Olive cultivation systems across the Mediterranean region are increasingly vulnerable to climate change, threatening the long-term economic and environmental sustainability of these agroecosystems. This study evaluates alternative soil management adaptation measures in traditional olive orchards, with the dual objective of mitigating climate-related impacts—particularly by reducing runoff—while maintaining olive oil production. To this end, we developed AdaptaOlive-WABOL, a new olive crop simulation model designed to estimate water balance components and olive oil yield under diverse climatic conditions. The model was applied to assess contrasting soil management strategies using an ensemble of climate projections from the ISIMIP repository. Results show that the effectiveness of soil management practices is highly dependent on water availability, underscoring the importance of strategy selection in water-limited environments. Under relatively wet conditions (around 600 mm annually), the use of a cover crop, such as Bromus rubens, reduced runoff by approximately 28

Crop modelling is a critical tool for assessing the impact of climate change and for evaluating adaptation strategies to ensure the sustainability of agricultural systems. In addition to increased temperature and reduced precipitation, studying the effects of increased atmospheric CO2 concentration ([CO2]) and water stress on water efficiency of crops is highly relevant for identifying and evaluating impacts and new adaptation measures. We carried out 12 experiments with 4 faba bean cultivars under controlled conditions of [CO2], temperature and water supply. An increase of [CO2] from 430 to 650 ppm caused a 20% reduction in stomatal conductance under optimal irrigation supply but had almost zero effect under water stress conditions. Our study shows that the beneficial effect of a higher atmospheric [CO2] on faba bean growth is counteracted by water stress, with the beneficial effect only detected when proper water management is applied. Thus, stomatal conductance appeared to be more sensitive to water stress than to elevated [CO2], indicating that the beneficial effects of elevated [CO2] on faba bean are largely dependent on the plant water status. This is particularly relevant in Mediterranean agricultural systems, where water shortage associated with droughts will become more frequent, even in areas of irrigation. Although differences in the response between cultivars were observed in our study when the water status was intermediate between optimal and severe drought, no single genotype among those studied will be sufficient to improve or fully guarantee yield under conditions of increasing [CO2] and water shortage. Therefore, the introduction of irrigation and/or sowing date strategies currently represent the only adaptation measures. The gaps in knowledge of the response of faba bean to climate change, and the limited number of adaptation measures available highlight the need for continued research, with breeding of drought-tolerant and high-yielding faba bean genotypes as one of the most promising alternatives.

In Spain, several local studies have highlighted the likely presence of unknown olive cultivars distinct from the approximately 260 ones previously described in the literature. Furthermore, recent advancements in identification techniques have significantly enhanced in terms of efficacy and precision. This scenario motivated a new nationwide prospecting effort aimed at recovering and characterizing new cultivated germplasm using high-throughput molecular markers. In the present study, the use of 96 EST-SNP markers allowed the identification of a considerable amount of new material (173 new genotypes) coming from areas with low intensification of production in different regions of Spain. As a result, the number of distinct national genotypes documented in the World Olive Germplasm Bank of IFAPA, Córdoba (WOGBC-ESP046) increased to 427. Likewise, 65 and 24 new synonymy and homonymy cases were identified, respectively. This rise in the number of different national cultivars allowed to deepen the knowledge about the underlying genetic structure. The great genetic variability of Spanish germplasm was confirmed, and a new hot spot of diversity was identified in the northern regions of La Rioja and Aragon. Analysis of the genetic structure showed a clear separation between the germplasm of southern and northern-northeastern Spain and indicated a significantly higher level of admixture in the latter. Given the expansion of modern olive cultivation with only a few cultivars, this cryptic germplasm is in great danger of disappearing. This underlines the fact that maintaining as many cultivars as possible will increase the genetic variability of the olive gene pool to meet the future challenges of olive cultivation.

