%0 Journal Article %1 plard2019toward %A Plard, Floriane %A Turek, Daniel %A Grüebler, Martin U. %A Schaub, Michael %D 2019 %J Ecological Monographs %K barn_swallows integral_projection_model integrated_population_models methods population_dynamics %N 3 %P e01364 %R https://doi.org/10.1002/ecm.1364 %T IPM$^2$: toward better understanding and forecasting of population dynamics %U https://esajournals.onlinelibrary.wiley.com/doi/abs/10.1002/ecm.1364 %V 89 %X Abstract Dynamic population models typically aim to predict demography and the resulting population dynamics in relation to environmental variation. However, they rarely include the diversity of individual responses to environmental changes, thus hampering our understanding of demographic mechanisms. We develop an integrated integral projection model (IPM2) that is a combination of an integrated population model (IPMpop) and an integral projection model (IPMind). IPM2 includes interactions between environmental and individual effects on demographic rates and can forecast both population size and individual trait distributions. First, we study the performance of this model using eight simulated scenarios with variable reproductive selective pressures on an individual trait. When the individual trait interacts with the environmental variable and the selective pressure on the individual trait is nonlinear, only IPM2 produces adequate predictions, because IPMind does not link predictions between the population level and observed data and because IPMpop does not include the individual trait. Second, we apply IPM2 to a population of barn swallows. The model accurately predicts trends of the barn swallow population while also providing mechanistic insights. High precipitation negatively influenced population dynamics through delaying laying dates, which lowered reproductive and survival rates. To predict the future of populations, we need to understand their individual drivers and thus include individual responses to their environment while following the entire population. As a consequence, IPM2 will improve our ability to test ecological and evolutionary hypotheses and improve the accuracy of population forecasting to aid management programs.

@article{plard2019toward, abstract = {Abstract Dynamic population models typically aim to predict demography and the resulting population dynamics in relation to environmental variation. However, they rarely include the diversity of individual responses to environmental changes, thus hampering our understanding of demographic mechanisms. We develop an integrated integral projection model (IPM2) that is a combination of an integrated population model (IPMpop) and an integral projection model (IPMind). IPM2 includes interactions between environmental and individual effects on demographic rates and can forecast both population size and individual trait distributions. First, we study the performance of this model using eight simulated scenarios with variable reproductive selective pressures on an individual trait. When the individual trait interacts with the environmental variable and the selective pressure on the individual trait is nonlinear, only IPM2 produces adequate predictions, because IPMind does not link predictions between the population level and observed data and because IPMpop does not include the individual trait. Second, we apply IPM2 to a population of barn swallows. The model accurately predicts trends of the barn swallow population while also providing mechanistic insights. High precipitation negatively influenced population dynamics through delaying laying dates, which lowered reproductive and survival rates. To predict the future of populations, we need to understand their individual drivers and thus include individual responses to their environment while following the entire population. As a consequence, IPM2 will improve our ability to test ecological and evolutionary hypotheses and improve the accuracy of population forecasting to aid management programs.}, added-at = {2024-01-26T23:22:01.000+0100}, author = {Plard, Floriane and Turek, Daniel and Grüebler, Martin U. and Schaub, Michael}, biburl = {https://www.bibsonomy.org/bibtex/2492e4a68f06be2e5f919307df030eaca/peter.ralph}, doi = {https://doi.org/10.1002/ecm.1364}, eprint = {https://esajournals.onlinelibrary.wiley.com/doi/pdf/10.1002/ecm.1364}, interhash = {4c76159b909d86ace7f855d97b9dfc0f}, intrahash = {492e4a68f06be2e5f919307df030eaca}, journal = {Ecological Monographs}, keywords = {barn_swallows integral_projection_model integrated_population_models methods population_dynamics}, number = 3, pages = {e01364}, timestamp = {2024-01-26T23:22:01.000+0100}, title = {{IPM}$^2$: toward better understanding and forecasting of population dynamics}, url = {https://esajournals.onlinelibrary.wiley.com/doi/abs/10.1002/ecm.1364}, volume = 89, year = 2019 }