ORIGINAL PAPER

Baseline data for Andean paleomobility research:a radiogenic strontium isotope study of modernPeruvian agricultural soils

Kelly J. Knudson & Emily Webb & Christine White &

Fred J. Longstaffe

Received: 28 November 2012 /Accepted: 11 June 2013# Springer-Verlag Berlin Heidelberg 2013

Abstract While the use of radiogenic strontium isotope valuesto examine paleomobility is increasingly common in the Andes,and beyond, many questions about baseline variability remain.To better understand baseline radiogenic strontium isotope com-positions in the Andes, we present new 87Sr/86Sr values fromPeruvian soil samples. Modern soil samples were collected fromagricultural fields from the following areas in central and south-ern Peru: Arequipa, Atico, Camaná, Chala, Cusco, Ica, Ilo,Lima, Mejía, Moquegua, Nazca, Ocoña, Palpa, Pisco, Puno,Tacna, and Yauca. Samples were partially dissolved to betterapproximate the bioavailable strontium. Radiogenic strontiumisotope values from the partially dissolved soil samples rangefrom 87Sr/86Sr=0.70202 to 0.71894 and, for all soil samples,have a mean of 87Sr/86Sr=0.70773±0.00166 (1σ, n=114). Ingeneral, the 87Sr/86Sr values measured for soil samples collectedfrom modern agricultural fields reflect the expected 87Sr/86Srvalues based on bedrock geology. Comparing our new soil datawith published radiogenic strontium isotope data for bedrock,soil, water, and faunal samples provides constraints on the re-gions in the Andes that can, and cannot, be distinguishedthrough radiogenic strontium isotope analysis.

Keywords Andes . Migration . Residential mobility . Peru .87Sr/86Sr

Introduction

Archaeologists increasingly use isotopic methods, such asradiogenic strontium isotope analysis of archaeological skele-tal and dental elements, to examine paleomobility. However,the best ways to interpret 87Sr/86Sr values as evidence ofresidential mobility and migration are still being investigated.Determining “local” signatures for various regions throughconstruction of radiogenic strontium isotope baselines usingvarious proxies is of utmost importance in the application ofthis method. Here, we investigate variability in radiogenicstrontium isotope ratios of modern soil samples collected fromagricultural fields in southern Peru. We first provide a briefintroduction to the principles of radiogenic strontium isotopeanalysis and its uses in archaeology. We then describe the useof isotopic tracers in Andean paleomobility studies, followedby a discussion of expected 87Sr/86Sr values based on bedrockgeology in the study area. After discussing our materials andmethods, we present new radiogenic strontium isotope data formodern soil samples collected from the following areas incentral and southern Peru: Arequipa, Atico, Camaná, Chala,Cusco, Ica, Ilo, Lima, Mejía, Moquegua, Nazca, Ocoña, Palpa,Pisco, Puno, Tacna, and Yauca. In our concluding sections, weinterpret our baseline data with published data from bedrockand faunal samples to better understand bioavailable 87Sr/86Srvalues in the Andes and discuss the implications of these datafor future paleomobility studies in the Andes and beyond.

Radiogenic strontium isotope analysis in archaeology

Over the past 15 years, the use of isotopic methods toexamine paleomobility has increased dramatically. Whileother isotopic systems can be used to investigate geographicorigins (e.g., White et al. 2009;White et al. 2007), radiogenicstrontium isotope analysis continues to be widely used (seeBentley 2006). Briefly, radiogenic strontium isotope ratios

K. J. Knudson (*)Center for Bioarchaeological Research, School of HumanEvolution and Social Change, Arizona State University,PO Box 872402, Tempe, AZ 85287, USAe-mail: kelly.knudson@asu.edu

E. Webb :C. WhiteDepartment of Anthropology, The University of Western Ontario,London, ON N6A 5C2, Canada

F. J. LongstaffeDepartment of Earth Sciences, The University of Western Ontario,London, ON N6A 5C2, Canada

Archaeol Anthropol SciDOI 10.1007/s12520-013-0148-1

vary in a given geologic zone according to bedrock age andinitial composition (Faure 1986). This isotopic variability islargely reflected in the soils, plants, and animals in a givengeologic zone (see Bentley 2006). Therefore, 87Sr/86Srvalues of archaeological human remains can be used todetermine the geologic region or regions in which an indi-vidual lived during enamel and bone formation, if “local”strontium sources were consumed and imbibed (Ericson1985; Price et al. 1994a, b).

While paleomobility studies using radiogenic strontium iso-topes have generally focused on human movement, there isalso a growing body of literature on the movement of plantproducts and animals in the past. For example, scholars haveinvestigated reindeer (Rangifer sp.) migration and Neanderthalhunting strategies in Europe (Britton et al. 2009, 2011), cattle(Bos taurus) mobility and husbandry practices in the BritishNeolithic (Viner et al. 2010), Iron Age horse (Equus feruscaballus) exchange and breeding programs in the UK(Bendrey et al. 2009), mountain sheep (Ovis canadensis) hunt-ing practices in western North America (Fisher and Valentine2013), and trade and exchange of deer (Odocoileusvirginianus) and peccary (Tayassuidae sp.) in Mesoamerica(Thornton 2011). In addition to the movement of wild anddomesticated animals in the past, 87Sr/86Sr values have beenused to investigate the trade and exchange of domesticatedgrains (Hordeum vulgare) in the UK (Heier et al. 2009),sources of plant fibers used in Danish Iron Age textiles (Freiet al. 2009b), and maize (Zea mays) in the North AmericanSouthwest (Benson et al. 2003, 2009, 2010; Benson 2010).

Introduction to Andean paleomobility studies

Light stable isotopes have also been used to investigate Andeanpaleomobility, as is described elsewhere (Buzon et al. 2011; Gilet al. 2011; Knudson 2009; Knudson et al. 2012a, b, 2009;Knudson and Price 2007; Knudson and Torres-Rouff 2009;Turner and Armelagos 2012; Turner et al. 2009; Ugan et al.2012; Webb et al. 2013; White et al. 2009). Here, we focus onpublished work using radiogenic strontium isotopes. The ear-liest isotopic work on Andean paleomobility involved theMiddle Horizon (c. AD 500–1100) Tiwanaku polity, wheresubstantial geologic variability ensures that movement betweenthe Tiwanaku capital in the Lake Titicaca Basin and Tiwanaku-affiliated sites in southern Peru, Bolivia, and northern Chile canbe identified (Knudson 2007, 2008; Knudson and Price 2007;Knudson et al. 2004, 2005; Knudson and Torres-Rouff 2009;Lucas 2012; Marsteller et al. 2011; Nado et al. 2012). In theMiddle Horizon Wari polity of Peru, radiogenic strontiumisotope analysis has been used to examine both populationmovement as well as the geographic origins of individualstransformed into trophy heads (Knudson and Tung 2007,2011; Slovak et al. 2009; Tung and Knudson 2008, 2010,2011). More recently, scholars have focused on Early

Intermediate Period and Middle Horizon paleomobility in theNazca Drainage of southern Peru (Buzon et al. 2012; Conleeet al. 2009; Horn et al. 2009; Knudson et al. 2009) and in theLate Horizon Inka Empire (Andrushko et al. 2011, 2009;Turner and Armelagos 2012; Turner et al. 2009). While muchof this work has focused on archaeological human remains,isotopic research on archaeological camelid remains has alsobeen used to elucidate animal movement (Horn et al. 2009;Knudson et al. 2012a; Thornton et al. 2011).

