Long-term patterns of erosion of hillsides due to earthquakes caused by the earthquake form a mountainous landscape

Brief summary

Widespread landslides due to storms or earthquakes are a predominant erosion mechanism in mountainous landscapes. If landslides happen repeatedly in certain locations within a mountain range, they will dominate the landscape development of this section and can leave a mark on the topography. Here, we track the source of corrosion with a new mixture of isotopic and molecular composition of the organic material deposited in Lake Baringa, New Zealand. The source of erosion has changed significantly after four major earthquakes over 1,000 years. Post-earthquake periods caused the erosion of organic matter from an average height of 722 + 329 / −293 m and provided 43% of the sediments in the core, while the periods of overlap were due to low elevations (459 + 256 / /226 m). These results are the first evidence that large, frequent earthquakes can continually focus on erosion at high altitudes, while intervals between overlaps appear to be less effective at modifying top parts of the terrain.

Introduction

The steep terrain of active mountain belts appears from the interaction between tectonic lift, river slit, and landslide. When competing hills and hills lead to hillside slopes to the point where they reach the gravitational failure threshold, hill slope erosion through ground slipping actions to reduce relief in these landscapes (1-3). Consequently, a landslide can be considered as a negative response to changes in the rate of nasal fissure in conventional perspectives of “threshold” conditions (1). However, both and modeling studies have shown that landslides dominate rates of hill slope erosion and provide sediments for river systems that in turn mediate river slit rates (4-6). It may also cause migration to split the drainage and river piracy that controls landscape development (7-9). Consequently, the spatial and temporal distribution of slippage should have a first-class effect on the development of landscapes in active mountain belts (10).

Storms and earthquakes can lead to thousands of landslides (11, 12) with different spatial patterns due to the way in which they affect the forces of the body within hillsides and promote gravitational failure. For example, stormy rain causes landslides by increasing the pressure of pore fluids, which can be exacerbated at low elevations on hillside slopes due to leakage (13, 14). Consequently, it is believed that the landslide caused by precipitation leads to erosion of low elevations on hillsides (15). In contrast, earthquakes may preferably lead to high-altitude landslides on hillsides (16, 17), due to the topographic amplification of strong ground movements at hilltops (18, 19). These observations support the hypothesis that the morphology of the hills in mountain belts is controlled by a dominant landslide (16, 20). This hypothesis is supported by differences in hill morphology between mountain belts dominated by either landslide caused by precipitation or an earthquake (20). However, the final test requires evidence that the spatial pattern of landslide predicted by the theory observed during discrete trigger events translates into coherent spatial patterns of mound slope erosion over millennial time scales (10, 20).

However, restricting the spatial patterns of erosion of the ramp slope due to multiple trigger events is a problem, given the long occurrence times of those events. Remote sensing is the most effective way to monitor the spatial patterns of landslides, but these datasets tend to extend individual events up to several decades at most (2, 5, 12). The short duration of these records indicates that we cannot assess whether the spatial patterns associated with landslides are causing events to continue over time scales related to landscape development. Sedimentary basins with watershed depleting mountainous terrain have the ability to archive millennium-wide records of landslides caused by earthquakes, rains, and related sediment flows (21-24). If we can solve the source of sediments in these records, especially in terms of high wear, then these records can allow us to track long-term spatial patterns of hill slope wear by ground slipping.

Here, we have developed approaches to reconstruct past erosion and depth using a new mix of geochemical techniques applied to organic materials in lake sediments. Specifically, we analyze the stable carbon isotope ratio for bulk organic matter (C13Corg), nitrogen isotope ratios in bulk sediments (δ15N), abundance and ratio of alkanes n (carbon preference index, CPIn-alkanes), radioactive carbon activity of bulk organic matter (modern part) , F14C), and isotopic composition of hydrogen from long-chain alkane (CDC29-n-alkane) (see Materials and Methods). These variables are expected to vary with higher plant growth or soil formation (25, 26) and soil depth (27, 28). We combine these measurements to track the source of erosion in lake sediments fed by river catchments that drain the front portion of the Southwest Alps, New Zealand (Figure 1; materials and methods). We first assess the composition of organic matter in soils collected along height and depth grades, before studying the sedimentary record of Baringa Lake, which archives cycles of flow of sediments destroyed by earthquakes and rains over a thousand years (23). Our analysis reveals that the landslide caused by the earthquake leads to erosion of high altitudes in watersheds, the formation of hill morphology and may lead to migration dividing the drain.

Figure 1: Study preparation and topography for Lake Baringa catchment and soil sample height sections.

(A) Southern New Zealand alpine mistake and study sites. The blue, red and white squares indicate locations (b), (c) and (d), respectively. (B) The location of Lake Baringa and the core of the PA6m1 sediment. The colored polygon shows a slope of the watershed of Barringa Lake. Gray and black lines are lines with a length of 460 and 720 m, which is the average wear height between sediments and post-seismic. (C) Soil sample sites from the Jebel Fox intersection above the terrain of the 8-meter digital height model. (D) The location of soil samples along the Alex Knop section.

