The memory of dynamic processes refers to the characteristic of dynamic systems where historical states influence their current and future behaviour. In modelling dynamic systems, it is crucial to ensure that the model design allows simulations that consider the system’s history and its impact on future dynamics beyond the integration interval. An important step toward this goal is identifying the characteristic time scale of the memory, i.e. memory longevity.

 In this research, we use the atmosphere as a dynamic system and air temperature at 2 m height as a variable that can carry memory information. To assess the impact of environmental conditions on memory characteristics, we selected meteorological data measured at climate stations and data from rural areas near Novi Sad and Vrsac (Serbia) measured at automatic weather stations (AWS) as part of the Forecasting and Warning Service for Plant Protection of Serbia (PIS) meteorological monitoring system.

Following Caballero et al. (2002), we analyzed the power spectral density (PSD) and autocorrelation functions (AC) of three air temperature time series. According to results of previous studies, processes represented with PSD following power law function, S(w) at low frequencies (w), [S(w) = w^-2d] are collectively referred to as “long memory” processes if 0<d<0.5. Parameter d is commonly described as the “intensity of long memory”.

Initial results obtained for climate station data series show clear differences between high- and low-frequency trends in PSD estimates for air temperature at the selected locations. Differences in AC are particularly noticeable for longer lags. 

Caballero, R., Jewson S., Brix, A., 2002: Long memory in surface air temperature: Detection, modelling, and application to weather derivative valuation. Clim. Res., 21, 127-140. 10.3354/cr021127.

How to cite: Lalic, B. and Firanj Sremac, A.: Impact of Environmental Conditions on Long-Memory of Surface Air Temperature, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-988, https://doi.org/10.5194/ems2024-988, 2024.

A useful resource for understanding and describing worldwide climatic patterns is the Köppen-Geiger (KG) climate classification system. The classification of climates suited for viticulture has been crucial to the wine sector, given the importance of climate in cultivating grapes for wine production. Wine production has come to be associated with Mediterranean climates due to the combination of the KG climate classification system and the geographic location of Europe's old-world wine areas. These climate types can also be found in the fynbos of South Africa, the Mallee of southern Australia, the matorral of Chile and Argentina, the chaparral and coastal valleys of western North America, and in the Mediterranean basin of Europe. But today, wine is produced in many different sorts of climates. Overall, a region's climate has a significant impact on wine production since it decides whether particular grape types can be grown there, greatly influencing the type of wine that can be produced and affecting the wine's quality.

This study examines the KG classification system's application to the most recent CMIP6 experiments. Using an ensemble of 14 global climate models and the WorldClim dataset, a baseline for the historical period 1970–2000 was established. Climate variability in winemaking regions is assessed using future estimates from 2041 to 2060, based on several scenarios of human radiative forcing (SSP2-4.5 and SSP5-8.5). The findings represent the most thorough record of past climate classifications for most wine regions globally, as well as prospective future changes to these categories.

Globally, temperate and arid zones (climate types C and B, respectively) are expected to undergo a substantial transition from a warm summer temperature to a hot summer climate. High temperatures can have a major impact on the grape development process. They may cause early ripening, alter the aromatic components in the grape berry, and perhaps change the acidity balance. Wine producers must modify their vineyard management practices in response to climate shifts and employ appropriate countermeasures to mitigate the negative effects of abiotic pressures on grape quality and vineyard health. These adaptation tactics could involve relocating to other microclimatic zones, adopting irrigation techniques, modifying canopy and soil management, or utilizing different variety-clone-rootstock combinations. Wine producers need to consider regional climate change projections to ensure the long-term sustainability of the environment and the socioeconomic landscape. This will help them make more informed decisions about vineyard management practices, and ultimately strengthen the wine industry's resilience and adaptability to the ongoing effects of climate change.

Acknowledgments: Research funded by National Funds by FCT under the project UIDB/04033/2020 and LA/P/0126/2020. Vine & Wine Portugal – Driving Sustainable Growth Through Smart Innovation, PRR e pelos Fundos Europeus Next Generation EU, no âmbito das Agendas Mobilizadoras para a Reindustrialização, Projeto n.º C644866286-011.

