In the semi-arid regions of Eastern Austria, windbreaks are essential for reducing wind velocity (WV) and grass reference and actual evapotranspiration (Et0, Eta), thereby influencing yields. This case study examines the effects of two windbreak systems: 1) a hedgerow-based wind protection system (WPS) and 2) a strip intercropping experiment(SICE)with variable row widths in a maize-soybean intercropping setup. Micrometeorological data were collected at both sites, including wind velocity, wind direction, air temperature, global radiation, and relative humidity at multiple heights. The WPS reduced wind velocity by 0.8-1.1 m s-1 (2 m height) and 0.6-0.8 m s-1 (1 m height) leeward of the hedge compared to a 10 m reference height. At the SICE, reductions ranged from 0.1-1.2 m s-1 (2 m) and 0.2-0.5 m s-1 (1 m). Relative wind reduction effects (WRE) reached 34-41% (WPS) and 31-56% (SICE). A hedgerow coefficient (triangle f) was used to standardize the WRE by hedgerow height and distance in different systems. Et0 decreased by 0.6-0.7 mm d-1 near the WPS, while Eta rose by 0.2-0.5 mm d-1 due to improved water availability. At the SICE, Et0 increased by 0.9-1.7 mm d-1, and Eta showed varied responses. Overall, windbreaks can enhance water use efficiency and support sustainable landscape design in semi-arid agriculture.

Wireworms within the genus Agriotes (Coleoptera: Elateridae) can cause substantial damage to agricultural crops. The vertical movements of these pest insects in the soil make the timing of control measures a difficult task. The forecast model SIMAGRIO-W utilizes soil temperature and moisture data to predict the migration of Agriotes wireworms to the upper soil layer. The model distinguishes between two risk levels: low risk (less than 30% of the wireworm population in the upper soil layer) and high risk (more than 30%), which are considered adequate for practical purposes. In German field sites, the model demonstrated an 80% success rate across four soil types. The SIMAGRIO-W model was tested under the warm and dry climate in eastern Austria. The validation process revealed an overall accuracy of just 46%, primarily due to the fact that SIMAGRIO-W assumes a maximum activity level for wireworms at 11 degrees C. However, high activity levels were observed at soil temperatures of up to 26 degrees C at the experimental sites. The discrepancy in the prediction power of the model between the German and Austrian field sites may be explained by differences in temperature tolerance between the Agriotes species occurring in eastern Austria (e.g. A. ustulatus) and in western Germany (e.g. A. obscurus). Our findings demonstrate that the thermal preferences of different wireworm species must be taken into account to make the SIMAGRIO-W model a widely applicable decision support tool for predicting vertical movements of Agriotes wireworms. Die Larven des Drahtwurms (Agriotes, Coleoptera: Elateridae) k & ouml;nnen erhebliche Sch & auml;den an landwirtschaftlichen Kulturen verursachen. Aufgrund ihrer vertikalen Wanderbewegungen im Boden ist das Timing von Regulierungsma ss nahmen gegen den Sch & auml;dling schwierig. Das Prognosemodell SIMAGRIO-W nutzt Daten zur Bodentemperatur und -feuchtigkeit, um die Wanderung von Drahtw & uuml;rmern der Gattung Agriotes in die obere Bodenschicht vorherzusagen. Das Modell unterscheidet zwischen zwei Risikostufen: geringes Risiko (weniger als 30% der Drahtwurmpopulation in der oberen Bodenschicht) und hohes Risiko (mehr als 30%), die f & uuml;r praktische Zwecke als ausreichend angesehen werden. Auf deutschen Standorten zeigte das Modell eine Erfolgsquote von 80% in vier Bodentypen. In der vorliegenden Studie wurde das Modell nun unter dem warmen und trockenen Klima Ost & ouml;sterreichs getestet. Die Validierung ergab eine Gesamtgenauigkeit von lediglich 46%. Dies ist haupts & auml;chlich darauf zur & uuml;ckzuf & uuml;hren, dass SIMAGRIO-W eine maximale Aktivit & auml;t der Drahtw & uuml;rmer bei 11 degrees C annimmt. An den Versuchsstandorten wurden jedoch hohe Aktivit & auml;tswerte bei Bodentemperaturen von bis zu 26 degrees C beobachtet. Die unterschiedliche Vorhersagekraft des Modells an den deutschen und & ouml;sterreichischen Versuchsstandorten l & auml;sst sich durch die unterschiedliche Temperaturtoleranz der in Ost & ouml;sterreich (z. B. A. ustulatus) und Westdeutschland (z. B. A. obscurus) vorkommenden Agriotes-Arten erkl & auml;ren. Um das SIMAGRIO-W-Modell zu einer breit anwendbaren Entscheidungshilfe f & uuml;r die Vorhersage der vertikalen Bewegungen von Agriotes-Drahtw & uuml;rmern zu machen, m & uuml;ssen demnach k & uuml;nftig die Temperaturpr & auml;ferenzen bzw. -toleranzen der verschiedenen Drahtwurmarten ber & uuml;cksichtigt werden.

