Lombardi, J. A. | bioRxiv Science

bioRxiv2023

New to Ehretiaceae: Keraunea. Re-evaluation of a genus of climbers from Brazil.

We definitively place Keraunea, a genus of showy forest climbers from remnants of the Mata Atlantica of Brazil, in Ehretiaceae. Previously Keraunea had been ascribed to Convolvulaceae based on morphology, or divided between Malpighiaceae and Ehretiaceae based on molecular analyses (polyphyletic). Keraunea is morphologically anomalous in the Ehretiaceae, having fruits which are held in the centre of a large wing-like bract by adnation of the pedicel, and due the stem-twining habit of some species. However, morphologically Keraunea shares two apomorphies with monotypic Cortesia Cav., halophytic shrubs of Argentina: 1) "two parted endocarps" (the fruit contains two endocarps each with two 1-seeded cells, while four 1-seeded endocarps are plesiomorphic in Ehretiaceae) and 2) a large bract that subtends the flower (absence of bracts is plesiomorphic in Ehretiaceae). A combined tree using four markers (ITS, trnL-F, rbcL and matK) places the three species of Keraunea sampled unambiguously in a clade with Ehretia + Cortesia + Halgania and monophyly for Keraunea is shown with high support. In an ITS tree Keraunea is sister to Cortesia with low support. We expand the generic description of Keraunea including the first account of the internal fruit structures and the seed, and present new data on the vegetative architecture including variation within the genus, some species being stem twiners while one species at least, is described as a scandent shrub. Keraunea lombardiana, previously included within K. brasiliensis, is formally described from Minas Gerais and Bahia as the third species of the genus and both these species are described. In all five species are recognised but two, known to us only from digital images, are not formally described because sufficiently detailed descriptions cannot be made. All five species are mapped, and provisional conservation assessments are recorded, of either Endangered or Critically Endangered. The state of Bahia, with three species, has the highest species diversity, mainly in dry forest. Three species appear confined to moist coastal forest, extending southwards from Bahia to the state of Rio de Janeiro. Keraunea remains incompletely known. Not one of the species has both anthetic flowers and fruits described. Studies on pollen, germination, anatomy, embryology and phytochemisty are entirely lacking. Field observations of pollination, seed dispersal and phenology are also required. However, the most urgent requirement is undoubtedly a formal taxonomic revision based on a full herbarium search and targeted fieldwork, with full IUCN 2012 extinction risk assessments for each taxon. This is urgent because it seems that all the taxa that we present in this paper (and more that can be expected to be found) appear to be highly range restricted and generally not to occur in protected areas, and so appear to be highly threatened.

plant biology↗

bioRxiv2021

Automated classification of bat echolocation call recordings with artificial intelligence

Acoustic recorders are commonly used to remotely monitor and collect data on bats (Order Chiroptera). These efforts result in many acoustic recordings that must be classified by a bat biologist with expertise in call classification in order to obtain useful information. The rarity of this expertise and time constraints have prompted efforts to automatically classify bat species in acoustic recordings using a variety of learning methods. There are several software programs available for this purpose, but they are imperfect and the United States Fish and Wildlife Service often recommends that a qualified acoustic analyst review bat call identifications even if using these software programs. We sought to build a model to classify bat species using modern computer vision techniques. We used images of bat echolocation calls (i.e., plots of the pulses) to train deep learning computer vision models that automatically classify bat calls to species. Our model classifies 10 species, five of which are protected under the Endangered Species Act. We evaluated our models using standard model validation procedures, but we also performed two out-of-distribution tests. For the out-of-distribution tests, an entire dataset was withheld from the procedure before splitting the data into training and validation sets. We found that our validation accuracy (93%) and out-of-distribution accuracy (90%) were higher than when we used Kaleidoscope Pro and BCID software (65% and 61% accuracy, respectively) to evaluate the same calls. Our results suggest that our approach is effective at classifying bat species from acoustic recordings, and our trained model will be incorporated into new bat call identification software: WEST-EchoVision.

ecology↗