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Society for American Archaeology

Defining and Measuring Midden CatchmentAuthor(s): James L. Boone, IIIReviewed work(s):Source: American Antiquity, Vol. 52, No. 2 (Apr., 1987), pp. 336-345Published by: Society for American ArchaeologyStable URL: http://www.jstor.org/stable/281785 .

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336 AMERICANANTIQUITY [Vol. 52, No. 2, 19871

Minnis, Paul, and Steven LeBlanc1976 An Efficient, Inexpensive Arid Lands Flotation System. American Antiquity 41:491-493.Schock, Jack M.1971 Indoor Water Flotation: A Technique for the Recovery of Archaeological Materials. Plains Anthro-pologist 16:228-231.Struever, Stuart1968 Flotation Techniques for the Recovery of Small-scale Archaeological Remains. American Antiquity33:353-362.Wagner, Gail E.1982 Testing Flotation Recovery Rates. American Antiquity 47:127-132.Watson, Patty Jo1976 In Pursuit of Prehistoric Subsistence: A Comparative Account of Some Contemporary Flotation Tech-niques. Midcontinental Journal of Archaeology 1:77-100.

336 AMERICANANTIQUITY [Vol. 52, No. 2, 19871

Minnis, Paul, and Steven LeBlanc1976 An Efficient, Inexpensive Arid Lands Flotation System. American Antiquity 41:491-493.Schock, Jack M.1971 Indoor Water Flotation: A Technique for the Recovery of Archaeological Materials. Plains Anthro-pologist 16:228-231.Struever, Stuart1968 Flotation Techniques for the Recovery of Small-scale Archaeological Remains. American Antiquity33:353-362.Wagner, Gail E.1982 Testing Flotation Recovery Rates. American Antiquity 47:127-132.Watson, Patty Jo1976 In Pursuit of Prehistoric Subsistence: A Comparative Account of Some Contemporary Flotation Tech-niques. Midcontinental Journal of Archaeology 1:77-100.

DEFINING AND MEASURING MIDDEN CATCHMENTJames L. Boone, III

The settlementarea that encompassesall the refuse-generatingctivities hat contributeo a single middenmay be referredo as a midden's"catchment."Two related ssues are exploredwith respect o the problemofmeasuringmidden catchment:1) the relationbetweensettlementdensity,middensize, and distribution,andmiddencatchment; nd 2) the relationbetween he heterogeneity f a midden'scontentsand its catchment.

The settlement area that encompasses all the refuse-generating activities that contribute to a singlemidden may be referred to as a midden's "catchment." Because middens typically accumulatematerial from a large surrounding area, analysis of excavated middens can allow the archaeologistto make inferences about activities that occurred in unexcavated areas. Thus the ability to determinesize and extent of midden catchments could be very useful for studying settlement organizationwhen only a sample of a site can be excavated. I explore here two related issues with respect to theproblem of measuring midden catchment. The first is the relation between settlement density, middensize and distribution, and midden catchment. The second concerns the relation between the het-erogeneity of a midden's contents and the relative extent of its catchment area. In the followingdiscussion, I emphasize midden accumulation in village and urban archeological contexts, withexamples based on the result of recent excavations at Qsar es-Seghir, a medieval walled town innorthern Morocco.

EXCAVATIONS AT QSAR ES-SEGHIRQsar es-Seghir is a fortified port settlement located halfway between Ceuta and Tangier on the

Moroccan coast of the Strait of Gibraltar. Originally founded as an Islamic port to Andalusia inthe twelfth century, it was occupied by the Portuguese in 1458 during the first stages of the Iberianexpansionism. The site was almost entirely rebuilt to Portuguese specifications by 1500, but soonafter began to decline as royal interests turned to India and China. In 1550, the settlement wascompletely abandoned, partially razed, and never again reoccupied. The occupational phase understudy here spans approximately the period 1500-1550.Excavations at Qsar es-Seghir were carried out between 1974 and 1980 (cf. Boone 1980; Redman

