Using GIS and Ecological Variables to Identify High Potential Areas for Paleoanthropological Survey: an Example from Northern Armenia
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Journal of Ecological Anthropology Volume 14 Issue 1 Volume 14, Issue 1 (2010) Article 8 2010 Using GIS and Ecological Variables to Identify High Potential Areas for Paleoanthropological Survey: An Example from Northern Armenia Charles P. Egeland University of North Carolina at Greensboro Christopher M. Nicholson University of Wyoming Boris Gasparian National Academy of Sciences of the Republic of Armenia Follow this and additional works at: https://scholarcommons.usf.edu/jea Recommended Citation Egeland, Charles P.; Nicholson, Christopher M.; and Gasparian, Boris. "Using GIS and Ecological Variables to Identify High Potential Areas for Paleoanthropological Survey: An Example from Northern Armenia." Journal of Ecological Anthropology 14, no. 1 (2010): 89-98. Available at: https://scholarcommons.usf.edu/jea/vol14/iss1/8 This Field Notes is brought to you for free and open access by the Anthropology at Scholar Commons. It has been accepted for inclusion in Journal of Ecological Anthropology by an authorized editor of Scholar Commons. For more information, please contact [email protected]. Egeland et al. / GIS and Paleoanthropological Site Selection FIELD NOTE Using GIS and Ecological Variables to Identify High Potential Areas for Paleoanthropological Survey: An Example from Northern Armenia Charles P. Egeland Christopher M. Nicholson Boris Gasparian Introduction The timing and nature of the initial hominid dispersals Plio-Pleistocene sites are extremely rare, and sites from Africa during the Plio-Pleistocene (here 2.0-1.5 preserved in high-integrity depositional contexts million years ago [Myr]) is an issue of great interest are even more so. In fact, the rich early Pleistocene for paleoanthropology. However, the biological, tech- component at Dmanisi was itself unearthed more-or- nological, and ecological context of these dispersals less accidentally during the excavation of a medieval remains cloudy due largely to a paucity of Eurasian fortress (Djaparidze et al. 1989). As fortunate as this paleoanthropological sites dating to this time period. discovery was, survey efforts informed by ecologi- Indeed, there are only a handful of well-accepted cally relevant variables such as vegetation, geography, Plio-Pleistocene sites from Eurasia: Dmanisi in the topography, and geology may not only increase the Republic of Georgia at 1.77-1.81 MYR (de Lumley chances of finding paleoanthropological sites, but et al. 2002), the Nihewan and Yuanmou basins of will also help place hominid occupations into a China at 1.66-1.70 Myr (Zhu et al. 2008), and the broader environmental context. Here we describe Indonesian island of Java at least 1.66 Myr (Sangiran) an approach to identify target areas for paleoanthro- but perhaps as early as 1.81 Myr (Mojokerto) (Larick pological survey. This method uses GIS to integrate et al. 2001; Swisher et al. 1994). Although the Levant, data from archaeology and ecology to identify high given its geographic location, is the most logical extra- potential areas for intensive ground survey. As an African source of dispersing hominid populations, the example, we present pre- and post-survey data from earliest well-accepted occupations there ('Ubeidiya a new paleoanthropological research project in in Israel) date to somewhat later in time at 1.4 Myr northern Armenia. (Belmaker et al. 2002). Journal of Ecological Anthropology Vol. 14 No. 1 010 Predictive Modeling Using GIS Northern Armenia as A High Data Potential Survey Region Predictive models assume that the locations of sites Current evidence indicates that by the early Pleis- are at least partially influenced by modern or pre- tocene, hominids had traveled between 1,000 and historic environmental factors such as vegetation, 5,400 miles from their African homeland (Carbonell distance to water, or topographic setting (e.g., Mehrer et al. 2008). However, this seemingly widespread and Wescott 2006). For example, remote sensing data occurrence does not necessarily mean that hominid have been successfully used to identify high potential populations were distributed evenly across Eurasian geological strata for paleoanthropological survey in landscapes, especially during the initial stages of East Africa (Asfaw et al. 1990; Harmand et al. 2009). dispersal. It is therefore possible that hominids used The greater affordability of digital data and the abil- particular corridors that contained favorable ecologi- ity of GIS to integrate and manipulate numerous cal conditions for their expansion. Therefore, the first step is the identification, in a very broad sense, of datasets now permit relatively sophisticated remote potential survey regions. predictive modeling. As described below, the isolation of possible hominid dispersal routes and—within A theoretical dispersal path was constructed between these dispersal corridors—areas that are likely to the Levant and the earliest well-accepted evidence for contain evidence of early hominid activity, allows hominid occupation outside of Africa—Dmanisi. for more focused pedestrian survey. Any origin point in the area provides the same results; FIGURE 1: Regional map showing origin (‘Ubeidiya, Israel) and destination (Dmanisi, Georgia) points for the Cost Path Analysis. 