Search for: All records

Genetically modified (GM) crops have been adopted by some of the world’s leading agricultural nations, but the full extent of their environmental impact remains largely unknown. Although concerns regarding the direct environmental effects of GM crops have declined, GM crops have led to indirect changes in agricultural practices, including pesticide use, agricultural expansion, and cropping patterns, with profound environmental implications. Recent studies paint a nuanced picture of these environmental impacts, with mixed effects of GM crop adoption on biodiversity, deforestation, and human health that vary with the GM trait and geographic scale. New GM or gene-edited crops with different traits would likely have different environmental and human health impacts. 

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 very different results when using different data sources (community science and herbarium specimens, respectively) to investigate whether warming threatens wildflowers with phenological mismatch in relation to shading by deciduous trees.Here, we investigated whether differences between the two studies' results could be reconciled by testing four hypotheses related to model design, species, spatiotemporal data extent and phenophase.Hybrid model structures brought results from the two datasets closer together but did not fully reconcile the differences between the studies. Neither the species nor the phenophase selected for analysis seemed to be responsible for differences in results. 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.Synthesis: Our analysis suggests that although species‐level estimates of phenological sensitivity may be similar between community science 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 expand to match the range of climate conditions present in herbarium collections or until herbarium collections 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.