Introduction
The climatic control on erosion in mountain belts remains a longstanding and
active debate in geomorphology. Some of this debate has focused on whether
spatial gradients in precipitation can be invoked to drive gradients in
erosion or whether these rates are more strongly controlled by their
tectonic setting (e.g., Burbank et al., 2003). While some studies have
argued for modern precipitation controls on erosion (e.g., Bookhagen et al.,
2005), climate's imprints via glacial processes are widely recognized to
significantly alter a landscape. For example, abrasion and plucking of
bedrock by overlying glacial ice widens and deepens valleys (Brocklehurst
and Whipple, 2002). Glacial erosion may increase mountain relief and cause
isostatic uplift of rocks (e.g., Champagnac et al., 2007; Molnar and
England, 1990). Through an erosional “buzzsaw”, glaciers have been suggested
to set the limit on mountain range height and relief (e.g., Egholm et al.,
2009; Mitchell and Humphries, 2015) and accelerate mountain erosion (e.g.,
Herman et al., 2013). Post-glacially, rivers export unconsolidated sediments
stored in basins (Hinderer, 2001; Hoffmann et al., 2007; Wittmann et
al., 2016), and steep glacial headwalls and valley sides undergo accelerated
hillslope erosion. The resulting post-glacial sediments can become effective
tools for rivers to rapidly incise their beds (Jansen et al., 2011). Glacial
processes significantly alter landscapes and therefore leave a lasting
topographic legacy that influences erosion, relief, and possibly uplift tens
of thousands of years after glacial retreat (e.g., Salcher et al., 2014).
Together, these processes and observations may suggest that glacial forcings
are the dominant control on landscape evolution in modern mid- and
high-latitude mountain belts.
Notwithstanding the clear topographic and erosional effects that glacial
processes imprint in the landscape, there has been notable pushback on the
idea that climate via glaciation is the dominant driver of erosion in
diverse mountain belts. For example, not all glaciers are efficient eroders,
and glaciers frozen to their base may instead protect bedrock from erosion
in high topography (Thomson et al., 2010). Even across glacial–interglacial
time periods, fluvial incision may outpace glacial erosion in valley bottoms
(Montgomery and Korup, 2011). Furthermore, global compilations of erosion
rates across multiple temporal scales show similar erosion rates by glaciers
and rivers, and these data suggest that tectonics likely controls erosion
rates over millennial and longer timescales regardless of glacial history
(Koppes and Montgomery, 2009).
This debate regarding climate's influence on mountain belt evolution has
been especially active for the European Alps, where both glacial and
tectonic forces have been invoked as principle drivers of erosion and uplift
(Cederbom et al., 2004; Fox et al., 2015; Mey et al., 2016). Wittmann et al. (2007)
and Champagnac et al. (2007) noted that millennial-scale erosion
rates vary with – and may exceed – modern uplift rates in the central
Alps and that correlations between topography, uplift, and erosion suggest that glacial and post-glacial erosion alone may explain rates of uplift in the
region via isostasy. Norton et al. (2010a, 2011) further argued that
glaciation drives uplift, based on the observation that river knickpoints
are highly correlated with previous glacial cover and glacial equilibrium
line altitudes. However, it has also been suggested that ongoing collision
and active convergence in the Eastern Alps may either primarily drive uplift
(Hergarten et al., 2010) or significantly contribute to changes in relief
across the Cenozoic (Legrain et al., 2014). In the eastern portion of the
range, accelerated rates of river incision and hillslope erosion since 5 Ma
have been suggested to record late Tertiary uplift (Legrain et al., 2015;
Wagner et al., 2010). These relatively local observations have been coupled
with landscape evolution models to suggest that the Alps as a whole are not a
decaying orogen as a glacial driver of uplift and erosion may suggest but
instead a young mountain range still experiencing tectonic rejuvenation
(Hergarten et al., 2010; Robl et al., 2015).
(a) The study area lies in the easternmost region of the
European Alps, with sites located across both Austria and northern Slovenia.
(b) Catchment outlines and sampling points for our 26 river sand
samples, used to measure millennial-scale erosion rates across both
previously glaciated and unglaciated catchments. Extent of Last Glacial
Maximum (LGM) ice is shown by the blue shaded area. The boundary between the
crystalline bedrock of the Alps and the Miocene sedimentary basin (Styrian
Basin) follows roughly the 300–500 m elevation contour marked by the yellow
color tones.
Here, we add insight to the debate on the role of glaciers in driving
Holocene Alpine erosion, by quantifying landscape morphology and
10Be-derived denudation rates (hereafter called erosion rates) in both
unglaciated and previously glaciated basins of the far Eastern Alps. We find
that the past glacial history exerts a stronger control on erosion rates
across the Eastern Alps than previously invoked tectonic forcings.
Approach
Study site
Our study region lies in the easternmost region of the European Alps
(Fig. 1), composing the Styrian as well as several intramontane basins and
adjacent massifs that make up the Alpine uplands: the Lavanttal Alps
(including Gleinalpe and Koralpe), the Schladminger Tauern, the Seckauer Tauern,
and Pohorje in Slovenia (Fig. 2a). The Styrian Basin (part of the Pannonian
Basin) was a shallow marine basin throughout much of the Miocene, becoming
brackish and finally freshwater during basin inversion, which commenced
around 10 Ma (Bada et al., 2001;
Cloetingh et al., 2006). These kilometer-thick Miocene sediments now underlie
a gentle hilly terrain that has uplifted some 300 m above sea level in the
last 7 My (e.g., Legrain et al., 2014). The upland regions of adjacent
massifs are made up of high-grade metamorphic rocks, with local limestone in
the range north of the basin.
