Both weather and resources influence masting in chestnut oak

• Published in: Plant ecology 2021-04, Vol.222 (4), p.409
• Main Authors: Smith, S. J, McCarthy, B. C, Hutchinson, T. F, Snell, R. S
• Format: Article
• Language: English
• Subjects: Analysis; Evolution; Hot springs; Plants
• ISSN: 1385-0237
• DOI: 10.1007/s11258-021-01115-7

Masting is the synchronous and highly variable production of fruit within a population. Although several hypotheses have been proposed to explain why and how masting evolved in plants as a reproductive strategy, the factors that trigger a large reproductive effort in a particular year are still not well understood. While both weather and resources have been proposed to play an important role, testing these hypotheses has been challenging due to a lack of long-term data and appropriate experimental designs. In this manuscript, we used 18 years of acorn production data to analyze the relationship between resources, weather, and masting in black oak (Quercus velutina) and chestnut oak (Q. montana). The data were collected in southeast Ohio as part of the Fire and Fire Surrogate (FFS) study, which applied silvicultural treatments (i.e., thinning and prescribed fires) to reduce competition and manipulate resources. We found species-specific responses to the thinning and fire treatments, with an overall increase in acorn production for chestnut oak in the thin + burn treatment and an increase for black oak in the thin-only treatment compared to the control. Chestnut oak reproduction also had strong positive relationships with warm spring temperatures, and a positive change in summer temperatures compared to the previous year (i.e., summer temperatures that went from cool to warm). For black oak, warm spring temperatures increased acorn production while later starts to spring warming the year before decreased acorn production. These results support the hypotheses that both resources and weather (as a cue and as a limiting factor) are important for masting in oaks. Thus, both factors should be included in predictive models for acorn production under current and future climate conditions.