Past and future impacts of land-use changes on ecosystem services in Austria.

Environmental and socio-economic developments induce land-use changes with potentially negative impacts on human well-being. To counteract undesired developments, a profound understanding of the complex relationships between drivers, land use, and ecosystem services is needed. Yet, national studies examining extended time periods are still rare. Based on the Special Report on land use, land management and climate change by the Austrian Panel on Climate Change (APCC), we use the Driver-Pressure-State-Impact-Response (DPSIR) framework to (1) identify the main drivers of land-use change, (2) describe past and future land-use changes in Austria between 1950 and 2100, (3) report related impacts on ecosystem services, and (4) discuss management responses. Our findings indicate that socio-economic drivers (e.g., economic growth, political systems, and technological developments) have influenced past land-use changes the most. The intensification of agricultural land use and urban sprawl have primarily led to declining ecosystem services in the lowlands. In mountain regions, the abandonment of mountain grassland has prompted a shift from provisioning to regulating services. However, simulations indicate that accelerating climate change will surpass socio-economic drivers in significance towards the end of this century, particularly in intensively used agricultural areas. Although climate change-induced impacts on ecosystem services remain uncertain, it can be expected that the range of land-use management options will be restricted in the future. Consequently, policymaking should prioritize the development of integrated land-use planning to safeguard ecosystem services, accounting for future environmental and socio-economic uncertainties.

ECORISK2050: An Innovative Training Network for predicting the effects of global change on the emission, fate, effects, and risks of chemicals in aquatic ecosystems.

By 2050, the global population is predicted to reach nine billion, with almost three quarters living in cities. The road to 2050 will be marked by changes in land use, climate, and the management of water and food across the world. These global changes (GCs) will likely affect the emissions, transport, and fate of chemicals, and thus the exposure of the natural environment to chemicals. ECORISK2050 is a Marie Sklodowska-Curie Innovative Training Network that brings together an interdisciplinary consortium of academic, industry and governmental partners to deliver a new generation of scientists, with the skills required to study and manage the effects of GCs on chemical risks to the aquatic environment. The research and training goals are to: (1) assess how inputs and behaviour of chemicals from agriculture and urban environments are affected by different environmental conditions, and how different GC scenarios will drive changes in chemical risks to human and ecosystem health; (2) identify short-to-medium term adaptation and mitigation strategies, to abate unacceptable increases to risks, and (3) develop tools for use by industry and policymakers for the assessment and management of the impacts of GC-related drivers on chemical risks. This project will deliver the next generation of scientists, consultants, and industry and governmental decision-makers who have the knowledge and skillsets required to address the changing pressures associated with chemicals emitted by agricultural and urban activities, on aquatic systems on the path to 2050 and beyond.

Phyllopertha horticola (Coleoptera: Scarabaeidae) larvae in eastern Austrian mountainous grasslands and the associated damage risk related to soil, topography and management.

The soil-dwelling larvae of several Scarabaeidae species (white grubs), like the cockchafer (Melolontha melolontha) and the garden chafer (Phyllopertha horticola), are serious pests in European cultivated grassland, reducing grass yield and destroying the turf by root-feeding. Nevertheless, the factors responsible for the development of large grub populations and the associated damage risk are poorly understood. The objectives of the study were to survey grub densities in grassland sites with different damage histories and find correlations with environmental and management variables. Data on grub densities were collected at 10 farms in the eastern Austrian Alps in September and October 2011. At each farm, one recently damaged site (high risk) and one site at which grub damage had never been observed by the farmers (undamaged site = low risk; each site: 500 m(2)) were sampled. All sites were dominated by P. horticola (99% of 1,422 collected individuals; maximum density 303 grubs/m(2)), which indicates that grub damage there is mainly caused by that species. Recently damaged sites tended to higher grub densities than undamaged sites. However, 3 out of 10 undamaged sites harbored high grub populations as well. Humus content together with the depth of the A-horizon significantly explained 38% of P. horticola grub density variance, with highest densities in deeper humus-rich soils. The risk of grub damage was positively connected to the humus content and negatively related to the cutting frequency. For the investigated mountainous grassland sites, these results suggest an important role of humus for the development of high grub densities and an effect of management intensity on grub damage.

Determination of areas with the most significant shift in persistence of pests in Europe under climate change.