JamesL. Boone, III, TexasArcheologicalResearchLaboratory,The University f Texasat Austin,BalconesResearchCenter,10,100 BurnetRd.,Austin,TX78758

AmericanAntiquity,52(2), 1987, pp. 336-345.Copyright? 1987 by the SocietyforAmericanArchaeology

336

DEFINING AND MEASURING MIDDEN CATCHMENTJames L. Boone, III

The settlementarea that encompassesall the refuse-generatingctivities hat contributeo a single middenmay be referredo as a midden's"catchment."Two related ssues are exploredwith respect o the problemofmeasuringmidden catchment:1) the relationbetweensettlementdensity,middensize, and distribution,andmiddencatchment; nd 2) the relationbetween he heterogeneity f a midden'scontentsand its catchment.

The settlement area that encompasses all the refuse-generating activities that contribute to a singlemidden may be referred to as a midden's "catchment." Because middens typically accumulatematerial from a large surrounding area, analysis of excavated middens can allow the archaeologistto make inferences about activities that occurred in unexcavated areas. Thus the ability to determinesize and extent of midden catchments could be very useful for studying settlement organizationwhen only a sample of a site can be excavated. I explore here two related issues with respect to theproblem of measuring midden catchment. The first is the relation between settlement density, middensize and distribution, and midden catchment. The second concerns the relation between the het-erogeneity of a midden's contents and the relative extent of its catchment area. In the followingdiscussion, I emphasize midden accumulation in village and urban archeological contexts, withexamples based on the result of recent excavations at Qsar es-Seghir, a medieval walled town innorthern Morocco.

EXCAVATIONS AT QSAR ES-SEGHIRQsar es-Seghir is a fortified port settlement located halfway between Ceuta and Tangier on the

Moroccan coast of the Strait of Gibraltar. Originally founded as an Islamic port to Andalusia inthe twelfth century, it was occupied by the Portuguese in 1458 during the first stages of the Iberianexpansionism. The site was almost entirely rebuilt to Portuguese specifications by 1500, but soonafter began to decline as royal interests turned to India and China. In 1550, the settlement wascompletely abandoned, partially razed, and never again reoccupied. The occupational phase understudy here spans approximately the period 1500-1550.Excavations at Qsar es-Seghir were carried out between 1974 and 1980 (cf. Boone 1980; Redman

JamesL. Boone, III, TexasArcheologicalResearchLaboratory,The University f Texasat Austin,BalconesResearchCenter,10,100 BurnetRd.,Austin,TX78758

AmericanAntiquity,52(2), 1987, pp. 336-345.Copyright? 1987 by the SocietyforAmericanArchaeology

336


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1986; Redman and Anzalone 1980). To date, over 18% of the 2.83 ha area within the walls of thesettlement has been excavated in the late Portuguese levels using both probability and judgmentsampling strategies. The excavations have revealed a densely occupied settlement organized arounda main plaza, with two churches, an assembly hall, and numerous residences and light industrialstructures.

MIDDEN SIZE AND DISTRIBUTIONTwo proximate factors determine the size-considered as the total quantity of artifacts-of a

