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Aim of study: We introduce the software ModERFoRest (Modelling Environmental Requirements for Forest Restoration), which is a tool to estimate the environmental requirements and environmental performance of the main forest tree species growing in Spain. Area of study: Two of their modules have been developed to be applied mainly in Spain, but the main section can be used elsewhere as long as the user provides with presence data and environmental information. Materials and methods: ModERFoRest has been programmed in C++, also using the Armadillo library for algebraic computation. The application can be downloaded from the INIA website (https://www.inia.es/serviciosyrecursos/recursosinformaticos/modernforest/Paginas/ModERFoRest.aspx) where there are also more accessible resources (currently only in Spanish language). Main results: ModERFoRest provides three basic utilities, firstly, to select the optimal species to be used for forest restoration, at local or regional scale, among the 22 most important taxa or formations in Spain, based on ecological criteria and physiographic, climatic and edaphic information. Secondly, to explore the potential distribution areas of the species using the ecological niche models and algorithms developed throughout different projects on the autecology of the species over the last 55 years. Finally, the application provides the option of comparing different areas of the species ecologically, in order to obtain the most suitable reproductive material for the forest site under study. Research highlights: Users can also run not only recent but also future climate scenarios in order to simulate the distribution of ecological species and use the results in reforestation programmes and planning.

La capa orgánica del suelo desempeña un papel fundamental en el ciclo de los nutrientes y en la protección del suelo, además de actuar como un almacén de carbono que no debe ser ignorado. Por ello se requieren estimaciones precisas tanto de las reservas de carbono como de su distribución espacial. Con este objetivo, se han recopilado diferentes bases de datos existentes y se ha realizado un muestreo complementario para obtener una base de datos de más de 1900 puntos de muestreo en masas forestales arboladas. Para la obtención de las estimaciones, se ha realizado un proceso de modelización utilizando “Random Forest”, probándose diferentes variables ambientales que pudieran tener importancia en la predicción (climáticas, topográficas, selvícolas y de composición específica), seleccionando finalmente aquellas más relevantes para ser incluidas en el mismo. Para obtener estimaciones robustas, el proceso de ajuste se llevó a cabo aplicando diversas iteraciones, utilizando una parte de los datos para ajuste y otra para validación, y variando aleatoriamente dichos conjuntos de datos en cada una de ellas. Con los resultados del modelo en cada iteración se realizó una estimación conjunta aplicada a los datos del Mapa Forestal de España. El resultado final ha sido la obtención del mapa de carbono acumulado en el horizonte orgánico en las masas forestales arboladas de la Península Ibérica y de las Islas Baleares. Se ha estimado que las reservas de carbono acumuladas en la capa orgánica son de 0,148 Pg C (0,381 Pg peso de biomasa seca).

Introduction: Patients with thoracic malignancies are at increased risk for mortality from coronavirus disease 2019 (COVID-19), and a large number of intertwined prognostic variables have been identified so far. Methods: Capitalizing data from the Thoracic Cancers International COVID-19 Collaboration (TERAVOLT) registry, a global study created with the aim of describing the impact of COVID-19 in patients with thoracic malignancies, we used a clustering approach, a fast-backward step-down selection procedure, and a tree-based model to screen and optimize a broad panel of demographics and clinical COVID-19 and cancer characteristics. Results: As of April 15, 2021, a total of 1491 consecutive eligible patients from 18 countries were included in the analysis. With a mean observation period of 42 days, 361 events were reported with an all-cause case fatality rate of 24.2%. The clustering procedure screened 73 covariates in 13 clusters. A further multivariable logistic regression for the association between clusters and death was performed, resulting in five clusters significantly associated with the outcome. The fast-backward step-down selection procedure then identified the following seven major determinants of death: Eastern Cooperative Oncology Group—performance status (ECOG-PS) (OR = 2.47, 1.87–3.26), neutrophil count (OR = 2.46, 1.76–3.44), serum procalcitonin (OR = 2.37, 1.64–3.43), development of pneumonia (OR = 1.95, 1.48–2.58), C-reactive protein (OR = 1.90, 1.43–2.51), tumor stage at COVID-19 diagnosis (OR = 1.97, 1.46–2.66), and age (OR = 1.71, 1.29–2.26). The receiver operating characteristic analysis for death of the selected model confirmed its diagnostic ability (area under the receiver operating curve = 0.78, 95% confidence interval: 0.75–0.81). The nomogram was able to classify the COVID-19 mortality in an interval ranging from 8% to 90%, and the tree-based model recognized ECOG-PS, neutrophil count, and c-reactive protein as the major determinants of

ModERFoRest es el acrónimo de Modelling Environmental Requirements for Forest Restoration (Modelización de los requerimientos ambientales para la restauración forestal), ya que es una aplicación especialmente diseñada para la elección de especie y el origen del material forestal de reproducción idóneos en tareas de restauración de la vegetación. Sin embargo, la actual versión ya disponible de la aplicación facilita, además, otra serie de funcionalidades como son: i) la modelización de la distribución de especies, con dos algoritmos diferentes, a partir de datos exclusivamente de presencias; ii) el cálculo masivo de hasta 38 variables climáticas a partir de datos de precipitación y temperaturas mensuales; y iii) la síntesis de hasta 23 variables edáficas a escala perfil derivados de los datos brutos de laboratorio por horizontes, incluyendo la generación de fichas hídricas. La aplicación se distribuye de manera gratuita y recoge toda la información sobre autoecología de 22 taxones arbóreos de relevancia en España, así como de los rodales semilleros selectos cuya caracterización ecológica completa está disponible hasta la fecha. ModERFoRest constituye una herramienta de fácil manejo, versátil, de uso libre y en continuo desarrollo que puede ser de utilidad tanto a gestores como investigadores del ámbito de la restauración de la vegetación.

Cones of the Mediterranean stone pine (Pinus pinea L.) constitute one of the most relevant non-wood forest products collected in the Mediterranean forests, providing high value edible kernels. In the last years it has been observed a severe decline in the kernel-per-cone yield (kg of kernels obtained from a kg of fresh cones) through the whole area of the species. This decline has been associated with both ongoing climate change and the recent expansion over the Mediterranean Basin of the Western Conifer Seed Bug, Leptoglossus occi-dentalis Heideman, an exotic pest which predates seeds of conifer species. In the present work we aimed to confirm and quantify the impact of this recent decline on pine nut and kernel production, identify the main factors provoking this reduction, and give evidence over causality by a potential biotic agent. We analysed recent and historical series of pine nut and kernel production obtained in the four main regions where Pinus pinea occurs in Spain. Our results showed a significant drop in the final kernel-per-cone yield on three of the four regions analysed, reaching reductions over 50% in the most affected areas. We observed that this reduction is mainly associated with a significant and generalised drop in the kernel-per-nut yield (kg of kernels per kg of pine nuts in shell), triggered by an increment in the rate of damaged pine nuts and, to a lesser extent, a reduction in the number of pine nuts per cone. The prevalence of this reduction on kernel-per-cone yield over different years and provenances with contrasting climate reinforces the hypothesis of the implica-tion of a biotic factor which can be aggravated on extreme drought years.