Limnol. Oceanogr., 35(S), 1990, 1112-1134
0 1990, by the American
Society
of Limnology
and Oceanography,
Inc.
Granite weathering and the sensitivity of alpine lakes to
acid deposition
Robert E. Staufer
3633 Humphrey Lane, Lexington, Kentucky 40502
Abstract
Lake chemical data from the National Surface Water Survey (NSWS) were corrected for the
effects of regional atmospheric deposition and then used to evaluate the role of weathering in
supplying base cations, silica, sulfate, and alkalinity to surface waters in alpine vs. subalpine, and
in glaciated vs. unglaciated granitic terrane of the western and southeastern United States. Thermodynamic models, idealized reaction stoichiometry, and multivariate regression involving solutes
and geographic variables indicate that irreversible weathering can largely account for lake chemistry.
By contrast, relatively minor roles are played by reversible ion exchange in soils and sediments,
terrestrial bioaccumulation, and transformations in lakes. The regional patterns in lake acidity
components (NO,, SO4, DOC, CO3, and statistical relationships between acidity and base cations
demonstrate that rock weathering is limited by acid inputs in many alpine catchments prior to fall
overturn. The empirical success of the Henriksen alkalinity model depends on a high Ca : Na
weathering ratio. The latter increases with increasing physical disturbance of the catchment (iuvenility), hence under natural circumstances attains a maximum as a result of on-going or recent
glaciation. The Henriksen model fails in geochemically “old” terrane, where cation losses accompanying silicate weathering attain steady state proportions.
Ever since the first reports of acid deposition in the western United States (e.g.
Lewis and Grant 1980; Oppenheimer et al.
1985) linked to historical decline in lake
alkalinity in Colorado (Lewis 1982), the
biogeochemical effects of acidity have come
under increased scientific scrutiny in that
region. As a consequence, the U.S. EPA
sponsored the Western Lake Survey (WLS)
as part of the National Surface Water Survey (NSWS) in early fall 1985 (Landers et
al. 1987). On the basis of the WLS and on
independent regional surveys (e.g. Melack
et al. 1985; Turk and Campbell 1987), alpine western lakes are now commonly regarded as among the most susceptible in
North America to acid deposition.
The weathering of granite has long interested geochemists (cf. Drever 1982) and
more recently those limnologists, soil scientists, and ecologists concerned with modeling the long-term responses of montane
catchments to acid deposition. But fundamental questions remain to be answered.
Acknowledgments
I thank B. Wittchen for our many discussions about,
and joint experiments on, weathering, and J. Drever
and W. Lewis, Jr., for helpful remarks on the draft
manuscript. Dixon Landers provided summaries for
the Eastern and Western Lake Surveys of EPA.
First, with geochemical techniques, how can
one reliably distinguish irreversible weathering from reversible cation exchange in
soils? Second, how is weathering rate (however measured) linked to acid flux, bedrock
geology, hydrology, and soil disturbance
history (e.g. surface mining, glaciation)?
These broad questions relate to an important and long-standing geochemical enigma,
namely the source of the Ca that dominates
the base cation (BC) output of many felsic
watersheds, thus confounding the predictions of classical (stoichiometric) weathering models (e.g. Garrels and MacKenzie
1967) while simultaneously underpinning
Henriksen’s (1980) statistical nomograph
relating alkalinity production in unperturbed catchments to the export of Ca plus
Mg alone (cf. Wright 1984).
Here, I address these questions using
comparative analysis of lake data (NSWS)
from alpine vs. subalpine and glaciated vs.
unglaciated felsic terrane. Included are the
Sierra Nevada, the North Cascades,the Idaho Batholith, the major anticlinal mountain
structures of the central and southern Rockies, and extraregionally, the southern Blue
Ridge.
This cross-sectional treatment was motivated by three aspects of the NSWS methodology. First, the procedures were analyt-
1112
Alpine lakes in granite
ically rigorous, yet provided nearly synoptic
sampling coverage of numerous watersheds
in large, undeveloped, and comparatively
inaccessible lithographic units. Second, unlike most earlier geochemical surveys, the
study lakes (catchments) were chosen by
stratified random sampling. This design ensured that regional geochemical estimators
derived from the data are statistically unbiased. Third, the NSWS was conducted
during fall overturn, following the normal
seasonal base-flow recession. The survey
design and timing thus maximized comparability of catchments by minimizing lakespecific effects of flushing episodes superimposed on winter or summer stratification.
Comparison is also favored by geography.
First, for structural reasons, the montane
glaciers that sculpted the western alpine lake
basins moved downward and outward from
the granitic cores of the mountain ranges
(Thornbury 1965). Hence, unlike the eastern lake districts, which were affected by
continental-scale glaciation, the western alpine lake catchments are comparatively free
of drift transported across major lithographic boundaries. Because the unglaciated Blue
Ridge also satisfies this criterion, all of the
geochemical data used here reflect processes
occurring in granite and associated crystalline rocks, not artifacts attributable to highly reactive but alien drift.
Second, my comparative analysis potentially reveals how the severity and recentness of glaciation (hence soil disturbance
history) influence watershed geochemistry.
Thus, Pleistocene and Holocene glaciation
moderated with declining elevation in the
Sierra (Harris and Tuttle 1983), were weak
throughout much of the Idaho Batholith
(Larsen and Schmidt 1958) and in portions
of the southern Rocky Mountains (Miller
196 l), and were altogether missing from the
southern Blue Ridge. Moreover, mass-wasting is currently more active in alpine than
subalpine western terrane.
Third, unlike typical eastern watersheds
with presently aggrading forest biomass (e.g.
Coweeta, Hubbard Brook), the WLS catchments probably feature smaller, more stable
inventories of plant nutrients. This consideration obviously applies to thinly vegetated alpine sites, but probably also to many
1113
subalpine basins long protected by park or
wilderness status. Because of this approximation of biotic steady state and the rapid
erosion of immature alpine soils, the chemistries of the western lakes should closely
reflect mineral weathering, after correcting
for anthropogenic contamination and atmospheric deposition. The WLS catchments, unlike those of the eastern USA, are
also subject to minimal anthropogenic influences; the majority lie in designated wilderness areas (Landers et al. 1987).
Finally, steady state weathering constitutes the principal geochemical influence on
water chemistry in forested catchments of
the southern Blue Ridge Mountains (Velbel
1988). Anthropogenic increases in SO, deposition are comparatively recent in that
locale, and, instead of leaching soil exchange cations in its role as the “mobile acid
anion” (Johnson and Reuss 1984), SO4 is
still largely being retained by adsorption in
the highly weathered surficial soils (Swank
and Waide 1988). The Blue Ridge thus provides an excellent contrast to montane western watersheds in terms of vegetative influences and soil disturbance history.
My comparative study complements the
longitudinal analysis of individual catchments in the Sierra Nevada (Stoddard
1987a), Colorado (Baron and Bricker 1987;
Stednick 1989; Mast and Drever in prep.),
and the Coweeta watersheds in North Carolina (Swank and Waide 1988; Velbel
1988).
Methods
Geographic partition -Landers et al.
(1987) and Linthurst et al. (1986) have described the sampling designs,analytical procedures, and quality assurance protocols
used during the NSWS. My physiographic
classification of montane lake groups (Table
1) was based on site characteristics given by
Eilers et al. (1987) and Kanciruk et al. (1986)
on map inspection (mainly 1 : 250,000 scale
topographic), and on descriptions of the regional hydrology and bedrock and surficial
geology (summarized below).
The Sierran core lake population (WLS4Al and WLS-4A2) featured a discontinuity in elevation between 2,9 16 and 2,8 16
1114
Staufer
Table 1. Summary statistics (medians with 1st-4th quintiles in parentheses) for lake elevation (m), watershed:
lake area ratio (W : L, dimensionless), and Cl (meq mw3).N-No. samples.
Zone*
SN-ALP
SN-SUB
NC
IB
BT-BH
WR
FR
SJ-SW
SC
SBR
N
43
46
60
82
30
49
51
32
12
59t
3,248(3,075-3,404)
2,442(2,015-2,633)
1,525(1,100-1,725)
2,250(2,002-2,593)
2,930(2,820-3,120)
3,112(2,955-3,242)
3,355(3,163-3,465)
3,655(3,475-3,765)
2,425(2,100-3,100)
520(347-908)
* SN-ALP--Sierra
Nevada (elev >2,900 m); SN-SUB-Sierra
Nevada
Beartooth-Bighorn;
WR-Wind
River; IX-Front
Range; SJ-SW-San
Ridge.
t Includes Seven Coweeta watersheds.
m. The 43 watersheds in the first category
are distinctly alpine in character and were
thus subclassified as SN-ALP. Conversely,
lake elevations in the latter group (N = 46)
range down to 1,695 m. Because lake elevations are significantly lower than in SNALP (Table l), and the watersheds are
mainly subalpine in character, I designated
this group SN-SUB. The population of SNSUB increases to 67 if lakes from the periphery (WLS4A3) are added. This subgroup includes reservoirs with much higher
Cl and situated on both sides of the divide
at elevations down to 859 m (Sonoran vegetation zone). I thus deleted the 4A3 periphery when comparing SN-ALP and SNSUB in order to limit the geographic range
of the lakes.
Most of the WLS lakes situated above
3,000 m in the Rockies are also strongly
influenced by drainage from alpine terrane
(Landers et al. 1987). Many are cirque lakes,
set in watersheds of high relief (> 500 m)
near a major drainage divide. Five lakes
from the Big Horn Range and 11 from the
Wind River Range are situated, however,
in granitic peneplains at elevations below
3,000 m. Like the lakes at lower elevations
in the Sierra, these Wyoming catchments
have significant subalpine character. Thus,
I depict them separately in the histograms.