The result: the chemistry of organic matter in the southwestern Alps soil

To assess the degree to which the geochemistry of the organic matter in eroded sediments symbolizes the height of its source or the depth of erosion, we first examine the collected soil along two elevated sections on the western side of the Southern Alps (Figure 1 and Figure S1; materials and methods). The samples collected from Mount Fox Trail, located 55 km northeast of Lake Baringa, cover elevations from 250 to 1160 AD. Samples of the Alex Knop trail cover elevations from 290 to 1290 m and located further to the northeast (Figure 1 and Fig S1; see Materials and Methods). The Mount Fox intersection was used to develop relationships between soil organic geochemistry and elevation due to its closest proximity to Lake Baringa and similar soils (Figure S1, D, and E), while Alex Knop intersection was used as an independent test of these relationships.

In Fox Mountain, the values ​​of δ13Corg of soil A are positively correlated with the sample height (r2 = 0.61, n = 8, P <0.05; Figure 2a), which varies by ~ 2.7 ‰ over the height of 750m (Fig. 2a). These trends are similar to those observed in other mountain forests of plants (25) and organic matter in soils (29). An increase in δ13Corg values ​​with elevation may reflect a mixture of atmospheric pressure decreases and Pco2 concentrations (partial carbon dioxide pressure), affecting isotopic fractionation during photosynthesis (25, 30), and / or partial pressure of oxygen concentrations (Po2) (31) . Org13Corg also positively correlates with the depth of soil organic material sampling (Figure 2B). The increase in قيم13Corg values ​​corresponds to the increase in soil depth with the roles of degradation of organic matter (32) and the addition of partially derived organic carbon (OC) from the rocks (33).

Figure 2 The relationship between δ13Corg and CPI-alkanes of organic matter in the soil of Mount Fox as a function of the height and depth of the soil.

(A) Positive linear relationship between CPIN alkenes and δ13 degree of soil horizons A with higher sampling. (B) The positive linear relationship between C13Corg and depth in two soil coils. (C) The negative linear relationship between CPIN alkenes and depth in two soil files.

Concentrations of n-alkanes in soils differ by depth aspects in three degrees of volume ranging from 1.4 to 1510.1 mcg-1 soil (Σalk) or 0.1 to 39.7 mg g-1 OC based on the normal OC concentration (Λalk). The molecular abundance distributions of n-alkanes show a significant preference for odd to even carbon numbers and a higher abundance of alkanes C27, C29 and C31n (Table S1). The consumer price index for long-chain alkanes (see Materials and Methods) has an average value in all soil samples of 12.0 ± 2.9 [±SD (σ) unless otherwise stated, n = 19]Similar to other ground samples (34, 35). We find that the CPIn alkane values ​​for soil A are positively correlated with the sample height (Figure 2A). This is consistent with measurements from some other mountain soils (36) and the observed links between soil temperature and CPIN values ​​(37). This high CPI link may either reflect changes in soil degradation rates with altitude (and thus temperature), or it may also reflect a change in vegetation type (38). We find that the values ​​of CPIN alkanes in two soil coils show a negative correlation with soil depth (Figure 2b), with lower CPIN alkanes which again reflect increased degradation with soil depth.

The values ​​of N15N and F14C of the organic matter in the soil differ with depth, but not the height (Fig. S2), consistent with these variables that are closely related to the degradation of the organic matter over time with soil development (27, 28, 39). The values ​​of 29DC29-n-alkane of soil A are not related to the height at Mount Fox, but they are plotted within the wide negative direction between δDC29-n-alkane and the height specified by Zhuang et al. (40) In the Hast River and adjacent watersheds south of Lake Baringa (Figure S3).

In terms of source tracking, the combined δ13Corg and CPI values ​​for the organic material provide a tool for restricting both the height and depth of eroded soils in this setting. This is because the C13Corg and CPI values ​​are positively correlated with height (Fig. 2a), while correlated with soil depth (Fig. 2b, c). قيم15N and F14C values ​​provide an independent restriction on soil depth, while CDC29-n-alkane can independently track altitude.

Lake sediment record from the Southwest Alps, New Zealand

A sedimentary core of 6 meters long collected from Lake Barenga records four megawatts (torque size)> 7.6 earthquakes as rapidly precipitating layers formed by the collective kosmic sub-wasting (23, 24). Previous studies have described these deposits and their chronology in detail (23, 24). In summary, sediments among these coseismic sediments represent deposition on multiple seismic cycles, each characterized by a stage of post-seismic precipitation and correlation. The primary chronology is based on plant activity 14C macrofossil (23, 41), and the cosmic deposits have been associated with independent restrictions on the timing of past earthquakes (42, 43). The accumulation of elevated sediments after each earthquake demonstrates that the post-seismic flow of sediments is five times between average interfering periods for approximately 50 years after each earthquake (24).

Lake Paringa is fed from watersheds that flow steep slopes of hills and vegetation near the fault of the Alps. The Windbag Creek (31 km 2) basin drains the front of the range and distributes sloping angles similar to the larger adjacent watershed (21) and plant slopes from 16 to 1,420 meters. Plants and soil are similar to samples on Mount Fox (Figure S1). Since the catchment length is relatively short, the composition of suspended suspended river organic materials may not change significantly during river transport (44, 45), compared to the Feakins et al study. (46), where mountain rivers fed 10 to 100 km of low flood plains. Thus, the theoretical and molecular formulations of organic matter of lake sediments are likely to be representative of hill slope source signatures.

