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Abstract Data availability limits phenological research at broad temporal and spatial extents. Butterflies are among the few taxa with broad-scale occurrence data, from both incidental reports and formal surveys. Incidental reports have biases that are challenging to address, but structured surveys are often limited seasonally and may not span full flight phenologies. Thus, how these data source compare in phenological analyses is unclear. We modeled butterfly phenology in relation to traits and climate using parallel analyses of incidental and survey data, to explore their shared utility and potential for analytical integration. One workflow aggregated “Pollard” surveys, where sites are visited multiple times per year; the other aggregated incidental data from online portals: iNaturalist and eButterfly. For 40 species, we estimated early (10%) and mid (50%) flight period metrics, and compared the spatiotemporal patterns and drivers of phenology across species and between datasets. For both datasets, inter-annual variability was best explained by temperature, and seasonal emergence was earlier for resident species overwintering at more advanced stages. Other traits related to habitat, feeding, dispersal, and voltinism had mixed or no impacts. Our results suggest that data integration can improve phenological research, and leveraging traits may predict phenology in poorly studied species.
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Method matters: pitfalls in analysing phenology from occurrence records
Abstract Large occurrence datasets provide a sizable resource for ecological analyses, but have substantial limitations. Phenological analyses in Fricet al. (2020) were misleading due to inadequate curation and improper statistics. Reanalysing 22 univoltine species with sufficient data for independent analysis, we found substantively different macroscale phenological patterns, including later onset at higher latitude for most species.
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- Award ID(s):
- 1702664
- PAR ID:
- 10452009
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Ecology Letters
- Volume:
- 24
- Issue:
- 6
- ISSN:
- 1461-023X
- Page Range / eLocation ID:
- p. 1287-1289
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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