A workflow for selecting seeding density in desert species experiments

Seeds and seed banks are fundamental components of plant community theory and experimental design in desert ecosystems. Here, we made two simple observations from previous research that used seed sowing as a first step and proposed a simple workflow comprised of 5 steps to facilitate more replicable science and control for potential confounding effects of density that can be introduced between seeds and seedlings. The first observation was that choice of seeding density was relatively arbitrary and based primarily on convenience, i.e. 10 seeds per pot was common in the seeding literature. Second, reporting of the key components needed to calculate seed density in desert experiments, wherein the primary focus was not density, was sparse and limited reproducibility and contrasts between studies for the same species. The 5 steps proposed to resolve these challenges focussed on data-checking in different categories of resources from texts to bibliometrics resources that index peer-reviewed publications and datasets archived in established data repositories. The implications of adopting this process include compiling and providing evidence justifies the choice of a reasonable and representative density for most species with an arid system in a given study and this improves replication science and higher levels of consistency in experimental design. This process will also improve the reporting in the literature that can enable novel scientific syntheses for arid ecosystems.

Automated summary

Seeds and seed banks play a crucial role in plant community theory and experimental design in desert ecosystems. It was observed that the choice of seeding density was often arbitrary and lacked key components needed for calculating seed density in desert experiments, leading to limitations in reproducibility and comparability between studies. A proposed workflow of 5 steps aims to address these challenges by improving data-checking processes and fostering higher levels of consistency and replication in experimental design, ultimately benefiting scientific syntheses for arid ecosystems.