Photoacoustic spectroscopy for estimating nutritional indices in Lepidopteran defoliators

Lymantria dispar L. and Malacosoma neustrium (L.) are the most serious defoliators of cork oak in the Mediterranean region. For this reason, information on their feeding behaviour are important in pest management. A non-destructive approach by using photoacoustic spectroscopy (PAS) combined with a partial least squares regression analyses (PLS), has been used to provide a rapid and cost-effective analysis to assess foliage chemistry and to estimate some nutritional indices of these insects

Wide divergence of fungal communities inhabiting rocks and soils in a hyper‐arid Antarctic desert

Highly simplified microbial communities colonise rocks and soils of continental Antarctica ice-free deserts. These two habitats impose different selection pressures on organisms, yet the possible filtering effects on the diversity and composition of microbial communities have not hitherto been fully characterised. We hence compared fungal communities in rocks and soils in three localities of inner Victoria Land. We found low fungal diversity in both substrates, with a mean species richness of 28 across all samples, and significantly lower diversity in rocks than in soils. Rock and soil communities were strongly differentiated, with a multinomial species classification method identifying just three out of 328 taxa as generalists with no affinity for either substrate. Rocks were characterised by a higher abundance of lichen-forming fungi (typically Buellia, Carbonea, Pleopsidium, Lecanora, and Lecidea), possibly owing to the more protected environment and the porosity of rocks permitting photosynthetic activity. In contrast, soils were dominated by obligate yeasts (typically Naganishia and Meyerozyma), the abundances of which were correlated with edaphic factors, and the black yeast Cryomyces. Our study suggests that strong differences in selection pressures may account for the wide divergences of fungal communities in rocks and soils of inner Victoria Land

Modelling of long-term Zn, Cu, Cd and Pb dynamics from soils fertilised with organic amendments

Soil contamination by trace elements (TEs) is a major concern for sustainable land management. A potential source of excessive inputs of TEs into agricultural soils are organic amendments. Here, we used dynamic simulations carried out with the Intermediate Dynamic Model for Metals (IDMM) to describe the observed trends of topsoil Zn (zinc), Cu (copper), Pb (lead) and Cd (cadmium) concentrations in a long-term (>60-year) crop trial in Switzerland, where soil plots have been treated with different organic amendments (farmyard manure, sewage sludge and compost). The observed ethylenediaminetetraacetic acid disodium salt (EDTA)-extractable concentrations ranged between 2.6 and 27.1 mg kg−1 for Zn, 4.9 and 29.0 mg kg−1 for Cu, 6.1–26.2 mg kg−1 for Pb, and 0.08 and 0.66 mg kg−1 for Cd. Metal input rates were initially estimated based on literature data. An additional, calibrated metal flux, tentatively attributed to mineral weathering, was necessary to fit the observed data. Dissolved organic carbon fluxes were estimated using a soil organic carbon model. The model adequately reproduced the EDTA-extractable (labile) concentrations when input rates were optimised and soil lateral mixing was invoked to account for the edge effect of mechanically ploughing the trial plots. The global average root mean square error (RMSE) was 2.7, and the average bias (overestimation) was −1.66, −2.18, −4.34 and −0.05 mg kg−1 for Zn, Cu, Pb and Cd, respectively. The calibrated model was used to project the long-term metal trends in field conditions (without soil lateral mixing), under stable climate and management practices, with soil organic carbon estimated by modelling and assumed trends in soil pH. Labile metal concentrations to 2100 were largely projected to remain near constant or to decline, except for some metals in plots receiving compost. Ecotoxicological thresholds (critical limits) were predicted to be exceeded presently under sewage sludge inputs and to remain so until 2100. Ecological risks were largely not indicated in the other plots, although some minor exceedances of critical limits were projected to occur for Zn before 2100. This study advances our understanding of TEs' long-term dynamics in agricultural fields, paving the way to quantitative applications of modelling at field scales

Croste superficiali su un suolo tropicale in Zimbabwe: processi di formazione e possibilita' di controllo

Dottorato di ricerca in scienza del suolo. 8. ciclo. A.a. 1994-95. Tutore G. G. RistoriConsiglio Nazionale delle Ricerche - Biblioteca Centrale - P.le Aldo Moro, 7, Rome; Biblioteca Nazionale Centrale - P.za Cavalleggeri, 1, Florence / CNR - Consiglio Nazionale delle RichercheSIGLEITItal

Assessment of the impact of conventional and organic agroecosystems management options and conservation tillage on soil fertility at the Montepaldi Long Term Experiment, Tuscany