Expected strontium isotopic signatures in the Andes

Andean bedrock geology and expected radiogenic strontiumisotope ratios

In general, the Andes Mountains are divided into theCordillera Occidental to the west and the Cordillera Orientalto the east (Figs. 1 and 2). The Cordillera Occidental is largelycomposed of late Cenozoic volcanic rocks, such as andesites(Bellido et al. 1956). Since the age of the Cenozoic volcanicrocks increases from the northern Andes to the southernAndes (see overview in Gregory-Wodzicki 2000), radiogenicstrontium isotope values are generally higher in the southernAndes (Francis et al. 1977; Harmon et al. 1984; Hawkesworthet al. 1982; Klerkx et al. 1977; McNutt et al. 1975; Rogers andHawkesworth 1989). For example, radiogenic strontium iso-tope values (87Sr/86Sr) from late Cenozoic volcanic rocks inEcuador exhibit 87Sr/86Sr=0.70431±0.00016 (1σ, n=23)(Francis et al. 1977), while exposed bedrock samples fromsimilar geologic formations in northern Chile exhibit mean87Sr/86Sr=0.70646±0.00020 (1σ, n=8) (Rogers andHawkesworth 1989). In between these extremes, lateCenozoic volcanic rocks near Arequipa in southern Peruexhibit mean 87Sr/86Sr=0.70737±0.00030 (1σ, n=16)(James 1982) and mean 87Sr/86Sr=0.70749±0.00050 (1σ,n=6) (Notsu and Lajo 1984). The Cordillera Oriental containsPaleozoic geologic formations (Bellido et al. 1956; Chepstow-Lusty et al. 2003; Gregory 1916). The Paleozoic geologicformations should be characterized by higher radiogenicstrontium isotope ratios, but their compositions have not beenmeasured in bedrock (see discussions in Andrushko et al.2011, 2009; Turner et al. 2009).

Areas that derive strontium from both the CordilleraOccidental and the Cordillera Oriental are distinct from theandesite-dominated Cordillera Occidental. For example, inthe Lake Titicaca Basin of Peru and Bolivia, igneous rocksincluding andesites and basalts are overlain by Quaternaryfluvial and lacustrine sediments from the surrounding moun-tains (Argollo et al. 1996). Although radiogenic strontiumisotope data do not yet exist for Lake Titicaca Basin bedrocksamples, sediment cores taken from Lake Titicaca exhibitmean 87Sr/86Sr=0.70838±0.00012 (1σ, n=25) (Grove et al.2003) and Lake Titicaca surface water is characterized by

Archaeol Anthropol Sci

mean 87Sr/86Sr=0.70863±0.00034 (1σ, n=3) (Coudrainet al. 2002). Farther south, the altiplano and Bolivian low-lands are characterized by much higher radiogenic strontiumisotope ratios in archaeological and modern faunal samples,although bedrock-derived data do not yet exist; for example,archaeological faunal samples from the Tiwanaku-affiliatedsite of Piñami in Cochabamba, Bolivia exhibit mean87Sr/86Sr=0.72148±0.00162 (1σ, n=4) (Lucas 2012), andsimilarly high 87Sr/86Sr values are reported for faunal sam-ples from the southern altiplano near Potosi, Bolivia(Knudson et al. 2005).

Coastal areas of Peru and Chile are dominated byQuaternary sedimentary geologic formations (Bellido et al.1956). However, we would also expect strontium from theadjacent highland areas in the Cordillera Occidental to beincorporated into the riverine and alluvial soils found on thecoasts (Bellido et al. 1956). Coastal areas may also incorpo-rate marine-derived strontium from sea spray (e.g., Whipkeyet al. 2000); strontium from sea spray or other marine sourcesexhibits the radiogenic strontium isotope value of modernsea water, which is 87Sr/86Sr=0.7092 (Veizer 1989).

Identifying sources of bioavailable strontium and baselineradiogenic strontium isotope signatures

While it is useful to generate expected radiogenic strontiumisotope values based on bedrock geology, there are a numberof advantages and disadvantages of using 87Sr/86Sr fromexposed bedrock to generate baseline radiogenic strontiumisotope signatures. As discussed above, strontium from sea

spray may contribute marine strontium to coastal areas (e.g.,Whipkey et al. 2000). More generally, not all strontium inbedrock is incorporated into soil and water, and is thereforenot necessarily incorporated into the plants and animals,including humans, in a given ecosystem (see Bentley 2006).

In addition to examining the radiogenic strontium isotopevalues in exposed bedrock, soil, plants and animal samplescan also be used to better understand 87Sr/86Sr values inbioavailable strontium. Collecting soil samples from agricul-tural fields and/or the plants themselves can target the bio-available strontium incorporated into foodstuffs. However,there are also disadvantages to using soil samples for base-line data. For example, if the soil samples are completelydissolved, rather than partially dissolved during sample prep-aration, the 87Sr/86Sr will reflect both bioavailable strontiumand strontium bound in forms that are not readily available inthe ecosystem (see discussion of strontium in environmentalsystems in Bentley 2006). In addition, the use of soil samplesfrom contemporary agricultural fields is most effective whenagricultural fields were used or likely to have been used inthe past.