This article reports the outcomes of the FAIRNESS COST Action (CA20108), a coordinated European initiative aimed at advancing micrometeorological data toward compliance with the FAIR (Findable, Accessible, Interoperable, Reusable) principles. The article presents three core achievements: (i) a structured inventory of urban and rural micrometeorological networks across Europe; (ii) the design and deployment of the FAIR Micrometeorological Portal, providing a digital infrastructure for data discovery, access, and standardized metadata description; and (iii) methodological guidance for quality control, gap detection, and gap filling tailored to the specific characteristics of micrometeorological time series. By providing both technical infrastructure and community-driven standards, the FAIRNESS outputs advance micrometeorological data from isolated datasets into coherent, reusable resources. Beyond technical developments, the FAIRNESS systematically addressed gaps in knowledge and skills within the micrometeorological community. A key outcome is the beginner-oriented book Micrometeorological Measurements - An Introduction for Beginners, which provides structured guidance on measurement design, instrumentation, data management, and quality assurance. In parallel, FAIRNESS implemented a comprehensive capacity-building programme, including summer schools, workshops, and short-term scientific missions, targeting both domain-specific competencies and transferable skills such as FAIR data stewardship, interdisciplinary collaboration, and practical problem solving. Together, these efforts contribute to strengthening the long-term usability of micrometeorological data and fostering a more integrated, FAIR-oriented research culture within the European meteorological community.

Wireworms, the subterranean larvae of click beetles (Elateridae), cause substantial economic losses, damaging a wide array of crops and thereby reducing both the quantity and quality of agricultural yield. The efficacy of different countermeasures, notably non-chemical approaches, can vary considerably depending on the species of wireworm encountered and the affected crop system. Surveys of wireworms in damaged crops were conducted in Austria for the first time, with the aim of determining which species most frequently occur as pests. Over a sixyear period, a total of 15,786 wireworms were collected directly from damaged crops at 189 agricultural sites across the country. The wireworms were identified, descriptive associations between the occurrence of the species causing damage and abiotic and environmental factors were determined and mapped according to Austrian landscapes. Species-specific occurrence and significance as pests varied across ecoregions and were influenced by the type of crop affected. In the Pannonian region, Agriotes ustulatus (Schaller, 1783) was the most significant pest species in potato cultivation. Its presence was positively correlated with higher st degrees C, elevated soil pH, and increased clay and silt content. Conversely, in the Bohemian Massif, potato crops were predominantly affected by Hemicrepidius niger (Linnaeus, 1758), for the first time identified as a relevant pest species in Austria. Its occurrence was linked to cooler, more humid conditions, lower soil pH, and higher sand and humus content. These findings provide a basis for future development of region- and species-specific wireworm control strategies, thereby serving as valuable baseline data for distribution and assessment models.

