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The European Mediterranean Basin (Euro-Med), a region particularly vulnerable to global warming, notably lacks research aimed at assessing and enhancing the widely used remote climate detection products known as General Circulation Models (GCMs). In this study, the proficiency of GCMs in replicating reanalyzed 1981–2010 temperature data sourced from the ERA5 Land was assessed. Initially, the least data-modifying interpolation method for achieving a resolution match of 0.1° was ascertained. Subsequently, a pixel-by-pixel evaluation was conducted, employing five goodness-of-fit metrics. From these metrics, we compiled a Comprehensive Rating Index (CRI). A Multi-Model Ensemble using Random Forest was constructed and projected across three emission scenarios (SSP1-RCP2.6, SSP2-RCP4.5, and SSP5-RCP8.5) and timeframes (2026–2050, 2051–2075, and 2076–2100). Empirical Bayesian Kriging, selected for its minimal data alteration, supersedes the commonly employed Bilinear Interpolation. The evaluation results underscore MPI-ESM1-2-HR, GFDL-ESM4, CNRM-CM6-1, MRI-ESM2-0, CNRM-ESM2-1, and IPSL-CM6A-LR as top-performing models. Noteworthy geospatial disparities in model performance were observed. The projection outcomes, notably divergent from IPCC forecasts, revealed a warming trend of 1 to over 2 °C less than anticipated for spring and winter over the medium–long term, juxtaposed with heightened warming in mountainous/elevated regions. These findings could substantially refine temperature projections for the Euro-Med, facilitating the implementation of policy strategies to mitigate the effects of global warming in vulnerable regions worldwide. [ABSTRACT FROM AUTHOR]

Aims : The task of classifying and naming Mexican vegetation types has been undertaken by previous botanists, ecologists, and mapping agencies. However, discrepancies remain due to the lack of criteria and joint efforts from a geographical and botanical perspective. We aim to unravel the complex interactions between climate and vegetation in Mexico using climatic data and advanced mapping techniques, display in maps the transition from land cover to vegetation maps and couple geobotanical and bioclimatological approaches to provide a sound, unified system for identifying Mexican bioclimatic physiognomic patterns. Methods : Bioclimatic mapping was developed from the Digital Climatic Atlas of Mexico data source. In addition, land cover and vegetation data were obtained from the National Institute of Statistics and Geography of Mexico regrouped as described by the Standardized Hierarchical Vegetation Classification. These data were analysed via standard map crossing technics using geographic information systems. Results and conclusions : The results revealed five ombrotypes and five thermotypes, leading to the identification of 13 different bioclimatic classes, which, when combined with physiognomic types, led us to recognize 11 forests, 3 shrublands and 3 herbaceous formations (at a scale of 1:4,000,000). The core outcome is a detailed bioclimatic/physiognomic vegetation map including forests, shrublands and areas dominated by Herbaceous/Non-Vascular formations. The map highlights the critical importance of harmonising methodologies to ensure comprehensive and accurate insights into Mexico's bioclimatic diversity. Taxonomic reference : Villaseñor et al. (2005). Syntaxonomic reference : Velázquez et al. (2021). Abbreviations : INEGI = Instituto Nacional de Estadística y Geografía; SECLAVEMEX = Standardized Hierarchical Vegetation Classification; WBCS = Worldwide Bioclimatic Classification System. [ABSTRACT FROM AUTHOR]

This study identifies and analyzes the plant communities that allow the definition of the geographic limits between Temperate and Mediterranean macrobioclimates, for the center of Portuguese mainland. The altitude of Serra da Estrela, Açor and Lousã, combined with the increase in atmospheric humidity, allows the presence of vegetation typical of a Temperate macrobioclimate. Thus, based on the phytosociological methodology, floristic relevés were carried out in order to identify the series of vegetation existing in these territories. Through these relevés carried out, four new plant associations were identified: Cytisetum grandifloro-striati ass. nova, Scrophulario grandiflorae-Sambucetum nigrae ass. nova, Pruno lusitanicae-Coryletum avellanae ass. nova that lives in the submediterranean bioclimatic variant, mesotemperate humid to hyper-humid. A new association namely Genisto falcatae-Quercetum broteroanae ass. nova with two subassociations were also identified. Based on the vegetation distribution, new biogeographic limits are proposed. Thus, it was intended to identify the southern limits of the European Atlantic Province (Atlantic Orolusitania Subrovince) based on the vegetation cover, namely the distinction between the Estrela Sierran District and a new Biogeographical District, the Alvo-Gardunhense. [ABSTRACT FROM AUTHOR]