The use of fertilizers can also contribute strontium to afield system, both in the past and present. Archaeologicalfield systems may have been fertilized with manure fromlocally raised animals (e.g., Bogaard et al. 2007; Finucane2007; Meharg et al. 2006), which would not have contribut-ed “non-local” strontium to the field system. In the Andes,seabird guano was used in the past and present (Julien 1985),contributing strontium with a radiogenic strontium isotoperatio indicative of seawater, which is 87Sr/86Sr=0.7092

0 100 200 300 km

0 100 200 miN

Pacific

Ocean

Lake Titicaca

Chile

PeruBolivia

Lima

Pisco

IcaPalpa

Nazca

AticoYauca

Chala

OcoñaCamaná Arequipa

Meija

Ilo

Moquegua

Tacna

Puno

Cusco

Quaternary

Cretaceous

TertiaryMesozoic-Cenozoic intrusives

Jurassic-Cretaceous

Jurassic

Carboniferous-Permian

Precambrian-DenovianPrecambrianundifferentiated

Cretaceous-Tertiaryvolcanics

Key

Fig. 1 Geologic map of the study area with sampling locations identified (based on Bellido et al. 1956)

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Rio

Colorado

Rio

Esmereldas

Rio

Dau

le

0 100 200 300 km

0 100 200 miN

RioPutum

Lake Titicaca

Argentina

PacificOcean

Ecuador

Colombia

Brazil

Bolivia

Chile

Rio

Marañó

RioYucayal

Rio Purus

Lima

Arequipa

Puno

Cusco

Quito

La Paz

Santiago

Tiwanaku

San Pedro de Atacama

Cochabamba

Lake Poopó

Late Cenozoic Volcanic RocksMean Sr Sr=0.70431±0.00016 (1 , n=23)

Late Cenozoic Volcanic RockMean Sr Sr=0.70646±0.00020 (1 , n=16)

Late Cenozoic Volcanic RockMean Sr Sr=0.70737±0.00030 (1 , n=16)

Late Cenozoic Volcanic RockMean Sr Sr=0.70749±0.00050 (1 , n=6)

Sediment CoreMean Sr Sr=0.70838±0.00012 (1 , n=25)

Surface WaterMean Sr Sr=0.70863±0.00034 (1 , n=3)Sea Water

Sr Sr=0.7092

Primarily Cenozoic to Mesozoic sedimentary rock

Primarily Paleozoic to Precambrian sedimentary rock

Primarily Precambrian igneous and metamorphic rock

Key

Primarily Cenozoic toMesozoic igneous and metamorphic rock

Fig. 2 Geologic sketch map ofthe South Central Andes withpublished mean radiogenicstrontium isotope ratios fromexposed bedrock (Francis et al.1977; Harmon et al. 1984;Hawkesworth et al. 1982; James1982; Klerkx et al. 1977;McNutt et al. 1975; Notsu andLajo 1984; Rogers andHawkesworth 1989) and LakeTiticaca Basin sediment andsurface water (Coudrain et al.2002; Grove et al. 2003)

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(Veizer 1989). In contemporary agricultural fields, the use ofimported fertilizers could also contribute “non-local” stron-tium to soil and plant samples; in a French watershed, forexample, mass-produced fertilizers contributed strontiumwitha radiogenic strontium isotope ratio of 87Sr/86Sr=0.715(Négrel and Deschamps 1996).

The addition of “non-local” strontium from fertilizers isalso an issue when using contemporary floral and faunalsamples. In addition, plants and the animals that eat themcan incorporate strontium from windborne sources, includ-ing dust (Grousset et al. 1992; Miyamoto et al. 2010; Wuet al. 2010) and sea spray (Evans et al. 2010; Whipkey et al.2000). If these sources also contributed strontium to the dietof the individuals under study, then soil, floral and faunalsamples will give a good understanding of bioavailablestrontium; for example, partially dissolved soil samples fromcoastal agricultural fields affected by sea spray, as well asfloral and faunal samples from the same area, could give anexcellent picture of bioavailable strontium in the region,including marine-derived strontium from sea spray. In con-trast, using a contemporary field system that has been treatedwith mass-produced artificial fertilizers not available in thepast would not provide a reasonable estimate of bioavailablestrontium for a population from that area.

A number of scholars have discussed the potential of faunalremains, particularly archaeological and/or modern enamelsamples from small mammals, for establishing baseline87Sr/86Sr signatures in a given region (Bentley 2006; Evansand Tatham 2004; Price et al. 2002). Like floral samples, faunalremains provide a good estimate of the bioavailable strontiumin a given ecosystem. However, the range over which an animalincorporates strontium from food and water sources will varybased on the species (e.g., Britton et al. 2011; Frei et al. 2009a;Hedman et al. 2009; Knudson et al. 2012a; Price et al. 2008;Shaw et al. 2009; Sykes et al. 2011, 2006; Thornton 2011;Thornton et al. 2011; Viner et al. 2010). The range for smallmammals provides data on 87Sr/86Sr values from a larger areathan that of floral samples, yet is relatively small compared to alarge geologic zone. Larger animals, such as llamas (Lamaglama), may incorporate strontium from a large area, makingit harder to trace the 87Sr/86Sr values to specific geologic zones(Knudson et al. 2012a; Thornton et al. 2011). When usingarchaeological remains, tooth enamel samples are more resis-tant to diagenetic contamination and are preferred (Bentley2006; Evans and Tatham 2004; Price et al. 2002).

We note that an essential aspect of using radiogenic stron-tium isotope analysis to infer human paleomobility is deter-mining the actual strontium sources in an individual’s diet. Ifthe dietary strontium derives from sources that wereimported or traded widely, radiogenic strontium isotopeanalysis would identify trade and exchange of foodstuffsrather than human residential mobility. In the Andes, manywidely traded plant products, like maize (Z. mays), or

animals that may have traveled over a wide range of geologiczones, like llamas (L. glama), are not generally high instrontium (e.g., Knudson et al. 2009; Tung and Knudson2008). However, understanding the 87Sr/86Sr values in bio-available strontium as well as the source of dietary strontiumis an important aspect of paleomobility studies using radio-genic strontium isotopes.

Materials

Soils from agricultural fields can provide a way to under-stand the bioavailable strontium incorporated by cultivatedplant products. This is particularly important given the rela-tively high strontium concentrations in many plant products(Runia 1987), which likely provide the majority of strontiumconsumed in many populations. In contrast, soil or geologicsamples from mortuary contexts or areas (e.g., bedrock out-crops) not extensively used in the past may not have contrib-uted much or any strontium to the diet, and therefore may notprovide a reasonable estimation of the bioavailable strontiumand its radiogenic strontium isotope ratios.

Soil samples were collected from modern agricultural fieldsin southern Peru between 2007 and 2009 (Table 1, Fig. 1).Given the lack of productive agricultural land in many parts ofthe Andes, it is possible that prehistoric populations used theselocations as well; indeed, many parts of the Andes have a longhistory of agricultural land use in the same field systems (seediscussions in Bandy 2005; Craig et al. 2011; Erickson 1988;Graffam 1992; Janusek and Kolata 2004; Wernke 2007, 2010).When possible, soil samples were collected from field systemsthat were being traditionally farmed with little or no importedfertilizers and were being used for crops grown in the Andeanpast, such as maize (Z. mays), yuca (Manihot esculenta), pota-toes (Solanum tuberosum), and oca (Oxalis tuberosa) (Table 1).However, particularly on the coast of Peru, many currentagricultural products were introduced after the arrival of theSpanish in AD 1532. We also included soil samples fromagricultural fields that were fallow at the time of sampling. Ineach study area, approximately 25–30 g of surface soil wascollected from the top 10 cm of soil since this interval generallycontains the highest concentrations of exchangeable cations(Blum et al. 2000; Johnson et al. 1991). Sampling locales werechosen to investigate both inter- and intra-regional variability inradiogenic strontium isotope ratios.