How to cite: Andrade, C., Fonseca, A., A. Santos, J., Bois, B., and V. Jones, G.: Worldwide Historical Shifts and Projections with CIMP6 Experiments for Köppen-Geiger Climate Classifications in Wine Regions, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-91, https://doi.org/10.5194/ems2024-91, 2024.

Understanding global plant phenology dynamics is essential for predicting ecosystem responses to climate variability. This study introduces a novel approach to analyse plant phenology dynamics across Köppen climate zones using the Normalised Daily Temperature Range (DTRT) and minimum daily relative humidity (R1) indices. By coupling these selected indices with phenology-related satellite data, we investigate the seasonality of plant development worldwide. We use global conventional temperature and humidity reports to explore how environmental factors influence phenological patterns across diverse ecosystems, from tropical rainforests to polar regions. The Köppen climate classification system serves as a framework for categorising climatic regions based on temperature, precipitation, and vegetation characteristics, facilitating a comprehensive analysis of regional climate variations and their impact on plant phenology. Integrating observed meteorological data and satellite imagery, we explore complex interactions between climate indices and vegetation dynamics. Satellite-derived metrics, such as the normalised difference vegetation index (NDVI), provide valuable insights into vegetation greenness and growth stages, complementing the meteorological data used to calculate DTRT and R1 indices. Our study, conducted on a global scale, focuses on identifying the start and end of the vegetation season and examining changes in seasonality across different Köppen climate zones. We hypothesise that DTRT and R1 indices can serve as standalone tools for determining these key phenological events and fill the gaps in satellite-derived data. By comparing DTRT and R1 indices with satellite NDVI data, we aim to assess their accuracy in capturing vegetation phenology dynamics globally. The comparative analysis of indices and satellite data allows a comprehensive understanding of how climate variability influences the timing and duration of the vegetation season. This research enhances our ability to predict ecosystem responses to climate change and offers valuable insights for ecosystem management and conservation efforts on a global scale. 

Funding: This work is supported by contract for the Implementation and Financing of Scientific Research Project NIO in 2024 No. 451-03-66/2024-03/200117 dated February 5, 2024, COST Action CA20108 - FAIR NEtwork of micrometeorological measurements (FAIRNESS) and Centre of Excellence One Health, Ministry of Science, Technological Development and Innovations 451-03-1524/2023-04/16 

Acknowledgements: Serbian micrometeorological measurements and phenological observations by Forecasting and Reporting Service for Plant Protection of the Republic of Serbia (PIS) are financed by the Ministry of Agriculture, Forestry and Water Management of the Republic of Serbia and Provincial Secretariat for Agriculture, Water management and Forestry of the Vojvodina province, Republic of Serbia. FAIRNESS FMP 2.0 portal is used as one of the sources of micrometeorological data.

How to cite: Firanj Sremac, A., Lalic, B., and Marcic, M.: Normalised DTR and Minimum Relative Humidity Across Köppen Climate Zones: Analysing Responses in Plant Phenology, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-426, https://doi.org/10.5194/ems2024-426, 2024.

As the Mediterranean region is affected by climate change, it is crucial to understand how the variability in meteorological parameters and human activities impacts the natural resources in agriculture. Higher temperatures, reduced precipitation and extreme events like droughts and floods are fundamental variables that contribute to a negative water balance in nature. Additionally, while intensive farming has increased agricultural productivity, concerns about its sustainability and the potential consequences for ecosystems have emerged. Developing natural-based solutions is necessary to address major challenges, including environmental degradation, water scarcity, loss of soil fertility and biodiversity.

This study focuses on integrated olive orchard agroecosystems management in Messenia regional unit, northwest Peloponnese, known for its rich agricultural heritage and olive oil production. Messenia has a Mediterranean climate, characterized by hot, dry summers and mild, wet winters, with a unique topography combining coastal plains and mountain area. In collaboration with local stakeholders we have developed two field experiments to monitor agrometeorological indicators and assess the current agricultural practices regarding soil and water management.: (i)The first experiment is being conducted in a hilly terrain orchard where we have applied a methodology to collect surface runoff and quantify soil erosion after rainfall events in three different treatments (use of herbicides, mowing of natural vegetation and cover crops seeding). (ii) The second experiment is being developed at a different orchard plant over flat terrain, where we are testing three different irrigation practices, namely: rainfed, irrigation based on common local practices and irrigation based on the phenological stages of olive trees. The agrometeorological conditions (e.g. ambient and soil temperature and humidity, potential evapotranspiration, vegetation properties) are monitored at both experiments with ground based instrumentation and airborne remote sensing. The three major aspects under study are soil characteristics, plant growth, and olive oil quality. First results indicate a difference of more than 30% in soil erosion rates for the different cover treatments. An improvement in oil quality without significant changes in olive oil content between rainfed and irrigated treatments is also found during the first year of the experimental study. Both experiments will remain active in the following years, and based on the results of our research we aim to consult local farmers on enhancing the resilience of olive tree cultivation and reducing the environmental footprint.