Rising temperatures and changes in precipitation patterns under climate change scenarios are accelerating the depletion of soil moisture and increasing the risk of drought, disrupting the conditions that many plant species need to survive. This study aims to establish the bioclimatic characterisation, both qualitative and quantitative, of ten native Californian Pinales for the period 1980–2019, and to determine their habitat suitability by 2050. To achieve this, an exhaustive search of the Gbif database for records of ten conifer taxa was carried out. To conduct the bioclimatic characterisation of the studied taxa, we worked with the monthly values of average temperature and precipitation for the period 1980–2019 from 177 meteorological stations. Linear regressions was performed in order to compile the future evolution of California's climate. Suitable areas and optimal areas were defined at the present time (1980–2019) and its future projection (2050). We applied Boolean logic and, in this investigation, the Conditional Logic Operator (CON) was used to determine the possible species presence (one) or absence (zero) for each of the 15 variables analysed. In general, most of the conifers studied here will experience a reduction in their habitat range in California by the year 2050 due to climate change, as well as the displacement of species towards optimal areas. Furthermore, the results have highlighted the applicability of bioclimatology to future conditions under climate change. This will aid conservation managers in implementing strategic measures to ameliorate the detrimental impacts of climate change, thereby ensuring the ecological integrity and sustainability of the affected conifer species. [ABSTRACT FROM AUTHOR]

A phytosociological analysis of the Iberian Quercus faginea forests was carried out. For this purpose, 291 relevés were studied. A multivariate analysis consisting of a numerical classification based on the floristic composition of the relevés, was performed. The coherence and explanatory value of the current syntaxa are reviewed. As a result, the diversity of Iberian gall oak forests is resolved into 15 associations characterised according to their floristic, biogeographical, bioclimatic and synecological data supported by the statistical analyses. Thirteen have been described previously, and two new associations are proposed: Glandoro diffusae-Quercetum fagineae and Helianthemo mollis-Quercetum fagineae. A new combination, a lectotypification and a nomenclatural correction are also proposed. The Ios2 (ombrothermic index of the warmest bimonth of the summer quarter), Itc (compensated thermicity index) and Ic (continentality index) indexes proved to be fundamental to explain the syntaxonomic differentiation of the forests in the study. We consider that the differentiation and precision in the definition of clear syntaxonomic entities is vital to prioritize objectives in the conservation of these singular forests, and to ensure their adequate management in the context of the Habitats Directive. [ABSTRACT FROM AUTHOR]

The relict communities of Prunus lusitanica are globally threatened, mainly by climatic and anthropic factors. Solid knowledge about floristic composition and serial dynamics provides a valuable basis for the implementation of management and conservation measures. This article focuses on peculiar communities that occur in hydric-compensated areas of the Iberian Peninsula and south of France, a submediterranean ecotonal area. A hierarchical cluster analysis allowed to identify two new syntaxa. For the first time an association of Prunus lusitanica, Lonicero periclymeni-Prunetum lusitanicae ass. nova, is reported for France, representing the mature stage of a minoriseries of vegetation, attributed to Lonicerion periclymeni. The discovery of populations of P. lusitanica in valleys embedded in the Municipality of Mação (Portugal), represent the new association Smilaco asperae-Prunetum lusitanicae ass. nova, enriched by thermophilous taxa. This relict association occurs in the South Beira District and corresponds to the southern limit of the natural distribution area in mainland Portugal, integrated in the suballiance Fraxino angustifoliae-Ulmenion minoris. Additional notes on the occurrence of P. lusitanica in other areas of the Iberian Peninsula are provided. [ABSTRACT FROM AUTHOR]

