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Das Klima bestimmt entscheidend das Auftreten, die Ausbreitung und Entwicklung von Schadorganismen. Weil die Temperatur die Entwicklung von Insekten massgeblich steuert, ist durch die globale Er-wärmung mit einer steigenden Befallsgefährdung von Kulturpflanzen durch Schadinsekten zu rech-nen. Ausgehend von Klimaszenarien, Verbreitungsdaten und den bekannten Umweltansprüchen von Schadinsektenarten verwenden wir diverse Modellierungsansätze, um die Entwicklung und künftige Verbreitung ausgewählter, landwirtschaftlich relevanter Schadinsekten vorherzusagen. Die bearbeiteten Fallbeispiele umfassen sowohl in der Schweiz etablierte Arten, wie auch gebietsfremde Arten, welche erst kürzlich eingeschleppt wurden und solche, die in der Schweiz noch nicht vorkommen aber aufgrund ihrer klimatischen Anforderungen demnächst zu erwarten sind. Die Ergebnisse bestätigen die sich abzeichnende Erhöhung des Schädlingsdrucks. Sie zeigen aber auch neue Perspektiven für die landwirtschaftliche Produktion auf, besonders aufgrund der Verschiebungen in der Standorteignung der Kulturpflanzen, der verlängerten Vegetationszeit und der Auswirkungen des Klimawandels auf das Pflanzenwachstum. Die erarbeiteten Szenarien bieten eine Entscheidungsgrundlage, die dazu dienen soll, die Risiken des Klimawandels rechtzeitig zu erkennen und zu steuern und andererseits die sich bietenden Chancen bestmöglich zu kapitalisieren. Die Umsetzung von verbesserten Früherkennungs- und Überwachungsmethoden, die Steigerung der Resilienz von Anbausystemen gegenüber klimatischen Veränderungen und die Anpassung von agronomischen Massnahmen werden unumgänglich sein, um die von Schadorganismen verursachten Ertragsausfälle zu minimieren. Dazu ist die frühzeitige, sachliche Information und Sensibilisierung der beteiligten Akteure entlang der gesamten Wertschöpfungskette zentral.

Large variability in N2O emissions from managed grasslands may occur because most emissions originate in surface litter or near-surface soil where variability in soil water content (θ) and temperature (Ts) is greatest. To determine whether temporal variability in θ and Ts of surface litter and near-surface soil could explain this in N2O emissions, a simulation experiment was conducted with ecosys, a comprehensive mathematical model of terrestrial ecosystems in which processes governing N2O emissions were represented at high temporal and spatial resolution. Model performance was verified by comparing N2O emissions, CO2 and energy exchange, and θ and Ts modelled by ecosys with those measured by automated chambers, eddy covariance (EC) and soil sensors on an hourly timescale during several emission events from 2004 to 2009 in an intensively managed pasture at Oensingen, Switzerland. Both modelled and measured events were induced by precipitation following harvesting and subsequent fertilizing or manuring. These events were brief (2–5 days) with maximum N2O effluxes that varied from Nm−2h−1 in early spring and autumn to > 3 mgNm−2h−1 in summer. Only very small emissions were modelled or measured outside these events. In the model, emissions were generated almost entirely in surface litter or near-surface (0–2 cm) soil, at rates driven by N availability with fertilization vs. N uptake with grassland regrowth and by O2 supply controlled by litter and soil wetting relative to O2 demand from microbial respiration. In the model, NOx availability relative to O2 limitation governed both the reduction of more oxidized electron acceptors to N2O and the reduction of N2O to N2, so that the magnitude of N2O emissions was not simply related to surface and near-surface θ and Ts. Modelled N2O emissions were found to be sensitive to defoliation intensity and timing which controlled plant N uptake and soil θ and Ts prior to and during emission events. Reducing leaf area index (LAI) remaining after defoliation to half that under current practice and delaying harvesting by 5 days raised modelled N2O emissions by as much as 80 % during subsequent events and by an average of 43 % annually. Modelled N2O emissions were also found to be sensitive to surface soil properties. Increasing near-surface bulk density by 10 % raised N2O emissions by as much as 100 % during emission events and by an average of 23 % annually. Relatively small spatial variation in management practices and soil surface properties could therefore cause the large spatial variation in N2O emissions commonly found in field studies. The global warming potential from annual N2O emissions in this intensively managed grassland largely offset those from net C uptake in both modelled and field experiments. However, model results indicated that this offset could be adversely affected by suboptimal land management and soil properties.