After preliminary geographic and geochemical analysis, four small Rocky Mountain clusters were combined into two to
strengthen statistical analysis (BT-BH; SJSW). The SJ-SW lakes are situated in Ter-
Cl
W:L
Elev
23.3( 14.4-67.0)
18.0(5.3-35.2)
19.6(11.0-40.6)
14.9(9.8-3 1.2)
40.0(25.0-85.0)
22.4( 12.3-57.0)
25.0(14.2-60.0)
19.0(10.3-52.0)
NA
85.0(26.5-234)
(elev ~2,900
Juan-Sawatch;
m); NC-North
SC-Sangre
1.6(1.3-2.3)
3.8(2.3-6.4)
4.9(2.7-l 1.3)
2.2(1.6-3.1)
3.8(2.6-5.2)
5.5(4.1-7.5)
2.4( l-7-3.7)
2.5(1.9-3.5)
-5.5
24.5(16/t-31.0)
Cascades; IB-Idaho
Batholith,
BT-BHde Christo (Miller
1961); SBR-southern
Blue
tiary volcanic (e.g. rhyolite) as well as granitic bedrock (Thornbury 1965). Although
texturally different from granite, the San
Juan volcanics have comparable plagioclase
composition (Larsen and Cross 1956). The
SJ-SW region includes both very dilute
samples and surface waters with elevated
SO, located in historical mining districts.
The SJ-SW block is distinctly alpine; it includes areas of prominent mass wasting
(Thornbury 1965) and features the highest
elevations of any region sampled during the
NSWS (Table 1).
Several WLS clusters in Colorado are not
considered here because of small sample
size, subalpine character, or dominant mafic or sedimentary influence (e.g. Park Range,
Flattops, Sangre de Cristo Range). I also
ignored five sites (including three reservoirs) with elevated Cl and P situated at
lower elevation (2,100-2,865 m) along the
eastern margin of the Front Range (WLS4E3). I did, however, examine Miller’s
(196 1) snowpack and subalpine stream data
(N = 12) from the Embudo granite in the
Sangre de Cristo (SC) Mountains of New
Mexico.
Despite their much lower elevations,
many of the catchments in the North Cascades also display alpine character. Moreover, this appelation might also apply to
certain lakes in Idaho’s Sawtooth Range.
Although no attempt was made to classify
“alpine” lakes separately in these two
regions, the effects of elevation and vegetation on geochemistry were examined with
Alpine lakes in granite
multivariate regression. The Idaho Batholith (IB) included samples representing crystalline portions of the Bitterroots (N = 44),
the Sawtooths (N = 18), and scattered sites
in the Salmon River and Clear-water Mountains (remainder).
I retained only those samples from the
southern Blue Ridge (SBR, ELS-3A) with
Cl < 41 meq m- 3. The others reflect excessive local cultural influences (Stauffer in
prep.). Because of the lithography of the
southern Appalachian Mountains (Hatcher
1988) and my focus on the weathering of
granitic rocks, I also excluded samples from
ELS-3A lying in Tennessee (final N = 53).
The relatively dilute SBR reservoirs lying
at elevations >700 m are most comparable
to the seven intensively monitored watersheds at Coweeta (Swank and Waide 1988).
Atmospheric deposition corrections-bke
data were corrected for atmospheric inputs
(asterisks) when analyzing watershed contributions of Si, BC, and SO,. For all samples I set: Si* = Si, because only traces (< 1
PM) of silicic acid are normally reported for
precipitation samples throughout montane
regions of North America (e.g. Stoddard
1987a; Kennedy 197 1; Feth et al. 1964;
Miller 196 1; Swank and Waide 1988). Partly for this reason, and partly because of silicate hydrolysis stoichiometry, the deposition correction for Si has by far the smallest
uncertainty relative to stream concentration
among all the potential solutes released by
granite weathering.
Along with silicic acid, Na is often the
most useful dissolved indicator of silicate
weathering in undeveloped granitic watersheds because it is easy to measure, appears
in high concentration relative to its deposition correction, is derived almost entirely
from the hydrolysis of a single dominant
mineral (plagioclase), and is most nearly
conservative among the major cations
(ranked last in both soil exchange preference
and biological utilization).
My correction for sodium, Na* = Na 0.86C1, was also universally applied; it reflects the conventional wisdom that Na : Cl
in wet and dry deposition follows the marine ratio and that both ions behave conservatively once in solution. Neither assumption is strictly correct. The deposition
1115
ratio is depressed by wind-blown fertilizer
(contains KCl), and by localized Cl emissions (Laird et al. 1986); it is enhanced by
wind-blown soils rich in alkali. Net retention of Cl has been claimed for the Sierra
(Stoddard 1987a; Feth et al. 1964). Watershed studies in the northern Colorado
Rockies (Turk and Campbell 1987; Baron
and Bricker 1987; Stednick 1989) have not
confirmed this uptake. Moreover, such tendencies can be locally offset by release of
minor Cl accompanying the weathering of
volcanic ash and mafic minerals.
Based only on the NADP network
(NADP/NTN 1989), which is both sparse
and severely biased toward lower elevations
except in Colorado, the long-term, volumeweighted mean Na : Cl in wet deposition is
distinctly marine in the SBR and along the
west coast (SN, NC); it increases slightly (to
- 1.05) in the northern Rockies (IB, BT,
WR) and is significantly higher (1.25-l .45)
in the Colorado Rockies (R. Stauffer unpubl.). If we assume that these NADP data
accurately reflect deposition ratios at higher
elevation, and that Cl is of external origin
and behaves conservatively, the resulting
error in Na* is ~0.6 meq m-3 for most
western alpine lakes (< 1.2 meq rnp3 in Colorado) and for the wetter districts of the
Idaho Batholith. Because the Na correction
is self-correcting for geographic variations
in evaporative concentration, the error in
Na* remains tolerably small ( 5 1.5 meq m- 3,
even for most of the drier subalpine lake
settings examined here. The overall uncertainty is Na* is higher in the SBR (- 3 meq
m-3), not because of uncertainty in the deposition correction, but because of potential
error arising from more diverse, local cultural influences (Stauffer in prep.).
My deposition adjustments for other ions
were based on mean annual solute wet deposition (meq mb2), divided by mean annual runoff R (m), after extrapolating both
parameters to catchment elevations. Both
extrapolations introduce considerable uncertainty because precipitation, deposition,
and runoff are all highly orographic in these
montane regions. Given the paucity of highelevation deposition data, particularly in the
northern Rockies, and the complex influences of elevation and aspect on atmospher-
1116
Staufer
ic inputs and evaporation in montane
regions, this approach is probably the best
practicable for these geographically dispersed western survey data.
I relied mainly on deposition studies by
Stoddard (1987a) and Laird et al. (1986) for
the Sierra Nevada and North Cascades because the regional NADP stations (Sequoia,
Yosemite, Marblemount) are at much lower
elevations. This elevation bias has been
confirmed by more recent Sierran surveys
(Williams and Melack in prep.). Otherwise
my western deposition estimates were based
on monthly NADP data available through
November 1988 (NADP/NTN 1989) at the
following stations: Headquarters, Idaho (IB);
Yellowstone, Wyoming (BT); Pinedale and
Gypsum Creek, Wyoming (WR); Loch Vale
and Niwot Saddle, Colorado (FR); Molas
Pass, Colorado (SJ-SW). As in the Sierra,
the SO, : Cl ratio at Pinedale is biased high
for alpine zones in the Wind River Range
(Naftz et al. in prep.). Based on 3-5 ‘yr of
data from each of these high-elevation (3,15 9
< elev < 3,520 m) NADP stations in Colorado, I rejected earlier BC deposition estimates (Lewis and Grant 1979; Lewis et al.
1984; Reddy and Claassen 1985) as being
unrepresentative of pristine alpine settings
in the Rockies.
Runoff estimates were based on regional
maps, on descriptions of USGS benchmark
watersheds (Cobb and Biesecker 197 1) and
the Wind River Range (Hembree and Rainwater 196 l), and on more recent hydrologic-deposition studies in northern Colorado
(Turk and Campbell 1987; Baron and
Bricker 1987; Stednick 1989), the Sierra
Nevada (Stoddard 1987a), and the southern
Blue Ridge (Swift et al. 1988; Swank and
Waide 1988). All of these sources suggest
that 0.7 < R < 1.2 m for most of these
alpine catchments in the Rockies, for the
lake watersheds in the Idaho Batholith, and
across much of the SBR. Runoff is even
higher (1.0-2.0 m) in the North Cascades,
in portions of the high Sierra, and in highly
exposed sections of the Nantahalas (SBR).
When expressed in concentration units,
the resulting regional deposition corrections
are probably subject to 30-50% relative error. The Ca correction (the term X in Ca*
= Ca - X) is 2-4 meq m-3 for alpine set-
tings in the Sierra and the North Cascades,
5-l 0 for the Idaho Batholith, and 8-l 5 for
alpine lakes in the Rocky Mountains. A
larger Ca correction is required for subalpine lakes in both the Sierra (5-l 0) and Wyoming (lo-20), reflecting dirtier air and
greater evaporative concentration at lower
elevation. In computing Mg* for western
lakes, I assumed that Ca : Mg in atmospheric deposition = 4 (see above sources). The
deposition adjustment for K is 0.5-l .Omeq
m-3, hence the least important in my overall analysis of silicate weathering. On the
basis of my own analysis of wet deposition
at NADP sites in the SBR (Elkmont, Tennessee; Coweeta, North Carolina), coupled
with independent analysis by Swank and
Waide (1988), the following adjustments
(meq m-3) were justified in the SBR : Ca (815); Mg (3-5); K (1.5-3). Because no account was taken of dry deposition (essentially unknown for these localities), I everywhere adopted the upper limit of these
indicated ranges. This approach helps to
avoid a serious positive bias in computed
weathering rates for BC. A lake was judged
to have a net watershed input of SO, if its
SO, : Cl exceeded the corresponding ratio in
regional wet deposition by >50%. Because
of the decrease in depositional SO, : Cl with
elevation (see above), this criterion leads to
conservative estimates of S weathering in
the west.
Geochemical models-The following geochemical ratios were computed and used to
evaluate the stoichiometry of rock weathering:
RI = Si*/(Na* + K*)
R2 = Ca*/Na*
R 3 = (Ca* - bNa*)/Mg*
(1)
(2)
(3)
The b coefficient in R3 is the prevailing An :
Ab ratio (anorthite : albite; here by equivalents) in the plagioclase. This coefficient is
typically -0.5 for the oligoclase dominant
in quartz monzonite and other “granitic”
rocks, but higher (- 1.O) for granodiorite
(Drever 1982). These two rock types (with
biotite as the principal mafic mineral) dominate the Sierra (Feth et al. 1964), the Idaho
Batholith (Larsen and Schmidt 1958), the
Alpine lakes in granite
Wind River Range, and other western intrusives (Thornbury 1965; Miller 196 1).
