Fernández-Habas J.1, Komainda M.2, Schmitz A.2, Fernández-Rebollo P.1 and Isselstein J.2,3
1University of Cordoba, Department of Forest Engineering, ETSIAM, Ctra. Madrid, Km 396, Córdoba, 14071, Spain; 2University of Göttingen, Department of Crop Sciences, Von-Siebold-Straβe 8, Göttingen, 37075, Germany; 3Centre of Biodiversity and Sustainable Land Use, Büsgenweg 1, 37077 Goettingen, Germany
The methods used to assess diversity rely on time-consuming and laborious field samplings that limit their application at a regional scale. There is a need for methods that can be used to make rapid assessments of the composition of grassland plant communities. Data collected through citizen science have the advantage of covering large spatial and temporal extents. This study intends to evaluate the feasibility of assessing grassland diversity from pictures collected by a photographic approach using smartphones and measures of picture heterogeneity. We analysed two sets of pictures from Mediterranean and Temperate permanent grasslands. The heterogeneity of the pictures was measured by the Mean information Gain index (MIG) and anisotropy in the Hue and Value channels of JPEG pictures. Pearson correlations and linear mixed-effects models were used to assess their relationships with species composition as assessed by visual determination. The MIG of value channel was positively correlated with the percentage of grasses in Temperate (r=0.364) and Mediterranean grasslands (r=0.400). Linear mixed effect models showed that MIG calculated on the value channel is mainly affected by the percentage of grasses which modulates the MIG relationship with diversity due to the negative correlation between grass cover and plant diversity irrespective of the environment. The MIG index has potential to be applied in a citizen science approach, but the accuracy of the method was found to be comparatively low. Further research is therefore needed.
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