Austria is experiencing increasingly frequent and prolonged drought periods as well as a rising number of heat days, both of which adversely affect agricultural productivity. The magnitude of these impacts depends on crop-specific growing periods and stress tolerances. Here, we assess how projected climate conditions during 1990-2039, assuming the shared socio-economic pathway SSP3-7.0 for the future period, influence yield expectations for winter wheat, spring barley, soybean, maize, potatoes, and grassland in Austria.Meteorological forcing is derived from the high-resolution General Circulation Model "Climate Change Adaptation Digital Twin", developed by the European Centre for Medium-Range Weather Forecasts. The data are statistically downscaled to a spatial resolution of 250 m and daily temporal resolution using Quantile Delta Mapping, with an observation-based in-house reference dataset for the historical period 1990-2019. Crop phenology, soil water balance, and combined heat and drought stress are simulated using the Agricultural Risk Information System. Phenological stage entry dates are computed from accumulated excess temperatures calibrated against near-surface air temperature observations and satellite-based remote sensing data for the years 2020, 2021, and 2023.The projections indicate increasing levels of crop stress accompanied by enhanced interannual variability. Winter wheat is least affected by combined heat and drought stress due to its relatively early maturity. However, drought and heat extremes lead to substantial yield reductions across all modeled crops in approximately half of the projected years. Overall, potential benefits of warmer temperatures during early growing stages are outweighed by increasing heat and drought stress later in the season.

Continuous long-term simulations of an ensemble of nine crop models covering the 1961-2080 period was employed to assess the expected impacts of climate change on the crop yield and water use for distinct crop rotations (CRs) in Europe. In this study, the likelihood of changes in two differently managed CRs (conventional and alternative) involving four important field crops (winter wheat, spring barley, silage maize, and winter oilseed rape) was assessed. The conventional agricultural practice (CR1) included only mineral fertilization with the removal of crop residues after harvest. The alternative agricultural practice (CR2) included cover crops and the application of mineral and organic fertilizers, with crop residues retained in the field. The simulations covered six sites in five European countries (M & uuml;hldorf and M & uuml;ncheberg in Germany, Ukkel in Belgium, & Oslash;dum in Denmark, Milhostov in Slovakia and Lednice in Czechia) based on two distinct soil profiles (universal soil and site-specific soils). The universal soil was the same across all the sites, while the site-specific soils were typical of each region. Eight transient climate change scenarios (4 general circulation models (GCMs) under representative concentration pathways (RCPs) 2.6 and 8.5) were used to capture the possible evolution of future climatic conditions. Compared with those during the 1962-1990 period, the ensemble projections for the 2051-2080 period indicated average increases in the annual yields of all crops of 0.7 t/ha (RCP 2.6) and 0.8 t/ha (PCP 8.5) under both CRs and soil types. Under most climate change scenarios, the crop model ensemble projections of the winter wheat and winter oilseed rape yield increases agreed for CR2 but not for CR1. For spring barley, the simulated increase was more sporadic, with no significant difference between CR1 and CR2. In regard to silage maize, the changes in the simulated yields depended on site-specific climatic conditions. If the same varieties were planted in the future, yield reductions would be expected, except at the & Oslash;dum site, where the silage maize growth conditions would remain satisfactory, regardless of the CR and soil type. The results indicated greater cover crop biomass production, which could affect the long-term soil water balance and groundwater replen- ishment. The crop model ensemble further indicated a greater spatial variability in the yield can be expected, which is likely caused by the expected increase in the air temperature and not by the expected increase, or even decrease, in the total precipitation and increases in the actual evapotranspiration under climate change at all sites. This trend was greater under CR2 and could affect the long-term soil water balance and soil regime in the case of rainfed agriculture.