Provided steady state conditions apply
(see below), RI (by atoms) yields information on the intensity of silicate weathering
and can also serve as a geochemical check
on the deposition corrections for the two
alkali elements in granitic terrane. I summarize the key weathering reactions below,
relying mainly on Drever ( 1982).
The stoichiometric breakdown of biotitegranite to kaolinite (plus residual quartz)
results in R, = 2.00, hence a dissolved Si
concentration that is independent of Ca and
Mg. For certain granites and all mafic rocks
R 1can then be augmented by the weathering
of hornblende and pyroxene to kaolinite.
If weathering is sufficiently intense, kaolinite is further converted to gibbsite,
yielding additional silicic acid but no BC.
The latter transition depends only on dissolved Si concentration, temperature, and
the crystallinity of the two solid phases.With
standard free energy and enthalpy data
compiled by Helgeson and adopted by
Drever ( 1982), the predicted equilibrium Si
concentration is 59 PM at 25”C, decreasing
to 45 PM at 15”, and 29 PM at 0°C. However, this computed equilibrium concentration is highly sensitive to potential errors in
the free energy data and would likely increase if the gibbsite is poorly crystalline. If
feldspar weathers directly to gibbsite, R, is
> 3.00 (the minimum occurs in the absence
of anorthite).
If feldspar weathering is less intense, and
the natural water is also dominated by Ca,
Ca-smectite is likely to form instead of kaolinite. As a consequence, R, is reduced at
steady state to well below 2.0 (e.g. 0.7 for
Sierran granodiorite). On the basis of Garrels’ work, the smectite transition occurs
when
(log Ca + 8 log Si + 2pH) = -16.
A larger pK (N 18.5) is suggested, however,
by a study of Rio Tanama in Puerto Rico
(Drever 1982). Mayer and Gloss (1980)
found evidence for both values, based on
“crossover plots” with two natural smectite
sources. Despite this uncertainty in the
smectite-kaolinite boundary, the kaolinite
stability field is evidently a broad one, po-
1117
tentially encompassing most of the natural
waters in alpine granitic terrane.
Environmental complications arise if biotite weathers to metastable vermiculite
(Drever 1982; Drever and Hurcomb 1986),
if the system, due to seasonal hydrologic
fluctuations, departs from steady state, or if
solutes behave nonconservatively. In the
first casestream R 1will fall below 2.00 when
feldspars are weathering to kaolinite. Here,
the net effect on R 1is generally small unless
local biotite content is high. In the second
case, Si can be temporally buffered by clay
minerals, independent of alkali concentration. Because Si is buffered more than Na,
the net result would be cyclical excursions
of RI above (high flow) and below (base
flow) 2.00, averaging 2.00 on a long-term,
volume-weighted basis (cyclical steady state
kaolinite model). Smectite buffers silica at
higher concentrations (200-350 PM), potentially biasing seasonal point estimates of
stream (lake) chemistry for mean outflow
composition in more saline environments
(Drever 1982; Mayer and Gloss 1980). In
the third case Si : alkali can be skewed by
the formation of biogenic opal or the seasonal uptake or release of K by terrestrial
and aquatic plants.
During the weathering of granite, K is initially derived mainly from the hydrolysis of
biotite, and later, following partial loss of
this relatively reactive mineral, from the
breakdown of the abundant but highly resistant K-feldspar (Garrels and MacKenzie
1967; Drever and Hurcomb 1986; Nesbitt
et al. 1980). On stoichiometric grounds, one
might thus expect a linear statistical relationship between aqueous K* and Mg* during early-stage weathering, with an intercept
near zero and a slope that depends on the
secondary phase (vermiculite vs. kaolinite)
and the ferrous-Fe : Mg ratio in the biotite.
This simple K-Mg stoichiometry can be distorted by the weathering of K-feldspar or
mafic minerals poor in K (e.g. hornblende),
leading to weaker correlations between K
and other BC (Nesbitt et al. 1980). These
geochemical relationships can also be obscured by biological processes because the
ratio of plant uptake to weathering is much
higher for K than for other BC (Likens et
al. 1977).
1118
Staufer
Table 2. Summary t-statistics for acidity components regressed on lake elevation: NSWS. Underlined values
statistically significant (P < 0.05). N-No. lakes.
Zone
N
Cl
SN-ALP
SN-SUB
NC
IB
BT-BH
WR
FR
SJ-SW
SBR
43
46
60
82
30
49
51
32
52
-1.98
-7.02
-11.69
-3.09
-1.05
-3.35
-2.84
-3.05
-4.45
so4
-1.35
-3.33
-1.51
-0.37
-1.26
-0.68
+0.70
+ 1.50
-0.61
Equations 2 and 3 (ratios by equivalents)
are mainly of diagnostic value in analyzing
Ca weathering. In particular, if Ca* > bNa*,
the excess Ca did not come from the stoichiometric breakdown of average plagioclase. if high R2 is accompanied by low R,
(5 1.O),however, the excessCa (Ca* - bNa*)
potentially resulted from the congruent
breakdown of common mafic minerals other than biotite (cf. Drever 1982). This latter
situation should be accompanied by anomalously high R 1ratios and involve statistical
dependence between Si and Mg during multivariate regression. High R2 and R3 ratios
could arise from weathering of amphiboles
to vermiculite, resulting in preferential retention of Mg in clay (M. Velbel pers.
comm.); preferential dissolution of minor
calcite (CaCO,) or fluorite (CaF,), occurring
either widely disseminated in the granitic
host rocks or as secondary vein replacements (Drever and Hurcomb 1986; Mast
and Drever in prep.; Wittchen and Stauffer
in prep.); or preferential hydrolysis of anorthite at crystal defects in recently fractured plagioclase grains.
Statistical analysis- Both histograms and
multivariate regression were used to analyze
solute relationships with geographic variables and other solutes for the purpose of
testing the various geochemical models
(above). The analysis was performed independently by montane region and, in the
case of the Sierra Nevada, separately for the
alpine vs. subalpine blocks.
The suite of independent regression variables included elevation, which is linked locally to vegetation type, glaciology, and ongoing mass wasting, and W : L (watershed :
so, : Cl
DOC
-0.88
+0.76
+2.95
+1.03
-0.42
+2.82
+1.89
+ 1.96
+2.30
-0.04
+1.02
-4.34
-4.86
-5.29
-7.50
-2.45
-4.50
+3.39
closed-co,
-1.84
-2.00
-5.05
-5.75
-2.33
-4.50
-1.89
-1.35
-1.47
lake area ratio), which increases linearly with
lake flushing intensity. For SO, and Si, I
also tested the transformed flushing parameter, F = 5O(W : L + 0.5)-l, which should
be more closely linked to solute retention
in lake sediments (Baker et al. 1986). According to geochemical principles, mineral
weathering is driven by acidity in addition
to contact opportunity (e.g. Schnoor and
Stumm 1985). Thus, for two key BC, Na*,
and Ca, I evaluated how their lake concentrations depended on inorganic (sulfate
linked) and biogenic (DOC linked) acidity.
Independent variables were dropped sequentially from the full model (beginning
with the least significant) until only those
variables were left which retained individual significance (P < 0.05). Usually there
was little cause for ambivalence, because l3 variables were consistently highly significant (across regions), whereas the others
were consistently nonsignificant. Residuals
were scrutinized at every stage in the analysis, but only a few especially serious outliers were ultimately removed (4A2-07, all
regressions; 4C 1- 16, K and Si analysis; 3A222, Si analysis).
Results and discussion
Chloride-Chloride
is low in these western montane lakes (Table l), and everywhere inversely correlated with lake elevation (Table 2). The latter trend arises from
progressive dilution of precipitation at higher elevations (especially in snow) and the
effect of elevation on annual precipitation :
runoff (evaporative concentration factor).
The fitted regional slope (- 1O3meq Cl m-4)
was 1.l-l .3 in the northern Rockies (BT-
Alpine lakes in granite
BH, IB) and SN-ALP and higher (2.7-5.1)
across the central and southern Rockies
(WR, FR, SJ-SW). The highest slope applied to the North Cascades(14.0), probably
because of lower elevations and proximity
to the coast.
Acidity components-The western montane lakes typically have much lower SO,
concentrations than lakes in the northeastem United States; this major geographic
trend roughly reflects the regional isopleths
in SO, deposition corrected for evaporative
concentration (Sullivan et al. 1988). More
exacting regional analysis, however, reveals
net watershed retention of SO4in the weakly
glaciated or unglaciated zones (SN-SUB,
SBR, perhaps IB) vs. net sources of SO, in
each alpine sector (Table 3). Although SO, :
Cl in precipitation generally decreases with
elevation in the montane west (preferential
washout in rain), the SO, : Cl ratio in the
alpine lakes typically increases with elevation (Table 2), where it also significantly
exceeds the ratios in local precipitation (Table 3). Moreover, unlike in forested subalpine terrane, these high alpine lake ratios
cannot be attributed to the effects of unmeasured dry deposition, because dry deposition is minimal for the dry snow surfaces that prevail most of the year at high
elevations (Williams and Melack in prep.).
Sulfur mineralization is evidently more
important than atmospheric deposition in
differentiating present SO, concentrations
in alpine western lakes, a conclusion independently reached by Loranger and Brakke
( 1988) after monitoring lakes in the North
Cascades. Because S minerals are reactive,
this correlation suggeststhat rapid physical
weathering at alpine locations continuously
exposes labile minerals to chemical attack.
By contrast, only trace amounts of SO, exit
long-weathered granitic terrane in New
South Wales, Australia (Banens 1987).
Lake SO, was significantly (P < 0.05) correlated with W : L in the alpine Sierra (t =
5.79), North Cascades (t = 2.7 l), and Idaho
Batholith (t = 4.86), but not in SN-SUB,
the SBR, or anywhere in the central or
southern Rocky Mountains. The alternative
flushing parameter, F = 5O/(W: L + 0.5),
was a much weaker correlate of SO, in these
same three regions (t = - 1.27; - 1.75;
1119
Staufer
15
25
35
+l5
45
I
I
25
I
I
35
I
I
45
I
I
I
I-
l-
d
b
bI.
co
IO
20
30
40
50
2
Fig. 1. Histograms for closed-CO, (FM) at fall overturn. a. SN-ALP. b. SN-SUB core. c. Alpine Rocky
Mountain composite (BT-BH+WR+FR-0);
subalpine BT-BH and WR (*). d. SBR reservoirs. The most
concentrated subcategory is open-ended (CO, > 50 PM). Vertical arrows (off scale) are numerically labeled.
