Using mark-recapture modeling in the context of nature conservation

Monitoring demography like survival needs long term datasets of local populations, which represent the study population well. Sometimes volunteers put a lot of effort, time and heart into marking and recapturing bats at their local roosts, leading to valuable long term mark recapture histories of individual bats. No funding program would pay for such field work activity. Therefore, these data sets are nearly the only available data source to learn about different aspects of survival in bats. Are there changes between years, age classes, sex...? Is survival driven by weather? Are different populations similar to each other? How is survival linked to reproduction, immigration, population size? Can we gain enough knowledge about the survival of local populations to tell something about the state of the bat species in Germany? My special interest lies in working closely with volunteers, which have the best knowledge of the data they collected, while combining it with my knowledge about capture-recapture modeling.

Modeling spatio-temporal survival of migrating species

Migrating species, e.g., long-distance migrants like ospreys Pandion haliaetus or short-distance migrants like robins Erithacus rubecula, use space on a broad scale across the year. Thus, they are influenced by different spatial conditions in their breeding areas, their wintering areas and their migration routes. All these conditions impact the survival of animals and thereby the population dynamics. Most of the time, we are not able to analyze these relationships directly, but we analyze observations being the result of complex biological processes. The observation process which generates the data makes analysis even more complex, but also allows interpreting the biological processes without the observation bias. Especially, I investigate how data of marked animals, which are found dead and are reported, can be used to describe and analyze survival, migratory connectivity and the observation process of migrating species. Therefore, I use a fully stochastic modeling framework in discrete space and in continuous space. I am interested in further development of this modeling framework to, e.g., seasonal survival.

Schirmer, S., Korner-Nievergelt, F., von Rönn, J. A. C. & Liebscher, V., Estimating Survival, Migratory Connectivity and Reencounter Probability in Continuous Space - Towards a Continuous Version of the Multinomial Reencounter Model. (2023) Journal of Theoretical Biology, 574, 111625, Elsevier. https://doi.org/10.1016/j.jtbi.2023.111625

Schirmer, S., Korner-Nievergelt, F., von Rönn, J. A. C. & Liebscher, V., Estimation in the multinomial reencounter model--Where do migrating animals go and how do they survive in their destination area? (2022). Journal of Theoretical Biology, 543, 111108, Elsevier. https://doi.org/10.1016/j.jtbi.2022.111108.

Schirmer, S.. Modeling spatial patterns of survival, space use and recovery probability (Doctoral thesis, 2022). https://nbn-resolving.org/urn:nbn:de:gbv:9-opus-58451.

Population indices

We support the usage of advanced population trend estimation using Hierarchical Generalized Additive Models (Schirmer et al. 2026) at https://batlas.info  a web application for bat population trends in Germany (Fritze et al. 2026).

Schirmer, S., Scheuerlein, A., & Fritze, M. How to estimate overall population trends when sites show varying population counts over time?. Available at SSRN 5704267. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5704267, R-Code: https://github.com/SaskiaSchirmer/HGAM_poptrends

Fritze, M., Mayr, S., Scheuerlein, A., Kerth, G., Schirmer, S. (2026): BATLAS: A Scalable Citizen Science Platform for Integrating Biodiversity Monitoring Data with Automatic Population Trend Analysis. under Review. Preprint is currently being processed by SSRN.

Politicians would rather like to have one single easy to understand measure that describes the state of nature to make their political decisions on a data-driven basis. But nature consists of hundreds of species and even if we break it down to a bird community of a country, combining all these species in one value comes with several issues. Most multi-species population indices combine the species on a relative basis, but what if a newly occurring species starts with one breeding pair and increases by 1000% in a few years? Does this really impact the state of the bird community so much, when in reality there are only 10 breeding pairs more? Moreover, most multi-species indices do not handle zeros. But rare or disappearing species will contain zero counts, which are mostly replaced by arbitrary small positive numbers. In some cases, the negative binomial model or the tweedie compound model may be a solution to these issues. But most of the time, a second index will make the measure of the state of nature much more transparent and understandable.

Korner-Nievergelt, F., Strebel, N., Buckland, S. T., Freeman, R., Gregory, R. D., Guélat, J., Isaac, N., Mc Rae, L., Roth, T.,  Schirmer, S., Soldaat, L. L., Vorisek, P, & Sattler, T. Multi-species population indices for sets of species including rare, disappearing or newly occurring species (2022). Ecological Indicators, 140, 109005, Elsevier. https://www.sciencedirect.com/science/article/pii/S1470160X22004769

Andere Projekte

Rizzi, S., Schäfer, F., Schirmer, S., & Kerth, G. (2025). The smell of familiarity: conspecific faeces influence roost exploration and occupation in wild Bechstein's bats. Animal Behaviour, 224, 123182. https://www.sciencedirect.com/science/article/pii/S0003347225001095

Paces, B., Wanek, W., Voigt, C. C., Schirmer, S., Leidinger, P., & Schulze, C. H. (2024). Trophic position determines the persistence of neotropical understory birds after forest disturbance. Ecology and Evolution, 14(5), e11370. https://doi.org/10.1002/ece3.11370