Refine
Language
- English (4)
Is part of the Bibliography
- yes (4)
Keywords
- Kenya Rift (2)
- Pleistocene (2)
- Adar formation (1)
- Bayesian modeling (1)
- East Africa (1)
- Magnetostratigraphy (1)
- Paleolimnology (1)
- Radiogenic isotopes (1)
- Sedimentology (1)
- Southern Ethiopia (1)
The role that climate and environmental history may have played in influencing human evolution has been the focus of considerable interest and controversy among paleoanthropologists for decades. Prior attempts to understand the environmental history side of this equation have centered around the study of outcrop sediments and fossils adjacent to where fossil hominins (ancestors or close relatives of modern humans) are found, or from the study of deep sea drill cores. However, outcrop sediments are often highly weathered and thus are unsuitable for some types of paleoclimatic records, and deep sea core records come from long distances away from the actual fossil and stone tool remains. The Hominin Sites and Paleolakes Drilling Project (HSPDP) was developed to address these issues. The project has focused its efforts on the eastern African Rift Valley, where much of the evidence for early hominins has been recovered. We have collected about 2 km of sediment drill core from six basins in Kenya and Ethiopia, in lake deposits immediately adjacent to important fossil hominin and archaeological sites. Collectively these cores cover in time many of the key transitions and critical intervals in human evolutionary history over the last 4 Ma, such as the earliest stone tools, the origin of our own genus Homo, and the earliest anatomically modern Homo sapiens. Here we document the initial field, physical property, and core description results of the 2012-2014 HSPDP coring campaign.
The role that climate and environmental history may have played in influencing human evolution has been the focus of considerable interest and controversy among paleoanthropologists for decades. Prior attempts to understand the environmental history side of this equation have centered around the study of outcrop sediments and fossils adjacent to where fossil hominins (ancestors or close relatives of modern humans) are found, or from the study of deep sea drill cores. However, outcrop sediments are often highly weathered and thus are unsuitable for some types of paleoclimatic records, and deep sea core records come from long distances away from the actual fossil and stone tool remains. The Hominin Sites and Paleolakes Drilling Project (HSPDP) was developed to address these issues. The project has focused its efforts on the eastern African Rift Valley, where much of the evidence for early hominins has been recovered. We have collected about 2 km of sediment drill core from six basins in Kenya and Ethiopia, in lake deposits immediately adjacent to important fossil hominin and archaeological sites. Collectively these cores cover in time many of the key transitions and critical intervals in human evolutionary history over the last 4 Ma, such as the earliest stone tools, the origin of our own genus Homo, and the earliest anatomically modern Homo sapiens. Here we document the initial field, physical property, and core description results of the 2012-2014 HSPDP coring campaign.
The Olorgesailie Drilling Project and the related Hominin Sites and Paleolakes Drilling Project in East Africa were initiated to test hypotheses and models linking environmental change to hominin evolution by drilling lake basin sediments adjacent to important archeological and paleoanthropological sites. Drill core OL012-1A recovered 139 m of sedimentary and volcaniclastic strata from the Koora paleolake basin, southern Kenya Rift, providing the opportunity to compare paleoenvironmental influences over the past million years with the parallel record exposed at the nearby Olorgesailie archeological site. To refine our ability to link core-to-outcrop paleoenvironmental records, we institute here a methodological framework for deriving a robust age model for the complex lithostratigraphy of OL012-1A. Firstly, chronostratigraphic control points for the core were established based on 4 Ar/39Ar ages from intercalated tephra deposits and a basal trachyte flow, as well as the stratigraphic position of the Brunhes-Matuyama geomagnetic reversal. This dataset was combined with the position and duration of paleosols, and analyzed using a new Bayesian algorithm for high-resolution age-depth modeling of hiatus-bearing stratigraphic sections. This model addresses three important aspects relevant to highly dynamic, nonlinear depositional environments: 1) correcting for variable rates of deposition, 2) accommodating hiatuses, and 3) quantifying realistic age uncertainty with centimetric resolution. Our method is applicable to typical depositional systems in extensional rifts as well as to drill cores from other dynamic terrestrial or aquatic environments. We use the core age model and lithostratigraphy to examine the inter connectivity of the Koora Basin to adjacent areas and sources of volcanism. (C) 2019 Elsevier Ltd. All rights reserved.
Mathematical analysis of partial differential equations (PDEs) has led to many insights regarding the effect of organism movements on spatial population dynamics. However, their use has mainly been confined to the community of mathematical biologists, with less attention from statistical and empirical ecologists. We conjecture that this is principally due to the inherent difficulties in fitting PDEs to data. To help remedy this situation, in the context of movement ecology, we show how the popular technique of step selection analysis (SSA) can be used to parametrize a class of PDEs, calleddiffusion-taxismodels, from an animal's trajectory. We examine the accuracy of our technique on simulated data, then demonstrate the utility of diffusion-taxis models in two ways. First, for non-interacting animals, we derive the steady-state utilization distribution in a closed analytic form. Second, we give a recipe for deriving spatial pattern formation properties that emerge from interacting animals: specifically, do those interactions cause heterogeneous spatial distributions to emerge and if so, do these distributions oscillate at short times or emerge without oscillations? The second question is applied to data on concurrently tracked bank volesMyodes glareolus. Our results show that SSA can accurately parametrize diffusion-taxis equations from location data, providing the frequency of the data is not too low. We show that the steady-state distribution of our diffusion-taxis model, where it is derived, has an identical functional form to the utilization distribution given by resource selection analysis (RSA), thus formally linking (fine scale) SSA with (broad scale) RSA. For the bank vole data, we show how our SSA-PDE approach can give predictions regarding the spatial aggregation and segregation of different individuals, which are difficult to predict purely by examining results of SSA. Our methods provide a user-friendly way into the world of PDEs, via a well-used statistical technique, which should lead to tighter links between the findings of mathematical ecology and observations from empirical ecology. By providing a non-speculative link between observed movement behaviours and space use patterns on larger spatio-temporal scales, our findings will also aid integration of movement ecology into understanding spatial species distributions.