Closed-CO, concentrations computed from closed-DIC and pH measurements with equilibrium constants listed
by Drever (1982). For reference, equilibrium CO, = 15.0 PM at 5°C and the median elevation of SN-ALP (for
atmospheric pC0, = 345 ppm).
-2.82) characterized by minimum S deposition and significant geologic sources of
S (SN-ALP, NC). Because F is more closely
linked to sediment S retention (Baker et al.
1986), whereas W : L is a direct measure of
external flushing, these various correlations
are inconsistent with the hypothesis that inlake alkalinity generation linked to S retention plays a major role in the acid-base regulation of these western alpine lakes (see
also Stoddard 1988). Instead, they suggest
that base-flow entering these lakes before
fall sampling was anomalously rich in SO,.
This base-flow acquires its chemical properties accompanying maximum penetration
of the regolith. Feth et al. (1964) first reported this pattern of SO4enrichment in the
perennial Sierran spring waters. It is equally
apparent in perennial Snyder’s Spring, Idaho (White et al. 1963).
The western alpine lakes, and the Sierran
subclass in particular, also featured the lowest concentrations of “closed’ (in situ; cf.
Landers et al. 1987) CO2 and DOC (Table
3; Figs. 1, 2) among all the geographic units
sampled in the NSWS. As a consequence
the closed-pH values were circumneutral or
alkaline, despite the low ionic strengths and
low closed-DIC concentrations. In each of
the alpine subunits the median and modal
DOC values were below 75 PM, and the
median and modal closed-CO, fell close to,
or even significantly below (Sierra), the
computed equilibrium concentration for the
temperature and elevation of the samples
(Figs. 1, 2). Both types of C acidity were
inversely correlated with elevation throughout the west (Table 2) and increased markedly on entering the more biologically active
subalpine zone (Figs. 1,2). Because S* (non-
1121
Alpine lakes in granite
50
100 150 200
30
a
20
0
/
10 O
L
30
I-
d
b
20
I-
0
/
10 O
II
L
25
75
125 175 225
DOC
25
75
125 175 225
PM
Fig. 2. As Fig. 1, but for sample DOC.
depositional SO,-S) is positively correlated
with alpine status, there is a strong inverse
correlation between S* and the sum of the
biological acidity components (DOC +
closed-CO,) across the montane west.
The heavily vegetated SBR also featured
low DOC values (Table 3; Fig. 2d), coupled
with the highest regional closed-CO, concentrations anywhere in the NSWS (Table
.3; Fig. Id). The increase in DOC with elevation in the SBR is unusual (Table 2; Rasmussen et al. 1989); this trend reflects shallower soils combined with higher runoff at
upper elevations, hence increased “quickflow” or “surface return flow” (Swift et al.
1988).
One possible interpretation of these regional acidity patterns is that mineral
weathering is limited by available acidity in
portions of these alpine catchments, including those with sulfide mineralization. Alternatively, the low closed-CO, concentrations in the western lakes at midfall overturn
might reflect antecedent biological uptake
and degassing, either in the lake or in turbulent inflows.
The second explanation appears insufficient. First, hydraulic residence time is very
short in most of these alpine lakes in summer (Stoddard 1987a; Baron and Bricker
1987), effectively limiting net primary productivity (Stoddard 19873) and gas exchange. Second, closed-CO2 concentrations
are as low in the seepage lakes as in the
drainage lakes throughout the alpine granitic districts of the west. Nevertheless, these
seepagelakes are of the flow-through type,
have - 90% of their closed-DIC in the form
ofbicarbonate alkalinity, yet also have highly elevated radon levels traced to recent
groundwater movement through talus and
coarse-grained glacial deposits (Norton et
al. 1985). Third, outside the SBR the low
closed-CO, values covary significantly with
low DOC, a nonvolatile constituent produced by terrestrial ecosystems.Fourth, both
Staufler
1122
30
20
0
/0
10
30
b
20
0
/0
10
l
l
0
l
I
II
II
I
I
II
+
I
IO1
I
I
l
I
I
I
I
I
I
I
I
I
30
I
e
0
cl
20
20
0
/0
10
/0
10
30
f
20
':
0
T '
/0
10 ; '
LIL
5
20
0
/
10 O
15
25
Na *
35
45
15
25
Na *
35
45
Fig. 3. Histograms for Na* (meq m-3) at fall overturn. a. SN-ALP (G,-Gem Lake in summer). b. SN-SUB
core. c. Rocky Mountain composite (alpine and subalpine BT-BH+WR+FR-0);
IB low alkalinity core (WLS4Cl-*). d. SBR reservoirs with Cl < 20 meq m-3 (0); SBR reservoirs with 20 < Cl < 40 meq m-3 (*). e. FR.
f. WR (0); BT-BH (*). g. IB-inclusive (n = 83). h. NC.
Alpine lakes in granite
ionic strength and alkalinity increase in the
alpine catchments with internal S sources
(examined later). And finally, perennial
spring waters and base-flow may attain secondary equilibrium with Ca-smectite, both
in the Sierra (Garrels and MacKenzie 1967;
Stoddard 1987a) and Rocky Mountains
(Miller and Drever 1977), indicating unfavorably high pH for intensive weathering.
The situation is different in the SBR,
where, because of SO, adsorption and efficient microbial degradation of organic C in
the highly evolved ultisols, CO, in high concentrations affects weathering accompanying deep percolation through the saprolite
(Velbel 1988). Figure 1d suggeststhat a significant amount of that CO, is not consumed by weathering reactions. Hence, to
an extent not found in the alpine catchments, the chemical evolution of the
groundwaters in the SBR is limited mainly
by the reactivity of the rock. Other geochemical indicators of reactivity support
these regional interpretations (see below).
Alkali and silica weathering-Although
Na concentrations ranged down to 3.2 meq
m-3 (two San Juan lakes at elev >3,625 m),
Na* was invariably positive (Fig. 3) and exceeded the probable error in the Na deposition correction, except for one of these
same San Juan samples (4E2-42). In most
cases Na* exceeded this error by an order
of magnitude (Table 3; Fig. 3). The small
errors in Na* are one consequence of the
low regional Cl concentrations (Table 1).
The alkali concentrations in the most dilute alpine lakes support the regional deposition corrections. Significantly higher
deposition estimates would lead to unrealistic negative feldspar weathering rates in
high-elevation lakes with minimal Na and
K concentrations. Moreover, my interpretation is consistent with the high sediment
loads in outflowing streams (e.g. 700 kg ha-l
yr-’ in the Merced River at Yosemite; Cobb
and Biesecker 1971), as compared to particulate deposition in the montane environment (m 50 kg ha- 1yr- l; Lewis et al. 1984).
The Na* histogram is distinctly bimodal
for alpine lakes in the Sierra (Fig. 3a), with
few values (8 or 19% of population) exceeding 25 meq m-3. A majority (5) of the
latter group also have anomalously high SO,
1123
(subclass of 10 lakes with SO, > 30 meq
m-3), suggesting increased plagioclase
weathering in response to sulfur mineralization. By contrast, the subalpine Sierran
histogram (Na*) is unimodal, yet more dispersed, being better represented at both the
lower end (<5 meq m-3; 9%) and upper
portion (>25 meq m-3; 38%) of the distribution. None of these subalpine Sierran lakes
had anomalously high SO,.
The Na* histograms are remarkably similar for each of the granitic montane regions
of the Rockies (Fig. 3c,e-g), and, if one allows for greater dilution (w 1.5 x ) caused by
higher regional precipitation, in the North
Cascades (Fig. 3h). In each case the distribution is unimodal (lo-20 meq m-3), with
-25% of the population having Na* > 25
meq m-3.
The Na* concentrations are a factor of
five higher in streams draining subalpine
granitic zones of the southern Sangre de
Cristo Range (Miller 196 1). Allowing for the
much lower hydraulic yields at these same
sites (-0.2 m yr- ‘) compared to alpine zones
of the central and northern Rockies (N 1.O
m yr-l), and assuming that lake-average
concentrations at late fall turnover are representative of annual-average outflow from
catchments (cf. Baron and Bricker 1987),
we find that the Na denudation rate is
roughly comparable (-20 meq m-2 yr- l)
in all of these western montane regions.
When examined intraregionally
with
multivariate regression, Na* is positively
correlated with both DOC and S04, even
after controlling for the influences of elev,
W: L, and Cl (Table 4). If we ignore the
three nonsignificant regional SO, coefficients (Table 4), the mean cross-regional
slopes are 0.12kO.03 (Na* vs. DOC) and
0.26 kO.08 (Na* vs. Sod). The coefficient for
DOC seems high, given the prevailing ratio
between acidic functional groups and DOC
for humic substances (N 0.12 meq mM- l at
pH 6.5; Oliver et al. 1983). DOC, however,
probably represents only a small fraction of
total biogenic C acidity affecting weathering
below the root zone. Although the evidence
is correlational, plagioclase weathering apparently increases with available acidity in
these western mountains. This view was articulated by earlier regional geochemists
1124
Staufer
Table 4. Regression analysis of Na* (dependent) in montane lakes (SE in parentheses; units as in Table 3).
Model
Zone
Full-t
SN-ALP
SN-SUB
NC
IB
BT-BH
WR
FR
SJ-SW
SBR
0.51
0.33
0.33
0.16
0.79
0.54
0.52
0.49
0.38
RZ
Parameter
Reduced~
Intercept
0.48
0.25
0.24
0.14
0.75
0.52
0.52
0.46
0.08
model$
DOC
4.8(3.0)
15.2(4.8)
10.3(1.7)
10.7(3.4)
- 12.9(5.2)
9.2(1.9)
2.1(3.1)
-0.3(5.1)
so,
0.169(0.037)
0.063(0.0 16)
0.031(0.012)
0.056(0.022)
0.222(0.027)
0.069(0.0 10)
0.134(0.02 1)
0.244(0.047)
NS
see noted
t Full model independent
variables: elev, W : L, DOC, SO,.
* DOC and SO, (where significant in 111 model); NS-not
significant.
8 Best equation: Na* = 29.2( 11.4) - 0.025(0.008)elev
+ 0.84(0.3O)Cl;
values in reduced
0.118(0.024)
0.12$.043)
0.492(0.178)
0.409(0.190)
0.165::.062)
NS
NS
R2 = 0.44.
