Holocene glacier and climate fluctuations of the maritime ice cap Høgtuvbreen,northern Norway

Abstract

Holocene fluctuations of a small outlet glacier from the ice cap Høgtuvbreen at 65° N in coastal northern Norway are reconstructed based on distal glacier-fed lake sediments, complemented by a moraine sequence dated by lichenometry. Glaciers respond to changes in accumulation-season precipitation, ablation-season temperature and redistribution of snow by wind. Hence, reconstructions of glacier fluctuations based on distal glacier-fed lakes may give detailed information about past climate at a potentially high temporal resolution. Yet, the importance of any of these climate components is often difficult to solve. Here, we apply the ‘Liestøl-relationship’, which expresses the relationship between ablation-season temperature and annual accumulation of snow at the equilibrium line altitude (ELA), to the reconstructed local temperature–precipitation–wind ELA (TPW-ELA) to infer the relative importance of winter-balance and ablation-season temperature as causes of reconstructed glacier variation. The reconstructions show a large glacier readvance corresponding with the 8.2-ka cold event and a sequence of eight distinct glacier advances and retreats during the Neoglacial time period bracket between 4300 ± 40 cal. yr BP and AD 1900. The glacier reached its Holocene maximum position in AD 1773 ± 29, subsequently followed by an ongoing unprecedented retreat, interrupted only by some minor halts and readvances. Based on a detailed comparison of our results with similar studies of both continental and maritime glaciers, as well as independent temperature proxy records across Scandinavia, we argue that significant and consistent deviations in ELA fluctuations between continental and maritime glaciers in the region are caused by a north–south migration of the arctic polar front. Additionally, we suggest that deviations in ELA fluctuations between Scandinavian maritime and continental glaciers around 7150, 6560, 6000, 5150, 3200 and 2200 cal. yr BP reflect the different response of continental and maritime glaciers to drops in total solar irradiance (TSI).

Keywords

glacier reconstruction Holocene lichenometry north Norway proglacial lake sediments

Introduction

The maritime glaciers in the Svartisen area of northern Norway are strongly influenced by their proximity to the Norwegian Sea and the interaction between arctic- and subtropical air masses converging at the arctic polar front in this region. The latitudinal position of the arctic polar front in this region determines the latitudinal extent of storm tracks; thus, periods when arctic air masses dominate are cold and dry, whereas periods when subtropical air masses from south–southwest dominate are relatively warm and moist (e.g. Miller et al., 2010; Sjögren, 2009). Since glaciers respond to changes in winter- and summer-balance, equilibrium line altitude (ELA) fluctuation records from this area may potentially give insight into key climate variables including atmospheric circulation patterns on a decadal to centennial time scale (Bakke et al., 2005b, 2008; Larsen et al., 2013).

Except for the late Weichselian deglaciation and early Holocene (Andersen, 1975; Andersen et al., 1995; Blake and Olsen, 1999; Olsen, 2002; Rasmussen, 1981; Theakstone, 1966), and the retreat following the ‘Little Ice Age’ (LIA) maximum advance c. AD 1750 (Andreassen et al., 2005; Holmsen, 1948; Innes, 1984; Karlén, 1979; Kjøllmoen et al., 2011; Rekstad, 1892, 1893, 1912; Theakstone, 1965, 1988, 1989, 1990, 2010; Theakstone and Knudsen, 1981, 1986; Winkler, 2003; Worsley and Alexander, 1975, 1976), little is known about the mid- to late Holocene glacier history of the Svartisen area. This is the result of (1) lack of geomorphological evidence as the LIA glacier advance around AD 1750 was the largest glacier readvance since early Holocene and therefore erased all previously deposited moraines in the local glacier forelands (e.g. Winkler, 2003), (2) extremely high erosion/sedimentation rates in glaciated catchments dominated by limestone (Seivåg, 2013; Søvegjarto et al., 1988) and (3) a lack of suitable distal glacier-fed lakes that can be used to reconstruct past glacier variations (Dahl et al., 2003).

The main objective of this study is therefore to reconstruct glacier fluctuations of Høgtuvbreen in the Svartisen area continuously throughout the Holocene. Lacustrine sediment cores combined with a moraine sequence dated by lichenometry form the basis for this glacier reconstruction. There are numerous downstream glacier-fed lakes beyond some of the outlet glaciers from Høgtuvbreen that are suitable for recording the input of clastic material which is produced by glacier erosion. Here, we have chosen to study the glacier Leirdalsbreen at the eastern sector of Høgtuvbreen (Figures 1b and 2a and b). Leirdalsbreen has a distinct glacier foreland with a well-preserved moraine sequence, and with the distal glacier-fed Lake Vardfjelltjønna being located well beyond the suggested local LIA glacier maximum (Figures 3 and 4a and b).