Extreme weather events caused by climate change, such as drought and heavy rainfall, will further increase in Central Europe in the near future. Resilient crop production requires in-depth knowledge of soil moisture (SM), its spatial and temporal variability and the dynamics of agriculturally used land. In the current study, different SM estimation methods, including measurement and simulation-based methods, were evaluated over a 17-ha experimental arable crop field with respect to their abilities to capture the spatial and temporal SM dynamics of within-field areas and their related uncertainty and spatial representativeness. The high-spatial resolution in-situ topsoil moisture measurements (50 m grid) were compared with the estimated SM from satellite-based remote sensing (S1ASCAT) and the simulated SM from three different crop water balance models (Agricultural Risk Information System [ARIS], AquaCrop and DSSAT). The evaluation revealed that the spatial variability in the experimental field obtained from the reference could not be captured by the alternative methods investigated because of the limitations of the grid size-related soil map information. Nevertheless, the analysis revealed a very good temporal correlation of SM dynamics with the field area average across all approaches, with AquaCrop and ARIS at a soil depth of 0-10 cm and S1ASCAT soil-water index 05 achieving a R2 and a Kling-Gupta efficiency >0.80. These results indicate the added value of complementary methods for estimating SM to reduce spatial and temporal uncertainties in the estimated topsoil water content.

The 10-year effects of organic fertilization have been shown to enhance crop yields and contribute to sustainable agricultural productivity, although the extent of these benefits can vary depending on specific conditions and management practices. To investigate the impact of different organic fertilization approaches, the present study examined the effects of livestock-keeping and stockless organic fertilization systems on the yield and yield variability of lucerne and market crops (such as grain maize, spring barley, field pea, winter rye, winter wheat after lucerne (WWL), and winter wheat after peas (WWP)) in Eastern Austria over a 10-year period. The study tested three organic fertilization systems with continuous application of organic fertilizers as follows: FS1: without livestock, only lucerne green manure (GM); FS2: without livestock, lucerne green manure and municipal compost (GM+MC); and FS3: with livestock, lucerne forage use and farmyard manure application (FU+FYM). The study found that the dry matter (DM) of lucerne and the grain yield of market crops distinctly varied from year to year, with higher productivity observed during years with more favorable weather conditions. Moreover, the 10-year application of organic fertilizers, especially GM+MC and FU+FYM, increased the grain yield of all studied market crops except maize and field peas in comparison with GM. The simplified soil surface nitrogen (N) balance estimation revealed large differences between the fertilization systems. The GM treatments showed a highly positive N balance (196-374 kg N ha-1 a-1) due to N retention in the aboveground biomass of lucerne and assumed minimal gaseous ammonia losses (GM and GM+MC) as well as high N input via compost fertilization (GM+MC). Regarding yield stability, the study found that organic fertilization systems only affected the variability of DM in WWL, with the highest variability observed in the FU+FYM system. In conclusion, the study suggests that GM+MC (FS2) and FU+FYM (FS3) have potential for improving crop productivity and nutrient values in organic farming, based on findings from a 10-year investigation. Moreover, during the study period, no adverse effects of a diversified farming system without livestock (FS2: GM+MC) were observed during the study period compared to a manure-based farming system with livestock (FS3: FU+FYM).

In the course of climate change, the framework conditions for agricultural production will change significantly. The ability of the soil to absorb water quickly and efficiently while at the same time storing as much water as possible for plants to use is a prerequisite for maintaining future agricultural production potential. The aim of this study was to investigate the application of recycled brick sand in agricultural soils with regard to its water absorption and storage capacity and thus to improve the efficiency of water utilisation. The influence of different precipitation intensities on the water storage capacity was analysed. In order to determine the influence of brick sand on the soil water balance, an experiment was carried out with nine small lysimeter systems. The lysimeters were all filled with soil samples from a vineyard in eastern Austria, whose soil has a high sand fraction and low clay mineral content. Three lysimeters were used as a reference and contained no brick sand. In three others, a mixture of soil sample and 10 % brick sand was used and in three others a mixture of soil sample and 30 % brick sand was applied. A 3-phase test was then carried out. The first phase was used to set a volumetric water content that was as constant as possible in all samples. The second phase was the simulation of a 10-millimetre precipitation event, followed by the third phase, the simulation of a 20-millimetre precipitation event. During the precipitation simulation, the amount of water corresponding to the precipitation intensity was applied to the lysimeter systems and the volumetric water content of the samples was recorded. Control values were determined using soil moisture sensors. The results showed that the addition of brick sand enabled the soil to store more water over time than the sample without brick sand. The simulations also showed that the amount of brick sand added made a difference in how the water storage capacity changed. Shortly after the rainfall simulation, the lysimeters with 30 % brick sand were able to store the water better. Towards the end of the precipitation simulation, the difference in stored water between the lysimeters with 30 % brick sand content and those with 10 % brick sand content became smaller, and in the 20 millimetre rainfall simulation, the lysimeters with 10 % brick sand content stored more water from halfway through the observation period. The results showed that the use of brick sand as a measure to improve the soil water balance has a high potential, however, the amount of brick sand applied must be adapted to the soil to be treated. These adjustments concern parameters such as grain size distribution and pore distribution, as these have a decisive influence on the water storage capacity.