Methods

All soil samples were prepared under the direction ofKnudson at Arizona State University in the ArchaeologicalChemistry Laboratory using published methods (Blum et al.2000). A representative soil sample was weighed and dried

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Table 1 87Sr/86Sr values for soil samples from modern agricultural fields in Peru

Site Laboratory number Specimen number Agricultural crop cultivated 87Sr/86Sr

Arequipa ACL-2193 AQP-AIS916 Solanum tuberosum 0.70768

Arequipa ACL-2194 AQP-AIS917 Zea mays 0.70789

Arequipa ACL-2195 AQP-AIS918 Allium cepa 0.70563

Arequipa ACL-2196 AQP-AIS921 Apium gravolens dulce 0.70849

Arequipa ACL-2197 AQP-AIS925 Medicago sativa 0.70801

Arequipa ACL-2198 AQP-AIS926 Zea mays 0.70798

Arequipa ACL-2199 AQP-AIS931 Zea mays 0.70934

Arequipa ACL-2200 AQP-AIS933 Medicago sativa 0.70846

Atico ACL-2256 ATICO-AIS844 Zea mays 0.70637

Atico ACL-2257 ATICO-AIS846 Olea europaea 0.70689

Atico ACL-2259 ATICO-AIS860 Olea europaea 0.70746

Atico ACL-2260 ATICO-AIS862 Olea europaea 0.70849

Camaná ACL-2236 CAMA-AIS876 Oryza sp. 0.70842

Camaná ACL-2237 CAMA-AIS878 Oryza sp. 0.70841

Camaná ACL-2238 CAMA-AIS880 Oryza sp. 0.70836

Camaná ACL-2239 CAMA-AIS882 Oryza sp. 0.70968

Chala ACL-2251 CHALA-AIS852 Ficus carica 0.70759

Chala ACL-2252 CHALA-AIS853 Malus domestica 0.70796

Chala ACL-2253 CHALA-AIS855 Citrullus lanatus 0.70724

Cusco ACL-2221 CUSCO-AIS879 Solanum tuberosum 0.70889

Cusco ACL-2222 CUSCO-AIS970 Fallow (native grasses) 0.70771

Cusco ACL-2223 CUSCO-AIS971 Fallow (native grasses) 0.70775

Cusco ACL-2224 CUSCO-AIS973 Fallow (native grasses) 0.70849

Cusco ACL-2225 CUSCO-AIS976 Fallow (native grasses) 0.70799

Cusco ACL-2226 CUSCO-AIS977 Fallow (native grasses) 0.70786

Cusco ACL-2227 CUSCO-AIS980 Fallow (native grasses) 0.70939

Cusco ACL-2228 CUSCO-AIS982 Solanum tuberosum 0.70850

Cusco ACL-2229 CUSCO-AIS984 Fallow (native grasses) 0.71335

Cusco ACL-2230 CUSCO-AIS988 Zea mays 0.71894

Cusco ACL-2231 CUSCO-AIS994 Phaseolus vulgaris 0.70853

Cusco ACL-2232 CUSCO-AIS998 Fallow (native grasses) 0.70932

Cusco ACL-2233 CUSCO-AIS999 Fallow (native grasses) 0.70912

Cusco ACL-2234 CUSCO-AIS1004 Zea mays 0.70988

Cusco ACL-2235 CUSCO-AIS1006 Fallow (native grasses) 0.71036

Ica ACL-2268 ICA-AIS780 Vitis sp. 0.70695

Ica ACL-2269 ICA-AIS782 Vitis sp. 0.70711

Ica ACL-2270 ICA-AIS784 Vitis sp. 0.70761

Ica ACL-2271 ICA-AIS786 Mangifera indica 0.70715

Ilo ACL-2192 ILO-AIS898 Passiflora edulis 0.70679

Ilo ACL-2245 ILO-AIS884 Oryza sp. 0.70870

Lima ACL-2178 LIMA-AIS724 Zea mays 0.70738

Lima ACL-2179 LIMA-AIS726 Zea mays 0.70736

Lima ACL-2180 LIMA-AIS728 Zea mays 0.70654

Lima ACL-2181 LIMA-AIS730 Phaseolus vulgaris 0.70746

Lima ACL-2182 LIMA-AIS733 Zea mays 0.70772

Lima ACL-2183 LIMA-AIS735 Zea mays 0.70758

Lima ACL-2184 LIMA-AIS737 Manihot esculenta 0.70745

Lima ACL-2185 LIMA-AIS739 Fallow (native grasses) 0.70691

Lima ACL-2186 LIMA-AIS743 Gossypium barbadense 0.70733

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Table 1 (continued)