Figure 1.

(a) The location of the study area is shown in relation to the North Atlantic Ocean and other localities that are discussed in the text. (b) Locality map showing the study area. Glaciers are outlined as dark grey areas and lakes and fjords as white areas.

Figure 2.

Comparison between (a) Høgtuva ice cap as it was mapped in 1896 (Johannesen and Paulsen, 1901) and (b) aerial photos taken in September 2013 reveals that the area covered by glacier ice is strongly reduced since 1896.

Figure 3.

Quaternary geological map of the catchment area of Lake Vardfjelltjønna. Symbology follows the standard given by the Norwegian Geological Survey.

Figure 4.

(a) Reconstructed glacier extent and surface profiles plotted with the calculated AABR ELA. (b) The surface profiles lay the foundation for reconstructing horizontal extent. Note the systematic overestimated surface profiles at the top of the backwall. (c) Time–distance diagram illustrating the general retreat between the LIA glacier maximum and the present.

A high-resolution reconstruction of Holocene glacier fluctuations at the outlet glacier Leirdalsbreen from the Høgtuva ice cap is here presented. Furthermore, we discuss how Leirdalsbreen has responded to variations in winter- and summer-balance through time and to what extent these fluctuations are influenced by the shifting position of the arctic polar front relative to the study area and variations in total solar irradiance (TSI).

Study area

The summit Høgtuva (1276 m a.s.l.) at the western coast of northern Norway is located northwest of the town Mo i Rana, and just south of the Arctic Circle (Figure 1a and b). The area surrounding Høgtuva is characterised by alpine and partly glacier-covered mountains. Just north of Høgtuva are the large plateau glaciers Austre- and Vestre Svartisen; the latter of which is the second largest glacier in continental Europe (Kjøllmoen et al., 2011).

Høgtuvbreen is the generic name for the numerous small plateau, outlet, valley and cirque glaciers found on the mountain Høgtuva (ice covered area of 13.8 km² as of AD 2013). The name was coined when Høgtuvbreen was considered as a plateau glacier with outlet glaciers occupying surrounding valleys. Like most glaciers worldwide (Nesje, 2009; Nesje et al., 2008; Oerlemans, 2005; Theakstone, 2010; Winkler, 2003), Høgtuvbreen has decreased dramatically in size compared with the LIA glacier maximum. The present glacier covers only about 20% of the area that was covered by ice during the LIA maximum. At present, the remnants of this former ice cap exist in the form of valley and cirque glaciers, except for a small area on Tjønnfjellet where a small plateau glacier still exists (Figure 2). The glacier reconstructed in this study was detached from the plateau glacier system between 2007 and 2013 and is thus characterised as a small valley glacier, here referred to as Leirdalsbreen.

Leirdalen drains the eastern part of Høgtuva, and is a tributary valley to the Stordalen/Vesterdalen valley, which separates the Austre- and Vestre Svartisen plateau glaciers (Figure 1b). The lower part of Leirdalen, between the mountains Melfjellet (553 m a.s.l.) and Høgtuva (1276 m a.s.l.), is oriented in a northwest–southeasterly direction and has a gently undulating relief. There are generally little superficial deposits or depositional landforms in this area, except for in the vicinity of Vardfjelltjønna (lake) near the mouth of the valley (Figure 3). The higher reach of Leirdalen is east–west oriented and separates Høgtuva from Tjønnfjellet (1062 m a.s.l.). There are generally more superficial deposits in this area, as illustrated in Figure 3.

The meltwater stream from the glacier in Leirdalen merges with meltwater streams from two smaller cirque glaciers situated at the northern and eastern slopes of Høgtuva. Until AD 1950, this stream entered Lake Vardfjelltjønna near the mouth of Leirdalen until local farmers artificially closed the inlet. At present, meltwater enters the lake only during abnormally high discharges (Eilif Leirånes (local farmer), personal communication).

