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AbstractSeagrasses are foundation species that provide ecosystem functions and services, including increased biodiversity, sediment retention, carbon sequestration, and fish nursery habitat. However, anthropogenic stressors that reduce water quality, impose large‐scale climate changes, and amplify weather patterns, such as marine heatwaves, are altering seagrass meadow configurations. Quantifying large‐scale trends in seagrass distributions will help evaluate the impacts of climate drivers on their functions and services. Here, we quantified spatiotemporal dynamics in abundances and configurations of intertidal and shallow subtidal seagrass (Zostera muelleri) meadows in 20 New Zealand (NZ) estuaries that span a 5‐year period (mid/late 2016–early 2022) just before, during and after the Tasman Sea 2017/18 marine heatwave, the warmest summer ever recorded in NZ. We used high‐resolution PlanetScope satellite imagery to map interseasonal seagrass extent and quantify seascape metrics across 20 estuaries along a latitudinal gradient spanning 12° in NZ. We also explored the association of changes in seagrass metrics with satellite‐derived predictors such as sea surface temperature (SST), SST anomaly (SSTa), water column turbidity, and nutrient concentration. Our analyses revealed that NZ seagrass meadows varied in areal extent between years and seasons, but with no clear patterns over the 5‐year period, implying resilience to large‐scale stressors like the 2017/18 marine heatwave. Small‐scale patterns were also dynamic, for example, patch sizes and patch configurations differed across estuaries, seasons, and years. Furthermore, seagrass patches expanded in some estuaries with increasing SST and SSTa. These results highlight dynamic seagrass patterns that likely affect local processes such as biodiversity and carbon sequestration. Our analyses demonstrate that a combination of high‐resolution satellite remote sensing and seascape metrics is an efficient and novel approach to detect impacts from anthropogenic stressors, like eutrophication and climate changes, and climate extremes like cyclones and heatwaves.

Women comprise a significant portion of the agricultural workforce in developing countries but are often less likely to attend government sponsored training events. The objective of this study was to assess the feasibility of using machine-supported decision-making to increase overall training turnout while enhancing gender inclusivity. Using data obtained from 1,067 agricultural extension training events in Bangladesh (130,690 farmers), models were created to assess gender-based training patterns (e.g., preferences and availability for training). Using these models, simulations were performed to predict the top (most attended) training events for increasing total attendance (male and female combined) and female attendance, based on gender of the trainer, and when and where training took place. By selecting a mixture of the top training events for total attendance and female attendance, simulations indicate that total and female attendance can be concurrently increased. However, strongly emphasizing female participation can have negative consequences by reducing overall turnout, thus creating an ethical dilemma for policy makers. In addition to balancing the need for increasing overall training turnout with increased female representation, a balance between model performance and machine learning is needed. Model performance can be enhanced by reducing training variety to a few of the top training events. But given that models are early in development, more training variety is recommended to provide a larger solution space to find more optimal solutions that will lead to better future performance. Simulations show that selecting the top 25 training events for total attendance and the top 25 training events for female attendance can increase female participation by over 82% while at the same time increasing total turnout by 14%. In conclusion, this study supports the use of machine-supported decision-making when developing gender inclusivity policies in agriculture extension services and lays the foundation for future applications of machine learning in this area.

Several external factors including lunar cycle and weather conditions might be associated with calving conditions. Our objective here was to determine the effects of lunar cycle and weather conditions on calving frequency and the occurrence of preterm calving in Japanese Black cows. Calving records were obtained from 905 farms in Miyazaki Prefecture, Japan. Data were collected from 41,116 calvings. We conducted two studies: Study 1 investigated the effects of lunar cycle and weather conditions on daily calving frequency (DCF) with the observational unit of each day and Study 2 investigated those effects on the occurrence of preterm calving with the observational unit for each calving. Preterm calving was defined by whether or not a cow calving before 280 days of gestation, lower 10th percentile of gestation length of the collected data, and by whether or not a cow calving before 289 days of gestation, median of the gestation length. For Study 1, lunar cycle was not associated with DCF in all cows, in only primiparous cows and in only multiparous cows. As well as lunar cycle, weather conditions such as temperature, diurnal temperature variation, the temperature-humidity index, precipitation amount, barometric pressure, relative humidity and solar radiation, were also not associated with DCF. For Study 2, lunar cycle phases were not associated with the occurrence of preterm calving. However, preterm calving was associated with all of the weather conditions (P < 0.05) except for precipitation amounts and solar radiation. Temperature, the temperature-humidity index and relative humidity were positively associated with the occurrence of preterm calving. In contrast, diurnal temperature variations and barometric pressure were negatively associated with the occurrence of preterm calving. In conclusion, the lunar cycle was not associated with DCF and preterm calving, but the weather conditions were associated with preterm calving.

