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In this work, the inter-relationship among 10 morphological characters, 8 climatic parameters and the content of total anthocyanins in the cob core of PMV 581 purple maize, cultivated and produced in three different places in Huanuco–Peru region, has been reported. This study of morphological characters was carried out using standard descriptors, both for the plant and the cob. Data on climatic parameters were obtained from three meteorological stations near the test locations. The total anthocyanin content (Acy), expressed as the glucoside-3-cyanidin concentration, has been determined by the differential pH method. From the statistical treatment of the data obtained, the following descriptors were found to be the most representative, given that they are poorly correlated with each other, but in general, depending on the localities: i/ (morphological) grain weight per cob GWC, plant length PL and cob core weight CCW; ii/ (climatic) minimum temperature Tmin, wind speed v and relative humidity RH. Between both types of descriptors, the best correlations occur for (CCW vs. Tmin) and (GWC vs. v). On the other hand, the total anthocyanin content Acy correlates very well with the CCW and Tmin descriptors. So, the highest concentration of Acy (684.2 mg/100 g) and also the highest CCW (38.6 g/cob) have been obtained in cobs of Winchuspata (W-Q), the coldest (Tmin = 7.89 °C) of the considered localities. On the contrary, the lowest concentration of Acy (603.7 mg/100 g) and also the lowest CCW 25.4 g/cob) have been obtained in cobs of Pistaloli (P-SA), the warmest (Tmin = 19.96 °C) of the three locations. The highest GWC value (139.4 g/cob) has been obtained in cobs of Marabamba (M-Y) where the wind speed v (4.13 m/s) was the highest of the locations considered. On the contrary, the lowest value of GWC (79.6 g/cob) has been obtained for cobs of Pistaloli (P-SA) where v was the lowest (1.19 m/s). In this context, it is important to propose studies on climatic variations’ impact on different crop cycles, investigating how different agronomic management practices and the use of genetic identification/expression tools can optimize the anthocyanin production of purple maize, in order to facilitate the selection of new varieties for specific climatic conditions.

The eastern sarus crane (Antigone antigone sharpii; ESC) is a species related to wetland ecosystems in Southeast Asia. The habitat suitability of the eastern sarus crane in Ayeyarwady Delta was surveyed between March 2018 and February 2019. Eastern sarus cranes were found at 73 locations and Maximum Entropy (MaxEnt) was used to classify the habitat suitability among different seasons. MaxEnt showed the largest total area of highly suitable habitat was in the winter season (2450 km2, AUC = 0.968), while the least amount of available suitable habitat was evident during the rainy season (1028.7 km2, AUC = 0.979). A difference in the assessment of home range areas using the Minimum Convex Polygon (95% MPC) and the Kernel Density Estimate (95% KDE) was found. The total area in the winter season was highest at 95% KDE (13,839.5 km2) and lowest in the rainy season (1238.1 km2), while 95% MCP was highest in the rainy season (7892.9 km2) and lowest in the summer season (7014.6 km2). Analysis of the environmental parameters indicated that low temperature in the summer season and high precipitation in the rainy season and winter season are important for ESC habitat suitability. These climatic parameters were important for ESC in all seasons (AUC > 0.9). Important parameters influencing ESC habitat suitability were elevation, slope, distance to road in the summer season, elevation, distance to road and village and slope in the rainy season, and elevation and slope in the winter season. Annual precipitation was the main parameter influencing ESC habitat suitability in both summer and winter, while in the rainy season it was mean diurnal range (>90%).

Myrtle (Myrtus communis L.) is an aromatic and medicinal plant spreading in the Mediterranean area. The main uses of myrtle plants are liqueur and essential oil production with several biological properties. A large part of the properties of these products is due to phenolic compounds. Twenty-two myrtle cultivars originating from several areas of Sardinia Island and cultivated at the same site were analysed for phenolic compounds determination. Pearson’s correlation was used to investigate a possible correlation between phenolic compounds content observed in the cultivation site and historical agrometeorological parameters in the sites of cultivar origin. Hierarchical cluster analysis (HCA) and principal component analysis (PCA) were applied to data to evaluate the characterization of myrtle cultivars based on the relationship between sites of origin with their climate traits and phenolic compounds content as recorded in the same field of comparison. Anthocyanins are negatively correlated with minimum, maximum, and average temperatures of some months. Total phenols content decreases with high temperatures in the summer months. Rainfall affected mainly tannins content. Two principal components explained about 79% of the variability and allowed the classification of cultivars into four groups, while cultivars from Laconi, Siniscola and Cuglieri sites were not included in any group. The HCA allowed the subdivision of the wild populations into three clusters.