How to cite: Pantazis, C., Solomos, S., Maneas, G., Centrito, M., Marino, G., Roggero, P. P., Mihail, J., Fountoulakis, I., Kapsomenakis, J., Gkisakis, V., Nastos, P., Kourgialas, N., and Zerefos, C. S.: Agrometeorological assessment of olive cultivation practices in Messenia, Peloponnese, under climate change, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-107, https://doi.org/10.5194/ems2024-107, 2024.

Montenegro is located on the Balkan Peninsula. This country portrays a complex topography, and so various climate types are found, from alpine conditions in inland mountains to a Mediterranean climate in valleys and near the coast. The Mediterranean conditions allowed Montenegro to develop a viticulture heritage, which is becoming threatened by climate change. Most of the vineyards are located in the vicinity of the capital, Podgorica, where the temperature will certainly increase. In this sequence, the present study aimed to expose the climate change impacts on Montenegrin Viticulture, resorting to a high-resolution dataset CHELSA (≈ 1km). Temperature data from the weather station was compared to the CHELSA dataset for the historical period, revealing that the dataset is accurate. Thermal bioclimatic indices were analyzed for the historical period 1981-2010, and for the future period 2041-2070. Projections were ensembled for 5 climate models, and encompassed 3 Shared Socioeconomic Pathways, SSP1—2.6, SSP3—7.0, SSP5—8.5. The results revealed that, regardless of the SSP scenario, the temperature increase threatens Montenegrin viticulture, as the baseline conditions will be surpassed. Temperature increase will be major during the warmest quarter, which will be around 4 °C. Regarding the growing season, the average temperature from April to October, will reach 24 °C, which is above traditional thresholds for successful grape growing. The mean annual temperature will increase by more than 2 °C, and as a consequence, the growing season will be expanded, by more than 1 month, anticipating phenological events. During the historical period, the Winkler Index is 2530 °C, suitable for wine production, but in future, there will be excessive heat in grapevines, as the Winkler index will become higher than 3000 °C, increasing the risk of thermal and hydric stress. These findings are alarming, serving as a careful alert that adaptation measures should be applied in the short term, to guarantee the long-term sustainability and productivity of Montenegrin Viticulture.

Acknowledgments:
Research funded by National Funds by FCT – Portuguese Foundation for Science and Technology, under the project UIDB/04033/2020 and LA/P/0126/2020 (https://doi.org/10.54499/UIDB/04033/2020)
This research was funded by the MONTEVITIS project “Integrating a comprehensive European approach for climate change mitigation and adaptation in Montenegro viticulture”, funded by the European Union’s Horizon Europe—the Framework Programme for Research and Innovation (2021–2027)—under grant agreement nº 101059461

How to cite: Fernandes, A., Kovač, N., Fonseca, A., Fraga, H., Radonjić, S., Simeunović, M., Menz, C., Costafreda-Aumedes, S., and Santos, J.: Climate Change Impacts on Montenegrin Viticulture, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-137, https://doi.org/10.5194/ems2024-137, 2024.

Phenological observations are expensive and demanding in terms of manpower to monitor the vegetation stages. Therefore, satellite products have opened new possibilities for easier and more widespread data collection. Nowadays biomass estimations extensively rely on these tools, given their extensive spatial and temporal coverage, which are defined by indicators such as vegetation indices, which describe the biomass growth, canopy structure, vegetation health and even water management etc. However, the detection of flowering stages through remote sensing is less explored, with fewer established methods available.

This study investigates temporal phenological changes during the blooming period of the most widely cultivated oilseed crops in Hungary in 2021, specifically the sunflower (Helianthus annuus L.) and the winter-cultivated oilseed rape (Brassica napus L.). The objective is to characterize the blooming phase and dynamics of these two crop species utilizing various vegetation indexes and satellite-derived products. The investigation is conducted across seven distinct regions, using honey bees as bioindicators of the fields.

