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

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

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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).

89 Journal of Ecological Anthropology Vol. 14 No. 1 2010

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. 90 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 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. 91 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 2010

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 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. of Occurrences LST Score1

14 - Rain-fed croplands 11 48

20 - Mosaic croplands/vegetation 23 100

30 - Mosaic vegetation/croplands 22 96

50 - Closed broadleaved deciduous forest 15 65

110 - Mosaic forest/shrubland/grassland 1 4

1LST = Linear Scale Transformation 92 Egeland et al. / GIS and Paleoanthropological Site Selection

Table 2: Aspect categories used in the site suitability analysis. All LST scores were scaled to the maximum value (13) to derive suitability scores. See text for full explanation.

Aspect (Degrees) No. of Occurrences LST Score1

23-67 5 38 68-112 8 62 113-157 11 85 158-202 11 85 203-247 4 31 248-292 13 100 293-337 12 92 338-360 6 46

Table 3: Slope categories used in the site suitability analysis. All LST scores were scaled to the maximum value (29) to derive suitability scores. See text for full explanation.

Slope (Degrees) No. of Occurrences LST Score1

0.0-0.5 29 100 0.6-1.0 17 59 1.1-1.5 11 38 1.6-2.0 12 41 2.1-2.5 1 3 2.6-3.0 2 7

Table 4: Elevation categories used in the site suitability analysis. All LST scores were scaled to the maximum value (31) to derive suitability scores. See text for full explanation.

Elevation (Meters) No. of Occurrences LST Score1

0-1000 19 61 1000-2000 31 100 2000-3000 16 52 3000+ 6 19

1LST = Linear Scale Transformation

93 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 2010

Site Suitability Analysis particular category. For land cover, known Paleo- lithic sites were most often associated with mosaic Site suitability analysis enters variables into a com- croplands/vegetation (a total of 23 times). Because puter model that geographically displays areas that this represented the highest frequency of asso- are most (and least) likely to preserve sites based on numerical suitability scores (the higher the score, ciations, croplands/vegetation received a suitability the more conducive an area is for site identification). score of 1 and all subsequent scores were scaled to The location of previously identified Paleolithic sites this value. The linear scale transformation values in northern Armenia (n = 72; see Figure 2) was used for each variable were summed using the raster to identify predictive variables for site location. The calculator, averaged to remove potential outliers, variables most closely associated with site location and multiplied by 100. This resulted in a composite were slope, aspect, elevation, land cover, and suitability score that ranged from 0 (lowest suit- proximity to rivers. For the GIS analysis, polygon ability) to 100 (highest suitability). In general, the data for each variable were converted from shapefiles highest suitability scores were associated with areas to raster files. As an example, consider land cover: five categories coincided with previously identi- located near rivers with low slope and relatively open fied Paleolithic sites (Table 1). Using a linear scale vegetation (i.e., cropland). Tables 2-4 summarize transformation (LST; Malczewski 1999), numerical the LST scores for aspect, slope, and elevation. A values for each land cover category were assigned 2 km buffer was constructed along major rivers to based on the number of sites that occurred in a assign distance-to-water scores.

Figure 3: Raster map of site suitability scores for the Debed River Valley and the location of identified paleoanthropological sites. 94 Egeland et al. / GIS and Paleoanthropological Site Selection

