The first Miocene fossils from coastal woodlands in the southern East African Rift.

The Miocene was a key time in the evolution of African ecosystems witnessing the origin of the African apes and the isolation of eastern coastal forests through an expanding arid corridor. Until recently, however, Miocene sites from the southeastern regions of the continent were unknown. Here, we report the first Miocene fossil teeth from the shoulders of the Urema Rift in Gorongosa National Park, Mozambique. We provide the first 1) radiometric ages of the Mazamba Formation, 2) reconstructions of paleovegetation in the region based on pedogenic carbonates and fossil wood, and 3) descriptions of fossil teeth. Gorongosa is unique in the East African Rift in combining marine invertebrates, marine vertebrates, reptiles, terrestrial mammals, and fossil woods in coastal paleoenvironments. The Gorongosa fossil sites offer the first evidence of woodlands and forests on the coastal margins of southeastern Africa during the Miocene, and an exceptional assemblage of fossils including new species.

Unsupervised learning of satellite images enhances discovery of late Miocene fossil sites in the Urema Rift, Gorongosa, Mozambique.

BACKGROUND: Paleoanthropological research focus still devotes most resources to areas generally known to be fossil rich instead of a strategy that first maps and identifies possible fossil sites in a given region. This leads to the paradoxical task of planning paleontological campaigns without knowing the true extent and likely potential of each fossil site and, hence, how to optimize the investment of time and resources. Yet to answer key questions in hominin evolution, paleoanthropologists must engage in fieldwork that targets substantial temporal and geographical gaps in the fossil record. How can the risk of potentially unsuccessful surveys be minimized, while maximizing the potential for successful surveys? METHODS: Here we present a simple and effective solution for finding fossil sites based on clustering by unsupervised learning of satellite images with the k-means algorithm and pioneer its testing in the Urema Rift, the southern termination of the East African Rift System (EARS). We focus on a relatively unknown time period critical for understanding African apes and early hominin evolution, the early part of the late Miocene, in an overlooked area of southeastern Africa, in Gorongosa National Park, Mozambique. This clustering approach highlighted priority targets for prospecting that represented only 4.49% of the total area analysed. RESULTS: Applying this method, four new fossil sites were discovered in the area, and results show an 85% accuracy in a binary classification. This indicates the high potential of a remote sensing tool for exploratory paleontological surveys by enhancing the discovery of productive fossiliferous deposits. The relative importance of spectral bands for clustering was also determined using the random forest algorithm, and near-infrared was the most important variable for fossil site detection, followed by other infrared variables. Bands in the visible spectrum performed the worst and are not likely indicators of fossil sites. DISCUSSION: We show that unsupervised learning is a useful tool for locating new fossil sites in relatively unexplored regions. Additionally, it can be used to target specific gaps in the fossil record and to increase the sample of fossil sites. In Gorongosa, the discovery of the first estuarine coastal forests of the EARS fills an important paleobiogeographic gap of Africa. These new sites will be key for testing hypotheses of primate evolution in such environmental settings.

Digitization of the Nissen-Riesen chimpanzee radiological growth series.

Longitudinal morphological growth data of apes are incredibly difficult to obtain. Long life histories, combined with practical and ethical issues of obtaining such long-term data have resulted in few longitudinal data sets in chimpanzees of known chronological ages. One classic, long-term growth study of chimpanzees was that of Drs Nissen and Riesen initiated at the Yale Laboratories of Primate Biology in 1939. Through that study, whole-body radiological images were taken on a regular basis from a "normative" group of chimpanzees from birth to adulthood. Here we have digitized the known remaining radiographs from that growth study, many of which are deteriorating, and uploaded the data set to the free, online database MorphoSource. The database comprises 3,568 X-ray images of 15 of the 16 chimpanzee subjects in the normative group and 1 individual from an experimental group. Herein, we briefly review the historical context of this study and specific details of the data set.

Let your fingers do the walking: A simple spectral signature model for "remote" fossil prospecting.

Even with the most meticulous planning, and utilizing the most experienced fossil-hunters, fossil prospecting in remote and/or extensive areas can be time-consuming, expensive, logistically challenging, and often hit or miss. While nothing can predict or guarantee with 100% assurance that fossils will be found in any particular location, any procedures or techniques that might increase the odds of success would be a major benefit to the field. Here we describe, and test, one such technique that we feel has great potential for increasing the probability of finding fossiliferous sediments - a relatively simple spectral signature model using the spatial analysis and image classification functions of ArcGIS(®)10 that creates interactive thematic land cover maps that can be used for "remote" fossil prospecting. Our test case is the extensive Eocene sediments of the Uinta Basin, Utah - a fossil prospecting area encompassing ∼1200 square kilometers. Using Landsat 7 ETM+ satellite imagery, we "trained" the spatial analysis and image classification algorithms using the spectral signatures of known fossil localities discovered in the Uinta Basin prior to 2005 and then created interactive probability models highlighting other regions in the Basin having a high probability of containing fossiliferous sediments based on their spectral signatures. A fortuitous "post-hoc" validation of our model presented itself. Our model identified several paleontological "hotspots", regions that, while not producing any fossil localities prior to 2005, had high probabilities of being fossiliferous based on the similarities of their spectral signatures to those of previously known fossil localities. Subsequent fieldwork found fossils in all the regions predicted by the model.

Phylogeny, life history and the timing of molar crown formation in two archaic ungulates, Meniscotherium and Phenacodus (Mammalia, 'Condylarthra').

The condylarths, or archaic ungulates, are a paraphyletic mammalian group including a number of fossil taxa whose relationships are unresolved. Included are two genera from the Paleocene and Eocene of North America, Meniscotherium and Phenacodus. Some workers place both genera in the family Phenacodontidae, while others exclude the highly dentally derived Meniscotherium. In this study, we use growth increments in histological thin sections to examine the timing of crown formation in five molars of Meniscotherium and one each of Phenacodusintermedius and Phenacodus trilobatus. We also use perikymata counts on an additional six molars of Meniscotherium. Although estimated body mass and molar dimensions in Meniscotherium are smaller than in either species of Phenacodus, molar formation times are longer, ranging from 0.71 to 1.44 years. Both Phenacodus molars take less than a year to form. Crown extension rates, the rate at which the crown grows in height, are as low as 3-15 microm per day in Meniscotherium, but range from 13 to 54 microm per day in Phenacodus. Although striae periodicities and daily enamel secretion rate are similar in both genera, the differences in the crown extension rate and overall timing of crown formation suggest differences in life histories and raise questions about the phylogenetic relationship of the two genera.