Site Laboratory number Specimen number Agricultural crop cultivated 87Sr/86Sr

Lima ACL-2187 LIMA-AIS745 Asparagus officinalis 0.70678

Lima ACL-2188 LIMA-AIS746 Gossypium barbadense 0.70729

Lima ACL-2189 LIMA-AIS748 Gossypium barbadense 0.70704

Mejía ACL-2246 MEJIA-AIS886 Zea mays 0.70808

Mejía ACL-2247 MEJIA-AIS889 Oryza sp. 0.70804

Mejía ACL-2248 MEJIA-AIS891 Oryza sp. 0.70798

Mejía ACL-2249 MEJIA-AIS893 Saccharum sp. 0.70801

Mejía ACL-2250 MEJIA-AIS895 Oryza sp. 0.70799

Moquegua ACL-2190 MOQ-AIS899 Vitis sp. 0.70202

Moquegua ACL-2191 MOQ-AIS901 Persea americana 0.70513

Nazca ACL-2262 NAZCA-AIS825 Vitis sp. 0.70611

Nazca ACL-2263 NAZCA-AIS828 Gossypium barbadense 0.70565

Nazca ACL-2264 NAZCA-AIS832 Gossypium barbadense 0.70673

Nazca ACL-2267 NAZCA-AIS837 Zea mays 0.70659

Nazca ACL-2261 NAZCA-AIS818 Gossypium barbadense 0.70598

Ocoña ACL-2240 OCONA-AIS864 Oryza sp. 0.70760

Ocoña ACL-2241 OCONA-AIS866 Oryza sp. 0.70739

Ocoña ACL-2242 OCONA-AIS869 Oryza sp. 0.70765

Ocoña ACL-2243 OCONA-AIS871 Oryza sp. 0.70653

Ocoña ACL-2244 OCONA-AIS874 Oryza sp. 0.70857

Palpa ACL-2272 PALPA-AIS789 Zea mays 0.70668

Palpa ACL-2273 PALPA-AIS790 Gossypium barbadense 0.70760

Palpa ACL-2274 PALPA-AIS792 Vitis sp. 0.70805

Palpa ACL-2275 PALPA-AIS794 Gossypium barbadense 0.70680

Palpa ACL-2276 PALPA-AIS797 Gossypium barbadense 0.70656

Palpa ACL-2277 PALPA-AIS799 Gossypium barbadense 0.70723

Palpa ACL-2278 PALPA-AIS802 Gossypium barbadense 0.70659

Palpa ACL-2279 PALPA-AIS804 Gossypium barbadense 0.70670

Palpa ACL-2280 PALPA-AIS805 Gossypium barbadense 0.70649

Palpa ACL-2281 PALPA-AIS807 Zea mays 0.70671

Palpa ACL-2282 PALPA-AIS809 Zea mays 0.70728

Palpa ACL-2283 PALPA-AIS812 Unknown (likely Zea mays) 0.70646

Palpa ACL-2284 PALPA-AIS814 Medicago sativa 0.70680

Palpa ACL-2285 PALPA-AIS816 Mangifera indica 0.70700

Pisco ACL-2286 PISCO-AIS750 Gossypium barbadense 0.70867

Pisco ACL-2287 PISCO-AIS752 Gossypium barbadense 0.70757

Pisco ACL-2288 PISCO-AIS754 Zea mays 0.70764

Pisco ACL-2289 PISCO-AIS756 Gossypium barbadense 0.70790

Pisco ACL-2290 PISCO-AIS758 Gossypium barbadense 0.70768

Pisco ACL-2291 PISCO-AIS760 Mangifera indica 0.70752

Pisco ACL-2292 PISCO-AIS762 Gossypium barbadense 0.70743

Pisco ACL-2293 PISCO-AIS764 Gossypium barbadense 0.70765

Pisco ACL-2294 PISCO-AIS766 Manihot esculenta 0.70801

Pisco ACL-2295 PISCO-AIS768 Zea mays 0.70748

Pisco ACL-2296 PISCO-AIS770 Zea mays 0.70729

Pisco ACL-2297 PISCO-AIS772 Gossypium barbadense 0.70742

Pisco ACL-2298 PISCO-AIS774 Zea mays 0.70706

Pisco ACL-2300 PISCO-AIS778 Medicago sativa 0.70704

Puno ACL-2201 PUNO-AIS937 Solanum tuberosum, Oxalis tuberosa 0.70921

Archaeol Anthropol Sci

for 48 h at 120 °C before preparation. The dried soil samplewas then crushed with a Coors porcelain mortar and pestleand then ashed for approximately 10 h at 800 °C. The soilsample was then partially dissolved in 10 mL of 1 M ammo-nium acetate (CH3COONH4, or NH4OAc) at room temper-ature for 24 h and then decanted. A partial dissolution meth-od was used to approximate the bioavailable strontium in thesoil samples. The partial dissolution method is designed tomaximize release of bioavailable strontium and minimizerelease of strontium that is generally not bioavailable and isinstead tightly bound in the mineral crystal lattices in the soil(Blum et al. 2000).

All samples were analyzed at the W.M. Keck FoundationLaboratory for Environmental Biogeochemistry at Arizona StateUniversity. First, strontium was separated from the sample ma-trix using EiChrom SrSpec resin (50–100 μm in diameter) andultrapure 5 M nitric acid (HNO3) following established pro-cedures (e.g., Knudson and Price 2007). Radiogenic and stablestrontium isotopes were measured on a Neptune multi-collectorinductively coupled plasmamass spectrometer, where SRM-987exhibited 87Sr/86Sr=0.710265±0.000010 (2σ, n=25), followingpublished values of 87Sr/86Sr=0.710263±0.000016 (2σ) inanalyses of international standard SRM-987 (Stein et al. 1997).

Results

The results for the modern soil samples show a wide range inradiogenic strontium isotope ratios, from 87Sr/86Sr=0.70202to 87Sr/86Sr=0.71894 (Table 1, Fig. 3). The mean for all soilsamples is 87Sr/86Sr=0.70773±0.00166 (1σ, n=114). Mean

87Sr/86Sr values for each region included in the study arelisted in Table 2.

Discussion

Comparison of radiogenic strontium isotope ratios in soiland bedrock samples

We first compare the measured 87Sr/86Sr values of soil sam-ples collected from modern agricultural fields with the ob-served 87Sr/86Sr values from bedrock samples (Tables 2 and3). The majority of radiogenic strontium isotope analyses onAndean bedrock samples are from late Cenozoic volcanicrocks. In this study, one sampling location was dominatedby late Cenozoic volcanic rocks; in Arequipa, Peru mean87Sr/86Sr=0.70797±0.00115 (1σ, n=8) (Tables 2 and 3).Andesite samples collected near Arequipa, Peru exhibit mean87Sr/86Sr=0.70737±0.00030 (1σ, n=16) (James 1982) andmean 87Sr/86Sr=0.70749±0.00050 (1σ, n=6) (Notsu andLajo 1984).

While no results from bedrock samples currently exist forthe Lake Titicaca Basin, sediment cores taken from LakeTiticaca exhibit mean 87Sr/86Sr=0.70838±0.00012 (1σ,n=25) (Grove et al. 2003). In addition, Lake Titicaca surfacewater exhibits mean 87Sr/86Sr=0.70863±0.00034 (1σ, n=3)(Coudrain et al. 2002). Our soil data from Puno, Peru in theLake Titicaca Basin exhibit mean 87Sr/86Sr=0.70835±0.00135(1σ, n=11) (Table 2).

The only other sampling location with published geologicdata is Cusco, Peru, where one andesite sample exhibits

Table 1 (continued)

Site Laboratory number Specimen number Agricultural crop cultivated 87Sr/86Sr

Puno ACL-2202 PUNO-AIS940 Triticum sp. 0.70812

Puno ACL-2203 PUNO-AIS942 Solanum tuberosum 0.70867

Puno ACL-2204 PUNO-AIS946 Solanum tuberosum, Chenopodium quinoa 0.70696

Puno ACL-2205 PUNO-AIS957 Solanum tuberosum, Chenopodium quinoa 0.70783

Puno ACL-2206 PUNO-AIS952 Solanum tuberosum 0.70743

Puno ACL-2207 PUNO-AIS954 Solanum tuberosum, 0.71191

Puno ACL-2208 PUNO-AIS957 Solanum tuberosum, Chenopodium quinoa 0.70842

Puno ACL-2209 PUNO-AIS960 Solanum tuberosum, Oxalis tuberosa 0.70787

Puno ACL-2210 PUNO-AIS965 Fallow (native grasses) 0.70790

Puno ACL-2211 PUNO-AIS966 Fallow (native grasses) 0.70837

Tacna ACL-2212 TACNA-AIS904 Fallow (native grasses) 0.70884

Tacna ACL-2213 TACNA-AIS909 Zea mays 0.70746

Tacna ACL-2214 TACNA-AIS911 Vitis sp. 0.70761

Tacna ACL-2215 TACNA-AIS913 Zea mays 0.70663

Yauca ACL-2254 YAUCA-AIS848 Olea europaea 0.70482

Yauca ACL-2255 YAUCA-AIS850 Olea europaea 0.70613

Archaeol Anthropol Sci

87Sr/86Sr=0.70670 (Notsu and Lajo 1984). Soil samplescollected from modern agricultural fields near Cusco, Peruexhibit mean 87Sr/86Sr=0.70980±0.00301 (1σ, n=15)(Tables 2 and 3). The difference in radiogenic strontium

isotope values from different sources in the Cusco regionwill be further explored below using faunal data.