(Miller 196 1; Hembree and Rainwater 196 1;
Feth et al. 1964; Miller and Drever 1977).
The situation is substantially different in
the SBR. Here, Na* decreaseswith increasing elevation (Table 4) and is lower for Appalachian reservoirs with Cl < 20 meq m-3
(Fig. 3d). These two trends likely reflect orographic influences on hydrology, because
studies at Coweeta reveal higher precipitation and greater runoff at upper elevations
(dilution effect) coupled with more intensive weathering accompanying deeper
groundwater penetration of saprolite in the
valley bottoms (Swank and Waide 1988;
Velbel 1988). The Na* concentrations are
significantly higher in the SBR than in any
of the western alpine regions (Table 3; Fig.
3). Because regional runoff is comparable,
plagioclase weathering is evidently a more
potent influence in the warmer, more heavily vegetated Blue Ridge.
K covaries with one or more BC throughout the west and in the SBR (Table 5). Mg
is a sufficient BC correlate of K in the central
Sierra, and is the dominant correlate (> Na*)
in the North Cascades and in the Idaho
Batholith. The IB regression equation even
accurately predicts the K concentration in
perennial Snyder’s Spring (measured K =
80; predicted K = 89 + 14 meq m-3), a moderately concentrated (conductance = 25 5 PS
cm- ‘) but uncontaminated groundwater issuing from quartz monzonite in the heart
of the Idaho Batholith (White et al. 1963).
Elsewhere, Na* or Ca or both displace (BTBH, FR, SJ-SW, SC) or augment (WR, SBR)
Mg in the best regional multivariate regression model (Table 5). The K* : Na* ratio
attains its western maximum in the Wind
River Range (Table 3).
Except for elevation, other variables (e.g.
W : L, DOC, Cl) lack statistical significance
Table 5. Regression analysis of K in montane lakes (units as in Tables 1, 3).
Model
Zone
Full-l
SN-ALP
SN-SUB
NC
BT-BH
IB
FR
WR
SJ-SW
SC
SBR
SBR
0.60
0.58
0.55
0.78
0.67
0.61
0.63
0.30
NA
0.70
0.70
R2
Reduced
0.57
0.56
0.54
0.74
0.64
0.61
0.63
0.23
0.71
0.685
0.67
Best reduced
Intercept
1.5(0.6)
2.5(0.8)
-4.9(2.7)
-0.7(0.9)
1.6(0.3)
- 14.4(5.8)
All+
4.0(1.5)
1.5(2.6)
20.4(2.2)
18.6(2.6)
model
Coefficients
for K (with
SE)
for independent
variables
+0.45(0.06)Mg
+0.20(0.03)Mg
+0.074(O.O13)Mg + 0.28(0.08)Na* + 0.0039(0.0015)e1ev
+0.08(0.0 1)Ca
+O. 120(0.0 15)Mg + 0.052(0.0 14)Na*
+O.O18(0.003)Ca + 0.062(0.020)Na* + 0.0048(0.00 17)elev
+O. 16(0.05)Na*
+O. 15(0.03)Na*
+O. 1l(0.02)Ca - 0.0 15(0.002)elev
+O. 17(0.03)Mg - 0.0 13(0.003)elev
t Full model independent
variables: elev, W : L, Na*, Mg, CTa.
* WR equation: K = -9.9(7.2)
+ 0.14(0.04)Mg
+ 0.028(0.009)Ca
- O.lO(O.O4)Na*
+ 0.0042(0.0022)elev
+ 0.020(0.006)W
5 Best SBR equation: K = 11.9(3.3) + 0.078(0.02l)Ca
- 0.0108(0.0025)elev
+ 0.32(O.lO)Ch
RZ = 0.73 (similar improvement
: L.
for Mg model).
Alpine lakes in granite
1125
(P > 0.05) when added to BC in the K re- the Idaho Batholith (Fig. 4c,g), and the North
gression equations (Table 5). Where signif- Cascades(Fig. 4h). These same regional hisicant, the effect of elevation on K is positive tograms also feature significant upper end
in the western alpine areas (SN, NC, WR, tailing (skewness) in the gibbsite field. Even
FR). These results collectively suggest that higher R1 values (dominantly gibbsite) are
neither the type and extent of vegetation characteristic of the SBR, particularly for
(DOC linked; nowhere significant) nor the the more dilute waters at higher elevations
recentness of lake flushing (W : L linked) has (low Cl; Fig. 4d). By contrast, the subalpine
a direct influence on K export from these core Sierra has wide-spanning ratios lacking
western catchments (relative to other BC of a central tendency (Fig. 4b), and R, values
lesser biological importance). Instead, the are low (spanning smectite-kaolinite
effect of elevation might signify a shift in boundary) throughout much of the central
hydrolysis stoichiometry upon entering the and southern Rockies (Fig. 4c,e,f). Miniphysically active, but slightly weathered al- mum ratios occur in the Wind River Range
pine zone. The K-vs.-Mg regression coeffi- (Fig. 40.
cient for subalpine lakes in the Sierra (0.17If I restrict the analysis to dilute lakes in
0.20 by equivalents) is the same as for Gar- each region (Table 6), the R, values fall eirels and MacKenzie’s ( 1967) model for bi- ther in the gibbsite field (NC, IB, BT-BH,
otite alteration to kaolinite in subalpine Si- SJ-SW, SBR) or are transitional between
erran springs. The higher coefficient for the gibbsite and kaolinite (SN, FR). The single
alpine Sierran lakes (0.45) thus accords with dilute lake from maximum elevation in the
Drever and Hurcomb’s (1986) observation Wind River Range is an exception. These
that biotite weathers to metastable vermic- silica concentrations confirm that silicate
ulite in glacially active watersheds of the weathering is occurring in these catchments
North Cascades. In alpine terrane the ver- with minimum alkali concentrations.
miculite is likely to erode before being transWith some important exceptions (disformed to kaolinite.
cussed below), the regional R, patterns are
The situation is substantially different in broadly consistent with continuous, steady
state silicate weathering models. Thus, the
the SBR where, in addition to the predictive
power of other BC (either singularly or in thermodynamic model predicts kaolinite as
combination), both elevation and Cl figure the sole weathering product at intermediate
importantly in the best K regression model alkali and Si concentrations and a shift to
gibbsite formation when weathered alkali (A
(Table 5). Here, and in the neighboring
Piedmont Province, the Cl coefficient (0.32) = Na* + K*) falls below - 1O-l 5 meq m-3.
might reflect increased fertilization with KC1 This gibbsite transition is reflected by sevin valley bottoms (Stauffer in prep.).
eral histograms (SN-ALP, NC, IB) and is
There is strong covariance between K ex- compatible with the dilute samples from evport and the release of other BC in silicate ery investigated region except the Wind
terrane (Table 5). These statistical relationRiver Range (Table 6).
ships either highlight the stoichiometric
Multivariate regression also supports this
weathering of a particular mineral (biotite; reaction model (Table 7). Thus, alkali conK-Mg association; Sierra) or, more com- centration is the dominant correlate of Si in
monly, the proportional weathering of min- every region, and the only significant cation
eral suites (K-Na association; Nesbitt et al. correlate in five of them (SN-ALP, NC, IB,
1980; Banens 1987). By contrast, studies of FR, SC). Moreover, in cases where the diBC mobilization in eastern, forested water- valent bases are retained in the final regressheds have emphasized the selective uptake sion equation the coefficient for Mg is posand retention of K by aggrading vegetation itive (excepting SJ-SW), the coefficient for
Ca is always negative, and the related im(Likens et al. 1977).
Turning now to silica, the median and provement in model R2 is exceedingly small
modal R1 slightly exceed the expected ratio (e.g. SJ-SW, SBR). When a quadratic term
for the weathering of feldspar + biotite to (alkali squared) is added to the model and
kaolinite (2.00) in the high Sierra (Fig. 4a), retained as significant, its sign is negative,
1126
Staufer
0.8
I
l
I
1.6
I
2.4
I
Ii
3.2
I
0.8
I
I
I
I
1.6 2.4
I
I
I
3.2
I
I
I
I
I
a
1
300/
20-
PS
0
4
10 -*
I
I
K
2.
I
l
l
l
G
+
9
l
l
rn30
30
0
d
c
0+*
I
b
ES
S
20
/0
10
30
0
20
20
0
/0
10
II
/
10 O
0.4
1.2
2.0 2.8
R1
3.6
0.4
1.2 2.0
2.8
3.6
R1
Fig. 4. As Fig. 3, but for R,. Arrows S, K, G-formation of smectite, kaolinite, and gibbsite from steady
state weathering of Sierran granodiorite. a. G,, G,-Gem Lake in summer and winter. b. ES, PS-ephemeral
and perennial Sierran springs. e. SC-Sangre de Cristo streams draining Embudo granite (mean R, = 1.53*O. 10;
range- 1.34, 1.67). g. SY-Snyder’s Spring (Na* = 350 PM; K* = 80 FM; Si = 450 PM).
Alpine lakes in granite
1127
Here, the inferred sedimentation losses averaged 2 1, 16, 11, and 3% of lake Si, respectively. Several factors might account for
Mean (and SE of mean)
these geographic trends in apparent Si reNa* + K*
Zone
N
Cond
R,
tention. First, alpine lakes are nutrient poor
SN-ALP
6
3.8
7.6
2.80(0.37)
(Stoddard 1987b) and rapidly flushed durSN-SUB
7
3.7
7.0
2.49(0.13)
ing the pulsed summer snowmelt (Stoddard
NC
7.6
13
7.4
3.26(0.26)
1987a); these features suppress annual priIB
7.1
8.7
5
3.83(0.34)
BT-BH
9.8
8.3
3.00(0.25)
6
mary productivity and delay its maximum
WR
1
7.2
6.0
1.33(NA)
into fall (Stoddard 1987b). By contrast, sea4
7.2
6.9
2.43(0.56)
FR-t
sonal flushing attains a prolonged summerSJ-SW
6
10.6
5.0
4.1 l(O.66)
fall minimum at all of these subalpine lo27.4
SBRz#z
11
12.8
3.23(0.18)
24.4
cations, allowing fuller antecedent develCoweeta$§
6
10.0
3.76(0.22)
opment of diatoms. Moreover, despite the
t Colorado Front Range.
