Rise and fall of late Pleistocene pluvial lakes in response to ......Rise and fall of late...

Rise and fall of late Pleistocene pluvial lakes in response to reduced evaporation and precipitation: Evidence from Lake Surprise, California

Daniel E. Ibarra1,†, Anne E. Egger2, Karrie L. Weaver1, Caroline R. Harris1, and Kate Maher1

1Department of Geological and Environmental Sciences, Stanford University, Stanford, California 94305, USA2Department of Geological Science, Central Washington University, Ellensburg, Washington 98926, USA

ABSTRACT

Widespread late Pleistocene lake sys-tems of the Basin and Range Province in-dicate substantially greater moisture avail-ability during glacial periods relative to modern times, but the climatic factors that drive changes in lake levels are poorly con-strained. To better constrain these climatic factors, we present a new lacustrine paleo-climate record and precipitation estimates for Lake Surprise, a closed basin lake in northeastern California. We combine a de-tailed analysis of lake hydrography and constitutive relationships describing the water balance to determine the infl uence of precipitation, evaporation, temperature, and seasonal insolation on past lake levels. At its maximum extent, during the last de-glaciation, Lake Surprise covered 1366 km2 (36%) of the terminally draining Surprise Valley watershed. Using paired radiocarbon and 230Th-U analyses, we dated shoreline tufa deposits from wave-cut lake terraces in Surprise Valley, California, to determine the hydrography of the most recent lake cycle. This new lake hydrograph places the highest lake level 176 m above the present-day playa at 15.19 ± 0.18 calibrated ka (14C age). This signifi cantly postdates the Last Glacial Maxi-mum (LGM), when Lake Surprise stood at only moderate levels, 65–99 m above modern playa, similar to nearby Lake Lahontan.

To evaluate the climatic factors associated with lake-level changes, we use an oxygen iso-tope mass balance model combined with an analysis of predictions from the Paleoclimate Model Intercomparison Project 3 (PMIP3) climate model ensemble. Our isotope mass balance model predicts minimal precipitation increases of only 2%–18% during the LGM relative to modern, compared to an ~75% increase in precipitation during the 15.19 ka highstand. LGM PMIP3 climate model sim-

ulations corroborate these fi ndings, simulat-ing an average precipitation increase of only 6.5% relative to modern, accompanied by a 28% decrease in total evaporation driven by a 7 °C decrease in mean annual temperature. LGM PMIP3 climate model simulations also suggest a seasonal decoupling of runoff and precipitation, with peak runoff shifting to the late spring–early summer from the late winter–early spring.

Our coupled analyses suggest that moder-ate lake levels during the LGM were a result of reduced evaporation driven by reduced summer insolation and temperatures, not by increased precipitation. Reduced evapora-tion primed Basin and Range lake systems, particularly smaller, isolated basins such as Surprise Valley, to respond rapidly to in-creased precipitation during late-Heinrich Stadial 1 (HS1). Post-LGM highstands were potentially driven by increased rainfall dur-ing HS1 brought by latitudinally extensive and strengthened midlatitude westerly storm tracks, the effects of which are recorded in the region’s lacustrine and glacial records. These results suggest that seasonal insolation and reduced temperatures have been under-investigated as long-term drivers of moisture availability in the western United States.

INTRODUCTION

The late Pleistocene landscape of the west-ern United States was characterized by vast lake systems indicative of a hydrologic balance dramatically different from the present (Fig. 1; Mifflin and Wheat, 1979; Reheis, 1999a). However, uncertainty in the timing of major hydrologic changes has made it diffi cult to connect the observational record to well-dated climatic events. In addition, the precise con-nection between lake levels and climate factors has proven challenging to establish, because the relationships among the physical and hydro-logic controls on measured variables and past climatic states are unresolved. In this study,

using a new lacustrine paleoclimate record from Surprise Valley, California, we reconcile how different factors, namely, the competing infl u-ences of solar insolation and increased precipi-tation, infl uenced Pleistocene lakes in the Basin and Range during the last deglaciation. Surprise Valley was chosen because it is located in an important climatic transition between the more arid Basin and Range Province and the wetter Pacifi c Northwest.

The geographic extent and temporal trends of the latest Pleistocene lake levels suggest that orbital conditions and changes in atmospheric circulation imposed wetter and/or cooler condi-tions on the western United States. In the Basin and Range, the majority of lake highstands from 31°N to 43°N occurred between 15 and 18 ka, during Heinrich Stadial 1 (HS1, ca. 19–14.5 ka), several thousand years after the Last Glacial Maximum (LGM, ca. 26–19 ka; Benson et al., 1990; Adams and Wesnousky, 1998; García and Stokes, 2006; Munroe and Laabs, 2012; Lyle et al., 2012). Prior to HS1, these lakes appear to have stood at moderate water levels during much of the early marine oxygen isotope stage 2 (MIS 2, ca. 29–11 ka; e.g., Benson et al., 1995; Wells et al., 2003; Bacon et al., 2006), and low to moderate levels through MIS 3 (ca. 57–29 ka; e.g., Tackman, 1993; Phillips et al., 1994; Reheis et al., 2012). The atmospheric mecha-nism driving these high lake levels is hypoth-esized to be midlatitude “dipping westerlies” (Negrini, 2002), which reached as far south as Lake Elsinore, California (~34°N; Kirby et al., 2013) and Cave of the Bells, Arizona (~32°N; Wagner et al., 2010). Despite evidence from late Pleistocene lake records and other paleoclimate archives, the temporal correspondence between (Munroe and Laabs, 2012) or robust latitudinal trends in (Lyle et al., 2012) lake highstands and stillstands during HS1 remain enigmatic. Fur-thermore, the mechanisms (e.g., reduced tem-peratures and lake surface evaporation, and/or increased rainfall) that produced moderate lake levels during the LGM, before the deglacial highstands, are not well understood. Knowledge

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GSA Bulletin; Month/Month 2014; v. 1xx; no. X/X; p. 1–29; doi: 10.1130/B31014.1; 10 fi gures; 8 tables; Data Repository item 2014221.

†E-mail: [email protected].

as doi:10.1130/B31014.1Geological Society of America Bulletin, published online on 2 June 2014

Ibarra et al.

2 Geological Society of America Bulletin, Month/Month 2014

of the spatial distribution of hydrologic shifts, recorded by paleoclimate archives, is required to resolve the underlying climatic drivers of pro-found hydrologic change in the late Pleistocene.

Most studies infer that Pleistocene lake levels record precipitation amounts driven by changes in midlatitude atmospheric circulation. Large ranges of estimates for the extent of increased precipitation (80%–260% of modern ), reduced evaporation (12%–90% of modern), and decreased temperature (3–15 °C lower than modern) during the LGM have been calcu-lated using proxy data with modern analogs, atmosphere-ocean global climate models (AOGCMs), and hydrologic, thermal evapora-tion, and mass balance models (cf. Matsubara and Howard, 2009, their table 1). These broad ranges are problematic for AOGCMs, which require spatially resolved changes in the hydrologic cycle for data-model intercomparison (e.g., Braconnot et al., 2012; DiNezio and Tierney, 2013; Hargreaves et al., 2013). Stable isotope analysis of shoreline deposits can further con-strain well-dated lake hydrographs by provid-

ing insight into watershed-scale moisture avail-ability driven by the climate system (Hostetler and Benson, 1994; Jones et al., 2007; Placzek et al., 2011).

While most research has focused on the large and complex lake systems of Lake Lahontan and Lake Bonneville (Fig. 1; Benson et al., 1990; Oviatt et al., 1992; Adams and Wes-nousky, 1998; Godsey et al., 2011; McGee et al., 2012), small lakes—which record hydrologic conditions of smaller watersheds—are more responsive to climate fl uctuations and thus pro-vide higher-resolution paleoclimatic data (Gar-cía and Stokes, 2006; Munroe and Laabs, 2013; Steinman et al., 2013). Thus, lakes with small watersheds, simple hypsometry, and short resi-dence times should record perturbations in the hydrologic cycle more rapidly and with shorter lag times (Hendriks et al., 2012).

One such small Pleistocene lake occupied Surprise Valley in northeastern California (Fig. 1). Surprise Valley is an ideal location for testing paleoclimate models because it lies in the transition between two major climatic zones:

the Pacifi c Northwest and the Basin and Range. Climate models of the LGM predict a more arid Pacifi c Northwest and a relatively wet central Nevada (Kim et al., 2008; Laîné et al., 2009; Braconnot et al., 2012). Paleoclimate records from the north and west suggest reduced pre-cipitation and a mean annual temperature ~7 °C lower during the LGM (Worona and Whitlock, 1995; Bradbury et al., 2004). To the southeast, Lake Lahontan stood at moderate levels during the LGM (Benson et al., 1995), prior to a brief deglacial highstand at ca. 15.8 ka (Adams and Wesnousky, 1998). A detailed analysis of the transition zone between these regions can help resolve the forcing mechanisms that could pro-duce such disparate conditions.

We use a “shore-based” approach (e.g., Red-wine, 2003; García and Stokes, 2006; Kurth et al., 2011; Munroe and Laabs, 2013) to quan-tify late Pleistocene lake levels in Surprise Val-ley, recorded in prominent wave-cut shorelines along the steep valley walls (Egger and Miller, 2011; Irwin and Zimbelman, 2012). While lake sediment core studies can provide higher-resolution climate archives (e.g., Benson et al., 1990; Bischoff et al., 1997a, 1997b; Licciardi, 2001; Rosenbaum et al., 2012), records of shoreline ages document the history of lake surface area, a measure of the balance of pre-cipitation and evaporation for a given basin (Miffl in and Wheat, 1979; Benson and Paillet, 1989; Currey, 1990; Reheis, 1999b; Munroe and Laabs, 2013). We incorporated stable iso-tope analysis into a simplifi ed hydrologic mass balance model based on lake surface area, which allows us to quantify the changes in precipitation and evaporation during lake-level fl uctuations, and provides direct comparison to climate model outputs. To obtain age-elevation constraints on lake level, we dated carbon-ate (tufa) deposits on wave-cut bedrock using 230Th-U and radiocarbon (14C) geochronology. We used these new data to test climate model predictions for the LGM in a region where models diverge in their prediction of past rain-fall magnitude and net change.

Our new lake record and isotope mass balance calculations provide evidence that addresses three key questions regarding the latest Pleisto-cene lakes in the Basin and Range: (1) Can mod-erate LGM lake levels be explained by lower evaporation rates due to decreasing summer solar insolation? (2) Is increased precipitation, driven by changes in atmospheric circulation, required to explain post-LGM highstands dur-ing late HS1? (3) Is there a temporal correspon-dence or robust latitudinal trend in lake high-stands and stillstands during HS1 that records changes in the position, strength, and/or charac-ter of midlatitude atmospheric circulation?

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Figure 1. Location map of late Pleistocene lakes (light blue), modern lakes (dark blue), and the extent of major Last Glacial Maximum (LGM) mountainous glaciation (gray) in the western United States (simplifi ed from Miffl in and Wheat, 1979; Reheis, 1999a; Ehlers et al., 2011). The black box delineates the extent of Figure 2A. Locations of additional paleo-climate archives compiled in Figure 10 and discussed within the text include glacier records (red triangles) and pollen records (red circle). Labeled lakes and pollen records are Alvord Basin (AL), Carpenter Lake (CR), Chewaucan Basin (CB), Columbus Lake (CO), Diamond Valley (DV), Fort Rock (FR), Jakes Lake (JL), Lake Bonneville (LB), Lake Clover (CL), Lake Franklin (LF), Lake Lahontan (LL), Lake Russell (LR), Lake Surprise (SV), Little Lake (LI), Mahleur Lake (MH), Newark Valley (NV), Railroad Lake (RR), Spring Lake (SL), Upper Klamath Lake (UKL), Waring Lake (WL), and Lake Warner (WR).


Lacustrine paleoclimate record from late Pleistocene Lake Surprise, California

Geological Society of America Bulletin, Month/Month 2014 3

BACKGROUND

Geologic Setting and Previous Work

Surprise Valley, located in northeastern Cali-fornia along the western margin of the Basin and Range Province (Fig. 1), is situated within a modern climatic transition from semiarid coniferous forest in the west to arid sagebrush- and grassland-dominated high-altitude desert in the east. The N-S–trending valley formed as a result of extension since the mid-Miocene, and it is bounded by normal faults along the range fronts of the Warner Range to west and the smaller Hays Canyon Range to the east (Egger and Miller, 2011; Egger et al., 2014). Playas in the upper, middle, and lower sub-basins occupy the valley fl oor (Fig. 2A). To the south lies Duck Flat, a higher-elevation small subbasin hydrologically connected to the Sur-prise Valley watershed.

Nearby Lake Lahontan and the Chewaucan Basin (Fig. 1) have been the subject of detailed study, but few studies have focused on Pleisto-cene Lake Surprise, despite the recognition of laterally continuous paleoshorelines throughout the valley and into Duck Flat (I.C. Russell, 1884; C.J. Russell, 1927; Hubbs and Miller, 1948). Erosional shoreline sequences in Surprise Valley are similar to those found in the Lahon-tan and Bonne ville basins (e.g., Adams and Wesnousky, 1998; Schofi eld et al., 2004; Felton et al., 2006; Jewell, 2007). On the east side of Surprise Valley, wave-cut shoreline features are eroded into bedrock that consists of mid- to late Cenozoic rhyolite, basalt, and tuff (Carmichael et al., 2006; Egger and Miller, 2011). Laminated shoreline tufa on exposed bedrock is abundant on several shorelines at elevations of 1420–1450 m (all elevations given as meters above sea level [asl]), but it is less common at higher and lower elevations (Fig. 2). Personius et al. (2009) noted that the latest Pleistocene high-stand appears to be found throughout the valley at ~1540 m. Additionally, two late Pleistocene highstand elevations have been proposed: Miffl in and Wheat (1979) and Reheis (1999a) both reported highstand elevations of 1567 m, whereas Irwin and Zimbelman (2012) reported a highstand elevation of 1545 m.

Analysis of modern topography by Irwin and Zimbelman (2012) suggests that the basin pour point is 1621 m, i.e., signifi cantly higher than any of the reported highstand elevations, indi-cating that Lake Surprise was a terminal lake. In support of that, Clawson et al. (1986) found that groundwater fl ows toward the center of the basin. C.J. Russell (1927) noted geomorphic evidence that suggests canyon-carving over-fl ow from Surprise Valley into the Lahontan

Basin through Buffalo Meadows during much older and higher highstands similar to other Great Basin lake systems (including Lahon-tan), likely recording progressive drying from the early middle to late Pleistocene (Reheis, 1999a, 1999b; Reheis et al., 2002; Kurth et al., 2011). However, fi eld and modeling studies investigating pluvial lake surface areas, hydrog-raphy, and watershed runoff have assumed that the younger late Pleistocene Lake Surprise was inward draining, not connected to the Lahon-tan system to the south or to Warner Valley to the northeast (Fig. 1; I.C. Russell, 1884; Hubbs and Miller, 1948; Miffl in and Wheat, 1979; Benson and Paillet, 1989; Benson et al., 1995; Adams and Wesnousky, 1998; Sack, 2002; Matsu bara and Howard, 2009).

Late Pleistocene hydrographs have been produced for Great Basin lake systems includ-ing Lahontan (e.g., Benson et al., 1995; Adams et al., 2008), Franklin (Lillquist, 1994; Munroe and Laabs, 2011, 2013), Searles (Smith, 1984), Bonneville (e.g., Oviatt et al. 1992), Russell (e.g., Zimmerman et al., 2011), and Chewaucan (Licciardi, 2001) (Fig. 1). To date, no similar hydrographs exist for Lake Surprise, although Personius et al. (2009) summarized constraints on Pleistocene hydrography based on the distri-bution of lacustrine sediments deposited along the western margin of the basin (Fig. 2A).

Existing time-depth constraints for the latest Pleistocene lake cycle at Lake Surprise are con-strained by the Trego Hot Spring tephra, with an assigned radiocarbon age of 23.2 ± 0.3 calibrated ka from nearby Pyramid Lake (Benson et al., 1997), and Holocene archaeological remains (details in Table DR11). The Trego Hot Spring tephra is exposed in two locations in the val-ley at ~1378 m (Fig. 2A; Personius et al., 2009; Hedel, 1980, 1984). Hedel (1980) noted that the tephra at both localities is deposited in fi ne sand and silt, likely associated with moderate to deep lake levels. Additionally, shallow-water deltaic deposits at 1475 and 1493 m postdate the Trego Hot Spring deposit and likely represent deposi-tion between ca. 24 and 18 ka (Personius et al., 2009). Personius et al. (2009) also reported subaerial sediment deposition at 1475 m from 13 to 1 ka (Fig. 2A). Archaeological evidence from three sites along the edges of the Holocene playas (with a minimum elevation of 1355 m; Fig. 2A) indicates that, since the middle Holo-cene, the Modoc and Northern Paiute occu-pied Surprise Valley as a seasonal winter home (James, 1983; O’Connell and Inoway , 1994). At

one site, a radiocarbon age from a bone on the second deepest excavated house fl oor was dated at 5640 ± 155 yr B.P. (radiocarbon age), the old-est age obtained from all three sites (O’Connell and Inoway, 1994).

Geochronology of Lake Shorelines

Lake hydrograph assembly provides a fi rst-order constraint on the climatic changes required to sustain terminally draining Lake Surprise during the late Pleistocene. We targeted wave-cut lake terraces occurring in Surprise Valley using 230Th-U and radiocarbon geochronol-ogy of tufas to provide absolute ages of sur-faces. Given recent advances in the precision of 230Th-U dating by multicollector–inductively coupled plasma–mass spectrometry (MC-ICP-MS; Hernández-Mendiola et al., 2011; Shen et al., 2012; Cheng et al., 2013), and the establish-ment of robust radiocarbon calibration curves (Reimer et al., 2013), these two methods pro-vide complementary constraints on the age of Pleistocene lacustrine carbonate.