Geographic distribution of erosion rates. (a) Study
catchments span several geologic regions marked by distinct massifs and
basins. Catchment outlines and data points are color-coded by region. Dashed
outlines represent basins that were previously glaciated during the Last
Glacial Maximum (LGM). Extent of LGM ice is shown by the thin grey line, and
bolder grey lines mark national boundaries. (b) Erosion rates
increase with mean basin slope and can generally be grouped by region
(replicate samples shown).
Data from cosmogenic nuclide analyses.
Size
Qtz.
10Be conc.a
Snow
Topographic
Production ratec
Sample
fraction
Long.
Lat.
Sample
weight
(×104 atoms
shielding
shielding
(atoms gquartz-1
Denudation rate
(µm)
(∘ E)
(∘ N)
elev. (m)
(g)
gquartz-1)
factorb
factorb
yr-1)
(mm ky-1)
Bistrica
250–500
15.139
46.613
382
30.2
10.87±0.89
0.93
0.99
9.58
69.2±6.4
Bistrica
500–800
15.139
46.613
382
30.2
11.74±0.87
0.93
0.99
9.58
64.0±5.6
Feistrichbach
250–500
14.778
47.151
717
31.2
12.79±0.60
0.92
0.98
11.63
69.3±4.2
Gleinbach
250–800
14.872
47.222
656
33.2
9.41±0.56
0.92
0.98
10.46
86.3±6.1
Gleinbach
500–800
14.872
47.222
656
35.1
9.35±0.45
0.92
0.98
10.46
86.8±5.0
Ingering
250–500
14.680
47.285
967
40.3
11.39±0.56
0.89
0.96
14.50
94.3±5.8
Kleinsolk
250–500
13.938
47.382
893
39.9
6.58±0.57
0.88
0.93
15.53
172.5±16.2
Krug
250–500
14.657
47.275
938
40.2
13.81±0.78
0.90
0.97
14.24
76.5±5.4
Lassnitz1
250–500
15.184
46.820
520
34.6
15.49±0.62
0.96
0.99
7.48
39.2±2.1
Lassnitz3
250–500
15.173
46.838
543
31.7
13.70±0.60
0.93
0.99
9.95
56.7±3.4
Lavant1
250–500
14.824
46.939
658
31.7
8.95±0.58
0.89
0.99
11.02
94.3±7.0
Lavant2
250–500
14.945
46.663
370
31.5
9.95±0.58
0.94
0.99
9.81
77.4±5.3
Mooskogel
250–500
15.372
47.359
490
39.0
7.04±0.83
0.95
0.97
9.19
103.7±13.4
Obertal
250–500
13.665
47.354
967
40.1
5.69±0.38
0.88
0.94
15.52
199.0±15.0
Pickelbach
250–500
15.750
47.003
326
30.7
4.91±0.38
0.99
1.00
5.65
101.6±8.3
Pohorje1
250–500
15.434
46.529
543
32.7
9.53±0.78
0.94
0.99
9.29
77.2±7.1
Pohorje1
500–800
15.434
46.529
543
31.5
8.86±0.47
0.94
0.99
9.29
83.1±5.1
Pohorje2
250–500
15.425
46.560
313
30.6
7.22±0.50
0.95
0.99
8.85
98.1±7.7
Ratten
250–500
15.732
47.487
752
30.3
10.10±0.48
0.93
0.99
10.58
81.1±4.8
Rottenmann
250–500
14.347
47.477
1077
35.5
5.51±0.39
0.89
0.95
15.04
200.1±15.9
SaintNico
250–500
14.038
47.335
1053
40.0
4.88±0.33
0.88
0.95
15.93
237.5±17.8
Seckauer
250–500
14.871
47.283
724
32.4
12.53±0.70
0.91
0.98
11.77
71.3±4.8
Stanz
250–500
15.506
47.465
650
29.5
7.71±0.65
0.94
0.98
9.71
99.0±9.3
Stiefing
250–500
15.592
46.905
304
31.2
4.35±0.31
0.99
1.00
5.62
114.3±8.5
Thörl
250–500
15.245
47.482
583
40.3
6.49±0.97
0.91
0.97
9.81
118.2±19.6
Triebental
250–500
14.516
47.444
1063
32.2
4.50±0.38
0.90
0.96
13.95
228.7±21.8
Untertal
250–500
13.698
47.357
999
40.5
6.53±0.50
0.88
0.93
16.00
178.1±15.4
Veitsch
250–500
15.502
47.564
672
34.2
4.96±0.51
0.94
0.98
9.55
151.8±16.5
Velka
250–500
15.328
46.585
372
34.3
6.91±0.45
0.96
0.99
8.13
95.8±6.8
a 10Be concentrations measured
at ETH Zürich in June 2010 and 2011. Results normalized to Nishiizumi et
al. (2007) 07KNSTD standard, corrected for average of six chemical
processing blanks (10Be /9Be =2.72±2.21×10-15;
μ± SD). b Snow shielding calculated from annual Swiss snow
data (Auer, 2003). Topographic shielding calculated from 10 m digital elevation models (DEMs).
c Per-pixel production rates calculated for quartz-bearing
lithologies following scaling laws of Dunai (2000), Schaller et al. (2002),
and Braucher et al. (2003) for nucleonic and muonic interactions. Based on
compilation of sea level, high-latitude production rates of
4.0 atoms gquartz-1 yr-1 (Phillips et al., 2016) and
assuming that negative and fast muons compose 1.2 and 0.65 % of total
production rates, respectively (Braucher et al., 2003). Mean catchment
production rates include both topographic and snow-shielding correction
factors.
