The genus Beauveria is considered a cosmopolitan anamorphic and teleomorphic genus of soilborne necrotrophic arthropod-pathogenic fungi that includes ecologically and economically important species. Species identification in Beauveria is difficult because of its structural simplicity and the lack of distinctive phenotypic variation. Therefore, the use of multi-locus sequence data is essential to establish robust species boundaries in addition to DNA-based species delimitation methods using genetic distance, coalescent, and genealogical concordance approaches (polyphasic approaches). In this regard, our study used multilocus phylogeny and five DNA-based methods to delimit species in Beauveria using three molecular makers. These polyphasic analyses allowed for the delimitation of 20–28 species in Beauveria, confirming cryptic diversity in five species (i.e. B. amorpha, B. bassiana, B. diapheromeriphila, and B. pseudobassiana) and supporting the description of B. peruviensis as a new taxon from northeastern Peru. The other five species were not evaluated as they did not have enough data (i.e. B. araneola, B. gryllotalpidicola, B. loeiensis, B. medogensis, and B. rudraprayagi). Our results demonstrate that the congruence among different methods in a polyphasic approach (e.g. genetic distance and coalescence methods) is more likely to show reliably supported species boundaries. Among the methods applied in this study, genetic distance, coalescent approaches, and multilocus phylogeny are crucial when establishing species boundaries in Beauveria.

Cadmium (Cd) contamination threatens cocoa farming in the province of Bagua in Amazonas, Peru. This study reports our assessment of Cd concentrations in cocoa farm soils, and in cocoa roots, leaves, testa, and cotyledon, thus evaluating the magnitude of the problem caused by Cd exposure. For our analysis, we sampled agricultural soil, cocoa roots, leaves and pods at 29 farms in the province of Bagua. Concentrations of Cd in each of the samples were measured and correlated with selected variables at each sampling site. Within our collection of samples, Cd levels showed great variability. In soil, Cd concentrations ranged between 1.02 and 3.54 mg kg−1. Concentrations of this metal within cocoa trees measured from roots, leaves, testa, and cotyledon, Cd ranged from 0.49 mg kg−1 to 2.53 mg kg−1. The cocoa trees exhibited variable degrees of allocation Cd from the soil to their tissues and thus considerable variation among themselves. We found that Cd amounts in roots were up to five times more concentrated than Cd levels in the soils and 2.85 times [Cd] the amounts found in cotyledon. Soil pH is a key variable enabling the uptake of this metal. Most importantly, our evaluation determined that measurements from the majority of farms exceeded the maximum permissible limits established by Peruvian and European legislation.

During the latest decades, the Amazon has experienced a great loss of vegetation cover, in many cases as a direct consequence of wildfires, which became a problem at local, national, and global scales, leading to economic, social, and environmental impacts. Hence, this study is committed to developing a routine for monitoring fires in the vegetation cover relying on recent multitemporal data (2017–2019) of Landsat-8 and Sentinel-2 imagery using the cloud-based Google Earth Engine (GEE) platform. In order to assess the burnt areas (BA), spectral indices were employed, such as the Normalized Burn Ratio (NBR), Normalized Burn Ratio 2 (NBR2), and Mid-Infrared Burn Index (MIRBI). All these indices were applied for BA assessment according to appropriate thresholds. Additionally, to reduce confusion between burnt areas and other land cover classes, further indices were used, like those considering the temporal differences between pre and post-fire conditions: differential Mid-Infrared Burn Index (dMIRBI), differential Normalized Burn Ratio (dNBR), differential Normalized Burn Ratio 2 (dNBR2), and differential Near-Infrared (dNIR). The calculated BA by Sentinel-2 was larger during the three-year investigation span (16.55, 78.50, and 67.19 km2) and of greater detail (detected small areas) than the BA extracted by Landsat-8 (16.39, 6.24, and 32.93 km2). The routine for monitoring wildfires presented in this work is based on a sequence of decision rules. This enables the detection and monitoring of burnt vegetation cover and has been originally applied to an experiment in the northeastern Peruvian Amazon. The results obtained by the two satellites imagery are compared in terms of accuracy metrics and level of detail (size of BA patches). The accuracy for Landsat-8 and Sentinel-2 in 2017, 2018, and 2019 varied from 82.7–91.4% to 94.5–98.5%, respectively.