$ Na* + K* < 35 meq mm3.
long growing season, median W : L and Si
§ Volume-weighted,
long-term
means (streams).
concentrations attain maxima for reservoirs
in the SBR (Tables 1, 3), potentially supand the effect is to reduce the Y-intercept pressing the relative role of in-lake process(often to nonsignificant levels) and steepen es.
Important model discrepancies are also
the slope near the origin. In three areas (SNALP, NC-4B1, SJ-SW) the resulting statis- apparent. Despite having a kaolinitic slope
tical model is consistent with the transfor- coefficient, the SBR has a highly significant
mation of feldspar + biotite to gibbsite at Y-intercept and no concavity (Table 7). As
low alkali concentrations, and then succes- a consequence, the median and modal R1
exceed 2.00 (Fig. 4d) across an alkali dosive displacement of gibbsite by kaolinite
and possibly Ca-smectite along the alkali main where thermodynamics predicts kaolinite as the only stable phase. Conversely,
domain.
Except for the IB region, elev and W:L R1 values are too low to fit the model in
were not significant in the Si regression many subalpine Sierran lakes (Fig. 4b) and
equations (Table 7). However, the alternate throughout much of the central and southflushing parameter, F = 5O(W : L + 0.5)-l,
ern Rockies (Fig. 4c,e,f). Mean annual R, =
was either highly (P < 0.05) or marginally
2.05 (kaolinite) for an alpine-subalpine
(P < 0.1) significant in every lower eleva- stream draining the granitic Hourglass Basin
tion lake group (SN-SUB, t = - 1.40; NC, in the northern Front Range (Stednick 1989).
t = -2.13; IB, t = -2.65; SBR, t = -1.85).
In several Rocky Mountain regions the
Table 6. R, = Si : (Na* + K*) in dilute lakes (low
conductance) with Na* + K* < 10 meq m-3.
Table 7. Regression analysis of Si (dependent).
Model
Zone
SN-ALP
SN-SUB
NC
NCS
IB
IB
BT-BH
WR
FR
S-SW
SC
SBR
SBR
Full?
0.59
0.47
0.64
0.72
0.71
0.71
0.72
0.37
0.79
0.70
NA
0.85
do
R2
Reduced
0.53
0.47
0.61
0.69
0.68
0.65
0.70
0.31
0.78
0.62
0.97
0.84
0.82
t Full model variables: elev, W : L, Mg, Ca,
$ Lowest alkalinity
subgroup (4Bl) of North
Best reduced
Intercept
4.4(7.6)
- 13.2(16)
36.8(8.9)
2.8(7.6)
13.5(4.9)
17.6(5.0)
21.7(6.4)
6.7(5.9)
6.1(3.5)
8.2(9.6)
3.9(6.7)
31.3(7.1)
30.8(7.1)
+2.32(0.52)x4 +2.1 l(O.89)A + 1.48(0.16)A +2.76(0.63),4 + 1.57(0.29)A + 1.60(0.31)x4+ 1.17(0.2 1)A +
+ 1.33(0.42),4 + 1.31(0.20)/l +2.28(0.34)/4 + 1.51(0.07)/4
+2.14(0.16)A +
+ 2.13(0.13)A
A = (Na* + K*), AA = AZ.
Cascades (N = 38).
model
Coefficients
for Si (with
SE)
for independent
variables
0.0 19(0.007)AA
0.019(O.OlO)AA + 1.23(0.46) Mg
0.0 15(0.005)elev
0.032(0.0 1l)AA + 0.19(0.06)Mg
0.006(0.004)AA + 0.23(O.O7)W: L
0.0053(0.0037),4,4
0.53(0.2O)Mg - 0.44(0.14)Ca
0.0 12(0.006&4 - 0.08(0.04)Ca
0.004(0.002),4/4
0.50(0.14)Mg
0.77(0.29)Mg - 0.53(0.19)Ca
1128
Staufer
lower slopes (Si vs. alkali) are accompanied
by positive Y-intercepts (Table 7), lending
support to the cyclical steady state model.
Under this scenario, soils selectively retain
silica (vs. Na*) in summer and subsequently
release it (desorption) in the late spring
snowmelt. On theoretical grounds one expects R, cyclicity to increase in montane
watersheds where outflow chemistry spans
the gibbsite-kaolinite phase boundary accompanying fluctuations in discharge and
in catchments where summer precipitation
generates an extended or bimodal annual
flushing cycle. Both conditions might contribute to low median RI at fall turnover in
the central and southern Rockies, while preserving the high RI in the ultradilute lakes
(Table 6).
The minimum R, for the Wind River
Range, coupled with maximum K* : Na*,
suggests another problem in the kaolinite
weathering model. As noted earlier, if K is
derived from the weathering of biotite to
vermiculite, the R, ratios decline. This reaction is less important in regions with low
mafic content, where abundant plagioclase
insures low K* : Na* (SN, IB).
Stoddard ( 1987a) proposed that the low
R1 (N 1.20) in Gem Lake (SN-ALP) over
winter resulted from smectite formation accompanying deep percolation of groundwater. Although the negative quadratic coefficients (Table 7) are generally consistent
with Stoddard’s hypothesis, the evidence
remains equivocal. For these low winter Si
concentrations (13 1 PM), smectite production requires pH > 8.3 (for pK = 18.5),
which is higher than reported by Feth et al.
(1964) for all but one perennial Sierran
spring. Si concentrations were much higher
in both the ephemeral (mean = 273 PM)
and perennial (mean = 4 10 PM) Sierran
springs and in perennial Snyder’s Spring,
Idaho (450 PM), commensurate with maximum concentrations reported (WLS) for
reservoirs in the Sierra and Cascade ranges.
Both the springs and the reservoirs feature
R 1 spanning the kaolinite-smectite boundary (-2.00) and -log activity quotients
consistent with the recognized thermodynamic boundary (16 + 3). Nevertheless, given that maximum groundwater salinities
exceed mean groundwater values, smectites
may be forming locally in alpine catchments
otherwise dominated by kaolinite formation (Drever 1982, pers. comm.).
Ca and Mg-According to the widely accepted Henriksen model, alkalinity production linked to BC mobilization can be attributed to Ca and Mg alone. Among the
montane regions studied here, median Mg*
< median Na* (Table 3) except in three
areas of the central and southern Rocky
Mountains (BT-BH, WR, SJ-SW). This inequality is greatest for the Sierra Nevada,
the Idaho Batholith, and in granitic sections
of the southern Sangre de Cristo Rangethree regions where mafic mineral content
is low and dominated by biotite (Feth et al.
1964; Larsen and Schmidt 1958; Miller
196 1) and where the weathering of biotite
best accounts for K and Mg concentrations
in regional surface and groundwaters (Table
5; Garrels and MacKenzie 1967). Elsewhere, Mg* is >Na* at the Q4 level (Table
3), while Mg* is <Na* at the median and
lower quintile levels (e.g. NC, FR, SBR).
This interquintile shift in ion dominance
might reflect increased weathering of hornblende and related mafic minerals, because
intrusions and metamorphic complexes feature zones of mafic enrichment that weather
more rapidly than sodic plagioclase.
Ca is the most abundant BC in most of
the felsic watersheds studied (Table 3). The
dominance of Ca* over Na* (RJ increases
markedly, however, when I compare perennial vs. ephemeral Sierran springs (Fig. 5b),
alpine vs. subalpine zones of the Sierran
core (Fig. 5a vs. 5b), severely glaciated or
alpine zones of the North Cascades and
Rockies with weakly glaciated (Pleistocene)
subalpine regions (IB, SC) of the Rockies
(Fig. Sc,e-h), and formerly glaciated regions
vs. the unglaciated SBR (contrast Fig. 5d
with all other panels). If, in addition, I consider Banens’ (1987) study of long-weathered, acid-igneous rocks in Australia, Fig. 5
reveals a perfect rank ordering between R2
and the glacial disturbance history of a region. Thus, the stoichiometric weathering
of plagioclase is subordinate to other reactions in supplying Ca, except in subalpine
granitic zones of the Sierra Nevada, Idaho
Batholith, Sangre de Cristo Range, southern
Blue Ridge, and New South Wales. Finally,
Alpine lakes in granite
1.5 2.5 3.5 4.5
I I I I I 1 1 1 1
30
1.5
I
I
1129
2.5
I
I
3.5
I
4.5
I
I
I
C
a
IA
30
42-
20
0
/0
IO
20
0
/0
IO
30
ES
0
20
0
/0
10
G
30
G
+
b
d
20
0
*
+
/
IO O
aI
-L
IIIII
l
l
l
11
130
-I
g
20
0
/0
IO
?
rL
30,
f
200
/0
IO-
30
51
*40
h
20
0
G
l
>:
1.0
/
IO O
2.0
3.0
R2
4.0
I
5.0
1.0
2.0
3.0
4.0
5.0
R2
Fig. 5. As Figs. 3 and 4, but for R,. Both maximum and minimum subcategories are open-ended. Arrow
G-maximum ratio consistent with stoichiometric weathering of Sierran granodiorite (An = 0.43); lower ratios
(-0.5-l .O) apply to true granitic rocks. Numbers in panel a denote % for 10 high-SO, SN-ALP samples (see
text). For comparison, R, ranged from 0.4 to 0.8 for reservoirs in the Stanthorpe leuco-adamellite (true granite)
in New South Wales (Banens 1987).
1130
Staufer
1.5
I
I
2.5
I
I
3.5
I
I
30
20
1
2.5
3.5
4.5
I
62
*
a
0
1.5
4.5
I
90
-
rn30
/0
IO
30 I -
80
68
53
b
d
*
20 I- G
+
/0
0
IOI-
T
1.0
2.0
3.0
4.0
5.0
R3
1.0
2.0
3.0
4.0
5.0
R3
Fig. 6. As Fig. 5, but for R, (panels a-d only). a. High-SO, subgroup (*). Arrow G--maximum ratio for
common mafic minerals. For comparison, R, ranged from 0.0 to 0.4 for Stanthorpe leuco-adamellite in New
South Wales (Banens 1987).
outside the unglaciated regions, this excess
Ca* (the fraction unaccounted for by simple
plagioclase weathering) cannot be assigned
to weathering of the common mafic minerals (Fig. 6) except in portions of Idaho’s
Sawtooth Range, nor is it significantly related to the weathering of fluorite. What then
accounts for this geographically linked Ca
behavior?
