If I understand your terminology correctly:
- "Flower Nested in Gardener": each Gardener scored several Flowers, but each Flower was scored by only one Gardener
- "Allotment Nested in Gardener": each Gardener scored Flowers in several Allotments, but Flowers in each Allotment were scored by only one Gardener
- "Flower Crossed in Allotment": each Flower occurred in more than one Allotment, and each Allotment had more than one Flower
- We would also assume that there were multiple scores for Flowers within each Allotment — otherwise (if there is a single observation per Allotment/Flower combination), then we typically handle the variation at this level as part of the residual variance; indeed, if there is only a single observation then software packages should warn you (but don't always) that the model is overparameterized (the residual variance is confounded/jointly unidentifiable with the Allotment:Flower random effect)
If this description is correct (adding a diagram of your experimental design to your question, as in this answer, might help), then the maximal model would be
(1 | Gardener/(Allotment * Flower))
however, this syntax might not won't work: you need to expand it out to
(1 | Gardener) + (1 | Gardener : Allotment) + (1 | Gardener : Flower ) +
(1 | Gardener : Allotment : Flower)
- if you only have one observation per Allotment/Flower, you would drop the last term
- don't forget that effects other than the intercept may vary among grouping variables, depending on your design (see e.g. Schielzeth and Forstmeier 2009)
Schielzeth, Holger, and Wolfgang Forstmeier. 2009. “Conclusions beyond Support: Overconfident Estimates in Mixed Models.” Behavioral Ecology 20 (2): 416–20. https://doi.org/10.1093/beheco/arn145.
Anested inG" means that each particularA(allotment) is observed with a single level ofG(gardener). (This is why I wanted to make sure that the language is clear.) A figure, or an example data set showing your design, would help ... – Ben Bolker Mar 25 '24 at 00:46