The global mean surface temperature has risen since the late 19th century. However, temperatures do not increase uniformly in space or time and few studies have focused on that peculiarity in the State of California. The aim of this research is to deepen our knowledge of the evolution of mean temperatures in the State of California on monthly, seasonal and annual time scales. The period under study comprises 40 years (from 1980 to 2019) and data from 170 meteorological stations were analysed. Statistical techniques, including Sen's slope and Mann-Kendall, were applied to each of the stations to establish the sign and slopes of trends and their statistical significance. The spatial distribution of monthly, seasonal and annual trends was analysed using the Empirical Bayesian Kriging (EBK) geostatistical technique. The trend analysis was also carried out for the State as a whole. This research also studies the relationships between mean temperatures and nine teleconnection patterns with influence on the Californian climate. To find out these links, a correlation analysis was performed using the partial non-parametric Spearman Test at a 95% confidence level. The study reveals a positive trend of +0.01 °C year−1 for the whole state and that Southern California is getting warmer than Northern California for the study period. On a seasonal scale, the local temperature increased significantly both in autumn and summer (+0.06 °C and +0.035 °C year−1 respectively) from 1980 to 2019. On a monthly scale, the largest increases are found in November at +0.04 °C year−1. Temperatures in February, March, April and May are highly correlated with most of the teleconnection patterns studied in the State of California. West Pacific Oscillation (WPO) teleconnection pattern has shown the highest negative correlation. However, The Pacific Decadal Oscillation (PDO) has a positive correlation with mean temperatures in coastal areas such as Los Angeles, San Francisco and Monterey. Moreover, Antarctic Oscillation (AAO) and Arctic Oscillation patterns (AO) are unlikely to show great influence on average temperature trends in California. [ABSTRACT FROM AUTHOR]

This work aims to review the natural communities of Pinus halepensis in Spain. The methodology consisted of subjecting 400 phytosociological relevés to georeferencing and statistical, biogeographical, and bioclimatic treatment. We analyse the communities of Pinus halepensis on the Iberian Peninsula and Balearic Islands. Five syntaxa with association rank are described in several works and included in the alliances Rhamno-Quercion and Oleo-Ceratonion. Ephedro-Pinetum halepensis was initially proposed as a community by Torres et al. and subsequently raised to the rank of association by Rivas-Martínez et al. In this work, we have separated the plant communities dominated by Pinus halepensis, which was previously included in other syntaxa, and as a result, we propose four new associations and a new alliance for the Iberian Peninsula: ass. Bupleuro rigidi-Pinetum halepensis; ass. Ephedro nebrodensis-Pinetum halepensis; ass. Rhamno angustifoliae-Pinetum halepènsis; ass. Rhamno laderoi-Pinetum halepensis; all. Rhamno lycioidis-Pinion halepensis. In view of the fact that some of the communities have been published as edaphoxerophilous and climatophilous, we suggest separating the climatophilous from the edaphoxerophilous character in the diagnosis of the communities, and have therefore recently proposed the ombroedaphoxeric index Ioex (Ioex = Pp − e/Tp × CR), which considers positive precipitation Pp, positive temperature Tp, residual evapotranspiration (e), and water retention capacity CR (0.25, 0.50, 0.75). In conclusion, we propose the associations mentioned above, which will allow the implementation of a reforestation treatment in accordance with the natural environment. [ABSTRACT FROM AUTHOR]

This study proposes a bioclimatic characterization and a new biogeographic division for the Antarctic territories up to the province level following the criteria and models of Rivas-Martínez et al. The Antarctic Kingdom comprises the continent of Antarctica, the surrounding ice-covered Antarctic islands, and the associated cold oceanic islands and archipelagos. It has two biogeographic regions: the Antarctic Region and the Subantarctic Insular Region. The Antarctic Region includes the entire pergelid Antarctic continent and the surrounding islands and archipelagos, and is characterized by upper suprapolar hyperoceanic and oceanic or Polar pergelid bioclimates on the coasts. The region has been divided into three pr6ovinces: Maritime Antarctica, West Antarctica and East Antarctica. The Subantarctic Insular Region comprises the circumantarctic islands and archipelagos that are widespread at the southern tip of the planet's most important oceans, mostly in the subtemperate latitudinal zone inside or not far from the Antarctic Convergence. Bioclimatically, all insular subantarctic territories (excluding the South-American Tierra de Fuego, Terra Magellanica and large islands) are characterized by thermo-suprapolar and semipolar antarctic hyperoceanic bioclimates on the coasts. Four provinces – Falklandian-South Georgian, Kerguelenian, Macquarian and Aucklandian-Campbellian – have been recognized in this region. All these units are characterized by floristic bioindicators. [ABSTRACT FROM AUTHOR]

