Annual Season Research Articles

Trait Interactions and Yield Enhancement in Linseed (Linum usitatissimum L.): Insights from Correlation and Path Analysis

Linseed (Linum usitatissimum L.) is a self-pollinated (2n = 30) annual Rabi season crop mainly cultivated for flax fiber and oil due to its commercial use. The present investigation was carried out to study an association analysis among the yield and yield attributes using 75 linseed genotypes including 10 checks in a randomized block design with three replications at Oilseeds Research Farm, Kalyanpur, Chandra Shekhar Azad University of Agriculture and Technology, Kanpur, Uttar Pradesh, (India) during Rabi season of 2019-20. The correlation analysis revealed that the traits number of secondary branches per plant followed the number of primary branches per plant and number of capsules per plant at both the genotypic and phenotypic levels. The results of the path coefficient analysis revealed that traits such as the number of secondary branches per plant, number of capsules per plant, number of seeds per capsule, and plant height exhibited a strong and positive direct effect on seed yield per plant at both the genotypic and phenotypic levels. The seed yield can be improved by selecting traits such as number of primary branches per plant, number of secondary branches, number of capsules per plant, and plant height. It is recommended that the breeder focus on these traits in linseed to enhance its commercial value for the farming community.

30 years of terrestrial insect richness patterns across elevation: What have we learned? A global meta-analysis.

Understanding elevation variation in biodiversity is a classic question in ecology and has implications for understanding climate change impacts on mountain ecosystems. While insects are the largest group of animals, the global trend in insect species richness with elevation is unknown. To date, single studies and taxa-specific syntheses have provided no single picture, finding variable patterns of insect richness with elevation. A global synthesis across systems would provide a better understanding of how insect species richness changes with elevation and the possible environmental correlates of those patterns. We used published studies of terrestrial insect elevation gradients from 1990 to 2020 to ask: How do insect species richness change with elevation, and which environmental variables best explain this relationship statistically? With 1486 sites spanning 151 species richness-elevation gradients from 80 studies from four diverse insect taxonomic groups and five biomes, we found that overall proportional richness reached a low-elevation plateau and then decreased. We also show that mean annual temperature and seasonality best explain this trend. We suggest best practices and areas of interest for the future of insect richness-elevation studies, including underrepresented groups, geographic areas, and more standardized methods.

Macro- and micro-geographic genetic variation in early fitness traits in populations of maritime pine (Pinus pinaster Ait.).

Assessing adaptive genetic variation and its spatial distribution is crucial to conserve forest genetic resources and manage species' adaptive potential. Macro-environmental gradients commonly exert divergent selective pressures that enhance adaptive genetic divergence among populations. Steep micro-environmental variation might also result in adaptive divergence at finer spatial scales, even under high gene flow, but it is unclear how often this is the case. Here, we assess genetic variation in early fitness traits among distant and nearby maritime pine (Pinus pinaster Ait.) populations, to investigate climatic factors associated with trait divergence, and to examine trait integration during seedling establishment. Open pollinated seeds were collected from seven population pairs across the European species distribution, with paired populations spatially close (between <1 km up to 21 km) but environmentally divergent. Seeds were sown in semi-natural conditions at three environmentally contrasting sites, where we monitored seedling emergence, growth and survival. At large spatial scales, we found significant genetic divergence among populations in all studied traits, with certain traits exhibiting association with temperature and precipitation gradients. Significant trait divergence was also detected between pairs of nearby populations. Besides, we found consistent trait correlations across experimental sites, notably heavier seeds and earlier seedling emergence were both associated with higher seedling survival and fitness over two years in all experimental conditions. We identified mean annual temperature and precipitation seasonality as potential drivers of P. pinaster population divergence in the studied early-life traits. Populations genetically diverge also at local spatial scales, potentially suggesting that divergent natural selection can override gene flow along local-scale ecological gradients. These results suggest the species exhibits substantial adaptive potential that has allowed it to survive and evolve under contrasting environmental conditions.