Atmospheric aerosol particles have a significant impact on both the climatic conditions and human health, especially in densely populated urban areas, where the particle concentrations in several cases can be extremely threatening (increased anthropogenic emissions). Most large cities located in high-income countries have stations responsible for measuring particulate matter and various other parameters, collectively forming an operating monitoring network, which is essential for the purposes of environmental control. In the city of Athens, which is characterized by high population density and accumulates a large number of economic activities, the currently operating monitoring network is responsible, among others, for PM10 and PM2.5 measurements. The need for satisfactory data availability though can be supported by using machine learning methods, such as artificial neural networks. The methodology presented in this study uses a neural network model to provide spatiotemporal estimations of PM10 and PM2.5 concentrations by utilizing the existing PM data in combination with other climatic parameters that affect them. The overall performance of the predictive neural network models’ scheme is enhanced when meteorological parameters (wind speed and temperature) are included in the training process, lowering the error values of the predicted versus the observed time series’ concentrations. Furthermore, this work includes the calculation of the contribution of each predictor, in order to provide a clearer understanding of the relationship between the model’s output and input. The results of this procedure showcase that all PM input stations’ concentrations have an important impact on the estimations. Considering the meteorological variables, the results for PM2.5 seem to be affected more than those for PM10, although when examining PM10 and PM2.5 individually, the wind speed and temperature contribution is on a similar level with the corresponding contribution of the available PM concentrations of the neighbouring stations.

Measurement of gas concentrations constitutes basic knowledge for the computation of emissions from livestock buildings. Although it is well known that hot climate conditions increase gas emissions, in the literature the relation between gas concentrations from open barns and animal-related parameters has not been investigated yet. This study aimed at filling this gap by evaluating daily gas concentrations within an open-sided barn in hot Mediterranean climate. The influence of microclimatic parameters (MC) and cow behavior and barn management (CBBM) were evaluated for ammonia (NH3), methane (CH4), and carbon dioxide (CO2) concentrations. Results showed that both MC and CBBM affected concentrations of NH3 (p < 0.02), CH4 (p < 0.001), and CO2 (p < 0.001). Higher values of NH3 concentration were detected during the cleaning of the floor by a tractor with scraper, whereas the lowest NH3 concentrations were recorded during animal lying behavior. Measured values of CO2 and CH4 were highly correlated (C = 0.87–0.89) due to the same sources of production (i.e., digestion and respiration). The different management of the cooling systems during the two observation periods reduced significantly CH4 concentrations in the barn when the cooling system in the feeding area was switched off. Based on methodological choices due to the specific barn typology, parameters related to animals can provide information on the variation of gas concentrations in the barn environment in hot climate conditions.

Forest herb-layer vegetation responds sensitively to environmental conditions. This paper compares drivers of both taxonomic, i.e., species richness, cover and evenness, and functional herb-layer diversity, i.e., the diversity of clonal, bud bank and leaf-height-seed plant traits. We investigated the dependence of herb-layer diversity on ecological determinants related to soil properties, climatic parameters, forest stand characteristics, and topographic and abiotic and biotic factors associated with forest floor structure. The study was conducted in different forest types in Slovenia, using vegetation and environmental data from 50 monitoring plots (400 m2 each) belonging to the ICP Forests Level I and II network. The main objective was to first identify significant ecological predictors and then quantify their relative importance. Species richness was strongly determined by forest stand characteristics, such as richness of the shrub layer, tree layer shade-casting ability as a proxy for light availability and tree species composition. It showed a clear positive relation to soil pH. Variation in herb-layer cover was also best explained by forest stand characteristics and, to a lesser extent, by structural factors such as moss cover. Species evenness was associated with tree species composition, shrub layer cover and soil pH. Various ecological determinants were decisive for the diversity of below-ground traits, i.e., clonal and bud bank traits. For these two trait groups we observed a substantial climatic signal that was completely absent for taxonomy-based measures of diversity. In contrast, above-ground leaf-height-seed (LHS) traits were driven exclusively by soil reaction and nitrogen availability. In synthesis, local stand characteristics and soil properties acted as the main controlling factors for both species and trait diversity in herb-layer communities across Slovenia, confirming many previous studies. Our findings suggest that the taxonomic and functional facets of herb-layer vegetation are mainly influenced by a similar set of ecological determinants. However, their relative importance varies among individual taxonomy- and functional trait-based diversity measures. Integrating multi-faceted approaches can provide complementary information on patterns of herb-layer diversity in European forest plant communities.