Michael Barton
My interests center around long-term human ecology and landscape dynamics with ongoing projects in the Mediterranean (late Pleistocene through mid-Holocene) and recent work in the American Southwest (Holocene-Archaic). I've done fieldwork in Spain, Bosnia, and various locales in North America and have expertise in hunter/gatherer and early farming societies, geoarchaeology, lithic technology, and evolutionary theory, with an emphasis on human/environmental interaction, landscape dynamics, and techno-economic change.
Quantitative methods are critical to archaeological research, and socioecological sciences in general. They are an important focus of my research, especially emphasizing dynamic modeling, spatial technologies (including GIS and remote sensing), statistical analysis, and visualization. I am a member of the open source GRASS GIS international development team that is making cutting edge spatial technologies available to researchers and students around the world.
Quantitative methods are critical to archaeological research, and socioecological sciences in general. They are an important focus of my research, especially emphasizing dynamic modeling, spatial technologies (including GIS and remote sensing), statistical analysis, and visualization. I am a member of the open source GRASS GIS international development team that is making cutting edge spatial technologies available to researchers and students around the world.
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Humans began to leave lasting impacts on Earth's surface starting 10,000 to 8000 years ago. Through a synthetic collaboration with archaeologists around the globe, Stephens et al. compiled a comprehensive picture of the trajectory of human land use worldwide during the Holocene (see the Perspective by Roberts). Hunter-gatherers, farmers, and pastoralists transformed the face of Earth earlier and to a greater extent than has been widely appreciated, a transformation that was essentially global by 3000 years before the present.
Science, this issue p. 897; see also p. 865
Environmentally transformative human use of land accelerated with the emergence of agriculture, but the extent, trajectory, and implications of these early changes are not well understood. An empirical global assessment of land use from 10,000 years before the present (yr B.P.) to 1850 CE reveals a planet largely transformed by hunter-gatherers, farmers, and pastoralists by 3000 years ago, considerably earlier than the dates in the land-use reconstructions commonly used by Earth scientists. Synthesis of knowledge contributed by more than 250 archaeologists highlighted gaps in archaeological expertise and data quality, which peaked for 2000 yr B.P. and in traditionally studied and wealthier regions. Archaeological reconstruction of global land-use history illuminates the deep roots of Earth’s transformation and challenges the emerging Anthropocene paradigm that large-scale anthropogenic global environmental change is mostly a recent phenomenon.
After some efforts made in order to relate the lithic record with such model (Clark and Barton, 2017), in this work we explore how lithic industry can be a reliable proxy for understanding the mobility patterns of the last hunter-gatherers of the Eastern Iberian Peninsula by studying a number of Late Mesolithic lithic collections. We try to bring a new insight into Clark and Barton's analysis, both by combining different sites -implementing geographical variability- and by taking into account functionality and its possible statistical traces, as shown by blades, bladelets and geometric microliths. We focus on the differences found at each site and how they relate with lithic industry in order to test hypotheses regarding mobility patterns.
Here, we examine the dynamics of agricultural dispersals, using the rich body evidence available from the Iberian Peninsula as a case study. We integrate two complementary approaches: (1) creating a high resolution Agent Based Modeling environment to simulate different processes that may have driven the spread of farming; (2) collecting and synthesizing empirical archeological data for the earliest Neolithic settlements that we use to evaluate our models results.
Our results suggest that, (a) the source of radiocarbon data used to evaluate alternative hypotheses play an important role in the results; and (b) the model scenario that produces de best fit with archeological data implies a dispersal via northwestern and southern routes; a preference for leap-frog movement; an influence of ecological conditions (selecting most favorable agricultural land) and demographic factors (avoiding settled regions).
This work represents a first attempt at high-resolution bottom-up modeling of this important dynamic in human prehistory. While we recognize that other social and environmental drivers could have also affected the dispersal of agropastoral systems, those considered here include many that have been widely considered important in prior research and so warrant inclusion.