It is expected that the development of plants and insects will be accelerated by global warming, resulting in an earlier occurrence of phenological stages in the future as compared to today. For plants, this could lead to a higher exposure to climatic shocks (late frosts in spring, and critical high temperatures in summer) and changes in the incidence of insect pests. Assessing the implications of such shifts in phenology is important to be able to devise, where necessary, means for reducing biotic and abiotic risks in plant production. In this contribution we present an analysis of the potential impacts of climate change on the risk of late frost and damages to fruits caused by critically high temperatures in apple orchards across Switzerland. We further discuss the possible effects of climate change on the appearance of the codling moth (Cydia pomonella L.), the key apple pest in many areas of the world. To conduct the analysis, we run carefully calibrated phenological models for different apple cultivars and the codling moth, feeding them with updated, transient climate change scenarios covering 1980-2100 developed for Switzerland on a 2 km x 2 km spatial-resolution grid. The climate scenarios represent three different emissions pathways allowing for consideration of a wide range of future climates. The results are discussed in a broader context by comparison with findings from other countries.

Global warming is expected to accelerate the development of plants and insects leading to earlier occurrence of phenological stages than under today’s climate. This can alter the exposure of plants to extreme climate events and further change the synchrony between host plants and pest insects. Assessing the implications of earlier development for the exposure to risks is necessary to inform adaptation. In this contribution we present an analysis of potential impacts of climate change on (i) the risk of early frost in apple orchards and damages to apple fruits due to critically high temperatures, (ii) the time of apple picking, and (iii) the potential of damages caused by the codling moth (Cydia pomonella L.), for three different apple cultivars in Switzerland. To this aim, carefully calibrated phenological models for apple trees and the codling moth are run with updated climate change scenarios. The climate scenarios comprises three different emissions scenarios. To underline the utility of phenological models and data for informing society, we show how this assessment is integrated into a recent initiative to implement National Climate Services in Switzerland in response to the Global Framework for Climate Services issued by the World Meteorological Organisation.

Ende 2015 hat der Bund das National Centre for Climate Services (NCCS) ins Leben gerufen, welches in Form eines Netzwerkes agiert. Aufgabe des NCCS ist die Koordination, Erarbeitung und Verbreitung von Klimadienstleistungen als Grundlage für die Anpassung an den Klimawandel. Dabei handelt es sich um Informationen über das vergangene, aktuelle und zukünftige Klima und die Folgen des Klimawandels. Sie helfen Behörden, Politik und Wirtschaft klimakompatible Entscheidungen zu treffen. Das NCCS bündelt die Klimadienstleistungen des Bundes, entwickelt gemeinsam neue massgeschneiderte Lösungen und initiiert und fördert den Dialog zwischen den verschiedenen Akteuren und Akteurinnen, welche Klimadienstleistungen nutzen. Im ersten Forum im Dezember in Bern stellt sich das NCCS selber vor. Was sind Funktionen und Tätigkeiten des Netzwerks? Der Anlass hat zum Ziel, Anbieter und Anwender auf allen Ebenen zu vernetzen sowie interaktiv Ideen und Bedürfnisse auszutauschen. Zusammen mit dem am Nachmittag stattfindenden alljährlichen Symposium «Anpassung an den Klimawandel» werden die enge Verknüpfung und Synergien