The calculated raster values were reclassified into three suit- Table 5: List of Paleolithic sites ability categories: Unsuitable, Suitable, and Very Suitable. identified in the Debed River Valley during the summer of 2009 and Suitable was defined as the mean suitability score of the associated site suitability scores. previously identified sites (= 65) with a range equal to the Suitability scores below 50 are standard deviation of the previously identified sites (SD considered Unsuitable scores = 15.4). This provided a range of 50-81 for the Suitable between 50-81 are considered category. Scores below 50 were then defined as Unsuitable Suitable, and scores above 81 are considered Very Suitable. and scores above 81 as Very Suitable. These values were then used to produce a raster map to visualize the potential location of paleoanthropological sites in the Debed River Site Suitability Valley (Figure 3), which in turn served to focus survey Site efforts. It quickly became clear that, based on the site suit- Score ability analysis, the northernmost stretch of the Debed near 49 the Georgian border had the highest potential to preserve Akori 1 59 paleoanthropological sites. Haghtanak 3 59 2 60 Post-survey results Vahagni 1 60 During the summer of 2009, preliminary survey was 5 61 conducted along the Debed River Valley between its Akori 2 64 confluence with the River in the south to the Georgian border in the north, a distance of approximately Arevatsag 1 66 60 km. Limited field time precluded a complete and sys- Debedavan 3 67 tematic survey of the entire 60 km stretch, so, guided by Haghtanak 2 68 the suitability analysis, the survey team was transported to 3 69 high potential localities by vehicle after which pedestrian survey was carried out. A total of 25 new sites spanning Haghtanak 1 71 the Lower Paleolithic through the Upper Paleolithic were Bagratashen 4 71 identified (Table 5). As can be seen in Table 5, a majority Ptghavan 4 77 of the sites were discovered—as predicted by the suitability 1 78 analysis—along the lower Debed near the border with Georgia (Figure 3). Two of these sites (Haghtanak 3 and Debedavan 1 78 Ayrum 2) preserved Oldowan-type chopper forms that may Debedavan 2 78 be associated with a Plio-Pleistocene hominid occupation Haghtanak 4 81 (Egeland et al. 2010). Ayrum 3 82 The concentration on Suitable and Very Suitable areas in Ayrum 2 84 the Debed River Valley was an effective survey strategy, Bagratashen 1 88 and the remote GIS analysis certainly maximized field Bagratashen 3 88 time. However, there are some limitations to the study as currently conceived. First, the goal of this initial round Bagratashen 2 89 of research was simply to identify the presence of paleo- Ptghavan 1 91 anthropological material. Survey of the valley in general Ptghavan 2 92 and at each site in particular was by no means systematic 95 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 2010 and it therefore cannot be determined at this point Boris Gasparian, Institute of Archaeology and what percentage of each suitability category was Ethnography, National Academy of Sciences of the surveyed. It can be said, however, that several areas Republic of Armenia, [email protected] with high suitability scores have yet to be surveyed. Second, the data on modern landscape variables were relatively coarse-grained and, importantly, Acknowledgments lacked a temporal dimension. Environmental recon- structions are available for the middle Pliocene in This is Paper No. 1 in the Lori Depression Paleoan- formats easily incorporated into a GIS (Salzmann et thropological Project publication series. Members of al. 2008). Unfortunately, these data are simply too the project not appearing as authors include Dmitri coarse to be of much use for an analysis at the scale Arakelyan, Ryan M. Byerly, and Robert Ghukasyan. presented here. More detailed data on a number Sincere thanks to Dr. Pavel Avetisyan and the In- of paleogeographic and paleoecological variables stitute of Archaeology and Ethnography (National and how they would affect the predictive model- Academy of Sciences of the Republic of Armenia) for ing are needed. The spatial extent of Pleistocene supporting this research. Thanks to Dina Zardaryan lakes throughout the Lesser Caucasus would be particularly useful in this context. Finally, it must (Institute of Archaeology and Ethnography) for be realized that remote GIS predictive modeling, help in dating materials and to Samvel Nahapetyan while providing a useful guide for site identifica- (Department of Cartography and Geomorphology, tion, is no substitute for (and can be modified by) Yerevan State University) for providing important on-the-ground experience. Consider the site of information on the geomorphology of the Debed Lchkadzor, which is the one locality that scored in River Valley. Funding for the Lori Depression Paleo- the Unsuitable category (though only by a single anthropological Project has been provided through a point). The site is a diffuse lithic scatter located on grant from the National Science Foundation (BCS- the relatively steep slopes of a small foothill over- 0936385) to Charles P. Egeland. looking the Debed. 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