Scaphoideus titanus Ball, 1932 (Hemiptera: Cicadellidae) is the main vector of Grapevine flavescence dor & eacute;e phytoplasma (FDp), causing the economically important grapevine yellows disease flavescence dor & eacute;e in Europe. Effective management of this disease relies on vector control and the uprooting of infected grapevines. By controlling the S. titanus third nymphal stage (N3), the spread of FDp can be prevented. In Austria, yearly monitoring of S. titanus nymphs in different wine-growing regions is necessary to determine the best time for control. The recent phenology changes of S. titanus make monitoring scheduling more difficult and propose the use of an accurate forecasting model. The present study aimed to test existing forecasting models for their accuracy and applicability to predict the first seasonal occurrence of the first nymphal stage (N1) of S. titanus and to develop new prediction models for N1 and N3 in Austria for the first time. Monitoring data from 2013 to 2020 from six different wine-growing areas in Austria were analysed. The existing forecasting models examined in this study predicted the first seasonal occurrence of N1 on average 3.3 days too early or 5.8 days too late, whereas the newly developed multiple linear regression model (MLR) for N1 predicted the first seasonal occurrence on average 3.4 days too early. The newly developed model for N3 predicted the first occurrence on average 6.6 days too early. To continuously improve the multiple linear regression models additional datasets, in particular from years with extreme weather events, should be included in the analysis.

Climate change will cause new challenges for sustainable crop production, as increasing temperatures may accelerate the development of thermophilic insect pests and promote their spread and overwintering capacities. Improved or new forecasting models to determine the potential future temporal and spatial shift in the occurrence of the European grapevine moth, Lobesia botrana (Denis and Schiffermüller) and the European grape berry moth, Eupoecilia ambiguella (Hübner) (Lepidoptera: Tortricidae) could help to better assess these future risks in Austrian wine-growing regions. Additionally, the timing of monitoring and control measures for both these pest species could be optimised to limit crop damages. In this context, prediction models for Lobesia botrana and Eupoecilia ambiguella were generated using long-term monitoring data (1980 to 2022) from 60 selected monitoring sites in 4 federal states in Austria, which had been collected using two different monitoring methods. Prediction models for the first seasonal occurrence of the different developmental stages (egg, larvae and adult) of the first and second flight/generation of both of the grape moth species were generated by applying stepwise multiple linear regression (MLR) analysis. The validation results showed high prediction accuracy for all six newly generated MLR models for L. botrana and for two out of six newly generated MLR models for E. ambiguella (R2 > 0.6; RMSE < 4.0; | BIAS | < 2.5). Depending on the developmental stage and generation of L. botrana, the validation results displayed an average prediction range of 0.89 days too early to 0.95 days too late. For E. ambiguella the predictions were on average 2.85 days too early to 0.20 days too late. To further improve model prediction accuracy, additional datasets should be included in the analysis, especially those from years in which extreme weather events occurred.