Temperature is a main climatic driver of plant phenology and the dominant abiotic factor directly affecting insect pests. Global warming is therefore expected to accelerate the development of plants and insects alike. In the case of multivoltine pest species, it was shown that higher temperatures lead to the appearance of additional generations toward the end of the warm season (Stöckli et al., 2012), which also has implications for pest management. The same effect was shown for the timing of flowering termination of apple trees (Stöckli and Samietz, 2015), the time when a pest can attack a fruit. In practice, however, much would depend on whether plant and pest phenology remain synchronized or not. Focusing on Switzerland, in this contribution we present an analysis of potential impacts of climate change on plant and pest phenology. and their interlinkages at the example of the apple tree (Malus pumila L.) and the codling moth (Cydia pomonella L.), a fruit crop of economic relevance worldwide. Key developmental stages of the apple and the codling moth were simulated by means of two heat summation models. The models were calibrated with lab and field data from Switzerland and subsequently run with observed weather data and various climate change scenarios. The time period between flowering termination and the harvest of the apples was compared to the appearance of the second and third generation of codling moth larvae to study the interlinkage between host and pest. To illustrate the potential for practical applications of the phenology models, we used spatial temperature data of Switzerland to produce risk maps that can serve as a basis for further studies and decision support.

Extreme events such as frost, drought or excessive heat occurring during a critical plant stage can cause extensive and sometimes irreversible damages to agricultural production. Tools for gauging the occurrence of extreme events can thus play an important role in the context of agricultural decision problems. Agroclimatic indicators offer simple means to discriminate between favourable and unfavourable conditions. Their evaluation can be supported by dedicated software tools, even though this typically requires local installation of the proposed solution. Here we present webXTREME, a new web-based tool to characterize the occurrence and intensity of extreme events in agriculture (available through www.modextreme.org/webxtreme, accessed on 6 April, 2016). Objectives, which motivated its development, were: ease of access (available from any internet-connected device), simple setup, universal compatibility (no installation required), extensibility and the possibility to offer regular updating services. webXTREME was designed to help scientists and practitioners with various backgrounds to configure the solving algorithms by taking into account plant-specific thresholds and relevant time windows during the growing seasons of arable crops, grasslands and woody species. Graphical display of the results enables comparative assessments, either in space or in time. webXTREME was implemented using Shiny, an open-source web application framework for R. This allows combining the computational power of dedicated R functions with modern web technologies. webXTREME can easily be integrated into other modelling platforms (e.g. BioMA, http://bioma.jrc.ec.europa.e

Process-based models (PBMs) are important tools for predicting and understanding the impacts of climate change on grassland systems. The models should be able to simulate changes in sward nutritional value (NV) over time in order to better understand the interactions between grasslands and ruminant nutrition. Changes in the NV of forage may not only alter animal performance but also the need for other feeds, the management and productivity of the system, the quality of final products and the environmental impacts of production. Climate change is expected to affect the NV of grasslands by affecting plant physiological processes, and via effects on species composition. An increase in temperature may cause an increase in NDF and lignin content of forages, thus reducing digestibility by domestic herbivores. On the other hand, under high CO2, analyses on both temporary and permanent grasslands indicate a strong increase in soluble sugar content, which increases the energetic value and the aptitude for ensiling of grass. Conversely, a decrease of the CP content in grass dry matter up to 30% is observed. The reduction in the forage protein and energy content lowers the rumen microbial synthesis and availability of microbial proteins for ruminant growth and production, and may also lead to increased production of methane (a greenhouse gas) by methanogens in the rumen. Ruminants kept in extensive systems that are based on low protein forages may be sensitive to these negative effects. On the contrary, an increase in soluble sugar and decrease in CP content would rather be positive for ruminants in intensive high protein forage systems. Modelling grassland NV is often based on variables describing the energy and protein content of forage. However, a wide range of variables are used to define forage NV in experimental data, presenting challenges for modellers. Further complication arises from the dissimilar feeding regimes used across the different production systems in countries and regions. The aim of this work was to review the extent to which current grassland PBMs are capable of characterising the NV of forage species in grassland swards in relation to projected climate change. This includes the identification of the modelling approaches used, the key characteristics of the forages represented and the production systems these models have been developed for.

