Biodiversity data, particularly species occurrence and abundance, are indispensable for testing empirical hypothesis in natural sciences. However, datasets built for research programmes do not often meet FAIR (findable, accessible, interoperable and reusable) principles, which raises questions about data quality, accuracy and availability. The 21 century has markedly been a new era for data science and analytics and every effort to aggregate, standardise, filter and share biodiversity data from multiple sources have become increasingly necessary.
View Article and Find Full Text PDFPremise: Distyly is a condition in which individual plants in a population express two floral morphs, L- and S-morph, characterized by reciprocal placements of anthers and stigmas between morphs. The function of distyly requires that pollinators collect pollen from L- and S-morphs on different parts along their bodies to then deposit it on the stigmas of the opposite morph, known as legitimate pollination. However, different pollinator groups might differ in the ability to transfer pollen legitimately.
View Article and Find Full Text PDFPremise: Distylous species possess two floral morphs with reciprocal positioning of stigmas and anthers that is hypothesized to promote disassortative pollination. Theoretical models predict equal morph frequencies, but many populations depart from the expected 1:1 ratio, a pattern that often correlates with asymmetric mating between morphs and/or presence of a weak incompatibility system. Variation in reciprocity can also affect the likelihood of disassortative pollination and, hence, reproductive fitness.
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