Search for: All records

Phenological mismatch can occur when plants and herbivores differentially respond to changing phenological cues, such as temperature or snow melt date. This often shifts herbivore feeding to plant stages of lower quality. How herbivores respond to plant quality may be also mediated by temperature, which could lead to temperature-by-phenology interactions. We examined how aphid abundance and mutualism with ants were impacted by temperature and host plant phenology. In this study system, aphids Aphis asclepiadis colonize flowering stalks of the host plant, Ligusticum porteri. Like other aphids, abundance of this species is dependent on ant protection. To understand how host plant phenology and temperature affect aphid abundance, we used a multiyear observational study and a field experiment. We observed 20 host plant populations over five years (2017–2021), tracking temperature and snow melt date as well as host plant phenology and insect abundance. We found host plant and aphid phenology to differentially respond to temperature and snow melt timing. Early snow melt accelerated host plant phenology to a greater extent than aphid phenology, which was more responsive to temperature. Both the likelihood of aphid colony establishment and ant recruitment were reduced when aphids colonized host plants at post-flowering stages. In 2019, we experimentally accelerated host plant phenology by advancing snow melt date by two weeks. We factorially combined this treatment with open top warming chambers surrounding aphid colonies. Greatest growth occurred for colonies under ambient temperatures when they occurred on host plants at the flowering stage. Altogether, our results suggest that phenological mismatch with host plants can decrease aphid abundance, and this effect is exacerbated by temperature increases and changes to the ant–aphid mutualism. 

Abstract The Gene Ontology Consortium (GOC) provides the most comprehensive resource currently available for computable knowledge regarding the functions of genes and gene products. Here, we report the advances of the consortium over the past two years. The new GO-CAM annotation framework was notably improved, and we formalized the model with a computational schema to check and validate the rapidly increasing repository of 2838 GO-CAMs. In addition, we describe the impacts of several collaborations to refine GO and report a 10% increase in the number of GO annotations, a 25% increase in annotated gene products, and over 9,400 new scientific articles annotated. As the project matures, we continue our efforts to review older annotations in light of newer findings, and, to maintain consistency with other ontologies. As a result, 20 000 annotations derived from experimental data were reviewed, corresponding to 2.5% of experimental GO annotations. The website (http://geneontology.org) was redesigned for quick access to documentation, downloads and tools. To maintain an accurate resource and support traceability and reproducibility, we have made available a historical archive covering the past 15 years of GO data with a consistent format and file structure for both the ontology and annotations. 

Abstract Flare frequency distributions represent a key approach to addressing one of the largest problems in solar and stellar physics: determining the mechanism that counterintuitively heats coronae to temperatures that are orders of magnitude hotter than the corresponding photospheres. It is widely accepted that the magnetic field is responsible for the heating, but there are two competing mechanisms that could explain it: nanoflares or Alfvén waves. To date, neither can be directly observed. Nanoflares are, by definition, extremely small, but their aggregate energy release could represent a substantial heating mechanism, presuming they are sufficiently abundant. One way to test this presumption is via the flare frequency distribution, which describes how often flares of various energies occur. If the slope of the power law fitting the flare frequency distribution is above a critical threshold,α= 2 as established in prior literature, then there should be a sufficient abundance of nanoflares to explain coronal heating. We performed >600 case studies of solar flares, made possible by an unprecedented number of data analysts via three semesters of an undergraduate physics laboratory course. This allowed us to include two crucial, but nontrivial, analysis methods: preflare baseline subtraction and computation of the flare energy, which requires determining flare start and stop times. We aggregated the results of these analyses into a statistical study to determine thatα= 1.63 ± 0.03. This is below the critical threshold, suggesting that Alfvén waves are an important driver of coronal heating.