When examined intraregionally, R2 is
positively correlated with SO, and negatively with DOC (Table 8). This linkage between R2 and SO, was an anomalous feature
of the Sierran perennial spring data (Fig.
5b); it is equally evident at Snyder’s Spring,
Idaho (Fig. 5g). Moreover, SO, is a significant binary correlate of Ca in every region
except SN-SUB and the leading correlate of
Ca in two severely glaciated sectors lacking
significant atmospheric deposition of either
Ca or S (SN-ALP, NC; Table 8). As noted
above, these correlations also apply interregionally.
Conversely, elevated SO4 traceable to atmospheric deposition does not increase RZ.
Thus, the three lakes lying closest to Missoula, Montana, had anomalously high S04,
above-average Na* (mean = 2 l), normal R 1
(2.50), and below-average R2 (mean = 1.1)
as compared to other lakes from the Bitterroot Range (Figs. 3c, 5~). Although their
lake chemistry is compatible with the regional Na* and Si regression models (Tables
4, 7) their deletion significantly increases
the Ca-SO, and R,-SO, correlations for the
entire Idaho Batholith (Table 8). Similarly,
R, values are lowest for upper elevations in
the SBR (including Coweeta; Fig. 5d), in
environments where thin soils and maximum rates of S deposition are promoting
faster attainment of steady state conditions
(conservative SO4 behavior). Clearly, high
1131
Alpine lakes in granite
Table 8. Correlates of Ca and R, = Ca* : Na*.
Binary
Zone
SN-ALP
SN-SUB
NC
IB
IB§
BT-BH
WR
FR
SJ-SW
SC
SBR
Ca-Na*
3.94
5.19
5.10
6.88
6.88
5.45
5.21
2.08
2.63
7.67
4.82
t values?
Regression
Ca-Mg
ca-so,
ANC-SO,
7.30
8.02
2.30
6.17
6.17
8.55
8.16
13.28
7.64
2.85
13.11
14.12
1.21
5.90
3.75
5.40
4.42
2.20
10.15
4.76
4.83
3.85
5.16
-0.20
4.43
3.46
5.26
2.96
1.84
7.17
0.85
3.02
1.55
R2
O-33$
0.09
0.22
0.16
0.27
0.43
0.30
0.33
0.22*
0.06
0.5211
model
for
R2t
t-DOC
t-so,
-1.81
-0.23
-2.02
-1.91
- 1.97
-4.06
-3.14
-1.87
-1A 53
3.54
1.80
3.81
3.23
4.86
2.57
3.49
4.73
2.11
- 0.80
5.92
NA
-2.83
not
t Underline:
t-statistic
significant
(P > 0.05).
$ Setting max R2 = 12.0 (reduces sensitivity
to very low Na*).
0 Eliminating
three Bitterroot
samples nearest Missoula,
Montana,
where SO, is apparently
elevated by local emissions.
- 0.0047(0.0017)DoC
+ 0.047(0.008)SO,
+ 0.036(0.011)
Cl.
11Best equation: R, = -0.80(0.45) + 0.0008(0.0003)elev
R2 is associated with deeper hydraulic flow
paths along fractures and faults and internal
sources of S04, hence the lability of the mineral suites undergoing weathering. Conversely, low R2 is linked to DOC, hence to
soil stability and long-term weathering attributable to vegetative influence.
More surprisingly, SO, is also a positive
correlate of lake ANC in each of the alpine
regions except the San Juans (Table 8). This
counter-intuitive association reflects maximum Ca-SO, linkage (SN-ALP, NC, FR)
and, coupled with the known regional incidence of base metal ore deposits, suggests
that the Ca-SO, correlation is primarily due
to sulfide and not gypsum weathering. Provided calcite is present in the host rocks
(Mast and Drever in prep.), the sulfuric acid
produced by weathering sulfide deposits can
react directly to yield CaSO, and H2CO3.
The subsequent reaction of this carbonic acid
then yields ANC, resulting in an overall
Henriksen “F-factor” = 2.0. This efficient
internal consumption of H2CO3 is supported by the low closed-CO, concentrations in
alpine lakes at fall turnover (Table 3; Fig.
2). Moreover, in the absence of calcite the
production of sulfuric acid accelerates plagioclase weathering, as suggestedby lake data
(Table 4) and evidenced by elevated Na*
(65-100 meq m-3) in acid mine drainage at
high elevations in Colorado (Bencala et al.
1987; McKnight et al. 1988). These corre-
lations thus reinforce the conclusion that
background acidity levels are too low to induce maximum weathering rates in deeply
penetrating groundwaters draining many alpine catchments.
Conclusions
First, like Stoddard (1987a), but in juxtaposition to Schindler et al. (1986), the
present work emphasizes the role of mineral
weathering in the catchment, not “in-lake”
processes, in regulating the ions that collectively determine lake alkalinity. Thus, W:L
proved nonsignificant (P > 0.05) in multivariate regression models for BC in these
regions. Moreover, input-output and correlational analysis (Sullivan et al. 1988; this
work) and paleolimnological
evidence
(Norton et al. 1988) collectively indicate that
sediment reduction and retention of S is
subordinate to acid deposition and geologic
sources in regulating regional SO, concentrations.
Second, in contrast to Hubbard Brook,
where computed net biomass uptake of K
B monitored export (by 6 : 1) in the aggregate annual “weathering” budget (Likens et
al. 1977), the strong statistical relationships
between K and other BC, and between silica
and the alkalis, de-emphasize bioaccumulation as a selective filter influencing solute
export from these western catchments. The
cross-regional geochemical comparisons cast
1132
Staufler
doubt on the computed (vs. monitored)
Hubbard Brook weathering budget. Thus,
R, = 2.10 for Hubbard Brook runoff, but
declines to 1.20 if biomass uptake is included. The first ratio is typically kaolinitic;
the second is smectitic, hence far too low to
be consistent with the local weathering regime (Johnson et al. 198 1). Moreover, K* :
Na* = 0.15 and K*:Mg* = 0.19 for reported Hubbard Brook runoff, i.e. comparable to ratios for undisturbed wilderness
lakes (and springs) at subalpine elevations
in the Sierra and Idaho Batholith (Table 3).
The same ratios for the combined HB budget (> 1) are incompatible with the classical
descriptions of weathering and higher than
found in every spring (Feth et al. 1964; White
et al. 1963) and every lake sample (WLS)
from felsic watersheds in the western United States. From this statistical study, the
major influence of vegetation is to stabilize
catchment soils (retard physical weathering)
and, through the production of acids (CO,
and DOC), promote chemical weathering
and the long-term preferential leaching of
Ca.
Third, as hypothesized by Stoddard
(1987a) and by numerous earlier investigators (e.g. Garrels and MacKenzie 1967),
evidence presented here indicates that silicate weathering is limited by available acidity in those portions of alpine catchments
featuring penetrative hydraulic pathways.
The antithetical view has also been expressed, however, and used to explain apparent historical changes in lake alkalinity
in the Colorado Rockies (Lewis 1982). Thus,
based on a 3-yr monitoring study of Como
Creek Watershed in the Colorado Front
Range, Lewis and Grant (1979) could find
no evidence of primary silicate weathering
(instead finding net retention of Na, K, Ca).
It is unfortunate that no Si data were obtained to corroborate this surprising result.
It has not been corroborated by later studies
(Baron and Bricker 1987; Stednick 1989).
Fourth, this study highlights the lability
of Ca-bearing minerals in juvenile terrane.
Thus, the preferential loss of CaO from recently deglaciated alpine catchments follows the classical reactivity series (Ca > Mg
> Na > K) as originally proposed by Goldich (1938). The Henriksen (1980) alkalinity
model thus owes its empirical successto the
much greater reactivity of carbonates in
mixed carbonate-silicate terrane and to the
Goldich reactivity series in immature felsic
terrane. As a corollary, one expects high pH
and alkalinity in lakes immediately following deglaciation offelsic terrane, consistent
with recent paleolimnological evidence from
the Adirondacks (Whitehead et al. 1986).
Conversely, I expect the Henriksen model
to fail when used to interpret alkalinity relationships in geochemically “old” catchments in which cations released by silicate
weathering have attained or surpassedsteady
state proportions. Included here are the SBR
and southern Piedmont Provinces of the
United States, as well as many other peneplained basement complexes at lower latitudes (e.g. New South Wales). For similar
reasons the Henriksen model will lose its
efficacy when comparing shallow vs. deep
groundwater flow paths, consistent with the
low Ca* : Na* in perched seepage lakes
(Stauffer et al. in prep.). Finally, from these
geochemical trends, I predict that subalpine
lakes in the Sierra and Idaho Batholith are
more sensitive to chronic acidification than
western lakes in alpine settings.
References
BAKER, L. A., P. L. BREZONIK, AND C. D. POLLMAN.
1986. Model of internal alkalinity generation:
Sulfate retention component. Water Air Soil Pollut. 31: 89-94.
BANENS, R. J. 1987. The geochemical character of
upland waters of northeast New South Wales.
Limnol. Oceanogr. 32: 129 l-l 306.
BARON, J., AND 0. P. BRICKER. 1987. Hydrologic and
chemical flux in Loch Vale watershed, Rocky
Mountain National Park, p. 141-156. In D.
McKnight and R. C. Averett [eds.], Chemical
quality of water and the hydrologic cycle. Lewis.
BENCALA,K. E.,D.M. MCKNIGHT,ANDG.
W. ZELLWEGER. 1987. Evaluation of natural tracers in an
acidic and metal-rich stream. Water Resour. Res.
23: 827-836.
COBB, E. D., AND J. E. BIESECKER. 197 1. The national
hydrologic benchmark network. U.S. Geol. Surv.
Circ. 460-D.
DREVER, J. I. 1982. The geochemistry of natural waters. Prentice-Hall.
-,
AND D. R. HURCOMB. 1986. Neutralization
of atmospheric acidity by chemical weathering in
an alpine drainage basin in the North Cascade
Mountains. Geology 14: 22 l-224.
EILERS, J. M., AND OTHERS. 1987. Characteristics of
Alpine lakes in granite
lakes in the western United States. V. 2. Data compendium for selected physical and chemical variables. U.S. EPA 600/3-86/054b.
FETH, J. H., C. E. ROBERSON,AND W. L. POLZER. 1964.
Sources of mineral constituents in water from granitic rocks, Sierra Nevada, California and Nevada.