Lake Baringa core was previously analyzed for total OC (TOC) to nitrogen ratio (C / N), C13Corg, F14C in bulk organic matter, and CPIN alkanes to assess OC corrosion across the four seismic cycles (21). Post-seismic stages are characterized by enriched OC 13C, with an average δ13Corg = −27.2 ± 0.6 ‰ (n = 101), and have C / N values ​​above 18.5 ± 6.9; The interfering phases have mean13Corg = −28.6 ± 0.5 values ​​and C / N values ​​from 11.4 ± 1.4 (n = 63). These data reveal enhanced carbon accumulation rates for the biosphere after four earthquakes in the Alps. Frith et al. (21) They indicated that shifts in δ13C and C / N are more likely to reflect the corrosion and delivery of carbon derived from eroded soil due to deep landslides, but they indicated that there are no restrictions on soil formation in watershed sources.

To shed more light on the source of sediments derived from landslides deposited on multiple seismic cycles, in this study, we significantly increased the number of CPI-alkanes measurements (Figure 3) from Frith et al. (21) δ15N of bulk organic matter and CDC29-n-alkane (see Materials and Methods) were analyzed below the pulp (Figure 4). Average values ​​of δ15N are 1.4 ± 0.5 ‰ in interference and 1.1 ± 0.9 ‰ in post-seismic phases. These mean values ​​mask significant changes in قيم15N values ​​after each earthquake, especially after the 1717m event, which initially tracks C13Corg values, before being separated after a period of precipitation (Figure S4). Values ​​of δ15N are negatively correlated with F14C of bulk organic material in the heart, with more enriched samples of 14C having lower15N values ​​(Fig. 4 and Fig S5A). The values ​​of δ13Corg, δ15N and F14C can be separated from a shift in the wear source in terms of height (affecting δ13Corg) and soil depth (affecting C13Corg, δ15N and F14C).

Fig. 3 Geochemical analysis, typical height and depth of the PA6m1 nucleus.

(A) Formation of stable isotopes to OC (C13Corg, ‰, analytical uncertainty smaller than symbol size) from Frith et al. (21) The ratio of TOC to nitrogen ratio (C / N; colors). (B) the variation in the consumer price index for n-long alkanes. (C) Typical wear and depth (color) corrosion of Eqs. 1 and 2. The gray bars show massive cosmic inflation, a sign of large earthquakes in the Alps. Heavenly bars show post-seismic deposits [as per (23)].

Figure 4 Evolution of the expected erosion source at Lake Baringa during the earthquake phase of 1717 AD.

(A) The expected height and depth of organic matter according to Figure 3, with a gray stripe showing the cosmic precipitations, the cyan showing the post-seismic phase of the sedimentation, and the white showing the overlap period [as per (23)]. (B) Formation of hydrogen isotopes from long-chain alkanes (CDC29-n-alkane, ‰) (note the inverse scale). (C) Radioactive carbon activity of bulk organic matter in the heart (modern part, F14C). (D) Formation of isotopes of nitrogen from bulk organic matter.

Concentrations of n (nalk) alkanes do not differ between post-seismic (mean Λalk = 1.1 ± 0.4 mg g-1 OC, n = 31) and translator (mean alk = 1.1 ± 0.3 mg g-1 OC, n = 16) deposits . However, the relative abundance of alkanes varies. CPIn alkanes are slightly higher in post-seismicity (mean CPIn alkene = 9.4 ± 2.3) than in fetal deposits (mean CPIn alkene = 8.6 ± 1.4), although this is not statistically significant (test t, P = 0.07). Within the post-seismic stages, the values ​​of CPIN alkanes are generally higher immediately after the earthquake marker (most notably in 1717 AD where we have the highest sampling accuracy), before gradually decreasing to a relatively constant interfering value (Figure 3).

C29n-alkane is thought to originate from higher terrestrial plants, and its isotopic composition of hydrogen (δD) in river sediments has been shown to be sensitive to upstream source height from the sample site (26, 40). We measured CDC29-n-alkane for the last seismic cycle (1717 m) and found it low immediately after the earthquake at −171.4 ± 0.2 ‰, before increasing it overall during the post-earthquake period to. 7146.7 ± 7.6 ‰ (Figure. 4). Based on the extensive pattern observed in the soils of the Southern Alps, New Zealand (Figure S3), these patterns indicate shifts in the lake’s C29n-alkane source depositing from high elevations immediately after the earthquake to later low elevations in post-seismic and interlaced sediments .