BACKGROUND: This study aimed to estimate the impact of climate change on the ranges of crop pest species in Europe. The organisms included in the study were species from the family Tortricidae (Cydia pomonella, Lobesia botrana) and the family Pyralidae (Ostrinia nubilalis), Chrysomelidae beetles (Leptinotarsa decemlineata, Oulema melanopus) and species from the family Aphididae (Ropalosiphum padi, Sitobion avenae). Climate conditions in the year 2055 were simulated using a subset of five representative global circulation models. Model simulations using these climate change scenarios showed significant shifts in the climatic niches of the species in this study. RESULTS: For Central Europe, the models predicted a shift in the ranges of pest species to higher altitudes and increases in the number of generations (NG) of the pests. In contrast, in the southern regions of Europe, the NG is likely to decrease owing to insufficient humidity. The ranges of species are likely to shift to the north. CONCLUSION: Based on the ensemble-scenario mean for 2055, a climate-driven northward shift of between 3° N (O. nubilalis) and 11° N (L. botrana) is expected. The areas that are most sensitive to experiencing a significant increase in climate suitability for future pest persistence were identified. These areas include Central Europe, the higher altitudes of the Alps and Carpathians and areas above 55° N.

Impacts of climate change and variability on European agriculture: results of inventory analysis in COST 734 countries.

Climate plays a fundamental role in agriculture because of to its influence on production. All processes are regulated by specific climatic requirements. Furthermore, European agriculture, based on highly developed farming techniques, is mainly oriented to high quality food production that is more susceptible to meteorological hazards. These hazards can modify environment-genotype interactions, which can affect the quality of production. The COST 734 Action (Impacts of Climate Change and Variability on European Agriculture), launched in 2006, is composed of 28 signature countries and is funded by the European Commission. The main objective of the Action is the evaluation of possible impacts arising from climate change and variability on agriculture and the assessment of critical thresholds for various European areas. The Action will concentrate on four different tasks: agroclimatic indices and simulation models, including review and assessment of tools used to relate climate and agricultural processes; evaluation of the current trends of agroclimatic indices and model outputs, including remote sensing; developing and assessing future regional and local scenarios of agroclimatic conditions; and risk assessment and foreseen impacts on agriculture. The work will be carried out by respective Working Groups. This paper presents the results of the analysis of the first phase of inventory activity. Specific questionnaires were disseminated among COST 734 countries to collect information on climate change analysis, studies, and impact at the European level. The results were discussed with respect to their spatial distribution in Europe and to identify possible common long- and short-term strategies for adaptation.

Effect of Estimated Daily Global Solar Radiation Data on the Results of Crop Growth Models.

The results of previous studies have suggested that estimated daily globalradiation (RG) values contain an error that could compromise the precision of subsequentcrop model applications. The following study presents a detailed site and spatial analysis ofthe RG error propagation in CERES and WOFOST crop growth models in Central Europeanclimate conditions. The research was conducted i) at the eight individual sites in Austria andthe Czech Republic where measured daily RG values were available as a reference, withseven methods for RG estimation being tested, and ii) for the agricultural areas of the CzechRepublic using daily data from 52 weather stations, with five RG estimation methods. In thelatter case the RG values estimated from the hours of sunshine using the ångström-Prescottformula were used as the standard method because of the lack of measured RG data. At thesite level we found that even the use of methods based on hours of sunshine, which showedthe lowest bias in RG estimates, led to a significant distortion of the key crop model outputs.When the ångström-Prescott method was used to estimate RG, for example, deviationsgreater than ±10 per cent in winter wheat and spring barley yields were noted in 5 to 6 percent of cases. The precision of the yield estimates and other crop model outputs was lowerwhen RG estimates based on the diurnal temperature range and cloud cover were used (mean bias error 2.0 to 4.1 per cent). The methods for estimating RG from the diurnal temperature range produced a wheat yield bias of more than 25 per cent in 12 to 16 per cent of the seasons. Such uncertainty in the crop model outputs makes the reliability of any seasonal yield forecasts or climate change impact assessments questionable if they are based on this type of data. The spatial assessment of the RG data uncertainty propagation over the winter wheat yields also revealed significant differences within the study area. We found that RG estimates based on diurnal temperature range or its combination with daily total precipitation produced a bias of to 30 per cent in the mean winter wheat grain yields in some regions compared with simulations in which RG values had been estimated using the ångström-Prescott formula. In contrast to the results at the individual sites, the methods based on the diurnal temperature range in combination with daily precipitation totals showed significantly poorer performance than the methods based on the diurnal temperature range only. This was due to the marked increase in the bias in RG estimates with altitude, longitude or latitude of given region. These findings in our view should act as an incentive for further research to develop more precise and generally applicable methods for estimating daily RG based more on the underlying physical principles and/or the remote sensing approach.