230Th-U Dating of Impure Lacustrine Carbonates

The 230Th-U dating method has been success-fully applied to a range of terrestrial carbonate materials, most notably to speleothems (e.g., Vacco et al., 2005; Oster et al., 2009; Wagner et al., 2010; Asmerom et al., 2010; Polyak et al., 2012), pedogenic calcite/opal (e.g., Lud-wig and Paces, 2002; Sharp et al., 2003; Maher et al., 2007, 2014; Fletcher et al., 2010), trav-ertine (e.g., Luo and Ku, 1991; Soligo et al., 2002), and a variety of lacustrine carbonates (e.g., Israelson et al., 1997; Haase-Schramm et al., 2004; Placzek et al., 2006a, 2006b; Blard et al., 2011; McGee et al., 2012; Torfstein et al., 2013). Lacustrine carbonate associated with tufa mounds and shoreline tufa deposits is common in late Pleistocene lake systems in the western United States (e.g., Benson et al., 1995; Ku et al., 1998; Felton et al., 2006; Godsey et al., 2011; Zimmerman et al., 2011) and elsewhere (e.g., Moeyersons et al., 2006; Placzek et al., 2006a, 2006b, 2011; Blard et al., 2011), making it useful for paleo–lake-level reconstructions.

The 230Th-U dating method relies on the fi rst three long-lived daughter products in the 238U decay series. Uranium-238 (t1/2 = 4.46 b.y.; Jaffey et al., 1971) decays via the follow-ing sequence: 238U → 234Th → 234Pa → 234U → 230Th. The 234Th (t1/2 = 24.1 d) and 234Pa (t1/2 = 1.18 min) daughter isotopes are very short-lived compared to 238U, 234U, and 230Th. Samples can thus be dated using the activity ratios (denoted by parentheses) of the two long-lived daughter isotopes (234U/238U) and (230Th/238U). Due to the

1GSA Data Repository item 2014221, analytical methods, discussion of the runoff coeffi cient assump-tions, supporting fi gures, and tables, is available at http://www.geosociety.org/pubs/ft2014.htm or by re-quest to [email protected].


Ibarra et al.


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Figure 2. Location maps for samples collected as part of this study. Sample locations (latitude, longitude, and elevation) are listed in Table 1. (A) Detailed map of the Surprise Valley region including the calculated Lake Surprise watershed (black line) and outlines of Lake Sur-prise’s extent (green, red, and dark blue lines) at key periods, with water sample (blue circles), playa sample (red squares), and weather sta-tion (black stars) locations. Lake Surprise outlines were generated by contouring the merged digital elevation model (DEM) from the U.S. Geological Survey (USGS) National Elevation Data set using ArcGIS 10.1. For the Last Glacial Maximum (LGM) lake level (1420–1440 m), only 1440 m is shown on this panel. Only streams within the basin’s watershed are included, demonstrating that Lake Surprise was an inward-draining, closed basin lake system. Also shown are the locations of additional lake-level constraints from archaeological sites (yellow stars) (James, 1983; O’Connell and Inoway, 1994), Trego Hot Spring tephra localities (green diamonds; Hedel, 1980), and a paleoseismic trench with lacustrine sediments (gray square; Personius et al., 2009). Black boxes B, C, D, and E delineate the areas of additional panels. (B–E) Locations where carbonate samples were collected on exposed shoreline ridges (green circles). Group 1 tufa samples were collected from the prominent lower-elevation shorelines at 1419–1478 m (white circles); group 2 samples were collected from the less-prominent middle-elevation shorelines of 1509–1531 m (black circles); and group 3 samples were collected from higher-elevation shorelines >1542 m (black diamonds). Each sample locality includes the USGS 7.5′ quadrangles (1:24,000 scale), overlain with shaded relief and Quaternary units adapted from Egger and Miller (2011) and Egger et al. (2014). HS—highstand.




TABLE 1. LOCATION OF SAMPLES

Sample name Material type Sample group no.

Latitude (°N)

Longitude (°W)

Altitude* (m)

Type of analysis

Accommodation zone shoreline (Fig. 2B)SVDI11-T2 Thick laminated tufa with porous

outer rind1 41.593662 120.070257 1453.5 U-Th (5 point isochrons [inner rind] + 5 subsamples [outer rind]), 14C,

Sr/Ca (2 subsamples) and δ18O-δ13C (2 subsamples)SVDI11-T3 Thick laminated tufa 1 41.593293 120.070956 1437.7 U-Th (7 point isochron), 14C, Sr/Ca (2 subsamples) and δ18O-δ13C

(2 subsamples)SVDI11-T4 Thin laminated tufa 1 41.592938 120.070912 1430.6 U-Th (7 point isochron), 14C, Sr/Ca (2 subsamples) and δ18O-δ13C

(2 subsamples)SVDI11-T14 Thick laminated tufa 2 41.591140 120.052266 1478.4 U-Th (7 point isochron), 14C, Sr/Ca (2 subsamples) and δ18O-δ13C

(2 subsamples)SVDI11-T18 Densely laminated tufa 3 41.596241 120.049039 1555.7 U-Th (7 subsamples), 14C, Sr/Ca (2 subsamples) and δ18O-δ13C

Middle lake shoreline set (Fig. 2D)SVDI12-T1 Thick laminated tufa on

porous basalt1 41.429916 119.975595 1419.5 U-Th (7 point isochron) and 14C, Sr/Ca, and δ18O-δ13C

5.1dnanorhcositniop7(hT-U5.9141595579.911619924.141afutdetanimaL2T-21IDVS N HNO3 leach residue), 14C, Sr/Ca (3 replicates) and δ18O-δ13C (3 replicates)

SVDI12-T3 Thin laminated tufa 1 41.429852 119.975167 1427.8 U-Th (2 subsamples), Sr/Ca (2 replicates), and δ18O-δ13C (2 replicates)

SVDI12-T4 Thin laminated tufa 1 41.429829 119.974638 1439.0 U-Th (2 subsamples), Sr/Ca (2 replicates), and δ18O-δ13C (2 replicates)

SVDI12-T5 Poorly consolidated tufa on porous basalt

1 41.429869 119.974454 1444.3 U-Th (7 point isochron and 1.5 N HNO3 leach residue), 14C, Sr/Ca (2 replicates), and δ18O-δ13C (2 replicates)

SVDI12-T7 Thin laminated tufa 1 41.428042 119.972521 1472.5 U-Th (1 sample), Sr/Ca and δ18O-δ13CSVDI12-T9 Thin laminated tufa 2 41.426983 119.970856 1508.9 U-Th (7 point isochron), 14C, Sr/Ca, and δ18O-δ13CSVDI12-T10 Densely laminated tufa 2 41.426865 119.970569 1516.8 U-Th (7 point isochron and 1.5 N HNO3 leach residue), 14C, Sr/Ca

(2 replicates), and δ18O-δ13C (2 replicates)SVDI12-T11 Poorly consolidated tufa 3 41.426084 119.969309 1554.9 U-Th (1 sample), Sr/Ca, and δ18O-δ13CSVDI12-T12 Thin laminated tufa 3 41.428400 119.967793 1576.9 U-Th (7 subsamples), 14C, Sr/Ca, and δ18O-δ13C

Lower lake shoreline set (Fig. 2E)

SVDI12-T13 Thick laminated tufa 1 41.217488 119.970070 1437.2 U-Th (7 point isochron), 14C, Sr/Ca, and δ18O-δ13CSVDI12-T14 Thin laminated tufa 2 41.219085 119.965077 1530.7 U-Th (7 point isochron), 14C, Sr/Ca, and δ18O-δ13C

Upper lake shoreline set (Fig. 2C)

SVDI12-T15 Porous densely consolidated tufa 1 41.717964 120.070054 1433.1 U-Th (7 point isochron and 1.5 N HNO3 leach residue), 14C, Sr/Ca (2 replicates), and δ18O-δ13C (2 replicates)

SVDI12-T17 Thin laminated tufa 3 41.717185 120.062345 1542.3 U-Th (1 sample), Sr/Ca, and δ18O-δ13CSVDI12-T18 Poorly consolidated tufa 3 41.713935 120.062480 1564.2 U-Th (2 subsamples), 14C, Sr/Ca, and δ18O-δ13CSVDI12T19 Poorly consolidated tufa on

porous basalt3 41.711839 120.062596 1566.8 U-Th (1 sample), Sr/Ca, and δ18O-δ13C

Modern playa samples (Fig. 2A)SVDI12-C1 Playa carbonate

(middle playa edge)- 41.532766 120.128760 - (234U/238U), (230Th/232Th), Sr/Ca, and δ18O-δ13C (2 replicates)

SVDI12-P1 Playa surface sediment (middle playa edge)

- 41.425504 119.987361 - 1:1 DI water extraction and NaOAc leach: (234U/238U)

SVDI12-P2 Playa surface sediment (middle playa center)


SVDI12-P3 Playa surface sediment (upper playa)


SVDI12-P4 Playa surface sediment (Duck Flats)


Modern water samples (Fig. 2A)SVDI12-WS1 Stream (Eagle Creek) - 41.427318 119.971265 - U concentration, (234U/238U), and Sr/CaSVDI12-WS2 Stream (Emerson Creek) - 41.426983 119.970856 - U concentration, (234U/238U), and Sr/CaSVDI12-WS3 Stream (Granger Creek) - 41.472795 120.188345 - U concentration, (234U/238U), and Sr/CaSVDI12-WS4 Stream (Deep Creek) - 41.510626 120.215339 - U concentration, (234U/238U), and Sr/CaSVDI12-WS5 Hot Spring (Boyd Spring) - 41.725518 120.082829 - U concentration, (234U/238U), and Sr/CaSVDI12-WS6 Hot Spring (Seyferth Hot Springs) - 41.613584 120.106561 - U concentration and Sr/CaSVDI12-WS7 Hot Spring (Leonard Hot Springs) - 41.598952 120.091965 - U concentration and Sr/CaSVDI12-WS8 Hot Spring (Surprise Valley

Hot Springs)- 41.534183 120.079076 - U concentration and Sr/Ca

SVDI12-WS9 Groundwater (Lake City Well) - 41.634140 120.215041 - U concentration, (234U/238U), and Sr/CaSVDI12-WS10 Stream (Mill Creek) - 41.642732 120.216200 - U concentration, (234U/238U), and Sr/CaSVDI12-WS12 Stream (Fort Bidwell Creek) - 41.848853 120.152633 - U concentration, (234U/238U), and Sr/CaSVDI12-WS13 Pond/Lake (Annie Lake) - 41.908525 120.108812 - U concentration, (234U/238U), and Sr/CaSVDI12-WS15 Groundwater (Cockeral Ranch

Well #1)- 41.657510 120.219208 - U concentration, (234U/238U), and Sr/Ca

SVDI12-WS16 Groundwater (Cockeral Ranch Well #2)

- 41.649840 120.214560 - U concentration, (234U/238U), and Sr/Ca

SVDI12-WS17 Hot Spring (Lake City Hot Springs) - 41.666514 120.212447 - U concentration and Sr/CaSVDI12-WS18 Hot Spring (Unnamed Hot Spring) - 41.218816 120.065092 - U concentration, (234U/238U), and Sr/CaSVDI12-WS19 Stream (Lost Creek) - 41.084588 119.892403 - U concentration, (234U/238U), and Sr/CaSVDI12-WS20 Groundwater (Eagleville Well) - 41.322792 120.117908 - U concentration, (234U/238U), and Sr/CaSVDI12-WS21 Groundwater (Cedarville Well) - 41.530723 120.184478 - U concentration, (234U/238U), and Sr/Ca

Note: DI—deionized water. Ac—acetate. *Tufa sample altitude determined by pinning latitude-longitude location to a 0.5-m-horizontal-resolution raster light detection and ranging (LiDAR) data set, reported as

meters above sea level. Typical elevation error is ±0.1m (2σ).


Ibarra et al.


relatively short half-lives of 230Th (t1/2 = 75.4 k.y.) and 234U (t1/2 = 245 k.y.), 230Th-U geochro-nology has an upper age limit of ca. 500–800 ka (Cheng et al., 2013). The equations for calculat-ing the ingrowth of 230Th and the closed-system decay of 234U are (Kaufman and Broecker, 1965; Thurber et al., 1965; Neymark, 2011):

234

238

234

238

0

1 234 234U

Ue

U

Ue

t

t t⎛⎝⎜

⎞⎠⎟

= − +⎛⎝⎜

⎞⎠⎟

− −( )λ λ , (1)

t te e+ ,+ −−

⎛⎝⎜

⎞⎠⎟

− −λ λλ λλ λ

230 234

1 234 230

230 234

230

238230

230 234

234

238

0

234Th

U

U

Ue

t

⎛⎝⎜

⎞⎠⎟

=−

⎛⎝⎜

⎞⎠⎟

⎛⎝⎜

⎞⎠⎟

−λλ λ

λ( tt te− −λ230 )

(2)

where λ230 and λ234 are decay constants for 230Th and 234U, respectively, t is the time in years since the mineral formed, and (234U/238U)t and (230Th/238U)t are the measured or corrected activity ratios. These equations are solved for (234U/238U)0 and time (t). In closed-system rocks and minerals older than ~106 yr, the (234U/238U) and (230Th/238U) are equal to one, a condition referred to as “secular equilibrium.” The (234U/238U) of natural water is typically elevated (>1) due to the preferential release of the daughter 234Th nuclide across grain boundar-ies during the α-decay of 238U, a process known as α-recoil (Kigoshi, 1971; Fleischer, 1982; Oster et al., 2012). Under oxidizing conditions typical of surface waters, U is mobile as the hexavalent uranyl ion [UVIO2]2+ and is incorpo-rated into secondary minerals such as carbon-ates (Reeder et al., 2001). In contrast, Th is relatively insoluble under oxic conditions, and ideal samples for 230Th-U dating have low initial Th concentrations [e.g., (230Th/238U) = 0], such that all postdepositional 230Th accumulation is derived from radioactive decay of 234U in the sample. However, by measuring the abundance of 232Th (t1/2 ~14 b.y.), corrections can be made for any “detrital Th” (i.e., Th derived from other processes aside from purely radioactive decay) that may have been originally incorporated into the carbonate (Luo and Ku, 1991; Ludwig and Titter ington, 1994; Ku, 2000; Neymark and Paces, 2000; Sharp et al., 2003; Paces et al., 2004; Fletcher et al., 2010).

In fact, the assumption of no initial 230Th is rarely valid for lake carbonates (Placzek et al., 2006a, 2006b; Blard et al., 2011; Torfstein et al., 2013). In Mono Basin (Fig. 1, Lake Rus-sell), unsupported dissolved Th, which may co precipi tate with lacustrine carbonates, can be the result of high Th activity and complexation with CO3

2– (Anderson et al., 1982; Lin et al., 1996; Zimmerman et al., 2012). This inhibits

removal and scavenging of hydrogenous Th by absorption to particles (Anderson et al., 1982), as observed in ocean sediments (Bacon and Anderson, 1982). In most cases, without correc-tion for initial 230Th, the measured (230Th/238U) is too high, resulting in an age calculation that is erroneously old. Lake carbonates are likely to have two end-member sources of Th: (1) hydrogenous Th in the primary carbonate derived from water-soluble Th, and (2) detrital Th incorporated within the carbonate as silici-clastic or organic particles (e.g., Lin et al., 1996; Blard et al., 2011; Torfstein et al., 2013). In freshwater systems, low hydrogenous Th con-centrations are expected; however, some studies of paleolake systems have observed substantial contribution from both Th end members (e.g., Lin et al., 1996; Haase-Schramm et al., 2004). Assuming that freshwater lake carbonates include only the detrital end member, we will apply and assess two complementary strate-gies, single-sample correction and an isochron approach, to calculate the 230Th-U ages for coeval sets (n ≥ 5) of whole-rock dissolutions.

Radiocarbon Dating of Lacustrine Carbonates

Radiocarbon geochronology has been exten-sively applied to inorganic and organic carbon-ates found as surfi cial deposits (e.g., tufa) and in nearshore sediments to date Pleistocene shore-lines (e.g., Oviatt et al., 1992; Lin et al., 1996; García and Stokes, 2006; Munroe and Laabs, 2013). Assuming a carbonate sample contains carbon originally fi xed from the atmosphere, radiocarbon geochronology relies upon the decay of 14C (t1/2 = 5.73 k.y.) to 14N to calculate a radiocarbon (14C) age. Because the production and reservoir of 14C in the atmosphere have not been constant with time, calibration data sets are required to correct the radiocarbon age of samples (Reimer et al., 2013). Beyond the Holo-cene, uncertainty in radiocarbon ages can be the result of plateaus occurring in the radiocarbon calibration curve during the last deglaciation and the short half-life of 14C (Trumbore, 2000; Southon et al., 2012). In lacustrine carbonates, two complications may occur. A reservoir effect due to the incorporation of signifi cant quanti-ties of “dead” carbon (i.e., low 14C/12C carbon from weathering of carbonate bedrock) results in a radiocarbon date that is up to thousands of years older than the true age. Alternatively, in poorly consolidated, porous, or impure carbon-ates, modern or younger atmospheric carbon can contaminate the sample (Cassata et al., 2010; Zimmerman et al., 2011, 2012). In an ideal situation, application of several absolute dating methods, such as 230Th-U or 40Ar/39Ar, applied to coeval or depositionally equivalent

material, can constrain the reservoir effect or identify anomalously young ages (e.g., Cassata et al., 2010; Zimmerman et al., 2011; Vazquez and Lidzbarski, 2012).

METHODS

Topographic Analyses

Calculation of Lake Surprise Basin GeometryBuilding on recent work by Irwin and

Zimbel man (2012), we used modern Surprise Valley topography to calculate lake volume and surface area at elevations spanning the modern playa to 10 m above the proposed highstand of Reheis (1999a). We analyzed digital eleva-tion models (DEMs) from the U.S. Geological Survey (USGS) National Elevation Data set (NED) with ArcGIS 10.1 hydrology and 3-D spatial analyst tools. Lake surface area and vol-ume were calculated from the minimum playa elevation to above the maximum lake terrace elevation (1355–1577 m). To calculate vol-ume, a triangulated irregular network (TIN) topographic surface representation was created from the DEM and intercepted with lake surface area. Lake volume calculations do not account for postlake sediment infi ll and thus represent minimum lake volumes. Empirical relation-ships, fi t using polynomial functions, were established to relate volume and surface area to elevation (Fig. DR1 [see footnote 1]). The inward-draining watershed area was calculated after smoothing the DEM with a 1 m vertical threshold. We assumed that modern contours and the basin topography accurately represent the watershed topography and lake hypsometry of the late Pleistocene, with minimal isostatic rebound. The results of the Lake Surprise basin geometry analysis were also compared to work by previous authors (Miffl in and Wheat, 1979; Reheis, 1999a; Zimbelman et al., 2009; Irwin and Zimbelman, 2012).

