Counts are normally used to assess the densities of plants. However, due to the physical characteristics of these sites, habitats and species associated with inaccessible rocky cliffs and other extreme environments pose additional challenges. It is therefore necessary to apply changes to the usual data collection methods. This system allows population sizes to be estimated from an incomplete data collection. This is important because when data collection sites are inaccessible, the fieldwork cannot be carried out within the time that is normally allocated. Furthermore, the minimum sampling effort involved enables economic resources to be saved. This method allows the time spent and the material, methodological and human resources used to be reduced while simultaneously allowing the highest level of accuracy to be maintained. •The minimum effort needed to carry out data collection of plants on vertical walls and other difficult-to-access environments is calculated.•The proposed method is based on the search for the theoretical distribution function with a better adjustment to the actual distribution of the studied species.•This system allows to reduce the necessary resources, while the maximum accuracy is maintained in the calculations.
Keywords: Data collection optimization; Grid-cells data collection for plants; Highest accuracy; Inaccessibility; Minimal effort; Rupicolous flora.