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• W4385519644 abstract "ABSTRACT Recent evidence suggests that community science and herbarium datasets yield similar estimates of species’ phenological sensitivities to temperature. Despite this, two recent studies by Alecrim et al. (2023) and Miller et al. (2022) found contradictory results when investigating an identical ecological mechanism (phenological mismatch of wildflower flowering and of shading by deciduous trees; “phenological escape”) with separate datasets. Here, we investigated whether differences between the two studies’ results could be reconciled by testing four hypotheses related to model design, species selection, spatiotemporal data extent, and phenophase selection. Hybrid model structures brought results from the two datasets closer together but did not fully reconcile the differences between the studies. Cropping the datasets to match spatial and temporal extents appeared to reconcile most differences but only at the cost of much higher uncertainty associated with reduced sample size. Neither species selection nor phenophase selection seemed to be responsible for differences in results. Synthesis: Our analysis suggests that although species-level estimates of phenological sensitivity may be similar between crowd-sourced and herbarium datasets, inherent differences in the types and extent of data may lead to contradictory inference about complex biotic interactions. We conclude that, until community science data repositories grow to match the range of climate conditions present in herbarium collections or until herbarium collections grow to match the spatial extent and temporal frequency of community science repositories, ecological studies should ideally be evaluated using both datasets to test the possibility of biased results from either." @default.
• W4385519644 created "2023-08-04" @default.
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• W4385519644 date "2023-08-03" @default.
• W4385519644 modified "2023-09-27" @default.
• W4385519644 title "Phenological mismatch between trees and wildflowers: Reconciling divergent findings in two recent analyses" @default.
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• W4385519644 doi "https://doi.org/10.1101/2023.08.01.551551" @default.
• W4385519644 hasPublicationYear "2023" @default.
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