midden. The first is the number of people contributing to the midden, which affects the rate ofartifact accumulation. The settlement space that these contributors take up in refuse-producingactivities constitutes what has been defined above as midden catchment. Given the spatial analyticalfocus of this discussion, I will be concerned primarily with accumulation rate as a function of activityspace, rather than numbers of contributors per se. The second factor affecting midden size is thelength of time the midden has taken to accumulate. For the moment, let us consider only the firstfactor and assume that accumulation time is constant. I return to the problem of variable accu-mulation time below.In densely occupied urban and village contexts, dumping generally occurs in abandoned roomsor other confined spaces not currently in use. The denser the occupation, the fewer abandonedspaces are available for refuse disposal. As occupational density increases and dumping areas becomemore restricted, it can be hypothesized that the area of refuse-producing activity contributing toany single midden, i.e., midden catchment, will tend to increase, as will the average size of individualmiddens in the settlement (Schiffer 1976:14-15).If midden accumulation was synchronous over an entire settlement, if occupation density andrefuse-producing activities were uniform over the settlement, and if people adhered to the leasteffort principle with regardto disposal of their refuse, we could expect a pattern of middens of equalsize dispersed evenly throughout the settlement. Each midden would have a catchment of equalsize, and midden size and dispersion would be entirely a function of activity density. Few settlementsare likely to conform to such ideal criteria. However, it is worthwhile to keep in mind the conditionsthat would create this ideal pattern in order to lay the groundwork for the systematic interpretationof expectable deviations from it. For example, spatial variation in occupational density within asettlement would be one obvious reason for nonuniform size and distribution of middens in asettlement, as the following example will illustrate.Figure 1 shows a map of the excavations of the late Portuguese occupation of Qsar es-Seghir,showing the size, location, and relative density of middens in relation to occupied space. Thesettlement was encircled and constrained by high walls and a moat, and had only three relativelyrestricted entrances. All the space within the walls was taken up with architecture. The largerexcavated areas of the site were subdivided into areas corresponding to "blocks" on the basis ofstreet patterns (see Figure 2). Within these areas, the small black squares denote the location ofdumps containing between 600 and 1,500 pottery sherds, the smaller triangles 1,500 to 3,600 sherds,and the larger triangles, between 6,000 and 10,000 sherds (there were no middens in the 3,600 to6,000 sherd range). The figures beside each area indicate the ratio of rooms or other walled spacesabandoned to dumping to the number of rooms still in use at site abandonment within in theexcavation area. The isopleth divides the site into areas of more and less than the average ratio(.23) of dumps to usable rooms.Areas of highest dumping density cluster around the periphery of the site, away from the entrancesto the walled town, and in an area near the center of town. Figure 2 shows the two long main streetsthat connect the main plaza with the two land entrances. A third entrance through the town wallswas located just southeast of the citadel. The greatest competition for space occurred along thesestreets and around the main plaza. These high settlement density areas correspond to areas of leastdumping density.The shading in Figure 1 indicates the area of greatest residential density (as opposed to the religiousand administrative buildings around the main plaza in the northwest center of the town and the


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338 AMERICANANTIQUITY [Vol. 52, No. 2, 1987]

:25

Figure1. Planof excavatedareasof site showingdumpingpatterns.Shadedarea s zone of densesthabitation.Large triangles ndicatedumps located n abandoned oomsorbuildings)containing6,000-10,000 ceramicandglass sherds;small triangles,1,500-3,600 sherds; squares,600-1,500 sherds. Figures indicateratio of roomsabandonedo dumping o number f roomsstill in use withinanexcavatedarea.Isoplethdividessettlementareainto areasof more and less than the average ratio (.23) of dumpsto usable rooms.Asteriskindicatesthat allavailablespaceswith the excavationunit weregiven over to dumping.

less densely packed settlement area around the periphery of the site and away from the main streets).This area was delineated by an independent analysis of architectural space use (cf. Redman andAnzalone 1980:287). This residential sector can be assumed to be the greatest refuse-producing areaas well. Significantly, the four largest dumps excavated, which averaged twice as large as the nextsmallest size category of dumps, lie right at the edge of this dense habitation zone. Dumping siteswere clearly limited within the zone, but the inhabitants wasted little effort in taking their refuse tothe nearest available abandoned space in the less densely packed areas around it. This patternsupports the prediction made previously that midden size increases with settlement density, as wellas the assumption concerning least effort.There is also a great deal of variation in dump size, indicating either that there is variability inaccumulation time, that not all areas of the site are producing refuse at the same rate, or that somedumps have larger catchment areas than others. Clearly, the large central dumps, being surroundedby an extensive, densely settled, high traffic area, probably have a much larger than average catch-ment. Generally, however, it is at this point impossible to distinguish whether midden size in anyparticular case is due to accumulation from a small catchment over a long time or a large catchmentover a short time. In order to accomplish this distinction, we turn now to a consideration of middenheterogeneity as an auxiliary means of estimating midden catchment.