The weather station in Mo i Rana (st. no. 79480, 41 m a.s.l.), situated 25 km southeast of Høgtuva, recorded a mean annual temperature of 2.8°C and a mean annual precipitation of 1431 mm during the last normal period (1961–1990) (Norwegian Meteorological Institute, 2015). The monthly mean temperature varies between −6.6°C in January and 13.2°C in July, while monthly mean precipitation varies between 184 mm in October and 63 mm in May (Norwegian Meteorological Institute, 2015). However, large differences in precipitation are found between the western and eastern portions of this region because of orographic precipitation. Hence, the mean annual precipitation at the modern ELA on Leirdalsbreen is estimated to be close to 3200 mm w.e., using an exponential increase in precipitation of 8%/100 m, whereas the mean ablation-season temperature (1 May–30 September) is estimated to be 3.7°C at the ELA based on a theoretical lapse rate of 0.6°C/100 m (Dahl and Nesje, 1996).

The majority of the bedrock of Høgtuva and Leirdalen consist of beryllium rich Precambrian coarse-grained granitic gneiss, while bands of amphibolite and garnet schist are found in the eastern and southwestern parts respectively (Lindahl et al., 2000; Qvale et al., 2012; Søvegjarto et al., 1988).

Methods

Geomorphological mapping and lichenometric dating

The geomorphology within the drainage area of Lake Vardfjelltjønna was mapped with emphasis on present and past processes that potentially could influence the depositional environment in the lake. The observed landscape features were delineated using orthorectified aerial photos (series 13475 and B2506MK) from the Norwegian Mapping Authorities. The resulting geomorphological map in Figure 3 is presented with symbols following the standard of the Norwegian Geological Survey. The background map is based on data from the Norwegian Mapping Authority.

Lichenometry was applied on the proximal slopes of the moraines M1–M4, M6 and M8–M9 in Leirdalen valley (see Figure 3b for overview). The long axes of thalli of Rhizocarpon geographicum were measured on moraines M1–M4 and M6 on up to three stations with an area of >400 m² with ⩾100 measurements on each moraine. The measurements on M8–M9 are from one station on each moraine with 50 measurements, as these moraines contain very few measurable lichen thalli.

The calculation of absolute lichenometric ages has traditionally been done by extracting a small number of samples, either the size of the largest lichen (LL) or the mean of a selection (e.g. five measurements) of the largest lichen (>5LL) in a population (Beschel, 1961; Matthews, 1975). The advantages of these methods are that they are transparent and cost-effective relative dating techniques (Bradwell, 2009). The LL and >5LL methods have, on the other hand, been criticised for their poor precision when used to calculate absolute ages, as well as the inability of the methods to calculate confidence intervals. During the past two decades, however, several efforts have been made to improve the precision of absolute age calculation by modelling the extreme values of thalli sizes in a large pool of sample measurements (Bradwell, 2009; McCarroll, 1993; Naveau et al., 2007; Orwin et al., 2008). This allows for the calculation of confidence intervals based on (1) the natural variability of lichen sizes in a population, (2) the uncertainty level of the calibration method that provides the transfer function and potentially (3) the uncertainty when combined with independent dating techniques used to define a growth rate (Jomelli et al., 2007). The potentially large uncertainties that surround fundamental questions around lichen ecology regarding genetics and the effect on growth rate due to geographically and temporally varying environmental factors are, however, not addressed by the aforementioned methods (Bradwell, 2009; Jomelli et al., 2007; Naveau et al., 2007; Osborn et al., 2015). Because of the difficulties in quantifying the response of a lichen population to the aforementioned sources of uncertainty, all age estimates presented in this study are defined as the mean age given by six plausible growth rate curves that are based on thalli sizes found on gravestone localities within 43 km from the study site (Winkler, 2003). The six growth rate functions are further applied to both the size of the largest- and the mean of the five largest thalli for each sampling station. The total variability of results given by these six growth rate functions (n = 12 for each moraine) lays the basis for an approximation of the total uncertainty surrounding lichenometric dating in the area. This method of assigning uncertainty intervals to absolute dates is thus not based on the sum of quantified effects of specified sources of uncertainty; however, the uncertainty intervals are based on empirically measured variability and therefore reflect the total potential uncertainty interval. Since the growth rate functions are based on measurements in different environments than the environment in which the dated moraines are situated, sources of uncertainty such as snow kill may be an important source of uncertainty near the glacier front, but are less significant at the low-lying cemeteries. Additionally, differences in humidity between the cemeteries and the glacier foreland may be considerable and thus introduce further uncertainty to the lichen growth rate. The uncertainty intervals used should therefore be regarded as a minimum estimate of uncertainty.

