Multi-temporal land use and cover changing analysis: the environmental impact in Mediterranean area

ABSTRACT

Human activity shapes the levels of anthropogenic pressure that depend on the land management method adopted. This has a fundamental role in the transformation of traditional landscapes. This study focuses on a representative region of the Mediterranean area with the objective to analyse the landscape’s dynamics, to detect the spatial arrangement of class patches, to identify the main agroecosystem characters and to provide a framework to assess ecosystems services. In order to assess land use/land cover changes and landscape persistence, the period between 1960 and 2012 was analysed, taking into consideration the years 1960, 2000 and 2012 using comparable land use maps. Land use and land cover analysis show an urban area growth of 24% during 2000–2012 and of 523% over between 1960 and 2012. The very high levels of land abandonment up to the year 2000 (+7216%) have reversed their trend between 2000 and 2012 (?95%). The orchards showed a relevant increase, particularly after 2000, while the vineyards were linked to the highest value of surface erosion (?74%). The outcomes showed that urban settlements can damage the ecological network with negative effects on the landscape’s environmental sustainability in proximity of significant urban centres. Instead, the ecological network is well preserved and highly associated to the agricultural areas when there is the persistence of many land uses and low urban density, despite the presence of dynamic changes.     

Neighborhood effects on seed dispersal by frugivores: testing theory with a mistletoe-marsupial system in Patagonia

The outcome of the dispersal process in zoochorous plants is largely determined by the behavior of frugivorous animals. Recent simulation studies have found that fruit removal rates and mean dispersal distances are strongly affected by fruiting plant neighborhoods. We empirically tested the effects of conspecific fruiting plant neighborhoods, crop sizes, and plant accessibility on fruit removal rates and seed dispersal distances of a mistletoe species exclusively dispersed by an arboreal marsupial in Northern Patagonia. Moreover, in this study, we overcome technical limitations in the empirical estimation of seed dispersal by using a novel 15N stable isotope enrichment technique together with Bayesian mixing models that allowed us to identify dispersed seeds from focal plants without the need of extensive genotyping. We found that, as predicted by theory, plants in denser neighborhoods had greater fruit removal and shorter mean dispersal distances than more isolated plants. Furthermore, the probability of dispersing seeds farther away decreased with neighborhood density. Larger crop sizes resulted in larger fruit removal rates and smaller probabilities of longer distance dispersal. The interplay between frugivore behavioral decisions and the spatial distribution of plants could have important consequences for plant spatial dynamics.     

Heavy metals detection in river water with cantilever nanobiosensor

Abstract

Heavy metals can be highly toxic depending on the dose and the chemical form. In this context, sensing devices such as nanobiosensors have been presented as a promising tool to monitor contaminants at micro and nanoscale. In this work, cantilever nanobiosensors with phosphatase alkaline were developed and applied to detect heavy metals (Pb, Ni, Cd, Zn, Co, and Al) in river water. The nanobiosensor surface was functionalized by the self-assembled monolayers (SAM) technique using 16-mercaptohexadecanoic acid, N-(3-dimethylaminopropyl)-N′-ethylcarbodiimide (EDC) and N- hydroxysuccinimide (NHS), and phosphatase alkaline enzyme. The sensing layer deposited on the cantilever surface presented a uniform morphology, at nanoscale, with 80?nm of thickness. The nanobiosensor showed a detection limit in the ppb range and high sensitivity, with a stability of fifteen days. The developed cantilever nanobiosensor is a simple tool, suitable for the direct detection of contaminants in river water.     

Physical–chemical processes of sustainable materials’ production from hazardous toner waste,galvanic glass waste and spent foundry sand

Journal of Material Cycles and Waste Management - Several sustainable white ceramic composites were prepared from 3 to 7 wt.% of hazardous toner waste, 30–40% of spent foundry sand,...     

