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Salinity stress represents a key factor for global agriculture. Plants can respond to salinity stress by adapting their physiology in different ways with the aim of limiting reductions in growth and development. Importantly, moisture retention capacity, permeability and nutrient availability of substrates represent critical variables for plants as they may further influence the effect of osmotic stress. Here, a multidisciplinary approach was applied to evaluate the role of two different substrates, peat and perlite, on 2-year-old potted cuttings of Olea europaea (cultivar Arbequina) under different salinity stress conditions (0, 100 and 200 mM NaCl). Biometric and physiological data indicate that plants potted in perlite (AP) generally present lower growth and photosynthetic rates when compared with peat (AS) in combination with salinity stress. Ion measurements indicate a rise in Na+ accumulation with increasing stress severity, which alters the ion ratio in both substrates. In addition, differences occurred in polyphenol contents, with a general increase in quinic acid and rutin contents in AS and AP samples, respectively. Metabolomic and biometric data were also coupled with metabarcoding analysis, which indicates that the moderate salinity treatment (100 mM NaCl, T100) reshaped the endophytic community of plants grown on both substrates. Taken together, the data suggest that the strategy used by a glycophytic species such as the olive tree to cope with salinity stress seems to be highly related to availability of water and nutrients. The lack of both may be simulated by perlite, enhancing the effect of salinity stress response in woody plants. Lastly, applying the beneficial endophytic bacterial taxa identified here could represent a step forward in increasing plant defence and nutrient uptake and reducing inputs for modern and more sustainable agriculture.

Despite a drought- and erosion-tolerant root system, olive trees are vulnerable to abiotic stress due to limited genetic variability. Though some olive cultivars are moderately tolerant to salinity stress, soil salinity is increasing in the semi-arid and arid regions where olive cultivation is common, significantly reducing overall production. In response, breeding programs may rely on proper selection markers for abiotic stresses, including salinity, but these are generally lacking for olive. Here, physiological and biochemical parameters were measured in four Olea europaea genotypes (Frantoio, Leccino, Lecciana, and Oliana) subjected to different intensities of salinity stress (0 mM, 100 mM and 200 mM NaCl). At moderate and high salt concentrations, Na+ exclusion, higher photosynthetic productivity and tissue water content in the tolerant cultivar Frantoio were linked with increased production of polyphenols, with more favorable K+/Na+ values (quercetin and rutin), mitigation of oxidative stress (oleuropein) and increased water absorption (luteolin). In Frantoio and Leccino, a significant change of the proteome repertoire occurred, with overrepresentation of components regulating cellular metabolism, ion transport, redox insult and dissipation of excess photochemical energy. Conversely, Lecciana and Oliana showed increased sensitivity to salinity stress in terms of photosynthetic parameters and elevated internal Na+ concentrations, together with the lowest number of differentially represented proteins. These results highlighted olive germplasm strategies to cope with osmotic stress, suggested a physiological and molecular basis for the augmented responsiveness of tolerant cultivars and identified specific biomarkers as useful targets for future breeding programs.

Olea europaea L. is a glycophyte representing one of the most important plants in the Mediterranean area, both from an economic and agricultural point of view. Its adaptability to different environmental conditions enables its cultivation in numerous agricultural scenarios, even on marginal areas, characterized by soils unsuitable for other crops. Salt stress represents one current major threats to crop production, including olive tree. In order to overcome this constraint, several cultivars have been evaluated over the years using biochemical and physiological methods to select the most suitable ones for cultivation in harsh environments. Thus the development of novel methodologies have provided useful tools for evaluating the adaptive capacity of cultivars, among which the evaluation of the plant-microbiota ratio, which is important for the maintenance of plant homeostasis. In the present study, four olive tree cultivars (two traditional and two for intensive cultivation) were subjected to saline stress using two concentrations of salt, 100 mM and 200 mM. The effects of stress on diverse cultivars were assessed by using biochemical analyses (i.e., proline, carotenoid and chlorophyll content), showing a cultivar-dependent response. Additionally, the olive tree response to stress was correlated with the leaf endophytic bacterial community. Results of the metabarcoding analyses showed a significant shift in the resident microbiome for plants subjected to moderate salt stress, which did not occur under extreme salt-stress conditions. In the whole, these results showed that the integration of stress markers and endophytic community represents a suitable approach to evaluate the adaptation of cultivars to environmental stresses.

