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Montado is a characteristic ecosystem of the Mediterranean region. The adequate management of this silvo-pastoral ecosystem requires good understanding of the effect of factors such as tree canopy, fertilization and soil amendment on pasture growth. The main objectives of this work were: (1) to evaluate the effect of tree canopy on soil characteristics and pasture productivity and quality; and (2) to test floristic composition assessment as a bio-indicator of soil improvements (amendment and fertilization) in each study area (under and outside tree canopy). Topsoil was characterized at the beginning of the project (October 2015) and at the end of the experiments (spring 2020). Soil parameters obtained by electronic sensors (soil moisture content, soil cone index and surface temperature) were monitored monthly during the 2017/2018 pasture vegetative cycle. Pasture productivity, quality and floristic composition were evaluated every two years (2016, 2018 and 2020) in the spring flowering period. The results of the floristic inventory were submitted to a multilevel pattern analysis (Indicator Species Analysis, ISA). Pasture biodiversity was evaluated based on the calculation of richness indices. This study showed a positive effect of tree canopy on soil fertility and pasture quality (e.g., CP). Pasture productivity, on the other hand, was higher in areas outside tree canopy. The great potential of ISA as a tool for identification of bio-indicator species was also demonstrated. Pasture species were identified as ecological and dynamic attributes characteristic of each study area, before and after soil amendment and fertilization.

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The evaluation of general suitability for viticulture in wine regions requires a knowledge of the spatial variation in temperature, which is also used to assess different grapevine cultivars and to delimit appropriate zones for winegrape production. However, usually temperature data and methods applied to properly delineate homogeneous areas are not adequate to generate accurate maps.With the aim of providing an analysis using four temperature-based indices, quantifying their spatial variability, and representing the spatial pattern of each index throughout Extremadura, one of the most important Spanish wine regions, temperature data from 117 meteorological stations, considering the 1980–2011 period, were utilized. The statistical properties of each index were assessed and, later, they were mapped by means of an integrated geographic information system (GIS) and a multivariate geostatistics (regression-kriging) approach. Results show that heat-sum temperature indices were highly related to the more simple growing season temperature; however, temperature regime differences varied upon which index was employed. The spatial variability of climate within Extremaduran natural regions (NR) is significant; although the warmer conditions predominate, some NR have part of their territory by up to eight climate classes. This information enables a better understanding of the viticulture suitability within each NR and delineating homogeneous zones. The use of consistent bioclimatic indices and an advanced geostatistical algorithm have made it possible to delimit and compare within-region climates and also enabled comparisons of Extremaduran NR with others worlwide, which should be taken into account to select varieties and assess the possibilities of producing new wines.