This commentary introduces a conceptual framework that reinterprets biodiversity assessment as a continuum, spanning from Dark diversity, representing the unobserved or uncolonized potential of species ecologically suited to a system, to Bright diversity, conceived as an aspirational, fully integrated upper bound of biodiversity knowledge. Bright diversity encompasses not only observed components and their intricate interactions, but also a profound understanding of the reasons for species' presence or absence, including the inferred insights from Dark diversity across taxonomic, functional, phylogenetic, and genetic facets. Situated in between is Grey diversity, which characterizes the predominant state of partial knowledge and inherent uncertainty in real-world ecological assessments as an epistemic gradient. By delineating this epistemological gradient, the framework offers a heuristic tool for ecologists and conservationists to critically evaluate the clarity, completeness, and uncertainty embedded in biodiversity data, and an operational basis for “epistemic cartography”, i.e., the spatial mapping of knowledge sufficiency and uncertainty. It facilitates the identification of knowledge gaps, guides research priorities, and informs conservation actions, especially under conditions of incomplete information, through a compact workflow and transparent indicators. This conceptual spectrum serves as both an epistemological reflection and a practical guide for advancing biodiversity science, while outlining a forward-looking agenda that leverages multi-faceted “bands of biodiversity knowledge” to support robust biodiversity planning.
Stopping rules for sampling designs are critical for limiting the effort needed to obtain adequate or significant data, and in many cases for conservation of the species sampled. Such rules are commonly based on pre-determined criteria or a lack of new information as sampling continues. Structural monophyly analysis of minimally monophyletic groups of one ancestral species and a few immediate ancestral species uses a series of steps, each step with a statistical evaluation that helps produce a concise model. Demonstration of two-sigma exclusion of uncertainty is a new stopping rule requirement. The full series of analytic steps has not previously been consolidated in one publication.