Therefore, in Arequipa, Peru, and Puno, Peru, the mea-sured 87Sr/86Sr values of soil samples collected from modernagricultural fields reflect the expected 87Sr/86Sr values basedon bedrock geology. In these cases, both the published87Sr/86Sr values from exposed bedrock, lake cores andground water and 87Sr/86Sr values from soil samples providean accurate measure of baseline radiogenic strontium isotopesignatures in these regions.

However, there are many parts of the Andes, particularlyon the coast, where published bedrock 87Sr/86Sr values are notavailable. In addition, while the coastal Andean valleys aredominated by Quaternary sedimentary geologic formations(Bellido et al. 1956), riverine and alluvial soils and water inthese regions would incorporate both strontium from theadjacent highlights, composed largely of late Cenozoic volca-nic rock (Bellido et al. 1956), and likely from the PacificOcean (e.g., Whipkey et al. 2000). Soil samples from agricul-tural fields within the same drainage system on the coast arevery similar, as expected. For example, Nazca, Peru andPalpa, Peru are both located within the Nazca Drainage. InNazca, Peru, mean 87Sr/86Sr=0.70624±0.00051 (1σ, n=5),while in Palpa, Peru, mean 87Sr/86Sr=0.70694±0.00048 (1σ,n=14; Table 2). Similarly, soil samples from other sites on thesouthern Peruvian coast, including Atico, Chala, Ica, Ocoña,Pisco, and Tacna, all exhibit similar mean 87Sr/86Sr values.Hence, broad population movements or migration among

0 100 200 300 km

0 100 200 miN

Peru

Pacific

Ocean

Bolivia

Chile

Lake Titicaca

LimaMean Sr/ Sr=0.70722±0.00036 (1 , n=12)Minimum Sr/ Sr= 0.70654Maximum Sr/ Sr= 0.70772

PiscoMean Sr/ Sr: 0.70751±0.00028(1 , n=14)Minimum Sr/ Sr= 0.70704Maximum Sr/ Sr= 0.70801

PalpaMean Sr/ Sr: 0.70694±0.00048 (1 , n=14)Minimum Sr/ Sr= 0.70646Maximum Sr/ Sr= 0.70805

AticoMean Sr/ Sr: 0.70761±0.00081 (1 , n=4)Minimum Sr/ Sr= 0.70689Maximum Sr/ Sr= 0.70849

Yaucan=2Minimum Sr/ Sr= 0.70482Maximum Sr/ Sr=0.70613

CamanáMean Sr/ Sr: 0.70882±0.00075 (1 , n=4)Minimum Sr/ Sr= 0.70836Maximum Sr/ Sr= 0.70968

MeijaMean Sr/ Sr: 0.70801±0.00003 (1 , n=5)Minimum Sr/ Sr= 0.70798Maximum Sr/ Sr= 0.70804 Ilo

n=2Minimum Sr/ Sr= 0.70679Maximum Sr/ Sr= 0.70870

TacnaMean Sr/ Sr: 0.70723±0.00053 (1 , n=4)Minimum Sr/ Sr= 0.70663Maximum Sr/ Sr= 0.70761

Moqueguan=2Minimum Sr/ Sr= 0.70202Maximum Sr/ Sr= 0.70513

PunoMean Sr/ Sr: 0.70835±0.00135 (1 , n=11)Minimum Sr/ Sr= 0.70696Maximum Sr/ Sr= 0.71191

ArequipaMean Sr/ Sr: 0.70797±0.00115 (1 , n=8)Minimum Sr/ Sr= 0.70563Maximum Sr/ Sr= 0.70934

OcoñaMean Sr/ Sr: 0.70754±0.00084 (1 , n=5)Minimum Sr/ Sr= 0.70653Maximum Sr/ Sr= 0.70857

ChalaMean Sr/ Sr: 0.70760±0.00051 (1 , n=3)Minimum Sr/ Sr= 0.70724Maximum Sr/ Sr= 0.70796

NazcaMean Sr/ Sr: 0.70624±0.00051 (1 , n=5)Minimum Sr/ Sr= 0.70565Maximum Sr/ Sr= 0.70673

IcaMean Sr/ Sr: 0.70729±0.00028 (1 , n=4)Minimum Sr/ Sr= 0.70711Maximum Sr/ Sr= 0.70761 Cusco

Mean Sr/ Sr: 0.709080±0.00301 (1 , n=15)Minimum Sr/ Sr= 0.70771Maximum Sr/ Sr= 0.71894

Fig. 3 Map of the study area with sampling locations and mean radiogenic strontium isotope ratios for modern soil samples collected from eachlocation

Table 2 Descriptive statistics for the 87Sr/86Sr values of soil samplesfrom Peru

Site Mean87Sr/86Sr

Standarddeviation

Number Minimum87Sr/86Sr

Maximum87Sr/86Sr

Arequipa 0.70797 0.00115 8 0.70563 0.70934

Atico 0.70761 0.00081 4 0.70689 0.70849

Camaná 0.70882 0.00075 4 0.70836 0.70968

Chala 0.70760 0.00051 3 0.70724 0.70796

Cusco 0.70980 0.00301 15 0.70771 0.71894

Ica 0.70729 0.00028 4 0.70711 0.70761

Ilo NA NA 2 0.70679 0.70870

Lima 0.70722 0.00036 12 0.70654 0.70772

Mejía 0.70801 0.00003 5 0.70798 0.70804

Moquegua NA NA 2 0.70202 0.70513

Nazca 0.70624 0.00051 5 0.70565 0.70673

Ocoña 0.70754 0.00084 5 0.70653 0.70857

Palpa 0.70694 0.00048 14 0.70646 0.70805

Pisco 0.70751 0.00028 14 0.70704 0.70801

Puno 0.70835 0.00135 11 0.70696 0.71191

Tacna 0.70723 0.00053 4 0.70663 0.70761

Yauca NA NA 2 0.70482 0.70613

Archaeol Anthropol Sci

different drainages on the southern Peruvian coast would bedifficult to identify using radiogenic strontium isotope analy-sis alone.

