Viticultural climatic indices were assessed for the evaluation of the meteorological variations in the requirements of wine cultivars. The applied bioclimatic indices have been widely used to provide an initial evaluation of climate change impacts on grapevine and to delineate wine regions and suitable areas for planting around the world. The study was carried out over a period of 16 years (from 2000 to 2015) in five Designation of Origin areas in Northwestern Spain located in the Eurosiberian region, the transition zone between the Eurosiberian and the Mediterranean areas, and in the Mediterranean area. In addition, the high-resolution meteorological dataset “Spain02” was applied to the bioclimatic indices for the period 1950–2095. To further assess the performance of “Spain02”, Taylor diagrams were elaborated for the different bioclimatic indices. A significant trend to an increase of the Winkler, Huglin, Night Cold Index and GSS Indices was detected in the North-western Spain, whereas slight negative trends for BBLI and GSP Indices were observed. To analyze future projections 2061–2095, data from the high-resolution dynamically downscaled daily climate simulations from EURO-CORDEX project were used. To further assess the performance of Spain02, Taylor diagrams were elaborated for the different bioclimatic indices. A trend to an increase of the Winkler, Huglin, Night Cold Index and GSP Indices was detected in Northwestern Spain, whereas slight negative trends for BBLI and GSP Indices were observed. Our results showed that climatic conditions in the study region could variate for the crop in the future, more for Mediterranean than Eurosiberian bioclimatic area. Due to an advance in the phenological events or the vintage data, more alcohol-fortified wines and variations in the acidity level of wines could be expected in Northwestern Spain, these processes being most noticeable in the Mediterranean area. The projections for the BBLI and GSP Indices will induce a decrease in the pressure of the mildew attacks incidence in the areas located at the Eurosiberian region and the nearest transition zones. Projections showed if the trend of temperature increase continues, some cultural practice variations should be conducted in order to preserve the grape cultivation suitability in the studied area.

Climate has a direct influence on crop development and final yield. The consequences of global climate change have appeared during the last decades, with increasing weather variability in many world regions. One of the derived problems is the maintenance of food supply in this unstable context and the needed changes in agricultural systems, looking for sustainable and adaptation strategies. The study was carried out from 2008 to 2017. Aerobiological data were obtained with a Lanzoni VPPS-2000 volumetric sampler, following the Spanish Aerobiological Network protocol. The pollen and flower production was studied on ten vines of the Godello grapevine cultivar. A HOBO Micro Station and a MeteoGalicia station were used to obtain meteorological information. We observed the detrimental effect of rain on airborne pollen presence, and we statistically corroborated the negative effect of high temperatures on fruit set and ripening. We developed an accurate multiple regression model to forecast the grape yield, applying a Spearman’s correlation test to identify the most influential variables. The use of aerobiological and meteorological studies for crop yield prediction has been widely used in different crops that suppose important engines for economy development. This enables growers to adapt their crop management and adjust the spent resources.

The aim of this study was to assess the thermal requirements of the most important grapevine varieties in northwestern Spain to better understand the impact of climate change on their phenology. Different phenological models (GDD, GDD Triangular and UniFORC) were tested and validated to predict budburst and flowering dates of grapevines at the variety level using phenological observations collected from Treixadura, Godello, Loureira and Albariño between 2008 and 2019. The same modeling framework was assessed to obtain the most suitable model for this region. The parametrization of the models was carried out with the Phenological Modeling Platform (PMP) platform by means of an iterative optimization process. Phenological data for all four varieties were used to determine the best-fitted parameters for each variety and model type that best predicted budburst and flowering dates. A model calibration phase was conducted using each variety dataset independently, where the intermediate-fitted parameters for each model formulation were freely-adjusted. Afterwards, the parameter set combination of the model providing the highest performance for each variety was externally validated with the dataset of the other three varieties, which allowed us to establish one overall unique model for budburst and flowering for all varieties. Finally, the performance of this model was compared with the attained one while considering all varieties in one dataset (12 years × 4 varieties giving a total number of observations of 48). For both phenological stages, the results showed no considerable differences between the GDD and Triangular GDD models. The best parameters selected were those provided by the Treixadura GDD model for budburst (day of the year (t₀) = 49 and base temperature (Tb) = 5) and those corresponding to the Godello model (t₀ = 52 and Tb = 6) for flowering. The modeling approach employed allowed obtaining a global prediction model that can adequately predict budburst and flowering dates for all varieties.

Phenological, aerobiological, and weather data are useful tools to study local and regional flowering dynamics in crops with economic importance. The present study focuses on four autochthonous grapevine cultivars, namely, ‘Treixadura’, ‘Godello’, ‘Loureira’, and ‘Albariño’ (Vitis vinifera L.), which belong to the Designation of Origin Ribeiro area (located in northwestern Spain) from 2015–2019. The aims of the work were to (1) compare the airborne pollen concentration in the vineyard collected by two different traps, (2) analyze the influence of the main meteorological variables on cultivar phenology and pollen concentration, and (3) test the contribution of the air masses on pollen concentrations in the vineyard. Phenological development has been assessed twice weekly, according to the Biologische Bundesanstalt, Bundessortenamt und Chemische Industrie (BBCH) scale. Airborne pollen concentrations were monitored by using two traps during stage 6 (flowering), namely, a Hirst volumetric sampler and a Cour passive trap. The bioclimatic conditions affected the duration of flowering, ranging from 11 and 24 days. The highest seasonal pollen integral (SPIn) was registered in 2016 for the Hirst sampler, with 302 pollen, and in 2019 for the Cour trap, with 1,797,765 pollen/m²/day. The main variables affecting pollen concentrations were average temperature during the main pollen season, as well as, temperatures and dew points during the pre-peak period. The relationship between pollen data registered by both traps and the obtained harvest indicate that the Hirst trap may be more suitable for predicting a local production and that the Cour sampler is more appropriate for forecasting regional productions.

Variations in the airborne pollen load are among the current and expected impacts on plant pollination driven by climate change. Due to the potential risk for pollen-allergy sufferers, this study aimed to analyze the trends of the three most abundant spring-tree pollen types, Pinus, Platanus and Quercus, and to evaluate the possible influence of meteorological conditions. An aerobiological study was performed during the 1993–2020 period in the Ourense city (NW Spain) by means of a Hirst-type volumetric sampler. Meteorological data were obtained from the ‘Ourense’ meteorological station of METEOGALICIA. We found statistically significant trends for the Total Pollen in all cases. The positive slope values indicated an increase in pollen grains over the pollen season along the studied years, ranging from an increase of 107 to 442 pollen grains. The resulting C5.0 Decision Trees and Rule-Based Models coincided with the Spearman’s correlations since both statistical analyses showed a strong and positive influence of temperature and sunlight on pollen release and dispersal, as well as a negative influence of rainfall due to washout processes. Specifically, we found that slight rainfall and moderate temperatures promote the presence of Pinus pollen in the atmosphere and a marked effect of the daily thermal amplitude on the presence of high Platanus pollen levels. The percentage of successful predictions of the C5.0 models ranged between 62.23–74.28%. The analysis of long-term datasets of pollen and meteorological information provides valuable models that can be used as an indicator of potential allergy risk in the short term by feeding the obtained models with weather prognostics.