Our study region is unique as the only part of the Alps in which unglaciated
and formerly glaciated mountainous catchments can be found in immediate
proximity. During the glaciation periods of the past million years, only the
western portion of the study region was pervasively glaciated (Fig. 1). East
of the contiguous Alpine ice cap, only isolated cirque glaciers occurred at
elevations above 2000 m, for example in the summit region of the Koralpe
range. In unglaciated portions of our study area, previous geomorphic work
has recognized two distinct landscape morphologies: a low-gradient,
low-relief upland region and a higher-gradient, higher-relief region
downstream of river knickpoints (Legrain et al., 2014; Robl et al., 2008).
Millennial erosion rates from small basins within these regions correlate
with slope and the degree of incision (Legrain et al., 2015). These two
morphologies are interpreted as representing the relict and incising portions of
a landscape responding to incision initiated at ∼ 4 Ma (Wagner et al.,
2010). The timing of incision coincides with the inversion and uplift of the
Styrian and northern Molasse basins. No work thus far has compared erosion
rates in the previously glaciated and unglaciated portions of this
landscape.
Catchment denudation rates and morphometrics.
Mean
Sample
Glacial
Catchment
Avg.
Avg.
elevation
Basin area
Mean local
Erosion rate
historya
area (km2)
slopeb (∘)
slopec (∘)
(m)
> 35∘ (%)
relief d (m)
(mm ky-1)
Gleinalpe
Feistrichbach
U
74.8
20.4
19.5
1322
2 %
1301
69.3±4.2
Gleinbach
U
80.9
21.2
20.4
1243
3 %
1201
86.3±6.1
Koralpe
Bistrica
U
141.2
15.8
15.1
1181
1 %
1136
69.2±6.4
Lassnitz1
U
2.9
15.6
15.5
810
0 %
681
39.2±2.1
Lassnitz3
U
66.3
15.5
14.8
1141
0 %
1155
56.7±3.4
Lavant1
U
234.5
11.6
11.4
1728
0 %
1450
94.3±7
Lavant2
U
952.3
14.5
14.2
1029
1 %
1029
77.4±5.3
Mürz Valley
Mooskogel
U
79.2
22.7
22.4
985
6 %
1017
103.7±13.4
Ratten
U
96.5
17.3
16.8
1213
0 %
1198
81.1±4.8
Stanz
U
62.3
19.2
19.0
1068
1%
1068
99±9.3
Thörl
U
321.1
22.5
21.9
1166
10 %
1157
118.2±19.6
Thörl-qtze
U
(163.7)
–
–
–
–
–
118.2±19.6
Veitsch
U
73.0
20.4
20.1
1060
2 %
1071
151.8±16.5
Veitsch-qtze
U
(63.3)
–
–
–
–
–
151.8±16.5
Pohorje
Pohorje1
U
10.9
15.6
14.8
1102
1 %
948
77.2±7.1
Pohorje2
U
78.3
15.5
14.6
890
1 %
897
98.1±7.7
Velka
U
52.5
16.4
16.0
814
1 %
828
95.8±6.8
Schladminger Tauern
Kleinsolk
G
117.8
31.1
30.6
1742
37 %
1779
172.5±16.2
Obertal
G
51.8
29.3
28.9
1800
33 %
1793
199±15
SaintNico
G
60.3
28.1
27.4
1792
25 %
1789
237.5±17.8
Untertal
G
67.8
30.8
30.3
1834
39 %
1808
178.1±15.4
Seckauer Tauern
Ingering
P
58.6
25.1
24.4
1679
16 %
1670
94.3±5.8
Krug
P
67.0
22.4
21.9
1606
8 %
1574
76.5±5.4
Rottenmann
G
32.2
28.0
27.2
1672
25 %
1654
200.1±15.9
Seckauer
P
37.7
21.7
21.2
1437
3 %
1362
71.3±4.8
Triebental
G
54.8
24.4
23.6
1590
13 %
1587
228.7±21.8
Styrian Basin
Pickel
U
27.7
7.5
7.0
406
0%
408
101.6±8.3
Stiefing
U
66.6
7.7
7.2
388
0%
394
114.3±8.5
a Catchments defined as previously glaciated (G),
partially glaciated (P), or unglaciated (U) in the Last Glacial Maximum
(LGM). Partially glaciated catchments were ice covered only in uppermost
regions of the catchment. b, c Mean catchment slopes are calculated
from both b 10 m digital elevation models (DEMs) and
c 80 m 1 arcsec DEMs. d Mean local relief calculated
using a 5 km moving window. e Thörl and Veitsch catchments
contained significant non-quartz-bearing lithologies. Area of quartz bearing regions shown in parentheses.
