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Understanding how marine taxa will respond to near-future climate changes is one of the main challenges for management of coastal ecosystem services. Ecological studies that investigate relationships between the environment and shell properties of commercially important marine species are commonly restricted to latitudinal gradients or small-scale laboratory experiments. This paper aimed to explore the variations in shell features and growth of the edible bivalve Chamelea gallina from the Holocene sedimentary succession to present-day thanatocoenosis of the Po Plain-Adriatic Sea system (Italy). Comparing the Holocene sub-fossil record to modern thanatocoenoses allowed obtaining an insight of shell variations dynamics on a millennial temporal scale. Five shoreface-related assemblages rich in C. gallina were considered: two from the Middle Holocene, when regional sea surface temperatures were higher than today, representing a possible analogue for the near-future global warming, one from the Late Holocene and two from the present-day. We investigated shell biometry and skeletal properties in relation to the valve length of C. gallina. Juveniles were found to be more porous than adults in all horizons. This suggested that C. gallina promoted an accelerated shell accretion with a higher porosity and lower density at the expense of mechanically fragile shells. A positive correlation between sea surface temperature and both micro-density and bulk density were found, with modern specimens being less dense, likely due to lower aragonite saturation state at lower temperature, which could ultimately increase the energetic costs of shell formation. Since no variation was observed in shell CaCO3 polymorphism (100% aragonite) or in compositional parameters among the analyzed horizons, the observed dynamics in skeletal parameters are likely not driven by a diagenetic recrystallization of the shell mineral phase. This study contributes to understand the response of C. gallina to climate-driven environmental shifts and offers insights for assessing anthropogenic impacts on this economic relevant species. [ABSTRACT FROM AUTHOR]

Climate modelling and palaeotemperature reconstructions derived from several proxies (TEX 86 , δ18O) suggest that the Late Cretaceous was one of the warmest intervals in Earth history. The greenhouse climate reached its acme near the Cenomanian-Turonian boundary (CTB) interval with sea surface temperatures over 35 °C in low and mid- palaeolatitudes, coinciding with the highest sea level stands of the Phanerozoic. Following this warming phase, a general cooling trend punctuated by short-term hot snaps characterized the rest of the Cretaceous. Palaeotemperature and palaeoenvironmental changes are well documented in deep-water carbonate deposits based on variations in geochemical proxies and distribution patterns of macro- and microfauna. However, such climatic and environmental fluctuations severely impacted carbonate platforms, sedimentary environments that are particularly sensitive to external perturbations. Palaeontological data show major changes within the main carbonate platform producers (rudists and benthic foraminifera) during the early Late Cretaceous. Both groups experienced major taxonomic turnovers at the CTB, followed by a further re-radiation in the middle/late Turonian. The lack of detailed palaeoclimatic reconstructions in shallow water carbonate succession hampers the possibility to investigate a possible causal relationship between temperature changes and faunal evolution. In this paper, we report integrated geochemical, sedimentological, and palaeontological data from the Adriatic Carbonate Platform (Friuli, north-east Italy). Benthic foraminifera biostratigraphy and isotope stratigraphy (δ13C and 87Sr/86Sr) were used to precisely constrain the stratigraphy of the late Cenomanian-middle Turonian interval. δ18O analysis on both well-preserved rudist shells and bulk rock samples enabled the construction of high-resolution palaeotemperature curves. The resulting temperature trends are comparable with those from the deep-water record across the late Cenomanian-Turonian interval. The warmest phase was in the Early Turonian with sea surface palaeotemperatures as high as 41–45 °C recorded in rudist shells. Data show temperature fluctuation from the late Cenomanian to the Early Turonian with a magnitude >7 °C. Benthic foraminifera and rudist evolution responded to these palaeotemperature fluctuations, and their decline in the late Cenomanian and full recovery in the Turonian suggest a strong link with temperature changes. • Reconstructed temperatures from carbonate platforms during the Cenomanian -Turonian interval are missing • High resolution paleotemperatures reconstruction and biota evolution (rudists and benthic foraminifera) from Friuli Carbonate Platform is presented • Paleotemperatures estimated using δ18O analyses on bulk rock and well preserved bivalve samples (rudists and Chondrodonta) • δ18O analyses in bivalve shells suggest warmest Temperatures °>40°C in the Early Turonian • Rudists and benthic foraminifera distribution/abundance strongly modulated by temperature changes [ABSTRACT FROM AUTHOR]