Fagus sylvatica forests are considered to be of Community interest according to Directive 92/43/EEC. Climate change predictions for Spain point to a warming scenario, coupled with decreasing rainfall, which may have an impact on their future distribution particularly at the extremes of its distribution area. Species distribution models incorporating bioclimatic, topographic and phytogeographic variables were used as predictors to assess their habitat suitability under current conditions and a climate change projection. Ten single models were generated and an ensemble-forecasting model was subsequently built by computing a consensus of single-model projections. The results revealed that ombrothermic indices are the main factors controlling the distribution of Spanish beech forests. They are highly vulnerable to climate change and could suffer a decline in their habitat suitability if climate trends observed are maintained in the future. The least favoured areas for them will be located close to the limit between the Temperate and Mediterranean climates, where they could suffer a loss of habitat suitability. Conversely, suitable new areas could be found mainly in western areas of the Cantabrian Range and in the Central Pyrenees. [ABSTRACT FROM AUTHOR]

Orthology detection requires more effective scaling algorithms. In this paper, a set of gene pair features based on similarity measures (alignment scores, sequence length, gene membership to conserved regions, and physicochemical profiles) are combined in a supervised pairwise ortholog detection approach to improve effectiveness considering low ortholog ratios in relation to the possible pairwise comparison between two genomes. In this scenario, big data supervised classifiers managing imbalance between ortholog and nonortholog pair classes allow for an effective scaling solution built from two genomes and extended to other genome pairs. The supervised approach was compared with RBH, RSD, and OMA algorithms by using the following yeast genome pairs: Saccharomyces cerevisiae-Kluyveromyces lactis, Saccharomyces cerevisiae-Candida glabrata, and Saccharomyces cerevisiae-Schizosaccharomyces pombe as benchmark datasets. Because of the large amount of imbalanced data, the building and testing of the supervised model were only possible by using big data supervised classifiers managing imbalance. Evaluation metrics taking low ortholog ratios into account were applied. From the effectiveness perspective, MapReduce Random Oversampling combined with Spark SVM outperformed RBH, RSD, and OMA, probably because of the consideration of gene pair features beyond alignment similarities combined with the advances in big data supervised classification. [ABSTRACT FROM AUTHOR]

The term 'Big Data' has spread rapidly in the framework of Data Mining and Business Intelligence. This new scenario can be defined by means of those problems that cannot be effectively or efficiently addressed using the standard computing resources that we currently have. We must emphasize that Big Data does not just imply large volumes of data but also the necessity for scalability, i.e., to ensure a response in an acceptable elapsed time. When the scalability term is considered, usually traditional parallel-type solutions are contemplated, such as the Message Passing Interface or high performance and distributed Database Management Systems. Nowadays there is a new paradigm that has gained popularity over the latter due to the number of benefits it offers. This model is Cloud Computing, and among its main features we has to stress its elasticity in the use of computing resources and space, less management effort, and flexible costs. In this article, we provide an overview on the topic of Big Data, and how the current problem can be addressed from the perspective of Cloud Computing and its programming frameworks. In particular, we focus on those systems for large-scale analytics based on the MapReduce scheme and Hadoop, its open-source implementation. We identify several libraries and software projects that have been developed for aiding practitioners to address this new programming model. We also analyze the advantages and disadvantages of MapReduce, in contrast to the classical solutions in this field. Finally, we present a number of programming frameworks that have been proposed as an alternative to MapReduce, developed under the premise of solving the shortcomings of this model in certain scenarios and platforms. WIREs Data Mining Knowl Discov 2014, 4:380-409. doi: 10.1002/widm.1134 For further resources related to this article, please visit the . Conflict of interest: The authors have declared no conflicts of interest for this article. [ABSTRACT FROM AUTHOR]

