Haemonchosis remains one of the most economically important helminth infections limiting small ruminant productivity in tropical and subtropical regions. This study determined the prevalence and intensity of Haemonchus contortus infection in sheep and goats slaughtered during the late dry season in Zaria, Kaduna State, Nigeria. A cross-sectional abattoir-based design was employed, involving 196 small ruminants comprising 98 sheep and 98 goats. Abomasa were collected immediately after slaughter, and adult worms were recovered using standard post-mortem worm count techniques. Identification was based on morphological features, and worm burdens were categorized into light, moderate, and heavy infections. Data were analysed using descriptive statistics and Chi-square tests to compare infection patterns between species. Findings revealed that light infection was the predominant category in both sheep (78.6%) and goats (70.4%), while moderate infection occurred at low levels in sheep (6.1%) and goats (3.1%). No heavy infections were recorded in either species. A higher proportion of goats (26.5%) were uninfected compared to sheep (15.3%). Statistical analysis indicated no significant difference in infection distribution between sheep and goats (p > 0.05). The overall pattern suggests widespread exposure to H. contortus but with relatively low worm burdens during the late dry season. The absence of heavy infections may reflect seasonal constraints on larval survival and transmission dynamics. These findings highlight the importance of season-specific parasite control strategies and provide baseline epidemiological data for the improvement of helminth management in small ruminants in northern Nigeria.

Stabilizing grain production in double-cropping rice areas depends largely on early rice; however, its production is often considered a reserve due to high-temperature stress during the grain filling stage, leading to poor quality and low market acceptance. High-quality late rice early planting-continuous cropping (HLREP-CC) model was proposed to improve grain quality in early-season rice under limited high-quality early rice varieties. Two high-quality late indica rice varieties were selected as test materials to explore the superiority of the HLREP-CC model. Meanwhile, we compared the differences in rice yield and quality between the early and late seasons across three ecological planting areas in China: central Jiangxi (C-Jx), south-central Jiangxi (SC-Jx), and southern Jiangxi (S-Jx). The HLREP-CC model significantly increased yield cooking and eating quality in the early season; although processing and appearance quality decreased in the early-season rice, it is recommended to select varieties with an environmentally quality-insensitive variety. As latitude decreased, rice processing and appearance, and nutritional quality enhanced; the cooking and eating quality depended on the rice variety. There are significant differences in the performance of this model among different ecological zones. The SC-Jx had the highest yield and best comprehensive performance, as it can balance yield and maintain good rice quality, making it the ideal core promotion area. The S-Jx region exhibited superior processing and appearance quality but slightly lower yield, requiring careful variety selection. The C-Jx showed limited potential due to significantly lower early-season yield and quality. © 2026 Society of Chemical Industry.

Background Dengue virus is a major cause of febrile illness and is often misdiagnosed as malaria in regions lacking appropriate diagnostics. This study assessed the prevalence and risk factors for dengue infection among febrile patients attending community health centers in the malaria hyperendemic Sikasso region of southern Mali. Methods From June (beginning of the rainy season) to December (post rainy season) 2023, patients presenting with fever at four community health centers (Bamba, Fakola, Filamana, and Guélélenkoro) were tested for dengue infection using rapid diagnostic tests. A multivariate logistic regression model was applied to identify risk factors associated with symptomatic infection. Results Of 251 enrolled patients, 63.0% were male, and the median age was 15 years (± 13.7). The prevalence of dengue infection varied between 9.7% to 47.8% with the highest observed in December after the rainy season. Headache, muscle pain, and abdominal pain were the most common clinical symptoms associated with dengue fever. Children 5-15 years had significantly higher risk of infection compared to those under 5 years of age (OR = 7.4; 95% CI [1.44; 38.26]). The risk of infection was highest in November (OR = 4.29; 95% CI [1.12; 16.48]) and December (OR = 10.30; 95% CI [2.56; 41.36]). Conclusion Dengue infections contribute substantially to febrile illness in southern Mali, particularly among school-aged children, mainly during the late rainy season and early dry season. The finding highlights the need for integration of dengue testing into routine diagnostic protocols for febrile patients in malaria-endemic rural settings to reduce misdiagnosis and improve patient outcomes.

Combined organic amendments reduce Cd accumulation in double-cropping rice by restructuring soil bacterial communities.

Effects of prescribed burning on fire regime dynamics in Amazonian savanna ecosystems.

