1. Halting biodiversity loss, a major environmental challenge, relies on the understanding of species richness patterns. The assessment of species richness is often hampered by limited taxonomic knowledge and the general dearth of trained systematists. Research has shown that we can predict the number of species in a community by the number of higher order taxonomic units present. Here, we test whether we need to know all the genera, families or orders in order to do so. Further, the number of common species in a region is a good predictor of total richness and we test if this predictability translates to using higher taxa.
2. We used data from 240 sites from the Natura 2000 network of protected areas in Greece, including 5148 plant species and subspecies, which are grouped in 1113 genera 174 families and 56 orders. We correlated species richness with the number of common genera, families or orders present. The analysis was repeated using the number of the most speciose higher orders instead of the most common.
3. We found that we do not need to know all higher order taxa present, in order to predict species richness. If we know how many out of the 30 most common orders are present, we can reliably predict the number of species. Similar results were obtained if we know how many of the 60 most common families or 200 most common genera are present.
4. Equally good results were obtained using the same numbers of the most speciose higher orders.
5. Synthesis and applications. Our analysis demonstrates that species richness can be predicted from the number of common or more speciose genera, families and orders present. These predictions hold without complete sampling of these higher taxa. The implication is that we need only limited systematic knowledge, resources and effort in order to predict species richness. Assuming these findings hold in other taxonomic groups and in other regions, we argue that the uncertainty introduced by limited knowledge of the systematics of less studied taxa should not be used as an excuse to avoid making conservation decisions.