Deriving erosion rates from in situ produced cosmogenic
10Be
Use of the cosmogenic nuclide 10Be in river sand is now standard for
quantifying rates of erosion over millennial timescales in diverse landscapes
(Granger and Schaller, 2014; Portenga and Bierman, 2011; von Blanckenburg,
2005). Cosmic ray bombardment of Earth's surface produces these nuclides
in situ, and their concentrations reflect the time that minerals spend within
the upper few meters of Earth's surface. 10Be concentrations in quartz
collected from river sands reflect erosion rates spatially integrated across
the basin. We sampled 26 rivers in the Eastern Alps of Austria and Slovenia
for cosmogenic 10Be analysis, targeting both previously glaciated and
unglaciated catchments across the region (Tables 1–2). Sand was collected
from channel bottoms and active channel bars, integrating along ∼ 20 m
reaches at each river location. Samples were oven-dried and sieved to extract
the 250–500 µm size fraction. In addition to the
250–500 µm fraction, three samples were also sieved at
500–800 µm, so that we could check for grain size dependence of
10Be concentrations. Heavy and magnetic minerals were removed using
magnetic and density separation methods. Standard hydrochloric and
hydrofluoric chemical leaches removed non-quartz minerals and etched
weathering rinds from quartz to remove meteoric 10Be. We digested 40 g
of clean quartz in a 5 : 1 concentrated hydrofluoric acid : nitric acid
mixture, along with 215 µmg of an in-house-developed 9Be
carrier derived from phenakite crystal. Beryllium was extracted from digested
quartz and oxidized using methods outlined in von Blanckenburg et al. (1996).
We measured 10Be / 9Be ratios on BeO targets with accelerator mass
spectrometry at ETH Zürich in Switzerland in June 2010 and 2011.
Initial accelerator mass spectrometry (AMS) results are normalized to AMS standard S2007N, with an isotope
ratio of 2.81×10-11. All results are renormalized to the
07KNSTD standardization from Nishiizumi et al. (2007). Table 1 presents analytical results. 10Be
concentrations are blank corrected by subtraction (average
10Be /9Be ratio of five chemical processing blanks =2.72±2.21×10-15).
10Be concentrations were used to derive catchment-wide erosion rates,
following scaling factors from Dunai (2000), absorption laws for nucleonic
interactions from Schaller et al. (2002), and muonic absorption laws from
Braucher et al. (2003). We determined basin-averaged production rates using
an ArcGIS-based production model, 10 m gridded elevation data, a sea level,
high-latitude total production rate of
4.0 atoms gqtz-1 year-1 (Phillips et al., 2016), and
assuming that slow and fast muons contribute ∼ 1.2 and 0.65 % of total
production (Braucher et al., 2003). Corrections for skyline shielding were
made following Norton and Vanacker (2009). We calculated snow shielding
following Norton et al. (2008) using elevation–snow-depth relationships
previously determined in the Swiss Alps by Auer (2003). Elevation–snow-depth
relationships likely vary spatially and temporally across the Alps; however,
these estimates provide the best available constraints on snow shielding. Because
our cosmogenic 10Be concentrations only reflect erosion rates in the
parts of the basin with quartz-bearing lithologies, parts of drainage basins
with carbonate terrains were excluded to calculate integrated basin 10Be
production rates (Table 1). 10Be-derived erosion rates are presented in
Table 2. We compile other 10Be-derived erosion rates from across the
Alps to gain a regional picture of Holocene erosion. These rates, published
in nine different prior studies (Delunel et al., 2010; Glotzbach et al., 2013;
Legrain et al., 2015; Norton et al., 2008, 2010b, 2011; Savi et al., 2014; Wittmann et al., 2007, 2016),
were derived assuming different sea level, high-latitude (SLHL) production
rates. To aid comparison of rates across disparate studies, we recalculate
all compiled rates using a consistent SLHL production rate of
4.0 atoms g-1 yr-1, regardless of original scaling factors.
Digital terrain analysis
Catchment topography was analyzed using two digital elevation models: 10 m
gridded data available from the Austrian Geological Survey (BEV,
http://www.austrianmap.at/) and 3 arcsec (∼ 80 m in this
region) gridded data from the Global Shuttle Radar Topography Mission (SRTM).
Terrain attributes, stream networks, and catchment extents were extracted in
ArcGIS on both sets of gridded data. Catchments were delineated upstream of
sample points (Table 2). Several catchments lay within Slovenia and outside
the extent of the Austrian 10 m data. Table 2 provides basin-wide terrain
attributes, including a comparison of variables extracted from 80 and 10 m
digital elevation models. Though the scale of these digital elevation models (DEMs) is very different,
the resulting topographic metrics are quite similar, with only a slight
lowering of average slopes in the coarser data. This similarity highlights
the fact that local slopes are largely controlled by landscape-scale
patterns. If local slopes were variable on a small spatial scale, then
analysis of 10 and 80 m gridded data would likely result in notable
differences (e.g., Zhang and Montgomery, 1994).
Results
10Be-derived erosion rates vary from 39 to 238 mm ky-1 across our
study catchments of the Eastern Alps. Catchment-wide erosion rates generally
show distinct patterns based on their geographic setting (Fig. 2a, b;
Tables 1–2). Rates across Gleinalpe and Koralpe range from 39 to
94 mm ky-1. The erosion rates measured in catchments entirely within
the Styrian Basin (101–114 mm ky-1; Fig. 1) are notably higher than
the rates within the adjacent Koralpe range. Streams in these lowland-basin
catchments of the Styrian Basin drain largely unconsolidated sediments of
Miocene age that form low-relief hillslopes. Tributaries of the Mürz
River valley in the northeast exhibit a broad range in erosion, from 81 to
151 mm ky-1. Catchment erosion rates in the Schladminger and Seckauer
Tauern range from 71 to 238 mm ky-1. The highest rates in this region
(> 170 mm ky-1) correspond to basins that lie within the range of
the Last Glacial Maximum ice and reflect the region that was previously
glaciated (see Fig. 1). Within the Seckauer Tauern, at the edge of Last Glacial
Maximum (LGM) ice,
several basins were only partially glaciated (Fig. 2), such that only small
portions of the catchment (uppermost elevations) show evidence of glacial
impact. Measured erosion rates in these catchments are similar to unglaciated
rates in other portions of the study area.