Methodologies outlined in prior scientific literature, focusing on the analysis of anthesis timing and duration in major nectar-producing crops utilizing Sentinel-1 SAR and Sentinel-2 optical products, serve as the basis for this research. Within each radius study areas, the parcel-averaged and smoothed daily time series were acquired. The estimation of the blooming phases was achieved through parcel smoothing methods using daily non-parametric local regression (loess) approach which showed better performance compared to the Savitzky-Golay (SG) algorithm. In our flowering detection analysis, we also examined the differences in the ascending and descending orbits and their combined results. In the case of oil seed rape, the NDVI index reached its maximum after flowering, while for sunflower it varied. Additionally, we investigated the outcomes of all polarization and method combinations within each crop type.

Our study enables the comprehension of temporal flowering patterns in bee pasture crops through the integration of SAR and optical measurements. Additionally, it supports the utilization of beehive scales to provide field-based reference data for estimating anthesis.

The research was funded by the National Multidisciplinary Laboratory for Climate Change, RRF-2.3.1-21-2022-00014 project. Project No. 993788 has been implemented with the support provided by the Ministry of Culture and Innovation of Hungary from the National Research, Development and Innovation Fund, financed under the KDP-2020 funding scheme.

How to cite: Vincze, C., Birinyi, E., Leelőssy, Á., Kristóf, D., Mészáros, R., and Kern, A.: Field-level analysis of phenological cycles and dynamics of sunflower (Helianthus annuus L.) and oil seed rape (Brassica napus L.) flowering within various regions of Hungary, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-415, https://doi.org/10.5194/ems2024-415, 2024.

Wireworms, the soil living larvae of several click-beetle species (Fam. Elateridae), are serious pests in various crops, e.g. vegetables, potatoes and maize, due to their feeding on underground plant parts. Controlling wireworm infestations in Europe has become increasingly challenging due to the lack of efficient insecticides and presumably the effects of reduced tillage and climate change. It is to be expected that rising temperatures will further enhance the population densities and spread of thermophilic species.

In the frame of the ACRP-project “RIMPEST¹”, the relationships between weather and wireworm damages in potatoes were investigated for an important potato production region in North-eastern Austria. An analysis was conducted using anonymised data on annual wireworm damages from 2002 to 2022, along with corresponding temperature and precipitation data. The resulting regression model calculates the damage level in potatoes in North-eastern Austria during late summer/autumn at the time of harvest, based on soil temperature sums from the previous months. The underlying significant positive correlation between soil temperatures and wireworm damages in the investigated region might be due to promoting effects of higher temperatures on the thermophilic species Agriotes ustulatus (Schäller) and A. brevis (Candeze).

By utilizing the model, farmers and extension workers can calculate a first forecast of the damage risk prior to potato harvest, making it a decision support tool for determining the optimal harvesting date. Additionally, the model approach can estimate future trends of wireworm infestation in potatoes in the respective region based on representative climate scenarios. First results indicate a clear increase in the risk of severe wireworm damages in potatoes in the period from 2031 to 2060. To ensure optimal performance in the future, the model approach should be continuously validated and calibrated with new data from further years.

[1] ACRP-13th Call Project RIMPEST (KR20AC0K17957) ("The effect of changing climate on potential risks from important insect pests on plant production in Austria and related adaptation options"). 

https://www.klimafonds.gv.at/report/acrp-13th-call-2020/

https://rimpest.boku.ac.at

How to cite: Hann, P., Trska, C., Kamptner, A., Eitzinger, J., and Wechselberger, K.: Forecasting regional wireworm damage levels in potatoes based on soil temperatures, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-405, https://doi.org/10.5194/ems2024-405, 2024.

Global warming is one of the most significant characteristics of climate change. Serbia is no exception; it was noted that the daily mean air temperature and the number of days with extreme weather conditions have increased. The tropical days that used to be common for the summer months recently have been registered in May and even April.

Extreme weather events can disrupt our usual perception of the time of occurrence of the development stages of pests and growth stages of plants. Since air temperature is the main trigger of plant and harmful organism development, a warm period occurrence earlier than usual in the spring could cause the earlier emergence of the pest and the earlier start of plant growing season.

