Repeated mass strandings of Miocene marine mammals from Atacama Region of Chile point to sudden death at sea.

Marine mammal mass strandings have occurred for millions of years, but their origins defy singular explanations. Beyond human causes, mass strandings have been attributed to herding behaviour, large-scale oceanographic fronts and harmful algal blooms (HABs). Because algal toxins cause organ failure in marine mammals, HABs are the most common mass stranding agent with broad geographical and widespread taxonomic impact. Toxin-mediated mortalities in marine food webs have the potential to occur over geological timescales, but direct evidence for their antiquity has been lacking. Here, we describe an unusually dense accumulation of fossil marine vertebrates from Cerro Ballena, a Late Miocene locality in Atacama Region of Chile, preserving over 40 skeletons of rorqual whales, sperm whales, seals, aquatic sloths, walrus-whales and predatory bony fish. Marine mammal skeletons are distributed in four discrete horizons at the site, representing a recurring accumulation mechanism. Taphonomic analysis points to strong spatial focusing with a rapid death mechanism at sea, before being buried on a barrier-protected supratidal flat. In modern settings, HABs are the only known natural cause for such repeated, multispecies accumulations. This proposed agent suggests that upwelling zones elsewhere in the world should preserve fossil marine vertebrate accumulations in similar modes and densities.

Snapshots of human anatomy, locomotion, and behavior from Late Pleistocene footprints at Engare Sero, Tanzania.

Fossil hominin footprints preserve data on a remarkably short time scale compared to most other fossil evidence, offering snapshots of organisms in their immediate ecological and behavioral contexts. Here, we report on our excavations and analyses of more than 400 Late Pleistocene human footprints from Engare Sero, Tanzania. The site represents the largest assemblage of footprints currently known from the human fossil record in Africa. Speed estimates show that the trackways reflect both walking and running behaviors. Estimates of group composition suggest that these footprints were made by a mixed-sex and mixed-age group, but one that consisted of mostly adult females. One group of similarly-oriented trackways was attributed to 14 adult females who walked together at the same pace, with only two adult males and one juvenile accompanying them. In the context of modern ethnographic data, we suggest that these trackways may capture a unique snapshot of cooperative and sexually divided foraging behavior in Late Pleistocene humans.

Applications of deep convolutional neural networks to digitized natural history collections.

Natural history collections contain data that are critical for many scientific endeavors. Recent efforts in mass digitization are generating large datasets from these collections that can provide unprecedented insight. Here, we present examples of how deep convolutional neural networks can be applied in analyses of imaged herbarium specimens. We first demonstrate that a convolutional neural network can detect mercury-stained specimens across a collection with 90% accuracy. We then show that such a network can correctly distinguish two morphologically similar plant families 96% of the time. Discarding the most challenging specimen images increases accuracy to 94% and 99%, respectively. These results highlight the importance of mass digitization and deep learning approaches and reveal how they can together deliver powerful new investigative tools.