Mountains are strongly seasonal habitats, which require special adaptations in wildlife species living on them. Population dynamics of mountain ungulates are largely determined by the availability of rich food resources to sustain lactation and weaning during summer. Increases of temperature affect plant phenology and nutritional quality. Cold-adapted plants occurring at lower elevations will shift to higher ones, if available. We predicted what could happen to populations of mountain ungulates based on how climate change could alter the distribution pattern and quality of high-elevation vegetation, using the “clover community-Apennine chamoisRupicapra pyrenaica ornata” system. From 1970 to 2014, increasing spring temperatures (2 °C) in our study area led to an earlier (25 days) onset of green-up in Alpine grasslands between 1700 and 2000 m, but not higher up. For 1970–2070, we have projected trends of juvenile winter survival of chamois, by simulating trajectories of spring temperatures and occurrence of clover, through models depicting four different scenarios. All scenarios have suggested a decline of Apennine chamois in its historical core range, during the next 50 years, from about 28% to near-extinction at about 95%. The negative consequences of climate changes presently occurring at lower elevations will shift to higher ones in the future. Their effects will vary with the species-specific ecological and behavioural flexibility of mountain ungulates, as well as with availability of climate refugia. However, global shifts in distributional ranges and local decreases or extinctions should be expected, calling for farsighted measures of adaptive management of mountain-dwelling herbivores.

In this work, essential oils (EOs) and hydrolates (Hys) of Rosmarinus officinalis L. and Lavandula angustifolia Mill., grown in Tuscany (Italy), were studied to describe their chemical composition and biological activities. The aromatic profile of the EOs liquid phase was carried out by gas chromatography–mass spectrometry (GC–MS), while the volatile composition of vapor phase EOs and Hys was performed by headspace (HS)/GC–MS. The obtained results show that monoterpene hydrocarbons (71.5% and 89.5%) were the main compounds, followed by oxygenated monoterpenes (26.0% and 10.5%) in the liquid and vapor phase of R. officinalis EO, respectively. The oxygenated monoterpenes were the main components of L. angustifolia EO, reaching 86.9% in the liquid phase and 53.7% in the vapor phase. Regarding Hys, they consisted only of oxygenated monoterpenes, and 1,8-cineole (56.2%) and linalool (42.9%), were the main components of R. officinalis and L. officinalis Hys, respectively. Their cytotoxicity was investigated on an SHSY5Y neuroblastoma cell line by thiazolyl blue tetrazolium bromide (MTT) test, showing a notable effect of the EOs with a time-independent manner of activity and half maximal effective concentration (EC₅₀) values quite similar for the two plant species (from 0.05% to 0.06% v/v for the three time points evaluated). A measurable activity of Hys was also obtained although with higher EC₅₀ values. The antibacterial activity against Escherichia coli ATCC^® 25922, Pseudomonas fluorescens ATCC^® 13525, Acinetobacter bohemicus DSM 102855 as Gram-negative bacteria and Kocuria marina DSM 16420, Bacillus cereus ATCC^® 10876 as Gram-positive bacteria, was evaluated by the agar disk-diffusion method and the VPT (vapor phase test) to determinate the MIC (minimal inhibitory concentration) and the MBC (minimal bactericidal concentration) values. Both EOs possessed a high activity against all the bacterial strains with MIC values ranging from 0.19% to 3.13% v/v. Unlike EOs, Hys did not show an inhibition of the bacterial growth at the tested concentrations. Furthermore, antioxidant power was measured by 2,2′-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt-based (ABTS•+) and the 2,2-diphenyl-1-picrylhydrazyl (DPPH) assays, showing a remarkable ability to reduce radicals by both EOs; Hys were slightly less active. The findings highlighted that R. officinalis and L. angustifolia EOs and Hys have a chemical composition rich in bioactive molecules, which can exert different biological activities.

Forest compartments are usually delineated according to artificial or natural boundaries and usually include portions of different strata. While volume estimation of each stratum can be performed from field plots located within each stratum, volume estimation in portions of the stratum may be problematic owing to the small number (or even the absence) of plots falling in those portions. If upper canopy heights from airborne laser scanning are available at the pixel level for the whole survey area, these data are used as auxiliary information. A ratio model presuming a proportional relationship between transformed heights (e.g., power of heights) and volumes at the pixel level is adopted to guide estimation. From this model, the volume within any portion of the survey area is estimated as the proportionality factor estimate multiplied by the total of transformed heights in that portion. This estimator is considered from the model-based, design-based, and hybrid perspectives. Variances and their estimators are derived under the three approaches together with the corresponding confidence intervals. The volume estimator and the variance estimators are checked from the design-based point of view by a simulation study performed on a real forest in northwestern Italy. An application to a public forest estate in the same zone is performed.

The estimation of the total of an attribute defined over a continuous planar domain is required in many applied settings, such as the estimation of canopy coverage in the Monterano Nature Reserve in Italy. If the design-based approach is considered, the scheme for the placement of the sample sites over the domain is fundamental in order to implement the survey. In real situations, a commonly adopted scheme is based on partitioning the domain into suitable strata, in such a way that a single sample site is uniformly placed (i.e., selected with uniform probability density) in each stratum and sample sites are independently located. Under mild conditions on the function representing the target attribute, it is shown that this scheme gives rise to an unbiased spatial total estimator which is “superefficient” with respect to the estimator based on the uniform placement of independent sample sites over the domain. In addition, the large-sample normality of the estimator is proven and variance estimation issues are discussed.