Applications are invited for a PhD fellowship/scholarship at Graduate School of Natural Sciences, Aarhus University, Denmark, within the Biology programme. The position is available from May 2025 or later.

Title:
Forecasting the near-future spread of Novel Ecosystems under alternative environmental scenarios.

Research area and project description:
Biotic assemblages across the globe are transforming at unprecedented rates, a phenomenon documented in the IPBES Global Assessment. This accelerating change stems from a complex interplay of direct and indirect anthropogenic drivers, mirroring the "Great Acceleration" in socio-economic and Earth System trends since the mid-20th century. As these pressures continue, they give rise to Novel Ecosystems (NEs)—natural or semi-natural ecosystems with species compositions and ecological functions that diverge significantly from historical baselines due to human influence.

The emergence and spread of NEs present risks and opportunities for global biodiversity and ecosystem function. Effective management and stewardship of these ecosystems are crucial for sustaining nature's contributions to humanity. However, achieving this requires an advanced, mechanistic understanding of how contemporary drivers of ecological change will reshape the biosphere in the near future.

This modelling-focused PhD project will focus on developing computationally intensive, high-resolution global forecasts of near future NE spread and assessing the resulting impacts on biodiversity and climate-related ecosystem functions. Specifically, the candidate will:

1. Develop and apply Dynamic Global Vegetation Models (DGVMs): By integrating high-dimensional datasets, including species distributions, plant functional traits, and climate projections, the candidate will use DGVMs to simulate shifts in dominant plant functional types under a range of climate and socio-economic scenarios. The project will focus on modelling ecosystem transitions to capture how NEs reshape the biosphere at global scales.

2. Assess climate system interactions: The project will investigate the feedbacks between NE spread and climate by quantifying changes in key biosphere-climate interactions—such as carbon storage, albedo, and evapotranspiration. These interactions are essential for understanding the role of NEs in global climate resilience and informing potential mitigation strategies.

3. Explore scenario-based simulations: Using Shared Socioeconomic Pathways (SSPs) and IPCC climate projections, the candidate will simulate NE expansion under a variety of plausible futures, identifying hotspots of NE emergence and estimating impacts on biodiversity, ecosystem services, and climate regulation.

4. Enhance model complexity: This project will refine DGVMs to account for ecological complexity, including trophic interactions and disturbance regimes (e.g., fire dynamics, herbivory effects) often underrepresented in current models. Integrating these factors will improve the accuracy of forecasts and capture the nuanced ways that NEs might influence biodiversity and ecosystem function.

The selected candidate will gain expertise in ecological modelling, high-performance computing, and data integration, contributing to a critical understanding of how NE spread will impact global biodiversity and climate resilience. These insights will be instrumental in shaping strategies for managing the biosphere under future environmental and societal changes.

Please upload a project description (½-4 pages). This document should describe your ideas and research plans for this specific project. If you wish to, you can indicate an URL where further information can be found.

Qualifications and specific competences:

• A Master’s degree degree (or at least one year of a Master’s degree to be qualified for a 4+4 years PhD scheme)  in ecology, biology, environmental science, climate science, computational biology, geography, or a related field, with a focus on quantitative or computational methods.
• Ability to solve complex problems, including evaluating and refining model outputs, identifying research questions, designing experiments, and interpreting results within the context of global environmental change and ecosystem dynamics.
• Relevant experience in ecological modeling, ecosystem forecasting, or climate impact studies, with preference for candidates who have contributed to peer-reviewed publications or technical reports.
• Experience integrating concepts from ecology, climate science, and computational modeling into research
• Proficient written and verbal communication skills, capable of conveying complex scientific ideas effectively to both specialized and broader audiences.
• Experience working in interdisciplinary teams, with a demonstrated ability to contribute constructively to collaborative research efforts.
• Proven capacity to quickly adopt and apply new computational tools, methods, and modeling approaches.
• Motivation to enhance expertise in ecological modeling and high-performance computing applications.
• Expertise in managing and systematically documenting datasets, code repositories, and model workflows.
• Self-motivated and capable of managing independent work effectively, with a strong track record of meeting project deadlines.

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Project-specific qualification requirements:

1. Computational modelling proficiency:
a) Experience in ecological or environmental modelling, preferably focusing on Dynamic Global Vegetation Models (DGVMs) or similar large-scale ecosystem models.
b) Data analysis and integration skills for modelling biodiversity and ecosystem functions across spatial and temporal scales.
 
2. Programming and coding skills:
a) Proficiency in programming languages used in ecological modelling (e.g., Python, R, or C++).
b) Familiarity with high-performance computing (HPC) environments and parallel processing techniques for running complex simulations.
c) Experience with version control systems (e.g., Git) for collaborative coding and data management.

3. Quantitative and statistical skills:
a) Knowledge of statistical methods and experience using statistical software to handle large datasets, conduct uncertainty analyses, and model validation.
b) Ability to apply and interpret statistical techniques for ecosystem forecasting and scenario analyses.

Place of employment and place of work:
The place of employment is Aarhus University, and the place of work is Department of Biology,

Center For Ecological Dynamics in a Novel Biosphere (ECONOVO). Ny Munkegade 114-116, building 1540, Aarhus, Denmark. 

Contacts:
Applicants seeking further information for this project are invited to contact: Associate Professor Alejandro Ordonez, alejandro.ordonez@bio.au.dk

How to apply:

For information about application requirements and mandatory attachments, please see the Application guide. Please read the Application guide thoroughly before applying.

When ready to apply, go to https://phd.nat.au.dk/for-applicants/apply-here/ (Note, the online application system opens 1 December 2024)

1. Choose February 2025 Call with deadline 1 February 2025 at 23:59 CET.
2. You will be directed to the call and must choose the programme “Biology”.
3. In the boxed named “Study”: In the dropdown menu, please choose: “Forecasting the near-future spread of Novel Ecosystems under alternative environmental scenarios (FnsNEu)”

Please note:

• The programme committee may request further information or invite the applicant to attend an interview.

At the Faculty of Natural Science at Aarhus University, we strive to support our scientific staff in their career development. We focus on competency development and career clarification and want to make your opportunities transparent. On our website, you can find information on all types of scientific positions, as well as the entry criteria we use when assessing candidates. You can also read more about how we can assist you in your career planning and development.

Aarhus University’s ambition is to be an attractive and inspiring workplace for all and to foster a culture in which each individual has opportunities to thrive, achieve and develop. We view equality and diversity as assets, and we welcome all applicants. All interested candidates are encouraged to apply, regardless of their personal background.