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Ecosystem services through restoration: Improving restoration outcomes through trait-based modelling

Subject Area Ecology and Biodiversity of Plants and Ecosystems
Term from 2016 to 2019
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 282567997
 
Final Report Year 2021

Final Report Abstract

Mediterranean-type ecosystems (MTEs) appear to be among the ecosystems that are most at risk from multiple global change factors (e.g. climate, nitrogen deposition), which are likely to exacerbate contemporary ecosystem degradations. Consequently, the provision of ecosystem services provided by MTEs (e.g. carbon sequestration, water supply) that are particularly crucial for the high regional population is at risk. Ecosystem restoration projects increasingly aim at improving multiple ecosystem services, and therefore we require a fundamental understanding of the link between ecosystem composition, related functions and services, and influencing environmental drivers. Measurable species traits (e.g. plant height, specific leaf area, seed mass) have been recognised as a quantifiable link between ecosystem composition and ecosystem functions, which provide the base for the provision of ecosystem services. However, until now, most studies have typically focused on a single ecosystem service and therefore cannot assess trade-offs among services caused by interactions among them or by shared environmental factors. In addition, the effects of global change factors on ecosystem functions and thus services may interact, which has been neglected in most studies on MTEs so far. Thus, traitbased research that addresses trade-offs among multiple ecosystem services under the impact of multiple environmental factors to reliably support future restoration outcomes, is still missing. The project aimed at assessing the linkage between plant traits and the provision of ecosystem services and trade-offs among them under the impact of environmental change to improve future restoration outcomes in MTEs, world-wide. We started closing this gap by integrating trait-based empirical research and process-based simulation modelling. We developed the eco-hydrological simulation model ModEST complementing an ongoing large-scale restoration project in Western Australia (the Ridgefield experiment). The model describes the fate of individual plants that are characterised by different traits. By simulating a whole plant community, we can calculate the coupled dynamics of vegetation, nutrients and water and quantify ecosystem functioning for a given species composition under varying climatic and soil conditions. In a full factorial design of different plant trait compositions, we systematically quantified ecosystem functions and trade-offs among them under current and future climate as well as for different environmental contexts. Our results show that multifunctionality cannot fully be achieved because of trade-offs among functions that are attributable to sets of traits that affect functions differently. Our measure of multifunctionality was increased by higher levels of planted species richness under current, but not future climatic conditions. In contrast, single functions were differently impacted by increased plant diversity. In addition, we found that trade-offs and synergies among functions shifted with climate change and the environmental context, in particular mean annual precipitation, mean annual temperature, and soil texture. Our findings imply that restoration ecologists will face a clear challenge to achieve their targets with respect to multifunctionality not only under current conditions, but also in the long-term. However, once ModEST is parameterized and validated for a specific restoration site, managers can assess which target goals can be achieved given the set of available plant species and site-specific conditions. It can also highlight which species combinations can best achieve long-term improved multifunctionality due to their trait diversity. Thus, our model will aid in improving restoration of MTEs in Australia and globally.

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