Effects of fertilization and crown release on white oak (Quercus alba) masting and acorn quality

Light spectra modify nitrogen assimilation and nitrogen content inQuercus variabilisBlume seedling components: A bioassay with15N pulses

“…However, the acorn was the only organ with higher NDFR under green light than under other lights, which led us to partly accept our second hypothesis. These results concur with those found in the field: certain abiotic factors can have significant effects on acorn quality [61,62]. The higher N content in acorns treated with the green light spectrum resulted from the difference in the accumulative effect on errors in the ANOVA model of the product between biomass and concentration.…”

From theory to experiments for testing the proximate mechanisms of mast seeding: an agenda for an experimental ecology

“…Resource addition experiments have thus far yielded variable results. A likely explanation for this variability is the potential for different macronutrients to be limiting in different species and both the differing time scales and phenological stages at which resources matter (Miyazaki et al ; Pulido et al ; Minor & Kobe ; Bogdziewicz et al ; Brooke et al ). Such differences highlight the desirability of performing fully factorial experiments on a variety of masting species over multiple years.…”

Temperature and masting control Norway spruce growth, but with high individual tree variability

“…In 1995 tree ID_01 produced 18 times more cones that the mean cone production of all trees 1982-2012, and this individual was responsible for 26% of all the cones produced over the study period (by 13 individuals). Various factors may explain such individual variability in reproductive output, including tree age, size, microenvironmental conditions, resource availability, and genetics (Davi et al, 2016;Greene et al, 2002;Seifert and Mueller-Starck, 2009;Thomas, 2011;Brooke et al, 2019), although with individual-tree data for only 13 trees, it was not possible to identify the factors controlling long-term cone productivity, or robustly test scaling with tree size. However, our data hinted that high cone production was associated with larger, faster growing trees.…”

“…Additionally, allocation to reproduction is known to vary between individuals due to canopy position and microenvironmental conditions (Davi et al, 2016;Greene et al, 2002;Brooke et al, 2019), tree age and size (Thomas, 2011;Krouchi, Derridj and Lefevre, 2004), genetic control (Seifert and Mueller-Starck, 2009), or other factors (note that these may not be independent). Consequently, cone production at the stand scale may be dominated by a subset of "super-producers" (Minor and Kobe, 2017;Brooke et al, 2019). Such intraspecific variation in allocation to reproduction may result in variation in the cost of reproduction between individuals during population-wide mast years, so that any growth reductions may be greater in individuals that invest more heavily in reproduction (Patterson and Knapp, 2018).…”