Climate change with increasing climate variability is likely to alter risks in agricultural production. The effectiveness of using weather derivatives to hedge against drought risks for rain-fed grain maize production was investigated for current (1981-2003) and future (2070- 2100) climates in Switzerland. The climate change scenario was extrapolated from results of a regional climate model (HIRHAM4) based on the IPCC A2 emission scenario. In addition, a sensitivity analysis was performed by varying the mean and variance of the initial probability space for the seasonal precipitation sum. Profits and risks with and without hedging were compared using the analogy of the value-at-risk measure (VaR), i.e., a quantile-based measure of risk. A Monte Carlo chain composed of different models was used, with each model consisting of functions translating weather variables into the stochastic distributions for grain yield and economic returns. Depending on location, hedging reduced VaR to a variable degree under both current and future climatic conditions, with a considerable basis risk due to spatial heterogeneity of precipitation. The results also showed that hedging might provide a valid risk transfer since loading of 90 to 240% of the fair premium can be paid to obtain a hedged situation with improved outcomes relative to the business-as-usual reference. However, due to the uncertainty attached to climate scenarios and a strong bias in precipitation scenarios for the European alpine region, application of weather derivatives would require continuous re-equilibration and recalculation of the premiums. Depending on local conditions, the fair premium of a specific contract for hedging against weather risks in grain maize production may vary by a factor of two to four over the 70-year period considered. This represents a substantial uncertainty for both the underwriter (farmer) and the institution writing the contract.

International audience; We improved a process-oriented biogeochemical model of carbon and nitrogen cycling in grasslands and tested it against in situ measurements of biomass and CO2 and CH4 fluxes at five European grassland sites. The new version of the model (PASIM) calculates the growth and senescence of aboveground vegetation biomass accounting for sporadic removals when the grassland is cut and for continuous removals when it is grazed. Limitations induced by high leaf area index (LAI), soil water deficits and aging of leaves are also included. We added to this a simple empirical formulation to account for the detrimental impact on vegetation of trampling and excreta by grazing animals. Finally, a more realistic methane emission module than is currently used was introduced on the basis of the quality of the animals' diet. Evaluation of this improved version of PASIM is performed at (1) Laqueuille, France, on grassland continuously grazed by cattle with two plots of intensive and extensive grazing intensities, (2) Oensingen, Switzerland, on cut grassland with two fertilized and nonfertilized plots, and (3) Carlow, Ireland, on grassland that is both cut and grazed by cattle during the growing season. In addition, we compared the modeled animal CH4 emissions with in situ measurements on cattle for two grazing intensities at the grazed grassland site of Laqueuille. Altogether, when all improvements to the PASIM model are included, we found that the new parameterizations resulted into a better fit to the observed seasonal cycle of biomass and of measured CO2 and CH4 fluxes. However, the large uncertainties in measurements of biomass and LAI make simulation of biomass dynamics difficult to make. Also simulations for cut grassland are better than for grazed swards. This work paves the way for simulating greenhouse gas fluxes over grasslands in a spatially explicit manner, in order to quantify and understand the past, present and future role of grasslands in the greenhouse gas budget of the European continent.

International audience; We apply a simulation model in order to quantify the patterns of carbon and nitrogen cycling within European grasslands. We map the fluxes of CO$_2$, N$_2$O and CH$_4$ exchanged with the atmosphere as controlled by climate and management conditions. We distinguish between grazing and cutting practice. Because geo-referenced management information for grasslands does not exist at the scale of Europe, we develop a new and robust set of rules defining some management variables. We then perform realistic simulations in term of N fertilization using a national level data set. The model results at European scale are compared with agricultural statistics (yield, animal stocks), which shows that our very simple management calculation is reasonably realistic. We also compare the simulated seasonal cycle of grassland phenology as calculated by PASIM with remote sensing observations from the EOS-TERRA-MODIS satellite, which shows a good general agreement. Emission factors for soil N$_2$O and grazing animals CH$_4$ emissions are diagnosed from the model runs and shown to be comparable to those of previous experimental surveys. We investigate impact of N fertilization on NPP and C storage potential, N$_2$O emissions by soils and CH$_4$ emissions by ruminants. We conclude that, for different time horizon, CH$_4$ and N$_2$O sources are lower than the potential sink of CO$_2$, on a carbon equivalent basis. This result is independent of fertilization intensity but assumes that the current soil C stocks are below the long-term equilibrium values.