Based on analyses of the high-resolution topographic data set, we updated topographic results from Irwin and Zimbelman (2012) in Table 2. The pour point elevation (1621 m) is >50 m higher than all proposed highstand ele-vations (Hubbs and Miller, 1948; Miffl in and Wheat, 1979; Reheis, 1999a; Personius et al., 2009; Zimbelman et al., 2009; Irwin and Zim-belman, 2012) and the pre–MIS 2 and MIS 2 highstands studied here. Furthermore, all mod-ern streams drain terminally into the playa lakes (Fig. 2A). Groundwater contribution to Lake Surprise is assumed to be negligible because the Pliocene–Pleistocene lacustrine sediments provide the primary groundwater storage capac-ity for modern-day Surprise Valley and are recharged by nearshore lacustrine deposits and




Holocene alluvial fans (Clawson et al., 1986). The groundwater aquifer capacity is estimated to be 4.93 km3 (4 million acre-feet) to 122 m below the valley fl oor (Clawson et al., 1986), which is only 2.9% of the lake volume at its lat-est Pleistocene highstand of 1531 m (lake vol-ume = 164 km3; Table 2).

Field Methods

Modern water and playa samples were col-lected in July 2012 to assess the geochemis-try of waters in the Surprise Valley watershed to better constrain the expected variability in elemental and uranium isotopic composition of the late Pleistocene tufa samples. Modern water samples were collected from seven streams, fi ve groundwater wells, six hot springs, and one small pond within the Surprise Valley watershed (Table 1; Fig. 2A). Water samples were fi ltered in the fi eld through 0.45 µm polyethylene fi lters into 1 L polyethylene bottles and acidifi ed with high-purity nitric acid (HNO3) to ~2% HNO3. Ten milliliters were aliquoted for concentration analyses (U, Th, Ca, and Sr), and 250–500 ml were dried down over ~2 wk in 50 mL Tefl on beakers for U isotope analysis. Four modern sur-face sediment samples were collected from the playas (Table 1; Fig. 2A). One modern evaporite sample was collected from the middle playa.

Tufa Sample CollectionTufa samples were collected in August 2011

and July 2012 from exposed bedrock on the front edge or the crest of wave-cut terraces and horizontal shoreline benches, prominent on the east side of the valley due to the prevailing west-erly winds. Four sample localities were targeted adjacent to each of the three modern playa lakes (Figs. 2B–2E). While the absolute depth of tufa formation relative to lake level is not certain or directly quantifi able, their association with wave-cut shoreline features and biologic tex-tures (cf. Rouchy et al., 1996) indicates their formation within the photic zone and likely near the lake surface and edge. Thus, the tufa sample elevations give minimum lake surface elevations at their time of deposition (e.g., Felton et al., 2006; Benson et al., 1996, 2011; Zimmerman et al., 2012).

Latitude and longitude of sample locations were recorded with a handheld global position-ing system (GPS; Garmin Oregon 550t). Using a newly acquired light detection and ranging (LiDAR) data set, sample elevations were deter-mined by pinning the location coordinates to the 0.5-m-horizontal-resolution raster digital eleva-tion model derived from the LiDAR point cloud. The elevation error associated with the elevation of the tufa samples, primarily collected from

TAB

LE 2

. LA

KE

GE

OM

ET

RY,

WA

TE

RS

HE

D A

RE

A, A

ND

HY

DR

OLO

GIC

IND

ICE

S F

OR

LA

KE

SU

RP

RIS

E

Stu

dyIn

terp

rete

d ag

eLa

ke e

leva

tion

(m a

.s.l.

)La

ke a

rea,

A

L (k

m2 )

Wat

ersh

ed

area

, AB

(km

2 )

Wat

ersh

ed a

rea/

lake

are

aLa

ke v

olum

e (k

m3 )

Pou

r po

int

elev

atio

n(m

a.s

.l.)

Hyd

rolo

gic

inde

x (H

I)*

Tufa

δ18

O(‰

, VP

DB

)Δ

tem

pera

ture

(°

C)

Est

imat

ed

prec

ipita

tion

(mm

/yr)

Δpr

ecip

itatio

n#

(%)

Thi

s st

udy

Mod

ern

met

eoro

logy

HI m

et =

0.1

1†

Thi

s st

udy

Mod

ern

play

a la

kes

1355

to 1

372

0 to

423

3812

>9.

010

to 2

.116

210

to 0

.12

Thi

s st

udy

MIS

2 (

post

-LG

M)

1531

1366

3812

2.79

164

1621

0.56

–3.8

45 –

5§99

1.0*

*~

75**

Thi

s st

udy

MIS

2 (

LGM

)14

20 to

144

085

1 to

977

3812

4.48

to 3

.90

39 to

57

1621

0.29

to 0

.34

–3.3

88 –

7§61

9.7*

*10

(2

to 1

8)**

Thi

s st

udy

MIS

4 o

r M

IS 6

1567

1499

3812

2.54

218

1621

0.65

Irw

in a

nd

Zim

belm

an

(201

2)

95.01261

86.27383

0 3415451

Zim

belm

an e

t al.

(200

9)15

34

35.009 .2

00 830 131

) 800 2(e

mrO

75.05 7. 2

040417 41

7651enecotsiel

Peta L

)a9991(siehe

R Miffl

in a

nd

Whe

at (

1979

)La

hont

an15

6714

7140

402.

75

0.

68

–2.

34††

552.

5††77

.1††

Not

e: M

IS—

mar

ine

oxyg

en is

otop

e st

age;

LG

M—

Last

Gla

cial

Max

imum

; VP

DB

—V

ienn

a P

eeD

ee B

elem

nite

.*H

I is

(top

ogra

phy

deriv

ed)

hydr

olog

ic in

dex

= la

ke s

urfa

ce a

rea/

trib

utar

y ar

ea (

basi

n ar

ea m

inus

lake

are

a) (

Miffl

in a

nd W

heat

, 197

9; R

ehei

s, 1

999a

).† H

I met is

(m

eteo

rolo

gy d

eriv

ed)

hydr

olog

ic in

dex

= r

unof

f fro

m tr

ibut

ary

basi

n/(la

ke e

vapo

ratio

n m

inus

lake

pre

cipi

tatio

n) (

Miffl

in a

nd W

heat

, 197

9; R

ehei

s, 1

999a

); v

alue

s ar

e fr

om a

nnua

l ave

rage

of t

hree

m

oder

n m

eteo

rolo

gica

l sta

tions

in S

urpr

ise

Val

ley

with

lake

eva

pora

tion

assu

med

to b

e eq

uiva

lent

to p

an e

vapo

ratio

n. A

vera

ge p

reci

pita

tion

= 5

66 m

m/y

r, av

erag

e pa

n ev

apor

atio

n =

905

mm

/yr,

and

aver

age

runo

ff =

38

mm

/yr.

Run

off e

stim

ated

from

gra

phs

in M

iffl in

and

Whe

at (

1979

).§ E

stim

ated

from

pol

len

asse

mbl

ages

at L

ittle

Lak

e, O

rego

n (W

oron

a an

d W

hitlo

ck, 1

995)

.# P

erce

nt c

hang

e in

pre

cipi

tatio

n, L

GM

min

us m

oder

n. M

oder

n pr

ecip

itatio

n is

take

n as

566

mm

/yr,

as th

e av

erag

e of

rai

nfal

l and

sno

w w

ater

equ

ival

ent f

rom

Lak

e C

ity (

1929

–196

0), C

edar

ville

(18

94–2

012)

, and

F

ort B

idw

ell (

1911

–201

1) m

eteo

rolo

gica

l sta

tions

arc

hive

d in

the

Wes

tern

Reg

iona

l Clim

ate

Cen

ter

data

base

(ht

tp://

ww

w.w

rcc.

dri.e

du/s

umm

ary/

Clim

smnc

a.ht

ml).

**S

ee T

able

8 fo

r ca

lcul

atio

ns.

††C

alcu

late

d by

Miffl

in a

nd W

heat

(19

79)

assu

min

g a

2.34

°C

(5

°F)

tem

pera

ture

red

uctio

n, 3

12 m

m/y

r pr

ecip

itatio

n, a

nd a

n av

erag

e hy

drol

ogic

inde

x of

0.6

8 in

the

sout

h-ce

ntra

l Ore

gon

and

extr

eme

nort

hwes

tern

Nev

ada

regi

on.


Ibarra et al.


exposed wave-cut shorelines, is ±10 cm. The location and elevation of all samples are pre-sented in Table 1 and Figure 2.

Analytical Procedures

The laboratory work carried out to deter-mine the Lake Surprise hydrograph during the last glacial cycle included the application of 230Th-U geochronology, stable isotopic analy-ses, elemental analyses, and accelerator mass spectrometer (AMS) radiocarbon (14C) geo-chronology on tufa samples. To support the 230Th-U geochronology, we also analyzed the elemental and U isotopic composition of mod-ern playa sediments (using leachate methods of Tessier et al., 1979; Maher et al., 2003, 2006; Oster et al., 2012) and modern water samples. Detailed analytical methods are provided in the Data Repository (see footnote 1).

U and Th isotopic compositions were ana-lyzed at the ICP-MS–thermal ionization mass spectrometry (TIMS) facility at Stanford Uni-versity, using a Nu Instruments Plasma high-resolution MC-ICP-MS. Column chemistry was performed using standard element specifi c ion exchange chromatography methods (Luo et al., 1997; Potter et al., 2005; Stirling et al., 2007). Isotopic standards CRM 145, SRM 4321A, IRMM-036, and OU Th “U,” and multiple dissolution aliquots of spiked rock references BZVV, BCR-2, and TML were measured during analytical sessions. The long-term averages of the isotopic standards and rock reference stan-dards (Fig. DR2; Table DR2 [see footnote 1]) agree with previously measured literature values (Turner et al., 1997, 2001; Thomas et al., 1999; Raptis et al., 1998; Cheng et al., 2000; Shen et al., 2002; Amelin and Back, 2006; Placzek et al., 2006a; Sims et al., 2008; Neymark, 2011; Oster et al., 2012; Torfstein et al., 2013).

U-Series Age DeterminationTo calculate detrital Th–corrected 230Th-U

ages, we relied upon both the isochron approach, involving suites of coeval samples, and single-sample detrital Th correction. From 21 tufa samples, we processed a total of 111 subsamples. This included 13 sets of 7 coeval samples, two sets of 5 coeval samples from the inner and outer rind of a thick lower-elevation sample (SVDI11-T2), and 10 supporting single or duplicate samples. Additionally, to support the construction of isochrons, four 1.5 N HNO3 leach residues and one modern carbonate sam-ple were also analyzed.

Single-sample correction. For a single (sub-)sample, the 230Th daughter (supported by 234U and 238U) can be determined given an assumed initial (230Th/232Th) and 232Th concentration

(normalized by either 234U or 238U). The mea-sured (230Th/238U) is corrected using the equation from Kaufman (1993):

230

238

230

238

232

238

230

232

Th

U

Th

U

Th

U

Th

A MM

⎛⎝⎜

⎞⎠⎟

=⎛⎝⎜

⎞⎠⎟

−⎛⎝⎜

⎞⎠⎟ TTh

e t⎛⎝⎜

⎞⎠⎟

−

0

230( )λ, (3)

where the A denotes the authigenic or sup-ported (230Th/238U), M denotes the measured isotope ratios (230Th/238U) and (233Th/238U), 0 denotes the assumed initial (230Th/232Th), and t is the apparent time calculated before correc-tion for initial Th (cf. Kaufman, 1993; Israelson et al., 1997; Placzek et al., 2006a, 2006b). Once the measured ratio is corrected for initial Th, a corrected age is calculated by substituting of (230Th/238U)A into Equation 1. The magnitude and error associated with this correction are a func-tion of the concentration of 232Th in a sample, the assumed (230Th/232Th)0, and the error on the assumed (230Th/232Th)0. The error on the assumed (230Th/232Th)0 is typically the greatest source of error on the calculated age when (230Th/232Th)M < 10. Although some authors have assumed that (230Th/232Th)0 is unity (e.g., Sylvestre et al., 1999) or equal to upper continental crust (e.g., Ludwig and Titterington, 1994; Polyak and Asmeron, 2001), it has been observed that in terrestrial aqueous environments, including paleolakes, (230Th/232Th)0 can vary from 0.5 to 4.2 (cf. Placzek et al., 2006a, their table 5). Thus, for a given system, the most accurate constraint on (230Th/232Th)0 is via modern lake carbonate mea-surements (e.g., Lin et al., 1996; Israelson et al., 1997) or an isochron approach (e.g., Placzek et al., 2006a; Blard et al., 2011; Torfstein et al., 2013), as described next. We calculated single-sample ages for all subsamples and error-weighted averages for each set of subsamples.

Isochron method. A complementary approach to single-sample corrections is an isochron approach. Isochrons allow for the calculation of the (230Th/238U) and (234U/238U) of the pure authigenic carbonate from sets of coeval sam-ples, without necessarily needing to constrain (230Th/232Th)0. Two mathematically equiva-lent pairs of two-dimensional (2-D) isochrons sharing one common axis or a simultaneous three-dimensional (3-D) solution can yield (230Th/238U)A and (234U/238U)A. The 2-D iso-chrons yield (230Th/238U)A and (234U/238U)A via the slopes of Rosholt isochrons [(238U/232Th)M vs. (230Th/232Th)M and (238U/232Th)M vs. (234U/232Th)M] or the y-intercepts of Osmond-type isochrons [(232Th/238U)M vs. (230Th/238U)M and (232Th/238U)M vs. (234U/238U)M] (Osmond et al., 1970; Rosholt, 1976; Luo and Ku, 1991; Bischoff and Fitzpatrick, 1991; Ludwig and Titterington, 1994). Further-more, the detrital (230Th/232Th) can be determined

by the y-intercept of the (238U/232Th)M versus (230Th/232Th)M Rosholt isochron or the slope of the (232Th/238U)M versus (230Th/238U)M Osmond isochrons (Lin et al., 1996; Blard et al., 2011). Various methods have been investigated to con-struct sample pair isochrons. Initially, studies relied on leachate/residue (L/R) and leachate/leachate (L/L) methods (e.g., Kaufman, 1971; Schwarcz and Latham, 1989) to produce mea-surement pairs used to construct isochrons. However, leachate schemes have been found to preferentially solubilize U or Th. Nevertheless, if the majority of U is in the authigenic carbonate phase, these methods may be acceptable (e.g., Ku and Liang, 1984; Schwarcz and Latham, 1989; Przyblowicz et al., 1991; Kaufman, 1993). Alter-natively, to produce consistent mixing relation-ships between the authigenic and detrital compo-nents, a total sample dissolution (TSD) method, involving full digestion of suites (n ≥ 3) of coeval samples (Bischoff and Fitzpatrick, 1991; Luo and Ku, 1991), has been used in recent studies (e.g., Hall and Henderson, 2001; Soligo et al., 2002; Garnett et al., 2004; Haase-Schramm et al., 2004; Blard et al., 2011; Torfstein et al., 2013). Here we used the TSD method for all subsamples. We also measured four residues from a 1.5 N HNO3 leach of separate subsamples with suffi cient sample material.

Several methodologies have been proposed to construct statistically signifi cant linear regres-sions of the paired isochrons. Statistical rigor is required to produce meaningful and representa-tive 230Th-U ages while accounting for both ana-lytical uncertainties in MC-ICP-MS or TIMS measurements, as well as geologic scatter. Luo and Ku (1991) proposed a methodology using a simple least-squares fi t with counting statistics, which does not consider error-weighting or error correlation (in x and y errors), noting that doing so would require more than three or four coeval samples, which is often unpractical given sample size and laboratory method limitations (cf. Ku, 2000). Ludwig and Titterington (1994) proposed a 3-D simultaneous solution of the Osmond isochrons using maximum-likelihood estima-tion (MLE), allowing for the projection of the detritus-free end member onto a traditional 230Th-234U-238U evolution plot. This method is imple-mented in Isoplot (Ludwig, 2012). Finally, recent studies (e.g., Hall and Henderson, 2001; Soligo et al., 2002; Garnett et al., 2004; Blard et al., 2011) have used error-weighted 2-D linear fi ts to the individual Rosholt or Osmond isochrons using methods originally developed by York (1968) and implemented in Isoplot (Ludwig, 2012).

For the suites of coeval samples, to calculate (230Th/238U)A and (234U/238U)A, and calculate a detrital Th–corrected isochron age, we evalu-ated both solutions to separate 2-D isochrons




(e.g., Hall and Henderson, 2001; Soligo et al., 2002; Garnett et al., 2004; Blard et al., 2011) and the simultaneous 3-D solution of the Osmond isochrons using MLE (Ludwig and Tit-terington, 1994). Both methods calculate nearly identical absolute ages but differ in the calcu-lated error on (230Th/238U)A and (234U/238U)A. For the 2-D solutions, to best illustrate spread along the isochrones, we use the slopes of Rosholt isochrons [(238U/232Th)M vs. (230Th/232Th)M and (238U/232Th)M vs. (234U/232Th)M]. While construct-ing isochrones, some subsamples were rejected, including residues, to minimize the error on the (238U/232Th)M versus (230Th/232Th)M isochron slope and produce a mean square weighted deviation (MSWD) closest to ~1 (cf. Hall and Henderson, 2001; Garnett et al., 2004). In an effort to maximize the precision of our 230Th-U ages, we attempted to construct isochrons using 5–7 subsamples, i.e., more than previous stud-ies that have used isochron approaches to date impure carbonates and evaporites (e.g., Luo and Ku, 1991; Blard et al., 2011).

Climate Model Output Analysis

To calculate changes in precipitation and evapotranspiration predicted by AOGCMs for the western United States, we computed aver-age monthly climatologies using the monthly precipitation, total evaporation, runoff, relative humidity, and mean annual temperature out-puts for the LGM (21 ka boundary conditions) and preindustrial control experiments com-piled by the Paleoclimate Model Intercompari-son Project 3 (PMIP3; Braconnot et al., 2012; http:// pmip3 .lsce .ipsl .fr/). The nine models we included are NCAR-CCSM4 (Gent et al., 2011; Brady et al., 2013), CNRM-CM5 (Voldoire et al., 2013), FGOALS-g2 and IPSL-CM5A-LR (Kageyama et al., 2013a, 2013b), MRI-CGCM3 (Yukimoto et al., 2012), MPI-ESM-P, GISS-E2-R, COSMOS-ASO, and MIROC-ESM (Sueyoshi et al., 2013); all were used because of their inclusion into the PMIP3/CMIP5 data-base (Coupled Model Intercomparison Project 5; http:// cmip-pcmdi .llnl .gov /cmip5/). Monthly and annually summed precipitation, total evapo-ration, and runoff anomalies (LGM minus pre-indus trial control) were calculated for Surprise Valley using bilinear interpolation for both climate model experiments. Similarly, annu-ally averaged relative humidity and tempera-ture anomalies were calculated. Not all output variables are uniformly archived in the PMIP3 database. COSMOS-ASO does not report run-off values, and COSMOS-ASO, FGOALS-g2, MIROC-ESM, and MPI-ESM-P do not report relative humidity values. No bias correction was applied to the climate models outputs. Instead,

for comparison to paleoclimate records, we report the percent change in precipitation, total evaporation, and runoff simulated by the LGM experiments minus preindustrial control experi-ments for each climate model in the PMIP3 ensemble. For relative humidity and mean annual temperature, we report the absolute change.