Over the past fourteen years, meteorological conditions have been measured in the plant canopies as part of the Forecasting and Warning Service for Plant Protection of Serbia (PIS) monitoring system. Extremely high winter temperatures and early winter-spring transition compared to the region's climatology are recorded, affecting plant and pest phenology dynamics. This research is focused on effects registered in the moth family Tortricidae (Lepidoptera) and their host plants.

The occurrence of different stages for the codling moth (Cydia pomonella) and apples, the oriental fruit moth (Grapholita molesta) and peach, the plum fruit moth (Grapholita funebrana) and plum, and the grape berry moth (Lobesia botrana) and grapevine, were analyzed and their association with air temperature and season transition indices. The data used in the study are gathered through the PIS monitoring network. Biological data series are collected on production plantations where protection measures were regularly applied. Biofix data, as well as timing and population of adults, are gathered using pheromone traps. Eggs and larvae presence, as well as the growth stages of host plants, result from visual inspections in the orchards and vineyards. Depending on the species, 20-40 locations were analyzed annually for each pest for 2012-2024.

Our research aims to explore the impact of extreme winter temperatures and winter-spring transitions on the development of pests and host plants. Monitoring and understanding these effects is crucial for accurately forecasting and effectively managing adverse impacts on agriculture.

How to cite: Marcic, M., Lalic, B., Firanj Sremac, A., and Koci, I.: Impact of Early Winter-Spring Transition on the Development Dynamics of theMoth Family Tortricidae and Host Plants, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-826, https://doi.org/10.5194/ems2024-826, 2024.

In the scope of the ACRP-project RIMPEST¹ we tested prognosis models for thermophilic, economically relevant insect pests in agriculture in Austria. We focused on Diabrotica virgifera virgifera and Ostrinia nubilalis, as pests in corn as well as Helicoverpa armigera, Aphis fabae, Acyrtosiphon pisum and Myzus persicae as pests in vegetables.

The respective models collected via extensive systematic literature research, were further processed, tested, and validated using historical monitoring and weather data to choose models with the best fit for Austria for each investigated species.

For Diabrotica v.v. the zero-inflated Poisson mixture model (Falkner (2018) was chosen as best fit, since it was developed with Austrian monitoring data (2002 – 2015) and utilizes spatial data on corn crop abundance.

The best fitting prognosis model for O. nubilalis in Austria is the model by Maiorano and Donatelli (2014). Prediction of the flight peak of the first (=winter) generation of the bivoltine race adults has an R² of 0.324 (RMSE 8.424 days, n =35). For the flight peak of the univoltine race, a priori set to 560 degree-days in the model for testing, the R² is 0.288 (RMSE 8.694 days, n = 105).

For H. armigera, a model for prognosis of the development from egg to adult (Dalal and Arora, 2019). performed well calculating the full development of an individual during the season, but did not account for winter diapause and needs an additional model to set the first biofix per year for simulations. We will utilize our monitoring data to design a negative prognosis model for this purpose, which will predict the earliest day an immigrating H. armigera adult can be detected in Austria.

For the aphids two models per species were tested, either for aphid development (A. fabae, A. pisum and M. persicae) or a phenological model (A. pisum and M. persicae). Further testing of these models is still in progress.

----------------------

¹ ACRP-13th Call Project RIMPEST (KR20AC0K17957) ("The effect of changing climate on potential risks from important insect pests on plant production in Austria and related adaptation options").

https://www.klimafonds.gv.at/report/acrp-13th-call-2020/

https://rimpest.boku.ac.at

https://www.ages.at/en/research/project-highlights/rimpest

References:

Dalal, P.K./ Arora, R.: Model‑based phenology prediction of Helicoverpa armigera (Hübner) (Noctuidae: Lepidoptera) on tomato crop. Journal of Plant Diseases and Protection 2019, 126, S. 281-291.

Falkner, K.: Analysing the influences of climate and land use on the spread and abundance of the Western Corn Rootworm in Austria. In, Department of Economics and Social Sciences, Institute for Sustainable Economic Development. Vienna: University of Natural Resources and Life Sciences 2018, S. 133.