Slow and long-term variations of sea surface temperature anomalies have been interpreted as a red-noise response of the ocean surface mixed layer to fast and random atmospheric perturbations. How fast the atmospheric noise is damped depends on the mixed layer depth. In this work we apply this theory to determine the relevant spatial and temporal scales of surface layer thermal inertia in lakes. We fit a first order auto-regressive model to the satellite-derived Lake Surface Water Temperature (LSWT) anomalies in Lake Garda, Italy. The fit provides a time scale, from which we determine the mixed layer depth. The obtained result shows a clear spatial pattern resembling the morphological features of the lake, with larger values (7.18± 0.3 m) in the deeper northwestern basin, and smaller values (3.18 ± 0.24 m) in the southern shallower basin. Such variations are confirmed by in-situ measurements in three monitoring points in the lake and connect to the first Empirical Orthogonal Function of satellite-derived LSWT and chlorophyll-a concentration. Evidence from our case study open a new perspective for interpreting lake-atmosphere interactions and confirm that remotely sensed variables, typically associated with properties of the surface layers, also carry information on the relevant spatial and temporal scales of mixed-layer processes. [ABSTRACT FROM AUTHOR]

The European Space Agency Soil Moisture and Ocean Salinity (SMOS) mission was launched on November 2, 2009. Providing accurate soil moisture (SM) estimation is one of its main scientific objectives. Since the end of the commissioning phase, preliminary global SMOS SM data [Level 2 (L2) product] are distributed to users. In this paper, we carried out a first assessment of the reliability of this product through a comparison with in situ observed and modeled SM over three different sites: One is located in Luxemburg, and two are located in Italy. The period from August 1, 2010, to July 1, 2011, has been analyzed, giving us the opportunity to evaluate the satellite response to different SM states. The selected period is important for hydrological predictions as it is typically characterized by a sequence of transitions from dry to wet and from wet to dry conditions. In order to compare SMOS and ground SM measurements, a two-step approach has been applied. First, an exponential filter has been applied to approximate root-zone SM, and second, a cumulative distribution function matching has been employed to remove systematic differences between satellite and in situ observations and model simulations of SM. Our results indicate rather good reliability of the filtered and bias-corrected SM estimates derived from the first SMOS L2 products. Bearing in mind that an updated/advanced version of the SMOS SM product has been recently produced, our preliminary results already seem to confirm the potential of SMOS for monitoring of water in soils. [ABSTRACT FROM AUTHOR]

Thermal infrared remote sensing measurements have greatly improved in terms of spectral, spatial, and temporal resolution. These improvements are producing a clearer picture of the land surface and Earth atmospheric composition than ever before. Nevertheless, the analysis of this big quantity of data presents important challenges due to incomplete temporal and spatial recorded information. The aim of the present paper is to discuss a methodology to retrieve missing values of some interesting geophysical variables on a spatial field retrieved from spatially scattered infrared satellite observations in order to yield level 3, regularly gridded, data. The technique is based on a 2-Dimensional (2D) Optimal Interpolation (OI) scheme and is derived from the broad class of Kalman filter or Bayesian estimation theory. The goodness of the approach has been tested on 15-min temporal resolution Spinning Enhanced Visible and Infrared Imager (SEVIRI) emissivity and surface temperature (ST) products over South Italy (land and sea), on Infrared Atmospheric Sounding Interferometer (IASI) atmospheric ammonia ( N H 3 ) concentration over North Italy and carbon monoxide ( C O ), sulfur dioxide ( S O 2 ) and N H 3 concentrations over China. All these gases affect air quality. Moreover, sea surface temperature (SST) retrievals have been compared with gridded data from MODIS (Moderate-resolution Imaging Spectroradiometer) observations. For gases concentration we have considered data from 3 different emission inventories, that is, Emissions Database for Global Atmospheric Research v3.4.2 (EDGARv3.4.2), the Regional Emission inventory in ASiav3.1 (REASv3.1) and MarcoPolov0.1, plus an independent study. The results show the efficacy of the proposed strategy to better capture the daily cycle for surface parameters and to detect hotspots of severe emissions from gas sources affecting air quality such as C O and N H 3 and, therefore, to yield valuable information on the variability of gas concentration to complete ground stations measurements. [ABSTRACT FROM AUTHOR]

