Ascus function: From squirt guns to ooze tubes.

Unlike the mechanism of ballistospore discharge, which was not solved until the 1980s, the operation of asci as pressurized squirt guns is relatively straightforward and was understood in the nineteenth century. Since then, mycologists have sought to understand how structural adaptations to asci have allowed the ascomycetes to expel spores of different shapes and sizes over distances ranging from a few millimeters to tens of centimeters. These modifications include the use of valves at the tips of asci that maintain ascus pressure and expel spores at the highest speeds, and gelatinous appendages that connect spores after release and create larger projectiles with greater momentum than single spores. Clever experiments in the twentieth century coupled with meticulous microscopic studies led investigators to understand how asci with complicated apical structures worked and mathematical models produced estimates of launch speeds. With the recent application of high-speed video microscopy, these inferences about ascus function have been tested by imaging the motion of spores on a microsecond timescale. These experiments have established that ascospore discharge is the fastest fungal movement and is among the fastest movements in biology. Beginning with the history of the study of asci, this review article explains how asci are pressurized, how spores are released, and how far spores travel after their release. We also consider the efficiency of ascospore discharge relative to the mechanism of ballistospore discharge and examine the way that the squirt gun mechanism has limited the morphological diversity of ascomycete fruit bodies.

From GenBank to GBIF: Phylogeny-Based Predictive Niche Modeling Tests Accuracy of Taxonomic Identifications in Large Occurrence Data Repositories.

Accuracy of taxonomic identifications is crucial to data quality in online repositories of species occurrence data, such as the Global Biodiversity Information Facility (GBIF), which have accumulated several hundred million records over the past 15 years. These data serve as basis for large scale analyses of macroecological and biogeographic patterns and to document environmental changes over time. However, taxonomic identifications are often unreliable, especially for non-vascular plants and fungi including lichens, which may lack critical revisions of voucher specimens. Due to the scale of the problem, restudy of millions of collections is unrealistic and other strategies are needed. Here we propose to use verified, georeferenced occurrence data of a given species to apply predictive niche modeling that can then be used to evaluate unverified occurrences of that species. Selecting the charismatic lichen fungus, Usnea longissima, as a case study, we used georeferenced occurrence records based on sequenced specimens to model its predicted niche. Our results suggest that the target species is largely restricted to a narrow range of boreal and temperate forest in the Northern Hemisphere and that occurrence records in GBIF from tropical regions and the Southern Hemisphere do not represent this taxon, a prediction tested by comparison with taxonomic revisions of Usnea for these regions. As a novel approach, we employed Principal Component Analysis on the environmental grid data used for predictive modeling to visualize potential ecogeographical barriers for the target species; we found that tropical regions conform a strong barrier, explaining why potential niches in the Southern Hemisphere were not colonized by Usnea longissima and instead by morphologically similar species. This approach is an example of how data from two of the most important biodiversity repositories, GenBank and GBIF, can be effectively combined to remotely address the problem of inaccuracy of taxonomic identifications in occurrence data repositories and to provide a filtering mechanism which can considerably reduce the number of voucher specimens that need critical revision, in this case from 4,672 to about 100.