RESULTS

In the following sections, we present our results and examine the reliability of the geo-chronologic approaches, spatial relationships, and the U-series and stable isotope systematics. We then construct a late Pleistocene hydrograph for Lake Surprise. For the purposes of discus-sion, the tufa samples are split into three groups by elevation: (1) samples from prominent lower-elevation shorelines at 1419–1472 m; (2) sam-ples from the less-prominent middle-elevation shorelines of 1478–1531 m; and (3) samples from higher-elevation shorelines >1542 m (Figs. 2B–2E).

Evaluating Stable Isotope, Sr/Ca, and U-Series Systematics

Stable Isotopic and Elemental Signatures of Tufas and Modern Samples

Measurements of δ18O, δ13C, and Sr/Ca in paleoshoreline carbonates and modern waters and sediment are shown in Figure 3. All paleo-shoreline samples from <1531 m have δ18O values of −2.50‰ to −4.51‰, and δ13C values of 2.68‰–4.10‰; the modern playa carbon-ate has δ18O = −4.05‰ and δ13C = −0.11‰. High-elevation samples have much lower δ18O values of −13.13‰ to −9.33‰, and lower δ13C values of −6.32‰ to −1.72‰. Others report a large, −14.4‰, seasonal variation in mod-ern lake-water δ18O from the middle playa of −9.5‰–4.9‰ and minimal variation in creek waters, from −15.0‰ to −13.7‰ (Ingraham and Taylor, 1989; Sladek et al., 2004; Table DR3 [see footnote 1]).

If the range of measured modern water Sr/Ca refl ects the range of late Pleisto cene lake-water Sr/Ca (Tables 3 and 4), and assuming a range of values for the partition coeffi cient (KSr) of

K

Sr Ca

Sr CaSr

calcite

solution= = −( / )

( / ). .0 12 0 35

(Gabitov and Watson, 2006), the Sr/Ca mea-sured in the tufa samples (Table 3) is at the high end of the range of expected values. The high-est-elevation samples have a lower Sr/Ca (aver-age = 0.86 ± 0.66 mmol/mol) compared to the samples from elevations <1531 m (average = 1.16 ± 0.30 mmol/mol).

A positive covariance with a rating of weak, moderate, or strong following the method of Davis et al. (2009) is shown in Table 3. For all samples <1531 m, both δ18O-δ13C and δ18O-Sr/Ca are moderately correlated (Figs. 3C and 3D). For the lowest-elevation samples of LGM age, δ18O-δ13C are strongly correlated; how-ever, δ18O-Sr/Ca are not correlated, likely due to minimal spread in measured Sr/Ca ratios. For middle-elevation samples, δ18O-δ13C are moderately correlated, and δ18O-Sr/Ca are very strongly correlated (Figs. 3A and 3B). Values of δ18O, δ13C, and Sr/Ca from the highest-elevation samples suggest potential alteration of the sam-ples due to recrystallization or pedogenic over-printing (Table 3; Fig. 3).

The covariance of δ18O-δ13C and δ18O-Sr/Ca can be used to evaluate the role of evaporation in lake systems (Müller et al., 1972; Eugster and Kelts, 1983; Talbot, 1990; Li and Ku, 1997; Davis et al., 2009; Chamberlain et al., 2013). Terminal basin lakes have comparatively long residence times, resulting in the evaporative enrichment of 18O in the lake water and preferential outgassing of 12C-rich CO2 from the system (Talbot, 1990). If a lake is hydrologically closed, and evaporation is high, then δ18O and δ13C will covary (Talbot, 1990; Li and Ku, 1997; Davis et al., 2009). Simi-larly, Sr/Ca ratios have been used to assess evapo-rative effects in lake systems (Müller et al., 1972; Davis et al., 2009). Müller et al. (1972) showed that for highly evaporative lakes, Sr/Ca in car-bonates is proportionally correlated to Sr and Ca concentrations in lake water. With a KSr less than 1 (Gabitov and Watson, 2006), Sr is not removed as effi ciently from lake water as Ca, which is taken up by precipitating carbonates; thus, Sr is concentrated when the net evaporative fl ux is high relative to lake volume (Eugster and Kelts, 1983; Davis et al., 2009). This correlation is not expected with an open-system lake because Sr is fl ushed from the system. Surprise Valley tufa samples demonstrate a moderate to high δ18O-δ13C and δ18O-Sr/Ca covariance among sample groups (Table 3; Fig. 3).

The extent to which the Surprise Valley lake system was a terminal basin in the past deter-mines the utility of lake shoreline ages and other geochemical data as indicators of past climate. Based on previous studies of lacustrine carbon-ates and the relatively robust trends observed here, we propose that the δ18O-δ13C-Sr/Ca sys-tem refl ects the fact that the latest Pleistocene Lake Surprise was indeed a closed, inward-draining pluvial lake system.

U-Series Measurements of Modern SamplesThe 19 water samples and 5 modern playa

samples (see Fig. 2A for locations) demonstrate the range of expected variability in U concentra-


Ibarra et al.


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tions and (234U/238U) within the Surprise Valley watershed (Table 4). The average measured U concentrations in surface waters and ground-waters from Surprise Valley are 0.430 ± 1.722 ng/mL and 0.687 ± 1.722 ng/mL, respectively. Hot spring waters have much lower U concen-trations, ranging from 0.0031 to 0.2552 ng/mL, suggesting that hot springs contribute minimally to the U budget of modern lake and ground-water. Surface-water (234U/238U) measurements, draining from primarily basaltic bedrock, range from 1.478 to 2.360. The (234U/238U) values from groundwater and hot spring waters dem-onstrate a greater range of variability from 1.391 to 3.508. Modern playa pore waters, authigenic carbonate fractions, and the modern playa car-bonate all fall within the lower end of the range of observed water sample variability (Table 4).

Geochronology

230Th-U GeochronologyThe results of the U and Th isotope measure-

ments, and the 230Th-U age calculations are pre-sented in Table 5 and Table DR4 (see footnote 1). Figure 4 and Figures DR3–DR5 (see footnote 1) show 230Th-U age calculations via pairs of 2-D

Rosholt isochrons and 3-D Osmond isochrons for suites of coeval samples. For all suites of 5+ coeval samples, calculated Rosholt isochron ages are reported in Table 5. One important assumption is that these isochrons constitute mixing relationships between the authigenic carbonate end member and a Th end member with a distinct Th isotope composition, either detrital or hydrogenous Th. Hydrogenous 232Th in modern surface waters was less than 6 pg/mL (see Data Repository methods [see footnote 1]), which suggests that detrital Th is the only sub-stantial Th isotope end member for Lake Sur-prise carbonates and is likely introduced into the tufa via incorporation of siliciclastic or organic particles containing Th.

To calculate the most robust isochron fi t that minimizes the error on the calculated (230Th/238U)A and the eventual 230Th-U age, some subsamples were excluded from the error-weighted linear regressions (Table DR4 [see footnote 1]). For three samples, no robust 2-D Rosholt or 3-D Osmond isochrons could be cal-culated. Additionally, two samples produced no robust 3-D Osmond isochron solutions because the calculated 230Th-U age error was greater than the corrected 230Th-U age. After excluding out-

lying data points, all Rosholt and Osmond ages are concordant with nearly identical calculated 230Th-U ages (Fig. 5A). Differences in the age error between the two methods are the result of the way in which analytical uncertainty and geo-logic scatter are handled (cf. Ludwig and Titter-ington, 1994; Ku, 2000). To be consistent with 230Th-U isochron ages reported in recent litera-ture (e.g., Hall and Henderson, 2001; Soligo et al., 2002; Garnett et al., 2004; Blard et al., 2011), hereafter we will refer to the 230Th-U ages from the Rosholt isochrons.

For all 111 subsamples, we calculated single-sample detrital Th–corrected ages. For samples with robust 2-D Rosholt isochrons (n = 68), we used the y intercept of the (238U/232Th)M versus (230Th/232Th)M plot to calculate the (230Th/232Th)0 value used in Equation 3 (Torfstein et al., 2013). For the remaining samples (n = 43), an error-weighted mean of the isochron intercepts and the modern carbonate (230Th/232Th) measure-ment was used to calculate a basin average (230Th/232Th)0 [(230Th/232Th)0 = 1.327 ± 0.096, error-weighted mean, 2σ] (Table DR5; Fig. DR6 [see footnote 1]). Because the distribution of errors on the (230Th/232Th)0 isochron intercepts is nonuniform and varies between samples (Fig.

TABLE 4. Sr/Ca, [238U], AND (234U/238U) OF MODERN WATER AND PLAYA SAMPLES

Sample name

(epytlairetaM 234U/238U) [238U] (ng/mL) [Sr] (ng/mL)

[Ca] (µg/mL)

Sr/Ca (mmol/mol)

Modern water samples804.1407.8897.621200.0±0570.0700.0±933.2)keerCelgaE(maertS1SW-21IDVS734.2227.31790.373700.0±9301.0500.0±648.1)keerCnosremE(maertS2SW-21IDVS742.1153.42083.664210.0±6374.0600.0±992.2)keerCregnarG(maertS3SW-21IDVS953.3036.41834.7013200.0±2180.0600.0±063.2)keerCpeeD(maertS4SW-21IDVS663.3301.2674.519600.0±2552.0600.0±630.2)gnirpSdyoB(gnirpStoH5SW-21IDVS

SVDI12-WS6 Hot Spring (Seyferth Hot Springs)* - 0.0045 ± 0.0002 548.531 29.163 8.604SVDI12-WS7 Hot Spring (Leonard Hot Springs)* - 0.0031 ± 0.0001 236.911 13.973 7.755SVDI12-WS8 Hot Spring (Surprise Valley Hot Springs)* - 0.0951 ± 0.0028 260.084 19.437 6.120SVDI12-WS9 Groundwater (Lake City Well) 2.137 ± 0.006 0.3692 ± 0.0105 181.739 29.890 2.781

319.2623.21305.879000.0±2620.0800.0±540.2)keerClliM(maertS01SW-21IDVSSVDI12-WS12 Stream (Fort Bidwell Creek) 2.399 ± 0.007 0.1137 ± 0.0035 33.688 7.382 2.087

018.1776.7073.039000.0±0630.0500.0±874.1)ekaLeinnA(ekaL/dnoP31SW-21IDVSSVDI12-WS15 Groundwater (Cockeral Ranch Well #1) 2.130 ± 0.006 0.4574 ± 0.0129 51.796 12.764 1.856SVDI12-WS16 Groundwater (Cockeral Ranch Well #2) 1.508 ± 0.004 0.9190 ± 0.0535 133.410 25.135 2.428SVDI12-WS17 Hot Spring (Lake City Hot Springs)* - 0.0047 ± 0.0003 400.516 22.214 8.247SVDI12-WS18 Hot Spring (Unnamed Hot Spring) 1.391 ± 0.004 0.0995 ± 0.0029 3.978 2.093 0.869

851.2887.12118.2014861.0±5035.2500.0±048.1)keerCtsoL(maertS91SW-21IDVSSVDI12-WS20 Groundwater (Eagleville Well) 1.797 ± 0.005 0.7240 ± 0.0657 176.296 36.048 2.237SVDI12-WS21 Groundwater (Cedarville Well) 3.508 ± 0.040 0.9628 ± 0.0815 152.034 29.660 2.345

Modern playa samplesSVDI12-C1 Modern playa carbonate (middle playa edge) 1.441 ± 0.005

Playa Pore WatersSVDI12-P1 1:1 DI water extraction (middle playa edge) 1.455 ± 0.005SVDI12-P2 1:1 DI water extraction (middle playa center) 1.640 ± 0.006SVDI12-P3 1:1 DI water extraction (upper playa) 1.595 ± 0.006SVDI12-P4 1:1 DI water extraction (Duck Flats) 1.591 ± 0.006

Playa authigenic carbonate fractionSVDI12-P1 NaOAc carbonate leach (middle playa edge) 1.327 ± 0.004SVDI12-P2 NaOAc carbonate leach (middle playa center) 1.542 ± 0.006SVDI12-P3 NaOAc carbonate leach (upper playa) 1.513 ± 0.004SVDI12-P4 NaOAc carbonate leach (Duck Flats) 1.571 ± 0.004

Note: DI—deionized water. Ac—acetate.*(234U/238U) not measured due to low U concentrations.


Ibarra et al.


TAB

LE 5

. IS

OC

HR

ON

DE

RIV

ED

AC

TIV

ITY

RA

TIO

S A

ND

DE

TR

ITA

L T

HO

RIU

M C

OR

RE

CT

ED

AG

ES

TS

D R

osho

lt Is

ochr

on C

arbo

nate

A

ctiv

ity R

atio

s (A

ll S

ub-S

ampl

es)

TS

D M

etho

d D

etrit

al C

orre

cted

Age

(A

ll S

ub-S

ampl

es)

2x R

osho

lt Is

ochr

on D

eriv

ed

TS

D R

osho

lt Is

ochr

on C

arbo

nate

A

ctiv

ity R

atio

s (M

ost R

obus

t Fit)

§T

SD

Met

hod

Det

rital

Cor

rect

ed A

ge (

Mos

t R

obus

t Fit)

2x

Ros

holt

Isoc

hron

Der

ived

Sam

ple

nam

eN

o. o

f Sub

-S

ampl

es(23

0 Th/

238 U

)*(23

4 U/23

8 U)†

Cor

rect

ed A

ge (

ka)

(234 U

/238 U

) initi

al

No.

of S

ub-

Sam

ples

(230 T

h/23

8 U)*

(234 U

/238 U

)†C

orre

cted

Age

(k

a ca

l BP

)(23

4 U/23

8 U) in

itial

Acc

omod

atio

n Z

one

Sho

relin

e S

et

SV

DI1

1-T

2 O

uter

Rin

d5

No

Rob

ust R

osho

lt (23

0 Th/

232 T

h) v

s (23

8 U/23

2(tlohso

Rtsuboro

NnorhcosI

)hT

230 T

h/23

2 Th)

vs

(238 U

/232 T

h) is

ochr

on

SV

DI1

1-T

2 In

ner

Rin

d5

0.28

3 ±

0.0

511.

561

± 0

.049

21.5

2 ±

4.3

41.

597

± 0

.051

40.

289

± 0

.014

1.56

3 ±

0.0

6421

.93

± 1

.53

1.59

9 ±

0.0

66 750.0±

175.136.1

±96.62

450.0±

925.1410.0

±733.0

4740.0

±475.1

41.5±

25.52440. 0

±435.1

850.0±

523.07

3T-11 I

DV

S

98 0.0±

616.180.2

±48.81

780.0±

485.1220.0

±452.0

4280.0

±766.1

26.01±

79.62670. 0

±816.1

521.0±

063.07

4T-11 I

DV

S

712.0±

710.214.9

±28.11

212.0±

389.155 1.0

±702.0

7712 .0

±710. 2

1 4.9±

28.11212.0

±389.1

551.0±

702.07

41T -11I

DV

S

(tlohsoRtsubor

oN

113.0±

904 .192.85 2

±48.5 01

570 .0±

403.1362.1

±638.0

781

T-11ID

VS

230 T

h/23

2 Th)

vs

(238 U

/232 T

h) is

ochr

on

Mid

dle

Lake

Sho

relin

e S

et

670.0±

21 6.168.5

±44.62

270.0±

765 .1660.0

±343.0

7670.0

±216 .1

6 8. 5±

44.6 2270 .0

±765 .1

660.0±

3 43 .07

1T-2 1I

DV

S SV

DI1

2-T

2**

7 +

res

idue

0.31

1 ±

0.0

151.

624

± 0

.016

22.7

8 ±

1.2

31.

666

± 0

.017

7 +

res

idue

0.31

1 ±

0.0

151.

624

± 0

.016

22.7

8 ±

1.2

31.

666

± 0

.017

SV

DI1

2-T

2**

7 (n

o re

sidu

e)0.

371

± 0

.035

1.52

2 ±

0.1

3529

.94

± 4

.42

1.56

8 ±

0.0

147

(no

resi

due)

0.37

1 ±

0.0

351.

522

± 0

.135

29.9

4 ±

4.4

21.

568

± 0

.014

-3

T-21 ID

VS

-

-4

T-21 ID

VS

-

SV

DI1

2-T

5**

7 +

res

idue

0.30

6 ±

0.1

201.

611

± 0

.060

22.5

7 ±

9.8

11.

651

± 0

.064

5 +

res

idue

0.31

0 ±

0.0

501.

615

± 0

.064

22.8

7 ±

4.1

71.

656

± 0

.067

SV

DI1

2-T

5**

7 (n

o re

sidu

e)0.

321

± 0

.175

1.55

7 ±

0.1

1324

.82

± 1

5.16

1.59

8 ±

0.1

215

(no

resi

due)

0.33

5 ±

0.0

861.

544

± 0

.181

26.2

7 ±

8.3

11.