Abstract: An unusually intense subsynoptic-scale cyclone has been documented in southeastern Italy on 26 September 2006. Numerical simulations are performed with the Weather Research and Forecasting model (WRF). Model results show that the model is able to realistically capture the timing and intensity of the cyclone, identifying in this small-scale cyclone the typical characteristics of a Mediterranean tropical-like cyclone. Sensitivity experiments to sea surface temperature (SST) of the simulated cyclone are discussed in the present paper. In these experiments the SST was changed by a constant few degrees uniformly throughout the Mediterranean Sea. The simulated-cyclone sensitivity to SST is studied in the framework of an air–sea interaction theory, in particular during the two phases that are fundamental for the development of an environment favorable to severe convection and thus for the cyclone to be self-sustained. The modifications of the properties of the simulated cyclones are then analyzed using an objective evaluation, based on a phase diagram used to study the tropical–extratropical transition of cyclones. The present simulations show that the features typical of a tropical cyclone are progressively lost as the SST is reduced. In the colder SST experiments, the lower intensity of the sea-surface fluxes has the effect of delaying and reducing the development of convection and the intensification of the cyclone, so that the cyclone loses the characteristics of a tropical cyclone when SST is reduced by more than 4°C. On the other hand, the cyclone shows a pressure minimum deeper than the control run, with a persistent symmetric warm core, for SST increased by more than 2°C. Finally, when SST is changed by less than 2°C, the cyclone depth and trajectory are not significantly affected by the change in SST and, like the control run, show tropical-like features only for a limited period. [Copyright &y& Elsevier]

Paleoproductivity is reconstructed across a Mediterranean benchmark record, the Early/Middle Pleistocene Montalbano Jonico section, cropping out in southern Italy. High‐resolution coccolithophore and alkenone data (C37 and C37:2/C38:2 ratio) were collected in order to extend the data set on Mediterranean paleoproductivity pattern and forcing mechanisms. The multi‐proxy record indicates low productivity during glacial and stadial phases and enhanced productivity during interglacial and interstadials. Increased surface water turbidity, cold‐water temperature and polar‐subpolar low salinity water incursion appear as the dominant controls for low productivity during Marine Isotope Stage (MIS) 20. Enhanced productivity during MIS 19c was sustained by warmer surface waters, coupled with a seasonal precipitation regime, providing higher nutrient availability. Productivity increases during interstadials with respect to stadials, in relation with enhanced land‐derived nutrient input through river discharge during wetter winters. The productivity scenario we propose is similar to those reconstructed from deep‐sea records in the central and western Mediterranean during Dansgaard‐Oeschger oscillations over the last 70 ka. This indicates that similar forcing mechanisms acted on productivity dynamics on a regional scale over different times. We suggest that migration of the westerly wind system over the Mediterranean and the polar water inflow influenced productivity on a regional scale. The acquired data set provides new evidences on the environmental significance of the C37:2/C38:2 ratio and on its relation with surface water productivity. Plain Language Summary: Coccolithophores are calcifying unicellular algae and one of the most important marine phytoplankton group. In the present‐day oceans their distribution strongly depends on environmental factors such as nutrient concentration, surface water temperature, sunlight availability. Therefore, changes in fossil coccolithophore assemblages are successfully used for paleoclimatic and paleoceanographic reconstructions. They are also the source of organic compounds (the alkenones), which provide estimation of paleotemperature and paleoproductivity. We used variations of coccolithophore assemblages and of alkenones to identify paleoproductivity variations in the central Mediterranean, in a nearshore environment, during a key Quaternary paleoclimate interval. Our approach benefited of other paleoenvironmental indicators such as sea surface temperature and stable oxygen and carbon isotopes available at the studied section. We find that past climate changes clearly affected coccolithophore productivity at our site. Paleoproductivity was clearly favored by warm surface waters and by seasonal nutrient availability resulting by enhanced humidity over the central Mediterranean region. Our data also provide new indications on the relation between coccolithophore assemblage and alkenone variations through climate phases which may have future implication on their use for paleoenvironmental reconstruction. Key Points: Coccolithophore and alkenones underline productivity changes in a reference Early/Middle Pleistocene record from the central MediterraneanProductivity proxies reflect millennial‐scale climate changes with low/high values during cold and drier/warm and wetter conditionsSimilarity with the Dansgaard‐Oeschger oscillations scenario suggests a common regional climate forcing over productivity through time [ABSTRACT FROM AUTHOR]