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~ ~ N~~OVENVEN0s ? RESS

\~~~~~\ / /

HURC ILLMILL (ANI

0 somFZ-GAT E

Figure2. Plan of settlementbasedon excavations, howing treet patternsand ocationof important uildingsand light industrialareas. Stippled areas denote streets and plazas actually excavated;dotted lines indicatehypotheticalconnecting treets.

MEASURING MIDDEN HETEROGENEITYTo the extent that variability exists in the spatial distribution of refuse-producing activities in a

site, the contents of any particular midden will vary according to which activities are taking placewithin its catchment. We might conceptualize all the artifact deposition that takes place within theconfines of a settlement during a given time period as a single global "dump" whose catchmentincludes the entire area of the site. The overall relative frequency of artifacts in this site wouldreflect the site-wide mix of activities particular to that settlement (that is, as a function of the varyingamounts of refuse each activity might produce; this, of course, is not the same as the relativefrequency of the activities themselves). Individual middens on the site would be attracting materialfrom some smaller proportion of the settlement activity space, and hence, a smaller portion of theactivities. How closely the mix of activities in the catchment of a particular midden approximatesthe mix of activities on the entire site, then, could constitute a useful measure of midden catchment.The following measure of midden heterogeneity was developed as a potential means of measuringmidden catchment.Heterogeneity (also referred to as "evenness," Pielou 1977: 14) is a measure of diversity that takes


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into account not only the number of different classes of entities in a population, but their proportionalrepresentation as well. Perfect heterogeneity is reached when all defined categories of entities in apopulation are present in equal quantities. Perfect homogeneity exists when the population consistsalmost entirely of only one category. In analyzing a series of refuse deposits excavated from Qsares-Seghir, a measure of heterogeneity was constructed in which the site-wide artifact mix, that is,the relative proportions of artifacts over the whole site, is considered "perfectly heterogeneous" inthat it reflects the relative proportion of refuse-producing activities over the whole settlement (atleast in terms of the amounts of artifacts they produced). This expression of site-wide activity mixwas used as a baseline from which to measure local differences in activity structure.

Because various artifacts in a site have very different overall deposition rates, a weighting systemwas employed that equalized overall variation in artifact deposition rate and isolated the effects oflocal variations due to localized differences in the activity mix. The result is that site-wide relativefrequencies, when subjected to the weighting procedure, appear as an array of equal values reflectingthe "perfect heterogeneity" of the site-wide activity mix. Observed relative artifact frequencies forindividual midden deposits within the site will deviate from this expected array of equal values tovarying degrees. The heterogeneity measure is calculated for each individual midden and constitutesthe sum of the squared deviations of the observed relative frequencies from the expected site-widearray. A small value for a particular midden would indicate less deviation from the site-wide activitymix (in other words, greater heterogeneity) and a greater evenness of activities. Largervalues of themeasure reflect greater deviation from the site-wide activity mix, and hence, that a more homo-geneous mix of activities had occurred within the catchment of that particular midden. The com-putational details of this measure are as follows:

1) The raw data consist of frequency counts (denoted yij) of an array of artifact classes (i) from aset of discrete midden deposits (i). Site-wide totals of each artifact class are denoted Yj.2) An expression of site-wide relative frequencies is obtained by computing the ratio of one classtotal to each remaining class total. In this case, the class that was generally the most frequent inany deposit, plainware, was chosen. This ratio becomes the weighting factor (JWj),where Wj= Ypi,n/Yj.The weighting factor is an expression of the estimated site-wide deposition rate of a given artifactclass relative to the deposition rate of plainware.

