Maximizing plant species inventory efficiency by means of remotely sensed spectral distances

Aim: Inventorying plant species in an area based on randomly placed quadrats can be quite inefficient. The aim of this paper is to test whether plant species richness can be inventoried more efficiently by means of a spectrally-based ordering of sites to be sampled. Location: The study area was a complex wetland ecosystem, the Lake Montepulciano Nature Reserve, central Italy. This is one of the most important wetland areas of central Italy because of the diverse plant communities and the seasonal avifauna. Methods: Field sampling, based on a random stratified sampling design, was performed in June 2002. Plant species composition was recorded within sampling units of 100 m2 (plots) and 1 ha (macroplots). A QuickBird multispectral image of the same date was acquired and corrected both geometrically and radiometrically. Species accumulation curves based on spectral information were obtained by ordering sites to be sampled according to a maximum spectral distance criterion (i.e. by ordering sampling units based on the maximum distances among them in a four-dimensional spectral space derived from the remotely sensed data). Different distance measures based on mean and maximum spectral distances among sampling units were tested. The performance of the species accumulation curve derived by the spectrally-based ordering of sampling units was tested against a rarefaction curve obtained from the mean of 10,000 accumulation curves based on randomly ordered sampling units. Results: The spectrally-derived curve based on the maximum spectral distance among sampling units showed the most rapid accumulation of species, well above the rarefaction curve, at both the plot and the macroplot scales. Other ordering criteria of sampling units captured less richness over most of the species accumulation curves at both the spatial scales. The accumulation curves based on other measurements of distance were much closer to the random curve and did not show differences with respect to the species rarefaction curve based on random ordering of sampling units. Main conclusions: The present investigation demonstrated that spectral-based ordering of sites to be sampled can lead to the maximization of the efficiency of plant species inventories, an activity usually driven by the ‘botanist’s internal algorithm’ (intuition),without any formalized rule to drive field sampling. The proposed approach can reduce costs of plant species inventorying through a more efficient allotment of time and sampling.