Land Management Versus Natural Factors in Land Instability: Some Examples in Northern Spain

The objective of this work is to test a hypothesis formulated on the basis of former results which considers that there might be a “global geomorphic change,” due to activities related to land management and not determined by climate change, which could be causing an acceleration of geomorphic processes. Possible relationships between some geomorphic processes related to land instability (landslides or sediment generation) and potential triggering factors are analyzed in study areas in northern Spain. The analysis is based on landslide inventories covering different periods, as well as the determination of sedimentation rates. Temporal landslide and sedimentation rate trends are compared with different indicators of human activities (land-use change, logging, forest fires) and with potential natural triggers (rainfall, seismicity). The possible influence of the road network in the distribution of landslides is also analyzed. Results obtained show that there is a general increase of both landslide and sedimentation rates with time that cannot be explained satisfactorily by observed rainfall trends and even less by seismicity. Land-use change appears to be by far the main factor leading to land instability, with some changes producing up to a 12-fold increase of landslide rate. A relationship between road network and the spatial distribution of landslides has also been observed. These results do confirm the existence of an acceleration of geomorphic processes in the region, and also suggest that climate-related factors play a limited role in the changes observed.     

Adaptive cluster double sampling with post stratification with application to an epiphytic lichen community

The implementation of an adaptive cluster sampling design often becomes logistically challenging because variation in the final sampling effort introduces uncertainty in survey planning. To overcome this drawback, an inexpensive and easy to measure auxiliary variable could be used in a two-phase survey strategy, called adaptive cluster double sampling (Félix-Medina and Thompson in Biometrika 91:877–891, 2004). In this paper, a two-phase sampling strategy is proposed which combines the idea of adaptive cluster double sampling with the principle of post-stratification. In the first-phase an adaptive cluster sample is selected by means of an inexpensive auxiliary variable. Networks from the first phase sampling are then post-stratified according to their size. In the second-phase, the network structure is used to select a subsample of units by means of stratified random sampling. The proposed sampling strategy employs stratification without requiring an a priori delineation of the strata. Indeed, the strata sizes are estimated in the course of the two-phase sampling process. Therefore, it is suitable for situations where stratification is suspected to be efficient but strata cannot be easily delineated in advance. In this framework, a new type of estimator for the population mean which mimics the stratified sampling mean estimator and an estimator of the sampling variance are proposed. The results of a simulation study confirm, as expected, that the use of post-stratification leads to gain in precision for the estimator. The proposed sampling strategy is applied for targeting an epiphytic lichen community Lobarion pulmonariae in a forest area of the Northern Apennines (N-Italy), characterized by several species of conservation concern.     

Urban air pollution monitoring and correlation properties between fixed-site stations

The rich regional air-monitoring network of the Emilia-Romagna region of Italy has been used to quantify the spatial variability of the main pollutants within urban environments and to analyze the correlations between stations. The spatial variability of the concentrations of the majority of pollutants within the city was very high, making it difficult to differentiate and characterize the urban environments and to apply legal limits with uniform criteria. On the other hand, the correlations between the fixed-site monitoring stations were high enough for their data to be retained generally very appropriately for controlling temporal trends. Starting from the high correlation level, a procedure was proposed and tested to derive pollution levels, using short-term measurements, such as passive samplers and mobile-station data. The importance of long-term statistics in urban air pollution mapping was emphasized. Treatment of missing data in time series and quality assurance were indicated as possible fields for applications for the correlation properties.     