Variation in the Phenolic Profile and Antioxidant, Antihyperglycemic, and Anti-Inflammatory Activity in Leaves of Cotoneaster zabelii during Growing Season

Cotoneaster zabelii is a medicinal plant that is beneficial due to its polyphenol-rich leaves. In the course of optimizing the harvest time for C. zabelii cultivated in Poland, the leaf samples were collected monthly during the annual plant vegetation season, and the hydromethanolic leaf extracts were evaluated for their phenolic composition and model biological activities, including antioxidant, antihyperglycemic, and anti-inflammatory effects in vitro. The phenolic profiles were analyzed using UHPLC-PDA-ESI-MS3, HPLC-PDA, and spectrophotometric methods (total phenolic content, TPC) to understand their seasonal variability and its correlation with bioactive properties. The identified phenolic compounds included caffeic acid derivatives, flavan-3-ols (especially (−)-epicatechin and procyanidins B-type), and flavonoids like quercetin mono- and diglycosides. Leaves harvested in July and October contained the highest polyphenolic levels and demonstrated significant antioxidant activity in most tests. The leaves harvested in July, September, and October showed optimal anti-inflammatory effects, whereas the highest antihyperglycemic activity was observed in the leaves collected from June to July. Regarding polyphenolic levels and bioactivity, the summer and autumn months appear to be the most advantageous for harvesting leaf material of optimal quality for phytotherapy.

Disentangling seasonal and annual precipitation signals in the tropics over the Holocene: Insights from δD, alkanes and GDGTs

Rainfall seasonality in the tropics has a substantial impact on both ecosystems and human livelihoods. Yet, reconstructions of past rainfall variability have so far generally been unable to differentiate between annual and seasonal precipitation changes. Past variations in seasonality are therefore largely unknown. Here, we disentangle hydrogen isotopic (δD) signals from terrestrial leaf waxes and algae in an 8000-year peat core from Sumatra, which reflect annual versus wet season rainfall signals, respectively. We validate these results using lipid biomarkers by reconstructing vegetation dynamics via n-alkane distributions and peatland hydrological conditions using glycerol dialkyl glycerol tetraethers (GDGTs), as well as biomass burning using levoglucosan concentrations in the core. Finally, we compare our proxy results to a transient climate model simulation (MPI-ESM1.2) to identify the mechanism for seasonality changes. We find that algal δD indicates stronger Indonesian-Australian Summer Monsoon (IASM) precipitation in the Mid-Holocene, between 8 and 4.2 cal ka BP. A period of alternating flooding, droughts and wildfires is reconstructed between 6 and 4.2 cal ka BP, implicating very strong monsoonal precipitation and drying out and burning during a longer and intensified dry season. We attribute this strong rainfall seasonality in the Mid-Holocene mainly to orbitally forced insolation seasonality and a strengthened IASM, consistent with the modeling results. In terms of annual rainfall, terrestrial plant δD, vegetation composition and GDGTs all indicate wetter conditions peaking between 3 and 4.5 cal ka BP, preceded by drier conditions, followed by drastic and rapid drying in the late Holocene from around 2.8 cal ka BP. Our multiproxy annual precipitation reconstruction thereby indicates the wettest overall conditions approximately 1500–2000 years later than a nearby speleothem δ18O record, which instead follows the seasonally biased algal δD in our record. We, therefore, hypothesize that speleothem reconstructions over the Holocene in parts of the tropics with low but significant seasonality may carry a stronger seasonal component than previously suggested. The data presented here contribute with new insights on how isotopic rainfall proxies in the tropics can be interpreted. Our findings resolve the seasonal versus annual components of Holocene rainfall variability in the Indo-Pacific Warm Pool region, highlighting the importance of considering seasonality in rainfall reconstructions.

Modeling the Current and Future Distribution of Indianthus virgatus (Roxb.) Suksathan & Borchs.: AMonotypic Plant Endemic to the Western Ghats-Sri Lanka Biodiversity Hotspot.

Species distribution modeling (SDM) is an essential tool in ecology and conservation for predicting species distributions based on species presence/absence data and environmental variables. The present study aimed to understand the distribution pattern and habitat suitability of Indianthus virgatus under current and future climate change scenarios (2050 and 2070) using MaxEnt (3.4.4) and Wallace Ecological Modeling (v2.1.2) tools. The study also intended to identify key environmental predictors of I. virgatus' distribution. Species occurrence data were collected from various sources, including herbarium (online and physical), field surveys, and online databases, yielding 105 unique locations in the Western Ghats (WG) of India and Sri Lanka. We used 19 bioclimatic variables and elevation data sourced from WorldClim for modeling. The MaxEnt and Wallace models showed excellent performance in predicting the distribution of I. virgatus, with area under the curve values of 0.958 (± 0.002) and 0.93, respectively. In MaxEnt modeling, Temperature Seasonality (bio4) was the most significant environmental parameter, followed by the Precipitation of the Coldest Quarter (bio19). In contrast, the Annual Mean Temperature (bio1), Temperature Seasonality (bio4), and Annual Precipitation (bio12) were among the key contributors in Wallace EcoMod. Both the models predicted relatively lesser areas in the species' distribution range as highly suitable habitats (HSH) in India and Sri Lanka. We found divergent trends in predicting I. virgatus distributions using MaxEnt and Wallace EcoMod, particularly for future projections. Nevertheless, both models predicted significant habitat loss under future climate change scenarios, especially under RCP85, with varying degrees of suitability across India and Sri Lanka. Overall, our findings on expected habitat loss under future climate change scenarios highlight the importance of conserving I. virgatus, which has already been declared critically endangered (CR) in Sri Lanka.

