Estimating ecological count-based measures from the point-intercept method

The point-intercept sampling method (PIM) is an efficient, applicable, and common technique for collecting ecological data. With the rise of digital data, its use is considerably increasing for the analysis of images. However, to date the PIM has been solely used to estimate parameters related to coverage. The limitations of the PIM originate from being a plotless technique (i.e. the sampling unit does not define an area), and because it is prone to substantial sizerelated biases. Based on geometrical considerations, we introduce a simple approach, provided as user-friendly Excel spreadsheets and R functions, to overcome these limitations, providing the sizes of individuals sampled at the sampling points are also recorded. We demonstrate that our approach enables the user to derive unbiased estimations of important ecological measures that could not previously be estimated by the PIM (e.g. population density, size-frequency distribution, average size, and species diversity), and that the improved PIM is even more efficient than conventional plot-based techniques (e.g. the quadrat method).