Maiorano, A./ Donatelli, M.: Validation of an insect pest phenological model for the European corn borer (Ostrinia nubilalis Hbn) in the Po Valley in Italy. Italian Journal of Agrometeorology 2014, 18, S. 43-50.

How to cite: Manhalter, S., Moyses, A., and Wechselberger, K.: Changes in vegetable and arable crop insect pest occurrence caused by climate change – models investigated in the scope of the ACRP-project RIMPEST1, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-298, https://doi.org/10.5194/ems2024-298, 2024.

Sustainable crop production will in future face further challenges from insect pests due to climate change. Rising temperatures will enable higher overwintering rates and accelerate the development of thermophilic insects, leading to increased damage risks for regional crop production systems. These changes pose problems for optimum timing of monitoring and control measures, which could be countered with improved and new prediction models.

Within the ACRP-Project RIMPEST^[1] new prediction models were developed for the European grapevine moth, Lobesia botrana (Denis & Schiffermüller) and the European grape berry moth, Eupoecilia ambiguella (Hübner) (Lepidoptera: Tortricidae) in Austria including monitoring data from 60 selected monitoring sites and measured weather data from adjacent reference weather stations in the period 1980 to 2023. Stepwise multiple linear regression (MLR) analysis was applied to generate prediction models for the first seasonal occurrence of the different developmental stages (egg, larvae, adult) of the first and second generation of L. botrana and E. ambiguella. As input data for the MLR analysis nine processed weather parameters, different calculation periods and the DOYs (day of year on which the first seasonal occurrence was observed) were used.

The performance evaluation of the six generated MLR models for predicting the different generations and developmental stages of L. botrana resulted in an R² of 0.51 to 0.92, a RMSE of 2.18 to 3.97 and an average prediction range of 1.90 days too early to 1.40 days too late. For E. ambiguella the validation resulted in an R² of 0.33 to 0.69, a RMSE of 3.48 to 4.15 and an average prediction range of 2.85 days too early to 1.00 day too early. The MLR models for E. ambiguella first generation egg and larvae were not sufficiently validated as too few datasets were available.

The implementation of the new MLR models for impact assessments under regional climate scenarios can help to determine the potential future risks of L. botrana and E. ambiguella occurrence in Austrian wine-growing regions. The inclusion of future observation data into the analysis, especially from years with extreme weather events, can further improve the prediction accuracy of the MLR models.

How to cite: Kolkmann, K., Blümel, S., Thaler, S., and Eitzinger, J.: Multiple linear regression models to predict seasonal occurrences of two important grapevine pest Lepidoptera in Austria, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-311, https://doi.org/10.5194/ems2024-311, 2024.

Global warming will modify the dynamics of thermophilic pest insect populations and their spread, which could raise the risk of crop damage and plant production. Long-term insect pest monitoring can provide important data for developing pest models, which can help to predict future pest risk trends in the face of climate change. Within the ACRP-project RIMPEST¹ ("The effect of changing climate on potential risks from important insect pests on plant production in Austria and related adaptation options") pest trends under crop land-use and climate scenarios by applying pest models are therefore investigated. Corresponding databases from monitoring programs for various insect pests of major crops are used for pest model development and testing for Austrian case study regions. To estimate the range of potential pest risks in the various Austrian crop growth regions in the future (2021-2050; 2071-2100), an ensemble of downscaled Austrian climate scenarios (ÖKS15) of two emission scenarios, RCP 4.5 and RCP 8.5, is used. Using validated pest algorithms on a site-specific and grid-based application reveals variable-sized shifts in pest phenology, depending on the climate region and the specified future time periods.

First results for the American grapevine leafhopper (Scaphoideus titanus), European grapevine/berry moths (Lobesia botrana and Eupoecilia ambiguella), and plum moth (Grapholita funebrana) indicate a significant response to climate change toward earlier first occurrence dates of relevant development stages, which partially coincides with shifted growing areas of the host plants. While hardly any changes are likely in the near future (2021-2050) compared to current conditions, a significantly earlier occurrence of the pests can be expected at the end of the century, which varies regionally and depending on the projection. On average, for example, European grapevine moths can be expected to appear around 4 days earlier (RCP 4.5) / 7 days earlier (RCP 8.5) than today.

The findings of the project should help practitioners and policymakers to develop future strategies for optimised cultivation and pest control options.

