The environmental context for the origins of modern human diversity: A synthesis of regional variability in African climate 150,000–30,000 years ago
Introduction
Fossil and genetic data are consistent with an African origin of Homo sapiens by 195,000 years ago (ka) (Ingman et al., 2000; Clark et al., 2003; White et al., 2003; McDougall et al., 2005; Gonder et al., 2007). Numerous studies have emphasized the diversity in morphology, life history, and genetic signatures likely present among populations of Middle and Late Pleistocene hominins, some of which dispersed from Africa in the Late Pleistocene, replacing existing hominin populations in parts of Eurasia and eventually colonizing Australia and North and South America. The variability among the source populations within Africa is compounded by local demographic changes and range expansions or contractions, as well as the persistence of ancestral or sister taxa (Lahr and Foley, 1998; Howell, 1999; Excoffier, 2002; Forster, 2004; Harding and McVean, 2004; Eswaran et al., 2005; Prugnolle et al., 2005; Trinkaus, 2005; Garrigan and Hammer, 2006; Garrigan et al., 2007; Smith et al., 2007; Bräuer, 2008; Pearson, 2008; Crevecoeur et al., 2009; Gunz et al., 2009; Hammer et al., 2011; Harvati et al., 2011). Middle Stone Age (MSA) archaeological sites provide the strongest record of the behavior of early African populations of H. sapiens, and these sites record pronounced spatial and temporal variation not seen in earlier periods (McBrearty and Brooks, 2000; Henshilwood and Marean, 2003; Marean and Assefa, 2005; Jacobs et al., 2008a; Shea, 2011).
Paleoenvironmental history and variability during the Middle and Late Pleistocene may have played a crucial role in shaping the biological diversity, distribution and behavior of H. sapiens populations during this period. Environmental change is a causal mechanism for the dispersal and isolation of animal populations, and the accumulation of variation through drift resulting from geographic isolation (allopatry) is a central cause of biological divergence and speciation (e.g., Barraclough and Nee, 2001; Mayr, 2001). Human behavioral change occurs as a result of a range of causal factors and we do not advocate strict environmental determinism. However, recent and ancient human forager subsistence, technology, land use, and some social behaviors show clear relationships with environment (Kelly, 1995; Binford, 2001; Kuhn and Stiner, 2001; Marlowe, 2005), and archaeological changes at some Middle Stone Age (MSA) sites have been interpreted as behavioral responses to variation in resource structure and availability as a result of environmental shifts (Ambrose and Lorenz, 1990; Marean et al., 2007; McCall, 2007). Our objective here is to synthesize available African Middle and Late Pleistocene paleoclimatic and paleoanthropological records relevant to early populations of H. sapiens. Although a number of studies have focused on providing the environmental context for subsequent hominin dispersals out of Africa (cf. Carto et al., 2009; Osbourne et al., 2008; Vaks et al., 2007; but see; Basell, 2008; Cowling et al., 2008; Drake et al., 2008), recent genetic evidence has also indicated the importance of Pleistocene population dispersal within Africa and its importance in shaping modern human genetic diversity (e.g., Reed and Tishkoff, 2006; Behar et al., 2008; Tishkoff et al., 2009; Verdu et al., 2009; see also Hammer et al., 2011). Our goal therefore is to explore climatic variability within Africa during this time period to better understand both the context of intra-African hominin population dispersal and conditions relevant to out-of-Africa scenarios.
We emphasize the importance of considering different temporal and spatial frameworks for interpreting the role of climate change in human evolution, and these can be conceived of as occupying a continuum from macro-scale to micro-scale approaches. Macro-scale approaches include those that examine continental scale changes across long time intervals (e.g., Potts, 1998; deMenocal, 2004) or use coarse temporal frameworks such as the Marine Isotope Stage boundaries and glacial/interglacial variation (e.g., Lahr and Foley, 1998; Marean and Assefa, 2005; Basell, 2008; Crowley and Hyde, 2008). At the other end of the continuum are micro-scale approaches that seek to understand the response of small populations to environmental change over relatively short periods recorded at a single archaeological site or depositional basin (e.g., Potts et al., 1999). We are not suggesting that either macro-scale or micro-scale approaches are ‘better’, but rather that the scale of the available data should match the scale of the questions being asked.
Following other recent efforts (e.g., Fisher et al., 2010; Marean et al., 2010; Drake et al., 2011), we employ what might be termed a ‘meso-scale’ approach in the examination of sub-continental variation in paleoclimate and the human fossil and archaeological records. To do so, we synthesize paleoclimate data from diverse datasets of varying degrees of temporal and spatial resolution, divided into three broad categories: (1) cores from offshore marine sites, whose age models are largely constrained by the global oxygen isotope time scale. These provide relatively continuous data sampled over a large area, and provide key data on sea surface temperatures and ocean circulation patterns, changes in terrestrial vegetation patterns and relative aridity; (2) cores from a number of African lakes, particularly Lake Malawi and Lake Tanganyika. As well as the impact crater lakes Tswaing and Bosumtwi, which provide relatively continuous records of watershed and regional environmental change; (3) a number of other terrestrial sedimentary archives, including caves, rockshelters, and open-air archaeological sites that provide temporally discontinuous, often highly local records of climatic and environmental change. We compare these climatic and environmental data to a database of published, radiometrically dated hominin fossil- or artifact-bearing deposits to test whether these changes are coincident with demographic changes in Pleistocene African hominin populations.
