| Literature DB >> 29902207 |
Jon-Paul P McCool1,2, Samantha G Fladd3,4, Vernon L Scarborough3, Stephen Plog5, Nicholas P Dunning1, Lewis A Owen6, Adam S Watson7, Katelyn J Bishop8, Brooke E Crowley3,5, Elizabeth A Haussner6, Kenneth B Tankersley3,6, David Lentz9, Christopher Carr1, Jessica L Thress3.
Abstract
Questions about how archaeological populations obtained basic food supplies are often difficult to answer. The application of specialist techniques from non-archaeological fields typically expands our knowledge base, but can be detrimental to cultural interpretations if employed incorrectly, resulting in problematic datasets and erroneous conclusions not easily caught by the recipient archaeological community. One area where this problem has failed to find resolution is Chaco Canyon, New Mexico, the center of one of the New World's most vibrant ancient civilizations. Discussions of agricultural feasibility and its impact on local population levels at Chaco Canyon have been heavily influenced by studies of soil salinity. A number of researchers have argued that salinized soils severely limited local agricultural production, instead suggesting food was imported from distant sources, specifically the Chuska Mountains. A careful reassessment of existing salinity data as measured by electrical conductivity reveals critical errors in data conversion and presentation that have misrepresented the character of the area's soil and its potential impact on crops. We combine all available electrical conductivity data, including our own, and apply multiple established conversion methods in order to estimate soil salinity values and evaluate their relationship to agricultural productivity potential. Our results show that Chacoan soils display the same salinity ranges and spatial variability as soils in other documented, productive fields in semi-arid areas. Additionally, the proposed large-scale importation of food from the Chuska Mountains region has serious social implications that have not been thoroughly explored. We consider these factors and conclude that the high cost and extreme inflexibility of such a system, in combination with material evidence for local agriculture within Chaco Canyon, make this scenario highly unlikely. Both the soil salinity and archaeological data suggest that there is no justification for precluding the practice of local agriculture within Chaco Canyon.Entities:
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Year: 2018 PMID: 29902207 PMCID: PMC6002086 DOI: 10.1371/journal.pone.0198290
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Fig 1General location of Chaco Canyon Cultural Historical Park in relation to the Chuska Mountains.
Four Corners is in upper left corner of figure at intersection of black state lines. Only selected major drainages contributing to or near Chaco Wash are represented. Black triangles are the three closest pedons to Chaco Canyon that have been sampled by the USDA.
Comparison of variations in electrical conductivity measurement.
| Common Name | Common Abbreviation(s) | Soil to Water Ratio | Brief Description | Common Complicating Factors | Methodological influence on measured EC |
|---|---|---|---|---|---|
| Soil Water Extract | None | Variable | Water is extracted from the soil in the field by applying a vacuum to a soil surface. Soil water flows under pressure to a collection cup for measurement. | field moisture content, temperature | Ion concentration and resulting measured EC dependent upon field water content at the time of observation. Good for measuring temporal change in local EC, but not possible to compare measurements between overall locations. Conductivity increases 1.9% for every degree centigrade of increased temperature [ |
| Extract of Saturated Paste | ECe; ECse; ECSP | Variable | Water is mixed with soil until it reaches saturation, and then this moisture is extracted under a vacuum from the solid soil. Amount of water used is dependent upon soil texture, and a general expectation is to recover 1/3 of added water upon extraction. | technician experience, saturation percentage variation, equilibration time, temperature | Method requires technician interpretation of qualitative attributes in sample production and is susceptible to variation based on experience. Insufficient equilibration time may result in an underestimation of EC. |
| Aqueous Mixture; Soil to Water Dilution | EC1:1 | 1:1 | A given mass of soil is mixed with its equivalent volume of water. E.g. 10 grams of soil with 10 ml of water for a 1:1 ratio. It is then allowed to sit, often with occasional stirring, in order for the solution to equilibrate. Equilibration time, stirring method, and dilution ratio can be highly variable between studies. | equilibration time, extraction under vacuum versus direct measurement on soil to water mixture, dried & disaggregated sample versus ground sample, temperature | The concentration of ions in solution will decrease with higher dilution ratios and result in a lower measured EC. Direct measure of soil-water mixture will include conductivity due to clays whereas conductivity of an extract will be of ions alone. Insufficient of equilibration time may result in an underestimation of EC. This may be counteracted by grinding the sample, and thus increasing total surface area for dissolution, but may also increase hydrolysis of minerals and contribute to an artificial increase in EC. |
| EC1:2 | 1:2 | ||||
| EC1:2.5 | 1:2.5 | ||||
| EC1:5 | 1:5 |
Conversion equations for estimating measured electrical conductivity on a saturated extract.
