Heike Siebert, Nataša Djurdjevac Conrad, Sara Varela
01.01.2021 − 31.12.2022
Biodiversity is unevenly distributed across the planet. Diversity hotspots, like the tropics, contrast sparse areas, like the Arctic or extreme deserts. Paleobiogeography, a field of ecology and paleontology, studies species distributions on Earth. Central is species composition, i.e., which genus or larger taxa inhabit certain areas, which is shaped through time by the paleogeographic and paleoclimatic history including events such as continental drift or ice ages. Following early work by, e.g., Humboldt, biogeographers have been using regionalization methods to describe species distribution and to understand the historical factors and climatic constrains shaping bioregions. More recently, the focus has shifted to network models that capture spatial species occurences using bipartite graphs with nodes representing spatial grid cells and species or higher taxa. Clustering of such networks yields so-called bioregions representing geographical areas characterized by specific species composition
In this project, we are using temporal networks to captured to analyze the evolution of bioregions through time and space. For this purpose, we will develop a rigorous framework for definition and analysis of cluster dynamics in time-evolving networks and apply it to temporal network models of spatial species dsitribution. After formalizing notions of cluster trajectories and ensemble dynamics, we will provide analysis strategies for cluster evolution, stability and dynamical smoothness. With these tools we will track evolution of bioregions through deep time (the last 540 million years) to understand how diversification events shaped observed patterns, e.g., by pinpointing major perturbations or tipping points.
Method development will be accompanied by modeling and testing. Data from the paleobioloy database paleobioDB.org will be used to build the bipartite taxa/location networks for the time intervals of interest. Our focus of the cluster dynamics analysis will be on discovering phases of stability as well as gradual or abrupt changes. For validation we will cooperate with colleagues from the Potsdam Institute for Climate Impact to link results to paleoclimatic data, since climate is known to be one of the main regulators of species distribution at large scales. Clarifying the link of climate to biodiversity is certainly a topic not only of interest to understand past, but also future developments of the global ecosystem.
C. Pimiento, J.N. Griffin, C.F. Clements, D. Silvestro, S. Varela, Uhen M.D., and C. Jaramillo. The pliocene marine megafauna extinction and its impact on functional diversity. Nat Ecol Evol, 1:1100–1106, 2017.
D. Thiel, N. Djurdjevac Conrad, E. Ntini, R. Peschutter, H. Siebert, and A. Marsico. Identifying lncRNA-mediated regulatory modules via ChIA-PET network analysis. BMC Bioinf, 20(1):292, 2019.
S. Varela, J. Gonzalez-Hernandez, L. F. Sgarbi, C. Marshall, M. D. Uhen, S. Peters, and M. Mc- Clennen. paleobioDB: an R package for downloading, visualizing and processing data from the paleobiology database. Ecography, 38(4):419–425, 2015.
Spatial distribution of plant fossils from the Paleozoic. Such data can be used to build bipartite graph models capturing species occurences in spatial grid cells. Subsequent clustering allows to determine bioregions.