Fertility is a characteristic of an agroecosystem which is usually and promptly identified with the crop yield. Nevertheless, it can be considered the result of many processes and factors such as climatic, edaphic and agronomic which cannot be extended and generalized to all systems and crops. This study evaluates the effects on soil fertility as influenced by organic (OR) and high-input (conventional, CO) management combined with three tillage systems, i.e., plowing (plw), chisel plowing (chp) and disk harrowing (dsh) at the Montepaldi Long Term Experiment (MoLTE), Tuscany, Italy. Fertility was evaluated through the following indicators: i) chemical (Olsen P, Kjeldahl N and, OM); ii) physical (bulk density on clods and cores, pore size distribution, penetrometry, aggregate stability, soil profile assessment, VESS, i.e. visual evaluation of soil structure); iii) biological (earthworm abundance and root distribution). As regards the effect of management, CO was higher in crop yields, available P2O5, bulk densities (clods), aggregate stability and soil penetration resistance, while OR was higher in bulk densities (cores). Nevertheless, the effect of management was observed for root distribution as a function of depth, where roots explored larger portions of soil in OR profiles. Regarding tillage, the order plw, chp, dsh was characterized by an increase in soil penetration resistance and number of earthworms. Moreover, a relationship with time was found for earthworm abundance, where the OR system exhibited a higher and constant population. Organic management seems to achieve a long-lasting soil fertility. In the MoLTE experiment results suggest that available P2O5, bulk density (clods), aggregate stability, soil penetration resistance, time-related earthworm abundance, root distribution and yields are the most informative on the impact of management and tillage options. Furthermore, results of physical and biological fertility indicators support the hypothesis that significant differences between OR and CO management, even if not observed in topsoil, might be detected in deeper soil layers, below 30cm

Elaboration of the Italian portion of the global soil organic carbon map (GSOCMAP)

The Global Soil Organic Carbon map (GSOCmap) published by the Food and Agriculture Organization constitutes a baseline estimation of soil organic carbon stock (CS, ton ha–1) from 0 to 30 cm, on a grid at 30 arc-seconds resolution (approximately 1 x 1 km). It has been produced for the Italian territory by the Italian Soil Partnership (ISP): a national hub of institutions dealing with soils, either academic/research institutions, and regional soil services (RSS). The RSS are the main soil data owners in Italy and play a central role in the elaboration of policies for soil management. The RSS adhering to the ISP are: Calabria, Campania, Emilia Romagna, Friuli Venezia Giulia, Liguria, Lombardia, Marche, Piemonte, Puglia, Sicilia, Toscana, and Veneto. A national soil database is maintained by the Consiglio per la Ricerca e l'Analisi dell'Economia Agraria (CREA). The RSS contributed with soil data, with mean density of 1 point per 50 square kilometres, selecting data analysed for soil organic carbon content (SOC, dag kg-1), which were representative and well distributed for the following environmental covariates: land use, geomorphology, and climate. The data were selected inbetween 1990 al 2013. This was necessary in order to exclude the effect of the new soil protection policies of the Rural Development Programme 2014-2020. For the RSS not included in the ISP, the data were selected from the national soil database. 6748 point data were finally selected. SOC values obtained with the Springer and Klee and flash combustion elemental analyser methods were retained for elaborations, because the 2 methods, were found to give statistically equivalent results. SOC values obtained with Walkey and Black method were, instead, corrected with an empirical factor of 1.3. 2292 of the 6748 point data had also measured bulk density (BD, Mg m–3). Pedotransfer functions were calibrated to estimate BD were measured BD were missing, with the following as auxiliary variables: land use, soil regions, texture, and SOC. The carbon stock (CS, ton ha–1) was calculated by multiplying: 0.3 (m) * SOC (dag kg-1) * fine earth fraction (1 - skeletal content expressed as daL m–3) * BD (Mg m–3). CS of the first 30 cm depth was calculated as depth-weighted average. A spatial statistics method was used for the CS interpolation. The following auxiliary variables were used: soil regions, soil subregions, Corine land cover 2006, lithology, soils affected by natural constrains (gleyic, histic, vertic, coarse, shallow, arenic, sodic, and acid), sand content, silt content, 30-m aster-DEM, distance from coast, distance from relieves, soil aridity index, annual mean precipitations, mean annual air temperature, soil inorganic carbon, and soil depth. For the soil region of Po valley, the land units at 1:250,000 scale were also used. The interpolation method was a general linear regression for the soil regions of Po valley, and a radial basis function for the remaining Italian territory. The 6748 point data were divided, by spatial random sampling, into 10 subsets. Ten interpolations were produced, each time leaving out 1/10 of the dataset. Average (fig. 1), standard deviation and confidence intervals of these 10 interpolations were calculated. Mean Absolute Errors (MAE) and Root Mean Squared Errors (RMSE) were respectively 25.5 and 36.4 Mg/ha. A.85 Italy Map source: Country submission Point data Number of samples: 6748 Sampling period: 1990-2013 SOC analysis method: SOC values obtained with the Springer and Klee and ’flash combustion elemental analyser’ methods were retained for elaborations. Uncorrected values obtained by the Walkey and Black method were corrected with an empirical linear equation, based on previous studies and as recommended by the Italian official methods. BD analysis method: Undisturbed sampling, core method and pit method Mapping method Mapping method details: Neural Networks and GLM, according to soil region Validation statistics: Mean Error (ME) of the prediction is 1.688 Mg/ha, MAE 25.57 Mg/ha, Root Mean Squared Error (RMSE) is 36.24 Mg/ha