Automated leaf physiognomic character identification from digital images
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Research into the relationship between leaf form and climate over the last century has revealed that, in many species, the sizes and shapes of leaf characters exhibit highly structured and predictable patterns of variation in response to the local climate. Several procedures have been developed that quantify covariation between the relative abundance of plant character states and the states of climate variables as a means of estimating paleoclimate parameters. One of the most widely used of these is the Climate Leaf Analysis Multivariate Program (CLAMP). The consistency, accuracy and reliability with which leaf characters can be identified and assigned to CLAMP character-state categories is critical to the accuracy of all CLAMP analyses. Here we report results of a series of performance tests for an image-based, fully automated at the point of use, leaf character scoring system that can be used to generate CLAMP leaf character state data for: leaf bases (acute, cordate and round), leaf ...