About 45% of the total surface area of the Castile and Leon region today can potentially be occupied by semi-deciduous forests, chiefly dominated by Quercus faginea Willd. and Quercus pyrenaica Lam. On the basis of extrapolated trends in annual mean temperature and precipitation in Castile and Leon observed over the 37-year period from 1961 to 1997 [del Río et al. 2005], predicted changes in the areas covered by Q. faginea and Q. pyrenaica forests in 2025, 2050 and 2075 were made. A decrease in Q. faginea forests may occur if observed trends in temperature and precipitation continue. With respect to Q. pyrenaica forests, they may increase in present Mediterranean areas and decreases in Temperate Submediterranean areas. In some cases, both types of forests could be replaced by deciduous forests. The predicted results in the natural distribution of vegetation types by the bioclimatic models can be used to establish policies for improved future nature conservation and land management. [ABSTRACT FROM AUTHOR]

• The wine sector plays a key role in the domestic Spanish economy. • A new integrated methodology is proposed for assessing suitable areas for viticulture. • The Compensated Thermicity Index is useful to delimitate potential areas for viticulture. • The approach is a helpful tool for agronomic and oenological management. In 2018, Spain was the third largest producer and the leading exporter of wine in the world. Viticulture is an important economic activity in the Castilla y León region, and is an element capable of halting the flight from the countryside and favouring demographic settlement in rural areas. A new integrated methodology for characterizing and delimitating areas suitable for vineyard cultivation is proposed here. The approach combines traditional climate indices with others used in bioclimatology and with soil variables, and applies various statistical analyses to select the predictors that best characterize the vineyards. These predictors are then integrated in species distribution models and a geographic information system. The methodology was tested in the Denomination of Origin León (hereafter DO León) in northwest Spain. Ten single models using the maximum entropy modelling algorithm were run for each of the six wine-grape varieties. Single-model projections built as a consensus of the ten models into an ensemble-forecasting approach were later used to generate maps of suitable areas for each variety. The results confirm the delimitation of the DO León as a Denomination of Origin. The bioclimatic variables Compensated Thermicity Index and Continentality Index and the soil variables pH, Clay Content, Soil Retention Capacity and Soil Saturation Humidity are defining for all the varieties studied. Garnacha and Mencía were the most different varieties in relation to their bioclimatic and soil requirements. Suitability maps revealed that the DO could be extended into neighbouring areas up to 30 km around it. The proposed methodology is a useful tool for agronomic and oenological management; it allows a more effective selection of sites for new vineyards, improves vineyard management, and can even be used to protect territories with a historical and cultural heritage of grape cultivation, thus favouring demographic settlement in rural areas and avoiding depopulation. [ABSTRACT FROM AUTHOR]

Prunus lusitanica L. is a paleotropical relic species with an Ibero-Maghrebian distribution, which is presently considered as an endangered species, recognized by the Natura 2000 Network (92/43/EEC) as a priority habitat for conservation in Europe. The mountains in the Portuguese mainland central region offer the best location for this species to occur. The main objective of this study is to measure the current conservation status of the communities of P. lusitanica, through the collection of field data, such as the number of existing individuals of each population and their location, which will then be comparatively analyzed based on the previous literature, published at least 15 years ago. Soil characterization analysis was carried out and the main threats to conservation were identified. As a result, a decline of approximately 40% was observed in the number of individuals and in the quality of their habitat. The main threats to their conservation were found to be the seasonal occurrence of rural fires and the expansion of invasive species, such as Acacia dealbata Link and Ailanthus altissima (Mill.) Swingle. Finally, we present the main management methodologies that should be considered for the valorization of this important vegetational relic in the central region of mainland Portugal. [ABSTRACT FROM AUTHOR]

The rocky habitats of southern Portugal are ecosystems with extreme xericity conditions, associated with special abiotic strains. In these unstable ecological conditions, a considerable diversity of plant communities occurs. The objective of this study, carried out in the Algarve and Monchique, and the Mariánica Range biogeographical sectors, is to compare chasmo-chomophytic communities of the southwestern Iberian Peninsula, using a phytosociological approach (Braun–Blanquet methodology) and numerical analysis (hierarchical cluster analysis). From these results, two new communities were identified, Sanguisorbo rupicolae-Dianthetum crassipedis and Antirrhinetum onubensis, as a result of floristic and biogeographical differences from other associations already described within the alliances Rumici indurati-Dianthion lusitani and Calendulo lusitanicae-Antirrhinion linkiani, both included in the Phagnalo saxatilis-Rumicetea indurate class. [ABSTRACT FROM AUTHOR]

