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Both proxies and models provide key resources to explore how palaeoenvironmental changes may have impacted diverse biotic communities and cultural processes. Whilst proxies provide the gold standard in reconstructing the local environment, they only provide point estimates for a limited number of locations; on the other hand, models have the potential to afford more extensive and standardised geographic coverage. A key decision when using model outputs is the appropriate geographic resolution to adopt; models are coarse scale, in the order of several arc degrees, and so their outputs are usually downscaled to a higher resolution. Most publicly available model time-series have been downscaled to 30 or 60 arc-minutes, but it is unclear whether such resolution is sufficient, or whether this may homogenise environments and mask the spatial variability that is often the primary subject of analysis. Here, we explore the impact of further downscaling model outputs from 30 to 5 arc-minutes using the delta method, which uses the difference between past and present model data sets to increase spatial resolution of simulations, in order to determine to what extent further downscaling captures climatic trends at the site-level, through direct comparison with proxy reconstructions. We use the output from the HadCM3 Global Circulation model for annual temperature, mean temperature of the warmest quarter, and annual precipitation, which we evaluated against a large empirical dataset of pollen-based reconstructions from across the Northern Hemisphere. Our results demonstrate that, overall, models tend to provide broadly similar accounts of past climate to that obtained from proxy reconstructions, with coherence tending to decline with age. However, our results imply that downscaling to a very fine scale has minimal to no effect on the coherence of model data with pollen records. Optimal spatial resolution is therefore likely to be highly dependent on specific research contexts and questions, with careful consideration required regarding the trade-off between highlighting local-scale variation and increasing potential error. [ABSTRACT FROM AUTHOR]

We challenge the view that our species, Homo sapiens, evolved within a single population and/or region of Africa. The chronology and physical diversity of Pleistocene human fossils suggest that morphologically varied populations pertaining to the H. sapiens clade lived throughout Africa. Similarly, the African archaeological record demonstrates the polycentric origin and persistence of regionally distinct Pleistocene material culture in a variety of paleoecological settings. Genetic studies also indicate that present-day population structure within Africa extends to deep times, paralleling a paleoenvironmental record of shifting and fractured habitable zones. We argue that these fields support an emerging view of a highly structured African prehistory that should be considered in human evolutionary inferences, prompting new interpretations, questions, and interdisciplinary research directions.

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Many explanations have been proposed for the evolution of our anomalously large brains, including social, ecological, and epiphenomenal hypotheses. Recently, an additional hypothesis has emerged, suggesting that advanced cognition and, by inference, increases in brain size, have been driven over evolutionary time by the need to deal with environmental complexity. The essential logic is that orbital variables have affected the quantity of solar energy reaching the earth, thus creating climatic changes that posed adaptive challenges to ancestral humans. Larger-brained humans were better equipped to deal with such changes, and proliferated accordingly, leading to the observed trajectory of increasing brain size. Though cross-citation remains rare, researchers from areas as apparently disparate as philosophy and botany are ultimately reaching similar conclusions. In order to test the validity of hypotheses linking encephalisation to climatic variability in the human lineage, the endocranial volumes of 180 fossil human skulls spanning the last 3.2 million years were collated from the literature and regressed upon a series of palaeoclimatic variables, including the amplitudes of the orbitally induced eccentricity, obliquity, and precession cycles. Multiple regression analyses demonstrate that the minimum amplitude of the eccentricity cycle explains 43% of the variance in endocranial capacity, with two further climatic variables accounting for a further 16%. These results are discussed in relation to the increasing weight of evidence that suggests that climatic instability may have played a significant part in the evolution of advanced cognition in both humans and other animals. (Contains 3 tables and 4 figures.)

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.anbehav.2010.04.002 Byline: Amy L. Schreier (a), Matt Grove (b)(c) Abstract: Random walks have long been used to characterize animal movement patterns; recently, this practice has received renewed impetus via the application of Levy walk models. Whilst such models have produced encouraging results, the methods applied have been inconsistent and often problematic; furthermore, primates remain under-represented in such studies. This paper addresses both of these problems via the explanation of a novel and robust analytical method as applied to an extensive primate data set. In a study of a band of hamadryas baboons at the Filoha outpost of Awash National Park, Ethiopia from March 2005 to February 2006, the baboons' location was mapped every 15min during all-day follows using a handheld GPS unit, yielding over 3000 step lengths and waiting times documented across 105 complete follows. Both power law and exponential models were fitted to the step length and waiting time data via maximum likelihood procedures within a model selection paradigm facilitated by the use of an information criterion to distinguish between models. Results show that the step lengths were exponentially distributed, and thus consistent with a random distribution of resources in space. Waiting times, however, were power law distributed, and thus consistent with a power law distribution of patch sizes. We evaluate these results within a discussion of the extent to which random search algorithms are applicable to animals with extensive knowledge of their habitats. Author Affiliation: (a) Department of Evolutionary Anthropology, Duke University, U.S.A. (b) Institute of Cognitive and Evolutionary Anthropology, University of Oxford, U.K. (c) Brasenose College, Radcliffe Square, Oxford, U.K. Article History: Received 2 February 2010; Revised 22 February 2010; Accepted 18 March 2010 Article Note: (miscellaneous) MS. number: A10-00072R