The large amount of olive cultivars conserved in germplasm banks can be used to overcome some of the challenges faced by the olive growing industry, including climate warming. One effect of climate warming in olive is the difficulty to fulfill the chilling requirements for flowering due to mild winter temperatures. In the present work, we evaluate seven olive cultivars for their adaptation to high winter temperatures by comparing their flowering phenology in the standard Mediterranean climate of Cordoba, Southern Iberian Peninsula, with the subtropical climate of Tenerife, Canary Islands. Flowering phenology in Tenerife was significantly earlier and longer than in Cordoba. However, genotype seems to have little influence on the effects of the lack of winter chilling temperatures, as in Tenerife. This was found even though the cultivars studied had a high genetic distance between them. In fact, all the cultivars tested in Tenerife flowered during the three-year study but showed asynchronous flowering bud burst. 'Arbequina' showed an earlier day of full flowering compared with the rest of the cultivars. The results observed here could be of interest to refine the phenological simulation models, including the length of the flowering period. More genetic variability should be evaluated in warm winter conditions to look for adaptation to climate warming.

Extreme weather events, lower precipitation and higher temperatures play a relevant role in the assessment of wheat yield and protein concentration under future weather conditions in Mediterranean environments. To explore this topic, a dataset of long-term wheat cultivar trials carried out in 17 locations in Andalusia, southern Spain, between 1990 and 2017, and covering a wide range of weather conditions, has been analyzed.The occurrence of maximum temperatures surpassing 32.5 degrees C during heading showed significant correlations with yield, and generated reductions of up to 30% of the maximum observed yield. Similarly, water stress up to 20 days after heading or numerous days with both high temperatures and water stress up to 45 days after heading, also showed significant correlations with yield, and generated reductions of up to 23% and 41%, respectively. Moreover, irrigation showed a very relevant role, with the minimum relative yield increasing from 9% under rainfed conditions to 56% with irrigation supply higher than 150mm. For protein concentration, frequent joint events combining mild temperatures and severe water stresses around heading showed increases of 3 %-units. The future weather conditions projected for southern Spain will enhance risk of yield reduction and protein concentration increases, with a high spatial variability.Earlier sowing dates reduce the coincidence of extreme weather events with critical crop development stages, and thus the effects on yield and protein concentration, even identifying conditions that the impact was fully reversed. Similarly, irrigation during heading mitigated the negative effects of water stress on yield and the positive effects on protein concentration.The combination of long-term cultivar trials under semi-arid weather conditions, modeling and future climate projections constitutes an excellent tool for the assessment of vulnerable/suitable areas, and for the identification of site-specific adaptation measures to ensure the sustainability of wheat-growing areas in southern Europe.

Durum wheat cultivation in Mediterranean regions is threatened by abiotic factors, mainly related to the effects of climate change, and biotic factors such as the leaf rust disease. This situation requires an in-depth knowledge of how predicted elevated temperatures and [CO2] will affect durum wheat-leaf rust interactions. Therefore, we have characterised the response of one susceptible and two resistant durum wheat accessions against leaf rust under different environments in greenhouse assays, simulating the predicted conditions of elevated temperature and [CO2] in the far future period of 2070-2099 for the wheat growing region of Cordoba, Spain. Interestingly, high temperature alone or in combination with high [CO2] did not alter the external appearance of the rust lesions. However, through macro and microscopic evaluation, we found some host physiological and molecular responses to infection that would quantitatively reduce not only pustule formation and subsequent infection cycles of this pathogen, but also the host photosynthetic area under these predicted weather conditions, mainly expressed in the susceptible accession. Moreover, our results suggest that durum wheat responses to infection are mainly driven by temperature, being considered the most hampering abiotic stress. In contrast, leaf rust infection was greatly reduced when these weather conditions were also conducted during the inoculation process, resembling the effects of possible heat waves not only in disease development, but also in fungal germination and penetration success. Considering this lack of knowledge in plant-pathogen interactions combined with abiotic stresses, the present study is, to the best of our knowledge, the first to include the effects of the expected diurnal variation of maximum temperature and continuous elevated [CO2] in the durum wheat-leaf rust pathosystem.