(a) Study catchments show increasing mean slope with mean
elevation (grey circles). The percent of slopes > 35∘ within these
basins increase nonlinearly with elevation (blue squares), such that
catchments at high elevations > 1500 m show strong variation in the
distribution of steep, threshold-style hillslopes. Small unglaciated basins
studied by Legrain et al. (2015) in this same region show little systematic
variation in slope with elevation (small open circles). Instead of reflecting
the broader regional signal, mean slopes of these smaller basins are likely
controlled by their position with respect to river knickpoints and the proportion
of the catchment that is actively incising. (b) Catchments sampled
in this study range from ∼ 3 to 950 km2 (Table 2). Catchment size
appears to have limited systematic influence on mean basin slope and measured
erosion rates, since basins of similar size show significant variation in
both.
The broad regional differences in basin erosion rates are complemented by
relationships between these rates and the topographic form of the basins
(Fig. 2a, b). Mean basin slope generally increases with mean elevation
(Fig. 3a; r2=0.64, p<0.001). This increase in slope is partially
controlled by a marked increase in the proportion of slopes that are steeper
than 35∘ at high elevations (Fig. 3a). Measured erosion rates also
generally increase with increasing mean basin slope (Fig. 2b; r2=0.58,
p<0.001). These correlations persist across catchments of disparate
drainage areas (Fig. 3b).
(a) Map of sampled basins across the Eastern Alps,
color-coded for erosion rates. (b) Cumulative slope distributions
color-coded by sample region (same as Fig. 2) show that catchment morphology
follows geographic groupings, with low-slope end-members in the Styrian Basin
and high-slope end-members represented by previously glaciated basins of the
Schladminger and Seckauer Tauern (dotted lines). Slope distributions across
these basins also complement measured erosion rates.
(c, d) Frequency and cumulative distributions of basin slope show
that rapidly eroding, previously glaciated basins tend to have higher mean
and modal slopes than more slowly eroding basins. Colors in panels
(c) and (d) correspond to the scale for basin erosion shown
in panel (a).
Variation of slope and elevation within sample catchments. Elevation
is binned between 50 m contours, and catchment slopes are averaged within
these bins. Hillslope angles are distinctly distributed with basin elevation
between slow and rapidly eroding catchments, with highest slope angles found
at middle elevations of previously glaciated basins and highest elevations of
non-glaciated basins. Symbol colors correspond to the scale for basin erosion
shown in Fig. 4a.
Catchments in the Schladminger Tauern and northern parts of the Seckauer
Tauern were glaciated in the Pleistocene (Fig. 2a). These catchments exhibit
the most rapid erosion rates across the study area (Fig. 4a;
170–230 mm ky-1), and have higher average slopes than non-glaciated
and only partly glaciated basins (Fig. 4b–d). Hillslope gradients of
unglaciated and partially glaciated basins tend to be normally distributed
about mean and modal slopes that range widely from ∼ 5 to 25∘
(Fig. 4c). In comparison, previously glaciated basins show higher mean and
modal slopes > 25∘ with a negative skew towards low values.
Furthermore, we find that these two domains also show clear distributions of
slope with elevation. By segmenting each catchment into distinct elevation
bins between 50 m contours, we determined the relationship between mean
slope angle and mean elevation within the bins (Fig. 5). Dissimilar patterns
emerge in how slope varies with elevation within previously glaciated and
non-glaciated catchments. For example, high-gradient hillslopes within the
non-glaciated basins tend to occur at the upper portions of these basins,
well above the mean elevation. However, the steepest hillslopes of glacially
sculpted basins are found at elevations well below the mean (< 1500 m
elevation compared to average elevations of ∼ 1800 m).
Discussion
Topographic controls on erosion rates
Correlations between 10Be-derived erosion rates and mean catchment slope
(Fig. 2b) are consistent with trends previously observed across other diverse
mountain ranges (e.g., Cyr et al., 2010; Ouimet et al., 2009), such that
erosion rates increase nonlinearly with mean catchment slope. This
nonlinear relationship may result either from the dominance of threshold-driven landsliding in controlling erosion across the range (e.g., Montgomery
and Dietrich, 1994) or from nonlinear diffusive transport (Roering et al.,
2001). Either of these erosional mechanisms may result in a similar form to
the nonlinear relationships between erosion rates and slope (e.g., DiBiase
et al., 2010). Considering that both erosion rates and catchment mean slope
correlate with the proportion of the catchment that exceeds 35∘
(Fig. 2b) and that these steep slopes generally are void of soil cover, it
is likely that local slopes > 35∘ within catchments undergoing
erosion rates of ∼ 200 mm ky-1 correspond to thresholds for soil
cover in this landscape.
Though we find a general trend of increasing erosion rates with basin slope,
this pattern is largely shown by two unique clusters of data: unglaciated
basins that exhibit low erosion rates and low to moderate slopes and
previously glaciated basins with high slopes and erosion rates. Within each
of these domains, the erosion-rate–slope relationships are less clear.
