Beskrivelse
Matrix population models (MPMs) are invaluable in ecological and evolutionary research for understanding population dynamics and informing conservation strategies. This presentation introduces a comprehensive approach to improving MPMs, focusing on uncertainty propagation and the diverse applications of the mpmsim R package. Initially, we address the critical issue of uncertainty in demographic rates within MPMs. Our study shows that many MPM applications neglect full uncertainty propagation, potentially leading to biased population growth predictions. To tackle this, we present mpmsim, a tool not only for robust simulation of MPMs but also for a broad range of other applications. mpmsim excels in exploring demographic variability, enabling comparative studies in life history evolution, and assessing the impacts of management strategies on population dynamics. Its utility in educational settings as a tool for teaching population dynamics is also highlighted. Moreover, mpmsim facilitates hypothesis testing in research, particularly in scenarios with limited empirical data, and assists in understanding the effects of sample size on matrix inferences. Our presentation synthesizes how integrating uncertainty analysis with the versatile functionalities of mpmsim leads to more accurate and reliable MPM outcomes. This integration is crucial for advancing ecological predictions, guiding conservation efforts, and contributing to biodiversity preservation. Attendees will gain insights into the extended capabilities of mpmsim, moving beyond uncertainty propagation to a broader application spectrum in ecological and evolutionary studies.| Periode | 13. mar. 2024 |
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| Begivenhedstitel | Nordic Oikos 2024 |
| Begivenhedstype | Konference |
| Placering | Lund , SverigeVis på kort |
| Grad af anerkendelse | International |