The production of maize in sub-Saharan Africa faces serious threats from the fall armyworm (FAW). Since its arrival to Nigeria in 2016, its rapid spread and destructive feeding habits have raised urgent concerns for effective control. This research assessed the biological control capacity of FAW natural enemies through seasonal field observations in Benin City, Edo State. Field trials were conducted in 2020 and 2021 at the University of Benin Experimental Farm. A split-plot design involving four maize varieties and fifteen sampling intervals (days after sowing, DAS) were used. Arthropod predators were monitored through direct plant sampling, while parasitoids were identified from laboratory rearing of FAW egg masses and larvae. Data were analyzed using Aanalysis of Variance and T-tests. Natural enemies recorded included insect predators from the families Forficulidae, Formicidae, Pentatomidae, Coccinellidae, and Blatellidae, spiders (Araneae), and parasitoids from Platygastridae, Braconidae, and Trombidiidae. Abundance did not vary significantly across maize varieties but differed with crop growth stages and between years. Predator peaks occurred at 65 DAS (1.22) and 75 DAS (5.50) in early and late season in the year 2020, and 65 DAS (6.79) in early 2021. Parasitoids’ peaks were observed at 30 DAS (1.54) in early 2020, and at 30 DAS (0.64) and 15 DAS (0.87) in early and late 2021, respectively. These results highlight the ecological importance of natural enemies and their potential integration into sustainable pest management strategies for maize production in the region.

Background Frequent fire characterises Australia’s tropical savannas and strongly influences vegetation structure and carbon (C) stocks. Fire management is widely used to reduce greenhouse gas emissions, but long-term effects of fire timing and frequency on woody C accumulation remain uncertain. Aims To quantify stand-level woody C stocks and assess cumulative multi-decadal effects of fire timing and frequency in northern Australian savannas. Methods Field measurements and historical biomass and basal area data from three long-term (17–30-year) fire trials were analysed. Treatments included unburnt controls and burned plots with up to four fire frequencies within a 6-year range and two fire seasons (early and late dry season). Carbon stocks were quantified for standing biomass, coarse woody debris and litter. Key results Total woody C accumulation was greater under early dry season fire than late dry season fire regimes. Longer between-fire intervals (particularly late dry season) may increase woody C stocks, although effect sizes were uncertain. Conclusions Early dry season burning was associated with greater long-term woody C accumulation than late dry season burning. Implications are that early dry season fire management remains important for reducing savanna fire emissions, but optimal fire regimes should consider site-specific conditions and broader ecological objectives.

Hydroponic (HP) and aquaponic (AQ) systems are widely known in greenhouse production; however, the combined effects of nutrient delivery system and substrate physical structure on crop performance and root-zone microbiomes remain insufficiently understood. Substrate physical properties influence water retention and aeration, which can affect root-associated microorganisms, plant growth, and yield. This study evaluated cucumber (Cucumis sativus L.) growth, yield, nutrient dynamics, physiological stress responses, and bacterial community composition under HP and AQ systems using bamboo-derived biochar substrates and coconut coir as a control. Vegetative growth was enhanced under AQ, with the greatest plant elongation (1102 ± 40.1 cm) and stem diameter (15.1 ± 1.0 mm) observed in biochar-grown plants. Total yield was consistently higher under AQ than HP, with the highest yield recorded in the coarse biochar treatment (28.6 kg m−2). Aquaponic systems were associated with greater nutrient availability under the conditions evaluated during mid to late season production, including nitrate concentrations of up to 226 mg L−1. Physiological stress monitoring indicated lower stress exposure under aquaponic conditions in plants grown in medium and coarse biochar substrates across both systems, with 78 to 81% of the growing season classified within low to balanced stress conditions. Bacterial community composition was primarily shaped by cultivation system, which explained 19.3% of the observed variation, whereas substrate treatment did not significantly alter overall bacterial community structure. Overall, cultivation system was the dominant factor associated with variation in cucumber performance and root-zone bacterial communities, while biochar substrates supported improved plant growth, yield, and reduced physiological stress.