Comparison of baseline radiogenic strontium isotope ratiosfrom bedrock, soil, faunal, and floral samples

Given the various advantages and disadvantages of using dif-ferent sample types to generate baseline radiogenic strontiumisotope ratios (see Table 1 in Evans and Tatham 2004), it isbeneficial to utilize multiple lines of evidence. Combining datafrom soil, water, fauna, and flora gives a reasonable sense of thespatial variation in 87Sr/86Sr values within and between specificgeologic zones (Blum et al. 2000; Evans and Tatham 2004;Hodell et al. 2004). For example, in Mesoamerica and CentralAmerica, there was general agreement among 87Sr/86Srvalues for soil, water, and floral samples within specificgeologic zones, although variability based on strontiumsources in each sample type and the relative strontiumcontributions of each source is also present (Hodell et al.2004). Similarly, in the UK, there is general agreement be-tween bedrock geology and samples from water and plants,though the authors note that marine-derived strontium fromsea spray and rainwater also contribute to bioavailable stron-tium, particularly in western regions (Evans et al. 2010).

With the advantages and disadvantages of different base-line sample types in mind, we turn to a comparison of asubset of 87Sr/86Sr values from contemporary soil sampleswith published 87Sr/86Sr values for both bedrock and faunalsamples from the same Andean regions. As with the previ-ously discussed bedrock data, faunal data do not yet exist forall of the regions included in our soil analyses. However,where both soil and faunal data exist, the two sample typesgenerally have similar 87Sr/86Sr values (Table 3). For exam-ple, as previously discussed, radiogenic strontium isotopedata from agricultural soils and andesite samples fromArequipa, Peru are in very close agreement. In the LakeTiticaca Basin of Peru and Bolivia, faunal bone samplesexhibit mean 87Sr/86Sr=0.70963±0.00028 (1σ, n=8) in theTiwanaku Valley and mean 87Sr/86Sr=0.70888±0.000719(1σ, n=5) in the Desaguadero Valley (Knudson andPrice 2007; Knudson and Torres-Rouff 2009). In com-parison, sediment cores taken from Lake Titicaca exhibitmean 87Sr/86Sr=0.70838±0.00012 (1σ, n=25) (Groveet al. 2003) and soil data from Puno, Peru exhibit mean87Sr/86Sr=0.70835±0.00135 (1σ, n=11).

In the Majes Valley of southern Peru, soil from agriculturalfields near the coastal town of Camaná, Peru exhibit mean87Sr/86Sr=0.70882±0.00075 (1σ, n=4). These data are verysimilar to modern and archaeological faunal data from Beringaand Aplao, located approximately 60 km inland from Camaná,Peru. At the archaeological site of Beringa, faunal bone sam-ples exhibited mean 87Sr/86Sr=0.70836±0.00027 (1σ, n=6),

while modern faunal bone samples from the nearby town ofAplao, Peru exhibited mean 87Sr/86Sr=0.70860±0.00001 (1σ,n=5; Knudson and Tung 2011).

Like the Majes Valley, the Nazca Drainage does not havepublished radiogenic strontium isotope data for bedrock.However, soil and faunal samples from various sites in theNazca Drainage are in close agreement. Soil from modernagricultural fields near the town of Nazca, Peru exhibit mean87Sr/86Sr=0.70624±0.00051 (1σ, n=5), and samples col-lected near the town of Palpa, Peru exhibit mean87Sr/86Sr=0.70694±0.00048 (1σ, n=14). Similarly, modernrodent bone samples from the Middle Nazca Valley exhibitmean 87Sr/86Sr=0.70642±0.00053 (1σ, n=3) and archaeo-logical faunal bone samples from the site of La Tiza exhibitmean 87Sr/86Sr=0.70646±0.00041 (1σ, n=3; Conlee et al.2009), while faunal enamel samples from the Ica, Palpa, andNazca Valleys in the Nazca Drainage exhibit mean87Sr/86Sr=0.70669±0.00026 (1σ, n=14; Horn et al. 2009).Samples from a higher-altitude sampling location in theNazca Drainage had slightly lower radiogenic strontiumisotope values than the samples collected from lower alti-tudes; in the Upper Tierras Blancas Valley, modern faunalbone samples exhibit mean 87Sr/86Sr=0.70587±0.00008(1σ, n=7).

However, some regions exhibited strontium isotopic vari-ability in bedrock, soil, and faunal samples. The largest rangeoccurs in the Cusco region, where one andesite sample ex-hibits 87Sr/86Sr=0.70670 (Notsu and Lajo 1984) and archae-ological enamel samples from Machu Picchu, Peru exhibitmean 87Sr/86Sr=0.71407±0.00014 (1σ, n=3; Turner et al.2009). Between these two extremes, soil from modern agri-cultural fields exhibits mean 87Sr/86Sr=0.70980±0.00301(1σ, n=15). In addition, modern faunal enamel samples fromtwo archaeological sites in the Cusco Valley exhibit mean87Sr/86Sr = 0.70826 ± 0.00027 (1σ , n= 4) and mean87Sr/86Sr=0.70795±0.00013 (1σ, n=4; Andrushko et al.2009). Although faunal samples from Machu Picchu are dis-tinct from other soil and faunal data from the Cusco area(Table 3), Turner et al. (2009) rightfully note that the faunaldata fromMachu Picchu reflect the differences in the bedrockgeology within the region. Similarly, while the andesite pro-vides an accurate reflection of the radiogenic strontium iso-tope values found in late Cenozoic volcanic rocks in theregion, relying solely on 87Sr/86Sr values found in one typeof bedrock in the region would not accurately reflect the inputsfrom different geologic formations found in the Cusco Valley.Therefore, the variability in baseline 87Sr/86Sr values fromCusco, Peru reflects variability in bedrock geology. In thiscase, as in other geologically complex areas, it would be idealto generate baseline data from soil and faunal samples, ratherthan relying on isolated bedrock samples.

