There is an increasing body of studies that show that land use intensification and homogenisation in agriculture landscapes, aimed at increasing food provisioning, decline other ecosystem services. Agroecological management has been proposed as an alternative to conventional agricultural management because of its presumed capacity to rehabilitate degraded ecosystem services. In this study we tested whether the agroecological principles of minimum mechanical soil disturbance, maintaining understory cover and application of organic amendments can improve the provisioning of ecosystem services and whether bundles of ecosystem services emerged. We experimentally implemented no-tillage (NT), green manure (GM), compost (CM) and conventional tillage (CT) as a control in five almond orchards in south-eastern Spain and monitored nutrient cycling, carbon stock, habitat provisioning, food provisioning, pest control and pollination after one year. We found that CM and NT had a higher overall ecosystem service performance than CT, and that GM did not differ from CT. The treatments significantly improved ecosystem services such as nutrient cycling, carbon stock, habitat provisioning and food provisioning, but not pest control and pollination. CM treatment resulted in higher soil enzyme activity (glucosidase and phosphatase), soil nutrient content (total N and extractable K), leaf nutrient content (P and K concentrations), soil organic carbon (SOC) content and almond kernel weight compared to other treatments. GM treatment resulted in higher phosphatase activity, understory carbon content and more understory cover than CT. NT treatment resulted in higher glucosidase, phosphatase and urease activity, understory plant diversity and more understory cover than CT. We also found an emerging bundle between SOC and soil enzyme activity and between individual almond weight and soil nutrient levels and SOC. This study shows that ecosystem services can rehabilitate rather quickly, given the one-year time frame of the study. Further, each agroecological practice may enhance a specific set of ecosystem services.

This study evaluates the potential for pasture improvement and restoration at two silvopastoral sites. We used a total of 16 wild legume species under different management systems (rhizobial inoculation, mycorrhizal inoculation, sheep penning, and sheep penning with mycorrhizal inoculation), at two mountain sites in Sierra Nevada Natural Park (Granada, southern Spain). The first site, Soportújar, had higher soil fertility and rainfall than the second, Lanjarón. Forage yields in Soportújar ranged from 265 to 8970 kg DM ha-1 , Vicia amphicarpa, Vicia monantha, Vicia disperma and Lathyrus clymenum being the most productive species. Mycorrhizal inoculation resulted in higher forage yields for Lens nigricans, V. disperma and Vicia lutea. Seed yields were low, ranging from 5.9 to 1234 kg ha-1. Forage yields in Lanjarón were lower, ranging from 46 to 1415 kg DM ha-1 ; and the most productive species were V. monantha, V. disperma, Lathyrus cicera and Medicago rigidula. Sheep penning alone and together with mycorrhizal treatment resulted in greater forage yields for most of the species studied, although differences were only significant for V. disperma, V. monantha and L. sphaericus. Seed yields ranged from 0.4 to 60 kg ha-1. In conclusion, we recommend V. Post-print: Agroforestry Systems (2019) 1-13 monantha, V. disperma and L. cicera followed by V. amphicarpa and L. clymenum (in wetter more fertile sites) and M. rigidula (in drier sites), as they seem to be the best adapted to the pedoclimatic conditions of Sierra Nevada Natural Park. Increasing nutrients in the soil (by sheep penning) and promoting nutrient assimilation (by mycorrhizal inoculation) may be effective strategies for increasing pasture biomass in silvopastoral sites.

(1) Background: Maintaining soil fertility and crop productivity using natural microbial diversity could be a feasible approach for achieving sustainable development in agriculture. In this study, we compared soils from vineyards under organic and conventional management by predicting functional profiles through metagenomic analysis based on the 16S rRNA gene. (2) Methods: The structure, diversity and predictive functions of soil bacteria related to the biogeochemical cycle of the soil were analyzed, including oxidative and hydrolytic C-cycling enzymes, N-cycling enzymes and P-cycling enzymes. The inter-row spontaneous vegetation in the organic vineyards was also characterized. (3) Results: A clear effect of the farming system (organic vs. conventional) and cover management (herbicides plus tillage, mowing only and mowing plus tillage) on bacterial beta diversity and predicted functions was evidenced. While conventional viticulture increased the potential capacity of the soil to regulate the cycling of inorganic forms of N, organic viticulture in general enhanced those functions involving organic N, P and C substrates. Although the soil bacterial community responded differently to contrasting soil management strategies, nutrient cycling and carbon sequestration functions remained preserved, suggesting a high bacterial functional redundancy in the soil in any case. However, most of the predicted bacterial functions related to soil organic matter turnover were enhanced by organic management. (4) Conclusions: We posit the potential for organic viticulture to adequately address climate change adaptation in the context of sustainable agriculture.

The use of drones for vegetation monitoring allows the acquisition of large amounts of high spatial resolution data in a simple and fast way. In this study, we evaluated the accuracy of vegetation cover estimation by drones in Mediterranean semi-arid shrublands (Sierra de Filabres; Almería; southern Spain) after prescribed burns (2 years). We compared drone-based vegetation cover estimates with those based on traditional vegetation sampling in ninety-six 1 m2 plots. We explored how this accuracy varies in different types of coverage (low-, moderate- and high-cover shrublands, and high-cover alfa grass steppe); as well as with diversity, plant richness, and topographic slope. The coverage estimated using a drone was strongly correlated with that obtained by vegetation sampling (R2 = 0.81). This estimate varied between cover classes, with the error rate being higher in low-cover shrublands, and lower in high-cover alfa grass steppe (normalized RMSE 33% vs. 9%). Diversity and slope did not affect the accuracy of the cover estimates, while errors were larger in plots with greater richness. These results suggest that in semi-arid environments, the drone might underestimate vegetation cover in low-cover shrublands.