Aguila Camacho, A, Ochoa Ahmed, F, Rowlett, M, Ríos-Gallardo, PT, Cabarkapa, DV, Cabarkapa, D, and Montalvo, S. Longitudinal changes in countermovement jump and isometric mid-thigh pull metrics and their relationship with on-court basketball performance in elite female collegiate basketball players. J Strength Cond Res XX(X): 000-000, 2026-To quantify within-subject relationships among countermovement jump (CMJ) and isometric mid-thigh pull (IMTP) variables, describe their temporal behavior across a competitive season, and examine their association with game performance in female collegiate basketball. Eighteen athletes (21.6 ± 1.9 years; 69.9 ± 9.1 kg; 171.6 ± 8.2 cm) completed CMJ and IMTP testing for 33 weeks. Within-subject (demeaned) Spearman correlation matrices were used to identify functional clusters. Representative CMJ (jump height, peak power, contraction time, reactive strength index(mod) and IMTP (peak force, impulse 100 ms, rate of force development [RFD] 50 ms) variables were modeled longitudinally with linear mixed-effects models (random intercepts; autoregressive (1) for a week). Game outcomes from 24 contests were linked to the nearest prior test and evaluated with bivariate Spearman correlations and leave-one-out cross-validated (LOOCV) linear models. Countermovement jump variables clustered into (a) force-production measures (e.g., impulses/peak power; moderate-high positive associations), (b) performance outcomes (jump height with relative power), and (c) temporal measures (contraction/phase durations). Isometric mid-thigh pull variables formed tight early impulse and RFD clusters, with peak-force measures grouping separately. Cross-test associations were generally small (|ρ| ≤ ∼0.30), indicating complementary constructs. Mixed-model marginal means showed modest, nonuniform seasonal trends-modified reactive strength index (mRSI) tended to increase and contraction time to decrease late season, while IMTP peak force exhibited a mid-season rise-amid substantial within-player variability. For game performance, only mRSI showed a statistically significant positive correlation with point differential (ρ = 0.46, p = 0.024); other variables were small and nonsignificant. Single-variable LOOCV models explained little variance in point differential (R2_cv ≤ 0.04). Countermovement jump and IMTP capture largely independent neuromuscular qualities and exhibit modest, test-specific seasonal changes. Although mRSI relates positively to game point differential, single neuromuscular metrics showed limited standalone predictive value, supporting their use primarily for monitoring readiness in conjunction with contextual factors rather than for game-to-game prediction.

ABSTRACT High temperatures are considered the most important limiting factor for the productivity of beans, and the ongoing increase in global temperature is estimated to have a strong negative impact on its yield. With the aim of mitigating the effects of high temperatures that usually prevail during growing seasons, the efficacy of two novel biostimulants (not yet commercially available) based on amino acids supplemented with sulfur or silicon was tested in two consecutive growing seasons (early and late). During the early season (May 7–June 30), conditions of intense heat stress prevailed, and in combination with the cultivation of a relatively sensitive genotype, the marketable yield was reduced by 51%, compared to the yield in the late season (7,323 kg ha−1). The exogenous application of amino acid-based biostimulants supplemented with sulfur or silicon did not significantly mitigate yield reduction (7,143–7,693 kg ha−1). On the other hand, during the late season (August 5–October 19), conditions of milder heat stress prevailed, and in combination with the cultivation of a relatively resistant genotype, the marketable yield was high (14,915 kg ha−1). The exogenous application of amino acid-based biostimulants supplemented with sulfur or silicon did not significantly affect chlorophyll fluorescence parameters or yield (13,908–15,833 kg ha−1).

The soilborne fungal pathogen Fusarium oxysporum f. sp. vasinfectum race 4 (FOV4) poses a risk to U.S. cotton (Gossypium spp.) following detection in California, Texas, and New Mexico. This study evaluated the influence of cotton cultivar resistance on relative variation in soil FOV4 DNA quantity, a proxy for inoculum density, in a naturally infested field over two years. Field trials included Upland (G. hirsutum) and Pima (G. barbadense) cotton cultivars and measured plant mortality, root necrosis, and lint yield. Bulk soil FOV4 DNA was quantified by qPCR at three timepoints each year: planting, midseason (first flower), and late season (crop maturity). Susceptible Pima cultivars exhibited the highest mortality, most severe necrosis, and lowest yields, whereas resistant Pima and Upland cultivars had lower necrosis with variable mortality and yield. Commercial Upland cultivars with differing degrees of susceptibility showed intermediate mortality and necrosis yet high yields. Midseason soil FOV4 DNA levels varied among cultivars in both years (p=0.011, 0.028), with elevated levels in a subset of susceptible cultivars. Late season DNA levels varied among cultivars in 2021 (p=0.017) but not in 2020 (p=0.080) and did not correspond to resistance designations. Within cultivars, mortality correlated with FOV4 DNA levels at planting (p<0.001, McFadden's pseudo-R2 [R2MF]=0.810) and late season (p<0.001, R2MF=0.802), necrosis with late season DNA levels (p<0.001, R2=0.849), and yield showed no correlation with FOV4 DNA at any timepoint. These findings relate host response to DNA-based soil pathogen quantification and emphasize resistance variation as a determinant of FOV4 disease ecology and management success.

