Due to the severe increase projected in future temperatures and the great economic and social importance of olive growing for vast agricultural areas in the Mediterranean Basin, accurate climate change impact assessment on olive orchards is required. The aim of this study is to assess the flowering date and the impact of mean and extreme temperature events on olive flowering in southern Spain under baseline and future climate conditions. To that end, experimental data were obtained from ten olive genotypes: six well‐known olive cultivars in the region, one cultivar, ‘Chiquitita’, obtained via conventional breeding, and three wild olives from the Canary Islands. A site‐specific model calibration was conducted resulting in satisfactory performance with an average error of 2 days for flowering date estimation under baseline and future climate conditions, and a RMSE equal to 5.5 days in the validation process. The outputs from 12 regional climate models from the ENSEMBLES European project with a bias correction in temperature and precipitation were used. Results showed an advance in the olive flowering dates of about 17 days at the end of the 21st century compared with the baseline period (1981–2010), and an increase in the frequency of extreme events around the flowering period. A spatial analysis of results identified the areas in southern Spain that are most vulnerable to climate change impact caused by the lack of chilling hours accumulation (areas located on the Atlantic coast and the south‐eastern coast) and by the occurrence of high temperatures during the flowering period (areas located in the north and north‐eastern areas of the Andalusian region).

Climate projections indicate that rising temperatures will affect summer crops in the southern Iberian Peninsula. The aim of this study was to obtain projections of the impacts of rising temperatures, and of higher frequency of extreme events on irrigated maize, and to evaluate some adaptation strategies. The study was conducted at several locations in Andalusia using the CERES-Maize crop model, previously calibrated/validated with local experimental datasets. The simulated climate consisted of projections from regional climate models from the ENSEMBLES project; these were corrected for daily temperature and precipitation with regard to the E-OBS observational dataset. These bias-corrected projections were used with the CERES-Maize model to generate future impacts. Crop model results showed a decrease in maize yield by the end of the 21st century from 6 to 20%, a decrease of up to 25% in irrigation water requirements, and an increase in irrigation water productivity of up to 22%, due to earlier maturity dates and stomatal closure caused by CO2 increase. When adaptation strategies combining earlier sowing dates and cultivar changes were considered, impacts were compensated, and maize yield increased up to 14%, compared with the baseline period (1981-2010), with similar reductions in crop irrigation water requirements. Effects of extreme maximum temperatures rose to 40% at the end of the 21st century, compared with the baseline. Adaptation resulted in an overall reduction in extreme Tmax damages in all locations, with the exception of Granada, where losses were limited to 8%

Agriculture plays a crucial role as a carbon sink in the atmosphere, contributing to a climate-neutral economy, which requires a comprehensive understanding of Earth’s complex biogeochemical processes. This study aims to quantify, for the first time, Gross Primary Productivity (GPP) and ecosystem water use efficiency (eWUE) in almond orchards during their vegetative phase. The study was conducted over six growing seasons (2017–2022) across two drip-irrigated commercial almond groves located in Albacete, SE Spain. Eddy covariance flux tower systems were used to measure Net Ecosystem Exchange (NEE) and evapotranspiration (ET), which were then used to calculate GPP and eWUE. A novel approach was developed to estimate eWUE by integrating the Normalized Difference Vegetation Index (NDVI), reference ET, and air temperature. The results show similar almond orchard carbon-fixing capacity rates to those of other natural and agro-ecosystems. Seasonal and interannual variability in GPP and eWUE were observed. The NDVI-ET combination proved to be effective for GPP estimations (regression coefficient of 0.78). Maximum carbon-fixing values were observed at ET values of around 4–5 mm/d. In addition, a novel method was developed to estimate eWUE from NDVI, reference ET and air temperature (RMSE of 0.38 g·C/kg·H₂O). This study highlights the carbon capture potential of almond orchards during their vegetative phase and introduces a novel approach for eWUE monitoring, with the intention of underscoring their significance in a climate change context and to encourage further research.

Climate change projections indicate a significant increase in greenhouse gas (GHG) emissions, leading to elevated temperatures, extreme weather events, and water scarcity, particularly in regions like southern Europe. Agriculture, forestry, and other land use activities contribute to 22% of these emissions, but they also offer the potential to act as carbon sinks, supporting the transition to a climate-neutral economy as outlined in the Paris Agreement. The concept of carbon offset involves compensating for emissions by reducing, avoiding, or sequestering an equivalent amount of CO2. Practices such as carbon credits could provide new economic incentives through participation in the voluntary carbon market.Hence, it is crucial to develop reliable methods to quantify carbon dynamics in terrestrial ecosystems, focusing on the relationship between carbon energy parameters; Net Ecosystem Exchange (NEE), Ecosystem Respiration, and Gross Primary Productivity (GPP). In Spain, the rise in irrigated almond orchards, particularly in the La Mancha region, highlights the need to understand ecosystem Water Use Efficiency (WUE) as a crucial parameter for sustainable crop management. The study employs Eddy Covariance (EC) flux towers to measure NEE, ET, and GPP, providing valuable insights into WUE and contributing to carbon cycle assessments and climate change mitigation strategies.This study spanned six almond growing seasons (2017-2022) in two different drip-irrigated almond orchards locations in Albacete (SE Spain). These orchards, meeting minimum fetch requirements, exhibited a notable carbon-fixing capacity, comparable to other natural and agroecosystems. Seasonal variability and environmental influences were evident throughout the six-year study. In this study, we also modelled WUE as a function of remote sensing vegetation indices, such as the Normalized Difference Vegetation Index (NDVI) and meteorological data.Seasonal variability, age and density of almond orchards significantly influence on the observed GPP and NEE. Almond orchards captured more CO2 than that released between April and October. The maximum monthly GPP values observed by EC was 263.7 g C m-2. Besides, the combination NDVI and ET proved effective in estimating GPP, with a regression coefficient (R2) of 0.78. Modelled WUE, incorporating 'NDVI, potential evapotranspiration (ETo), and air temperature (Tair),' strikes an optimal balance between explanatory capacity and simplicity. While showing promise with determination coefficients of 0.88 and 0.86, caution is advised due to the limited sample size, necessitating future further validation with larger datasets. Nevertheless, this approach could be a valuable tool for stakeholders addressing efficient water use challenges in agriculture. This study highlights the importance of quantifying carbon uptake and ecosystem water use efficiency by almond orchards as a strategy for mitigating climate change.