Because of climate change and the scarce availability of natural resources there is a need to develop sustainable intensification strategies intended for optimizing water use in vineyards. In this study, water regime, fertilization and soil management practices were assessed in terms of vineyard water use, by evaluating the inter-row and crop line evapotranspiration (ET) components using the Mapping EvapoTranspiration at high Resolution with Internalized Calibration (METRIC) model in combination with unmanned aerial vehicle multispectral and thermal images taken on five dates throughout the growing season. The application of the METRIC-UAV using high-resolution imagery was proven as a useful tool for evaluating the effects of sustainable intensification strategies on water use of crops where vegetation does not completely cover the soil, identifying the most efficient site-specific strategies for water conservation purposes. Moreover, METRIC-UAV allowed evaluating separately their effects on the inter-row and the crop line. Among the assessed sustainable intensification stra-tegies, the application of mulching provided the highest water savings (-28%) when compared to traditional soil tillage management, reducing inter-row soil evaporation by 63%, while increasing crop-line ET by 14%. In spite of this, the mulching application did not affect yield, but significantly enhanced water use efficiency (WUE) in terms of grape yield compared to tillage. The adoption of deficit irrigation (DI) strategies did not result in vine water stress that was severe enough to significantly affect crop line ET when compared with fully irrigated (FI) vines. Both DI and FI strategies increased vine water use by 18% and 27%, respectively, as compared to the rainfed regime, with no differences found in the inter-row water consumption. DI and FI, in turn, significantly increased yield as compared to rainfed crops, leading to significant improvements in WUE. In the short term, the application of supplemental inorganic fertilizers did not modify either the vineyard water use or vine performance.

Wheat interactions against fungal pathogens, such as Zymoseptoria tritici, are affected by changes in abiotic factors resulting from global climate change. This situation demands in-depth knowledge of how predicted increases in temperature and CO2 concentration ([CO2]) will affect wheat—Z. tritici interactions, especially in durum wheat, which is mainly grown in areas considered to be hotspots of climate change. Therefore, we characterized the response of one susceptible and two resistant durum wheat accessions against Z. tritici under different environments in greenhouse assays, simulating the predicted conditions of elevated temperature and [CO2] in the far future period of 2070–2099 for the wheat-growing region of Córdoba, Spain. The exposure of the wheat—Z. tritici pathosystem to elevated temperature reduced disease incidence compared with the baseline weather conditions, mainly affecting pathogen virulence, especially at the stages of host penetration and pycnidia formation and maturation. Interestingly, simultaneous exposure to elevated temperature and [CO2] slightly increased Z. tritici leaf tissue colonization compared with elevated temperature weather conditions, although this fungal growth did not occur in comparison with baseline conditions, suggesting that temperature was the main abiotic factor modulating the response of this pathosystem, in which elevated [CO2] slightly favored fungal development.

Some adaptation measures in response to the severe impacts of climate change on Mediterranean olive orchards were evaluated under a wide range of weather conditions. For this task, a decision support system for improving resources management by the integration of the AdaptaOlive simulation model, perturbed climate and impact and adaptation response surfaces for the model output analysis was developed. Thus, the introduction of irri-gation (considering different irrigation strategies such as full demand, regulated deficit irrigation or irrigation support), the implementation of cultivars with lower chilling requirements, the modification of orchard density and an increase in irrigation efficiency were evaluated under current and future weather conditions. Optimal sustainable and environmentally friendly adaptation measures varied depending on the local weather conditions. Thus, the introduction of irrigation provided excellent results under dry and cool winter weather conditions. Cultivars with low chilling requirements reduced flowering failure associated with the lack of chill accumulation and registered optimal performance under mild winter conditions. This adaptation measure played a critical role under these weather conditions, even more so than measures focused on preventing water stress as irrigation. Finally, increasing orchard density was appropriate in non-water-limited areas with cool winter conditions. This study confirms the great importance of integrating crop modelling and tools for model output analysis into the assessment of site-specific adaptation measures to climate change, in order to ensure the sustainability of Mediterranean agricultural systems under semi-arid conditions.

Olive, the emblematic Mediterranean fruit crop, owns a great varietal diversity, which is maintained in ex situ field collections, such as the World Olive Germplasm Bank of Córdoba (WOGBC), Spain. Accurate identification of WOGBC, one of the world's largest collections, is essential for efficient management and use of olive germplasm. The present study is the first report of the use of a core set of 96 EST-SNP markers for the fingerprinting of 1273 accessions from 29 countries, including both field and new acquired accessions. The EST-SNP fingerprinting made possible the accurate identification of 668 different genotypes, including 148 detected among the new acquired accessions. Despite the overall high genetic diversity found at WOGBC, the EST-SNPs also revealed the presence of remarkable redundant germplasm mostly represented by synonymy cases within and between countries. This finding, together with the presence of homonymy cases, may reflect a continuous interchange of olive cultivars, as well as a common and general approach for their naming. The structure analysis revealed a certain geographic clustering of the analysed germplasm. The EST-SNP panel under study provides a powerful and accurate genotyping tool, allowing for the foundation of a common strategy for efficient safeguarding and management of olive genetic resources.