Changing climates are leading to more frequent and severe heat waves, potentially threatening plant populations. Both acclimation to stress and selection for heat-escape or heat-resistance phenotypes occur during heat waves. However, plastic responses and selection do not necessarily interact cohesively-even producing trait responses in opposite directions that could cause maladaptation. We examined patterns of maternal provisioning and natural selection on seed mass and germination characteristics after two natural heat waves across 12 annual populations of Mimulus guttatus. We then recreated heat-wave events occurring early and late within a growing season using a manipulative experiment to determine the reproducibility of our results. There was selection for greater seed mass during the year of the early season heat wave, and seed mass remained high through the late-season heat wave. Maternal provisioning also impacted seed mass and germination during the late-season heat wave. Field observations of seed mass only reflect selection for increased seed mass after the early season heat wave, and plants that experienced a late season heat wave had small seeds that germinated later. This pattern during the late season heat wave reflects decreased maternal provisioning coinciding with selection for larger seeds. Our results demonstrate that the relationship between selection and maternal provisioning fluctuates between years, facilitating adaptive evolution during an early-season heat wave and causing conflict during a late-season heat wave. The consequences for evolutionary responses are uncertain and depend on the seed bank, but could result in high mortality in heat waves occurring during successive years.

Region-specific modeling of refugia and anthelmintic resistance dynamics in gastrointestinal nematodes of Nigerian small ruminants.

Molecular characteristics of organic aerosols and impacts of transboundary biomass burning in Southwest China.

Abstract Bayesian Causal Networks (BCNs) are adapted to investigate causal factors of hydroclimate variability in the Brahmaputra River Basin (BRB) during the seasonal and sub‐seasonal periods. This is the longest monsoonal river system in India, prone to frequent severe flooding. Directed Acyclic Graphs are constructed to connect response variable (streamflow) with various covariates, which include indices of large‐scale climate drivers, Sea Surface Temperatures (SSTs), across tropical Indo‐Pacific and basin Precipitation, and Bayes Factors are computed for flow regimes to quantify the strength of causal connections. Results show that eastern precipitation exerts strong influence during Early and Peak monsoon (|BF| &gt; 1), while western precipitation dominates during the late season. Niño4 index exhibits substantial influence ((|BF| &gt; 0.5) during Early, Peak and Monsoon season. Bayesian Causal Network was applied to each grid point SSTs and Antecedent SSTs in Directed Acyclic Graph configuration to capture lagged ocean influences. Regions (“hotspots”) in Central Pacific in the Niño4 and Eastern Pacific regions exert strong causality in modulating streamflow variability during Early, Peak and Monsoon season. Composite analysis of Integrated Vapor Transport and pressure anomalies show concomitant patterns. In wet years, strong moisture transport from the Bay of Bengal during Early and Peak seasons is driven by anomalous high‐pressure region over Southeast Asia, and vice‐versa in dry years. SSTs from the hotspots in machine learning model show interesting nonlinear interactions at varying thresholds in enabling skillful probabilistic estimates of seasonal flow categories. The results provide new insights into streamflow variability in BRB and potential for use developing skillful forecasts of streamflow attributes.

Abstract Crop models have been widely used to simulate crop growth and yield. However, few studies have investigated factors contributing to uncertainty in crop models. This study evaluated the predictive uncertainty of AquaCrop, WOFOST, and ORYZA version 3 in predicting the early and late season rice ( Oryza sativa L.) yield in Guangxi province, China, and quantified the relative contributions of model structure‐driven (the simplification and/or misrepresentation of crop growth‐defining, ‐limiting, and ‐reducing factors) and parameter value‐driven uncertainties to the total predictive uncertainty. Our results showed that (1) the AquaCrop model achieved the best predictive performance, with root mean square error ranging from 274 to 622 kg ha −1 , mean absolute percentage error ranging from 4% to 15%, and R 2 ranging from 0.50 to 0.63. (2) For each individual crop model, the posterior distribution of rice yield prediction was constructed using 10,000 sets of parameter vectors, which were randomly generated based on the posterior parameter distributions. The 95% confidence interval of the simulated rice yield prediction distribution contained 79.3% of the observed rice yields. (3) The average relative contributions of structure‐driven and parameter value‐driven uncertainties in the early‐season rice yield prediction were 51% and 50%, respectively, and were 39% and 61% in the late‐season rice yield prediction, respectively. This study demonstrated the importance of quantifying structure‐driven and parameter value‐driven uncertainties when evaluating the crop model predictive uncertainty in rice yield prediction.

