Impacts of past and future land changes on landslides in southern Italy

Regional Environmental Change - Land use and land cover (LULC), as well as their geographical and temporal variations, affect landslide occurrence and the related risk, in ways that are difficult...     

Environmental Security: A Geographic Information System Analysis Approach—The Case of Kenya

Studies into the relationships between environmental factors and violence or conflicts constitute a very debated research field called environmental security. Several authors think that environmental scarcity, which is scarcity of renewable resources, can contribute to generate violence or social unrest, particularly within states scarcely endowed with technical know-how and social structures, such as developing countries. In this work, we referred to the theoretical model developed by the Environmental Change and Acute Conflict Project. Our goal was to use easily available spatial databases to map the various sources of environmental scarcity through geographic information systems, in order to locate the areas apparently most at risk of suffering negative social effects and their consequences in terms of internal security. The analysis was carried out at a subnational level and applied to the case of Kenya. A first phase of the work included a careful selection of databases relative to renewable resources. Spatial operations among these data allowed us to obtain new information on the availability of renewable resources (cropland, forests, water), on the present and foreseen demographic pressure, as well as on the social and technical ingenuity. The results made it possible to identify areas suffering from scarcity of one or more renewable resources, indicating different levels of gravity. Accounts from Kenya seem to confirm our results, reporting clashes between tribal groups over the access to scarce resources in areas that our work showed to be at high risk.     

Behavioural evidence for the involvement of Dufour’s gland secretion in nestmate recognition in the social wasp Polistes dominulus (Hymenoptera: Vespidae)

The results of recent studies by our group have suggested that in social wasps of the genus Polistes the Dufour’s gland is involved in kin recognition. In fact, the same hydrocarbons occurring on the cuticle are found in the gland secretion, and in P. dominulus the composition of the glandular secretion is more similar in foundresses belonging to the same colonies than in heterocolonial foundresses. In this study, P. dominulus colonies were experimentally presented with previously treated dead conspecific females. These lures had been deprived of their epicuticular lipids and coated with epicuticular or Dufour’s gland secretion extracts from females hetero- or homocolonial with respect to the tested colonies. The behaviour of the colonies towards these lures indicates that, like the epicuticular lipids, the Dufour’s gland secretion is involved in nestmate recognition. Received: 14 August 1995/Accepted after revision: 5 November 1995     

Modeling the vegetation-atmosphere carbon dioxide and water vapor interactions along a controlled CO2 gradient

Ecosystem functioning is intimately linked to its physical environment by complex two-way interactions. These two-way interactions arise because vegetation both responds to the external environment and actively regulates its micro-environment. By altering stomatal aperture, and therefore the transpiration rate, plants modify soil moisture and atmospheric humidity and these same physical variables, in return, modify stomatal conductance. Relationships between biotic and abiotic components are particularly strong in closed, managed environments such as greenhouses and growth chambers, which are used extensively to investigate ecosystem responses to climatic drivers. Model-assisted designs that account for the physiological dynamics governing two-way interactions between biotic and abiotic components are absent from many ecological studies. Here, a general model of the vegetation-atmosphere system in closed environments is proposed. The model accounts for the linked carbon-water physiology, the turbulent transport processes, and the energy and radiative transfer within the vegetation. Leaf gas exchange is modeled using a carbon gain optimization approach that is coupled to leaf energy balance. The turbulent transport within the canopy is modeled in two-dimensions using first-order closure principles. The model is applied to the Lysimeter CO₂ Gradient (LYCOG) facility, wherein a continuous gradient of atmospheric CO₂ is maintained on grassland assemblages using an elongated chamber where the micro-climate is regulated by variation in air flow rates. The model is employed to investigate how species composition, climatic conditions, and the imposed air flow rate affect the CO₂ concentration gradient within the LYCOG and the canopy micro-climate. The sensitivity of the model to key physiological and climatic parameters allows it to be used not only to manage current experiments, but also to formulate novel ecological hypotheses (e.g., by modeling climatic regimes not currently employed in LYCOG) and suggest alternative experimental designs and operational strategies for such facilities.     

