Two millennia of climate variability in the Central Mediterranean

This experimental work addresses the need for high-resolution, long and homogeneous climatic time series that facilitate the study of climate variability over time scales of decades to millennia. We present a high-resolution record of foraminiferal δ18O from a Central-Mediterranean sediment core that covers the last two millennia. The record was analyzed using advanced spectral methods and shows highly significant oscillatory components with periods of roughly 600, 350, 200, 125 and 11 years. Over the last millennium, our data show several features related to known climatic periods, such as the Medieval Optimum, the Little Ice Age and a recent steep variation since the beginning of the Industrial Era. During the preceding millennium, the δ18O series also reveals a surprising maximum at about 0 AD, suggesting low temperatures at that time. This feature contradicts widely held ideas about the Roman Classical Period; it is, therefore, discussed at some length, by reviewing the somewhat contradictory evidence about this period. We compare the δ18O record with an alkenone-derived sea surface temperature time series, obtained from cores extracted in the same Central-Mediterranean area (Gallipoli Terrace, Ionian Sea), as well as with Italian and other European temperature reconstructions over the last centuries. Based on this comparison, we show that the long-term trend and the 200-y oscillation in the records are temperature driven and have a dominant role in describing temperature variations over the last two millennia

A high-resolution δ18O record and Mediterranean climate variability

A high-resolution, well-dated foraminiferal δ18O record from a shallow-water core drilled from the Gallipoli Terrace in the Gulf of Taranto (Ionian Sea), previously measured over the last two millennia, has been extended to cover 707 BC–1979 AD. Spectral analysis of this series, performed by Singular Spectrum Analysis (SSA) and other classical and advanced methods, strengthens the results obtained analysing the shorter δ18O profile, detecting the same highly significant oscillations of about 600 yr, 380 yr, 170 yr, 130 yr, and 11 yr, respectively explaining about 12%, 7%, 5%, 2% and 2% of the time series total variance, plus a millennial trend (18% of the variance). The comparison with the results of Multi-channel Singular Spectrum Analysis (MSSA) applied to a data set of 26 Northern Hemisphere (NH) temperature-proxy records shows that NH temperature anomalies share with our local record a long-term trend and a bicentennial cycle. These two variability modes, previously identified as temperature-driven, are the most powerful modes in the NH temperature data set. Both the long-term trends and the bicentennial oscillations, when reconstructed locally and hemispherically, show coherent phases. Also the corresponding local and hemispheric amplitudes are comparable, if changes in the precipitation-evaporation balance of the Ionian sea, presumably associated with temperature changes, are taken into account

Tweet-tales: moods of socio-economic crisis?

The widespread adoption of highly interactive social media like Twitter, Facebook and other platforms allow users to communicate moods and opinions to their social network. Those platforms represent an unprecedented source of information about human habits and socio-economic interactions. Several new studies have started to exploit the potential of these big data as fingerprints of economic and social interactions. The present analysis aims at exploring the informative power of indicators derived from social media activity, with the aim to trace some preliminary guidelines to investigate the eventual correspondence between social media indices and available labour market indicators at a territorial level. The study is based on a large dataset of about 4 million Italian-language tweets collected from October 2014 to December 2015, filtered by a set of specific keywords related to the labour market. With techniques from machine learning and user’s geolocalization, we were able to subset the tweets on specific topics in all Italian provinces. The corpus of tweets is then analyzed with linguistic tools and hierarchical clustering analysis. A comparison with traditional economic indicators suggests a strong need for further cleaning procedures, which are then developed in detail. As data from social networks are easy to obtain, this represents a very first attempt to evaluate their informative power in the Italian context, which is of potentially high importance in economic and social research

The network of plants volatile organic compounds

Abstract Plants emission of Volatile Organic Compounds (VOCs) is involved in a wide class of ecological functions, as VOCs play a crucial role in plants interactions with biotic and abiotic factors. Accordingly, they vary widely across species and underpin differences in ecological strategy. In this paper, VOCs spontaneously emitted by 109 plant species (belonging to 56 different families) have been qualitatively and quantitatively analysed in order to provide an alternative classification of plants species. In particular, by using bipartite networks methodology from Complex Network Theory, and through the application of community detection algorithms, we show that is possible to classify species according to chemical classes such as terpenes and sulfur compounds. Such complex network analysis allows to uncover hidden plants relationships related to their evolutionary and adaptation to the environment story

Carbon dioxide fluxes in Alpine grasslands at the Nivolet Plain, Gran Paradiso National Park, Italy 2017–2023

The version of record of this article, first published in [Scientific Data], is available online at Publisher’s website: http://dx.doi.org/10.1038/s41597-024-03374-1We introduce a georeferenced dataset of Net Ecosystem Exchange (NEE), Ecosystem Respiration (ER) and meteo-climatic variables (air and soil temperature, air relative humidity, soil volumetric water content, pressure, and solar irradiance) collected at the Nivolet Plain in Gran Paradiso National Park (GPNP), western Italian Alps, from 2017 to 2023. NEE and ER are derived by measuring the temporal variation of CO2 concentration obtained by the enclosed chamber method. We used a customised portable non-steady-state dynamic flux chamber, paired with an InfraRed Gas Analyser (IRGA) and a portable weather station, measuring CO2 fluxes at a number of points (around 20 per site and per day) within five different sites during the snow-free season (June to October). Sites are located within the same hydrological basin and have different geological substrates: carbonate rocks (site CARB), gneiss (GNE), glacial deposits (GLA, EC), alluvial sediments (AL). This dataset provides relevant and often missing information on high-altitude mountain ecosystems and enables new comparisons with other similar sites, modelling developments and validation of remote sensing data.This work was funded by the H2020 projects ECOPOTENTIAL (grant number: 641762), e-shape (grant number: 820852), eLTER PLUS (grant number: 871128), by the Italian National Biodiversity Future Center (NBFC), National Recovery and Resilience Plan (NRRP; mission 4, component 2, investment 1.4 of the Ministry of University and Research, funded by the European Union–NextGenerationEU; project code CN00000033), and by the ITINERIS NRRP Italian infrastructure project (project code No. IR0000032 - ESFRI Environment)

Carbon dioxide measurements in mountain and Arctic ecosystems using eddy covariance method

<p>Presentation at the Mediterranean Mountains Meeting (25-28 October 2023, Granada) organized by LifeWatch Eric and the University of Granada. </p&gt

Climate variability and amplification revealed from indicators in the Gulf of Taranto

A well-dated, high-resolution core (GT90-3), extracted from the Gallipoli Terrace in the Ionian Sea, is used to deduce information about climate variability during the last millennia and in particular before 1000 AD, where few proxy records are available. We present the foraminiferal δ18O record measured in this core and covering the last 2200 years, whose spectral analysis, performed by several advanced methods, reveals highly significant oscillatory components with periods of about 600, 350, 200, 125 and 11 years. These components are discussed also in comparison with those deduced from other archives, concluding that the overall trend and the 200 y component together are very likely temperature-driven. On the contrary, concerning the decadal range the situation is not so clear and salinity and circulation effects probably cannot be completely neglected