Abstract Tropical cyclone activity was intermittent during the 2025 Atlantic season, with extended quiet periods. Cumulative activity was near‐average relative to 1991–present, despite warm sea‐surface temperatures and La Niña conditions. We compare drivers of activity in 2025 with climatology, using reanalysis data to examine variability in environmental conditions, wave activity, and circulation patterns. During the early and peak season, high pressure, a strong upper‐level trough and cool equatorial sea‐surface temperatures led to weak seed disturbances and unfavourable development conditions. Stronger disturbances coinciding with Kelvin wave activity and favourable MJO conditions led to a more active late season.

Parental care is widespread, but exclusive paternal care is rare in the animal kingdom. To understand the evolution of paternal care, it is important to evaluate the costs and benefits of this behaviour. In the family Belostomatidae (Hemiptera), males care for their eggs until they hatch. In this family, it has been revealed that egg-caring behaviour increases offspring survival and mating opportunities of egg-caring males through female mate choice, while it decreases the swimming and feeding abilities of the males as well as longevity. The behaviour would also decrease the survival rate due to predation. Although few previous studies have conducted field surveys, survival costs were detected in one study but not in another. In this study, we focused on the influence of field survey periods on the detection of egg-caring costs during the entire breeding season in the giant water bug, Appasus japonicus. Using a multi-state modelling approach, we found that the estimated survival rate was lower in egg-caring males compared to non-caring males and females. Furthermore, when we performed similar analyses during different periods (early and peak breeding season, peak breeding season, and peak and late breeding season) separately, the difference in survival rates was not clearly observed in the analyses of the former two periods, although it was still detected in the later period. Our findings suggest that paternal care in A. japonicus could incur survival costs and indicate the importance of survey timing and duration in assessments of parental costs.

Wheat plays a critical role in global food security; however, its vulnerability to rising temperatures introduces significant uncertainty about future yields in a changing climate. Although earlier studies have linked higher temperatures to yield reductions, the moderating influence of terrain elevation on crop-climate interactions remains insufficiently explored. We combine 42 years of county-level yield data (1982-2023) with phenology-specific climate exposures to evaluate how terrain elevation shapes U.S. winter wheat responses to extreme heat and precipitation. Using an econometric framework with county-specific temperature thresholds for extreme degree days, we identify a critical elevation cutoff at 350 meters that delineates two distinct yield-climate regimes. Low-elevation counties exhibit faster long-term yield growth but greater vulnerability to late season heat stress compared to high-elevation counties. Indeed, the late season coincides with the grain-filling stage, which is critical for winter wheat yield outcomes. Rolling-window estimates further reveal that heat-related yield losses have intensified since the 1980s, with late season penalties nearly doubling. Trends also indicate stronger vulnerability among low-elevation counties, especially in the recent period (2004-2023). These findings demonstrate that topography fundamentally mediates climate risks to wheat production. Adaptation may therefore require not only a latitudinal but also an elevational redistribution of wheat cultivation, reshaping the geography of U.S. production under climate change. More broadly, the results underscore the importance of integrating terrain elevation into climate-crop assessments to improve yield projections and inform adaptation strategies across diverse agricultural systems.

Background Recurrent large wildfires have become a global problem threatening human lives and assets. Extreme fire weather conditions and cured biomass increase the chances of severe and high-intensity fires that can be hard to control. The Cerrado is a tropical humid savanna with frequent, late dry season (LDS) large wildfires prevailing in protected areas. Since 2014, prescribed early dry season (EDS) fires have been applied within the integrated fire management approach. Aims To assess effects of relative humidity and fuel load on fire intensity and fuel consumption. Methods We undertook experimental fires during early and late dry seasons, during day and evening and in areas with different fuel loads. Key results We found that: (1) EDS fires under lower air relative humidity daytime conditions yielded similar fire intensities to LDS fires; (2) under higher relative humidity evening conditions, EDS fires exhibited lower intensities, which also varied with available fuels in different years. Conclusions Fire management in Cerrado landscapes should consider taking advantage of different diurnal, seasonal and fuel load conditions to address specific management objectives. Implications Acknowledging different local conditions can enhance management cost benefits.