Pilot template for the source of organic matter

Based on the observed relationships between soil height (Z, m), soil depth (H, cm), δ13Corg, and CPIN-alkanes (Figure 2), we proposed an model for predicting Z and H from δ13Corg pair and CPIn-alkanes values ​​in the core the lake. With Mount Fox data only, we fit two levels of discrete data (materials and methods) δ13Corg = 3.9 ± 0.8 × 10−3Z + 4.3 ± 1.2 × 10−2H – 31.9 ± 0.8 (r2 = 0.75, P <0.01) (1 (CPIn - Alkanes = 5.3 ± 2.1 × 10−3 · Z - 0.1 ± 0.03H + 9.8 ± 1.8 (r2 = 0.34, P <0.01) (2)

These models describe patterns of first order in the data and provide a way to explore the lake record in terms of relative changes in Z and H over time. When the values ​​of δ13Corg and CPIn-alkanes are high (or both low), the organic matter in the samples is likely to derive predominantly from topsoil horizons, and both variables track elevation (Figure 2A). In contrast, the difference between these variants is designed as a contribution from different soil depths (Figure 2, b, c).

As a test to see if these models are supported for the wider study area, we first expect the13Corg values ​​for soil samples collected from Alex Knop using the equivalent. 1 and sample values ​​for Z and H, spreading uncertainty about models (materials and methods). The expected δ13C values ​​correspond to the measured values ​​in case of uncertainty (n = 23, r2 = 0.32, P <0.01; Figure S6), across a range of C13Corg values ​​from ~ −30 to −25 ‰. Testing of this model indicates that it can provide a realistic restriction on the height and depth of erosion of lake sediments. We note that the CPI may not be related to the increase in other settings [e.g., (46)]Therefore, these models may not be applicable outside of this study area. We also note that our expected depth is derived from Eqs. 1 and 2 cannot track foundation input due to low OC content (33). It is assumed that the mixture of organic matter present in each depth of sediment of the lake sediments represents the average depth and average height of the corrosive materials.

Using Eqs. 1 and 2, we expect the source height and depth of the soil profile for the organic materials deposited in lake sediments over four seismic cycles. The typical wear height ranges from 283 (+ 217 / −176) m to 1118 (+ 225 / −222) m, while depth ranges from 18 (+ 18 / −12) cm to 63 (+ 24 / −20) cm. The large uncertainties reflect the small size of the Mount Fox dataset and model fit (Figure 2). We note that the expected mean depth of wear for the post-seismic precipitation stages is 44 (+ 24 / −22) cm and within the large uncertainty range of the medium of 36 (+ 21 / −18) cm from the interference phases (Figure 3). The average height of the post seismic stages 722 (+ 329 / −293) m, however, is much higher than the mean of the junction 459 (+ 256 / −226) m (Figure 5).

Figure 5 Source of elevation of organic matter in Lake Baringa during the post-seismic intervals.

(A) The blue and red lines show elevation distributions of eroded soil for the entire record (Figure 3c) during the period between seismic and post-seismic, respectively. Dashed lines show 16, 50, and 84 percentages of distributions. (B) The gray line shows the high distribution of alpine watersheds (watershed flowing west from the Windbag River) at 16, 50 and 84 percent of the distribution as dashed lines. The black line is the distribution of slopes greater than 20 ° at the alpine catchment. Frequency data (A) and (B) were stored at 25 m vertical intervals.

يرتبط الارتفاع المتوقع بشكل سلبي بقياسات 29DC29-n-alkane (P <0.01، n = 10؛ fig. S5B) ويتناسب مع القياسات المنشورة لقيم Alkane أقل δDC29-n في التربة المجمعة من ارتفاعات أعلى في جبال الألب الجنوبية ونيوزيلندا (40) وأماكن أخرى (26 ، 36 ، 46). يرتبط العمق المتوقع للتآكل ارتباطًا إيجابيًا بقيم δ15N (P <0.01، n = 30؛ fig. S5C) ويتوافق مع قيم F14C الأعلى لأعماق منخفضة للتربة (P = 0.03، n = 5؛ fig. S5D).

نقاش

تشير قيم k13Corg و CPIn-alkanes للرواسب في بحيرة Paringa إلى تحسين تسليم المواد المتآكلة من الارتفاعات العالية بعد الزلازل الكبيرة (الشكل 5). بالنسبة للدورة الزلزالية الأخيرة (بعد حدث 1717 م) ، يحدث أعلى ارتفاع متوسط ​​متوقع لتآكل المواد العضوية مباشرة بعد الزلزال ، مع قيم 1041 (+ 246 / −227) م و 1118 (+ 225 / −222) م (الشكلان 3 و 4). ثم ينخفض ​​ارتفاع مصدر الرواسب نحو متوسط ​​الارتفاع المتوقع في الفترات التداخلية 458 (+ 242/17217) م على مدى 78 ± 28 سنة (الشكلان 3 و 4) (23).

في حين أن النماذج التجريبية التي نستخدمها لقياس ارتفاع المواد العضوية المتآكلة لديها قدر كبير من عدم اليقين (من 200 إلى 300 متر تقريبًا) ، فإن استدلال تعبئة الرواسب بعد الزلزال من الارتفاعات العالية بعد زلزال 1717 م باستخدام δ13Corg و CPIn-alkanes القيم مدعومة بالتغيير في قيم CDC29-n-alkane. ترتبط قيم δDC29-n-alkane مع الارتفاع المتوقع للتآكل (الشكل S5B). في حين أن بيانات التربة δDC29-n-alkane من هذه الدراسة والبيانات المنشورة من جبال الألب الجنوبية (40) متناثرة ، فإنها تُظهر تدرجًا مرتفعًا متوقعًا من خلال تغيير التكوين النظائري لهطول الأمطار (الشكل S3) ، وهو أساس باستخدام δDC29-n-alkane كبديل لقياس الحفريات القديمة (40).