| Original Measurement | Equation | Model r2 | Specified Texture | Notes | Source |
|---|---|---|---|---|---|
| 1:1 | ECe = 3(EC1:1) | -- | -- | Theoretical & likely to produce a higher predicted than necessary. Specific multiplication factors for conversion ranged between 2.78 and 1.6 based on the dominant salt type. | [ |
| 1:1 | ECe = 3.01(EC1:1) -0.06 | 0.98 | Coarse | Suspension to Saturated Extract | [ |
| 1:1 | ECe = 3.01(EC1:1) -0.77 | 0.98 | Medium | Suspension to Saturated Extract | [ |
| 1:1 | ECe = 2.66(EC1:1) -0.97 | 0.98 | Fine | Suspension to Saturated Extract | [ |
| 1:1 | ECe = 1.85(EC1:1) | 0.85 | -- | Only the regression without y-intercept was used in their validation. The regression equation of their validation set is also significantly different than that of their training set. Only their equation without a y-intercept is used here. | [ |
| 1:1 | ECe = 3.01(EC1:1) -0.06 | -- | Coarse | Specifically states they are not well calibrated & are a rough guide to interpretation only | [ |
| 1:1 | ECe = 3.01(EC1:1) -0.77 | -- | Medium | Specifically states they are not well calibrated & are a rough guide to interpretation only | [ |
| 1:1 | ECe = 2.96(EC1:1) -0.95 | -- | Fine | Specifically states they are not well calibrated & are a rough guide to interpretation only | [ |
| 1:1 | ECe = 1.93(EC1:1) -0.57 | -- | -- | 1:1 predictions were closer to ECe than their other dilutions (1:2.5, 1:5) | [ |
| 1:1 | ECe = 2.72(EC1:1) -1.27 | 0.99 | Sandy | -- | [ |
| 1:1 | ECe = 2.42(EC1:1) | 0.98 | Sandy | -- | [ |
| 1:1 | ECe = 2.15(EC1:1) -0.44 | 0.99 | Loamy | -- | [ |
| 1:1 | ECe = 2.06(EC1:1) | 0.98 | Loamy | -- | [ |
| 1:1 | ECe = 2.23(EC1:1) -0.58 | 0.98 | Combined | -- | [ |
| 1:1 | ECe = 2.11(EC1:1) | 0.98 | Combined | -- | [ |
| 1:1 | ECe = 3.35(EC1:1) | 0.95 | — | -- | [ |
| 1:2 | ECe = 2.79(EC1:2) +0.71 | 0.91 | Coarse | Extract to saturated extract | [ |
| 1:2 | ECe = 2.35(EC1:2) -0.36 | 0.95 | Medium | Extract to saturated extract | [ |
| 1:2 | ECe = 2.16(EC1:2) +0.03 | 0.97 | Fine | Extract to saturated extract | [ |
| 1:5 | ECe = 5.97(EC1:5) -1.17 | -- | -- | 1:1 predictions were closer to ECe than their other dilutions (1:2.5, 1:5) | [ |
| 1:5 | ECe = 8.22(EC1:5) -0.33 | 0.98 | Sandy | -- | [ |
| 1:5 | ECe = 7.98(EC1:5) | 0.98 | Sandy | -- | [ |
| 1:5 | ECe = 7.58(EC1:5) +0.06 | 0.99 | Loamy | -- | [ |
| 1:5 | ECe = 7.62(EC1:5) | 0.99 | Loamy | -- | [ |
| 1:5 | ECe = 7.68(EC1:5) -0.16 | 0.98 | Combined | -- | [ |
| 1:5 | ECe = 7.57(EC1:5) | 0.98 | Combined | -- | [ |
| 1:5 | ECe = 5.35(EC1:5) | 0.96 | Combined | See source for greater range of specialized conversions by texture & presence of gypsum | [ |
| 1:5 | ECe = 7.31(EC1:5) | 0.91 | none | -- | [ |
| 1:5 | ECe = (EC1:5)(Q1:5/Qe) | -- | sample | Q1:5 can be assessed as (500 + 6ADMC) for a 1:5 soil to water suspension (where ADMC is air dry moisture content expressed as kg/100 kg). | [ |
| ECe | EC1:1 = 0.33(ECe) +0.06 | -- | Coarse | Specifically states they are not well calibrated & are a rough guide to interpretation only | [ |
| ECe | EC1:1 = 0.33(ECe) +0.77 | -- | Medium | Specifically states they are not well calibrated & are a rough guide to interpretation only | [ |
| ECe | EC1:1 = 0.375(ECe) +0.97 | -- | Fine | Specifically states they are not well calibrated & are a rough guide to interpretation only | [ |
This table shows estimated crop yield declines at particular soil or irrigation water conductivities.