Rainfall And Drought Characteristics For Crop Planning In Cuttack District Of Odishastate, India

The increasing frequency of agricultural droughts and variability in rainfall patterns over the past three decades prompted this study, which analyzed 34 years of block-wise daily rainfall data (1988-2021) from Cuttack district, Odisha. The aim was to determine the long-term average and temporal variability of rainfall on weekly, monthly, seasonal, and annual scales, with a focus on identifying strategies to mitigate production risks in the region. The average annual rainfall in Cuttack was 1597.6 mm, with August receiving the highest amount of rainfall (476 mm), followed by July (407 mm) during the monsoon season. A trend analysis on rainfall over the past 34 years showed an increasing pattern of an average 6.03 mm and 3.6 mm per year in annual and kharif season rainfall, respectively. Agricultural droughts were frequently observed during the early (22-28 Standard Meteorological Week) and late (36-42 SMW) stages of kharif crops. The study also revealed that the station is prone to mild-moderate meteorological droughts of different intensities, including mild,moderate, and severe. To minimize production risks, short duration, low water-requiring, high-value crops such as maize, pulses, oilseeds, and some vegetables are recommended for this region.

Modeling spatiotemporal distribution of yellow rust wheat pathogen using machine learning algorithms: Insights from environmental assessment

The yellow rust pathogen (Puccinia striiformis Westend) poses a significant threat to wheat production in the world, necessitating a comprehensive understanding of its spatiotemporal distribution and the influence of climatic factors. In this study, we employed an ensemble of four prominent machine learning algorithms to assess the impact of various environmental and remote sensing variables on the spread of yellow rust at a national scale. Our analysis incorporated 55 climatic parameters, including monthly temperature, precipitation, solar radiation, and wind speed. The results demonstrated that the RF algorithm yielded robust predictions, with a Receiver Operator Characteristic (ROC) of 0.916 and True Skill Statistic (TSS) of 0.748. Furthermore, the study identified key influencing variables for wheat disease modeling, such as annual precipitation, temperature seasonality, and isothermality. Projections based on the model indicate a potential decrease in disease spread by 2050 in specific regions. The findings underscore the efficacy of ensemble modeling in predicting the spatiotemporal distribution of yellow rust on a large scale, offering valuable insights for the development of robust agricultural management strategies in the face of evolving climate conditions.

Spatiotemporal climate variability and food security implications in the Central Ethiopia Region

Studies focusing on the spatiotemporal distribution of climatic parameters and meteorological drought are of paramount significance for countries like Ethiopia, where climate change and variability cause major losses to rain-dependent agriculture. In this study, the National Meteorology Institute of Ethiopia provided an Enhanced National Climate Services (ENACTS) dataset at a spatial resolution of approximately 4 km by 4 km over 38 years (1981–2018) was used to study climate trends, spatiotemporal variability, and meteorological drought in the Central Ethiopia Region. Coefficient of variation (CV), Standardized Rainfall Anomaly (SRA), Standardized Precipitation Index (SPI), Mann-Kendall trend test, and Sen's slope were used for the analysis. The findings suggest that Belg rainfall (also known as "small-rain") varied greatly in space and time over the study area, with area-averaged CV of 29 % and pixel-level CVs ranging from 63 to 93 %. The average precipitation during Belg experienced a 15 % decrease from 2000 to 2019 compared to the preceding two decades, from 1981 to 1999. The maximum temperature has increased significantly during the Annual, Belg, and Bega seasons. The SPI and SRA showed that there have been multiple drought episodes with rising negative rainfall anomalies, with a drought occurring every 2.9 years during the Kiremt (also called "big rain", spanning from June to September) and Belg seasons. The growing negative rainfall anomaly, high CV, and highly significant increase in mean maximum temperature during the Belg season is concerning for food security and poverty eradication. The notable rise in rainfall during the June (sowing period) and November (harvesting period) also hurts crop production during the main cropping season. Thus, developing appropriate adaptation strategies and policies oriented toward climate-resilient agriculture is crucial to meet the global sustainable development goals (SDGs) and Africa Union's Agenda 2063.