تتبع دورات الزلازل الثلاثة الأخرى لخطأ جبال الألب نمطًا مشابهًا لنمط حدث 1717 م ، مع ارتفاعات متوقعة أعلى من التآكل بعد كل زلزال (الشكل 3). C. م 925 الزلزال (الأعمق في القلب) ، من الواضح أن الارتفاع النموذجي مرتفع بعد الزلزال ثم ينخفض ​​بشكل عام خلال مرحلة ما بعد الزلازل. الدورتان السيزميتان الأخريان لها مراحل ما بعد الزلازل التي تظهر أنماطًا أكثر تعقيدًا للارتفاع النمطي بعد الزلازل ، على الرغم من أن قيم الارتفاع تظل بشكل عام أعلى من القيم المتوسطة لعينات التداخل.

على عكس الارتفاع ، لا نجد فرقًا كبيرًا في عمق التآكل المتوقع للمادة العضوية بين مرحلتي الترسيب وما بعد التداخل. ومع ذلك ، فإن مزيج مصادر المواد العضوية السطحية والأعمق في التربة في كل من المراحل ما بعد الزلزالية والمرامية يدعم الانزلاق كآلية أولية للتآكل على منحدرات التلال في مستجمعات المياه. تتوافق ملاحظاتنا مع كون الانزلاق الأرضي هو العملية السائدة التي تؤدي إلى تآكل منحدرات التلال على الجزء الغربي من جبال الألب الجنوبية في فترات التداخل (5). من المحتمل أيضًا أن يتم فرز المواد العضوية المتآكلة بعد حدوث حدث انزلاقي أرضي. هناك اقتراح في حدث ما بعد عام 1717 م بأن أول مادة عضوية تصل إلى البحيرة هي من تربة سطحية عالية الارتفاع (الشكلان 3 و 4) ، قبل أن تصل التربة الأعمق من تلك الارتفاعات إلى البحيرة. في المستقبل ، قد يساعد نهج المعلمات الجيوكيميائية المستخدمة هنا في تسليط الضوء على هذه التفاصيل الهامة للتآكل والنقل النهري بعد الانهيار الأرضي الواسع الانتشار (47 ، 48).

تقدم ملاحظاتنا اختبارًا للفرضية القائلة بأن آليات تحريك الانزلاق الأرضي تؤثر على النمط المكاني الطويل الأمد للتآكل على منحدرات التلال في أحزمة الجبال (20). بسبب زيادة ضغط المسام السائلة المنخفضة على منحدرات التلال ، يميل الانزلاق الأرضي الناجم عن هطول الأمطار إلى تآكل الارتفاعات المنخفضة بسبب التسرب (13). وعلى العكس من ذلك ، فإن التضخيم الطبوغرافي للحركات الأرضية عند قمم التلال وانكسارات المنحدرات أثناء الزلازل يؤدي إلى أخذ عينات ارتفاعات شاهقة ناتجة عن الزلزال (الشكلان 3 و 5) (18 ، 19).

تظهر هذه الأنماط على أنها تحولات كبيرة في مصدر إنتاج الرواسب التي يتم تسجيلها في طبقات طبقات البحيرة. يشير سجل بحيرة بارينجا إلى أن 43 ٪ من تدفق الرواسب من مستجمعات المياه يحدث من متوسط ​​ارتفاع 722 (+ 329 / −293) م خلال مراحل ما بعد الزلزالية مقارنة بـ 57 ٪ من تدفق الرواسب من 459 (+ 256 / −226) م خلال المراحل التداخلية (الشكلان 3 و 5) (21). يبدو أن ما يزيد على ألف عام في مستجمعات المياه التي تغذي بحيرة بارينجا ، تتجمع العواصف والزلازل لتدفع بالتساوي نسبيًا لتآكل منحدرات التلال عن طريق الانزلاق الأرضي من حيث الارتفاع. بالنظر إلى نموذج مفاهيمي ثنائي الأبعاد (20) ، يمكن أن يكون تأثير ذلك تعزيز مورفولوجيا التلال المستوية.