Humans began to leave lasting impacts on Earth's surface starting 10,000 to 8000 years ago. Through a synthetic collaboration with archaeologists around the globe, Stephens et al. compiled a comprehensive picture of the trajectory of human land use worldwide during the Holocene (see the Perspective by Roberts). Hunter-gatherers, farmers, and pastoralists transformed the face of Earth earlier and to a greater extent than has been widely appreciated, a transformation that was essentially global by 3000 years before the present.
Science, this issue p. 897; see also p. 865
Environmentally transformative human use of land accelerated with the emergence of agriculture, but the extent, trajectory, and implications of these early changes are not well understood. An empirical global assessment of land use from 10,000 years before the present (yr B.P.) to 1850 CE reveals a planet largely transformed by hunter-gatherers, farmers, and pastoralists by 3000 years ago, considerably earlier than the dates in the land-use reconstructions commonly used by Earth scientists. Synthesis of knowledge contributed by more than 250 archaeologists highlighted gaps in archaeological expertise and data quality, which peaked for 2000 yr B.P. and in traditionally studied and wealthier regions. Archaeological reconstruction of global land-use history illuminates the deep roots of Earth’s transformation and challenges the emerging Anthropocene paradigm that large-scale anthropogenic global environmental change is mostly a recent phenomenon.
After some efforts made in order to relate the lithic record with such model (Clark and Barton, 2017), in this work we explore how lithic industry can be a reliable proxy for understanding the mobility patterns of the last hunter-gatherers of the Eastern Iberian Peninsula by studying a number of Late Mesolithic lithic collections. We try to bring a new insight into Clark and Barton's analysis, both by combining different sites -implementing geographical variability- and by taking into account functionality and its possible statistical traces, as shown by blades, bladelets and geometric microliths. We focus on the differences found at each site and how they relate with lithic industry in order to test hypotheses regarding mobility patterns.
Here, we examine the dynamics of agricultural dispersals, using the rich body evidence available from the Iberian Peninsula as a case study. We integrate two complementary approaches: (1) creating a high resolution Agent Based Modeling environment to simulate different processes that may have driven the spread of farming; (2) collecting and synthesizing empirical archeological data for the earliest Neolithic settlements that we use to evaluate our models results.
Our results suggest that, (a) the source of radiocarbon data used to evaluate alternative hypotheses play an important role in the results; and (b) the model scenario that produces de best fit with archeological data implies a dispersal via northwestern and southern routes; a preference for leap-frog movement; an influence of ecological conditions (selecting most favorable agricultural land) and demographic factors (avoiding settled regions).
This work represents a first attempt at high-resolution bottom-up modeling of this important dynamic in human prehistory. While we recognize that other social and environmental drivers could have also affected the dispersal of agropastoral systems, those considered here include many that have been widely considered important in prior research and so warrant inclusion.
Several different spreading algorithms are available to the user (explained in more detail below). The starting point(s) of the spread of agriculture can be set interactively with a mouse or by importing a text file of xy coordinates (geospatial earth coordinates, not NetLogo world coordinates). The GIS Extension allows the user to import a raster basemap in which cell values represent the suitability of the associated land for agriculture (applicable in several spread routines), and a vector map of known prehistoric farming sites. The time of arrival of agriculture (in model ticks) is recorded at each site, and site information can be saved at the end of a simulation run. The time of arrival of agriculture at each site in the simulation can then be compared with the real-world arrival of agriculture at the same sites.
The model is designed to explore some of the factors affecting swidden (sometimes called slash-and-burn) agriculture. Agricultural households take control of the land around them and rotate agricultural fields within this area. Field fertility decreases if a patch is used, and the patch or patches with the highest potential net return is chosen to farm during each time step. The model explores the importance of soil fertility upon swidden strategies as well as issues of land ownership. In addition, the model also explores the effects of swidden agriculture on vegetation communities.
n controlled mode, the researcher sets all parameter values. In adaptive mode, the model explores the success (or failure) of strategies created randomly at the model’s initialization, and during agent reproduction. The agricultural strategy of the agents results from the combination of six key values (move-dist, move-threshold, fission-rate farm-dist, & min-fertility). These values are all initialized with random values from within specified ranges. If an agent reproduces, a copy of the agent is created; however, any of the six key values may randomly change. The resulting selection will produce a set of agents with decision rule values that out compete all other agents.