During the Messinian, the sensitivity of the Mediterranean Basin to ecosystem perturbation was enhanced in response to the progressive restriction of water exchange with the Atlantic Ocean. The widespread deposition of organic-rich layers (i.e. sapropel) during the Messinian testifies the perturbation of the carbon and oxygen cycles; indeed, these sediments were deposited under conditions of oxygen starvation, presumably in response to a periodic deterioration of the thermohaline circulation strength. Disentangling the causes, the effect and magnitude of the thermohaline circulation weakening during the geological past is crucial for better constraining present and near-future deoxygenation dynamics in the Mediterranean region under the current climate warming. For this purpose, we investigate a Messinian sapropel-bearing succession cropping out at Monte dei Corvi (Ancona, central Italy) with mineralogical, petrographic, micropaleontological and stable Carbon and Oxygen isotopic analyses. We show that sapropel layers were deposited in response to an increase of the sea surface buoyancy, which hampered the thermohaline circulation and thus the oxygenation of bottom water, in turn affecting the bioturbating organisms. Within the lithological cycle, the recovery of an efficient thermohaline circulation is recorded by thin packstone layers underlying the marly limestone/marlstone, which record intense bottom currents. The marly limestone/marlstone accumulated during periods of intense primary productivity and organic carbon export to the sea bottom, which promoted bottom hypoxia but not organic matter preservation. We infer that these lithological changes resulted from variations in the Adriatic Deep Water formation system, controlled by precession-driven climatic and oceanographic changes. By integrating previously published Sea Surface Temperature (SST) with new isotopic and mineralogical data, we show that variations in Sea Surface Salinity (SSS) were the leading factor controlling sapropel deposition, minimizing the role of primary productivity. The SSTs characterizing the sapropel deposits are close to the range of those projected in the Eastern Mediterranean at the end of this century under climate warming. In this scenario, future warming will be coupled with SSS increase, which will counteract the density loss provided by temperature, making the bottom deoxygenation in the Eastern Mediterranean abysses unlikely. However, additional forcing, such as winter heat waves and eutrophication, could contribute to negatively affecting the Mediterranean oxygen balance and should be considered in model-based projections. • The Monte dei Corvi recorded the changes in the ADW formation during the Messinian. • The bottom deoxygenation resulted from variations in the freshwater input. • Future deoxygenation in Mediterranean can be provided by productivity or heatwaves. [ABSTRACT FROM AUTHOR]