سجل بحيرة Paringa ذو صلة أيضًا بفهمنا لمعدلات وعمليات تقسيم الهجرة إلى الصرف ، وبالتالي ديناميات تطور المناظر الطبيعية في أحزمة الجبال. تظهر الإغاثة المحلية الكبيرة وكذلك مقاطع القناة الأكثر انحدارًا ومنحدرات التلال التي تتدفق غربًا على نطاق جبال الألب الجنوبية الأمامية أنهم “معتدون” ، ومن المحتمل أن يلتقطوا منطقة الصرف من نظيرتهم المتدفقة شرقا التي يشتركون معها في تقسيم الصرف (الشكل S7) (8 ، 49 ، 50). على أساس رسم خرائط حدث واحد ، تم اقتراح الانهيارات الأرضية لتكون العملية السائدة التي تحدث بها هجرة تقسيم الصرف في أحزمة الجبال (7). تشير النتائج التي توصلنا إليها إلى أنه على المدى الطويل ، يمكن أن تكون الزلازل العملية المسيطرة التي تدفع الانزلاقات الأرضية عند ارتفاعات تقسيم الصرف (الشكل 5 والشكل S7). لهذه الأسباب ، نفترض أنه في الأحزمة الجبلية النشطة ، فإن الزلازل الكبيرة هي العملية الأساسية التي تدفع الهجرة إلى تقسيم الصرف. النتيجة الطبيعية لهذه الفرضية هي أن تواتر الزلازل الكبيرة يوفر رابطًا مباشرًا بين التكتونيات ، وهجرة تقسيم الصرف ، وديناميات تطور المناظر الطبيعية. يوضح عملنا أن الأحداث المتطرفة ، مثل الزلازل والعواصف ، قد يكون لها تأثير من الدرجة الأولى على تطور المناظر الطبيعية من خلال الأنماط المكانية المتماسكة للتآكل عن طريق الانهيار الأرضي الذي تولده.

المواد والطرق موقع الدراسة وقلب الرواسب

تتشكل جبال الألب الجنوبية من التقارب المائل بين الصفائح الأسترالية والهادئة التي تبلغ 39.7 مم عامًا ونصف on على محمل 245 درجة (51) ، حتى 80 ٪ منها يتم استيعابها على خطأ جبال الألب المحيط بالمدى (52). يعتقد أن خطأ جبال الألب قد تمزق في الزلازل الكبرى (ميغاواط> 7) مع فترة عودة شبه دورية 263 ± 68 سنة (43 ، 53 ، 54). تهيمن على المنحدرات الحادة التي تم تطويرها في صخور الأساس metasedimentary كافية للمناظر الطبيعية لجبال الألب الجنوبية الغربية وكافية لدعم معدلات عالية من الانهيارات الأرضية (5 ، 55). تستمد الرطوبة في الغالب من بحر تسمان (56) ويتم نقلها بواسطة الرياح الشمالية الغربية ، والتي تدفع هطول الأمطار حتى 10 إلى 12 مترًا عامًا − 1 (57). يدفع المناخ والتكتونية معدلات تآكل تصل إلى 10 ملم في السنة − 1 (58 ، 59).

تقع بحيرة Paringa على بعد 3 كم غربًا من جبال الألب. تبلغ مساحة مستجمعات المياه إلى بحيرة بارينجا حوالي 60 كم 2 في جبال الألب الجنوبية الغربية الأمامية ، مع ارتفاعات تتراوح من 16 إلى 1420 م (الشكل 1). تشمل الأحجار الصخرية الأساسية Mylonites وعلماء البليتيك والسماميين في Torlesse Terrane إلى الشرق من خطأ جبال الألب في نطاق Matataketake ، بينما تحتل مجموعة Greenland Group الكوارتز والأحجار الطينية من Buller Terrane مستجمعات Collie Creek والتلال المتاخمة للبحيرة نفسها (60). المنطقة مغطاة بغابات مطيرة معتدلة أقل من 800 م تقريبًا. تستمر الشجيرات والمراعي والأعشاب الألبية فوق خط الجليد الإقليمي عند ~ 1250 م (الشكل S1).

لتقييد تكوين المواد العضوية في التربة كدالة للارتفاع وعمق التربة ، تم جمع 19 عينة من التربة من آفاق مختلفة للتربة عبر ممر الارتفاع في جبل فوكس ، على بعد 55 كم شمال شرق منطقة الدراسة على طول خط صدع جبال الألب . تمثل هذه التربة O (السطح إلى 0.05 ± 0.04 م) ، أ (0.05 ± 0.04 إلى 0.18 ± 0.06 م) ، E (0.18 ± 0.06 إلى 0.42 ± 0.10 م) ، ب (0.42 ± 0.10 إلى 0.65 ± 0.09 م) ، و C (> 0.65 ± 0.09 م) آفاق التربة. تم جمع العينات باستخدام مثقاب التربة ، مع ملاحظة عمق العينة ، والتربة المسجلة في الحقل وفقًا لنظام تصنيف القاعدة المرجعية العالمية لموارد التربة (WRB) (على سبيل المثال ، طبقات O و A و E و B و C ).

تم جمع نواة رواسب بطول 6 أمتار من مركز بحيرة بارينجا باستخدام جهاز جمع Mackereth (PA6m1). كان اللب مرتبطًا بنواة رئيسية مؤرخة جيدًا استنادًا إلى تحليل الكربون المشع لـ 22 من الأحافير الكبيرة الأرضية (23). تم استخدامه مؤخرًا لتقييم تأثير الزلازل الكبيرة على تآكل OC (21). تم تسجيل أربعة زلازل كبيرة بقوة mw> 7.6 في القلب عند 1717 م ، ج. 1400 م ، ج. 1150 م ، وج. م 925 (24) وقد تم تحديدها من خلال ثلاث وحدات رسوبية مميزة: (1) مكورات التوربينية الضخمة ، (2) مكدسات هايبكنيت ما بعد الزلازل ، و (3) طمي الطبقات الداخلية (21 ، 23 ، 24).

