Population dynamics
What is Population dynamics modelling?
Population dynamics modelling is about understanding how populations change through time. Births, deaths, and movement in and out of an area all impact population size. We build mathematical models to describe these processes and then calibrate these models using real-world data. Some models are simpler and focus just on population size without explicitly incorporating demographic processes such as births and deaths, while other models incorporate metapopulation dynamics (i.e., sets of connected populations) or demographic features such as age- or density-dependent survival and birth rates. These models help us look at population dynamics under different human impact levels, climate and environmental conditions and management regimes. In turn, the models frequently support management and conservation decisions.
What has CREEM contributed?
Our research uses modelling techniques such as state-space models and integrated population models that can calibrate models using multiple data sources, and also properly translate uncertainty coming from the data sources into uncertainty in the population dynamics. We often use Bayesian models, which allow incorporation of expert opinion on demographic parameters into the modelling. We also develop new statistical methods for model calibration and use large-scale simulations to test model performance and better quantify uncertainty in population dynamics.
Who in CREEM works on these methods?
- Len Thomas
- Eiren Jacobson
- Sophie Smout
- Debbie Russell
- Tiago Marques
- Cornelia Oedekoven
- Charlotte Jones-Todd
PhD Students:
A few relevant and recent publications by CREEM staff
Camp, R.J., D.L. Miller, L. Thomas, S.T. Buckland and S.J. Kendall. 2020 Using density surface models to estimate spatio-temporal changes in population densities and trend. Ecography 43: 1079-1089
Schaub, M., Maunder, M.N., Kéry, M., Thorson, J.T., Jacobson, E.K., & Punt, A.E. (2024). Lessons to be learned by comparing integrated fisheries stock assessment models (SAMs) with integrated population models (IPMs). Fisheries Research, 272, Article 106925.
Marques, T.A. et al. (2023). Population consequences of the Deepwater Horizon oil spill on pelagic cetaceans.
Thomas, L., Marques, T.A., Booth, C., Takeshita, R., & Schwacke, L.H. (2022). Model predicts catastrophic decline of common bottlenose dolphin (Tursiops truncatus) population under proposed land restoration project in Barataria Bay, Louisiana, USA. Marine Mammal Science, 38(4), 1654–1664.
Auger-Méthé, M., K. Newman, D. Cole, F. Empacher, R. Gryba, A.A. King, V. Leos-Barajas, J. Mills Flemming, A. Nielsen, G. Petris and L. Thomas. 2021. An introduction to state-space modeling of ecological time series. Ecological Monographs 91: e01470.
Jacobson, E.K., C. Boyd, T.L. McGuire, K.E.W. Shelden, G.K. Himes Boor, and A.E. Punt. (2020). Assessing cetacean populations using integrated population models: an example with Cook Inlet beluga whales. Ecological Applications 30(5):e02114.
Newman, K., S.T. Buckland, B. King, D.R. Borchers, D.L. Cole, P. Besbeas, O. Gimenez and L. Thomas. 2014. Modelling Population Dynamics: Model Formulation, Fitting and Assessment using State-Space Methods. Springer Series: Methods in Statistical Ecology, 215p.
Some relevant links