Climate change in the 21st century is predicted to push ecosystems across ecological thresholds, potentially resulting in abrupt ecosystem change into new and irreversible states. Ecological theory proposes that non-linear biotic responses are the result of a complex interplay of feedbacks, thresholds and interactions that operate over decades to thousands of years. As a result, standard ecological research methods are generally unable to quantify key ecological dynamics that are relevant for forecasting abrupt ecological change and there is a critical need to integrate long-term ecological data with process-based models. This will result in improved forecasting of climate-change impacts on ecosystems at both local- to global-scales. Such studies will play a critical role in understanding the ‘intrinsic’ factors (e.g. climate-vegetation feedbacks) that can result in non-linear biotic responses to climate change. Sediments are natural data-loggers that preserve the remains of plants and animals over thousands of years. They provide a unique resource for answering current high priority questions related to predicting future ecosystem change because they are the only way to obtain empirical information relevant for understanding long-term ecological dynamics and functioning. In this project I will develop an interdisciplinary framework that integrates state-of-the-art process-based modelling with new high-quality palaeoecological information to quantify the factors that result in non-linear responses to climate change. I will apply the framework to a major vegetation transition in the past: the sclerophyll-rainforest transition in north-east Australia that occurred between 10 and 7 thousand years ago. I will develop this case study for proof-of-concept of a new interdisciplinary framework. This will result in a greater understanding of non-linear biotic responses to climate change.

Wood production depends on how effectively trees convert atmospheric CO2 into wood. Moreover, forests mitigate climate change through their net carbon uptake from the atmosphere. Both these forest functions are crucially dependent on tree carbon use efficiency (CUE), which is determined by gross primary production (GPP, photosynthesis at large spatial scales) and respiration. Although GPP is so far stimulated under recent climate change conditions, the effect of future climate on CUE is unclear due to the unknown response of plant respiration to more severe increases in temperature. It is thus necessary to identify the drivers of changes in CUE and to increase CUE to enhance wood production and carbon stocks under future climatic conditions. In light of the typical rotation lengths, forest managers need to be informed already today on which species will be optimally adapted in certain regions to a changing climate. Within this 2-year project, I will develop novel data-driven estimates of plant respiration, net primary production and tree CUE based on recent satellite-driven maps of tree living biomass, extensive databases of tree compartment respiration rates, and temperature datasets. Subsequently, I will detect spatial relationships between CUE and climate variables dependent on tree species in northern hemisphere boreal and temperate forests and predict the change in CUE in response to future climate by using a dynamic global vegetation model (DGVM) under different forest management scenarios. I have recently derived remote sensing based forest biomass products that will be the basis for this research. Prof. Dr. Thomas Hickler and his research group at the Senckenberg Biodiversity and Climate Research Centre (BiK-F) are experts in ecosystem modelling, thereby particularly using the LPJ-GUESS model, the DGVM that we will apply within this project. His connections to the modelling community and to forestry experts will facilitate the exploitation of our results.

Soil food webs process 90% of the terrestrial primary production and regulate the second largest carbon pool on Earth – soil organic matter. Soil food webs themselves are regulated by soil animals through changes in microbial functioning, detritus quality, and physical soil structure. However, neither drivers of soil food web structure and functions nor their effects on global biogeochemistry and carbon stabilisation are quantified across large environmental gradients. CARBONWEB addresses this challenge at the global scale and tests the following Key Hypotheses: (A) biotic controls of soil food web structure and functions increase under conditions promoting biological activity and nutrient limitation; (B) consumption of detritus by consumers in soil food webs increases the stable fraction of soil carbon across ecosystem types; (C) the effect of soil animals on multiple ecosystem functions increases with temperature, precipitation, and nutrient limitation, proportionally to the total energy flux in soil food webs; (D) the global net effect of soil animals on topsoil carbon is positive (>10% increase) and will increase with climate warming. To test my hypotheses, I will use (1) the first comprehensive global monitoring of soil animal communities in the framework of Soil BON, (2) an EU-wide survey and isotopic experiments on carbon stabilisation, (3) steady-state and dynamic food web modelling and AI-based animal image analysis approaches, and (4) geospatial extrapolations. My experience in soil macroecology, functional ecology, large-scale project coordination, and the established collaborative network will help to ensure this project is successful. I will describe and mechanistically model the status and trends of energy fluxes, animal biodiversity, and carbon pools in global topsoils. Results of the project will provide the first-ever global estimation of soil food web effects on soil functioning and facilitate long-term monitoring of soil biodiversity.

Environmental degradation due to land-use, over-exploitation and climate change rapidly erodes Europe’s unique biodiversity, resulting in irreversible loss of valuable resources both for ecosystem functions and for human well-being. However, despite the numerous monitoring and conservation efforts, our ability to predict and mitigate the extinction risk of wild populations remains limited. Assessing the temporal variation in genetic diversity and its environmental drivers represents a powerful approach to address this challenge, but incorporating it into conservation planning has been hindered by i) lack of affordable technology, ii) lack of interdisciplinarity, and iii) disconnection between fundamental research and applied conservation. BEEP will address these gaps by combining modern sequencing technologies for quantifying species temporal genomic erosion, with satellite observations of the earth for assessing the corresponding environmental change. By bridging diverse technological fields and scientific principles, BEEP will provide an applied predictive framework for species extinction risk in response to human pressure that can be directly utilised by major environmental organisations (IUCN, EEA, IPBES). I will showcase the power and importance of this approach using the European endemic and highly threatened mountain tea species (Ironwort), that are of significant conservation interest due to their traditional and emerging medicinal properties. I will achieve BEEP's objectives at SBiK-F (Senckenberg Biodiversity and Climate Research Centre), a world-class centre in interdisciplinary biodiversity research, ranging from earth observations from space to species evolutionary genomics.The proposed project will provide new research and training opportunities that will bring me in a very competitive position in order to successfully establish myself as a leading and interdisciplinary European researcher in the fields of biodiversity research and conservation.