Probabilistic Assessment of the Impact of Electric Vehicle Fast Charging Stations Integration into MV Distribution Networks Considering Annual and Seasonal Time-Series Data

Electric vehicle (EV) fast charging stations (FCSs) are essential for achieving net-zero carbon emissions. However, their high power demands pose technical hurdles for medium-voltage (MV) distribution networks, resulting in energy losses, equipment performance issues, overheating, and unexpected tripping. Integrating FCSs into the grid requires considering annual and seasonal variations in EV fast-charging energy consumption. Neglecting these variations can lead to either underestimating or overestimating the impacts of FCSs on the networks. This paper introduces a probabilistic method to assess voltage profile violations, overload capacity, and increased power losses due to FCSs. By incorporating annual and seasonal time-series data, the method accounts for uncertainties related to EV fast charging. Applied to an MV feeder in Brazil, our evaluations highlight the impact of annual power consumption seasonality on EV-grid integration studies. Considering seasonal dependency is crucial for precise impact assessments of MV distribution networks. The proposed method aids utility engineers and planners in quantifying and mitigating the effects of EV fast charging, contributing to more reliable MV grid integration strategies.

Ecological Shifts: Plant Establishment in an Animal-Based Ecosystem

Shifts from saltmarsh to mangroves are well-documented at mangrove poleward boundaries. A regime shift from intertidal oyster (Crassostrea virginica) reefs to mangrove islands has recently been documented in transitional phases in Florida, USA. To understand the local drivers of an oyster/mangrove regime shift and potential tipping points leading to a permanent mangrove state, we tracked all mangrove propagules (n = 1681) across 15 intertidal oyster reefs with or without adult mangroves for 15 months in Mosquito Lagoon, FL. While no propagule bottleneck was observed, few (3.2%) mangrove propagules/seedlings survived on reefs with no prior encroachment, compared to 11.3% and 16.1% on reefs with established older (pre-1943) or newer (1943 to present) adult mangrove stands, respectively. In total, 90.6% of the arriving propagules were from the red mangrove Rhizophora mangle; 13.2% of these were alive at the end of this study. Survival was &lt;1% for black (Avicenna germinans) and 0% for white (Laguncularia racemosa) mangroves. Factors that promoted red mangrove success included close proximity (≤0.3 m) to adult mangroves, especially black mangroves; partial, upright burial of propagules in sediment; and arrival on reefs after annual high-water season. Additionally, once reefs had 50% mangrove cover, the density of red mangrove seedlings increased from 0.04 to 0.46 individuals m−2. Although climate change has alleviated the impact of extreme freezes on mangroves, local factors determine whether the regime shift will be complete and permanent; positive feedback loops associated with established mangroves suggest mangrove recruitment on intertidal oyster reefs will continue to increase.

Global risk of dengue outbreaks and the impact of El Niño events

BackgroundDengue fever is an arboviral disease caused by the dengue virus (DENV). Its geographical distribution and health burden have been steadily increasing through tropical and subtropical climates in recent decades. MethodsWe developed a temperature- and precipitation-dependent mechanistic model for the global risk of dengue fever outbreaks using the basic reproduction number (R0) as the metric of disease transmission risk. We used our model to evaluate the global risk of dengue outbreaks from 1950 to 2020 and to investigate the impact of annual seasons and El Niño events. ResultsWe showed that the global annual risk of dengue outbreaks has steadily increased during the last four decades. Highest R0 values were observed in South America, Southeast Asia, and the Equatorial region of Africa year-round with large seasonal variations occurring in other regions. El Niño was shown to be positively correlated with the global risk of dengue outbreaks with a correlation of 0.52. However, the impact of El Niño on dengue R0 was shown to vary across geographical regions and between El Niño events. ConclusionsStrong El Niño events may increase the risk of dengue outbreaks across the globe. The onset of these events may trigger a surge of control efforts to minimize risk of dengue outbreaks.