Revista oficial de la Asociación Española de Teledetección, [EN] Natural fire regimes have been modified; therefore robust post-fire monitoring tools are needed to understand the post-fire recovery process. Satellites with high temporal resolution allow us to build time series of vegetation indices for monitoring post-fire vegetation recovery. One of the techniques used is to compare the time series of a burned plot with that of an unburned control plot. However, for its implementation it is necessary to select control plots in which the vegetation has the same structure and functioning than the plot burned before the fire. Previous study defined biological criteria to detect burned and unburned control plots with identical pre-fire vegetation functioning. Moreover, a non-parametric test routine of low statistical power was proposed to test them, this was based on the analysis of the QVI (Quotient Vegetation Index), calculated between NDVI (Normalized Difference Vegetation Index) time series of the burned and control site. However, currently there are autoregressive analysis techniques with greater statistical power. Therefore the aims were to propose six new statistical routines based on autoregressive test, and compare the performance of these with the non-parametric routine. We selected 13,700 forest plots and extracted the NDVI MODIS time series between 2002 and 2005. We randomly selected 43 reference plots, and through each routine, we compared each reference time series with the other 13,657 time series. We estimated the performance of the routines measuring the euclidian distance between the time series of the reference plot and the time series of the plots accepted for each routine. We also measured the quality and the amount of the QVI time series selected by each routine. Autoregressive routines showed better performance than the non-parametric routine, since they selected control plots with NDVI time series with greatest similarity with respect to the reference plots and QVI series with highest quality., [ES] Los regímenes naturales de incendios han sufrido modificaciones; consecuentemente, es indispensable disponer de herramientas robustas para el seguimiento post-fuego de la vegetación. Los satélites de alta resolución temporal permiten construir series temporales de índices de vegetación para monitorear la recuperación post-fuego. Una de las técnicas utilizadas consiste en comparar la serie temporal de una parcela quemada con la de una parcela control no quemada. Sin embargo, para su implementación es necesario seleccionar parcelas control que antes del incendio tengan una vegetación con igual estructura y funcionamiento que la parcela quemada. Un estudio previo definió criterios biológicos para localizar parcelas quemadas y control con idéntico funcionamiento pre-incendio. Para testearlos se propuso una rutina de test no paramétricos de baja potencia estadística, analizando el cociente QVI (Quotient Vegetation Index) de las series temporales de NDVI (Normalized Difference Vegetation Index) de parcelas control y quemadas. Sin embargo, actualmente existen técnicas de análisis autorregresivas con mayor potencia estadística. Los objetivos del presente trabajo fueron proponer seis nuevas rutinas basadas en test autorregresivos y comparar el desempeño de éstas contra la rutina no paramétrica. Seleccionamos 13.700 parcelas de bosque y extrajimos las series temporales NDVI MODIS entre 2002 y 2005. Aleatoriamente seleccionamos 43 parcelas de referencia. A través de las rutinas planteadas comparamos la serie temporal de referencia con cada una de las 13.657 series restantes. Estimamos el desempeño midiendo la distancia euclidiana entre la serie de temporal de la parcela de referencia y las series temporales de las parcelas aceptadas por cada rutina. También, medimos la calidad y contabilizamos la cantidad de las series temporales QVI seleccionadas por cada rutina. Las rutinas autorregresivas tuvieron mejor desempeño, ya que seleccionaron parcelas control con series tempor