Furthermore, it is surprising that several basins at the lowest elevations in
the Styrian Basin to the south erode at faster rates than catchments in the
middle uplands of the Koralpe range (Figs. 2, 4). These slightly higher
erosion rates at low elevation have previously been linked to both weaker
lithologies and tectonic transience in the Koralpe range, such that a wave of
incision and erosion propagating upslope has accelerated erosion but not yet
reached upper relict landscapes. Legrain et al. (2015) mapped the transition
between incising and upland relict hillslopes and found that erosion rates
in small basins (< 1 km2) across Koralpe correlate with the fraction
of the catchment below transient propagating knickpoints. Catchment
morphology and erosion rates within these small basins show greater
variability at mid-to-low elevations than the larger basins studies here, and
reflect the local topographic and erosional response of hillslopes to
transient river incision (Legrain et al., 2014; Robl et al., 2008). Higher
rates in the Styrian Basin compared to the uplands of Koralpe therefore likely
reflect this erosional response to river incision and tectonic processes
across the range rather than lithologic differences. This local-scale
topographic variability and transience attributed to tectonics is likely only
reflected in the high rates in the Styrian Basin and is not otherwise strongly
reflected in the large basins studied in this paper, which we believe
integrate spatially across this variability.
Glacial legacies and their influence on Holocene erosion in the Eastern
Alps
We hypothesize that topography–erosion relationships reflect the control
of glacial legacies on mountain erosion in this Alpine system. Indeed, we
find that the fastest eroding catchments were previously eroded in the
Pleistocene and have higher averaged slopes than unglaciated ones
(Fig. 2). However, basin average slope angles only provide limited proof of
concept since we find a wide range of mean values across both unglaciated and
glaciated basins. The distribution of slopes within each catchment provides an
added topographic fingerprint of past glaciation (Fig. 3). Mean slopes tend
to be greater at low elevations than high elevations in the faster eroding,
glacially sculpted catchments. This detailed distribution of slope and
elevation within glaciated basins is not distinct from the general trend of
increasing mean basin slope with mean basin elevation across the study area
(Fig. 3a). The distribution of slope by elevation within basins (Fig. 5)
therefore represents a local signal not reflective of the larger regional
trend, and we consider it a fingerprint of past glacial sculpting, consistent
with characteristic slope–elevation curves and relief in glacial and
non-glacial catchments (Robl et al., 2015; van der Beek and Bourbon, 2008).
Considering that these previously glaciated basins erode at rates roughly
3 times faster than average non-glaciated basins, this slope distribution
similarly provides a predictive tool for erosion rates (Fig. 5).
Importantly, past glaciation may have other impacts on measured erosion rates
that must also be considered. 10Be-derived rates presented in this study
are calculated assuming erosion has been constant for sufficient time for the
landscape surface to attain steady-state 10Be concentrations. This
assumption may not be correct when erosion rates have been variable over the
integration time of 10Be accumulation or if the surface has been zeroed
by deep erosion, as is likely the case for previously glaciated areas.
Furthermore, this assumption may result in nontrivial overestimation in
calculated erosion rates, especially in slowly eroding terrain (Glotzbach et
al., 2013; Norton et al., 2010b; Wittmann et al., 2007). Using non-steady-state calculations from
Lal (1991) and assuming that 10Be concentrations at the surface began to
accumulate only after deglaciation at 15 ka would result in as much as a
9 % difference in calculated erosion rates from the steady-state rates
presented in Table 1 (based on steady-state erosion rates for glaciated
basins of 172–203 mm ky-1). This steady-state assumption therefore
results in a nontrivial but still relatively small bias to calculated
erosion rates, considering that our glaciated basins erode roughly a factor-of-2
times faster than non-glaciated basins and up to a factor-of-5 times
faster than background erosion rates near 40 mm ky-1.
Another complication of measuring 10Be-derived denudation rates in
complex previously glaciated terrain results from the potential that glacial
erosion products, potentially remobilized from storage in moraines or flood
plains, will have inherited 10Be concentrations associated with
preglacial times. This may occur if glaciers have incompletely zeroed
surface concentrations via shallow erosion (Delunel et al., 2014) or if
glacial advance overrode soils and later incorporated them into glacially
eroded sediments (Wittmann et al., 2007). In this case, 10Be
concentrations may instead underestimate erosion rates, though this effect
should be the largest in currently glaciated or recently glaciated
catchments. A final complication may arise due to the fact that previously
glaciated catchments may contain high-altitude, low-gradient areas such as
cirque valleys. If these portions of the landscape did not deliver sediment,
perhaps because it was trapped in cirque lakes, then they should be excluded from
calculated production rates. Hence catchment-wide production rates would
decrease and so would denudation rates. This could result in erosion rates
in glacially conditioned catchments being lower than calculated.
Competing controls on Holocene erosion rates
We find compelling evidence of topographic control on erosion; however, other
competing hypotheses may explain some of the range of erosion rates found
across the region. For example, other climatic controls such as precipitation
rates have been invoked to explain fast erosion rates in high peaks of the
Alps (Anders et al., 2010). In the Western and Italian Alps, several lines of
evidence were used to suggest that post-glacial climates drive the bulk of
exhumation and erosion in the region. Multiple studies have suggested that
temperature-driven frost-cracking processes likely control Holocene erosion
rates, based on correlations between elevation and erosion rates (Delunel et
al., 2010; Savi et al., 2015). It might be hypothesized that the intensity of
frost-cracking processes is (or was) greatest in our previously glaciated
catchments, thus potentially explaining the distribution of erosion rates.
