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• W2026631792 abstract "The importance of a careful choice of the appropriate scale for studying ecological phenomena has been stressed repeatedly. However, issues of spatial scale in metapopulation dynamics received much more attention compared to temporal scale. Moreover, multiple calls were made to carefully choose the appropriate model structure for Population Viability Analysis (PVA). We assessed the effect of using coarser resolution in time and model structure on population dynamics. For this purpose, we compared outcomes of two PVA models differing in their time step: daily individual-based model (dIBM) and yearly stage-based model (ySBM), loaded with empirical data on a well-known metapopulation of the butterfly Boloria eunomia. Both models included the same environmental drivers of population dynamics that were previously identified as being the most important for this species. Under temperature change scenarios, both models yielded the same qualitative scenario ranking, but they quite substantially differed quantitatively with dIBM being more pessimistic in absolute viability measures. We showed that these differences stemmed from inter-individual heterogeneity in dIBM allowing for phenological shifts of individual appearance. We conclude that a finer temporal resolution and an individual-based model structure allow capturing the essential mechanisms necessary to go beyond mere PVA scenario ranking. We encourage researchers to carefully chose the temporal resolution and structure of their model aiming at (1) depicting the processes important for (meta)population dynamics of the species and (2) implementing the environmental change scenarios expected for their study system in the future, using the temporal resolution at which such changes are predicted to operate." @default.
• W2026631792 created "2016-06-24" @default.
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• W2026631792 date "2014-01-01" @default.
• W2026631792 modified "2023-09-24" @default.
• W2026631792 title "Appropriate resolution in time and model structure for population viability analysis: Insights from a butterfly metapopulation" @default.
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• W2026631792 doi "https://doi.org/10.1016/j.biocon.2013.12.004" @default.
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