Retrospective analysis of spatial and temporal variability of chlorophyll-a in the Curonian Lagoon

The Curonian Lagoon, the largest in Europe (total surface area 1584?km²), is located in the southern part of the Baltic Sea, from which it is separated by a narrow sand bar and to which it is connected by the Klaipeda Straits. It is characterised by shallow eutrophic waters (mean depth 3.8?m) with average low salinity (<5??) due to the nutrient-rich freshwaters discharged by the river Nemunas. Cyanobacteria blooms, including species producing toxic metabolites, have been a frequent phenomenon in summer. In this study a series of MERIS Full Resolution (FR) satellite images acquired between 2004 and 2009 during summer periods were used to assess the temporal evolution and spatial variability of the lagoon water quality in terms of chlorophyll-a. The models/algorithms were calibrated/validated with field data collected in 2009, based on in situ radiometric (remote sensing reflectance -Rrs-) and limnological (chlorophyll-a concentrations -chl-a-) measurements. The chl-a concentrations were estimated by developing a semi-empirical band ratio (Rrs(708)/Rrs(664)) equation applied to MERIS images after correction for atmospheric effects with the 6S code. Results from this study suggest elevated spatial and temporal variability of chl-a. Spatial variability probably arises from the mosaic of situations within the Curonian lagoon in terms of bottom sediment features, nutrient availability in the water column, water depth and hydrodynamics. Temporal variability is probably linked to complex and interplaying metereological and environmental constraints such as the length of the ice cover period, average water temperatures, wind-induced sediment re-suspension, the pattern of precipitations and river-associated nutrient transport to the lagoon. This study stresses the importance of remote sensing as a valid tool for long-term whole ecosystem studies. The preliminary results need more through analyses and intersection with other environmental data in order to better comprehend algal bloom determinants in complex and extremely dynamic systems such as coastal lagoons.     

Finite population properties of individual predictors based on spatial patterns

In this study a conceptual framework for assessing the statistical properties of a non-stochastic spatial interpolator is developed through the use of design-based finite population inference tools. By considering the observed locations as the result of a probabilistic sampling design, we propose a standardized weighted predictor for spatial data starting from a deterministic interpolator that usually does not provide uncertainty measures. The information regarding the coordinates of the spatial locations is known at the population level and is directly used in constructing the weighting system. Our procedure captures the spatial pattern by means of the Euclidean distances between locations, which are fixed and do not require any further assessment after the sample has been drawn. The predictor for any individual value turns in a ratio of design-based random quantities. We illustrate the predictor design-based statistical properties, i.e. asymptotically p-unbiasedness and p-consistency, for simple random sampling without replacement. An application to a couple of environmental datasets is presented, for assessing predictor performances in correspondence of different population characteristics. A comparison with the equivalent non-spatial predictor is presented.     

Air pollution perception in ten countries during the COVID-19 pandemic

As largely documented in the literature, the stark restrictions enforced worldwide in 2020 to curb the COVID-19 pandemic also curtailed the production of air pollutants to some extent. This study investigates the perception of the air pollution as assessed by individuals located in ten countries: Australia, Brazil, China, Ghana, India, Iran, Italy, Norway, South Africa and the USA. The perceptions towards air quality were evaluated by employing an online survey administered in May 2020. Participants (N = 9394) in the ten countries expressed their opinions according to a Likert-scale response. A reduction in pollutant concentration was clearly perceived, albeit to a different extent, by all populations. The survey participants located in India and Italy perceived the largest drop in the air pollution concentration; conversely, the smallest variation was perceived among Chinese and Norwegian respondents. Among all the demographic indicators considered, only gender proved to be statistically significant.Supplementary InformationThe online version contains supplementary material available at 10.1007/s13280-021-01574-2.     

Projected future climate change and Baltic Sea ecosystem management

Climate change is likely to have large effects on the Baltic Sea ecosystem. Simulations indicate 2–4 °C warming and 50–80 % decrease in ice cover by 2100. Precipitation may increase ~30 % in the north, causing increased land runoff of allochthonous organic matter (AOM) and organic pollutants and decreased salinity. Coupled physical–biogeochemical models indicate that, in the south, bottom-water anoxia may spread, reducing cod recruitment and increasing sediment phosphorus release, thus promoting cyanobacterial blooms. In the north, heterotrophic bacteria will be favored by AOM, while phytoplankton production may be reduced. Extra trophic levels in the food web may increase energy losses and consequently reduce fish production. Future management of the Baltic Sea must consider the effects of climate change on the ecosystem dynamics and functions, as well as the effects of anthropogenic nutrient and pollutant load. Monitoring should have a holistic approach, encompassing both autotrophic (phytoplankton) and heterotrophic (e.g., bacterial) processes.