes. National Institute of Allergy and Infectious Diseases (National Institutes of Health) and Bill & Melinda Gates Foundation. For the Spanish translation of the abstract see Supplementary Materials section.

The Contribution of Moisture Sources of Precipitation to Water Resources Recharge in Semi-Arid Regions

This study investigates the isotopic composition of precipitation in Iran and its moisture sources, offering insights crucial for addressing water recharge and management in semi-arid regions. This study analyzes 150 precipitation events collected from 11 stations across Iran over multiple years. The HYSPLIT model was used to trace air mass trajectories contributing to these events. The isotopic composition of precipitation from each moisture source was examined to identify their distinct characteristics. Furthermore, the contribution of each air mass to groundwater and surface water recharge was quantified using the Simmr mixing model in R programming language, combining stable isotope data from precipitation and surface/groundwater samples. Precipitation in northern Iran is associated with low d-excess values, indicating moisture from high-latitude sources, particularly the Caspian Sea, while higher d-excess values in the west and south point to moisture mainly from the Persian Gulf and the Mediterranean Sea. Air mass trajectory analysis via the HYSPLIT model identified the dominant pathways of Continental Tropical (CT), Continental Polar (CP), and Mediterranean (MedT) air masses across Iran. Quantitative analysis using the Simmr mixing model revealed that the CT air mass contributes up to 33.6% to groundwater recharge in southern Iran’s karstic regions, while the CP air mass dominates in the north, with up to 46.8% contribution. The MedT air mass, although significant in the west, decreases in influence towards the east. Isotope data from groundwater and surface water sites showed more depleted values than local precipitation, likely due to larger catchment areas. These findings contribute to water management strategies by identifying the variations in moisture sources that influence groundwater and surface water recharge in Iran. Understanding these variations enables the development of targeted strategies for managing water resources in semi-arid regions facing increasing water scarcity. The methodologies applied in this study can be adapted to other regions, providing a valuable framework for sustainable water management in areas where identifying moisture sources is critical.

Examining Use of Pharmacotherapy for Behavioral Support Among Americans with IDD Using Machine Learning

ABSTRACT Background Adults with intellectual and developmental disabilities (IDD) often have behavioral support needs that must be met in order to live in community settings. Pharmacotherapies are often used to meet such needs. We explored factors that predict medication for behavioral support among adults with IDD. Methods We integrated three major U.S.- based IDD-specific datasets over multiple years, creating a large dataset. We used machine learning to build and test an algorithm to predict factors associated with the use of pharmacotherapies to address behavioral support needs for adults with IDD. Findings Our algorithm correctly predicted the use of pharmacotherapies with about 79% accuracy. Top predictors of medication use to address behavioral support needs included disruptive behavior, use of medication to treat a mental health condition, and presence of an autism diagnosis. Conclusions Use of behavior plans should be given more attention in conjunction with medication use, especially in relation to managing disruptive behavior.

A robust method for mapping soybean by phenological aligning of Sentinel-2 time series

Soybean is an important crop for food and animal feed. Production and area both continue to increase and expand into new areas and countries. Spatially explicit information on soybean cultivation is essential to crop monitoring, production estimation, and national accounting systems. However, its cultivation in diverse climate conditions, landscapes, and agricultural systems poses challenges to accurately map soybean across different regions and years. We propose an innovative soybean mapping method combining phenological alignment with machine learning (named here RF-DTW), which can be applied to diverse geographies and years by aligning phenological shifts and using distinctive features from Sentinel-2 time-series. The method first uses the dynamic time warping (DTW) algorithm to align the growing season between pixels across different sites. Then, based on the harmonized time-series, a set of distinctive features was identified and used to build random forest (RF) models to classify soybean across ten globally distributed sites and multiple years. Results show that the green chlorophyll vegetation index (GCVI), greenness and water content composite index (GWCCI), normalized difference senescent vegetation index (NDSVI), red edge position (REP), and short-wave infrared bands are important inputs for distinguishing soybean from other crops. Spectral-phenological features, particularly the curve slope metrics of GCVI and GWCCI during the peak to late growing season, rank as the most important features for mapping soybean. RF-DTW demonstrates good generalizability across ten study sites, achieving an overall accuracy (OA) of 0.92 and an F1-score of 0.84. F1-scores for eight out of ten sites ranged between 0.82 and 0.98, outperforming a benchmark method, although they were lower (F1-score < 0.60) for the two sites in Sub-Saharan Africa. Additionally, RF-DTW performs robustly when transferred to untrained regions and years, with most cases showing an F1-score higher than 0.70. Our proposed method, as a combination of phenological alignment and machine learning, can be used to map soybean accurately and efficiently across different regions and years, to provide crucial information for understanding the rapid dynamics of soybean cultivation and its global-scale impacts.