¹ACRP-13^th Call Project RIMPEST (KR20AC0K17957) ("The effect of changing climate on potential risks from important insect pests on plant production in Austria and related adaptation options"). https://www.klimafonds.gv.at/report/acrp-13th-call-2020/; https://rimpest.boku.ac.at

How to cite: Thaler, S., Kolkmann, K., Blümel, S., and Eitzinger, J.: Use of climate change scenarios for pest algorithms in Austria, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-302, https://doi.org/10.5194/ems2024-302, 2024.

In the context of climate change and globalisation, the risks for invasive species are increasing. One example of this is Spodoptera frugiperda (JE Smith), commonly known as the fall armyworm (FAW). The FAW originates from the tropical and subtropical regions of America and has spread to most continents worldwide in recent years. Since the FAW has recently also spread to the Mediterranean regions of Europe, the aim of this study was to analyse the potential susceptibility of Slovenian agriculture to this pest, with specific emphasis on maize (Zea mais). Additionally, the climate suitability was assessed for four possible natural enemies of FAW. The climate suitability of the past and future climate in Slovenia was evaluated in relation to the latest available data on the global occurrence of FAW and its natural enemies. The analysis was carried out on the basis of historical data and climate model projections for temperature and precipitation. The climate projections included 6 sets of regionally downscaled model results from the EURO-CORDEX project for the RCP4.5 and RCP8.5 scenarios. The results show that an increasing probability of FAW occurrence in Slovenia throughout the 21^st century, especially in the maize-growing areas of Slovenia with the largest areas under maize cultivation. The natural enemies whose climatological niches were calculated to be the most comparable to those of the FAW are parasiotids Telenomus remus and Trichogramma Pretiosum. The results of this study can serve as a tool for the possibilities of pre-emptive introduction of natural enemies of FAW to Slovenia, which is a method of biological pest control, in which the use of synthetic pesticides is replaced by the introduction and release of natural enemies of the pests.

How to cite: Žnidaršič, Z., Curk, M., Trdan, S., and Pogačar, T.: Exploring the climate suitability of Slovenia for the invasive species Spodoptera frugiperda (JE Smith), EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-116, https://doi.org/10.5194/ems2024-116, 2024.

How to cite: Baldi, M. and Biancolini, D.: Effects of climate change on wild pollinators: the case of butterflies in Central Italy, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-484, https://doi.org/10.5194/ems2024-484, 2024.

The complex and nonlinear characteristics of atmospheric dynamics, along with their high dimensionality and interconnections across several spatial and temporal factors, pose significant challenges in comprehending, modeling, and predicting hydroclimatic extreme events. Understanding complex systems such as the atmosphere requires establishing causal relationships; therefore, this study focuses on hydroclimatic extremes, including heat waves, droughts, and extreme precipitation, which continue to be emphasized in climate change projections. Hydroclimatic extreme events pose a significant threat to agricultural sustainability, impacting crop yields, public health, migration patterns and ecological balance. The present research delves into the spatial and temporal dynamics of extreme precipitation, droughts, and heatwaves, specifically analyzing their influence on corn and soybean yields. Moreover, we aim to discover the causal relationships between these extreme events and crop yields by employing cross convergent mapping (CCM). CCM is a technique that relies on nonlinear state space reconstruction and is capable of distinguishing between causality and correlation. In accordance with Takens’ embedding theory, the attractor is reconstructed by CCM using time series data. This reconstruction allows for the identification and measurement of causation through cross-mapping prediction. The study uses the Evaporative Demand Drought Index (EDDI) as a metric of agricultural drought, the Palmer Drought Severity Index (PDSI) as an indicator of hydrological drought, together with maximum air temperature, extreme precipitation, and data on corn and soybean yields. Beyond that, this investigation is carried out on rainfed agricultural lands in Iowa with the specific aim of elucidating the impacts of hydroclimatic extreme events. Agricultural sustainability research and the quantification of economic consequences and impacts of extreme events on agriculture will benefit significantly from the findings of this investigation.

How to cite: Baydaroğlu, Ö., Yeşilköy, S., and Demir, I.: A Causality Perspective on the Impact of Hydroclimatic Extremes on Crop Yields, EMS Annual Meeting 2024, Barcelona, Spain, 1–6 Sep 2024, EMS2024-291, https://doi.org/10.5194/ems2024-291, 2024.