ECe is a measurement on the extract from a saturated soil paste. ECw is the conductivity of irrigation water with yield declines based on an estimated 15–20% leaching fraction. These data are always presented as guidelines, not definitive limits, and are for modern crop varieties. Given the range of tolerance within a given crop type, see squashes, it is possible that varieties used by Chacoan farmers were less susceptible than modern varieties largely grown in wetter climates. Data, except for sunflower, is from [81]. Amaranthus, found to be part of diets at Salmon Ruin and Antelope House, is considered a tolerant plant to salinity [82]. Chenopodium, Amaranthus, and Asteraceae were found to be significant diet contributions [82], and each is considered a halophytic, or salt adapted, plant.
| Yield Decline Percentage | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| 0% | 10% | 25% | 50% | 100% | ||||||
| Crop | ECe | ECw | ECe | ECw | ECe | ECw | ECe | ECw | ECe | ECw |
| Corn ( | 1.7 | 1.1 | 2.5 | 1.7 | 3.8 | 2.5 | 5.9 | 3.9 | 10 | 6.7 |
| Sunflower ( | 4.8 | / | 6.8 | / | 9.8 | / | 14.8 | / | 24.8 | / |
| Squash, scallop ( | 3.2 | 2.1 | 3.8 | 2.6 | 4.8 | 3.2 | 6.3 | 4.2 | 9.4 | 6.3 |
| Squash, zucchini ( | 4.7 | 3.1 | 5.8 | 3.8 | 7.4 | 4.9 | 10 | 6.7 | 15 | 10 |
| Bean ( | 1 | 0.7 | 1.5 | 1 | 2.3 | 1.5 | 3.6 | 2.4 | 6.3 | 4.2 |
1This is for sweet corn or grain corn. For forage corn, it is given as 1.8 with a decrease of 7.5% per 1 dS/m increase, not the 12% presented here.
2Based on the initial threshold and 5% seed yield reduction per unit dS/m increase.
Fig 2Shows the relation of key water characteristics for 113 observations between 8/6/1976 and 10/6/1983.
The average for pH (7.55) and EC (0.46) are each indicated by a solid line behind each data type. Chaco discharge is shown for visual comparison of covariation between periods of increased flow and EC.
Fig 3Shows SAR variation from 41 measurements from 8/6/1976 to 10/6/1983.
Max SAR/fine—the highest flat horizontal line—is the maximum SAR value usable for irrigation on fine textured soils under any management practice and is the highest flat horizontal line. Mean SAR represents the value of 5.74. No SAR issues—the horizontal shaded area at the base—indicates that below a value of 3 there is no projected impact from the Na composition. The Na/SO4 Ratio is the simple ratio of the USGS data for each reported in mg/L. Shaded vertical bars indicate the seasonal period of precipitation at Chaco Canyon: July through October.
Fig 4Figure shows the location for all known soil salinity samples in the main are of Chaco Canyon.
Larger circles are to avoid providing precise location information for non-public archaeological areas. Selected profiles are presented with values for single depth samples shown next to their location. Blue circles, connected by a simple smoothed line for visual interpretation, represent estimated ECe values in profiles. For sources that specify a depth range for specific samples, point depth is the range midpoint. For each salinity graph, the Y-Axis is Depth (cm), and the X-Axis is Estimated ECe. Vertical lines represent varying yield decrease thresholds for maize (moving left to right): Yellow = 0%, Peach = 10%, Orange = 25%, Brown = 50%, and (when shown) Red = 100%. See S1 Table for raw and converted data.
