A note on the use of temporal frequency distributions in studies of prehistoric demography

Surovell, Todd A.; Brantingham, P. Jeffrey

doi:10.1016/j.jas.2007.01.003

Cited by 219 publications

(215 citation statements)

References 25 publications

(54 reference statements)

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“…Similar timedependent loss processes seem to affect geological and palaentological data, as well as historical coin records (85,86). Therefore, the temporal frequency distributions should be corrected for this taphonomic bias.…”

Section: Methodsmentioning

confidence: 94%

Human population dynamics in Europe over the Last Glacial Maximum

Tallavaara

Luoto

Korhonen

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

161

109

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The severe cooling and the expansion of the ice sheets during the Last Glacial Maximum (LGM), 27,000-19,000 y ago (27-19 ky ago) had a major impact on plant and animal populations, including humans. Changes in human population size and range have affected our genetic evolution, and recent modeling efforts have reaffirmed the importance of population dynamics in cultural and linguistic evolution, as well. However, in the absence of historical records, estimating past population levels has remained difficult. Here we show that it is possible to model spatially explicit human population dynamics from the pre-LGM at 30 ky ago through the LGM to the Late Glacial in Europe by using climate envelope modeling tools and modern ethnographic datasets to construct a population calibration model. The simulated range and size of the human population correspond significantly with spatiotemporal patterns in the archaeological data, suggesting that climate was a major driver of population dynamics 30-13 ky ago. The simulated population size declined from about 330,000 people at 30 ky ago to a minimum of 130,000 people at 23 ky ago. The Late Glacial population growth was fastest during Greenland interstadial 1, and by 13 ky ago, there were almost 410,000 people in Europe. Even during the coldest part of the LGM, the climatically suitable area for human habitation remained unfragmented and covered 36% of Europe.hunter-gatherers | demography | niche modeling | climate change | Paleolithic G rowing populations of anatomically and behaviorally modern humans have been partly responsible for past ecosystem changes such as the extinctions of Pleistocene megafauna and Neanderthal humans (1, 2). In addition to the destiny of other species, human population size also influences our own cultural and genetic evolution. Large pools of interacting individuals can create and maintain adaptive skills, as well as phonological variation, more effectively than small populations, and they are also capable of faster cumulative cultural evolution (3-5). A decrease in population size may even result in a loss of complex cultural traits (6). The effects of population size on cultural variation are thus roughly similar to the effects of population size on genetic variation (7).The study of the role of human population size in cultural and genetic evolution and past ecosystem changes necessitates estimates of population dynamics extending far beyond historical times. The archaeological record illustrates patterns of human population range and size dynamics (8-10), but it does not offer quantitative population size data. Archaeological reconstructions of population dynamics are also bound to the regions and time periods that offer a sufficiently rich archaeological record. In addition to archaeological data, information on past population patterns can be inferred from genetic data using skyline-plot methods (11) and pairwise or multiple sequentially Markovian coalescent analyzes (12, 13). However, these methods depend on estimates of DNA mutation rate and ...

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Section: Methodsmentioning

confidence: 94%

Human population dynamics in Europe over the Last Glacial Maximum

Tallavaara

Luoto

Korhonen

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

161

109

View full text Add to dashboard Cite

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“…2). Given the progressive loss of materials through time, radiocarbon ages are expected to decrease nonlinearly with age from recent modes, producing a heavily right-skewed distribution (15,16). Even after correction for taphonomic bias, the CUSA and SA datasets form curves typical of this phenomenon.…”

Section: Spacings Analyses (mentioning

confidence: 99%

Test of Martin’s overkill hypothesis using radiocarbon dates on extinct megafauna

Surovell

Pelton

Anderson-Sprecher

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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Following Martin [Martin PS (1973) Science 179:969–974], we propose the hypothesis that the timing of human arrival to the New World can be assessed by examining the ecological impacts of a small population of people on extinct Pleistocene megafauna. To that end, we compiled lists of direct radiocarbon dates on paleontological specimens of extinct genera from North and South America with the expectation that the initial decline of extinct megafauna should correspond in time with the initial evidence for human colonization and that those declines should occur first in eastern Beringia, next in the contiguous United States, and last in South America. Analyses of spacings and frequency distributions of radiocarbon dates for each region support the idea that the extinction event first commenced in Beringia, roughly 13,300–15,000 BP. For the United States and South America, extinctions commenced considerably later but were closely spaced in time. For the contiguous United States, extinction began at ca. 12,900–13,200 BP, and at ca. 12,600–13,900 BP in South America. For areas south of Beringia, these estimates correspond well with the first significant evidence for human presence and are consistent with the predictions of the overkill hypothesis.

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“…An important assumption is that higher frequencies of dated sites represent higher population densities (Brantingham et al 2004, Holdaway et al 2005. Temporal frequency distributions, however, may be affected by taphonomic bias where the loss of data increases with time, which Surovell and Brantingham (2007) suggested may be largely responsible for the positive curvilinear frequency distributions often observed in archaeological, paleontological, and geological data. One potential improvement to population models based on temporal frequency distributions could be to focus on short-term variations, which presumably occur at different rates than either the time-dependent effects of taphonomic bias or the long-term trends in other factors that affect human populations, such as climate change.…”

Section: A Population Prehistory Of Sanak Islandmentioning

confidence: 99%

An Introduction to the Biocomplexity of Sanak Island, Western Gulf of Alaska

et al. 2009

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The Sanak Biocomplexity Project is a transdisciplinary research effort focused on a small island archipelago 50 km south of the Alaska Peninsula in the western Gulf of Alaska. This team of archaeologists, terrestrial ecologists, social anthropologists, intertidal ecologists, geologists, oceanographers, paleoecologists, and modelers is seeking to understanding the role of the ancient, historic, and modern Aleut in the structure and functioning of local and regional ecosystems. Using techniques ranging from systematic surveys to stable isotope chemistry, long-term shifts in social dynamics and ecosystem structure are present in the context of changing climatic regimes and human impacts. This paper presents a summary of a range of our preliminary findings.

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A note on the use of temporal frequency distributions in studies of prehistoric demography

Cited by 219 publications

References 25 publications

Human population dynamics in Europe over the Last Glacial Maximum

Human population dynamics in Europe over the Last Glacial Maximum

Test of Martin’s overkill hypothesis using radiocarbon dates on extinct megafauna

An Introduction to the Biocomplexity of Sanak Island, Western Gulf of Alaska

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