Abstract:Invasion by alien plant species may be rapid and aggressive, causing erosion of local biodiversity. This is particularly true for islands, where natural and anthropogenic corridors promote the rapid spread of invasive plants. Although evidence shows that corridors may facilitate plant invasions, the question of how their importance in the spread of alien species varies along environmental gradients deserves more attention. Here, we addressed this issue by examining diversity patterns (species richness of endemic, native and alien species) along and across roads, along an elevation gradient from sea-level up to 2050 m a.s.l. in Tenerife (Canary Islands, Spain), at multiple spatial scales. Species richness was assessed using a multi-scale sampling design consisting of 59 T-transects of 150 m × 2 m, along three major roads each placed over the whole elevation gradient. Each transect was composed of three sections of five plots each: Section 1 was located on the road edges, Section 2 at intermediate distance, and Section 3 far from the road edge, the latter representing the "native community" less affected by road-specific disturbance. The effect of elevation and distance from roadsides was evaluated for the three groups of species (endemic, native and alien species), using parametric and non-parametric regression analyses as well as additive diversity partitioning. Differences among roads explained the majority of the variation in alien species richness and composition. Patterns in alien species richness were also affected by elevation, with a decline in richness with increasing elevation and no alien species recorded at high elevations. Elevation was the most important factor determining patterns in endemic and native species. These findings confirm that climate filtering reflected in varying patterns along elevational gradients is an important determinant of the richness of alien species (which are not adapted to high elevations), while anthropogenic pressures may explain the richness of alien species at low elevation.

Increased frequency of tree mortality and forest decline due to anomalous drought events calls for the adoption of effective monitoring of tree water status over large spatial and temporal scales. We correlated field-measured and remotely sensed plant water status parameters, to test the possibility of monitoring the risk of drought-induced dehydration and hydraulic failure using satellite images calibrated on reliable physiological indicators of tree hydraulics. The study was conducted during summer 2019 in the Karst plateau (NE Italy) in a woodland dominated by Fraxinus ornus L.; Sentinel-2 images were acquired on a seasonal scale on the same dates when absolute water content (AbWC), relative water content (RWC), and minimum water potential (Ψmin) were measured in the field. Plant water status parameters were correlated with normalized difference vegetation index (NDVI and NDVI 8A), normalized difference water index (NDWI), and soil-adjusted vegetation index (SAVI). Significant Pearson and Spearman linear correlations (α < 0.05) emerged between all tree-level measured variables and NDWI, while for NDVI, NDVI 8A, and SAVI no correlation was found. Our results suggest the possibility of using the NDWI as a proxy of tree water content and water potential.

This study was carried out using Ixodes ricinus ticks collected during 2005 and 2006 from the Friuli Venezia Giulia (FVG) region in the northeastern part of Italy and an area along the Slovenian side of the western border of Italy. The results indicate that Rickettsia spp. is widely distributed throughout these areas, with the greatest prevalence in the central part of the FVG region. The prevalence of Rickettsia spp. was 4.5% during 2005 and 6.1% during 2006. By sequencing the 16S rRNA gene, we show for the first time the presence of Rickettsia helvetica in I. ricinus ticks in the FVG region and the presence of R. monacensis in ticks in both areas. Furthermore, we detected a sequence with a high homology with that of R. limoniae in a tick obtained from the alpine zone.

Drought-induced tree mortality frequently occurs in patches with different spatial and temporal distributions, which is only partly explained by inter-and intraspecific variation in drought tolerance. We investigated whether bedrock properties, with special reference to rock water storage capacity, affects tree water status and drought response in a rock-dominated landscape. We measured primary porosity and available water content of breccia (B) and dolostone (D) rocks. Saplings of Fraxinus ornus were grown in pots filled with soil or soil mixed with B and D rocks, and subjected to an experimental drought. Finally, we measured seasonal changes in water status of trees in field sites overlying B or D bedrock. B rocks were more porous and stored more available water than D rocks. Potted saplings grown with D rocks had less biomass and suffered more severe water stress than those with B rocks. Trees in sites with B bedrock had more favourable water status than those on D bedrock which also suffered drought-induced canopy dieback. Bedrock represents an important water source for plants under drought. Different bedrock features translate into contrasting below-ground water availability, leading to landscape-level heterogeneity of the impact of drought on tree water status and dieback.

Recently, methods for constructing Spatially Explicit Rarefaction (SER) curves have been introduced in the scientific literature to describe the relation between the recorded species richness and sampling effort and taking into account for the spatial autocorrelation in the data. Despite these methodological advances, the use of SERs has not become routine and ecologists continue to use rarefaction methods that are not spatially explicit. Using two study cases from Italian vegetation surveys, we demonstrate that classic rarefaction methods that do not account for spatial structure can produce inaccurate results. Furthermore, our goal in this paper is to demonstrate how SERs can overcome the problem of spatial autocorrelation in the analysis of plant or animal communities. Our analyses demonstrate that using a spatially-explicit method for constructing rarefaction curves can substantially alter estimates of relative species richness. For both analyzed data sets, we found that the rank ordering of standardized species richness estimates was reversed between the two methods. We strongly advise the use of Spatially Explicit Rarefaction methods when analyzing biodiversity: the inclusion of spatial autocorrelation into rarefaction analyses can substantially alter conclusions and change the way we might prioritize or manage nature reserves