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Tumours are nowadays the second world‑leading cause of death after cardiovascular diseases. During the last decades of cancer research, lifestyle and random/genetic factors have been blamed for cancer mortality, with obesity, sedentary habits, alcoholism, and smoking contributing as supposed major causes. However, there is an emerging consensus that environmental pollution should be considered one of the main triggers. Unfortunately, all this preliminary scientific evidence has not always been followed by governments and institutions, which still fail to pursue research on cancer's environmental connections. In this unprecedented national-scale detailed study, we analyzed the links between cancer mortality, socio-economic factors, and sources of environmental pollution in Italy, both at wider regional and finer provincial scales, with an artificial intelligence approach. Overall, we found that cancer mortality does not have a random or spatial distribution and exceeds the national average mainly when environmental pollution is also higher, despite healthier lifestyle habits. Our machine learning analysis of 35 environmental sources of pollution showed that air quality ranks first for importance concerning the average cancer mortality rate, followed by sites to be reclaimed, urban areas, and motor vehicle density. Moreover, other environmental sources of pollution proved to be relevant for the mortality of some specific cancer types. Given these alarming results, we call for a rearrangement of the priority of cancer research and care that sees the reduction and prevention of environmental contamination as a priority action to put in place in the tough struggle against cancer., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

In Italy, approximately 400.000 new cases of malignant tumors are recorded every year. The average of annual deaths caused by tumors, according to the Italian Cancer Registers, is about 3.5 deaths and about 2.5 per 1,000 men and women respectively, for a total of about 3 deaths every 1,000 people. Long-term (at least a decade) and spatially detailed data (up to the municipality scale) are neither easily accessible nor fully available for public consultation by the citizens, scientists, research groups, and associations. Therefore, here we present a ten-year (2009-2018) database on cancer mortality rates (in the form of Standardized Mortality Ratios, SMR) for 23 cancer macro-types in Italy on municipal, provincial, and regional scales. We aim to make easily accessible a comprehensive, ready-to-use, and openly accessible source of data on the most updated status of cancer mortality in Italy for local and national stakeholders, researchers, and policymakers and to provide researchers with ready-to-use data to perform specific studies., (© 2022. The Author(s).)

The calibration of a reliable phenological model for olive grown in areas characterized by great environmental heterogeneity, like Italy, where many varieties exist, is challenging and often suffers from a lack of observations, especially on budbreak. In this study, we used a database encompassing many phenological events from different olive varieties, years, and sites scattered all over Italy to identify the phases in which site-enlarged developmental rates can be well regressed against air temperature (Developmental Rate function, DR ) by testing both linear and nonlinear functions. A K-fold cross-validation (KfCV) was carried out to evaluate the ability of DR functions to predict phenological development. The cross-validation showed that the phases ranging from budbreak (BBCH 01 and 07) to flowering (BBCH 61 and 65) and from the beginning of flowering (BBCH 51) to flowering can be simulated with high accuracy ( r 2 = 0.93-0.96; RMSE = 3.9-6.6 days) with no appreciable difference among linear and nonlinear functions. Thus, the resulting DRs represent a simple yet reliable tool for regional phenological simulations for these phases in Italy, paving the way for a reverse modeling approach aimed at reconstructing the budbreak dates. By contrast, and despite a large number of phases explored, no appreciable results were obtained on other phases, suggesting possible interplays of different drivers that need to be further investigated., Competing Interests: The authors declare no conflict of interest.