3) The observed frequencies yij in each deposit are multiplied by their respective weighting factorsWj, producing weighted counts (Wjyij).Weighted counts are the counts that would obtain if eachartifact class under consideration had the same site-wide deposition rate.4) Weighted percentages are obtained by taking the row percentages of each observation, in whichthe raw counts have been converted to weighted counts:

wjyij

5) An array of site-wide expected values (Pj) is produced by taking the weighted percentages ofthe site-wide class totals:

p - WjYj

This, of course, results in a closed array of identical values. For example, if there are 10 artifactclasses included in the analysis, Pj for each class would be .10. These identical values reflect perfectheterogeneity. That is, any deposit producing the expected array of values of pj will contain exactlythe same artifact mix as the site as a whole. The observed values of pij, then, constitute a measureof deviation from the expected Pjs.6) Finally, an expression of heterogeneity of a particular deposit would be the sum of the squareddeviations from the expected array:Hi,= p -Pj)where smaller values indicate greater heterogeneity, or evenness. It should be emphasized that"heterogeneity" here is measured in relation to the site-wide artifact mix. The site-wide artifact mix


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HighDeviation

L wJ00

LowDeviation

DEPOSIT SIZE -Figure3. Graphshowing predicted urvesproducedby plottingdumpsize andheterogeneityn threehypo-thetical settlementsituationswith a) fine-grained,b) coarse-grained, nd c) sectoredspatial distributionofactivities.The dottedLine C denotes that little or no correlationbetweendeposit size and heterogeneitysexpected,andthat points representingmiddenswouldbe scattered n the upperhalf of the graph.

is "perfectly heterogeneous" because it encompasses the widest possible range of artifact-producingactivities. In the sense intended here, a particular deposit would be "perfectly heterogeneous" if itaccumulated each artifact class at the same relative rate as the entire site.ACTIVITY STRUCTURE AND MIDDEN HETEROGENEITY

If the activity structure of the site in question was such that the larger the catchment of a dump,the more different kinds of activities (and therefore kinds of artifacts) would be encompassed by it,then midden heterogeneity could be expected to increase (values of Hi become smaller) in directproportion with midden size, and the regression line of a plot of the two variables would be astraight line. Of course, in an actual site it would be more likely that midden catchment wouldincrease up to a point where evenness of activities is approximated before it actually encompassedthe entire settlement space. In this case, heterogeneity would tend to increase at a slower and slowerrate with midden size, producing a curve at the end of the regression line. At the same time, at theother end of the regression, where deposits are very small and homogeneous due largely to thestochastic nature of the accumulation process, values of the sum-squared deviations would startout very high, slowly flatten out to values representative of the homogeneous nature of localizedactivities, and then gradually approach perfect heterogeneity. Thus, the regression line describingthe relation between dump size and heterogeneity would more likely approximate a curve such aspictured in Figure 3.In any case, the overall activity structure of the site in question will have a predictable effect onthe shape of this curve. For example, consider a site where artifact deposition reflects a set ofactivities evenly interspersed over the whole settlement (example: a village of households all engagedin similar subsistence activities or occupations). In such a case, the catchment area of a middenwould not have to extend out very far before it encompassed all the activities that would take place


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a)E DABDA BCEDC E DABDABCADCDAE )

b) BFmnegrained B BBCCCE E A cEE AAA DDDD

c)Coarse grained

/ A BE

D c /

SectoredFigure 4. Schematic plan of the spatial distribution of activities in three idealized settlements with fine-grained, coarse-grained, and sectored activity structures. Letters indicate location of hypothetical activities A,B, C, D, and E, each of which produces distinct artifact types.