In this paper, we use molecular paleothermometry, based on the TEX 86 proxy derived from fossilized archaeal lipids, to reconstruct absolute sea surface temperatures (SSTs) for the northwest Tethys Shelf during the late Pliensbachian to early Toarcian (Early Jurassic, ~183 Ma) stages. Our composite record from outcrops in Spain and Italy reveals that tropical SSTs varied between 22 and 32 °C over a ~ 3 Myr time period, including transient temperature excursions of 5–10 °C magnitude with lapse rates of ~0.1 °C/kyr. Changes in reconstructed SSTs covaried with sea level fluctuations and δ18O isotope signatures of marine biocalcifiers, recording recurrent shifts between icehouse and greenhouse states. Parallel trends of reconstructed SST and δ13C isotopes of atmospheric CO 2 may reflect storage of isotopically light carbon in cryosphere reservoirs during icehouse phases and release during greenhouse phases. The existence of a labile cryosphere is considered a prerequisite to explain the inferred rapid climate fluctuations and as a reservoir to facilitate pronounced carbon isotope excursions. • First Toarcian SST record based on molecular paleothermometry. • Highly variable SSTs attest to contrasting climate modes. • Direct coupling between SST, oxygen isotopes and sea level evolution. • Perception of an overall warm early Jurassic Greenhouse world should be discarded. [ABSTRACT FROM AUTHOR]

Reliable reanalysis products can be exploited to drive mesoscale numerical models and generate highresolution reconstructions of high-impact weather events. Within this framework, regional weather and climate models may greatly benefit from the recent release of the ERA5 product, an improvement to the ERA-Interim dataset. In this study, two different convection-permitting models driven by these two reanalysis datasets are used to reproduce three heavy precipitation events affecting a Mediterranean region. Moreover, different sea surface temperature (SST) initializations are tested to assess how higher-resolution SST fields improve the simulation of high-impact events characterized by strong air-sea interactions. Finally, the coupling with a distributed hydrological model allows evaluating the impact at the ground, specifically assessing the possible added value of the ERA5 dataset for the high-resolution simulation of extreme hydrometeorological events over the Calabria region (southern Italy). Results, based on the comparison against multiple-source precipitation observations, show no clear systematic benefit to using the ERA5 dataset; moreover, intense convective activity can introduce uncertainties masking the signal provided by the boundary conditions of the different reanalyses. The effect of the high-resolution SST fields is even more difficult to detect. The uncertainties propagate and amplify along the modeling chain, where the spatial resolution increases up to the hydrological model. Nevertheless, even in very small catchments, some of the experiments provide reasonably accurate results, suggesting that an ensemble approach could be suitable to cope with uncertainties affecting the overall meteo-hydrological chain, especially for small catchments. [ABSTRACT FROM AUTHOR]

Increasingly variable hydrologic regimes combined with more frequent and intense extreme events are challenging water systems management worldwide. These trends emphasize the need of accurate medium‐ to long‐term predictions to timely prompt anticipatory operations. Despite in some locations global climate oscillations and particularly the El Niño Southern Oscillation (ENSO) may contribute to extending forecast lead times, in other regions there is no consensus on how ENSO can be detected, and used as local conditions are also influenced by other concurrent climate signals. In this work, we introduce the Climate State Intelligence framework to capture the state of multiple global climate signals via artificial intelligence and improve seasonal forecasts. These forecasts are used as additional inputs for informing water system operations and their value is quantified as the corresponding gain in system performance. We apply the framework to the Lake Como basin, a regulated lake in northern Italy mainly operated for flood control and irrigation supply. Numerical results show the existence of notable teleconnection patterns dependent on both ENSO and the North Atlantic Oscillation over the Alpine region, which contribute in generating skilful seasonal precipitation and hydrologic forecasts. The use of this information for conditioning the lake operations produces an average 44% improvement in system performance with respect to a baseline solution not informed by any forecast, with this gain that further increases during extreme drought episodes. Our results also suggest that observed preseason sea surface temperature anomalies appear more valuable than hydrologic‐based seasonal forecasts, producing an average 59% improvement in system performance. Key Points: We introduce the Climate State Intelligence framework to capture the state of multiple climate signals and improve seasonal forecastStrong influence of divergent SST patterns dependent on ENSO and NAO phases is detected over the Alpine regionPreseason SST anomalies appear more valuable than hydrologic‐based seasonal forecasts for informing reservoir operations [ABSTRACT FROM AUTHOR]