تحليلات جيوكيميائية

تم جمع ما مجموعه 189 عينة من الرواسب من قلب PA6m1 بدقة تتراوح من 0.2 إلى 5.8 سم بواسطة Frith et al. (21) ، حيث تركيز OC ، [TOC] (٪) ، وتركيب نظائر الكربون المستقر للمواد العضوية السائبة ، C13Corg (‰) ، ونشاط الكربون المشع للمواد العضوية السائبة (تم الإبلاغ عنه على أنه جزء حديث ، F14C) ، وإجمالي تركيز النيتروجين ، [TN] (٪)، وقد تم تحليل. كما تم تحليل هذه العينات لتكوين نظائر النيتروجين الأكبر δ15N (‰). التفصيل [TOC]و δ13Corg و [TN] يمكن العثور على الطرق التحليلية في دراسة Frith et al. (21). باختصار ، تم طحن 0.4 إلى 0.6 جم من العينة إلى مسحوق وتفاعلت مع 20 مل من حمض الهيدروكلوريك 0.25 م لمدة 4 ساعات عند 70 درجة مئوية تقريبًا لإزالة أي كربونات غير عضوية. في دراستنا ، تمت معالجة عينات التربة لدينا باستخدام الطريقة داخل الكبسولة. تمت إضافة حوالي 2 مجم من التربة الجوفية إلى كبسولة فضية (يتم حرقها في غضون أسبوعين من الاستخدام) وتتفاعل مع حمض الهيدروكلوريك M 1 داخل الكبسولة. ثم تم تجفيف الكبسولة عند 60 درجة مئوية في الفرن ، وتكررت العملية مرتين أكثر. لجميع العينات ، [TOC] و δ13Corg تم تحديدها عن طريق الاحتراق عند 1020 درجة مئوية في O2 ضمن محلل عنصري Costech CHN مقترنًا عبر ConFlo III إلى مطياف الكتلة النسبية الحرارية (EA-IRMS) في مختبر الكيمياء الحيوية للنظائر المستقرة في جامعة دورهام. Total nitrogen content and stable nitrogen isotopic ratio (δ15N) were measured by combustion of untreated samples in an EA-IRMS with a Carbosorb trap to inhibit large CO2 peaks from affecting measurements. δ13Corg and δ15N values were normalized on the basis of measured values of several standards and reported relative to Vienna Pee Dee Belemnite (VPDB) and relative to air. Duplicates of the samples (n = 20) returned mean ± 1σ of [TOC] = ± 0.09%, δ13Corg = ± 0.08‰ and [TN] = ± 0.01% (21), and δ15N = ± 0.14‰. Radiocarbon measurements were made by accelerator mass spectrometry (AMS) as described by Frith et al. (21).

A subset of samples (n = 73) from periods of interest were selected across the lake sediment core and soil samples for the analysis of n-alkane abundance. Fifteen of these values were reported by Frith et al. (21) to indicate the predominantly terrestrial source of sediment. A total of 19 soil samples were also analyzed, including nine soil A horizons from across different elevations and two depth profiles. A detailed description of the n-alkane analysis can be found in the study of Frith et al. (21). In summary, total lipids were extracted in a microwave accelerated reaction system (MARS, CEM Corporation) in 12 ml of dichloromethane and methanol (3:1) before adding an internal standard (hexatriacontane; Sigma-Aldrich). The lipid extract was first saponified with 8% KOH in methanol/water (99:1) at 70°C for 1 hour. The “base” fractions were liquid-liquid extracted in 2.5 ml of pure hexane three times. The n-alkanes were separated by silica column chromatography, eluting with 4 ml of hexane. The abundance of n-alkanes was quantified using a gas chromatograph fitted with a flame ionization detector (Thermo Scientific TRACE 1310).

We report the concentration of individual homologs and the sum of the C21-C35n-alkanes on a μg g−1 sediment/soil (Σalk) and μg g−1 OC basis (Λalk). The long-chain (C25-C33) CPI was calculated asCPI=1/2(∑(C25+C27+…C33)/∑(C24+C26+…C32))+1/2(∑(C25+C27+…C33)/∑(C26+C28+…C34))(3)