U.S. Geol. Surv. Water Supply Pap. 1535-I.
GARRELS,R. M., AND F. T. MACKENZIE. 1967. Origin
of the chemical composition of some springs and
lakes, p. 222-242. Zn Equilibrium concepts in natural waters. Am. Chem. Sot. Adv. Chem. Ser. 67.
GOLDICH, S. S. 1938. A study of rock weathering. J.
Geol. 46: 17-58.
HARRIS, A. G., AND E. TUTTLE. 1983. Geology of
national parks, 3rd ed. Kendal/Hunt.
HATCHER, R. D., JR. 1988. Bedrock geology and regional geologic setting of Coweeta Hydrologic
Laboratory in the eastern Blue Ridge, p. 81-92.
Zn W. T. Swank and D. A. Crossley [eds.], Forest
hydrology and ecology at Coweeta. Ecol. Stud. Ser.
66. Springer.
HEMBREE, C. H., AND F. H. RAINWATER. 196 1. Chemical degradation on opposite flanks of the Wind
River Range. U.S. Geol. Surv. Water Supply Pap.
1535-E.
HENRKSEN, A. 1980. Acidification of freshwatersa large-scale titration, p. 68-74. Zn Ecological impact of acid precipitation. Symp. Proc. SNSF Project, Oslo.
JOHNSON, D. W., AND J. 0. REUSS. 1984. Soil mediated effects ofatmospherically deposited sulphur
and nitrogen. Phil. Trans. R. Sot. Lond. B 305:
383-392.
JOHNSON, N. M., AND OTHERS. 198 1. Acid rain, dissolved aluminum and chemical weathering at the
Hubbard Brook Experimental Forest, New Hampshire. Geochim. Cosmochim. Acta 45: 1421-1437.
KANCIRUK, P., AND OTHERS. 1986. Characteristics of
lakes in the eastern United States. V. 3: Data compendium of site characteristics and chemical variables. U.S. EPA/600/4-86/007c.
KENNEDY, V. C. 1971. Silica variation in stream water with time and discharge, p. 94-l 3 1. Zn Nonequilibrium systems in natural water chemistry.
Am. Chem. Sot. Adv. Chem. Ser. 106.
LAIRD, L. B., H. E. TAYLOR, AND V. C. KENNEDY.
1986. Snow chemistry of the Cascade-Sierra Nevada Mountains. Environ. Sci. Technol. 20: 275290.
LANDERS, D. H., AND OTHERS. 1987. Characteristics
of lakes in the western United States. V. 1. Population descriptions and physico-chemical relationships. U.S. EPA/600/3-86/054a.
LARSEN, E. S., JR., AND W. CROSS. 1956. Geology and
petrology of the San Juan region, southwestern
Colorado, U.S. Geol. Surv. Prof. Pap. 258.
-,
AND R. G. SCHMIDT. 1958. A reconnaissance
of the Idaho batholith and comparison with the
southern California batholith. U.S. Geol. Surv.
Bull. 1070-A.
LEWIS, W. M., JR. 1982. Changes in pH and buffering
capacity of lakes in the Colorado Rockies. Limnol.
Oceanogr. 27: 167-l 72.
-,
AND M. C. GRANT. 1979. Change in the out-
1133
put of ions from a watershed as a result of the
acidification of precipitation. Ecology 60: 10931097.
-,AND1980. Acid precipitation in the
western United’ States. Science 207: 176-l 77.
-,
AND J. F. SAUNDERS. 1984. Chemical
paitems of bulk atmospheric deposition in the state
of Colorado. Water Resour. Res. 20: 1691-1704.
LIKENS, G. E., F. H. BORMANN, R. S. PIERCE, J. S.
EATON, AND N. M. JOHNSON. 1977. Biogeochemistry of a forested ecosystem. Springer.
LINTHURST, R. A., AND OTHERS. 1986. Characteristics
of lakes in the eastern United States. V. 1. Population descriptions and physico-chemical relationships. U.S. EPA/600-/4-861007a.
LORANGER, T. J., AND D. F. BRAKKE. 1988. The extent of snowpack influence on water chemistry of
a North Cascades lake. Water Resour. Res. 24:
723-726.
M&NIGHT, D. M., B. A. KIMBALL, AND K. E. BENCALA.
1988. Iron photoreduction and oxidation in an
acidic mountain stream. Science 240: 637-640.
MAYER, L. M., AND S. P. GLOSS. 1980. Buffering of
silica and phosphorus in a turbid river. Limnol.
Oceanogr. 25: 12-22.
MELACK, J. M., J. L. STODDARD, AND C. A. OCHS.
1985. Major ion chemistry and sensitivity to acid
precipitation of Sierra Nevada lakes. Water Resour. Res. 21: 27-32.
MILLER, J. P. 196 1. Solutes in small streams draining
single rock types, Sangre de Cristo Range, New
Mexico. U.S. Geol. Surv. Water Supply Pap.
1535-F.
MILLER, W. R., AND J. I. DREVER. 1977. Chemical
weathering and related controls on surface water
chemistry in the Absaroka Mountains, Wyoming.
Geochim. Cosmochim. Acta 41: 1693-1702.
NADP/NTN
[NATIONAL ATMOSPHERIC DEPOSITION
PROGRAM (IR-~)/NATIONAL
TRENDS NETWORK].
1989. NADP/NTN Coordination Office, Nat.
Resour. Ecol. Lab, Colorado State Univ.
NESBITT, H. W., G. MARKOVICS, AND R. C. PRICE. 1980.
Chemical processes affecting alkalis and alkaline
earths during continental weathering. Geochim.
Cosmochim. Acta 44: 1659-1666.
NORTON, S. A., C. T. HESS, G. M. BLAKE, M. L.
MORRISON, AND J. BARON. 1985. Excess unsupported 2 lo-Pb in lake sediment from Rocky
Mountain lakes: A groundwater effect. Can. J. Fish.
Aquat. Sci. 42: 1249-1254.
-,
M. J. MITCHELL, J. S. KAHL, AND G. F. BREWER.
1988. In-lake alkalinity generation by sulfate reduction: A paleolimnological assessment. Water
Air Soil Pollut. 39: 33-45.
OLIVER, B. G., E. M. THURMAN, AND R. K. MALCOLM.
1983. The contribution of humic substances to
the acidity of colored natural waters. Geochim.
Cosmochim. Acta 47: 203 l-2035.
OPPENHEIMER, M., C. B. EPSTEIN, AND R. E. YUHNKE.
1985, Acid deposition, smelter emissions, and the
linearity issue in the western United States. Science 229: 859-861.
RASMUSSEN, J. B., L. GODBOUT, AND M. SCHALLENBERG. 1989. The humic content of lake water
1134
Staufler
and its relationship to watershed and lake morphometry. Limnol. Oceanogr. 34: 1336-l 342.
REDDY, M. M., AND H. C. CLAASSEN. 1985. Estimates
of average major ion concentration in bulk precipitation at two high-altitude sites near the continental divide in southwestern Colorado. Atmos.
Environ. 19: 1199-1203.
SCHINDLER, D. W., M. A. TURNER, M. P. STAINTON,
AND G. A. LINSEY. 1986. Natural sources of acid
neutralizing capacity in low alkalinity lakes of the
Precambrian Shield. Science 232: 844-847.
SCHNOOR, J. L., AND W. STUMM. 1985. Acidification
of aquatic and terrestrial systems, p. 31 l-338. Zn
W. Stumm [ed.], Chemical processes in lakes. Wiley.
STEDNICK, J. D. 1989. Hydrochemical characterization of alpine and alpine-subalpine stream waters,
Colorado Rocky Mountains, U.S.A. Amt. Alp. Res.
21: 276-282.
STODDARD, J. L.
1987a. Alkalinity dynamics in an
unacidified alpine lake, Sierra Nevada, California.
Limnol. Oceanogr. 32: 825-839.
-.
1987b. Micronutrient and phosphorus limitation of phytoplankton abundance in Gem Lake,
Sierra Nevada, California. Hydrobiologia 154: 103113.
-.
1988. Are Sierran lakes different? A reply to
the comments of Kelly and Schindler. Limnol.
Oceanogr. 33: 1641-l 646.
SULLIVAN, T. J., AND OTHERS. 1988. Atmospheric wet
sulfate deposition and lakewater chemistry. Nature 331: 607-609.
SWANK, W. T., AND J. B. WAIDE. 1988. Characterization of baseline precipitation and stream chemistry and nutrient budgets for control watersheds,
p. 57-79. Zn W. T. Swank and D. A. Crossley, Jr.
[eds.], Forest hydrology and ecology at Coweeta.
Ecol. Stud. Ser. 66. Springer.
SWIFT, L. W., JR., G. B. CUNNINGHAM, AND J. E.
DOUGLASS. 1988. Climate and hydrology, p. 3555. Zn W. T. Swank and D. A. Crossley, Jr. [eds.],
Forest hydrology and ecology at Coweeta. Ecol.
Stud. Ser. 66. Springer.
THORNBURY, W. D. 1965. Regional geomorphology
of the United States. Wiley.
TURK, J. T., AND D. H. CAMPBELL. 1987. Estimates
of acidification of lakes in the Mt. Zirkel WildernessArea, Colorado. Water Resour. Res. 23: 17571761.
VELBEL, M. A. 1988. Weathering and soil-forming
processes, p. 93-102. Zn W. T. Swank and D. A.
Crossley, Jr. [eds.], Forest hydrology and ecology
at Coweeta. Ecol. Stud. Ser. 66. Springer.
WHITE, D. E., J. D. HEM, AND G. A. WARING. 1963.
Data of geochemistry, chapter F. Chemical composition of subsurface waters. U.S. Geol. Surv.
Prof. Pap. 440-F.
WHITEHEAD, D. R., D. F. CHARLES, S. J. JACKSON, S.
E. REED, AND M. C. SHEEHAN. 1986. Late-glacial
and Holocene acidity changesin Adirondack (N.Y.)
lakes, p. 251-274. Zn J. P. Smol et al. [eds.], Diatoms and lake acidity. Junk.
WRIGHT, R. F. 1984. Norwegian models for surface
water chemistry: An overview, p. 213-230. Zn C.
M. Bhumralkar ted.], Meteorological aspects of
acid rain. Butterworth.
Submitted: 22 December 1988
Accepted: 25 April 1989
Revised: 11 May 1990