Changes over the twentieth century in seasonal mean potential predictability (PP) of global precipitation, 200 hPa height and land surface temperature are examined by using 100-member ensemble. The ensemble simulations have been conducted by using an intermediate complexity atmospheric general circulation model of the International Center for Theoretical Physics, Italy. Using the Hadley Centre sea surface temperature (SST) dataset on a 1° grid, two 31 year periods of 1920-1950 and 1970-2000 are separated to distinguish the periods of low and high SST variability, respectively. The standard deviation values averaged for the ('Niño-3.4'; 5°S-5°N, 170°W-120°W) region are 0.71 and 1.15 °C, for the periods of low and high SST variability, respectively, with a percentage change of 62 % during December-January-February (DJF). The leading eigenvector and the associated principal component time series, also indicate that the amplitude of SST variations have positive trend since 1920s to recent years, particularly over the El Niño Southern Oscillation (ENSO) region. Our hypothesis states that the increase in SST variability has increased the PP for precipitation, 200 hPa height and land surface temperature during the DJF. The analysis of signal and noise shows that the signal-to-noise (S/N) ratio is much increased over most of the globe, particularly over the tropics and subtropics for DJF precipitation. This occurs because of a larger increase in the signal and at the same time a reduction in the noise, over most of the tropical areas. For 200 hPa height, the S/N ratio over the Pacific North American (PNA) region is increasing more than that for the other extratropical regions, because of a larger percentage increase in the signal and only a small increase in noise. It is also found that the increase in seasonal mean transient signal over the PNA region is 50 %, while increase in the noise is only 12 %, during the high SST variability period, which indicates that the increase in signal is more than the noise. For DJF land surface temperature, the perfect model notion is utilized to confirm the changes in PP during the low and high SST variability periods. The correlation between the perfect model and the other members clearly reveal that the seasonal mean PP changed. In particular, the PP for the 31 years period of 1970-2000 is higher than that for the 31 years period of 1920-1950. The land surface temperature PP is increased in northern and southern Africa, central Europe, southern South America, eastern United States and over Canada. The increase of the signal and hence the seasonal mean PP is coincides with an increase in tropical Pacific SST variability, particularly in the ENSO region. [ABSTRACT FROM AUTHOR]

About 6,300,000 pressure head waves beneath the sea surface were recorded by an array of 26 transducers aligned orthogonally to the coastline of Reggio Calabria, Italy. The data set covered spectra from very narrow unimodal to very broad multimodal and waves from shallow to deep waters. Herein, the quasi-determinism (QD) theory is proven to be very effective in predicting the probability of large-wave heights as well as the period and particle acceleration of these waves both on deep and shallow waters. In addition, the Tayfun model for predicting the probability of large-wave heights is also proven to be highly effective. [ABSTRACT FROM AUTHOR]

Recent recurring episodes of heavy flash flood producing rainfall events on the Veneto coastal area have renewed the interest in documenting the frequency and key dynamical ingredients of such events. A climatological analysis of the precipitation in Veneto reveals that, in comparison with the rest of the region, the coastal area is characterized by fewer rain days, lower rainfall accumulations, yet more days with heavy precipitation. If set in relation to the yearly rainfall, daily accumulation can reach values as high as 40% of the yearly total rainfall, more regularly between 15% and 30 %, often in periods of 12 h or less. Four such heavy rainfall events were analyzed and synthetically described to highlight key ingredients which appear instrumental in producing the high rainfall accumulations. These comprise an upper-level trough elongating or cutting off into the Western Mediterranean basin after a period of one to two weeks of anticyclonic fair weather conditions with temperatures above normal. The moisture supply over the Adriatic onto north-eastern Italy is favoured by above normal sea surface temperatures, enhanced advection by a surface low in the Gulf of Genoa, and in three of the four cases, an additional surface low over southern Italy. The air flows associated with the upper-level trough for the cases discussed were of moderate to weak intensity, and convectively conditionally unstable. The flow intensity was such that the lower tropospheric portion was blocked by and forced to flow around the Alpine barrier, i.e. manifesting as a north-easterly, low-level flow over much of the north-eastern Italian plains. This blocked flow seemed to interact with the larger-scale synoptic flow to form a distinct and persistent low-level convergence in the area of the Veneto coast. It is suggested that these low-level convergence patterns are key in releasing the convective instability present in the larger-scale flow just on the Veneto coastal area. Hereby, it is the synoptic rather than the convective setting which dictated the observed timescales of intense rainfall. Therefore, the convective rainfall rates paired with the synoptic durations combine to produce the exceptionally high rainfall accumulations observed. Cases like these are significant contributors to forming the coastal precipitation climatology, which for this area is found to be distinctly different than for the rest of the region in terms of precipitation concentration. [ABSTRACT FROM AUTHOR]

