Effect of Soil Moisture on Morpho-Anatomical Leaf Traits of Ranunculus acris (Ranunculaceae)

Leaf morphological and anatomical differences between two collection sites in central Poland were examined in tall buttercup Ranunculus acris. We hypothesized that the availability of soil moisture would affect leaf morphological and anatomical traits. The objective of this study was to examine the effect of soil moisture content on: leaf size, epidermal features and on a number of stomatal characteristics in populations of R. acris species. The plants were investigated at sites differing in soil moisture conditions (a dryer upper site and a wetter lower site). Relatively semi-dry and wet sites were identified by plant communities and soil moisture content. We found out that morphological and anatomical leaf traits of R. acris were significantly related to soil moisture content. Leaves from plants growing in the wet site were 26% smaller in size than those from the semi-dry site. The population with smaller leaf area had larger leaf perimeter and higher dissection index. The stomatal index of the leaves sampled in the semi-dry site was higher than that of the leaves sampled in the wet site. Greater leaf thickness in the semi-dry site was primarily the result of increased spongy parenchyma thickness. On the abaxial leaf surface epidermal cell density was significantly higher at the wet site implying more epidermal cells. On the adaxial leaf surface, however, epidermal cell density decreased when plants were exposed to the elevated soil moisture. The results may indicate that soil moisture content influences leaf anatomy and morphology of R. acris. Thus, all these leaf morphoanatomical traits provide a basis for R. acris to reduce water loss from leaves and to balance water use efficiency under reduced precipitation. The present study demonstrates that R. acris can maximize growth in habitats with a wide range of soil moisture availability and such information can be crucial for developing management strategies and predictive models of its spread.