Jump Squat Vs. Resisted Sprint Training Programs Applied to Elite Youth Soccer Players: Effects on Sprint and Power-Related Performance.

Loturco, I, Pereira, LA, Mercer, VP, Oliveira, LP, Zanetti, V, Lima, L, Bastos, T, Moura, TBMA, and McGuigan, MR. Jump squat vs. resisted sprint training programs applied to elite youth soccer players: effects on sprint and power-related performance. J Strength Cond Res XX(X): 000-000, 2024-This study examined the effectiveness of 2 different and widely used training programs on the sprint and power-related performance of youth soccer players. Two distinct training strategies-vertically oriented jump squats (JSs) or horizontally oriented resisted sprints (RSs)-were executed under the same absolute loading conditions (i.e., 30% of the athletes' body mass [BM]) during a 4-week preseason period. Training schemes, loading intensities (based on %BM), and the number of experimental sessions were designed in conjunction with the soccer club's coaching staff, considering the calendar, available resources, and regular training programs. Twenty-five under-17 soccer players performed a series of speed, power, and jump tests before and after 10 resisted training sessions, consisting solely of loaded JS or RS. Overall, neither group (i.e., JS or RS training groups) exhibited any improvement in linear sprint and change-of-direction (COD) speed. Conversely, vertical jumping ability and peak velocity in the loaded JS increased significantly only in the JS group, which may positively affect players' performance and training prescription during short soccer preseasons. Given the challenges in enhancing sprint speed among soccer players during preseasons (and even over the competitive season), coupled with the limited effectiveness of RS in improving sprinting, COD, and jumping capabilities within congested and short training phases (i.e., ≤4 weeks), the regular use of RS training methods during these phases may be highly questionable. Coaches should carefully consider these critical limitations and potential disadvantages when designing neuromuscular training programs for soccer players during the preparatory phases of the annual training season.

Identification of Potential Future Areas for Sustainable Cashew (Anacardium occidentale L.) Nut Production in Togo Using the Maxent Model

Understanding present and potential habitats is critical for developing climate-resilient cashew-growing techniques and sustainable management strategies. This study aims to identify the existing distribution of Anacardium occidentale L. in Togo and anticipates the possible impact of climate change on its habitat distribution by 2050 using two global circulation models (HadGEM3-GC3.1-L and MIROC6) and two shared socioeconomic paths (SSP245 and SSP585). The maximum entropy algorithm, 2538 species occurrence records, and a set of seventeen (17) climatic and soil variables were used. The findings revealed that soil, followed by annual precipitation (bio12) and temperature seasonality (bio4), are the most important environmental variables influencing cashew distribution in Togo. According to the present model, 78.92% of Togo's topography is very favourable to sustainable cashew-growing practices. According to the MOROC6 Model, very favourable cashew nut production areas will be decreased to 5.24% in the SSP 245 scenario and altogether disappear with the SSP585 scenario by 2050. However, for the HadGEM3-GC3.1-L model by 2050, the areas of sustainable cashew nut production in Togo will be reduced to 3.71% and 0.26% respectively for the SSP245 and 585 scenarios. In short, the results of this study, which was carried out for the first time in Togo, point out the need to put in place a strategy for the conservation and sustainable cultivation of cashew trees in Togo.

Influenza virus strains expressing SARS-CoV-2 receptor binding domain protein confer immunity in K18-hACE2 mice

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease (COVID-19), rapidly spread across the globe in 2019. With the emergence of the Omicron variant, COVID-19 shifted into an endemic phase. Given the anticipated rise in cases during the fall and winter seasons, the strategy of implementing seasonal booster vaccines for COVID-19 is becoming increasingly valuable to protect public health. This practice already exists for seasonal influenza vaccines to combat annual influenza seasons. Our goal was to investigate an easily modifiable vaccine platform for seasonal use against SARS-CoV-2. In this study, we evaluated the genetically modified influenza virus ΔNA(RBD) as an intranasal vaccine candidate for COVID-19. This modified virus was engineered to replace the coding sequence for the neuraminidase (NA) protein with a membrane-anchored form of the receptor binding domain (RBD) protein of SARS-CoV-2. We designed experiments to assess the protection of ΔNA(RBD) in K18-hACE2 mice using lethal (Delta) and non-lethal (Omicron) challenge models. Controls of COVID-19 mRNA vaccine and our lab’s previously described intranasal virus like particle vaccine were used as comparisons. Immunization with ΔNA(RBD) expressing ancestral RBD elicited high anti-RBD IgG levels in the serum of mice, high anti-RBD IgA in lung tissue, and improved survival after Delta variant challenge. Modifying ΔNA(RBD) to express Omicron variant RBD shifted variant-specific antibody responses and limited viral burden in the lungs of mice after Omicron variant challenge. Overall, this data suggests that ΔNA(RBD) could be an effective intranasal vaccine platform that generates mucosal and systemic immunity towards SARS-CoV-2.