This study investigates the main drivers of uncertainties in simulated irrigated maize yield under historical conditions as well as scenarios of increased temperatures and altered irrigation water availability. Using APSIM, MONICA, and SIMPLACE crop models, we quantified the relative contributions of three irrigation water allocation strategies, three sowing dates, and three maize cultivars to the uncertainty in simulated yields. The water allocation strategies were derived from historical records of farmer's allocation patterns in drip-irrigation scheme of the Genil-Cabra region, Spain (2014-2017). By considering combinations of allocation strategies, the adjusted R2 values (showing the degree of agreement between simulated and observed yields) increased by 29% compared to unrealistic assumptions of considering only near optimal or deficit irrigation scheduling. The factor decomposition analysis based on historic climate showed that irrigation strategies was the main driver of uncertainty in simulated yields (66%). However, under temperature increase scenarios, the contribution of crop model and cultivar choice to uncertainty in simulated yields were as important as irrigation strategy. This was partially due to different model structure in processes related to the temperature responses. Our study calls for including information on irrigation strategies conducted by farmers to reduce the uncertainty in simulated yields at field scale.

Sustainable intensification (SI) of agriculture is a promising strategy for boosting the capacity of the agricultural sector to meet the growing demands for food and non-food products and services in a sustainable manner. Assessing and quantifying the options for SI remains a challenge due to its multiple dimensions and potential associated trade-offs. We contribute to overcoming this challenge by proposing an approach for the ex-ante evaluation of SI options and trade-offs to facilitate decision making in relation to SI. This approach is based on the utilization of a newly developed SI metrics framework (SIMeF) combined with agricultural systems modelling. We present SIMeF and its operationalization approach with modelling and evaluate the approach’s feasibility by assessing to what extent the SIMeF metrics can be quantified by representative agricultural systems models. SIMeF is based on the integration of academic and policy indicator frameworks, expert opinions, as well as the Sustainable Development Goals. Structured along seven SI domains and consisting of 37 themes, 142 sub-themes and 1128 metrics, it offers a holistic, generic, and policy-relevant dashboard for selecting the SI metrics to be quantified for the assessment of SI options in diverse contexts. The use of SIMeF with agricultural systems modelling allows the ex-ante assessment of SI options with respect to their productivity, resource use efficiency, environmental sustainability and, to a large extent, economic sustainability. However, we identify limitations to the use of modelling to represent several SI aspects related to social sustainability, certain ecological functions, the multi-functionality of agriculture, the management of losses and waste, and security and resilience. We suggest advancements in agricultural systems models and greater interdisciplinary and transdisciplinary integration to improve the ability to quantify SI metrics and to assess trade-offs across the various dimensions of SI.

A substantial area of the new almond plantations in Spain is under irrigation, but due to recurring severe droughts, the irrigation water allocation for agriculture can be drastically reduced eventually. This study assesses the physiological and yields effects of a single-season water deprivation (2017) over three seasons (2017–2019) on a previously well-irrigated mature almond [ Prunus dulcis (Mill) D.A. Web, cv. Guara] orchard in southern Spain. Three irrigation treatments were imposed during 2017: full irrigation, applying the amount required to match maximum crop evapotranspiration (FI); sustained deficit irrigation applying 25% of FI (DI); and rain-fed which received no irrigation at all (RF). During 2018 and 2019, all treatments were irrigated as FI. The results document the vulnerability of irrigated almond orchards to severe water stress, as the rainfed treatment resulted in 92% tree mortality. In relation to FI, yield and quality were reduced in RF and DI by the negative impact of water stress on kernel weight and the formation of hull tights in the season of water deprivation. In the two following years, the negative impact on yields persisted due to reductions in fruit load (carry-over effects) even though trees in DI and RF were restored to full-irrigation levels. The three-year average yields of DI and RF treatments were less than what could be predicted from an almond production function obtained in the same orchard. This highlights the long-term negative impacts that severe water stress resulting from suspending or reducing drastically irrigation in a single season has on almond trees.