Lately, the prices of photovoltaic (PV) technology, including modules and inverters, have significantly dropped, making it more economically feasible to use PV power for heating water in homes. Although thermal energy storage (TES) has the potential to balance energy supply and demand, it remains largely underexplored. TES solutions may have a key role in dealing with the adverse effects of the dynamically growing share of electricity generated by photovoltaic (PV) systems on electricity networks. This research explored the potential of implementing a novel technological approach in conjunction with PV usage in Austria and Hungary, aiming to encourage the adoption of economical energy storage solutions and lessen energy dependence. This study aimed to investigate the joint use of TES and PV systems in Austria and Hungary, specifically using a 3.5 kW quasi-sine inverter and an electric water heating appliance for households with a capacity of 200 liters, as examples. According to the results of the research, the tested 200-liter domestic electric water heating system can store an average of more than 16 kWh of heat energy per day during the summer months, with a maximum water temperature increase (Delta T) of up to 53 degrees C during this period. The research is innovative and practical, as it explores the application of this solution to assess the seasonal energy-saving potential of this method of sensible heat storage in the contexts of Austria and Hungary.

Maize is affected by changing growing and crop management conditions under ongoing climate change, posing potential production risks in the future. This study analyzes maize growing conditions in Northern Vietnam by utilizing the AGRICLIM agrometeorological indicator model. The climate projections are sourced from a global circulation model, supplemented by a regional climate model for two emission pathways (RCP4.5 and RCP8.5) spanning from 1951 to 2100. The three main local maize growing seasons (winter, spring, and forage maize season) were meticulously analyzed across four distinct time slices, encompassing annual, seasonal, and monthly scales. The results reveal that future agrometeorological conditions will generally become more extreme compared to current conditions. However, the calculated increase in heat stress days, heavy precipitation events, and drought stress days for maize shows varying changes across the specific maize growing seasons. For instance, drought and heat stress conditions may occur more frequently during the spring and forage maize seasons, while the risk of soil erosion and nitrogen leaching may rise in the winter and forage maize seasons. These findings will support the development of adaptation strategies under more adverse weather conditions for maize growing systems in Northern Vietnam.

Wireworms within the genus Agriotes (Coleoptera: Elateridae) can cause substantial damage to agricultural crops. The vertical movements of these pest insects in the soil make the timing of control measures a difficult task. The forecast model SIMAGRIO‐W utilizes soil temperature and moisture data to predict the migration of Agriotes wireworms to the upper soil layer. The model distinguishes between two risk levels: low risk (less than 30% of the wireworm population in the upper soil layer) and high risk (more than 30%), which are considered adequate for practical purposes. In German field sites, the model demonstrated an 80% success rate across four soil types. The SIMAGRIO‐W model was tested under the warm and dry climate in eastern Austria. The validation process revealed an overall accuracy of just 46%, primarily due to the fact that SIMAGRIO‐W assumes a maximum activity level for wireworms at 11°C. However, high activity levels were observed at soil temperatures of up to 26°C at the experimental sites. The discrepancy in the prediction power of the model between the German and Austrian field sites may be explained by differences in temperature tolerance between the Agriotes species occurring in eastern Austria (e.g. A. ustulatus) and in western Germany (e.g. A. obscurus ). Our findings demonstrate that the thermal preferences of different wireworm species must be taken into account to make the SIMAGRIO‐W model a widely applicable decision support tool for predicting vertical movements of Agriotes wireworms.

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. [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

