This is my current work at Temple University since February 2024. Ongoing work includes diving into species distribution models and global patterns of extinction risk according to IUCN Red List assessment in Primary Forest and other habitat types.
This is a project I was working on as a Postdoc at Aarhus University. Tropical rainforests harbour about half of the world’s terrestrial species, despite covering less than 10% of the world’s land surface. These numbers are not precise for various reasons, but it is clear that tropical rainforests are outstandingly (“hyper”-)diverse. Read more on the lab webpage.
In this project, we look into when and how frequently extant tropical rainforest (TRF) plant lineages have colonised the biome. We aim at identifying temporal changes of rates of TRF immigration and emigration and connect them to environmental changes over millions of years. First results hint at immigration rates having only contributed little to TRF diversity.
This is still work in progress and on the “to-publish”-pile.
Global hotspots of plant PD and how PD scales with area compared to species richness.
What drives global plant biodiversity? We show the interaction of plant diversity with diversification rates and environmental variables in a structural equation model framework combining data for 330.000 seed plant species.
Read the paper here: Tietje et al. 2022, PNAS
My PhD thesis bridged paleobiology and conservation-motivated questions. Using the amphibian fossil record, I explored the influences of habitat types on extinction risk, the evaluation of modern day amphibians IUCN assessed extinction risk using the fossil record, and temporal variations in the influence of geographic range size on extinction risk.
The correlation of geographic range and duration of amphibian species changes over time, and is strongly connected to the global latitudinal temperature gradient. Our results suggest that climatic conditions influence the importance of geographic range on extinction risk for amphibians.
The results are published in Paleo3.
We were able to show in a unique combination of fossil and neontological data and machine learning based models how the fossil record can predict the IUCN assessed extinction risk of living species. The results are published in Ecology Letters Tietje, M. and Rödel, M. O. (2018), figure 1.
Predicted durations in million years for living amphibian species, based on the model fitted with paleontological data. Tietje, M. and Rödel, M. O. (2018), figure 3.