A correction to this paper has been published: https://doi.org/10.1007/s00271-021-00733-3

Combining an olive growth simulation model with a specific module for economic components?namely, net margin (NM) and irrigation water productivity (IWP)?resulted in the AdaptaOlive v2.0 model. This model, used with perturbed climate (PC) and impact response surfaces (IRS), provided a tool that enabled the assessment of the impact of climate change on economic components of Mediterranean olive groves in southern Spain. Under future mild winter conditions, reductions in NM and IWP are expected; negative NM values may even be registered, with water availability having a relatively small effect on the results. In the opposite case, under future cool winter conditions, NM and IWP will increase, except for rainfed olive groves under low rainfall conditions, with water availability playing a major role. In addition, the distance (in terms of changes in temperature and rainfall compared to baseline conditions) to critical thresholds such as negative NM or IWP lower than irrigation water cost was assessed, identifying changes depending on weather conditions, water cost and olive oil price. Thus, future temperature increases of around 3 ?C under mild winter conditions could generate negative values of NM. These economic results impact the performance of adaptation strategies for olive groves, even ruling out some strategies that were previously recommended when only agronomic components were taken into account (e.g., deficit irrigation under mild winter conditions). There is thus a need for site-specific recommendations related to the use of irrigation and olive orchard management to maintain or increase the sustainability of these cropping systems. Despite the utility of using PC and IRS to achieve a scientifically sound evaluation of Mediterranean olive groves under future weather conditions, the approach presents some limitations that can be overcome using climate model outputs.

Olive is a woody crop extended over 10 Mha around the world (FAOSTAT, 2019), being Spain the country with the largest area (2.7 Mha). Andalusia is located in the South of Spain, with 1.6 Mha cultivated with olive trees, most of them (around 90%) dedicated to olive oil production (MAPA, 2020). This region is characterized by a great diversity of weather conditions. This diversity greatly affects important agronomic parameters of olive as the pattern of oil accumulation. This influence is different depending on the cultivar considered. In addition, this pattern of oil accumulation is a key aspect since is the most relevant trait determining the optimal harvest time. For that reason, in the present study, the relative influence of cultivar and environment, and their interaction, have been evaluated for the full pattern of oil accumulation. This study was carried out in four locations of Andalusia covering a wide range of weather conditions, and where olive trees are well established or under expansion: Antequera (Málaga), Córdoba, Úbeda (Jaén) and Gibraleón (Huelva). In 2008, five cultivars were planted in a randomized complete block design consisting in four blocks and four trees per elementary plot: Arbequina, Hojiblanca, Koroneiki, Picual and Sikitita-3 (a new registered cultivar from the olive breeding program developed by the University of Córdoba and IFAPA). The first two locations were monitored in 2018 and 2020 while the other two locations were monitored only during 2020 campaign. Fruits samples were collected periodically, starting 4 weeks after full bloom until the oil accumulation was finished. Then, in the laboratory, fruits’ oil content was measured by nuclear magnetic resonance. Results show sigmoid patterns regarding fruit oil accumulation and dry basis along each campaign in all genotypes, locations and years. There were significant differences of maximum olive oil accumulation among genotypes, recording the genotype Sikitita-3 the maximum ones. Furthermore, a significant genotype-environment interaction was also found for these. These results have relevant consequences regarding the selection of the optimal harvest time, to accomplish a desired balance between maximum oil accumulation and quality indicators which require early harvest dates. References: FAOSTAT, 2019. Food and Agriculture Organization of the United Nations. FAOSTAT database available at http://www.fao.org/faostat/en/#data. Last accessed 12 January 2020. MAPA, 2020. Ministry of Agriculture, Fisheries and Food. Survey of surfaces and crop yields 2020 available at https://www.mapa.gob.es/es/estadistica/temas/estadisticas-agrarias/agricultura/esyrce/. Last accessed 12 January 2020.