586

± 0

.190

-7

T-2 1ID

VS

36 3. 0±

138 .105.4

±10. 21

6 53.0±

3 08 .16 50.0

±091 .0

5612 .0

±621. 2

4 7. 9±

81 .0 2902. 0

±460.2

451.0±

5 53 .07

9T-2 1I

DV

S

36 0. 0±

139. 178.0

±8 4. 61

260.0±

8 88.10 10.0

±962 .0

5031. 0

±909. 1

0 1. 2±

38 .6 1621. 0

±768.1

520.0±

1 72.07

0 1T -2 1I

DV

S

-11

T-2 1ID

VS

-

(tl ohs oRts ubor

oN

72 1

T-2 1ID

VS

230 T

h/23

2 Th)

vs

(238 U

/232

(tlohsoRts ubor

oN

nor hcosi)h

T23

0 Th/

232 T

h) v

s (23

8 U/23

2 Th)

isoc

hron

Low

er L

ake

Sho

relin

e S

et

67 0. 0±

785. 148.1

±58. 02

370.0±

4 55 .18 10.0

±472 .0

7670 .0

±785. 1

4 8. 1±

58 .0 2370. 0

±455.1

810.0±

4 72 .07

3 1T-2 1I

DV

S

260.0±

728.176.2

±52.81

060.0±

587.1730.0

±972.0

5460.0

±138 .1

5 3. 7±

61.81060 .0

±987 .1

401 .0±

8 72.07

41T-2 1I

DV

S Upp

er L

ake

Sho

relin

e S

et

650.0±

706.164.1

±44.91

450.0±

575.1610.0

±062.0

5650.0

±216 .1

91.8±

48.1 2250. 0

±675.1

990.0±

092.07

5 1T-21 I

DV

S

-7 1

T-21 ID

VS

-

-8 1

T-2 1ID

VS

- --

9 1T-21 I

DV

S

(con

tinue

d)




TAB

LE 5

. IS

OC

HR

ON

DE

RIV

ED

AC

TIV

ITY

RA

TIO

S A

ND

DE

TR

ITA

L T

HO

RIU

M C

OR

RE

CT

ED

AG

ES

(co

ntin

ued

)

egA

nobracoidaR

gvA

dethgieW-rorr

Enoitcerro

Celp

maS

elgniS

)noitu loS

D- 3dn o

msO

ELM(

e gA

d etc erroCl at irt e

DD

ST

Sam

ple

nam

eN

o. o

f Sub

-S

ampl

es(23

0 Th/

238 U

)(23

4 U/23

8 U)

Cor

rect

ed A

ge (

ka)

(234 U

/238 U

) initi

al

Cor

rect

ed A

ge (

ka)#

(234 U

/238 U

) initi

al

Cor

rect

ed A

ge

(ka

cal.)

Acc

omod

atio

n Z

one

Sho

relin

e S

et

SV

DI1

1-T

2 O

uter

Rin

dN

o R

obus

t Osm

ond

Isoc

hron

17.2

8 ±

1.6

11.

610

± 0

.011

SV

DI1

1-T

2 In

ner

Rin

d4

0.28

5 ±

0.0

261.

560

± 0

.029

21.7

± 2

.21.

595

± 0

.031

21.4

7 ±

0.9

41.

609

± 0

.003

19.2

2 ±

0.2

3 72.0±

42.12310.0

±755.1

68.0±

01.62620.0

±275.1

1.2±

5.62420.0

±035.1

32 0.0±

533. 04

3T- 11I

DV

S

12.0±

48.02230.0

±935.1

78.1±

48.91430.0

±536.1

6. 2±

1. 81430.0

±306.1

13 0.0±

74 2. 04

4T- 11I

DV

S SV

DI1

1-T

14N

o R

obus

t Osm

ond

Isoc

hron

11.4

1 ±

2.0

11.

682

± 0

.247

12.7

0 ±

0.0

6

SV

DI1

1-T

18N

o R

obus

t Osm

ond

Isoc

hron

15.4

1 ±

5.8

51.

261

± 0

.009

16.0

0 ±

0.1

8

Mid

dle

Lake

Sho

relin

e S

et

5 2. 0±

22.12810. 0

±794 .1

8 8. 0±

45.81570.0

±995 .1

8. 4±

6. 6257 0. 0

±55 5. 1

84 0.0±

24 3. 07

1T-21 I

DV

S SV

DI1

2-T

2**

7 +

res

idue

0.31

2 ±

0.0

141.

624

± 0

.019

23.0

± 1

.31.

665

± 0

.018

24.8

4 ±

0.9

21.

544

± 0

.003

22.1

3 ±

0.2

3

SV

DI1

2-T

2**

7 (n

o re

sidu

e)0.

363

± 0

.039

1.53

0 ±

0.1

5029

.0 ±

3.9

1.58

0 ±

0.1

60

-3

T-21ID

VS

18.3

3 ±

1.8

21.

527

± 0

.104

-4

T-2 1ID

VS

19.8

0 ±

2.0

01.

504

± 0

.193

SV

DI1

2-T

5**

7 +

res

idue

0.31

0 ±

0.0

571.

600

± 0

.055

23.2

± 5

.21.

640

± 0

.054

24.9

1 ±

3.1

01.

507

± 0

.039

10.6

9 ±

0.1

1

SV

DI1

2-T

5**

7 (n

o re

sidu

e)0.

326

± 0

.088

1.52

0 ±

0.1

3026

.0 ±

8.4

1.56

0 ±

0.1

40

-7

T-2 1ID

VS

16.6

7 ±

6.5

71.

543

± 0

.011

SV

DI1

2-T

9N

o ro

bust

Osm

ond

Isoc

hron

11.7

8 ±

2.8

51.

840

± 0

.021

14.5

3 ±

0.3

5 42.0±

49.41920.0

±6 48.1

74.0±

54.71290.0

±9 29.1

7.1±

5.6109 0. 0

±68 8. 1

120 .0±

86 2.05

0 1T-2 1I

DV

S

-11

T-21 ID

VS

27.4

9 ±

2.8

71.

237

± 0

.003

SV

DI1

2-T

12N

o ro

bust

Osm

ond

Isoc

hron

29.2

1 ±

8.4

51.

197

± 0

.024

8.58

± 0

.07

Low

er L

ake

Sho

relin

e S

et

03.0±

31.12800.0

±7 55.1

31.1±

03.12440.0

±1 85 .1

4.3±

9.0244 0. 0

±18 5. 1

93 0.0±

37 2. 07

3 1T-2 1I

DV

S

81. 0±

91.51610.0

±487 .1

41. 2±

89.81640.0

±548.1

5. 2±

8. 7154 0. 0

±308. 1

53 0.0±

47 2. 05

41T-2 1I

DV

S Upp

er L

ake

Sho

relin

e S

et

32.0±

74.91110.0

±685.1

21.1±

17.91040.0

±506.1

6. 3±

5. 91930.0

±275.1

440.0±

062.05

51T-2 1I

DV

S

-71

T-2 1ID

VS

70.3

7 ±

1.5

51.

196

± 0

.003

-8 1

T-21 ID

VS

115.

92 ±

6.4

41.

128

± 0

.004

25.3

1 ±

0.3

0

-9 1

T-21 ID

VS

24.7

0 ±

2.2

51.

177

± 0

.003

*Slo

pe o

f Ros

holt

Isoc

hron

(23

8 U/23

2 Th)

vs

(230 T

h/23

2 Th)

.† S

lope

of R

osho

lt Is

ochr

on (

238 U

/232 T

h) v

s (23

4 U/23

2 Th)

.§ S

ee T

able

DR

4 (t

ext f

ootn

ote

1) fo

r sa

mpl

es o

mitt

ed fr

om r

obus

t fi t

Ros

holt

isoc

hron

s.# S

ee T

able

DR

4 (t

ext f

ootn

otes

1)

for

sam

ples

om

itted

from

err

or-w

eigh

ted

mea

n.**

Ros

holt

and

Osm

ond

isoc

hron

age

s ca

lcul

ated

with

and

with

out r

esid

ue.


Ibarra et al.


0

1

2

3

4

0 2 4 6 8

(23

0T

h/2

32T

h)

(238U/232Th)

0

2

4

6

8

10

12

0 2 4 6 8

(23

4U

/23

2T

h)

(238U/232Th)

Residue

Residue

A - “Rosholt” Isochron

Slope = 0.311 ± 0.015 (2σ) = (230Th/238U)authigenic

Intercept = 0.904 ± 0.096 = (230Th/232Th)initial

MSWD = 3.7

Rosholt Isochron Age: 22.8 ± 1.2(234U/238U)

initial = 1.666 ± 0.017

B - “Rosholt” Isochron

Slope = 1.624 ± 0.016 (2σ) = (234U/238U)authigenic

Intercept = -0.829 ± 0.080

MSWD = 0.49

1.0

1.2

1.4

1.6

1.8

0.0 0.2 0.4 0.6 0.8

(23

4U

/23

8U

)

(230Th/238U)

230Th-U Age = 23.0 ± 1.3 ka (234U/238U)initial = 1.665 ± 0.018

MSWD = 17

C - “Osmond” 3-D Isochron

Residue

Rosholt IsochronsMeasured Isotope Ratios (2σ)

Error-weighted Regression

Error Envelope (2σ)

Osmond 3-D IsochronMeasured Isotope Ratios (2σ)

Projected Data Points (2σ)

Isochron Intercept (2σ)

Isochron

DR6 [see footnote 1]), we chose to use an error-weighted mean and standard deviation, rather than an unweighted mean, to represent the basin average (230Th/232Th)0 for samples without robust isochrons or a suffi cient number of sub-samples. The calculated value is similar to other Great Basin paleolakes (Lin et al., 1996, 1998; Fig. DR6 [see footnote 1]). All age calculations and the error-weighted means of the single-sam-

ple detrital Th–corrected ages for suites of sub-samples (n = 2–7) were calculated using Isoplot 3.75 (Ludwig, 2012).

A comparison of the error-weighted means of the single-sample detrital Th–corrected 230Th-U ages to the Rosholt isochron 230Th-U ages (con-sisting of samples from the two lower-elevation groups) indicates the utility of the two comple-mentary age calculation methods. For samples

with robust isochrons, all samples are concor-dant or nearly concordant (Fig. 5A). On aver-age, the error-weighted mean single-sample ages are 0.17 k.y. younger than the Rosholt ages, with no apparent trend with elevation (Fig. 5B). One outlier is SVDI12-T1, which has a much older Rosholt isochron age (26.44 ± 5.86 ka compared to 18.54 ± 0.88 ka). The older age is a result of a low (230Th/232Th)0 isochron intercept

Figure 4. Example of Rosholt and Osmond isochron plots calculating 230Th-U ages (in ka) for SVDI12-T2. All error ellipses and error enve-lopes are 2σ. (A–B) Rosholt isochrons of (230Th/232Th) vs. (238U/232Th) and (234U/232Th) vs. (238U/232Th) (measured values), with error-weighted linear regressions (see text for details), calculate the (230Th/238U)authigenic and (234U/238U)authigenic, based on the slopes of the linear regressions. The intercept of (230Th/232Th) vs. (238U/232Th) is the (230Th/232Th)initial value of the suite of coeval samples. Samples not included in linear regressions are gray ellipses. (C) Projected representation of a three-dimensional (3-D) Osmond isochron calculation of 230Th-U ages for coeval suites of samples (see text for details) onto a 230Th-234U-238U evolution plot. Black ellipses are measured values, and white ellipses are projected values based on the projected isochron (gray line). Gray ellipses are the calculated 230Th-U age (95% confi dence) and (234U/238U)0 of the sample. MSWD—mean square of weighted deviates.




and steeper slope in the (238U/232Th)M versus (230Th/232Th)M isochron. Due to this anoma-lously low (230Th/232Th)0 value, the basin average (230Th/232Th)0 was used to calculate the single-sample ages for SVDI12-T1. SVDI12-T2, from the same elevation (1419.5 m), yielded nearly concordant ages of 22.78 ± 1.23 ka (Rosholt age) and 24.84 ± 0.92 ka (single-sample age).

The calculated (234U/238U)0 values of the tufa samples (Table 5; Table DR4 [see footnote 1]), which should refl ect the (234U/238U) value of the water precipitating carbonate, demonstrate less variation in (234U/238U) than modern water, car-

bonate, and playa samples and form three groups (Fig. 6): (1) the lower-elevation samples of ca. 27–18 ka, which cluster around a (234U/238U)0 of 1.497–1.682; (2) the middle-elevation, post-LGM samples with elevated (234U/238U)0 from 1.784 to 1.846; and (3) the highest-elevation samples, with (234U/238U)0 between 1.128 and 1.261, below the minimum of modern values (Figs. 2B–2E and 6).

Radiocarbon GeochronologyThe radiocarbon geochronology results and

calibrations are presented in Table 6. Two of

the 15 samples have radiocarbon ages that inter-sect the IntCal13 calibration curve (Reimer et al., 2013) at multiple ages, resulting in two or more statistically probable calibrated ages. For all samples, the ages discussed hereafter are the calibrated average ages of the tufa samples taken from the age range with the highest rela-tive probability based on the area under the cali-brated age probability distribution. For all but one sample (SVDI12-T5-b), this area was >88% of the total area under the curve (Table 6).

A hydrograph using only the radiocarbon ages indicates that 12 of the 15 radiocarbon ages

8

12

16

20

24

28

32

8 12 16 20 24 28 32230Th-U 3-D “Osmond” Isochron Age (ka)

23

0T

h-U

“R

osholt”

Isochro

n A

ge (

ka)

8

12

16

20

24

28

32

8 12 16 20 24 28 32230Th-U SS Age (ka)

23

0T

h-U

“R

osholt”

Isochro

n A

ge (

ka)

A B

C D

8

12

16

20

24

28

32

8 12 16 20 24 14C Age (ka)

23

0T

h-U

SS

Age (

ka B

P)

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16

20

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32

8 12 16 20 24 14C Age (ka)

23

0T

h-U

“R

osholt”

Isochro

n A

ge (

ka)

Group 1

Group 2

Group 3

1:1 Line

Rejected

Figure 5. Comparison among 230Th-U age calculations, and between paired calibrated radiocarbon (14C) ages and 230Th-U ages. Samples are grouped by the same symbology as in Figures 2 and 3. Samples rejected due to apparent open-system behavior have gray error ellipses (see text for details). All error ellipses are 2σ. (A) Rosholt isochron-based 230Th-U ages compared to three-dimensional (3-D) Osmond isochron-based 230Th-U ages. (B) Rosholt isochron-based 230Th-U ages compared to error-weighted averages of single-sample (SS) detrital-corrected 230Th-U ages. (C) Rosholt isochron-based 230Th-U ages compared to radiocarbon ages. (D) Error-weighted averages of single-sample (SS) detrital-corrected 230Th-U ages compared to radiocarbon ages.


Ibarra et al.


Minimum modern (234U/238U)

Group 1 “Rosholt” Isochron Age

and (234/238U)initial

Range of Single Sample Detrital Th

Corrected Ages and (234U/238U)initial

Group 2 “Rosholt” Isochron Age

and (234/238U)initial

1.0

1.4

1.8

2.2

2.6

10 14 18 22 26 30 34

(23

4U

/23

8U

) initia

l

Age (ka)

A B

Mo

de

rn W

ate

r an

d

Pla

ya

(2

34U

/2

38U

)

Gro

up

3

Re

jecte

d S

am

ple

(2

34U

/2

38U

)in

itial

Figure 6. Comparison of 230Th-U age vs. (234U/238U)0 calculated using Equation 2 and the measured modern values of (234U/238U). Only sample groups 1 and 2 are plotted. (A) Rosholt isochron-derived (234U/238U)0 are shown as ellipses, with the range val-ues for the single-sample detrital Th–cor-rected samples shaded in gray. All errors are 2σ. (B) Box and whisker plots show the median and interquartile ranges of modern (234U/238U) and the rejected single-sample ages’ (234U/238U)0 from the group 3 samples.

TABLE 6. NEW RADIOCARBON AGES FOR LAKE SURPRISE

Sample name Laboratory number

Altitude (m)

14C age (yr ± 1σ)

Calibrated age range

(cal. yr ± 2σ)*

Relative area under distribution

Median age

(cal. yr)†

Calibrated age (ka cal. ± 2σ)*,§

IntCal13

Accommodation zone shoreline setSVDI11-T2-1 inner rind Beta –342012 1453.5 15,930 ± 70 18,988–19,457 (1.000) 19,212 19.22 ± 0.23SVDI11-T3-2 Beta –342013 1437.7 17,580 ± 70 20,978–21,511 (1.000) 21,247 21.24 ± 0.27SVDI11-T4-1b Beta –340102 1430.6 17,280 ± 60 20,631–21,052 (1.000) 20,836 20.84 ± 0.21SVDI11-T14-1c Beta –342014 1478.4 10,790 ± 50 12,644–12,758 (1.000) 12,708 12.70 ± 0.06SVDI11-T18-1c Beta –340103 1555.7 13,310 ± 40 15,820–16,187 (1.000) 16,010 16.00 ± 0.18

Middle lake shoreline setSVDI12-T1-a Beta –340104 1419.5 1,7560 ± 60 20,971–21,464 (1.000) 21,217 21.22 ± 0.25SVDI12-T2-b Beta –342015 1419.5 18,270 ± 70 21,899–22,355 (1.000) 22,140 22.13 ± 0.23SVDI12-T5-b Beta –342016 1444.3 9470 ± 40 10,581–10,794 (0.888) 10,713 10.69 ± 0.11

00.0±68.01)100.0(758,01–558,0120.0±99.01)250.0(700,11–369,0120.0±40.11)950.0(560,11–120,11

SVDI12-T9-1 Beta –340105 1508.9 12,420 ± 50 14,183–14,875 (1.000) 14,515 14.53 ± 0.35SVDI12-T10-b Beta –342017 1516.8 12,600 ± 50 14,693–15,178 (1.000) 14,964 14.94 ± 0.24SVDI12-T12-1 Beta –340106 1576.9 7810 ± 40 8459–8498 (0.045) 8587 8.48 ± 0.02

8509–8656 (0.929) 8.58 ± 0.0710.0±86.8)920.0(8968–1768

Lower lake shoreline setSVDI12-T13 Beta –342018 1437.2 17,490 ± 90 20,836–21,432 (1.000) 21,127 21.13 ± 0.30SVDI12-T14 Beta –342019 1530.7 12,750 ± 50 15,006–15,364 (1.000) 15,192 15.19 ± 0.18

Upper lake shoreline setSVDI12-T15-b Beta –342020 1433.1 16,150 ± 70 19,248–19,699 (1.000) 19,491 19.47 ± 0.23SVDI12-T18 Beta –342021 1564.2 20,970 ± 110 25,016–25,611 (1.000) 25,322 25.31 ± 0.30

*Calibrated using the Calib 7.0 program with IntCal13 (Stuiver and Reimer, 1993; Reimer et al., 2013). †Median age calculated using the Calib 7.0 program.§Bolded ages are the preferred ages with the highest probability and are used for comparison to the 230Th-U ages (Table 5; Fig. 5).




record the transgression and regression of Lake Surprise (Fig. 7A). Two samples from the low-est shoreline of the middle playa set are not con-cordant but have very similar ages of 21.22 ± 0.25 and 22.13 ± 0.23 ka cal. Similarly, two nearly identical-elevation samples from differ-ent sampling localities have concordant ages of 21.24 ± 0.27 and 20.13 ± 0.03 ka cal. With the exception of one anomalously young age, the lowest-elevation samples record transgres-sion from 1419.5 to 1453.5 m and have LGM ages ranging from 19.22 ± 0.23 to 22.13 ± 0.23 ka cal. Four tufa samples at middle elevations (1530.7–1478.4 m) and the anomalous low-elevation sample (1444.3 m) record consistent gradual regression from an apparent highstand at 15.19 ± 0.18 to 10.69 ± 0.11 ka cal. Out-liers to this apparent lake cycle are three of the highest-elevation samples at different sample

localities, which have discordant ages of 8.58 ± 0.07, 16.00 ± 0.16, and 25.31 ± 0.30 ka cal. Of these three samples, the lowest-elevation sample recorded an age of 16.00 ± 0.16 ka cal., which is potentially compatible with lower-ele-vation samples.