We focus on the 150–30 ka time interval for theoretical and practical reasons. This time period is important as it includes much of the early history of H. sapiens, and from an archaeological perspective, it includes the shift from MSA to Later Stone Age (LSA) technologies, an important change that may signal changes in human cognition or demography (cf. Klein, 2009; Powell et al., 2009). Pragmatically, 150 ka marks the beginning of the time interval for which statistically significant numbers of detailed, well-constrained records are available from both the oceanic sites surrounding Africa and for a number of the key lake records such as Lake Malawi. In addition, the paleoclimate records for the past 30 kyr (thousand years) in Africa have long been a focus of earlier reviews (e.g., Street and Grove, 1979; Nicholson and Flohn, 1980). Because we are aggregating datasets of varying degrees of temporal resolution, often particularly poor for the archaeological record, we examine paleoclimate change using 5 kyr intervals and paleoanthropological change using estimated 10 kyr intervals, as detailed below.
Section snippets
Research questions and hypotheses
We synthesize African paleoclimate and paleoanthropological data from 150 to 30 ka, and use these data to test a number of hypotheses.
Methods
To test these hypotheses, we constructed a database from the published literature, synthesizing all relevant dated climatic and paleoanthropological data. The geographic locations of these datasets are shown in Figure 1, Figure 2, with data synthesized in Tables 1 and 2. Note that throughout the paper, paleoclimate data archives are referenced by the numbers presented in Table 1.
Interpretive frameworks for African paleoclimates
Modern African climates provide the basic interpretive framework for interpreting Pleistocene climate and environment. The climate of a given location describes the average annual as well as seasonal variation in temperature and precipitation over a long period of time. Climate dynamics refers to the physical mechanisms that create a particular climate in one location, and a different climate in another.
Paleoclimate results: sea surface temperatures and paleoceanographic conditions
Sea surface temperatures (SSTs) typically reflect changes in mean global temperature because they are global in extent, and water has a high heat capacity. The various measures of SST are summarized in Table 3. Fig. 4 summarizes various measures of sea surface temperatures for the northern Atlantic, Mediterranean, southern Atlantic, Indian Ocean, and Southern Ocean regions.
Paleoclimate results: terrestrial and marine records of continental temperature and precipitation variability
SSTs are an important measure of global temperature and have an important impact on continental moisture availability, but the relationship between oceanic and continental records is complex. The continental records, although often providing less continuous data than the oceanic records, are more directly relevant for understanding the climatic and environmental context of Pleistocene human evolution. Areal coverage and the types of paleoclimate proxies and indicators available are more varied
Regional coherence of temporal trends in African climate change
The evidence presented above indicates that SSTs often co-vary with climate changes predicted by δ18O-derived MIS boundaries, with terrestrial data often out of phase although varying by sub-region. Principal components analysis (PCA) provides a more formal means of comparing aggregate data from both marine and terrestrial sources. On a PCA plot, datasets with similar patterns of variability will plot together. The PCA results are presented in Figure 9, Figure 10, Figure 11. For the purposes of
An evaluation of causal mechanisms
Throughout the discussion of the SST records, there was a recurring theme: all records seem to follow global MIS boundaries, except where they do not. In other words, circum-Africa SSTs record both the global temperature variability, as well as perturbations in that overall signal by local or regional effects such as changing wind zonality and/or upwelling activity. As illustrated in the previous section, terrestrial temperature and precipitation across Africa do not seem to be responding to
Synthesis: African climate from 150 to 30 ka
African paleoclimates from 150 to 30 ka are spatially and temporally complex, with variation in the outcome of multiple related processes. We summarize these here before considering their implications for human evolution, determining the degree to which our hypotheses are supported or rejected. Hypothesis 1 Pleistocene African climate change is coincident with North Atlantic glacial/interglacial periods. Fig. 14 demonstrates that although SSTs do tend to vary with glacial/interglacial cycles and MIS
Paleoanthropological implications
The results of our regional comparisons of paleoanthropological site density and inferred climate for each of the four sub-regions are summarized in Fig. 15. The results are used to test each of our three hypotheses linking climate change to Pleistocene African hominin demography, followed by suggestions for further testing at similar and finer analytical scales. Overall, there is a general increase in the relative frequency of sites over time in most regions (Fig. 15). This pattern is
Conclusions
In this paper. we synthesized African paleoclimate from 150 ka to 30 ka using diverse datasets at a regional scale, testing for coherence with North Atlantic glacial/interglacial phases, Northern and Southern Hemisphere insolation cycles, and the atmospheric dynamics responsible for the observed regional climates. We have examined the temporal and spatial components of paleoenvironmental change across the continent, in order to further investigate the relationship between the varying regional
Acknowledgments
Many thanks to the NSF Integrative Graduate Education and Research Traineeship (IGERT) program and the Foreign Language and Area Studies (FLAS) fellowship program for providing financial support during the research and writing of this manuscript. In addition, many thanks to colleagues who provided comments, advice, and support throughout the process, especially Michael McGlue, Christine Gans, Jessica Conroy, Sarah Ivory, Mark Warren, Daniel Peppe, and Tyler Faith. Sarah Pilliard and Ryan
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