A study was conducted on 14 grassland communities located in the south of the Iberian Peninsula and their edaphology, which is identified as specific plant associations. The edaphic study of each association allows a rapid evaluation of the nutrient content in the soil without the need for laboratory edaphic analysis. For each phytosociological relevé and soil, samplings were carried out. The field data were subjected to various statistical analysis—canonical correspondence analysis (CCA), Bayesian networks, and decision trees—to establish nutrient content. When the abundance value of the species is 9 in the Van der Maarel scale, there is an increase in the values of several soil parameters. In the case of Hordeum leporinum, when the Van der Maarel index is 9, the Kc (exchangeable potassium in cmol/kg) undergoes the greatest variation, to a value of up to 0.729 cmol/kg. The application of the decision tree to this species reveals that the soil attributes with the greatest influence in the classification are conductivity, %_si (silt texture), pH, and pF 15 atm (pressure at 15 atmospheres (water retention capacity) in %). Indeed, this interlaced edaphic and phytosociological study provides us with a high-value tool to obtain quick information on the content of nutrients in the soil. [ABSTRACT FROM AUTHOR]

Mapping pollen concentrations is of great interest to study the health impact and ecological implications or for forestry or agronomical purposes. A deep knowledge about factors affecting airborne pollen is essential for predicting and understanding its dynamics. The present work sought to predict annual Quercus pollen over the Castilla and León region (Central and Northern Spain). Also to understand the relationship between airborne pollen and landscape. Records of Quercus and Quercus pyrenaica pollen types were collected at 13 monitoring sites over a period of 8 years. They were analyzed together with land use data applying the Concentric Ring Method (CRM), a technique that we developed to study the relationship between airborne particle concentrations and emission sources in the region. The maximum correlation between the Quercus pollen and forms of vegetation was determined by shrubland and “dehesa” areas. For the specific Qi pyrenaica model ( Q . pyrenaica pollen and Q . pyrenaica forest distribution), the maximum influence of emission sources on airborne pollen was observed at 14 km from the pollen trap location with some positive correlations up to a distance of 43 km. Apart from meteorological behavior, the local features of the region can explain pollen dispersion patterns. The method that we develop here proved to be a powerful tool for multi-source pollen mapping based on land use. [ABSTRACT FROM AUTHOR]

This paper describes the relationships between rainfall in Spain (1961–2010) and four teleconnection patterns on three time scales (monthly, seasonal and annual) using data from 144 meteorological stations. Spearman's test was used to carry out partial correlations, and spatial distribution maps of the correlation coefficients were generated with kriging method. We regionalise the study area into homogeneous areas containing weather stations with a similar precipitation response to the patterns. The links between precipitation and the NAO, AO and EA are generally positive in the east and negative in the west of Spain, whereas WeMO correlates positively in the north and negatively in the rest. As a general result, the winter months and winter season show the highest percentage of weather stations with statistically significant correlations. Spearman coefficients of up to 0.62 were found for the NAO, AO and EA. WeMO strongly correlates (values up to 0.55) from October to April. Five areas have been defined: centre/southwest, northwest, north, northeast, and southeast. The mode which best explains rainfall in the two western areas is the NAO; in the north, the WeMO exerts a notable influence; EA correlates better with precipitation in the two eastern zones, especially in spring, autumn and part of winter. They are better controllers of rainfall in these areas than in the whole of the study area. [ABSTRACT FROM AUTHOR]

Abstract: Two panels of assessors from France and Spain assessed 41 dry-cured hams from diverse geographical origins, pig breedings and feedings. Univariate (Kolmogorov–Smirnov test and t-test) and multivariate (canonical correlation and principal component analysis) statistical procedures have been used to explain the agreement and disagreement between panels evaluating similar and dissimilar sensory attributes quantified with a 9-points structure scale. The results pointed out that there were basic agreements between panels, although some disagreements were detected in mould, acorn and crust attributes. The classification of Iberian and white dry-cured hams and the sensory attributes that characterise them are also displayed. [Copyright &y& Elsevier]