Comparison of Radiocarbon and 230Th-U Geochronology

Other studies attempting to reconcile radio-carbon and 230Th-U ages in lacustrine carbon-ates, particularly tufa samples, have considered the limitations of both methods (Lin et al., 1996; Placzek et al., 2006a; Kurth et al., 2011; Zim-merman et al., 2012). The Surprise Valley water-shed, unlike many other watersheds containing late Pleistocene lakes, drains primarily basaltic bedrock and contains no substantial carbon-ate sediments (Egger and Miller, 2011). Thus,

radiocarbon dates are unlikely to be affected by dead carbon incorporation. For the samples dated in this study, with ages three to fi ve times the radiocarbon half-life of 5.73 k.y., modern contamination of 5% can impact the calculated age by as much as 7 k.y. (cf. Cassata et al., 2010, fi g. 4). Open-system behavior in the uranium system, typically a result of U-loss due to the preferential solubility of U relative to Th, results in an anomalously high (230Th/238U) and an older apparent age (cf. Kurth et al., 2011).

Eleven group 1 and 2 samples dated using both radiocarbon and 230Th-U demonstrate acceptable agreement (Figs. 5C and 5D). Seven of the 11 sample ages (Rosholt 230Th-U ages) are concordant between the two methods, and the remaining four 230Th-U ages are on average 3.19 k.y. older (Fig. 5C). Previous studies on other paleolakes have also observed that a majority of

LGMHS1B-AYD

MIS 2 MIS 3MIS 1 / Holocene

A

B Calculated Precipitation Increase

(Isotope Model)

14C Ages

“Rosholt” 230Th-U Ages

SS Detrital Th Corrected Ages

No Fill - Rejected Datapoint

14C Derived Hydrograph

Age Envelope

Basin Pour Point

Modern Playa Minimum

Cooks Canyon lacustrine sediments

(Personius et al., 2009)

Playa Prehistoric Settlements

(~0.5 to 6 ka)

Trego Hot Spring tephra

moderate to deep water

deposition (Hedel, 1980; 1984)

Cooks Canyon subaerial sediments(Personius et al., 2009)

Pre

cip

ita

tio

n (

% M

od

ern

)

0

20

40

60

80

Ele

va

tio

n (

m)

1400

1500

1600

Age (ka)0 5 10 15 20 25 30 35

Figure 7. (A) Hydrograph for the latest pluvial cycle of Lake Surprise. The gray error envelope bounds all sample ages with elevations <1531 m; the gray line relies on radiocarbon ages only. Dashed lines are tentative correlations. Other constraints include moderate- to deep-water deposition of the Trego Hot Spring tephra at 1378 m (Hedel, 1980, 1984), Cooks Canyon deltaic lacustrine and subaerial sediments deposited at 1493 m (Personius et al., 2009), and playa prehistoric settlements (O’Connell and Inoway, 1994). See Figure 2A for the location of the additional lake-level constraints. (B) Calculated precipitation increase (% modern) from the isotope mass balance model. See Tables 7 and 8 for assumptions and calculations. MIS—marine oxygen isotope stage; YD—Younger Dryas; B-A—Bølling-Allerød; HS1—Heinrich Stadial 1; LGM—Last Glacial Maximum.


Ibarra et al.


samples dated using both methods, while falling close to the 1:1 concordant line, have slightly older 230Th-U ages (e.g., Kaufman and Broecker, 1965; Placzek et al., 2006a; Blard et al., 2011). Given these constraints, for samples dated by both methods, we consider the radiocarbon ages with discordant 230Th-U ages as minimum ages and the 230Th-U ages as maximum ages.

The only signifi cant outlier from the lower-elevation group 1 and 2 samples is SVDI12-T5. This tufa sample, formed on vesicular basalt bedrock, has a signifi cantly younger radiocarbon age of 10.69 ± 0.11 ka cal., compared to concor-dant 230Th-U ages of 22.87 ± 4.17 ka (Rosholt age) and 24.91 ± 3.10 ka (single-sample age). This suggests either an insuffi cient detrital Th correction or modern contamination of the carbonate sample. The only concordant group 3 sample age is the single-sample average of SVDI11-T18, with a radiocarbon age of 16.00 ± 0.18 ka cal. and a 230Th-U age of 15.41 ± 5.85 ka; however, the single-sample ages range from 6.30 to 20.74 ka. We reject both the radiocarbon and 230Th-U ages from this sample based on the δ18O, δ13C, Sr/Ca, and (234U/238U)0 values, which col-lectively suggest open-system behavior due to recrystallization or pedogenic overprinting.

Taking the 11 accepted radiocarbon ages as the “true” age of the samples also allows for a comparison between the ages calculated using isochron and single-sample methods (Fig. 5B). Single-sample 230Th-U ages are on average 0.80 k.y. older than the radiocarbon ages and are closer than the Rosholt 230Th-U isochron ages, which are 1.18 k.y. older. The single-sample detrital correction method only corrects the (230Th/238U) ratio (using Eq. 3), whereas Rosholt 230Th-U isochrons also correct the (234U/238U) of the authigenic carbonate (cf. Ku, 2000). Although the correction of the (234U/238U) of the authigenic carbonate is negligible at the young age range of these samples, we consider the Rosholt 230Th-U isochron ages as the most accurate 230Th-U ages of the samples, because this method corrects both the U and Th ratios of the authigenic carbonate for detritus. Addi-tionally, depending on the (232Th/238U) ratio of a given subsample, the age error of the single-sample error-weighted 230Th-U ages will vary signifi cantly. Because we observe concor-dance between the Rosholt isochron and error-weighted averages of the single-sample 230Th-U ages (Fig. 5B), we consider the single-sample 230Th-U ages as valid supporting ages in the hydrograph construction.

Older Pre-LGM Ages from High ShorelinesTwo samples from the highest shoreline

elevations and the Upper Lake shoreline set (Fig. 2) record ages that may be from past

pluvial lake cycles; however, both samples recorded (234U/238U)0 less than the range of mod-ern water and playa samples. A single-sample age from a group 3 sample at 1542.3 m yielded an early MIS 4 age of 70.37 ± 1.55 ka. Addi-tionally, one subsample of SVDI12-T18b at 1564.2 m recorded an early MIS 5 age of 115.92 ± 6.44 ka. This age is questionable, as the other subsample yields an incalculable age, presum-ably due to U loss. Uranium loss is evidenced by a much lower U concentration relative to the 115.92 ± 6.44 ka subsample (417 vs. 2544 ppb), and an anomalously high (230Th/238U) of 2.277. This open-system behavior is further refl ected in a discordant radiocarbon age of 25.31 ± 0.30 ka cal. While inconclusive, these two samples may record a higher, older lake cycle(s) in Surprise Valley, similar to those found in other Basin and Range lake systems, corresponding to MIS 4 or MIS 6 (Reheis, 1999b; Kurth et al., 2011).

Lake Surprise Hydrograph

To construct the Lake Surprise hydrograph, we used only ages obtained from lower and middle elevations and plotted calibrated radio-carbon ages, single-sample 230Th-U ages, and Rosholt isochron 230Th-U ages against the LiDAR-derived sample elevations (Fig. 7A). We connected radiocarbon ages assuming that a given sample records the minimum lake-water level (e.g., Felton et al., 2006; Benson et al., 1996). For samples of statistically equivalent ages, the sample at higher elevation was taken as the likely lake level, rather than recording higher-frequency fl uctuations. In addition to the radiocarbon hydrograph, we constructed an age envelope of all available ages from samples <1531 m (Fig. 7A). Based on the radiogenic and stable isotopic evidence presented here, we have concluded that Lake Surprise lake levels reached 1531 m (a water depth of 176 m) at 15.19 ± 0.18 ka cal. (radiocarbon age) during the latest Pleistocene (Fig. 7A). This highstand age is supported by a concordant, but signifi -cantly older, 230Th-U isochron age of 18.25 ± 2.67 ka (Rosholt age). At higher elevations, one sample (SVDI11-T18) suggests that Lake Sur-prise may have briefl y reached 1555 m at 16.00 ± 0.18 ka cal. (radiocarbon age), although stable isotope, Sr/Ca, and (234U/238U)0 evidence sug-gests that this age may be in error due to calcite recrystallization causing open-system behavior.

Our results correlate well with the limited previous studies (Table DR1 [see footnote 1]) and help to clarify some ambiguous relation-ships. An infrared-stimulated luminescence (IRSL) age on feldspar grains constraining the older age range of the deltaic deposits from Personius et al. (2009) appears to be too old

(28.08 ± 4.44 ka), as originally suspected by the authors, due to potential contamination. How-ever, the younger age of 18.40 ± 3.17 ka of the deltaic sediments, using a weighted mean of the optically stimulated luminescence (OSL) and IRSL ages (Personius et al., 2009), agrees well with the constructed lake-level curve. Finally, three of four subaerial ages from Personius et al. (2009) are much younger than the proposed lake level at that elevation (1475 m); however, the oldest subaerial age, 13.38 ± 2.64 ka, is within error of the plotted radiocarbon- and 230Th-U–based hydrographs during the deglacial lake-level recession. All other previous constraints on Lake Surprise lake level are consistent with the constructed hydrograph plotted in Figure 7A.

DISCUSSION

In the following discussion, we examine the new Lake Surprise hydrograph of Figure 7A and explore the implications for western United States paleoclimatology during the late Pleisto-cene. Our key results are: (1) The Lake Surprise watershed remained a closed, inward-draining basin throughout the last glacial cycle with lateral correspondence found among samples from the four shoreline localities based on topo-graphic analysis, δ18O-δ13C-Sr/Ca covariance, and concordant geochronology; (2) the new lake hydrograph is in agreement with previous lake-level constraints and places the highest lake level ~176 m above modern playa at 15.19 ± 0.18 ka cal. and during the LGM ~80 m above modern playa; and (3) multiple lines of evidence reveal that samples from the highest shorelines are likely from older, higher lake cycles and were infl uenced by variable amounts of open-system exchange or pedogenic overprinting. Using these results, we modify an existing δ18O isotope mass balance model by including basin geometry to assess hydrologic controls on Lake Surprise lake levels and compare the calculated changes in precipitation (Fig. 7B) to climate models from the PMIP3 climate model ensemble (Fig. 8).

Hydrologic Controls on Lake Surprise Lake Levels

A description of the changes in atmospheric circulation patterns and the seasonal role of solar insolation in regional climate during the last deglaciation requires quantitative predic-tions of meteorologic and hydrologic processes. We incorporate the Lake Surprise hydrograph, the stable isotope analyses, and the topographic analysis of the basin geometry into two models that enable us to estimate past changes in pre-cipitation and evaporation: hydrologic index and isotope mass balance.




Hydrologic Index CalculationsThe “pluvial hydrologic index” (HI), origi-

nally derived by Miffl in and Wheat (1979), is a measure of the ratio of lake surface area to tribu-tary area given an equilibrium (steady-state) lake level, whereby moisture into the lake equals moisture out of the lake. It has been used in vari-ous forms (e.g., Hostetler and Benson, 1990; Reheis, 1999b) to solve for the ratio of runoff to evaporation using paleohydrologic constraints derived from related landforms (e.g., wave-cut shorelines, beaches, strandlines). Based only on mass balance, the dimensionless hydrologic index (HI) is (Miffl in and Wheat, 1979):

HIA

A

A

A A

R

E P

P ET

E PL

T

L

B L

T

L L

T T

L L

= =−

=−

= −−

, (4)

where AL, AB, and AT are the areas of the lake, basin, and tributary (AT = AB – AL), P is the aver-age on-lake (subscript L) and tributary (subscript T) precipitation, EL is the gross lake evaporation, ETT is the average tributary evapotranspiration, and RT is the combined surface and ground water runoff, where RT = PT – ETT. We computed the HI from AL/AT (1) the range of LGM stillstands (1420–1440 m), (2) the post-LGM highstand (1531 m), and (3) the pre–MIS 2 (possibly

MIS 6) highstand (1567 m) (Table 2). Modern weather station data ([PT – ETT]/[EL – PL]) and modern maximum lake levels (AL/AT) indicate that the modern HI equals 0.11 and 0.12, respec-tively. Quantifying these variables in the past, particularly tributary evapotranspiration (ETT), requires calibration using modern meteorologi-cal observations (Miffl in and Wheat, 1979). Dur-ing the LGM stillstands, HI was almost 300% of modern, with values of 0.29–0.34. At the post-LGM deglacial highstand, the HI was 0.56. The calculated HI values are consistent with other nearby lake systems evaluated by Miffl in and Wheat (1979) in south-central Oregon and north-western Nevada and provide a useful framework with which to constrain changes in precipitation, evaporation, and temperature during the LGM.

Isotope Mass Balance CalculationsThe stable isotope mass balance provides a

complementary method to the HI calculations for determining basin average changes in pre-cipitation. We modifi ed the isotope mass bal-ance model of Jones et al. (2007), which was developed for similar steady-state midlatitude lake systems in Turkey (Jones et al., 2007; Jones and Imbers, 2010). We then incorporated the basin geometry (i.e., lake surface area and tribu-tary area), derived from the ArcGIS analysis, to calculate changes in precipitation, relative to modern, at the LGM and post-LGM highstand.

The time-varying (t) water balance and iso-topic mass balance for a lake, assuming ground-water fl ux across the sediment-water interface is negligible, can be described by two equations. The fi rst describes the change in lake volume (VL; modifi ed from Jones et al., 2007; Jones and Imbers, 2010; Steinman et al., 2013):

dV

dtQ Q QL

p r e= + − , (5)

where Q is the input and output fl uxes, and sub-scripts correspond to on-lake precipitation (p), runoff (r), and lake surface evaporation (e). The isotopic mass balance is similarly described as (modifi ed from Benson and Paillet, 2002; Jones et al., 2007; Jones and Imbers, 2010; Doebbert et al., 2010; Steinman et al., 2013):

d O V

dtO QL L

p p

( )( )

δ δ18

18× = × +

O Q O Qr r e e( ) ( ),δ δ18 18× − × (6)

where subscripts also apply to the δ18O of the input and output fl uxes. We simplifi ed Equation 5 by combining precipitation and runoff into the total surface and subsurface inputs (Qw) multi-plied by the isotopic composition, δ18Ow. Apply-ing the chain rule to Equation 6 yields:

Figure 8. Last Glacial Maximum (LGM) isotope mass balance–calculated precipitation (A) and lake evaporation (B), and the PMIP3 climate model ensemble predictions for Lake Surprise. The values derived by this study are compared to literature values derived using a mass balance model (Miffl in and Wheat, 1979), a thermal evaporation model (Hostetler and Benson, 1990) for Lake Lahontan, and a hydrologic model (Matsubara and Howard, 2009) for the Great Basin. Individual climate model predictions are presented as black dots and a box-and-whisker plot (Table DR6 [see text footnote 1]). PMIP3 climate model output is total evaporation, calculated from the surface latent heat fl ux. Isotope mass balance calculations from all LGM samples are presented as a box-and-whisker plot (Table 8). Lake evapora-tion is calculated using the equations of Linacre (1992) and Jones et al. (2007). See Figure DR7 (text footnote 1) for the isotope calculation’s sensitivity to relative humidity, assumed change in temperature, average wind speed, and input δ18O (runoff and precipitation). The black and white bars indicate the range of predicted values by the literature.

-20

0

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-50

-40

-30

-20

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(Isot

ope

Mod

el)

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IP 3

Ens

emble

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prise

Valley

Mifflin

and

Whe

at (1

979)

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Lah

onta

n

Hos

tetle

r and

Ben

son

(199

0)

Lake

Lah

onta

n

Mat

suba

ra a

nd H

owar

d (2

009)

Gre

at B

asin S

urpr

ise

Valley

(Isot

ope

Mod

el)

PM

IP 3

Ens

emble

Sur

prise

Valley

(Tot

al E

vapo

ratio

n)

Mifflin

and

Whe

at (1

979)

Lake

Lah

onta

n

Hos

tetle

r and

Ben

son

(199

0)

Lake

Lah

onta

n

Mat

suba

ra a

nd H

owar

d (2

009)

Gre

at B

asin

Pre

cip

ita

tio

n (

% M

od

ern

)

La

ke

Eva

po

ratio

n (

% M

od

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)

A B


Ibarra et al.


Vd O

dtO

dV

dtLL

LLδ δ

1818+ =

O Q O Qw w e eδ δ18 18× − ×( ) ( ). (7)

By substituting Equation 5 into Equation 7 and rearranging, we fi nd an expression for time-varying changes in δ18OL:

Vd O

dtO O QL

Lw L w

δ δ δ18

18 18= − × −(( ) )

O O Qe L eδ δ18 18− ×(( ) ). (8)

Since Qe = ALEL, and assuming that for a given lake level, recorded in the isotopic com-position and altitude of a tufa sample, dδ18OL/dt = 0, solving for Qw yields an expression for the volumetric fl ux of moisture into the lake:

QA E O O

O OwL L e L

w L

= × −−

( )

( )

δ δδ δ

18 18

18 18 . (9)

Using the methods and assumptions outlined in Jones et al. (2007), we calculated δ18Oe and

EL using the equations of Benson and White (1994) for δ18Oe and the evaporation model of Linacre (1992) for EL (see Table 7 for details). The value for δ18OL was derived from the mea-sured tufa samples (Table 3) and converted using the temperature-dependent water-calcite fractionation factor (Table 7; Kim and O’Neil, 1997). Given the calculation for the total water input fl ux, Qw, PL was calculated according to mass balance (Qw = [PL × AL] + [RT × AT]) assuming that RT is 0.15 × PL. Integrated water-shed modeling of the Lake Estancia basin, New Mexico, during the LGM, assuming a colder and wetter climate, suggests that annual runoff (RT) was 15% of precipitation (PL) (Menking et al., 2004). No stream gauges have been histori-cally recorded in Surprise Valley, but analysis of annual stream discharge data (1949–2012) from the nearest gauge maintained by the USGS on the South Fork of the Pit River, indicates that the modern runoff coeffi cient is 16.9% ± 2.6% (2σ, n = 56 yr; http:// waterdata .usgs .gov /usa /nwis /rt; see Data Repository [footnote 1] for additional details).

