BUSCADOR RECOLECTA

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. © 2022 by the authors., This research was funded by Interreg Sudoe Programme, European Regional Development Fund, European-Union, grant number SOE2/P5/E0804; by MICINN through European Regional Development Fund (SUMHAL, LIFEWATCH-2019-09-CSIC-13, POPE 2014-2020); and by Ministry of Science and Innovation (MCIN/AEI/10.13039/501100011033) grant number PID2020-116786RB-C32.

Soils store an important amount of carbon (C), mostly in the form of organic matter in different decomposing stages. Hence, understanding the factors that rule the rates at which decomposed organic matter is incorporated into the soil is paramount to better understand how C stocks will vary under changing atmospheric and land use conditions. We studied the interactions between vegetation cover, climate and soil factors using the Tea Bag Index in 16 different ecosystems (eight forests, eight grasslands) along two contrasting gradients in the Spanish province of Navarre (SW Europe). Such arrangement encompassed a range of four climate types, elevations from 80 to 1420 m.a.s.l., and precipitation (P) from 427 to 1881 mm year–1. After incubating tea bags during the spring of 2017, we identified strong interactions between vegetation cover type, soil C/N and precipitation affecting decomposition rates and stabilization factors. In both forests and grasslands, increasing precipitation increased decomposition rates (k) but also the litter stabilization factor (S). In forests, however, increasing the soil C/N ratio raised decomposition rates and the litter stabilization factor, while in grasslands higher C/N ratios caused the opposite effects. In addition, soil pH and N also affected decomposition rates positively, but for these factors no differences between ecosystem types were found. Our results demonstrate that soil C flows are altered by complex site-dependent and site-independent environmental factors, and that increased ecosystem lignification will significantly change C flows, likely increasing decomposition rates in the short term but also increasing the inhibiting factors that stabilize labile litter compounds., This work was supported by the Public University of Navarre; the
Spanish Ministry of Science [grant numbers AGL2016-76035-C2,
PID2020-116786RB-C32] and the Spanish Ministry of Economy and Competitiveness [grant BES-2017-080326]. Open access funding provided by
the Public University of Navarre.