This document introduces the main concepts of Collaborative Engineering as a new methodology, procedures and tools to design and develop an aircraft, as Airbus Military is implementing. Airbus designs and industrializes aircrafts under Concurrent Engineering techniques since decades with success. The introduction of new PLM methodologies, procedures and tools, mainly in the industrialization areas, and the need to reduce time-to-market conducted Airbus Military to push the engineering teams to do things in a different way. Traditional Engineering works sequentially, Concurrent Engineering basically overlaps tasks between teams using maturity states and taking assuming risks. Collaborative Engineering promotes a single team to develop product, processes and resources from the conceptual phase to the start of the serial production. The deliverable of the team is an iDMU (industrial DMU), a complete definition and verification of the virtual manufacturing of the product.

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Abstract. The aim of this work was to study the short-term effects (first 9 months after the fire) of a low-severity spring boreal grassland fire on soil colour, soils organic matter (SOM) and soil water repellency (SWR) in Lithuania. Three days after the fire we designed a plot of 400 m2 in a control (unburned) and unburned area with the same geomorphological characteristics. Soil water repellency analysis were assessed through the 2 mm mesh (composite sample) and in the subsamples of all of the 250 samples divided into different soil aggregate fractions of 2–1, 1–0.5, 0.5–0.25 and < 0.25 mm, using the Water Drop Penetration Time (WDPT) method. The results showed that fire darkened the soil significantly during the entire study period due to the incorporation of ash/charcoal into the soil profile. Soil organic matter was significantly higher in the first two months after the fire in the burned plot, in comparison to the unburned plot. Soil water repellency (SWR) of the composite sample was higher in the burned plot during the first two months after the fire. However, considering the different aggregate fractions studied, the SWR was significantly higher until 5 months after the fire in the coarser fractions (2–1 mm, 1–0.5 mm) and 7 months after in the finer (0.5–0.25 mm and < 0.25 mm), suggesting that the leachability of organic compounds is different with respect to soil aggregate size fractions. This finding has implications for the spatio-temporal variability of fire effects on SWR. SOM was significantly negative correlated with SWR (composite sample) only in the two months after the fire. These results demonstrated that in the first two months the hydrophobic compounds produced by fire were one of the factors responsible for the increase in SWR. Subsequently repellent compounds were leached, at different rates, according to particle size. The impacts of this low severity grassland fire were limited in time, and are not considered a~threat to this ecosystem.

Agricultural productivity in the Peruvian region of Amazonas is being jeopardized by conflicts and inadequate land use, that are ultimately contributing to environmental degradation. Therefore, our aim is to assess land suitability for potato (Solanum tuberosum L.) farming in the Jucusbamba and Tincas microwatersheds located in Amazonas, in order to improve land-use planning and enhance the crop productivity of small-scale farmers. The site selection methodology involved a pair-wise comparison matrix (PCM) and a weighted multicriteria analysis using the Analytical Hierarchy Process (AHP) on selected biophysical and socioeconomical drivers. Simultaneously, land cover mapping was conducted using field samples, remote sensing (RS), geostatistics and geographic information systems (GIS). The results indicated that for potato crop farming, the most important criteria are climatological (30.14%), edaphological (29.16%), topographical (25.72%) and socioeconomical (14.98%) in nature. The final output map indicated that 8.2% (22.91 km2) was highly suitable, 68.5% (190.37 km2) was moderately suitable, 21.6% (60.11 km2) was marginally suitable and 0.0% was not suitable for potato farming. Built-up areas (archaeological sites, urban and road networks) and bodies of water were discarded from this study (4.64 km2). This study intends to promote and guide sustainable agriculture through agricultural land planning.