Estimated time and labor efforts for Chuska residents to transport maize to Chaco Canyon based on varying population sizes, carrying capacities, and travel times.
Drennan [132] used loads of 20 and 50 kilograms in his studies of long distance transport. The final weight estimate derives from Malville [131], as reported in Windes and McKenna ([142] p136).
| Weight Carried per Person per Trip (kg) | Chaco Population of 2,000: 304,200 kg Maize | Chaco Population of 5,000: 895,700 kg Maize | ||
|---|---|---|---|---|
| Percentage of 10,625 Chuska Population | Percentage of 17,000 Chuska Population | Percentage of 10,625 Chuska Population | Percentage of 17,000 Chuska Population | |
| 20 | 143% | 89% | 422% | 264% |
| 50 | 57% | 36% | 169% | 105% |
| 100 | 29% | 18% | 84% | 53% |
Estimated time and labor efforts for Chaco residents to transport maize to the canyon based on varying population sizes, carrying capacities, and travel times.
Round trip lengths are based on a distance of 85 km between Chaco Canyon and the Chuska Mountains. Six-day trips were suggested by Benson [33] based on traveling 26.67 km/day, while 9.5 and 27 days—assuming a speed of 18 km/day and 6.34 km/day respectively—were derived from travel times determined by Malville [137] and reported by Windes and McKenna ([142] p136). Drennan [132] used loads of 20 and 50 kilograms in his studies of long distance transport, both of which are paired with Benson’s assertion that the trip could be made in six days. The second two weight estimates derive from Malville [131], as reported in Windes and McKenna ([142] p136) and are directly linked to the trip lengths determined in the first column. Number of trips and travel days are rounded based on the completion of an entire trip.
| Round Trip to Chaco (days) | Weight Carried per Person per Trip (kg) | Chaco Canyon Population of 2,000: 304,200 kg of Imported Maize | Chaco Population of 5,000: 895,700 kg of Imported Maize | ||||
|---|---|---|---|---|---|---|---|
| Trips by 100% of Population | Trips by 25% of Population | Trips by 100% of Population | Trips by 25% of Population | ||||
| 6 | 20 | 15,210 | 8 (48 days) | 30 (180 days) | 44,785 | 8 (48 days) | 33 (198 days) |
| 6 | 50 | 6,084 | 3 (18 days) | 12 (72 days) | 17,914 | 3 (18 days) | 13 (78 days) |
| 9.5 | 50 | 6,084 | 3 (29 days) | 12 (114 days) | 17,914 | 3 (29 days) | 13 (124 days) |
| 27 | 100 | 3,042 | 2 (54 days) | 8 (217 days) | 8,957 | 2 (54 days) | 7 (189 days) |
Estimated transport time and labor efforts for transport of maize to the canyon by seasonal residents living 6 months in the Chuskas and 6 months in Chaco Canyon based on varying population sizes, carrying capacities, and travel times.
In this case, the amount of required maize is halved to represent only seasonal occupation within the canyon. Round trip lengths are based on a distance of 85 km between Chaco Canyon and the Chuska Mountains. Six-day trips were suggested by Benson [33] based on traveling 26.67 km/day, while 9.5 and 27 days—assuming a speed of 18 km/day and 6.34 km/day respectively—were derived from travel times determined by Malville [137] and reported by Windes and McKenna ([142] p136). Drennan [132] used loads of 20 and 50 kilograms in his studies of long distance transport, both of which are paired with Benson’s assertion that the trip could be made in six days. The second two weight estimates derive from Malville [131], as reported in Windes and McKenna ([142] p136) and are directly linked to the trip lengths determined in the first column. Number of trips and travel days are rounded based on the completion of an entire trip.
| Round Trip to Chaco (days) | Weight Carried per Person per Trip (kg) | Trips by 100% of Chaco’s Population to Import Maize for 6 Months |
|---|---|---|
| 6 | 20 | 3.5 (21 days) |
| 6 | 50 | 1.5 (9 days) |
| 9.5 | 50 | 1.5 (14 days) |
| 27 | 100 | 0.5 (14 days) |