Despite increasing the potential unknowns, the isotope model allows for an explicit solu-tion to a steady-state isotope mass balance for the lake input fl uxes (Eq. 9) while also consid-ering basin geometry (AL and AT). Additionally, we can account for temperature and evaporation processes while solving for the basin average precipitation.

Calculating Late Pleistocene Precipitation Amounts for Lake Surprise

To calculate precipitation changes during the LGM and the post-LGM highstand, we applied the hydrologic index (Eq. 4) and our isotope mass balance model (Eqs. 5–9). Our isotope mass balance model also incorporates lake surface area within a basin of fi xed total area, thereby decreasing tributary area with increas-ing lake surface area and sample altitude (Fig. DR1 [see footnote 1]). The key parameters used to calculate changes in precipitation are: tem-perature (T), lake hypsometry (AL), watershed geometry (AT), δ18OL (from δ18Ocalcite), δ18Oe, δ18Ow, relative humidity (Hr), and lake surface evaporation rate (EL) (see Table 7 for all val-ues and related equations). We assumed that local temperatures were uniformly 7 °C lower during the LGM and 5 °C lower during the deglacial period, based on pollen assemblages at nearby Little Lake, Oregon (Fig. 1; Worona and Whitlock, 1995). We assumed that tem-perature changes were uniform among seasons (Jones et al., 2007). The δ18OL was calculated for each sample using the calcite-water frac-tionation, αw-c, of Kim and O’Neil (1997). The δ18Ow was assumed to be the average of mod-ern creek waters (δ18OL = −14.57‰ relative to Vienna Standard Mean Ocean Water [VSMOW]; Table DR3 [see footnote 1]). Calculation of δ18Oe assumed (1) a kinetic fractionation factor, αkin, for wind speeds <6.8 m/s of αkin = 0.994 (modern average wind speeds are 1.9 m/s), (2) the fraction of atmospheric vapor in the lake boundary layer equal to zero (Benson and White, 1994; Jones et al., 2007), (3) no change in Hr from modern values, and (4) a tempera-ture-dependent equilibrium fractionation factor, αeq (Majoube, 1971). Lake surface evaporation rate was calculated using temperature, latitude, lake surface altitude (sample altitude), and modern average wind speed. Jones et al. (2007) noted that for similar midlatitude lakes during the LGM, the combined temperature and ice-volume effects on incoming precipitation δ18O would only be between −0.5‰ and +1‰. Thus, the δ18OW (the δ18O of runoff and precipitation) was held as the average of measured literature values from Surprise Valley (Table 7; Table DR3 [see footnote 1]; Ingraham and Taylor, 1989; Sladek et al., 2004).

TABLE 7. ISOTOPE MODEL PARAMETER VALUES

eulaVnoitpircseDsretemaraP

T Temperature (°C) Modern = 9.2, LGM = 2.2, post-LGM = 4.2, based on Worona and Whitlock (1995)

PL Precipitation (L, lake) (mm/yr) Modern = 566 mm/yr (solved by model)RT Runoff (surface + subsurface)

(mm/yr)Unknown (assumed 0.15 × PT , based on Menking et al., 2004)

Hr Relative humidity Unknown (modern = 0.57%)EL Lake surface evaporation rate

(mm/yr)Linacre (1992) based on T, latitude (41.5°N), lake surface

altitude, and wind speed (modern = 1.9 m/s)*

AL Lake area (km2) Varies with lake surface level, based on modern topography, calculated using fi fth-order polynomial fi t through results of DEM analysis†

AB Basin area (km2) 3812 km2 based on modern topography (DEM analysis)AT Tributary area (km2) AT = AB – AL

δ18OL Lake water δ18O Calculated using αw-c at given T from tufa sample measurements

δ18Ow Input fl uxes (precipitation + runoff) δ18O

–14.57‰ (VSMOW, modern creek average; Table DR3 [see text footnote 1])

δ18Oe Evaporation δ18O Benson and White (1994) assuming fraction of atmospheric water vapor in lake boundary layer, fad, is negligible (fad = 0)§

Qw Total input fl ux Qp + Qr

Qp Lake surface precipitation fl ux PL × AL

Qr Runoff fl ux RT × AT

Qe Evaporation fl ux EL × AL

αw-c Calcite-water fractionation Kim and O’Neil (1997)#

αkin Kinetic evaporation fractionation

0.994 for wind speeds <6.8 m/s (Majoube, 1971)

αeq Equilibrium evaporation fractionation

Majoube (1971)**

Note: LGM—Last Glacial Maximum; DEM—digital elevation model; VSMOW—Vienna Standard Mean Ocean Water.

*EL = [0.015 + 4 × 10–4T + 10–6z] × [480(T + 0.006z)/(84 − Lat) − 40 + 2.3u(T − Td)], where T is mean annual temperature, z is lake altitude (meters a.s.l.), u is wind speed, Lat is latitude, and Td is dew point temperature. Td(°C) is calculated as: Td = 0.52 × Tmin + 0.6 × Tmax − (0.009 × [Tmax]

2) − 2. Tmin and Tmax are assumed to uniformly shift by the same magnitude as mean annual temperature (T) (Linacre, 1992; Jones et al., 2007).

†AL = (–25.028) + (44.127 × hL) + ([–1.0357] × hL2) + (0.013333 × hL

3) + ([–0.000088611] × hL4) +

(0.00000029112 × hL5) + ([–0.00000000037455] × hL

6), where hL = lake-surface altitude (altitude – 1355 m). §δ18Oe = (Revap − 1) × 1000, where Revap = Rlake × (αkin/αeq) × (1/[1 − Hr + {Hr × αkin}]) and Rlake = (δ18OL/1000) + 1

(Benson and White, 1994).#1000 × ln(αcalcite-water) = 18.03 × (103 × T–1) − 32.42. T in Kelvin, assumed to be average summer temperature

uniformly shifted by the same magnitude as mean annual temperature (T) (Kim and O’Neil, 1997).**αeq = exp(1137 × T–2 − 0.4156 × T–1 − 0.0020667). T in Kelvin (Majoube, 1971).




Solving Equations 4 and 9 allows us to calcu-late the absolute and percent change in precipi-tation for each LGM and post-LGM tufa sample δ18O measurement, given the associated lake surface altitude and lake surface area for each sample (Table 8; Fig. 7B). Sensitivity analy-sis presented in Figure DR7 (see footnote 1) demonstrates that the isotope model is most sensitive to the prescribed temperature anoma-lies and runoff coeffi cient. With an increased temperature anomaly, the calculated precipita-tion amounts would decrease. Similarly, with an increased runoff coeffi cient, due to colder temperatures and/or increased spring snowmelt, the calculated precipitation amounts would also decrease (see Data Repository [footnote 1]).

At the lake highstand, the HI calculation pre-dicts an 85.1% increase in precipitation rela-tive to modern, greater than the isotope mass balance model, which predicts a 75% increase (Table 8). This HI-derived value for the Lake Surprise highstand is similar to those calcu-lated by Reheis (1999b) for other proximal lake systems, and Miffl in and Wheat’s (1979) prediction of a 77.1% increase for south-cen-tral Oregon and northwestern Nevada (Table 2). At the LGM, the HI calculation predicts a 53% increase in precipitation compared to 10% increase predicted by the isotope mass balance calculations (Table 8; Figs. 7B and 8). The primary difference between the two models is because the isotope mass balance calculations allow for sensitivity to changes in humidity and temperature (see equations in Table 7). As a result, the ratio of lake precipitation and run-off to net lake surface evaporation, Qw/Qe, is >1. Despite the potential uncertainties in the model parameters in Table 7 and the sensitivity analy-sis in Figure DR7 (see footnote 1), we regard the isotope mass balance calculations as the most accurate estimate of precipitation change at the LGM and post-LGM highstand because the stable isotope values allow for the inclusion of processes that are dependent on temperature and evaporation rate (Table 7). These processes are the evaporation model (Linacre, 1992), and isotope fractionation equations (Majoube, 1971; Benson and White, 1994; Kim and O’Neil, 1997) as assembled by Jones et al. (2007).

Our calculated changes in precipitation for Surprise Valley are on the lower end of the range of estimates for nearby Lake Lahontan (Fig. 8; Miffl in and Wheat, 1979; Hostetler and Benson, 1990) and for the Basin and Range (Matsubara and Howard, 2009, their Table 1; Menking et al., 2004). This result suggests that decreases in sum-mer evaporation (36.4% annual decrease at the LGM; Table 8; Fig. 8B) may have played a major role in driving and sustaining lake levels in the northern Basin and Range during the late LGM.

TAB

LE 8

. HY

DR

OLO

GIC

IND

EX

(H

I) A

ND

ISO

TO

PE

MA

SS

BA

LAN

CE

CA

LCU

LAT

ION

S

noitaluclacecnalab

ssam

epotosI*noita lucl ac

) IH (

xe dnici gol ordy

H†

Sam

ple

Lake

leve

l al

titud

e(m

a.s

.l.)

Wat

er

dept

h(m

)

Sur

face

ar

ea(k

m2 )

Trib

utar

y ar

ea(k

m2 )

Hyd

rolo

gic

inde

xP

reci

pita

tion

(mm

/yr)

Δ P

(%)

δ18O

calc

ite(‰

, VP

DB

)δ18

OL

(‰, V

SM

OW

)La

ke

evap

orat

ion

(mm

/yr)

δ18O

e(‰

, VS

MO

W)

Qw

(m3 /

yr)

Pre

cipi

tatio

n(m

m/y

r)Δ

P(%

)

LGM

sam

ples

SV

DI1

1-T

2-1

1453

.598

.510

3127

810.

371

917.

562

–3.1

23–3

.448

585.

5–2

0.64

9328

0469

064

4.2

14S

VD

I11-

T2–

214

53.5

98.5

1031

2781

0.37

191

7.5

62–3

.385

–3.7

1058

5.5

–20.

9095

5057

055

659.

617

SV

DI1

1-T

3-1a

1437

.782

.794

428

680.

329

879.

155

–4.0

45–4

.369

578.

1–2

1.54

9185

0832

466

8.6

18S

VD

I11-

T3–

214

37.7

82.7

944

2868

0.32

987

9.1

55–2

.988

–3.3

1357

8.1

–20.

5183

3179

570

606.

57

SV

DI1

1-T

4-1a

1430

.675

.690

729

050.

312

861.

952

–3.2

38–3

.563

574.

9–2

0.75

8142

9016

560

6.5

7S

VD

I11-

T4-

1b14

30.6

75.6

907

2905

0.31

286

1.9

52–3

.225

–3.5

5057

4.9

–20.

7481

3284

920

605.

77

SV

DI1

2-T

114

19.5

64.5

854

2957

0.28

983

5.8

48–3

.696

–4.0

2056

9.7

–21.

2079

2886

253

610.

88

SV

DI1

2-T

2a14

19.5

64.5

854

2957

0.28

983

5.8

48–3

.491

–3.8

1656

9.7

–21.

0077

7951

961

599.

36

SV

DI1

2-T

2b14

19.5

64.5

854

2957

0.28

983

5.8

48–3

.472

–3.7

9656

9.7

–20.

9877

6575

497

598.

36

SV

DI1

2-T

2c14

19.5

64.5

854

2957

0.28

983

5.8

48–3

.124

–3.4

4956

9.7

–20.

6475

2560

774

579.

82

SV

DI1

2-T

3a14

27.8

72.8

893

2918

0.30

685

5.2

51–3

.460

–3.7

8557

3.6

–20.

9781

6361

203

613.

38

SV

DI1

2-T

3b14

27.8

72.8

893

2918

0.30

685

5.2

51–3

.457

–3.7

8257

3.6

–20.

9781

6126

318

613.

28

SV

DI1

2-T

4a14

3984

950

2861

0.33

288

2.2

56–3

.827

–4.1

5257

8.7

–21.

3390

7069

092

657.

516

SV

DI1

2-T

4b14

3984

950

2861

0.33

288

2.2

56–3

.511

–3.8

3657

8.7

–21.

0288

0661

324

638.

313

SV

DI1

2-T

1314

37.2

82.2

941

2871

0.32

887

7.8

55–3

.343

–3.6

6857

7.9

–20.

8685

7278

731

625.

110

SV

DI1

2-T

1514

33.1

78.1

920

2892

0.31

886

7.9

53–3

.089

–3.4

1457

6.0

–20.

6181

6317

153

603.

17

SV

DI1

2-T

1514

33.1

78.1

920

2892

0.31

886

7.9

53–3

.129

–3.4

5457

6.0

–20.

6581

9220

785

605.

37

LG

M a

vera

ge

pre

cip

(H

I):

867.

653

LG

M a

vera

ge

lake

eva

p

(iso

top

e m

od

el):

575.

9L

GM

ave

rag

e p

reci

p

(iso

top

e m

od

el):

619.

710

Pos

t-LG

M s

ampl

esS

VD

I12-

T7

1472

.511

7.5

1134

2678

0.42

495

9.6

70–3

.463

–3.3

5077

6–2

0.34

1332

5617

4686

7.7

53S

VD

I12-

T7

1472

.511

7.5

1134

2678

0.42

495

9.6

70–3

.789

–3.6

7577

6–2

0.66

1371

9199

1289

3.3

58S

VD

I11-

T14

-1a

1478

.412

3.4

1163

2648

0.43

997

1.2

72–2

.501

–2.3

8777

9–1

9.40

1264

8569

8381

0.5

43S

VD

I11-

T14

-1c

1478

.412

3.4

1163

2648

0.43

997

1.2

72–2

.851

–2.7

3777

9–1

9.74

1301

7999

2983

4.1

47S

VD

I12-

T9

1508

.915

3.9

1284

2528

0.50

810

19.0

80–3

.587

–3.4

7379

4–2

0.46

1560

3529

6293

8.3

66S

VD

I12-

T9

1508

.915

3.9

1284

2528

0.50

810

19.0

80–3

.465

–3.3

5279

4–2

0.34

1543

6465

8092

8.2

64S

VD

I12-

T10

a15

16.8

161.

813

0925

030.

523

1029

.382

–3.5

52–3

.438

798

–20.

4315

9390

1125

946.

267

SV

DI1

2-T

10b

1516

.816

1.8

1309

2503

0.52

310

29.3

82–3

.538

–3.4

2479

8–2

0.42

1591

9213

5794

5.0

67S

VD

I12-

T14

1530

.717

5.7

1354

2458

0.55

110

47.2

85–3

.846

–3.7

3380

5–2

0.72

1089

3074

8399

1.1

75S

VD

I12-

T14

1530

.717

5.7

1354

2458

0.

551

1047

.285

–3

.844

–3.7

3080

5–2

0.72

1089

3074

8399

0.9

75

Not

e: L

GM

—La

st G

laci

al M

axim

um; V

PD

B—

Vie

nna

Pee

Dee

Bel

emni

te; V

SM

OW

—V

ienn

a S

tand

ard

Mea

n O

cean

Wat

er.

*Ass

umes

no

chan

ge in

tem

pera

ture

or

hum

idity

rel

ativ

e to

mod

ern

valu

es.

† See

Tab

le 7

for

isot

ope

mas

s ba

lanc

e ca

lcul

atio

n as

sum

ptio

ns a

nd e

quat

ions

.


Ibarra et al.


Previous investigations have proposed that the primary driver of maximum LGM and post-LGM pluvial lake levels was increased precipi-tation (Thompson et al., 1999; Menking et al., 2004; Lyle et al., 2012). Menking et al. (2004) modeled Lake Estancia (34.6°N) and proposed that precipitation was doubled during Estancia’s LGM highstands. During the Surprise Valley post-LGM highstand, we fi nd that precipitation may have increased by up to 75% (Fig. 7B). Our combined results bracket the “mean position” of the polar jet stream and midlatitude storm tracks to the southern Basin and Range (~35°N) during the LGM and to the northern Basin and Range (~41°N) during the late HS1, as proposed by Munroe and Laabs (2012).

Comparison of Precipitation Estimates to Climate Model Predictions

Evaluation of PMIP3 climate models against paleoclimate data provides an important oppor-tunity to test climate models at mean states very different than modern conditions. The direct comparison between climate models and climate records aids in understanding both the past and future regional sensitivity to changing climatic conditions (Braconnot et al., 2012; DiNezio and Tierney, 2013; Hargreaves et al., 2013).

The LGM precipitation anomaly varies widely among the PMIP3 ensemble members in both magnitude and direction of change (Table DR6 [see footnote 1]). Eight of the nine climate models reproduce the modern seasonal precipitation patterns observed at the three meteorological stations in Surprise Val-ley, while most overpredict absolute precipita-tion amount (Figs. DR8 and DR11 [see foot-note 1]). All nine models suggest that the winter contribution to total annual rainfall decreased during the LGM (Fig. 9; Figs. DR8 and DR11 [see footnote 1]). The results of the AOGCM analysis demonstrate a PMIP3 ensemble aver-age increase of 6.5% LGM precipitation rela-tive to modern, ranging from −14.5% to 50.3% (Fig. 8A; Table DR6 [see footnote 1]). This is compara ble to the isotope mass balance calcula-tions, which estimate a 10% increase. The pre-dicted total evaporation, a variable parameter-ized from the surface latent heat fl ux by climate models, is predicted to decrease by an ensemble average of 28.2% at the LGM (Fig. 8B; Fig. DR12 [see footnote 1]). While not equivalent to lake surface evaporation rate (EL), these val-ues agree with the 36% decrease in evaporation rate estimated for Lake Surprise at the LGM. Among the PMIP3 ensembles, the mean annual temperature LGM anomaly is −7.0 °C (Table DR6; Fig. DR10 [see footnote 1]), which is the same value used in the isotope mass bal-ance model and predicted by the nearby pollen

record (Worona and Whitlock, 1995). Addition-ally, the assumption of a uniform temperature anomaly is supported by the climate models, which on average demonstrate a minimal range of variation in the monthly temperature anoma-lies of between −6.0 °C and −8.0 °C (Fig. DR10 [see footnote 1]). Corroborating evidence for the importance of temperature on basin hydrol-ogy is the seasonality of peak subsurface and surface runoff predicted by the PMIP3 ensem-ble. Runoff, which is coupled to precipitation in modern times, is shifted from late winter–early spring in modern time to the late spring–early summer during the LGM (Fig. 9; Fig. DR9 [see footnote 1]). Finally, the PMIP3 ensemble sup-ports our assumption used in the isotope mass balance calculations that relative humidity has not changed dramatically since the LGM (only a 4.1% increase).