While the understanding of average impacts of climate change on crop yields is improving, few assessments have quantified expected impacts on yield distributions and the risk of yield failures. Here we present the relative distribution as a method to assess how the risk of yield failure due to heat and drought stress (measured in terms of return period between yields falling 15% below previous five year Olympic average yield) responds to changes of the underlying yield distributions under climate change. Relative distributions are used to capture differences in the entire yield distribution between baseline and climate change scenarios, and to further decompose them into changes in the location and shape of the distribution. The methodology is applied here for the case of rainfed wheat and grain maize across Europe using an ensemble of crop models under three climate change scenarios with simulations conducted at 25 km resolution. Under climate change, maize generally displayed shorter return periods of yield failures (with changes under RCP 4.5 between −0.3 and 0 years compared to the baseline scenario) associated with a shift of the yield distribution towards lower values and changes in shape of the distribution that further reduced the frequency of high yields. This response was prominent in the areas characterized in the baseline scenario by high yields and relatively long return periods of failure. Conversely, for wheat, yield failures were projected to become less frequent under future scenarios (with changes in the return period of −0.1 to +0.4 years under RCP 4.5) and were associated with a shift of the distribution towards higher values and a change in shape increasing the frequency of extreme yields at both ends. Our study offers an approach to quantify the changes in yield distributions that drive crop yield failures. Actual risk assessments additionally require models that capture the variety of drivers determining crop yield variability and scenario climate input data that samples the range of probable climate variation.

The assessment of the impact of climate change on Mediterranean crop systems is affected by a large number of uncertainties. To overcome this issue in an impact and adaptation assessment for tree crops, an experimental dataset containing 556 phenological observations was used to calibrate and validate a modelling framework based on the Dynamic Model and ASYMCUR approach, for assessing the flowering date of common Mediterranean almond cultivars. Data were collected over 12 years for 15 almond cultivars in 5 locations in Andalusia (Southern Spain), covering a wide range of weather conditions. The model performance was good: for late-flowering cultivars Root Mean Square Error (RMSE) was 3.6 days and Nash-Sutcliffe model efficiency (NSE) was 0.89, while for early-flowering cultivars RMSE was 3.4 days and NSE was 0.83. Weather projections from an ensemble of 12 climate model outputs including 3 Representative Concentration Pathways (RCPs) were used with the modelling framework for each almond cultivar to quantify the changes in flowering date and the associated weather conditions during this stage, under the future weather conditions of the Iberian Peninsula (IP). Thus, in future scenarios, depending on location, start of full bloom was delayed (in mild-winter areas) or advanced (in cold-winter areas), with the change in weather conditions during critical phenological stages potentially affecting the yield in different ways, depicting a high spatial variability in the projections within the IP. For this reason, a spatial analysis was applied to demarcate those areas with adverse weather conditions related to flowering stage. In light of our results it is concluded that the identification of impacts and adaptation strategies for Mediterranean agriculture requires a careful prior evaluation of the systems at local scale, due to the marked spatial heterogeneity and the remaining high uncertainties associated with the crop modelling.

Aim of study: Crop phenology is a critical component in the identification of impacts of climate change. Then, the assessment of germplasm collections provides relevant information for cultivar selection and breeding related to phenology, being the base for identifying adaptation strategies to climate change. Area of study: The World Olive Germplasm Bank located at IFAPA Centre “Alameda del Obispo” (WOGB-IFAPA) in Cordoba (Southern Spain) was considered for the study. Material and methods: Data gathered for nine years on flowering and ripening time of olive cultivars from WOGB-IFAPA were evaluated. Thus, full flowering date (FFD) for 148 cultivars and ripening date (RD) for 86 cultivars, coming from 14 olive growing countries, were considered for characterization of olive phenology and for calibration/validation of phenological models. Main results: The characterization of WOGB-IFAPA has allowed the identification of cultivars with extreme early (‘Borriolenca’) and late (‘Ulliri i Kuq’) flowering as well as the ones with extreme early (‘Mavreya’) and late (‘Gerboui’) ripening dates. However, the very limited inter-cultivar variability, especially for FFD, resulted in a non-optimal simulation models performance. Thus, for FFD and RD the root mean square error was around 6 and 24 days, respectively. The limited inter-cultivar variability was associated to the low average temperatures registered during winter at WOGB-IFAPA generating an early accumulation of the chilling requirements, thus homogenizing FFD of all the analyzed cultivars. Research highlights: The identification of cultivars with early FFD and late RD provides useful information for breeding programs and climate change studies for identifying adaptation strategies.