Agricultural activity replaces natural vegetation with cultivated land and it is a major cause of local and global climate change. Highly specialized agricultural production leads to extensive monoculture farming with a low biodiversity that may cause low landscape resilience. This is the case on the Salento peninsula, in the Apulia Region of Italy, where the Xylella fastidiosa bacterium has caused the mass destruction of olive trees, many of them in monumental groves. The historical land cover that characterized the landscape is currently in a transition phase and can strongly affect climate conditions. This study aims to analyze how the destruction of olive groves by X. fastidiosa affects local climate change. Land surface temperature (LST) data detected by Landsat 8 and MODIS satellites are used as a proxies for microclimate mitigation ecosystem services linked to the evolution of the land cover. Moreover, recurrence quantification analysis was applied to the study of LST evolution. The results showed that olive groves are the least capable forest type for mitigating LST, but they are more capable than farmland, above all in the summer when the air temperature is the highest. The differences in the average LST from 2014 to 2020 between olive groves and farmland ranges from 2.8 °C to 0.8 °C. Furthermore, the recurrence analysis showed that X. fastidiosa was rapidly changing the LST of the olive groves into values to those of farmland, with a difference in LST reduced to less than a third from the time when the bacterium was identified in Apulia six years ago. The change generated by X. fastidiosa started in 2009 and showed more or less constant behavior after 2010 without substantial variation; therefore, this can serve as the index of a static situation, which can indicate non-recovery or non-transformation of the dying olive groves. Failure to restore the initial environmental conditions can be connected with the slow progress of the uprooting and replacing infected plants, probably due to attempts to save the historic aspect of the landscape by looking for solutions that avoid uprooting the diseased plants. This suggests that social-ecological systems have to be more responsive to phytosanitary epidemics and adapt to ecological processes, which cannot always be easily controlled, to produce more resilient landscapes and avoid unwanted transformations. [ABSTRACT FROM AUTHOR]

The article discusses the mortality events that affected the population of Paramuricea clavata in the Gulf of La Spezia in Italy. It is said that the population was monitored for three years after the mortality events, in which comparison of population density and population size structure is derived. It is cited that P. clavata's bathymetric distribution ranges the summer thermocline, which makes the population sensitive to an increase in temperature. Substantial larval supply is prevented due to lack of deeper colonies.

A 1-yr-long series of Advanced Very High Resolution Radiometer sea surface temperature (SST) images is used to study the SST distribution in 1992 over the Channel of Sicily. Time- and spatial scales of the SST are studied by estimating the SST autocorrelation function directly from satellite images. SST timescales vary from 1 week to 45 days, with lower values in areas of intense upwelling. Spatial scales of the SST show seasonal variations with values from 80 to 300 km, with higher values during the summer. Oscillations with periods from 11 to 35 days modulate the annual variability of the SST spatial scales. The first four internal radii of deformation are estimated on the basis of climatological density profiles. The first internal radius varies from 7 km during the winter to 14 km during the summer. It is shown that, although differences between horizontal scales of the SST and internal radii of deformation exist, the annual variability of the SST spatial scales can be interpreted in terms of seasonal variations of the first Rossby radius of deformation. [ABSTRACT FROM AUTHOR]