Modelling of climate-sensitive pests in plant health

Klimasensitive Schadorganismen sind Arten, deren Risiko einen Schaden zu verursachen sich aufgrund der vorhergesagten klimatischen Veränderungen voraussichtlich erheblich verändern wird. Damit stellen sie eine besondere Herausforderung für die Pflanzengesundheit dar. Zur Vorhersage des Etablierungs- und Ausbreitungspotenzials dieser Schadorganismen ist eine Bewertung unter verschiedenen Umwelt- und Managementszena­rien unerlässlich. Ein effizientes Werkzeug zur Unter­suchung des Risikos klimasensitiver Schadorganismen (SO) sind prozess-orientierte Simulationsmodelle. Im Rahmen des Projektes,,ProgRAMM“ wird ein solches Modell, das auf Grundlage artspezifischer physiologischer Parameter und Verbreitungseigenschaften arbeitet, entwickelt. Mit diesem Modell wird es möglich sein, die o.g. Vorhersagen und Szenarioanalysen zu realisieren und langfristig einen übertragbaren, verallgemeinerten Open-Source-Modellrahmen als Standardverfahren zur Unterstützung von pflanzengesundheitlichen Risikoanalysen klimasensitiver SO zu etablieren. Dabei steht beson­ders im Vordergrund, dass das Modell leicht erweiterbar ist und sich leicht mit einzelnen Wirtspflanzen, aktu­ellen Klimadatensätzen sowie neuen An-/Abwesenheitsdaten der SO koppeln lässt. Die Ergebnisse des Modells werden in Form von Verbreitungs- und Risikokarten grafisch dargestellt. Diese Karten dienen der verbesserten Abschätzung und Darstellung der wirtschaft­lichen und ökologischen Risiken durch die Schadorganismen in Risikoanalysen. Zusätzlich kann durch die Identifizierung von Hochrisikogebieten für die Ansiedlung von SO, die Planung von Monitoring-Aktivitäten unterstützt werden. Das Modell wird open-source gehalten und um verschiedene Untermodelle sowie artspezifische Funktionen und Parametrisierung erweiterbar sein, damit die Übertragbarkeit auf möglichst viele Schadorganismengruppen (Pilze, Insekten, Milben, Nematoden, Bakte­rien) sichergestellt ist.Climate-sensitive pests are those whose risk of causing damage is likely to change significantly due to predicted climatic changes. They therefore pose a particular challenge to plant health. In order to predict the establishment and spread potential of these pests, an assessment under various environmental and management scenarios is essential. Process-oriented simulation models are an efficient tool to investigate the occurrence and spread of climate-sensitive pests. In the project ‘ProgRAMM’ (Proactive phytosanitary risk analysis through modelling and monitoring: adaptation to long-term risks caused by climate-sensitive pests) such a model based on species-specific physiological parameters and distribution characteristics is being developed. With this model the above mentioned predictions and scenario analyses can be carried out. A transferable, generalized open-source modelling framework will be established as a standard procedure to support plant health risk analyses (PRA) of climate-sensitive pests. A particular focus is on the fact that the model is easily extensible and that it can be easily coupled with a different set of additional host plants, plant databases, different climate data sets as well as new presence/absence data of pests. The results of the model are presented graphically in the form of distribution and risk maps. The results can be used in PRAs to better assess the economic and ecological risks of a pest. In addition, the high-risk areas for the occurrence of pests will be identified to support the planning of efficient monitoring activities. The open source license along with the modular nature of the model components will ensure transferability to pest groups such as fungi, insects, mites, nematodes and bacteria. This will also enable the extension of the model by different sub-models as well as by species-specific functions and parameterization

Spatial and temporal changes of spring temperature, thermal growing season and spring phenology in Germany 1951–2015

Climate change has a strong impact on vegetation dynamics and the relationship between temperature changes and shifts in plant development is well known. However, temperature does not change homogeneously and high spatial and temporal variabilities are possible. For a 65-year period from 1951–2015, we examined trends of mean air temperatures and bioclimatic parameters such as the onset of thermal growing season and two relevant phenological stages in Germany. We focused our analysis only on statistical significant trends. In order to compare them for the same spatial and temporal resolution, gridded datasets were used. From 1951–2015 spring air temperature (March-May) increased by 1.9 K. In the same time the average onset of thermal growing season started 20 days earlier and the beginning of cherry flowering and leaf unfolding of silver birch was advanced by 11 and 13 days, respectively. Nevertheless, a high spatial variability of trends was detected for all parameters. Strongest shifts were more pronounced in coastal areas of Germany and the regional investigation showed significantly stronger trends for North Germany than for South Germany. The study confirmed a strong synchronisation of the temporal and spatial changes in air temperature and the investigated bioclimatic parameters.Peer Reviewe

Summary for Policy Makers: Intergovernmental Panel on Climate Change Special Report Renewable Energy Sources (SRREN)

The Working Group III Special Report on Renewable Energy Sources and Climate Change Mitigation (SRREN) presents an assessment of the literature on the scientific, technological, environmental, economic and social aspects of the contribution of six renewable energy (RE) sources to the mitigation of climate change. It is intended to provide policy relevant information to governments, intergovernmental processes and other interested parties. This Summary for Policymakers provides an overview of the SRREN, summarizing the essential findings. The SRREN consists of 11 chapters. Chapter 1 sets the context for RE and climate change; Chapters 2 through 7 provide information on six RE technologies, and Chapters 8 through 11 address integrative issues