Microorganisms form dynamic communities with plants, providing benefits such as nutrient acquisition and stress resilience. Understanding how these microorganisms are affected by environmental factors such as growth conditions and soil characteristics are essential for harnessing these communities for sustainable agriculture practices and their response to climate change. The microbiome associated to Lupinus angustifolius, a legume native in Europe, with a high protein value and stress resilience was characterized for the first time. Using 16S rRNA gene and ITS amplicon sequencing, we characterized the compositional and temporal changes of the bacterial and fungal communities associated to the soil, rhizosphere, and plant compartments where Lupinus angustifolius grows naturally. Our results suggest that the main difference in the soil microbial communities is related to the edaphic properties, although environmental factors such as temperature, humidity or rainfall also influenced the composition of the soil microbial communities. We also characterized the bacterial communities associated with the rhizosphere, roots, nodules, and leaves of wild plants collected in the field and compared them against plants obtained under greenhouse conditions. In the plant compartments, the bacterial composition appeared to be more affected by the growing conditions (field vs greenhouse), than by soil characteristics or location. These results can be used to identify key taxa that may play crucial roles in the development and adaptation of the host plant and its associated microbiota to environmental changes and highlight the importance of characterizing the plant microbiomes in their natural habitats. Soil, influenced by climatic seasons, shapes the plant microbiome assembly. Lupinus recruits a core microbiome across rhizosphere, roots, nodules, and leaves, that is stable across locations. However, cultivation conditions may alter microbiome dynamics, impacting the adaptability of its components. Wild plants show a resilient and adaptable microbiome while germination and cultivation in greenhouse conditions alter its composition and vulnerability.

The expansion of cities towards flood zones, and the increasingly frequent episodes of torrential rains arising from global warming, mean that the population is becoming more exposed to floods. Due to this, a correct assessment of flood events is of great help in the development of preventive actions, planning and resource management, or interventions. For this reason, in this work we aim to establish guidelines to assess the hazard, exposure, and vulnerability of the population and its properties to flood events, using Hec-Ras for the simulation of the flood and ArcGis and GeoHecRas to treat geographic information and prepare the cartography. The study was focused on the Tormes River in Salamanca (Spain). We studied three return periods with different probabilities of occurrence and intensity, corresponding to 5, 100, and 500 years. The flow corresponding to each episode was calculated, along with the extension, speed, and depth that would be achieved in each case. Then, the probability of occurrence was delimited, as well as the magnitude, allowing us to obtain different hazard maps. In addition, the areas of greatest hazard to people and property were established for each event. Regarding the exposure, the areas and land use, infrastructure, and buildings that would be flooded in each case were identified, quantifying the extension or length of the affected properties at the different levels of hazard in each case. Additionally, the vulnerability of the different buildings and exposed infrastructure was studied. Finally, the flood risk was estimated by combining these three components.

This study has established a methodology to determine the most environmentally suitable area for the expansion of Zamora (Spain) using geographic information system (GIS) technology. The objective was to develop a GIS-based methodology for the identification of urban peripheral areas that are suitable for the accommodation of new buildings and services, that are compliant with environmental criteria, and that guarantee an adequate quality of life for the future population such that extra construction costs are avoided. The methodological core is based on two multi-criteria analyses (MCAs): MCA-1 determines areas suitable for building—the most environmentally sustainable areas that do not present risks or discomforts to the population—by analyzing the restrictive factors; MCA-2 takes the sectors that received a favorable evaluation in MCA-1, determines which of those have a lower economic overhead for construction, and analyzes the different conditioning criteria related to their pre-existing infrastructures. Finally, the location of the sectors is determined by a decision factor that satisfies some strategic need of the municipality.

Traditional knowledge about the behavior of grazing livestock is about to disappear. Shepherds well know that sheep behavior follows non-random patterns. As a novel alternative to seeking behavioral patterns, this study quantified the grazing activities of two sheep flocks of Churra breed (both in the same area but separated by 10 years) based on Global Position System (GPS) monitoring and remote monitoring sensing techniques. In the first monitoring period (2009-10), geolocations were recorded every 5 min (4,240 records), while in the second one (2018-20), records were taken every 30 min (7,636 records). The data were clustered based on the day/night and the activity (resting, moving, or grazing). An airborne LiDAR dataset was used to study the slope, aspect, and vegetation height. Four visible-infrared orthophotographs were mosaicked and classified to obtain the land use/land cover (LU/LC) map. Then, GPS locations were overlain on the terrain features, and a Chi-square test evaluated the relationships between locations and terrain features. Three spatial statistics (directional distribution, Kernel density, and Hot Spot analysis) were also calculated. Results in both monitoring periods suggested that the spatial distribution of free-grazing ewes was non-random. The flocks showed strong preferences for grazing areas with gentle north-facing slopes, where the herbaceous layer formed by pasture predominates. The geostatistical analyses of the sheep locations corroborated those preferences. Geotechnologies have emerged as a potent tool to demonstrate the influence of environmental and terrain attributes on the non-random spatial behavior of grazing sheep.

The lack of urban sustainability is a widespread deficiency in urban agglomerations. To achieve adequate land use, we present a methodology that allows for: 1) the identification of the impacts caused by urban expansion since 1956 to the present in Salamanca (Spain); and 2) the promotion of a more sustainable future in urban development. A multi-temporal assessment of land use was made by remote sensing, while sustainability criteria were analyzed using the multicriteria analysis (MCA) with Geographical Information Systems (GIS). In addition, we established recommendations for soil carbon management in semi-arid ecosystem soils that contribute to climate change mitigation. The results show an increase of the urbanized area from 3.8% to 22.3% in the studied period, identifying up to 15% of buildings in zones with some type of restriction. In 71% of the cases, urbanization caused the sealing of productive agricultural soils (2519 Ha), almost 20% of which were of the highest quality. In last few decades, an excessive increase of built-up areas in comparison to population dynamics was identified, which causes unnecessary soil sealing that affects the food production and the capacity to mitigate climate change by managing the carbon cycle in the soil.