The organic matter stored in soils is a major carbon pool with fundamental importance for the global atmospheric carbon balance. Its decomposition contributes not only to the emission of greenhouse gases into the atmosphere but also to the release of minerals that serve as nutrients for plants growing in these soils. SOC is an indicator of soil fertility, reflecting the influences of agricultural practices on this property. Using crop models, the amount of soil organic carbon (SOC) can be simulated under the assumption of different climate scenarios and different agricultural practices. The conventional agricultural practice in Czechia includes short crop rotations of mainly cereals and oil-seed rape, mineral fertilisation and removal of crop residues for technical and energy use. However, the conventional approach is often associated with soil degradation and constant depletion of soil carbon stocks. Based on the standard crop rotation method, we compared the conventional practice (CR1) to an alternative practice (CR2), in which more effort is made towards stabilising soil carbon stocks by including cover crops in the rotation, organic fertilizers and leaving crop residues in the field. We used an ensemble of crop models (APSIM, DAISY, DSSAT, HERMES, and MONICA) to assess the carbon loss from two typical agricultural soils (Chernozem and Cambisol) at three locations in Czechia under current and future climate conditions (RCP 8.5, as represented by five global climate models). The ensemble simulations revealed that using CR2 could lead to an average increase in the SOC content by 15.427 kg/ha for Chernozem and 12.624 kg/ha for Cambisol until 2080. With the use of CR1 the SOC values on average decreased by 34.462 kg/ha for Chernozem and 24.096 kg/ha for Cambisol until 2080. The 1990 value was taken as the SOC reference level. Furthermore, both the increase (CR2) and decrease (CR1) amounts SOC stabilised after 2050. As such, even at the cost of high levels of nitrogen fertilisation and the associated risk of nitrogen leaching (CR2), the additional carbon that can be stored in soils is limited. The differences due to the different climate models are negligible in the case of CR1, while in the case of CR2, the different climate scenarios (baseline vs. future) yielded different SOC equilibrium levels, with a lower level (by 4.400 kg/ha on average) under the RCP 8.5 scenario for both soils. The results showed that carbon can be sequestered by increasing organic inputs. The crop models predicted that CR2 could lead to a higher SOC content, which occurs at the cost of high manure application levels and increased risk of nitrogen leaching.

The export of agrochemicals and their transformation products (TPs) following their application in the agricultural fields poses a threat to water quality. Future changes in climatic conditions (e.g. extreme weather events such as heavy rainfall or extended dry periods) could alter the degradation and mobility of agrochemicals. In this research, we use an integrated modelling framework to understand the impact of extreme climate events on the fate and transport of the agrochemical S-Metolachlor and two of its TPs (M-OXA, Metolachlor Oxanilic Acid and M-ESA, Metolachlor Ethyl Sulfonic Acid). This is done by coupling climate model outputs to the Zin-AgriTra agrochemical reactive transport model in four simulation scenarios. 1) Reference (2015-2018), 2) Very dry (2038-2041), 3) Very wet (2054-2057) and 4) High temperature (2096-2099) conditions of a selected RCP8.5 based regional climate scenario. The modelling framework is tested on an agricultural catchment, Wulka, in Burgenland, Austria. The model results indicate that 13-14 % of applied S-Metolachlor is retained in the soil, and around 85 % is degraded into TPs in the different scenarios. In very dry and high-temperature scenarios, degradation is higher, and hence, there is less S-Metolachlor in the soil. However, a large share of formed M-OXA and M-ESA are retained in the soil, which is transported via overland and groundwater flow, leading to a build-up effect in M-OXA and M-ESA river concentrations over the years. Though a small share of S-Metolachlor and TPs are transported to rivers, their river export is affected by the intensity and amount of rainfall. The very wet and high-temperature scenarios show higher S-Metolachlor and TP concentrations at the catchment outlet due to higher river discharge. The reference scenario shows higher river peak concentrations associated with higher overland flow caused by measured hourly rainfall compared to disaggregated daily precipitation data in the other scenarios.

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-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

Zusammenfassung Das Thema Landnutzung und Klima berührt Akteur_innen mit unterschiedlichen Zielsetzungen, die sowohl Synergien erzeugen, als auch miteinander in Konkurrenz stehen. Die Land- und Forstwirtschaft, das produzierende Gewerbe, die Freizeitwirtschaft, der Verkehr, Siedlungen, Infrastrukturausbau und der Naturschutz sind aktive Gestalter. Die Stadt- und Raumplanung, Naturschutz-, Forst- und Landwirtschaftsgesetzgebung stellen den Handlungs- und Lenkungsrahmen her. Klima- und Umweltkrisen, deren Dynamik teilweise von Antriebskräften außerhalb der Landnutzung herrührt, können existierende Zielkonflikte verschärfen oder neue herbeiführen (Plieninger et al., 2016). Viele wissenschaftliche Disziplinen sind mit dem Thema befasst, von den Natur- und Umweltwissenschaften über die Wirtschafts- und Sozialwissenschaften bis hin zu den technischen Wissenschaften.