Master of Science Kirsi Alahuhta
Faculty and research unit
University of Oulu Graduate School, Faculty of Science, Ecology and Genetics Research Unit
Field of study
Date and time of the thesis defence
Place of the thesis defence
Remote connection: https://oulu.zoom.us/j/66315489604, Linnanmaa L10 (limited audience based on recent guidelines).
Topic of the dissertation
Consequences of incomplete demographic information on ecological modelling of plant populations with hidden life-history stages
Professor Johan Ehrlén, University of Stockholm
Docent Anne Jäkäläniemi, University of Oulu
Sometimes simplified model is good enough – consequences of incomplete demographic information on ecological modelling of plant populations
Species’ abundances and distributions are studied using population models. Models are simplifications and rely on assumptions and justifications of the model structure, i.e., which ecological processes and interactions are important to include, and which are excluded. It is important to evaluate how these assumptions and justifications are translated to model outcomes, such as population growth rate, which are then used both in conservation biology and evolutionary ecology.
I studied how incomplete demographic information affects the ecological modelling of plants with hidden stages (dormancy). Using long-term demographic data of four species I investigated how model assumptions, model structure or limitations of data sets affects the estimates of vital rates (e.g., survival, reproduction). Furthermore, I constructed population models based on incomplete information and assessed how the model outcomes, such as population growth rate, were affected. Finally, I discussed how the results affect the ecological and evolutionary interpretations of the models in plants.
My results showed that many ecological parameters are robust to incomplete demographic information. Population growth rate, generation time and net reproductive rate were only moderately or not at all affected by assumptions about plant dormancy or whether we use data of known age, stage or both. However, other model outcomes (reproductive values, sensitivity of population growth rate to vital rates) were affected.
On the other hand, if the main interest is to study vital rates, missing demographic information can affect the results. For example, estimates of survival depend on the assumptions we make about the fate of dormant plants (dead or alive). Also, studying senescence (decrease in vital rates with age) without knowing the age of plants (age-from-stage method) does not always reveal a true pattern of age-dependence. Furthermore, it is not always possible to replace a long-term data set with a shorter time series from several sites when investigating relationship between environmental drivers and vital rates.
Altogether, additional demographic information could produce more reliable estimates for demographic parameters, but even simplified population models can be sufficient to study ecology of plants when resources are limited or when information is out of reach.
Last updated: 9.11.2020