Phytoremediation of Soil Polluted by Nickel Using Agricultural Crops

Soil pollution due to heavy metals is widespread; on the world scale, it involves about 235 million hectares. The objectives of this research were to establish the uptake efficiency of nickel by some agricultural crops. In addition, we wanted to establish also in which part of plants the metal is stored for an eventual use of biomass or for recycling the metal. The experiments included seven herbaceous crops such as: barley (Hordeum vulgaris), cabbage (Brassica juncea), spinach (Spinacea oleracea), sorghum (Sorgum vulgare), bean (Phaseolus vulgaris), tomato (Solanum lycopersicum), and ricinus (Ricinus communis). We used three levels of treatment (150, 300, and 600 ppm) and one control. At the end of the biological cycle of the crops, the different parts of plants, i.e., roots, stems, leaves, fruits, or seeds, were separately collected, oven dried, weighed, milled, and separately analysed. The leaves and stems of spinach showed a very good nickel storage capacity. The ricinus too proved to be a very good nickel storer. The ability of spinach and ricinus to store nickel was observed also in the leaves of cabbage, even if with a lower storage capacity. The bean, barley, and tomato, in decreasing order of uptake and storage capacity, showed a high concentration of nickel in leaves and stems, whereas the sorghum evidenced a lesser capacity to uptake and store nickel in leaves and stems. The bean was the most efficient in storing nickel in fruits or grains. Tomato, sorghum, and barley have shown a storage capacity notably less than bean. The bean appeared to be the most efficient in accumulating nickel in the roots, followed in decreasing order by sorghum, ricinus, and tomato. With regard to the removal of nickel, spinach was the most efficient as it contains the highest level of this metal per gram of dry matter. The ricinus, cabbage, bean, sorghum, barley, and tomato evidenced a progressively decreasing efficiency in the removal of nickel.     

Socioeconomic spillovers of the 2016–2017 Italian earthquakes: a bi-regional inoperability model

Environment, Development and Sustainability - In August and October 2016, and January 2017, Central Italy was shaken by four strong earthquakes followed by other earthquake swarms. These disruptive...     

Hierarchical modeling of seed variety yields and decision making for future planting plans

Eradicating hunger and malnutrition is a key development goal of the twenty first century. This paper addresses the problem of optimally identifying seed varieties to reliably increase crop yield within a risk-sensitive decision making framework. Specifically, a novel hierarchical machine learning mechanism for predicting crop yield (the yield of different seed varieties of the same crop) is introduced. This prediction mechanism is then integrated with a weather forecasting model and three different approaches for decision making under uncertainty to select seed varieties for planting so as to balance yield maximization and risk. The model was applied to the problem of soybean variety selection given in the 2016 Syngenta Crop Challenge. The prediction model achieved a median absolute error of 235 kg/ha and thus provides good estimates for input into the decision models. The decision models identified the selection of soybean varieties that appropriately balance yield and risk as a function of the farmer’s risk aversion level. More generally, the models can support farmers in decision making about which seed varieties to plant.     

Bibliometric analysis of Climate Change Vulnerability Assessment research

The first step in planning the actions for climate change adaptation involves performing Climate Change Vulnerability Assessment (CCVA) to vulnerable populations and ecological systems. The study aims to perform a bibliometric analysis on the CCVA research field to identify how it was structured in terms of the mostly occurring research terms and their citation impact. A set of scientific papers related to CCVA (n?=?8941) were retrieved via Elsevier’s Scopus database over the period 1996–2016 using specific keywords. The search was carried out in February 2017. The number of yearly papers published in CCVA research field increased after 2006, increasing more than six times in 2016. Our co-occurrences term analysis grouped four clusters related to (i) exposure, sensitivity, and quantitative methods for assessing CCVA, (ii) adaptive capacity and qualitative approaches, (iii) CCVA integrated approaches by combining participatory methods to quantitative ones, and (iv) collaboration and participation issues related to global change. The co-citation analysis showed that highly cited research terms were related to adaptation, exposure factors, and related changes and global change. This bibliometric analysis has provided an overall picture on the CCVA research field, particularly highlighting its utility for climate change adaptation.     

Competition for the home and aggressive behaviour in the chiton Acanthopleura gemmata (Blainville) (Mollusca: Polyplacophora)

Summary Computerized screening of all the positions recorded during a synodic month on 120 individually marked chitons (Acanthopleura gemmata) pinpointed their preferential resting points. Unlike the majority of intertidal chitons so far studied, A. gemmata rests in well-defined homes actively dug in the rock. Homes proved to be not strictly individual and periodically interchangeable. A complex aggressive behaviour was recorded in the field when two animals came in contact at home. When competing for ownership of a resting site rival chitons may suppress their nocturnal feeding activity. Despite its strong home-related territoriality A. gemmata showed no mutual exclusion on the feeding area. The highly specialized resting habits clearly protects A. gemmata from its most important predator, the toad fish Arothron immaculatus. The behaviour of A. gemmata is compared to that of other chitons and gastropods, and the current hypotheses concerning the adaptive value of the homing behaviour in littoral molluscs are discussed.