WP1: Grassland Dynamics

Prof. Dr. Nina Buchmann and Yi Wang

Institute of Agricultural Sciences, ETH Zürich

Permanent grasslands provide a broad set of ecosystem services (ES), which include both marketable ES (e.g., yield quantity and quality) and non-marketable ES (e.g., biodiversity, GHG fluxes, soil carbon sequestration, pollination, weed suppression, nitrate leaching, aesthetics). ES show synergies (i.e., positive coupling of their response to human or natural impacts) and trade-offs (i.e., negative coupling of their respective response) with each other, and also vary temporally. All ES are strongly affected not only by management, plant diversity, and environmental conditions such as soil characteristics and climate, but also by extreme events (e.g., drought, heatwave, late freeze) and compound extreme events (e.g., drought and heatwave).

In WP1, we will focus on how extreme and compound extreme events affect the provision of ES by temperate permanent grasslands under different management intensities and with different plant diversity. This overarching question will be answered with different tasks:

  • the establishment of a benchmark set of ES with different management intensities and plant diversity as well as the intra- and inter-annual variability of ES provision (Task 1.1),
  • the quantitative characterization of magnitude, frequency, and duration of extreme and compound extreme events (Task 1.2), and
  • the assessment of how extreme and compound extreme events impact the provision of ES (Task 1.3).

In Task 1.1, we will compile a benchmark dataset of ES and their temporal variability for permanent grasslands in Central Europe based on published literature, open-access databases, and our own past and ongoing research projects. This benchmark dataset will serve as a basis for the risk assessment in WP2, and as input into the agent-based model of WP4, as well as additional information for assessing natural and social insurances in WPs 2 and 3, and in the dialogue with stakeholders (WP5).

In Task 1.2, we will analyze existing high-resolution time-series data of atmospheric and soil climate variables (e.g., temperature, precipitation, vapor pressure deficit, soil moisture), measured since more than 15 years at three grasslands in Switzerland (Swiss FluxNet, 30min averages) and at sites across Central Europe (Fluxnet, national weather services; 30min to hourly averages), as well as at sites used in Task 1.1. Extreme events will be defined using the upper or lower 1st, 5th, or 10th percentiles, and their magnitude, frequency, and duration will be evaluated using time-series analysis and extreme value statistics. This characterization of climate variables will also serve as input to WPs 2 and 4 to assess the occurrence of climate-related risks.

In Task 1.3, we will assess the impact of extreme and compound extreme events on the provision of ES based on our results from Tasks 1.1 and 1.2. The impacts of extremes on ES, in addition to management and plant diversity, will be analyzed using both traditional statistical models and machine learning algorithms. We will also identify which climate impact on ES is the most relevant, and value plant diversity to reduce the impact of extremes, as well as investigate feedback of extreme events on management strategies. This information will then be used as input into WPs 2 to 5.