The climate models and isotope mass balance models presented here provide a framework for investigating whether wetter or cooler condi-tions (or a balance of the two) drove pluvial lake evolution during the LGM and deglaciation. Based on our analysis, moderate LGM lake levels at Lake Surprise were driven primarily by reduced temperatures and resultant reduced summer lake evaporation, with a minimal pre-cipitation increase of 10% relative to modern. Following moderate LGM lake levels, Lake Surprise lake levels responded rapidly to a

75% increase in precipitation during late HS1. Given the range of uncertainty in some of the input parameters used in the isotope mass bal-ance calculations (see Fig. DR7 for the sensitiv-ity analy sis of precipitation increase to RH, T, δ18OW, runoff coeffi cient, and wind speed [see footnote 1]), and the coarse scale of the climate models (~0.75° to 2° horizontal resolution; Figs. DR11 and DR12 [see footnote 1]), further con-straints and/or modeling approaches are neces-sary to fully assess model bias.

Regional Implications of the Latest Pleistocene Lake Surprise Lake Levels

During the LGM, Lake Surprise stood at moderate lake levels (65–99 m depth), similar to Lake Lahontan (Benson et al., 1995; Adams et al., 2008), with an HI of 0.29–0.34 covering 62%–72% of the ultimate highstand surface area (Table 2). During HS1, Lake Surprise rose to the highest latest Pleistocene lake level (176 m depth), peaking at 15.19 ± 0.18 ka cal. (radio-carbon age). The HI increased by 39% to 0.56, with Lake Surprise covering 36% of the termi-nally draining watershed. The lack of substan-tial carbonate deposition and shoreline develop-ment (relative to LGM shorelines) suggests this highstand was apparently brief. Additionally, Sr/Ca ratios of the post-LGM samples are very similar to LGM samples, suggesting that dilute

Pre

cip

ita

tio

n (

% A

nn

ua

l)

Ru

no

ff (

% A

nn

ua

l)

Jan March May July Sept NovJan March May July Sept Nov

Surprise Valley Meteorological DataPMIP3 Ensemble 0 kaPMIP3 Ensemble 21 ka (LGM)

0

5

10

15

20

25

30

0

5

10

15

20

A B

Figure 9. Seasonal precipitation and runoff predicted by the PMIP3 climate model ensem-ble. All climate models except COSMOS-ASO uniformly output both precipitation and run-off in the PMIP3 database (Table DR6 [see text footnote 1]). (A) PMIP3 ensemble average precipitation normalized to the percent of total annual precipitation for the 0 ka (preindus-trial) and 21 ka (Last Glacial Maximum [LGM]) experiments. Surprise Valley meteorologi-cal data are the average of three weather stations (Fig. 2A). Climate models suggest that the seasonality of precipitation during the LGM was unchanged. (B) PMIP3 ensemble average runoff (surface and subsurface) normalized to the percent of total annual runoff for the 0 ka (preindustrial) and 21 ka (LGM) experiments. Climate models suggest that temperature effects caused the decoupling of precipitation and runoff during the LGM, with peak runoff shifting to the late spring–early summer. See Figures DR8–DR12 and Table DR6 for indi-vidual climate model results (text footnote 1).




lake waters did not inhibit carbonate precipita-tion. Recession was subsequently recorded in several stillstands between 15.2 and 12.7 ka. In the following synthesis, we link our new MIS 2 Lake Surprise hydrograph (Fig. 7A), isotope mass balance precipitation calculations (Figs. 7B and 8), and PMIP3 ensemble results (Figs. 8 and 9) to regional records (Fig. 10) from the LGM through the deglaciation.

Regional lake and glacial records record the combined effects of temperature and precipita-tion during the LGM (Fig. 10). Coincident with a maximum winter insolation and a minimum summer insolation (Fig. 10C), Lake Franklin and the much larger Lake Bonneville (Fig. 1) to the east rose gradually during the LGM (Fig. 10G), although neither reached highstand levels until after the LGM (Oviatt et al., 1992; Munroe and Laabs, 2013). Similarly, Lake Surprise records a gradual transgression from 22.13 to 19.22 ka cal. At the same time, glaciers were persis-tent: Glacial activity in the southeast Cascades gradually increased through the LGM (Fig. 10F; Rosenbaum et al., 2012), two glacial advances are recorded in the Sierra Nevada (Tioga 1 and 2) at the beginning and end of the LGM (Phil-lips et al., 2009), a terminal moraine recorded an age of 20.5 ka in the Ruby Mountains (Laabs, et al., 2013), and a glacial maximum is observed at 21.6 ka in the Wallowa Mountains (Fig. 10E; Licciardi et al., 2004; radiocarbon ages recalcu-lated in Rosenbaum et al., 2012).

Decreased insolation and reduced tem-peratures would have decreased summer lake surface evaporation, decreased glacial melt/sublimation, and enhanced basin average run-off. Summer insolation at 40°N was lower than the long-term average between 27.1 and 14.5 ka (during HS1 and the late LGM), reach-ing a minimum at 20.3 ka (Fig. 10I). During the LGM, increases in regional moisture avail-ability refl ected by lake hydrographs and gla-cial growth, the absence of abrupt shifts in lake and/or glacial records, and decreasing summer insolation all suggest that reduced temperatures decreased lake surface evaporation. The results from our isotope mass balance calculations and the PMIP3 climate model support the minimal increase in precipitation (2.5%–18.2% relative to modern; Figs. 7B and 8) and reduced lake surface evaporation (~36% decrease relative to modern; Fig. 8). Such results are consistent with reduced temperatures due to lower atmospheric CO2 levels (Denton et al., 2010; Shakun et al., 2012), combined with lower summer insolation, as the key drivers for reduced evaporation and, by extension, moderate LGM lake levels (Mun-roe and Laabs, 2013; Maher et al., 2014). These conditions may have primed lake systems to respond rapidly to decreases in North Atlantic

temperatures and attendant increases in precipi-tation (Fig. 10H) during HS1.

Following the LGM, the temporal correspon-dence among highstands at Lake Surprise and other small lake systems in the western United States refl ects a shift in Northern Hemisphere midlatitude atmospheric circulation during HS1 (Fig. 10). Highstands and signifi cant stillstands of small lake systems during the latter parts of the LGM are attributed to a southward displace-ment of the mean position of the southern arm of the split PJS (Polar Jet Stream) and dipping westerlies, which would have brought more precipitation to the region (Negrini, 2002; Mun-roe and Laabs, 2012; Kirby et al., 2013). Our isotope mass balance results require that the pluvial maximum of Lake Surprise was driven by increases in precipitation (~75% increase relative to modern), confi rming that displaced midlatitude storm tracks likely drove increased lake levels during the latter part of HS1. Addi-tionally, reassessment of radiocarbon ages from highstands and signifi cant stillstands spanning 31.8°N to 45.9°N (Fig. 10J; see Table DR7 [see footnote 1]) indicates that the regional plu-vial maximum lies between ca. 17 and 15 ka, during the latter part of HS1. Prior to this and immediately following the LGM, during the early part of HS1 (ca. 19–17 ka), some authors have suggested a regional “big dry” event based on desic cation in Lake Estancia, New Mexico (Allen and Anderson, 2000), but this event is not apparent in the lakes in the northern Basin and Range (Broecker et al., 2009; Broecker and Put-nam, 2012; Munroe and Laabs, 2013).

Atmospheric forcing of precipitation in the western United States is attributed to North Atlantic cooling during HS1 (COHMAP, 1988; Zic et al., 2002; Denniston et al., 2007; Wag-ner et al., 2010; Broecker and Putnam, 2012; Munroe and Laabs, 2012; Benson et al., 1998, 2003, 2013). The proposed mechanism is the winter enhancement of the Aleutian Low via reduced tropical Atlantic precipitation (Oku-mura et al., 2009) and the suppression of the Atlantic Meridional Overturning Circulation (McManus et al., 2004; Denton et al., 2010). The lake highstand compilation of Munroe and Laabs (2012) demonstrated temporal syn-chrony between some Basin and Range lake highstands and the onset of iceberg discharge and reduced North Atlantic sea-surface tem-peratures during Heinrich Event 1 at ca. 17 ka. However, several highstands from smaller lakes near Bonneville and Lahontan postdate this period, as does the Lake Surprise highstand radiocarbon age (15.19 ± 0.18 ka cal.; Table DR7 [see footnote 1]; Fig. 10J). Northern Basin and Range highstands that postdate the appar-ent mid-HS1 maximum (ca. 17 ka) may have

instead been sustained by regional lake-atmo-sphere effects (e.g., Hostetler et al., 1994; Lic-ciardi, 2001) brought about by the much larger and longer-lasting Lahontan (highstand at 15.8 ka; Adams and Wesnousky, 1998) and Bonne-ville lake systems (recession from Provo shore-line between ca. 16 and 14.5 ka; Godsey et al., 2011; Miller et al., 2013). In addition, the lack of a signifi cant latitudinal trend in highstands and signifi cant stillstands (Fig. 10J) contrasts with the fi ndings of Lyle et al. (2012). Evidence from Lake Elsinore, California (~34°N; Kirby et al., 2013), and Cave of the Bells, Arizona (~32°N; Wagner et al., 2010), provides addi-tional support for the hypothesis that westerly, North Pacifi c moisture sources were respon-sible for post-LGM, mid- to late HS1, pluvial maxima in the interior western United States. Cumulatively, this evidence suggests a latitudi-nally broad and strengthened midlatitude west-erly storm track during HS1.

Post-LGM glacial activity also supports these conclusions. Although the Laurentide ice sheet was receding (Fig. 10B) and North-ern Hemisphere temperature was increasing (Figs. 10A and 10H), persistent glacial activity has been documented. Glacial activity in the southeastern Cascades was recorded until ca. 15 ka (Rosenbaum et al., 2012; Fig. 10F), two fi nal post-LGM advances are recognized in the Sierra Nevada (Phillips et al., 2009; Tioga 3 and 4), four post-LGM recessional moraines are recorded from 17.2 to 14.8 ka in the Ruby Mountains (Laabs et al., 2013), and a glacial maximum has been observed (ca. 17.4 ka) in the Wallowa Mountains (Fig. 10E; Licciardi et al., 2004). Comparable to the small lake sys-tems of similar latitude, these glacial records indicate increased winter precipitation during HS1 despite increasing Northern Hemisphere temperatures. Finally, while the Laurentide ice sheet began to retreat at the end of the LGM, the Cordilleran ice sheet advanced southward into parts of Washington, Idaho, and Montana until ca. 18–15 ka (Waitt, 1985; Clague and James, 2002; Dyke, 2004) before fully melting during the Bølling-Allerød and Younger Dryas from 14 to ca. 11.5 ka (Dyke, 2004). The per-sistence of the Cordilleran ice sheet may have maintained the southward defl ection of the PJS until the onset of the Bølling-Allerød inter-stadial (ca. 14.5 ka; COHMAP, 1988; Benson et al., 1990; García and Stokes, 2006; Godsey et al., 2011).

Further evidence for differential seasonal anomalies driving different paleorecords of the moisture balance in the interior western United States is demonstrated in the temporal asyn-chrony between the late-LGM and HS1 maxima recorded in lakes and glaciers, with late MIS 3


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Figure 10. Paleoclimate archives and orbital parameters for comparison to the Lake Surprise hydrograph. (A) Proxy-derived Northern Hemisphere temperature stack (black line; dashed line is 1σ error bound) deviation from the early Holocene (11.5–6.5 ka) (compiled by Shakun et al., 2012). (B) North American ice-sheet percent area deglaciated, including both the Laurentide and Cordilleran ice sheets (compiled by Dyke, 2004); note scale is inverted (gray line). (C) Summer (red) and winter (blue) insolation for 40°N (Laskar et al., 2004). (D) The Lake Surprise hydrograph (this study); see the Figure 7 caption for explanation and radiocarbon ages are white circles. (E) Glacier advances (Tioga 1–4 [T1–T4]) in the Sierra Nevada, California, recorded by cosmogenic 36Cl ages (blue bars; Phillips et al., 2009), maximal glaciations (LGM maximum [TT] and post-LGM maximum [WT]) in the Wallowa Mountains, Oregon, documented by cosmogenic 10Be ages (gray bars; Licciardi et al., 2004), recalculated in Rosenbaum et al. (2012), and 10Be ages (Bayesian averages) of the terminal (RT) and range of recessional moraines (RR) from the Ruby Mountains, Nevada (Laabs et al., 2013). (F) Lacustrine record of glacial fl our fl ux recording glacial extent in the southeastern Cascades, calculated from the glacial fl our content in the Caledonia Marsh core from Upper Klamath Lake (Rosenbaum and Reynolds, 2004; Rosenbaum et al., 2012). (G) Lake-level curves plotted as the percent of Last Glacial Maxi-mum (LGM) maximum: Lake Bonneville, Utah (black dashed line; Oviatt et al., 1992; as compiled in McGee et al., 2012), Lake Lahontan, Nevada (black line; Benson et al., 1995; Adams et al., 2008), and Lake Franklin, Nevada (green line; Munroe and Laabs, 2013). (H) North Greenland Ice Core Project (NGRIP) Greenland ice-core δ18O on Greenland Ice Core Chronology 2005 (GICC05) time scale (gray line) smoothed with LOESS smoothing function (red line; Rasmussen et al., 2006). SMOW—Standard Mean Ocean Water. (I) Solar insolation as in C. (J) Lake highstands (black) and stillstands (white boxes) arranged from south to north, as compiled by Munroe and Laabs (2012), Lyle et al. (2012), and recalculated by this study in Table DR7 (see text footnote 1). (K) Great Basin and Mojave soil opal precipitation minus evapotranspiration (P-ET) maxima (Maher et al., 2014) derived from (234U/238U)0 variations in soil opal (Maher et al., 2014) and vadose zone opal (Paces et al., 2010). (L) δ18O from Devils Hole, Nevada (Winograd et al., 2006), interpreted as decreased Pacifi c sea-surface tempera-tures during δ18O minima. VPDB—Vienna PeeDee Belemnite. (M) δ18O from speleothem records: Cave of the Bells, Arizona (Wagner et al., 2010), and Fort Stanton, New Mexico (Asmerom et al., 2010). Both records are interpreted to refl ect increased winter precipitation during δ18O minima. Both records are smoothed using a LOESS smoothing function (red lines). MIS—marine oxygen isotope stage; YD—Younger Dryas; B-A—Bølling-Allerød; HS1—Heinrich Stadial 1.




and early LGM speleothem and vein calcite δ18O minima recording wet and cold winter conditions (Winograd et al., 2006; Asmerom et al., 2010; Wagner et al., 2010; Figs. 10L and 10M), and maximum (winter) infi ltration rates recorded in soil opal (Maher et al., 2014; Fig. 10K). Lakes, soils, glaciers, and speleothems are sensitive to different seasonal variations in the hydrologic cycle. Late LGM lake levels are particularly sensitive to summer insolation and reduced temperatures, which in the midlati-tudes is more than twice winter insolation (Fig. 10I). Given these observations, we propose that changes in orbital conditions that infl uence sea-sonal insolation, particularly summer insola-tion and its infl uence on lake evaporation (as well as evapotranspiration), is a key long-term driver of hydrologic variability in the western United States.

CONCLUSION

Construction of the late Pleistocene lake hydrograph for Lake Surprise, isotope mass balance calculations, and the regional synthesis herein reveal that previously overlooked con-straints—namely, reduced temperature and the effect of seasonal insolation variability on sum-mer lake evaporation—may have driven lake levels in the Basin and Range during MIS 2. Based on isotope mass balance calculations, moderate LGM lake levels observed in Surprise Valley were driven by decreased evaporation (36% relative to modern), with minimal precipi-tation increases (10% relative to modern). These results agree with climate model simulations, which predict a 28% decrease in total evapora-tion and an average of 6.5% increase in precipi-tation relative to modern. Evidence presented here questions the long-standing paradigm of a “rainy LGM” in western North America and highlights the strong infl uence of temperature and seasonal insolation on water availability in the region.

The moderate late LGM lake levels and sus-tained glacial activity post-LGM, driven by a minimum in summer insolation (20.3 ka), primed the Basin and Range lake systems to respond rapidly to increased rainfall during HS1 brought by latitudinally broad and strengthened midlatitude westerly storm tracks. This rapid response was recorded in highstands across the Basin and Range (32°N–42°N) via atmosphere-ocean teleconnection to reduced North Atlan-tic sea-surface temperatures (ca. 17.5–16.5 ka until ca. 14.7 ka). The rapid response of lake systems to substantial increases in precipitation emphasizes the role of atmosphere-ocean tele-connections in water availability in the western United States.

ACKNOWLEDGMENTS

We thank Benjamin Laabs (GSA Bulletin associ-ate editor), Jeff Munroe, and an anonymous reviewer for thorough reviews and comments; Jorge Vazquez (second reader for Daniel Ibarra’s M.S. thesis) and Jeremy Caves for extensive comments and discus-sions on earlier versions of this manuscript; Marith Reheis, Jessica Oster, David Miller, and Perach Nuriel for detailed discussions; Jonathan Glen and Sabina Kraushaar for fi eld work support; Guangchao Li for cation analyses; Dave Mucciarone for stable isotope analyses; David Medeiros and Claire Kouba from the Stanford Geospatial Center for assistance on the ArcGIS analysis; Kimberly Lau and Conni De Massi for help with laboratory work; Hari Mix for suggesting and discussing the Sr/Ca and stable isotope analyses; and Matthew Winnick and Daniel Horton for assis-tance with the PMIP3 climate model processing. Joseph Rosenbaum provided the raw data plotted for the glacial fl ux record from the Caledonia Marsh core from Upper Klamath Lake, Oregon, in Figure 10. LiDAR data were collected by the National Center for Airborne Laser Mapping (NCALM) with funding from the National Aeronautic and Space Administra-tion (NASA) through award 10-UAS10-0021 to Jona-than Glen, Anne Egger, and Corey Ippolito. This work was supported by the National Science Foundation (NSF) grant EAR-0921134 to Kate Maher and sup-port from Stanford University.

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