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Phenology, the timing of recurrent biological events, is a key mechanism by which species adapt or acclimatize to variable environmental conditions, including those influenced by climate change. Measurable traits, including the onset and end of activity, peak activity, and duration, characterize the phenology of life events, and could be significant predictors of trends in population abundance or stability in a changing climate. Bees provide critical pollination services, and understanding the covariates of bee phenological traits can refine predictions on the vulnerabilities of bees and their services to climate change. We paired 16 years of monthly bee survey data (2002-2019) with climate data for 74 bee species in dryland ecosystems of central New Mexico, USA. Contrary to the current paradigm of temperature as the key driver of insect phenology, twice as many bee species had phenological sensitivity to precipitation (39%) than to temperature (20%). Among phenological traits, the end date of active flying periods was most sensitive to climate. Of the 20% of bee species for which precipitation predicted activity end date, 73% ended activity later in wetter years. Fifteen bee species (~20%) had phenological traits sensitive to temperature, but temperature sensitivity was idiosyncratic, and only four species had earlier onset in warmer years, as expected from results in other biomes. Oligolectic (diet specialist) bee species began, peaked, and ended activity later in the year than polylectic (generalist) species, but phenological traits did not correlate with sociality. All phenological traits showed phylogenetic signal, suggesting evolutionary conservatism of phenology among the common bees of central New Mexico drylands. Finally, species with long activity durations were more common, had greater temporal stability in abundance from year to year, and were less likely to decline over time, perhaps because of their longer window for resource acquisition. Our results suggest that drier climates of the future may shift bee phenological activities toward earlier onset, peak, and end dates, that bees with short activity durations may be among the most sensitive to declines in future climates, and that both generalist and social bees may be able to resist or recover from climate change if they have long durations of flight activity.
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Consistent trait-temperature interactions drive butterfly phenology in both incidental and survey data
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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- PAR ID:
- 10381800
- Publisher / Repository:
- Nature Publishing Group
- Date Published:
- Journal Name:
- Scientific Reports
- Volume:
- 12
- Issue:
- 1
- ISSN:
- 2045-2322
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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