Across our study basins, catchment mean slope and elevation are correlated
(Fig. 3a); however, elevation poorly correlates with the fraction of steep
(> 35∘) slopes, notably in the rapidly eroding, previously
glaciated basins where the abundance of steep topography varies widely
despite similar mean basin elevations. Therefore, the elevational proxy for
frost cracking does not correspond to topographic indicators of rapid erosion
in our study area. Furthermore, we find large differences in erosion rates in
basins of the same elevation (Table 2). While frost cracking may enhance
erosion at Alpine sites, it does not appear to explain the patterns and
variability in erosion rates across our catchments. Furthermore, mean annual
precipitation is likely a poor indicator of erosion in our unglaciated
catchments since areas of the Mürz Valley that display the highest
non-glacial erosion rates tend to be drier than more slowly eroding portions
of the Koralpe range (BMLFUW, 2007).
Our measured hillslope erosion rates in the Eastern Alps may also be driven
by rock uplift and river incision across the region. Previous work has
suggested that glaciation during the LGM may drive a Holocene erosional
response across the Alps and thereby enhance uplift (Wittmann et al., 2007).
Providing a mechanism to engineer this link, Norton et al. (2010a) used
observations of correlated river knickpoints and LGM equilibrium line
altitudes (ELAs) to suggest that the topographic imprint of glacial erosion
leads to increased river incision post-glacially, which in turn strengthens
the positive feedback between rock uplift and erosion. Could this same
mechanism be invoked to explain high erosion rates in our previously
glaciated catchments? If catchment erosion were driven by increased river
incision, then we would expect steeper stream gradients in rapidly eroding
catchments. Legrain et al. (2015) observed correlations between higher
normalized stream steepness indices and erosion rates within the Koralpe
region of our study area but only within small non-glaciated catchments.
Therefore, evidence of incision-driven hillslope erosion was found only in
the absence of glacial forcings. This finding led Legrain et al. (2015) to suggest that tectonic uplift in the Eastern
Austrian Alps could reasonably explain both 500 m of relief change and a
factor-of-3 spatial variation in Holocene erosion rates. The scale of uplift
(encompassing both the Pannonian Basin and entire eastern end of the Alps)
may reflect deep-seated lithospheric processes (Legrain et al., 2015), and
seismic anisotropy suggests slab detachment could provide the tectonic
mechanism for surface uplift in this Eastern region (Qorbani et al., 2015).
Erosional response to rock uplift may explain local erosional differences
within the non-glaciated catchments studied here. For example, following
Legrain's model, low-elevation catchments in the Styrian Basin lie within the
incised region below river knickpoints, while higher-elevation catchments in
Koralpe with lower erosion rates include significant portions of “relict
terrain”. Importantly, this surface uplift mechanism cannot similarly
account for erosional differences between glaciated and non-glaciated basins.
The glaciated basins studied here would fall within the “relict landscape”
region mapped by Legrain et al. (2015) as above river knickpoints, and
therefore our high erosion rates do not correlate with the area below
knickpoints. Furthermore, if uplift drove erosion in these basins, then we
would expect to see higher area-normalized stream gradients in more rapidly
eroding catchments reflecting the enhanced river incisional response.
Figure 6 shows local hillslope gradients within each catchment, binned by
accumulation area, the upslope and upstream contributing area for all points
within the basin. While mean basin slopes are generally higher in more
rapidly eroding glaciated catchments, these higher gradients occur only at
the uppermost portions of the catchments – in small upslope accumulation
areas less than ∼ 102 m2 that are within the hillslope
domain. By comparison, local stream gradients in glaciated and non-glaciated
basins are similar in the larger contribution areas (approaching
105 m2) that reflect the fluvial domain. The variability in
within-basin slope seen only in low contributing areas indicates that the
morphological differences within our large catchments studied here are driven
by processes solely within the hillslope domain. The lack of evidence of
incision-driven erosion further supports our conclusions that topographic
forcings, and not rock uplift, are largely responsible for the patterns in
erosion we observe here.
Slope–area plots for catchments across the study area. Accumulation
area is calculated on a per pixel basis from the 10 m digital elevation
model and represents the upslope contributing area (drainage area). Slopes
within each catchment are binned by increments of 0.2 log10
accumulation areas to show downslope and downstream changes in mean basin
gradient. Binned values are color-coded by erosion rate and correspond to
the basin erosion scale provided in Fig. 4a. Data points in large
accumulation areas (> 105 m2) reflect local stream steepness
and plot within a similar range of values despite disparate erosion rates.
However, data points in small accumulation areas (< 104 m2)
represent upslope hillslope gradients and have distinct steepnesses based on
the erosion rates of the basin and the glacial history. These data largely
reflect disparate hillslope steepnesses between glaciated (rapidly eroding;
green) and unglaciated (more slowly eroding; pink) catchments.
(a) Published erosion rates across the European Alps range
from ∼ 40 to 2100 mm ky-1, recorded by over 100 cosmogenic
samples from nine studies that report both mean catchment slope and erosion
rates. Published erosion rates were rescaled to a consistent sea level,
high-latitude production rate of 4.0 atoms g-1 year-1. Symbol
size reflects erosion rate, and symbol color reflects past glacial history
(red: previously unglaciated; blue: previously glaciated). (b)
Across the range, these rates vary only weakly but significantly with mean
basin slope (linear fit r2=0.23; exponential fit r2=0.34).