Application of smart irrigation systems for water conservation in Italian farms

Environmental Science and Pollution Research - In many countries, water supplies are limited and must be managed for different uses. Providing additional resources for irrigation can be an...     

Responses of soil microbial communities to water stress: results from a meta-analysis

Soil heterotrophic respiration and nutrient mineralization are strongly affected by environmental conditions, in particular by moisture fluctuations triggered by rainfall events. When soil moisture decreases, so does decomposers' activity, with microfauna generally undergoing stress sooner than bacteria and fungi. Despite differences in the responses of individual decomposer groups to moisture availability (e.g., bacteria are typically more sensitive than fungi to water stress), we show that responses of decomposers at the community level are different in soils and surface litter, but similar across biomes and climates. This results in a nearly constant soil-moisture threshold corresponding to the point when biological activity ceases, at a water potential of about -14 MPa in mineral soils and -36 MPa in surface litter. This threshold is shown to be comparable to the soil moisture value where solute diffusion becomes strongly inhibited in soil, while in litter it is dehydration rather than diffusion that likely limits biological activity around the stress point. Because of these intrinsic constraints and lack of adaptation to different hydro-climatic regimes, changes in rainfall patterns (primary drivers of the soil moisture balance) may have dramatic impacts on soil carbon and nutrient cycling.     

A correlation study between multiple sclerosis and type 1 diabetes incidences and geochemical data in Europe

Complex multifactorial disorders usually arise in individuals genetically at risk in the presence of permissive environmental factors. For many of these diseases, predisposing gene variants are partly known while the identification of the environmental component is much more difficult. This study aims to investigate whether there are correlations between the incidence of two complex traits, multiple sclerosis and type 1 diabetes, and some chemical elements and compounds present in soils and stream sediments in Europe. Data were obtained from the published literature and analyzed by calculating the mean values of each element and of disease incidence for each Country, respectively, 17 for multiple sclerosis and 21 for type 1 diabetes. Correlation matrices and regression analyses were used in order to compare incidence data and geochemical data. R correlation index and significance were evaluated. The analyses performed in this study have revealed significant positive correlations between barium and sodium oxide on one hand and multiple sclerosis and diabetes incidences on the other hand that may suggest interactions to be evaluated between silicon-rich lithologies and/or marine environments. The negative correlations shown by cobalt, chromium and nickel (typical of silicon-poor environment), which in this case can be interpreted as protective effects against the two diseases onset, make the split between favorable and protective environments even more obvious. In conclusion, if other studies will confirm the involvement of the above elements and compounds in the etiology of these pathologies, then it will be possible to plan strategies to reduce the spread of these serious pandemics.     

Adaptive cluster sampling with clusters selected without replacement and stopping rule

Adaptive cluster sampling (ACS) has received much attention in recent years since it yields more precise estimates than conventional sampling designs when applied to rare and clustered populations. These results, however, are impacted by the availability of some prior knowledge about the spatial distribution and the absolute abundance of the population under study. This prior information helps the researcher to select a suitable critical value that triggers the adaptive search, the neighborhood definition and the initial sample size. A bad setting of the ACS design would worsen the performance of the adaptive estimators. In particular, one of the greatest weaknesses in ACS is the inability to control the final sampling effort if, for example, the critical value is set too low. To overcome this drawback one can introduce ACS with clusters selected without replacement where one can fix in advance the number of distinct clusters to be selected or ACS with a stopping rule which stops the adaptive sampling when a predetermined sample size limit is reached or when a given stopping rule is verified. However, the stopping rule breaks down the theoretical basis for the unbiasedness of the ACS estimators introducing an unknown amount of bias in the estimates. The current study improves the performance of ACS when applied to patchy and clustered but not rare populations and/or less clustered populations. This is done by combining the stopping rule with ACS without replacement of clusters so as to further limit the sampling effort in form of traveling expenses by avoiding repeat observations and by reducing the final sample size. The performance of the proposed design is investigated using simulated and real data.