0 Egeland et al. / GIS and Paleoanthropological Site Selection in the analysis presented here, the site of 'Ubei- create a raster layer of the least cost path, which was diya in Israel was used. A simple cost path analysis then converted to a vector file for display. (CPA) model was employed, which determines the path from a source to a destination using a series of Based on modern terrain, the cheapest route between algorithms that take into account impediments to 'Ubeidiya and Dmanisi runs northeast across Syria, travel (e.g., Hare 2004). Assuming that populations into eastern Turkey and skirts along the northwestern will select a path that minimizes the cost (energy) of border of Armenia (Figure 1). Once in the Lesser travel, the goal of the application was to identify a Caucasus of northern Armenia, the least cost path least cost path (LCP). This function was performed passes north across the Tashir Plateau before termi- in ArcMap 9.3 using the Spatial Analyst with two nating at Dmanisi. Because regional topography has input raster layers: the cost raster and the back link changed somewhat over the past two million years raster. The cost raster was represented by modern ter- (see below), this cost path analysis was not meant to rain (derived using digital elevation models [DEM]), predict the precise location of paleoanthropological while the back link raster retraced the least-costly sites; rather, as mentioned above, it served to isolate route from the destination to the source over the potential survey regions. That the cost path analysis cost distance surface. Using these two raster layers, matched well with the distribution of known Lower an algorithm calculated a single path of raster cells Paleolithic occurrences in northern Armenia supports that is the “cheapest” cumulative route relative to cost the presumption that the region was an important (i.e., slope). Once the slope and back link rasters were corridor for the movement of early hominid popula- created, ArcMap performed the cost path analysis to tions (Figure 2). FIGURE 2: Map of northern Armenia (inset) and northeastern Armenia with the location of geographic features, previously identified Paleolithic sites, and the Least Cost Path. 1 https://scholarcommons.usf.edu/jea/vol14/iss1/8 | DOI: http://dx.doi.org/10.5038/2162-4593.14.1.8 Journal of Ecological Anthropology Vol. 14 No. 1 010 Although systematic data for the Plio-Pleistocene of The next step was to identify specific areas in the the Lesser Caucasus is only beginning to emerge (e.g., Lesser Caucasus for focused pedestrian survey. As Roiron et al. 2007), paleoenvironmental consider- Figure 2 shows, there are several paleoanthropologi- ations further buttress this assertion. Perhaps most cal sites documented on the Tashir Plateau that lie importantly, the site of Dmanisi clearly indicates that along the dispersal path calculated by the cost path the Lesser Caucasus could accommodate hominid analysis. However, many of these and other known habitats during the Plio-Pleistocene. It has even sites in the region document hominid occupation been suggested that the region served as a refugium only back to the early middle Pleistocene—which during colder time periods (Gabunia et al. 2000). In post-dates the earliest dispersals from Africa—and addition, many of the intermontane depressions of tend to lack materials that provide reliable dates the Lesser Caucasus were filled by large freshwater (e.g., volcanic material and/or well-preserved fauna) lakes during the late Pliocene. Pleistocene volcanism (Doronichev 2008). The closest area within the high eventually fragmented these lakes into smaller lacus- potential dispersal region (as determined by the cost trine basins (Lededev et al. 2008a, 2008b; Sayadyan path analysis) that preserves alluvial, lacustrine, and, 2006a, 2006b). The potential presence of lake-mar- most importantly, datable volcanic deposits spanning gin and alluvial environments of Plio-Pleistocene age much of the Plio-Pleistocene, is the Debed River Val- in the region is especially significant given that Dma- ley of northeastern Armenia. The Debed was there- fore considered to be an attractive area for identifying nisi itself is thought to have been in close proximity new paleoanthropological sites. Particularly striking to a lake (Gabunia et al. 2000), and early hominid was the lack of paleoanthropological sites in and occupation of well-watered habitats such as riparian along the valley (Figure 2), which is related directly woodlands and lake-margins is well-documented in to a lack of prior paleoanthropological research in East Africa at both Olduvai Gorge and sites in the the area. GIS was therefore used to conduct a site Turkana Basin (Hay 1976; Rogers et al. 1994). suitability analysis for the Debed River Valley. TablE 1: Land cover categories used in the site suitability analysis. All LST scores were scaled to the maximum value (23) to derive suitability scores. See text for full explanation. Land Cover Type No.