To introduce new genetic diversity into the bread wheat gene pool from its progenitor, Aegilops tauschii (Coss.) Schmalh, 33 primary synthetic hexaploid wheat genotypes (SYN) were crossed to 20 spring bread wheat (BW) cultivars at the International Wheat and Maize Improvement Center. Modified single seed descent was used to develop 97 populations with 50 individuals per population using first back-cross, biparental, and three-way crosses. Individuals from each cross were selected for short stature, early heading, flowering and maturity, minimal lodging, and free threshing. Yield trials were conducted under irrigated, drought, and heat-stress conditions from 2011 to 2014 in Ciudad Obregon, Mexico. Genomic estimated breeding values (GEBVs) of parents and synthetic derived lines (SDLs) were estimated using a genomic best linear unbiased prediction (GBLUP) model with markers in each trial. In each environment, there were SDLs that had higher GEBVs than their recurrent BW parent for yield. The GEBVs of BW parents for yield ranged from -0.32 in heat to 1.40 in irrigated trials. The range of the SYN parent GEBVs for yield was from -2.69 in the irrigated to 0.26 in the heat trials and were mostly negative across environments. The contribution of the SYN parents to improved grain yield of the SDLs was highest under heat stress, with an average GEBV for the top 10% of the SDLs of 0.55 while the weighted average GEBV of their corresponding recurrent BW parents was 0.26. Using the pedigree-based model, the accuracy of genomic prediction for yield was 0.42, 0.43, and 0.49 in the drought, heat and irrigated trials, respectively, while for the marker-based model these values were 0.43, 0.44, and 0.55. The SYN parents introduced novel diversity into the wheat gene pool. Higher GEBVs of progenies were due to introgression and retention of some positive alleles from SYN parents.

Life-sciences are pointing towards an alarming worldwide pollinator decline. This decline proceeds along with overall biodiversity losses, even in the context of urban landscapes and human welfare. At the same time, social-sciences are arguing an increased distance from nature, experienced by citizens. The strong connection between the public good and pollinator sustainability, even in urban areas, is well-documented. However, usually basic and applied life-sciences tend to underestimate public perception of nature, which is better tackled by the fields of social-sciences. Therefore, more efforts are needed to link scientific questions and public 'perception' of nature. We designed a transversal project where research questions directly confront public concerns: i.e., even while addressing scientific knowledge gaps, our questions directly arise from public concerns. Social studies highlighted that appreciation of (exotic) plants is related to the impact they may have on the surrounding natural environment: therefore, we investigated links of native and exotic flowers to local pollinators. Other studies highlighted that scientific results need to link to everyday individual experience: therefore, we investigated pollination modes of the renown Salvia, native and exotic, largely used in cuisine and gardening. The botanic garden was the promoter of scientific questions addressed by the public, and also collated the results in a travelling exhibition. The exhibition, together with a dedicated catalogue, were especially designed to enlighten the wide public on the relationships that plants, native and exotic alike, establish with the surrounding world.

Background Atopic dermatitis (AD) is a common inflammatory and chronically relapsing disorder with increasing prevalence. However, little is known about its prevalence in Shanghai, the top metropolitan of China. This study will estimate and compare the prevalence of AD in urban and rural areas in representative samples of 3 to 6-year-old children in Shanghai. Methodology/Principal Findings A descriptive cross-sectional study was performed. Pre-school children were obtained by cluster sampling from 8 communities in different districts in Shanghai. The main instrument was the core questionnaire module for AD used in the U.K. Working Party's study. All the data were statistically analyzed by EpiData 3.1 and SPSS16.0. A total of 10436 children completed the study satisfactorily, with a response rate of 95.8%. The prevalence of AD in 3 to 6-year-old children was 8.3% (Male: 8.5%, Female: 8.2%). The prevalence in urban areas of Shanghai was gradiently and significantly higher than that in rural areas. The highest prevalence was in the core urban area (10.2% in Xuhui Tianping) vs. the lowest far from the urban areas (4.6% in Chongming Baozhen). Conclusions/Significance The prevalence of AD was 8.3% (95%CI: 7.6%–9.1%) in children aged 3 to 6 in Shanghai. The prevalence of AD decreased from the center to the rural areas in Shanghai.

The basidiomycete Heterobasidion annosum (Fr.) Bref. s.l. is a filamentous white rot fungus, considered to be the most economically important pathogen of conifer trees. Despite the severity of the tree infection, very little is known about the molecular and biochemical aspects related to adaptation to abiotic stresses. In this study, the osmotic and oxidative tolerance as well as the role of the HaHOG1 Mitogen Activated Protein Kinase (MAPK) gene were investigated. The transcript levels of the yeast orthologues GPD1, HSP78, STL1, GRE2 and the ATPase pumps ENA1, PMR1, PMC1 known to have an important role in osmotolerance were also quantified under salt osmotic conditions. The HaHOG1 gene was used for a heterologous expression and functional study in the Saccharomyces cerevisiae Δhog1 strain. Moreover, the phosphorylation level of HaHog1p was studied under salt osmotic and oxidative stress. The result showed that H. annosum displayed a decreased growth when exposed to an increased concentration of osmotic and oxidative stressors. GPD1, HSP78, STL1 and GRE2 showed an induction already at 10 min after exposure to salt stress. Among the ATPase pumps studied, PMC1 was highly induced when the fungus was exposed to 0.2 M CaCl₂ for 60 min. The heterologous expression of the HaHOG1 sequence in yeast confirmed that the gene is able to restore the osmotolerance and oxidative tolerance in the S. cerevisiae hog1Δ mutant strain. The HaHog1p was strongly phosphorylated in the presence of NaCl, KCl, H₂O₂ but not in the presence of CaCl₂ and MgCl₂. The GFP-HaHog1p fusion protein accumulated in the nuclei of the S. cerevisiae hog1Δ cells when exposed to high osmotic conditions but not under oxidative stress. These results provide the first insights about the response of H. annosum to osmotic and oxidative stress and elucidate the role of the HaHOG1 gene in such conditions.