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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]

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]

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]

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]

Abstract: This paper reports the results of the analysis of annual mean temperature and precipitation series from 171 meteorological stations distributed over Castile and Leon [Castilla y León in Spanish] in Spain on monthly, seasonal and annual time-scales for a 37-year study period (1961–1997). Various statistical tools were used to detect and characterize significant changes in these series. The magnitude of the trends was derived from the slopes of the regression lines using the least squares method, and the statistical significance was determined by means of nonparametric tests. Positive trends of about 0.33 °C in the annual mean temperature were found for the whole period. Mean temperatures increased in spring and winter, the winter trend being statistically significant. The months of December and March also showed significant trends. Decreases in rainfall were found for three seasons (winter, spring and autumn), with statistically significant trends in March. Summer precipitation showed slight increases over the 37-year period. On this basis, the authors consider that the increase in summer precipitation and the decrease in the range of average temperatures between the warmest and the coldest months of the year (continentality), point towards a trend to a more oceanic climate in Castile and Leon. [Copyright &y& Elsevier]