on the site and the artifact mix of the midden would rapidly approximate that of the whole site.This "fine-grained" activity structure (refer to Figure 4) would produce a line approximating LineA in Figure 3, where sum squared deviations start out high due to stochastic variability, but reachmaximum heterogeneity very quickly. Consider, though, another settlement situation where discreteactivity areas are segregated into rather larger activity clumps (example: a village with differentiatedcraft or subsistence production associated with various households). In this case, the midden'scatchment would have to expand to encompass at least one of each activity clump before it wouldapproximate perfect heterogeneity. Thus in a "course-grained" situation, the fall-off of the curvewould be considerably slower (as in Line B).A third contrasting situation would be where refuse-producing activities are segregated into large,discrete activity sectors (example: a settlement where various production activities and residentialquarters are spatially segregated). In the sectored model, the catchment area of any given dumpwould have to encompass practically the entire site before it began to accumulate various activity-related artifacts at the same relative frequency as the site-wide mix. In the sectored model, then,the overall correlation between dump size and heterogeneity should be very low: points representingthe various dumps would be scattered in a cloud in the upper regions of the graph (symbolized byLine C).To summarize, in a fine-grained activity pattern, we would expect to see points distributed in arelatively thin, parabolic band along the x and y axes, with a high correlation between deposit sizeand heterogeneity (Line A, Figure 4). In a coarse-grained activity situation, the plotted points wouldlie in a wider band along Line B in Figure 4, with a correspondingly lower correlation between thetwo variables. Finally, with the sectored activity pattern (Line C), points would be scattered overthe upper regions of the graph, and we would expect to see little correlation between midden sizeand heterogeneity.

These three activity structure models are of course highly idealized: no actual settlement situationwill conform perfectly to one type or another. But it can be worthwhile to plot refuse deposits inthis manner to gain an overall idea of how a series of deposit accumulations are "behaving" with


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\0 /5000 ~ ~ ~ ~ ~ ~ ~ ~~~~~4000 - - -

Z 20000

*-

o3000 .I.

.0 .

o 200 0J.4.....

0 1000- H *-= %- -

20. 000 I600 220 S= 360

DEPOSITSIZEFigure5. Scatterplotof valuesof Hi againstdepositsize (low deviationvaluesapproach"perfectheteroge-neity" in relation to site-wideartifactmix, as explainedin text). Dotted line isolates two extreme outliersdescribedn text.

respect to the adjacent activities they reflect. Figure 5 shows a plot of dump size and heterogeneityat Qsar es-Seghir, based on the relative frequencies of nine pottery ware types. I have included allroom deposits on the site with over 50 sherds. Thus, primary and de facto refuse accumulationsare probably included. These would produce high sum-squared deviation values because they reflectvery localized activities. The curve represented by this plot appears to conform to the "fine-grained"model. This conclusion is corroborated by analysis of architectural features on the site. The townwas principally a garrison containing the residences of soldiers, tradesmen, and merchants with theirfamilies. Low-level settlement maintenance/production activities were interspersed throughout theresidential areas (see Figure 2), which took up most of the site. The only perceptible differentiationin the town (other than the public versus residential sector, which was distinguished architecturally,as discussed above) is a tendency for high-status residences to occur near the main plaza and alongthe two streets connecting the plaza with the two gates. These were detectable through differentialdeposition of imported display wares (Boone 1980; Redman and Anzalone 1980).Another interesting aspect of this plot is that the point where deposits begin to approximate perfectheterogeneity coincides with a rapid fall-off in the overall number of deposits (at around 600 artifacts),indicating that the depositional behavior that resulted in their formation was distinct from that ofmost smaller deposits. In fact, the heterogeneity measure is a good general technique for distin-guishing quantitatively between primary/de facto and secondary refuse deposits. Two extremeoutliers in the scatter plot (outlined by dashed lines) provide an illustration of this point. These twoprovenience units are actually the result of one depositional episode, and were excavated a yearapart in adjacent squares on the main plaza of the site. They are apparently the result of more thana dozen large globular flasks being dropped in transport and later smashed into about 3,800 smallpieces by carts and other traffic. Thus, they are the result of a very localized activity uncharacteristicof the site-wide activity mix.Earlier in this discussion, I pointed out that a major problem with predicting refuse catchment


