I am a research scientist at the University of Konstanz, working at the intersection of predictive ecology, biodiversity conservation, and invasion science. My research examines how human-mediated processes and the data we rely on shape what we think we know about global biodiversity patterns.

By combining large-scale biodiversity data, ecological theory, and machine learning, my work aims to improve inference, prediction, and decision-making in conservation and invasion science under global change. My current research focuses on understanding and forecasting the distribution of alien species, and on developing quantitative methods to map and predict biodiversity patterns worldwide.

I also curate and manage the Global Naturalized Alien Flora (GloNAF) database, a FAIR, openly accessible resource compiling global data on naturalized alien plant species. Since joining in 2023, I have expanded it by tens of thousands of records, modernized its infrastructure, and implemented reproducible data standards. The updated database is described in a 2025 data paper in Ecology and is archived on Zenodo.

Research Themes


Predictive modeling and machine learning for ecology
My work integrates species distribution models with machine learning to improve prediction and quantify uncertainty under non-stationary conditions.

Human-mediated biodiversity change
Investigating how trade, urbanization, recreation, and other human activities structure biodiversity patterns across regions and taxa.

Data, bias, and reproducibility
Developing and applying reproducible, open analytical practices to assess how data availability, sampling bias, and modeling choices influence ecological inference, risk assessment, and conservation decision-making.

Selected Publications

Collaboration

I collaborate widely with researchers in invasion biology, macroecology, biodiversity informatics, and conservation science. I am particularly interested in projects involving large-scale biodiversity datasets, synthesis across regions or taxa, and reproducible analytical workflows that support evidence-based decision-making.

Contact

Please get in touch via email: amy.davis (at) uni-konstanz (dot) de

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