Similarly, in the Osmore Drainage of southern Peru, therelatively large range in 87Sr/86Sr values from modern soil

Archaeol Anthropol Sci

Table 3 Descriptive statistics for 87Sr/86Sr values from Peruvian bedrock, soil, and faunal samples

Site, country Sample type Mean 87Sr/86Sra Standard deviation(1σ)

Number Source

Arequipa, Peru

Arequipa, Peru Andesite 0.70737 0.00030 16 James 1982

Arequipa, Peru Andesite 0.70749 0.00050 6 Notsu and Lajo 1984

Arequipa, Peru Soil (modern) 0.70797 0.00115 8 This manuscript

Central Coast, Peru

Lima, Peru Soil (modern) 0.70722 0.00036 12 This manuscript

Ancón, Peru Soil (modern)b 0.70786 b,0.70761 b

NA 2 Slovak et al. 2009

Ancón, Peru Rodent bone (modern andarchaeological)

0.70654 0.00012 5 Slovak et al. 2009

Pachacamac, Peru Rodent bone (modern) 0.70684 0.00016 9 This manuscript

Cusco, Peru

Cusco, Peru Andesite 0.70670 NA 1 Notsu and Lajo 1984

Cusco, Peru Soil (modern) 0.70980 0.00301 15 This manuscript

Tipón, Peru Rodent enamel (modern) 0.70826 0.00027 4 Andrushko et al. 2009

Choquepukio, Peru Rodent enamel (modern) 0.70795 0.00013 4 Andrushko et al. 2009

Machu Picchu, Peru Rodent enamel (archaeological) 0.71407 0.0014 3 Turner et al. 2009

Lake Titicaca Basin, Peru and Bolivia

Lake Titicaca, Bolivia andPeru

Sediment cores (modern) 0.70838 0.00012 25 Grove et al. 2003

Puno, Peru Soil (modern) 0.70835 0.00135 11 This manuscript

Tiwanaku Valley, Bolivia Rodent bone (modern) 0.70963 0.00028 8 Knudson and Price 2007

Desaguadero Valley, Bolivia Rodent bone (archaeological) 0.70888 0.00019 5 Knudson and Torres-Rouff2009

Majes Valley, Peru

Camaná, Peru Soil (modern) 0.70882 0.00075 4 This manuscript

Beringa, Peru Rodent, dog bone (archaeological) 0.70836 0.00027 6 Knudson and Tung 2011

Aplao, Peru Rodent bone (modern) 0.70860 0.00001 5 Knudson and Tung 2011

Nazca Drainage, Peru

Nazca, Peru Soil (modern) 0.70624 0.00051 5 This manuscript

Palpa, Peru Soil (modern) 0.70694 0.00048 14 This manuscript

La Tiza, Peru Rodent bone (archaeological) 0.70646 0.00041 7 Conlee et al. 2009

Middle Nazca Valley, Peru Rodent bone (modern) 0.70642 0.00053 3 Conlee et al. 2009

Upper Tierras BlancasValley, Peru

Rodent bone (modern) 0.70587 0.00008 7 Conlee et al. 2009

Ica, Palpa, and NazcaValleys, Peru

Faunal enamel (archaeological) 0.70669 0.00026 14 Horn et al. 2009

Osmore Drainage, Peru

Ilo, Peru Soil (modern) 0.70679,0.70870

NA 2 This manuscript

Moquegua, Peru Soil (modern) 0.70202,0.70513

NA 2 This manuscript

Ilo, Peru Rodent bone (modern) 0.70671,0.70668

NA 2 Knudson and Price 2007

Chiribaya Baja, Peru Rodent bone (archaeological) 0.70789,0.70672

NA 2 Knudson and Price 2007

Moquegua, Peru Rodent bone (modern) 0.70625 0.00018 3 Knudson et al. 2004

aWhen less than three data points were available, the actual 87 Sr/86 Sr values are listed rather than mean 87 Sr/86 Sr valuesbModern soils from mortuary contexts at the archaeological site of Ancón, Peru were prepared using similar methods as the soil samples in this study(Slovak et al. 2009). Data reported are for the ammonium acetate extractable fraction of soil (Slovak et al. 2009)

Archaeol Anthropol Sci

samples from Ilo and Moquegua, Peru is reflected in therange of 87Sr/86Sr values of archaeological and modern fau-nal samples, particularly from Ilo (Table 3; Knudson andBuikstra 2007; Knudson and Price 2007). This likely reflectsmixing of strontium from different sources in this geologi-cally heterogeneous area (Knudson and Buikstra 2007).

Finally, on the central coast of Peru, there is a smalldifference between radiogenic strontium isotope valuesin soil and fauna samples (Table 3). Soil samples frommodern agricultural fields near Lima, Peru exhibit mean87Sr/86Sr=0.70722±0.00036 (1σ, n=12). Similarly, soilsfrom the archaeological site of Ancón, Peru exhibit87Sr/86Sr=0.70786 and 87Sr/86Sr=0.70761 (Slovak et al.2009). However, archaeological and modern faunal samplesfrom Ancón, Peru exhibit mean 87Sr/86Sr=0.70654±0.00012(1σ, n=5; Slovak et al. 2009), while modern faunal samplesfrom Pachacamac, Peru exhibit mean 87Sr/86Sr =0.70684±0.00016 (1σ, n=9; Table 3). This offset and,more particularly, bioavailable strontium isotope values onthe Central Coast of Peru are currently being investigated.

Conclusion

We measured radiogenic strontium isotope ratios for soil sam-ples frommodern agricultural fields from the following areas incentral and southern Peru: Arequipa, Atico, Camaná, Chala,Cusco, Ica, Ilo, Lima, Mejía, Moquegua, Nazca, Ocoña, Palpa,Pisco, Puno, Tacna, and Yauca. In general, radiogenic stron-tium isotope ratios from soil samples reflect the observed87Sr/86Sr values in bedrock sources, and are in agreement withthe isotopic composition of bioavailable strontium determinedusing faunal samples. The large dataset of 87Sr/86Sr values forsoil samples also helps to point out the regions that can, andcannot, be distinguished in the Andes using this method. Forexample, soil samples from sites on the southern Peruviancoast, including Atico, Chala, Ica, Nazca, Ocoña, Palpa,Pisco, and Tacna, exhibit similar mean 87Sr/86Sr values.Therefore, radiogenic strontium isotope analysis alone wouldnot easily distinguish population movement between differentdrainages on the southern Peruvian coast, although movementsbetween the coast and highlands could be more easily identi-fied. For study sites on, for example, the southern coast of Peru,multiple lines of evidence would be necessary to “geo-locate”an individual to a specific valley. Rather than “geo-locating”individuals who lived in the past, we look forward to futurestudies that instead “geo-restrict” individuals, incorporatingsophisticated understandings of the variability of bioavailablestrontium in the study area, diet, and larger region.

Acknowledgments This project would not have been possible with-out generous funding to White, Knudson, and Longstaffe from theSocial Science and Humanities Research Council of Canada and with

grants to Knudson from the Institute for Social Science Research atArizona State University and the School of Human Evolution andSocial Change at Arizona State University. We are grateful to Dr.Jean-Francois Millaire of The University of Western Ontario and Lic.Estaurdo La Torre for sample collection in the field. In the Archaeolog-ical Chemistry Laboratory at Arizona State University, we are gratefulfor the laboratory assistance of Allisen Dahlstedt and AlejandraGonzalez and the mapmaking expertise of Elise Alonzi. We also thankDrs. Ariel Anbar and Gwyneth Gordon of the W.M. Keck Foundationfor Environmental Biogeochemistry for laboratory access and expertise.Finally, the first author would like to thank a number of scholars forfruitful discussions about isotopic research in the Andes, particularlyDrs. Corina Kellner and Bethany Turner.

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