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sooo-w2500

2500 ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~~~~~0oo* 0* * 0

0~~~~~~~~~~~0 0>:25 - * -2500- \0 Soo- *00

momen oreato is 63~~~~~~o10020 - 50 100 250 - 00 * 10000; *

from midden size is that it is impossible to tell from size alone whether a midden is the result of asmall catchment accumulating material over a long time or a large catchment accumulating materialover a short time. Plotting heterogeneity and dump size presents a potential solution to this problem.Individual deposits that fall far above the regression line represent deposits that are much lessheterogeneous than would be predicted by size. Following the logic of the heterogeneity measurepresented here, these deposits should represent accumulations of comparatively small catchmentsover a long time. By the same token, points falling below the line represent middens that are moreheterogeneous than predicted and should indicate middens that have just begun to accumulatematerial from a comparatively large area of the settlement. Of course, the reliability of this distinctiondepends initially upon how well heterogeneity is predicted by size in general (estimated by the valueof r), and hence, on the general predictability of the overall activity structureof the site. In a sectoredsettlement, a large dump exhibiting a high deviation from the site-wide mix might just be accu-mulating material from a large catchment encompassing a small range of activities within one sector.In order to determine how much midden heterogeneity is predicted by deposit size in this testcase, I linearized the regression model by plotting the relation between the logarithms of the twovariables. The resulting plot is presented in Figure 6. An r value was calculated at - .63, indicating(as r2-)hat about 40% of the variation in heterogeneity is predicted by deposit size alone.

DISCUSSIONI present here a way of thinking about artifact accumulation in middens within the context ofartifact deposition over the entire site. A measure of deposit heterogeneity was developed that wasderived directly from the logic of the deposit accumulation process. The heterogeneity measure fails

to measure midden catchment in an absolute sense, but does prove to be a useful way of characterizingindividual accumulations in relation to the site-wide activity/artifact mix. By plotting a number ofsuch accumulations by size and heterogeneity, it is possible to make useful statements about the


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activity structure of a site. Clearly, this method is most useful in excavation situations that producea large number of separate provenience units.A few remarks regarding sample size effects are appropriate here. Kintigh (1984) has discussedthe effects of sample size on measures of diversity. His concern was with diversity considered asthe number of different classes of artifacts in a sample. In the present study, I am concerned withevenness expressed in terms of relative proportions of selected classes. In employing the measureof heterogeneity, I attempted to strike a balance between including as many ceramic classes aspossible while at the same time not including classes that were rare over the whole site. Increasingthe number of classes decreases the relative effect of zero frequencies on the rest of the values ofpij,while selecting relatively abundant classes will decrease the likelihood that zero frequencies willoccur by chance alone, except among the smallest midden accumulations. As previously discussed,low sample sizes will produce high values of Hi among the smallest accumulations, but as middensize increases, settlement activity structure will be the predominant factor in shaping the curveproduced by plotting Hi against midden size.This analysis was designed specifically for within site investigation of village or urban contexts.However, the general approach could easily be extended to apply to other kinds of problems. Forexample, artifact accumulations within individual settlements could be investigated in relation toaccumulation over an entire settlement system. Data on site specific deviations from the settlementwide mix could be used to measure the degree of functional differentiation within the system.

Acknowledgments.I thank Albert Ammerman, George Cowgill, Keith Kintigh, Emlen Myers, CharlesL.Redman,the reviewers,and the Editorfor theirhelpful comments in the preparation f this report.Part of theresearch orthis study was funded by National Science FoundationResearchGrant BNS-80-02289.

REFERENCES CITEDBoone, J. L.

1980 Artifact Deposition and Demographic Change: An Archeological Case Study of Medieval Colonialismin the Age of Expansion. Ph.D. dissertation, SUNY-Binghamton. University Microfilms, Ann Arbor, Mich-igan.Kintigh, Keith W.1984 Measuring Archaeological Diversity by Comparison with Simulated Assemblages. American Antiquity49:44-54.Pielou, E. C.1977 Ecological Diversity. John Wiley and Sons, New York.Redman, C. L.1986 Qsar es-Seghir: An Archeological View of Medieval Life. Academic Press, New York.Redman, C. L., and R. A. Anzalone1980 Discovering Architectural Patterning in a Complex Site. American Antiquity 45:284-290.Schiffer, M. B.1976 Behavioral Archeology. Academic Press, New York.

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