(c) Compiled erosion rates plotted against sample longitude (data
provided in the Supplement). Symbols for individual samples are color-coded as
in panel (b) but with slight transparency so as to increase
visibility of average erosion rates binned by 1∘ latitude (grey
ovals). The y axis error bars reflect standard deviation (standard error is
smaller than symbols). Despite variations in surface uplift, precipitation,
and other potential controlling variables, we find little systematic
east-to-west variation in average Holocene erosion rates across the range.
Only rates in our easternmost study region appear to vary significantly from other portions
of the Alpine range.
Erosion and topography across the Alpine range
While post-glacial topography largely explains the range of erosion rates
found at the far end of the Eastern Alps, we note that these measured erosion
rates are still significantly lower than measurements across other regions of
the Alps (Fig. 7a). The highest rates measured in our study region are
amongst the lowest measured across the Alpine range. Compiling previously
reported cosmogenic 10Be-derived rates across the Alps, we find that mean
basin slope and Holocene erosion rates are generally weakly correlated
(linear regression r2=0.26, p<0.001), providing limited predictive
power for assessing erosion patterns (Fig. 7b) on an orogen scale. A lack of
correlation is not surprising at high mean slope angles and rapid erosion
rates since erosional processes become nonlinear approaching threshold slope
angles (e.g., DiBiase et al., 2010). Poor correlations between most
topographic metrics and Alpine erosion rates have been noted before (e.g.,
Norton et al., 2011; Salcher et al., 2014; Wittmann et al., 2007).
Complexities in lithologic variation can partially explain the high scatter
in erosion rates at steep gradients (e.g., Norton et al., 2011) since rock
strength and fracturing may control slope thresholds. Weaker lithologies
often correspond to low hillslope gradients (e.g., Norton et al., 2011) and
normalized stream steepness indices (Sternai et al., 2012) in the absence of
other controls. Despite some lithologic influence, orogen-scale controls on
Holocene denudation rates have remained relatively elusive.
We might expect Holocene erosion to reflect uplift or rates of long-term
exhumation across the range. In the central Alps, some of the observable
modern rock uplift has been attributed to a combination of an isostatic
response to Holocene erosion (Champagnac et al., 2007; Wittmann et al., 2007)
and ice melting (Barletta et al., 2006). Though some dispute this latter
mechanism as a driver of modern rock uplift (e.g., Persaud and Pfiffner,
2004), recent flexural models based on glacial ice thickness suggest that
glacial isostatic adjustment primarily explains the magnitude and patterns of
modern uplift (Mey et al., 2016). Long-term exhumation rates from
thermochronometric ages have been partially attributed to deep tectonic
processes that increased during the Cenozoic (Cederbom et al., 2011),
possibly due to slab detachment focused primarily in the west (Baran et al.,
2014; Fox et al., 2014, 2015) but also potentially observable in the Eastern
Alps (Qorbani et al., 2015). Short-term rates of uplift and erosion and
modern topographic metrics appear to poorly or only partially reflect this
broad tectonic signal (Koons, 2009; Norton et al., 2011; Vernon et al.,
2009), though along-orogen tectonic differences cannot be ruled out as contributing to the variation in erosion rates (Baran et al., 2014). However,
on an orogen scale and with the exception of the far Eastern Alps where
erosion rates are low, average erosion rates vary little with longitude
across the range despite high local variability (Fig. 7c).
Climate variability should also be considered in controlling erosion on an
orogen scale. Precipitation patterns vary across the range, with highest LGM
precipitation occurring on the northern slopes of the Alps and decreasing to
the south and east (Florineth and Schlüchter, 2000). Modern precipitation
varies from ∼ 400 to > 3000 mm yr-1 across the orogen, also
generally decreasing to the east, and small-scale variations in topography
have a pronounced effect on local patterns (Isotta et al., 2014). This means
that precipitation varies on both large and small scales across the orogen.
There is reason to believe that modern precipitation gradients should control
Holocene erosion and sediment transport by influencing the discharge of
sediment out of a basin, controlling landslide thresholds, and by influencing
the magnitude of river incision. While similar relationships have been
observed across other mountain ranges (e.g., Bookhagen et al., 2005),
explicit links between modern precipitation and post-glacial hillslope
erosion remain elusive in the Alps (Bennett et al., 2013; Schlunegger and
Norton, 2013). However, multiple lines of evidence, including data presented
here, suggest that paleoclimate may instead have a greater and lasting
imprint on landscape topography and erosion. Anders et al. (2010) found
that precipitation is inversely correlated with the elevation of cirque floors in
portions of the Swiss Alps, suggesting a climate-driven glacial buzzsaw
across the region. Furthermore, glacial erosion during the Pleistocene
resulted in notable increases in valley-scale topographic relief (Sternai et
al., 2012; Valla et al., 2011). Because these glacially driven topographic
legacies persist to the modern day, we propose that modern hillslope response to
glacial history can partly explain local-scale variability in erosion rates.
Though focused locally in the Eastern Alps, our new erosion rates and
topographic analysis add weight to an increasingly compelling argument that
local Holocene denudation rates across the Alps, which often poorly reflect
other broader tectonic and climatic controls, are overprinted by the local
topographic legacy of glacial sculpting. It is not yet clear whether the
topographic legacy and its influence on Holocene erosion directly reflects
the local magnitude of past glaciation (e.g., LGM ice thickness) or perhaps
whether erosional and morphometric variability in previously glaciated portions of
the Western and central Alps is especially variable since modern hillslope
response to deglaciation may be considered transient.