The hydrogen isotopic compositions (δD) of individual compounds were measured on 12 sediment and 7 soil samples using a Thermo GC-Py-IRMS system at the Department of Geography, Durham University. The system consists of a Trace 1310 GC coupled to a Thermo Delta V Plus via GC IsoLink II and a Thermo TG-5MS 30 m × 0.25 μm × 0.25 μm column. The alumina pyrolysis reactor was operated at 1420°C and conditioned with a CH4 backflush before use. H2 reference gas pulses were introduced at the start and end of each chromatogram to provide an isotope ratio reference point and to check the system stability during the run. Individual n-alkane isotope ratio values were corrected using a multipoint linear normalization of a C16-C30n-alkane reference material (A6 standard provided by A. Schimmelmann, Indiana University, Bloomington). Reference n-alkanes from C18-C30 were used to generate the normalization curve, covering δD values from −29.7 to −263.0‰. The H3+ factor was determined on a daily basis with repeated measurements of H2 reference gas at varying dilutions at the start of each sequence. The mean H3+ factor was 2.719 ± 0.048 parts per million (ppm) mV−1 (±1σ, n = 17) over the 3-month analysis period, with day-to-day SDs of between 0.01 and 0.03 ppm mV−1. Reference materials A6 and B4 (provided by A. Schimmelmann, Indiana University, Bloomington) were used to check the validity of the H3+ factor calibration (using peak-based measurements) and to determine the minimum usable amplifier signal, which minimized the residuals, and gave an r2 value of at least 0.995 for the normalization plot. The concentration of the A6 n-alkane standard used for the linear normalization was adjusted to obtain amplifier intensities within this range (1000 to 4000 mV). Each sample was diluted and prerun to determine the optimum solvent volume required to fit within the amplifier signal range of the standards. One sample (PA6m1_s1_111.5) was found to be below the analytical range (700 mV) but has been included along with the uncertainty in Fig. 4.

The δD of the C29n-alkane is reported here, as it is most abundant in most of the samples. δD values are reported relative to Vienna Standard Mean Ocean Water (VSMOW) and are expressed in per mil (‰). The precision (±1σ) of isotopic measurements of the standard is ±2‰ (n = 6) for C29n-alkane. Each sample has been run twice, and the SD was reported as the analytical error. The chromatographic resolution was generally good for most of the n-alkanes with no coelution evident for the reported C29n-alkane peak (fig. S8).

Empirical model of organic matter provenance

Multiple linear regression was used to fit both δ13Corg and CPI to the elevation (Z, m) and depth (H, cm) for the soil samples from Mount Foxδ13Corg=a1×Z+b1×H+c1(4)CPI=a2×Z+b2×H+c2(5)

Parameters and their SEs were returned from the regression. The Z and H values can be determined by solving the equations for the lake sediment to reconstruct the elevation and depth of erosion.

The model is based on discrete soil sample values. In reality, erosion will integrate across a range of depths and elevations. To include this in the empirical model would require more detailed information on the spatial distribution of organic matter and biomolecules in the landscape than we currently hold. We therefore assume that erosion of a soil will mix materials in a linear manner, and that the resultant composition of sediments produced reflects the mean value of that mixture. In other words, the discrete values of Z and H returned for each lake sediment depth interval are assumed to be the mean value of a distribution.

A Monte Carlo simulation was used to take account of the uncertainty on the parameters. For each group of parameters, the elevation and depth calculations were repeated 10,000 times with random sampling of normally distributed scaling parameters. The elevation and depth values were reported on the basis of the median of the Monte Carlo distribution with lower and upper bounds defined by the 16th and 84th percentiles of the distribution, respectively.

This is an open-access article distributed under the terms of the Creative Commons Attribution license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

REFERENCES AND NOTES↵↵↵↵↵↵↵↵↵↵↵↵↵↵↵↵↵↵↵↵↵↵↵↵↵↵↵↵↵↵↵↵↵

J. I. Hedges, F. G. Prahl, Early diagenesis: Consequences for applications of molecular biomarkers, in Organic Geochemistry: Principles and Applications, M. H. Engel, S. A. Macko, Eds. (Springer US, 1993), pp. 237–253.

↵↵↵↵↵↵↵↵↵↵↵↵↵↵↵↵↵↵

R. J. Norris, A. F. Cooper, in A Continental Plate Boundary: Tectonics at South Island, New Zealand, D. Okaya, T. Stern, F. Davey, Eds. (American Geophysical Union, 2007), pp. 157–175.

↵↵↵↵↵↵↵↵

M. Rattenbury, R. Jongens, S. Cox, Geology of the Haast Area (Institute of Geological & Nuclear Sciences, 2010).

Acknowledgments: We thank G. Soulet and A. Woolley for the field support and E. Maddison, K. Melvin, and A. George for laboratory support. Samples were collected under Department of Conservation research license. Funding: This work was funded by the National Natural Science Foundation of China (41991322) and COFUND Junior Research Fellowship at Durham University to J.W.; Natural Environment Research Council Standard Grant to R.G.H., A.L.D., E.L.M., and J.D.H. (NE/P013538/1); and Rutherford Foundation Postdoctoral Fellowship to J.D.H. (RFTGNS1201-PD). The soil radiocarbon analysis was supported by NERC radiocarbon analysis allocation number 2170.1118. Author contributions: R.G.H., J.D.H., J.W., and A.L.D. designed the study. J.D.H. and S.J.F. collected the core, and J.W., T.C., and E.L.H. collected the soil. N.V.F. and J.W. undertook bulk geochemical analysis under direction from R.G.H., J.D.H., and D.R.G. جي دبليو and M.D.W. undertook the biomarker analysis under direction from R.G.H. and E.L.M. M.H.G. ran the radiocarbon analyses. جي دبليو analyzed and interpreted the bulk and biomarker data with R.G.H. and J.D.H. J.D.H., R.G.H., and J.W. wrote the paper with input from all authors. Competing interests: The authors declare that they have no competing interests. Data and materials availability: All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. Additional data related to this paper may be requested from the authors.

Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY).

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