Interannual variability and seasonality of litterfall in three temperate and boreal forest ecosystems of eastern Canada: A synthesis of long-term monitoring

Litterfall is a major pathway for transferring aboveground biomass to the forest floor and thus plays an important role in building forest soil carbon stocks. However, inter- and intra-annual variability of litterfall remains poorly documented, especially in North American temperate and boreal forests, due to the lack of recent long-term studies at high sampling frequencies. This potentially creates uncertainties in estimates of forest carbon budget models. The objectives of the present study were to 1) quantify the mean annual flux, interannual variability, and seasonality of litterfall in three sites (dominated respectively by sugar maple (Acer saccharum Marsh.), balsam fir (Abies balsamea (L.) Mill. 1768), and black spruce (Picea mariana (Mill.) B.S.P.)) in eastern Canada over a period of 22–32 years, 2) relate the litterfall amounts and temporal variations to the changes in the size of major organic matter pools in these ecosystems, and 3) compare our litterfall estimates with reference values used in national greenhouse gas inventories. Litterfall production decreased from the sugar maple to the balsam fir and black spruce sites, preponderantly due to species composition. Litterfall evolution was related to the aboveground biomass of live trees in both conifer sites; in contrast, in the broadleaf site, changes in forest composition and structure were apparently the main drivers. The litterfall seasonality varied between broadleaf and conifer sites and could be explained by a sigmoidal model. Substantial departures from the seasonality for some given years were likely due to important climatic anomalies. Forest floor biomass remained stable over time at all three sites despite the increase in litterfall at the balsam fir and sugar maple sites and rapid forest floor turnover at the latter site. Our analyses of litterfall suggest that reference values from the literature used for national greenhouse gas inventories underestimate annual litterfall and forest floor carbon stocks for temperate and boreal forests.

Changes in Runoff and Sediment Loads in the Tuhai River Basin and the Factors Influencing These Changes

In this study, rainfall, runoff, and sediment load data were collected from the Tuhai River Basin from 1972 to 2021. The Mann–Kendall test, runoff–sediment curve, and double mass curve were used to identify the characteristics and factors influencing runoff and sediment loads in the Tuhai River Basin. The results showed that the average annual runoff and sediment loads in the river basin were 4.03 × 108 m3 and 3.52 × 108 kg, respectively; furthermore, the flood season (June–September) accounted for 79.9% and 99.4% of these values, respectively. There were no apparent runoff trends in the annual, flood, and non-flood (October–May) stages, and the annual and flood season sediment loads decreased significantly. The abrupt change points of annual and flood season runoff in the Tuhai River Basin mainly occurred from 2003 to 2004 and from 2013 to 2014. Moreover, the abrupt change points of annual and flood season sediment load only occurred from 1978 to 1979. The runoff–sediment curve showed a clear power function relationship between runoff and sediment loads. The runoff in the Tuhai River Basin from 2003 to 2013 was mainly affected by precipitation. Additionally, the contributions of human activities to runoff and sediment load reduction in the Tuhai River Basin were 57.7–88.9% and 63.1–86.0%, respectively. The increase in human water consumption was the main reason for the decrease in runoff in the Tuhai River Basin. Furthermore, the measures taken in soil and water conservation and reservoir construction were the main factors behind a reduction in sediment loads in the Tuhai River Basin.

Seasonal life cycle of Pintomyia longiflocosa (Diptera: Psychodidae) under semi-controlled conditions in the Huila state, Colombia.