A Serious Game for the Digital Transformation of Organizations

To aid human resource management professionals design a configuration of human resource management practices that facilitates the employee behaviour needed for the digital transformation, a serious game was created. The serious game challenges human resource management professionals to combine and design human resource management practices that align to the organizational strategy and optimize employee digital transformation behaviour over multiple simulated years. In this paper, the underlying rationale, design, and outcomes of the first test rounds of the game are presented. Organizational change shaped by the diffusion of technology is labelled the digital transformation (Hanelt et al., 2021). Employees can accelerate or slow down the digital transformation. Hence, organizations are looking to facilitate digital transformation enhancing employee behaviours: adaptive performance and proactive agility behaviour (Collou and Bruinsma, 2022). Aligned human resource management configurations (i.e., combination of human resource management practices such as recruitment, selection, and job design) can shape that employee behaviour (Gratton and Truss, 2003; Delery and Doty, 1996). Designing such a human resource management configuration however is challenging. There are many human resource management practices that need to be designed over multiple years and effects on employee behaviour vary. Serious games are well suited tools to enhance understanding of challenges such as strategic human resource management design. They allow professionals to experiment with choices and gauge the outcomes of their selection without the need to test these decisions in real life. Prior work (Collou and Bruinsma, 2022, 2019) illustrated that a serious game can aid human resource management professionals in their quest to design human resource management configurations that align to the organizational strategy. In the current game an additional challenge was added: shaping digital transformation behaviour. Tested in multiple rounds the game shows great promise for professionals and students to experiment with human resource management configuration design. First evaluations illustrate that responders are positive in terms of their learning experience. Balancing the need to align the human resource management configuration and affecting the employee behaviour simultaneously has proven to be challenging for players of the game. Future steps are focused on this balance and empirically validating the serious game.

Applying to Lead: A Mixed-Methods Investigation of Prospective Principals’ Job Application Strategies in Two Urban Districts

Purpose: Urban school districts often face challenges in filling principal vacancies with effective leaders, especially in high-needs schools. Prospective principals’ engagement with the job application process may contribute to these challenges. The goal of this study is to better understand the job search strategies and behaviors of prospective principals and how their approaches might contribute to leadership staffing challenges in high-needs schools. Research Design and Methods: We employ a convergent mixed-methods design that draws on data from two urban school systems. We pair analysis of interviews of 36 principals who have recently navigated the districts’ hiring systems with multiple years of applications and other administrative data provided by the two districts. We explored how patterns and themes that emerged from each data source were confirmed or disconfirmed with the other source. Findings: Guided by a job-search model, our analysis uncovers three main findings. First, the typical principal applicant conducted a targeted rather than a wide search, reflecting multiple strategies, preferences, and relational factors. Second, elementary educators showed a strong propensity to apply to the same grade level. Third, leaders applied to schools serving larger proportions of historically marginalized students at similar rates as other schools, reflecting their motivations to work with underserved students. Implications for Research and Practice: Considerations informing prospective principals’ job searches are multifaceted. High-needs schools are desirable to many principal candidates. Identifying and strategically recruiting candidates with preferences for working in such schools can be a strategy for districts seeking to overcome challenges in filling principal vacancies.

Energetics explain predator occurrence and movement in pyrodiverse landscapes

ContextFire-adapted species have evolved to exploit resources in heterogenous landscapes that presumably maximize energy acquisition and minimize energetic expenditure. However, limited empirical work exists demonstrating the explicit energetic mechanisms that drive such adaptive responses to fire across diverse landscapes.ObjectivesThe California spotted owl (Strix occidentalis occidentalis) appears to benefit from landscape heterogeneity and preferentially uses smaller patches of severely burned forest, a behavior that has been hypothesized as adaptive. Here, we investigate empirical support for this hypothesis.MethodsWe leveraged high-resolution GPS tracking and nest video monitoring to examine the hunting success, movement, and nest provisioning of 34 spotted owls in the Sierra Nevada and San Bernardino Mountains, California across burned and unburned landscapes.ResultsRegardless of time since fire, individuals avoided foraging directly within moderately or severely burned patches. 1 to 2 years post-fire, individuals had more success capturing prey in unburned forest, and the energy individuals spent moving increased with the proportion of high-severity fire and decreased with the proportion unburned forest. Multiple years after a fire, individuals had more success capturing prey, spent less energy moving, and provisioned more energy to nests in landscapes with more low-severity fire.ConclusionsThese results support the hypothesis that spotted owls are adapted to fire-prone landscapes and that disturbance events within this region’s natural range of variation can ultimately promote hunting and provisioning. As fires deviate from regional norms across the globe, the negative impacts of fire may become more extreme and long-term benefits of fire may degrade for animals in fire-prone landscapes. Examining the mechanistic impacts of disturbance can allow us to better understand animal responses to rapidly changing landscapes.

Efficient epistasis inference via higher-order covariance matrix factorization.

Epistasis can profoundly influence evolutionary dynamics. Temporal genetic data, consisting of sequences sampled repeatedly from a population over time, provides a unique resource to understand how epistasis shapes evolution. However, detecting epistatic interactions from sequence data is technically challenging. Existing methods for identifying epistasis are computationally demanding, limiting their applicability to real-world data. Here, we present a novel computational method for inferring epistasis that significantly reduces computational costs without sacrificing accuracy. We validated our approach in simulations and applied it to study HIV-1 evolution over multiple years in a data set of 16 individuals. There we observed a strong excess of negative epistatic interactions between beneficial mutations, especially mutations involved in immune escape. Our method is general and could be used to characterize epistasis in other large data sets.