Background: A likely increasing demand for varieties mixtures, landraces and genetic diversity in cropping systems will underpin calls for models able to generalize phenological development at the species level, at the same time as providing the expected range of phenological variability. In the present article, we aimed to obtain a generalized phenological model of durum wheat (Triticum durum, Desf.)., Results: Using a large phenological dataset embracing field data collected under different sowing dates, varieties and locations over the Italian peninsula, we searched for the phenophases enabling the best linear approximations between developmental rates and air temperature, aiming to minimize the residual variability from drivers other than temperature, as genetic and environmental diversity. The developmental rates of the resulting phases were then examined with respect to the mean daylength to determine possible additional relations with photoperiod. If a correlation with daylength was also present, the developmental rate is calibrated by multiple linear regression, or otherwise by simple linear regression of temperature. The resulting calibration, tested on an independent data subset, confirms that the model is able to generalize wheat development over the Italian peninsula with high accuracy (mean absolute error =3-8 days; r 2  = 0.75-0.98), regardless of the wheat variety., Conclusion: The generalized phenological model is potentially suitable for many agro-ecological and large-scale applications. It is hoped that the model will aid in situations where phenological observations to parameterize a model are still lacking, as is probably the case for landraces and underutilized crop varieties. © 2019 Society of Chemical Industry., (© 2019 Society of Chemical Industry.)

In a previous work we developed a mathematical model to explain the co-occurrence of evergreen and deciduous oak groups in the Mediterranean region, regarded as one of the distinctive features of Mediterranean biodiversity. The mathematical analysis showed that a stabilizing mechanism resulting from niche difference (i.e. different water use and water stress tolerance) between groups allows their coexistence at intermediate values of suitable soil water content. A simple formal derivation of the model expresses this hypothesis in a testable form linked uniquely to the actual evapotranspiration of forests community. In the present work we ascertain whether this simplified conclusion possesses some degree of explanatory power by comparing available data on oaks distributions and remotely sensed evapotranspiration (MODIS product) in a large-scale survey embracing the western Mediterranean area. Our findings confirmed the basic assumptions of model addressed on large scale, but also revealed asymmetric responses to water use and water stress tolerance between evergreen and deciduous oaks that should be taken into account to increase the understating of species interactions and, ultimately, improve the modeling capacity to explain co-occurrence.

The scientific community offers numerous crop models with different levels of sophistication. In such a wide range of crop models, users should have the possibility to choose the most suitable, in terms of detail, scale and representativeness, to their objectives. However, even when an appropriate choice is made, model limitations should be clarified such that modelling studies are put in the proper perspective and robust applications are achieved. This work is an overview of available models to simulate crop growth and yield. A summary matrix with more than 70 crop models is provided, storing the main model characteristics that can help users to choose the proper tool according to their purposes. Overall, we found that two main aspects of models, despite their importance, are not always clear from the published references, i.e. the versatility of the models, in terms of reliable transferability to different conditions, and the degree of complexity. Hence, the developers of models should be encouraged to pay more attention to clarifying the model limitations and limits of applicability, and users should make an effort in proper model selection, to save time often devoted to iteration of tuning steps to force an inappropriate model to be adapted to their own purpose., (© 2015 Society of Chemical Industry.)

The Mediterranean region is one of the hot spots of climate change. This study aims at understanding what are the conditions sustaining tree diversity in Mediterranean wet forests under future scenarios of altered hydrological regimes. The core of the work is a quantitative, dynamic model describing the coexistence of different Mediterranean tree species, typical of arid or semi-arid wetlands. Two kind of species, i.e. Hygrophilous (drought sensitive, flood resistant) and Non-hygrophilous (drought resistant, flood sensitive), are broadly defined according to the distinct adaptive strategies of trees against water stress of summer drought and winter flooding. We argue that at intermediate levels of water supply the dual role of water (resource and stress) results in the coexistence of the two kind of species. A bifurcation analysis allows us to assess the effects of climate change on the coexistence of the two species in order to highlight the impacts of predicted climate scenarios on tree diversity. Specifically, the model has been applied to Mediterranean coastal swamp forests of Central Italy located at Castelporziano Estate and Circeo National Park. Our results show that there are distinct rainfall thresholds beyond which stable coexistence becomes impossible. Regional climatic projections show that the lower rainfall threshold may be approached or crossed during the XXI century, calling for an urgent adaptation and mitigation response to prevent biodiversity losses.