Pintomyia longiflocosa is considered a vector of etiological agents of cutaneous leishmaniasis. The objective of this research was to establish the parameters of the life cycle of Pi. longiflocosa in semi-controlled conditions in a rural area of the Campoalegre municipality, Huila, Colombia. The life cycle of individuals of Pi. longiflocosa, obtained from two cohorts of collected, fed, and individualized females, was monitored during two different times of the year (between February and August 2020 and between July 2020 and January 2021, respectively). Determining parameters associated with the fertility and fecundity, time and attributes of development and survival, and its association with abiotic variables. The average duration of Cycle 1 (C1) and Cycle 2 (C2) was 134.9 and 148.78 days, respectively. The gonotrophic cycle of parental females presented significant differences (p-value <0.05) between C1 and C2 (8.47 and 11.42 days) as well as between fecundity and fertility parameters. The number of days it takes the development of the immature stages between the two cycles studied, also showed significant differences in the larvae II (15.21 and 22.23), larvae III (11.93 and 17.56), and pupae (24.48 and 22.9) stages. During C1, the survival rate was higher and consistent with the productivity of adult individuals (F1), compared to C2. Fecundity and fertility values were significantly higher in C2. Finally, a significant correlation between the number of individuals and temperature was evidenced in C1 while, for C2, there was a negative correlation with precipitation. Significant differences were found in several biological and reproductive parameters between the two cycles monitored. The parameters of the life cycle of Pi. longiflocosa in its natural habitat would be influenced by environmental factors related to the annual seasonality in the sub-Andean rural area, conditioning the temporal distribution of this species and, consequently, the possible transmission of causative agents of cutaneous leishmaniasis.

Deployment of attractive targeted sugar baits in western Zambia: installation, monitoring, removal, and disposal procedures during a Phase III cluster randomized controlled trial

BackgroundAttractive Targeted Sugar Baits (ATSBs) offer a complementary vector control strategy to interventions targeting blood feeding or larval control by attacking the sugar feeding behaviour of adult mosquitoes using an attract-and-kill approach. Western Zambia was the first location to receive and deploy ATSB Sarabi version 1.2 stations in a Phase III cluster randomized controlled trial. This paper describes ATSB station installation, monitoring, removal, and disposal, quantifies ATSB station coverage, and reports major reasons for ATSB station replacement.MethodsATSB stations were deployed during two annual transmission seasons, through scheduled installation and removal campaigns. During deployment, monitoring was conducted per protocol to maintain high coverage of the ATSB stations in good condition. Routine monitoring visits during the trial captured details on ATSB station damage necessitating replacement following pre-defined replacement criteria. Annual cross-sectional household surveys measured ATSB station coverage during peak malaria transmission.ResultsA total of 67,945 ATSB stations were installed in Year 1 (41,695 initially installed+ 26,250 installed during monitoring) and 69,494 ATSB stations were installed in Year 2 (41,982 initially installed+ 27,512 installed during monitoring) across 35 intervention clusters to maintain high coverage of two ATSB stations in good condition per eligible household structure. The primary reasons for ATSB station replacement due to damage were holes/tears and presence of mold. Cross-sectional household surveys documented high coverage of ATSB stations across Year 1 and Year 2 with 93.1% of eligible structures having ≥ 2 ATSB stations in any condition.DiscussionATSB station deployment and monitoring efforts were conducted in the context of a controlled cRCT to assess potential product efficacy. Damage to ATSB stations during deployment required replacement of a subset of stations. High coverage of eligible structures was maintained over the two-year study despite replacement requirements. Additional research is needed to better understand the impact of damage on ATSB station effectiveness under programmatic conditions, including thresholds of threats to physical integrity and biological deterioration on product efficacy.ConclusionsOptimizing ATSB stations to address causes of damage and conducting implementation research to inform optimal delivery and cost-effective deployment will be important to facilitate scale-up of ATSB interventions.

Conifer fossil woods from the Upper Cretaceous (Neuquén Group) of Mendoza Province, Argentina

An assemblage of four silicified woods from the Neuquén Group (Upper Cretaceous) collected in the Cara Cura Mountain Range, southwest of Mendoza Province, Argentina is described. The specimens are composed of secondary xylem, and the preservation varies among them. Two specimens were assigned to Agathoxylon antarcticum (Poole et Cantrill) Pujana et al., related to Araucariaceae. This fossil-species is characterized by its distinct growth ring boundaries, uni- to biseriate araucarian pitting on tracheid radial walls, and araucarioid cross-fields. Other specimens could not be assigned to a fossil-genus because of their poor preservation, but they show a conifer anatomy. The distinct growth ring boundaries of some specimens suggest annual seasonality. Additionally, the presence of small globose structures in areas of highly degraded secondary xylem is consistent with the erosion bacteria type observed in modern and fossil woods.