Table 1 shows that the lichenometric dating result for each moraine varies widely between the 10 growth functions from the area, as well as between the LL and 5LL methods. Furthermore, growth functions from the localities at Korgen, Nevernes and Røssvoll yield similar ages, while growth rate functions from the localities at Beiarn and Høyforsmoen give a wider distribution of ages compared with growth rate functions from the three former localities. Since the localities at Korgen, Nevernes and Røssvoll are geographically close to the current study site (within 43 km) and the fact that these localities agree well with each other, the mean age given by growth functions from these localities are probably more accurate than the mean age given when the localities at Beiarn and Høyforsmoen are included. The uncertainty interval for each calculated age is here presented as the 68% confidence interval (±1 σ) of the variability of the 12 calculated dates for each moraine.

Table 1.

Mean age estimates (AD ± 1σ) are based on measurements of both the largest lichen thallus (LL) and the mean of the five largest thalli (5LL), which are transferred to age using 10 transfer functions from five local gravestone localities (Winkler, 2003).

Gravestone locality (distance from Høgtuva)	Growth function (Winkler, 2003)	Sampling method	M1 (years AD)	M2 (years AD)	M3 (years AD)	M4 (years AD)	M6 (years AD)	M8 (years AD)	M9 (years AD)
Korgen (43 km)	log (y + 90) = 0.0048 × + 1.9748	LL	1727	1755	1853	1862	1903	1961	1982
		5LL	1764	1780	1862	1873	1909	1978	1986
	log (y + 30) = 0.0062 × + 1.6289	LL	1790	1814	1894	1900	1931	1971	1984
		5LL	1821	1834	1900	1909	1935	1982	1987
Nevernes (39 km)	log (y + 120) = 0.004 × + 2.0868	LL	1747	1771	1858	1866	1905	1961	1983
		5LL	1779	1792	1867	1876	1911	1978	1986
	log (y + 60) = 0.0051 × + 1.8493	LL	1766	1790	1874	1881	1916	1964	1981
		5LL	1798	1812	1882	1891	1921	1978	1986
Røssvoll (28 km)	log (y + 100) = 0.0045 × + 2.0173	LL	1733	1760	1854	1862	1902	1960	1982
		5LL	1768	1783	1863	1873	1909	1977	1985
	log (y + 30) = 0.0063 × + 1.6426	LL	1774	1800	1886	1892	1925	1968	1982
		5LL	1808	1822	1893	1902	1930	1979	1984
LL size (mm)			125.0	118.0	88.0	85.0	68.0	36.9	22.5
5LL size (mm)			115.7	111.4	84.7	80.6	66.3	25.6	19.8
n			116	150	150	150	100	50	50
Mean age (AD ± 1σ)			1773 ± 29	1793 ± 25	1874 ± 17	1882 ± 16	1916 ± 12	1971 ± 8	1984 ± 2

The presented 1σ uncertainty interval is empirically based and is regarded as an approximation to the sum of uncertainties regarding lichen growth rate as well as analytical uncertainty. A locality map is provided in Winkler (2003).

Aerial photos from AD 1962 (series 1322), AD 1971 (series 3821) and AD 1982 (series 7551) as well as a topographical map from 1896 (Johannesen and Paulsen, 1901) were used to delineate glacier extent and they are, thus, in combination with lichenometry used to date mapped moraines.

Glacier- and ELA-reconstructions

Although moraines constrain the extent of the terminus of the outlet glacier with high accuracy, less is often known about the glacier ice-surface profile at higher altitudes because of the lack of glacial deposits above the ELA. Since the reconstructed ice-surface gradient determines the areal extent of the higher reach of the glacier, and thus has implications on the resulting ELA estimate, it is critical to address potential uncertainties regarding the past ice-surface profile of the glacier. Here, the ice-surface profiles of the glaciers M1–M8 were reconstructed using the steady state model ‘profiler’ (Figure 4b), presented in Benn and Hulton (2010). Ice-surface gradients that are reconstructed from DTMs made from overlapping aerial photos from 1962, 1971 and 1982 agree well with the modelled ice-surface gradients, thus confirming a high level of accuracy of the reconstructed ice-surface profiles.

All ELA estimates are conducted using an ArcGIS-tool for automatic calculation of glacier ELA, where the Accumulation × Area Balance Ratio (AABR)-method is applied to a DTM reflecting the main glacier lobe illustrated in Figure 5a and b (Osmaston, 2005; Pellitero et al., 2015). The GIS-tool allows for very precise calculations of the area × altitude–relationship, thus taking into account a very detailed glacier hypsometry.

Figure 5.

Bathymetric map of Lake Vardfjelltjønna. Core localities are plotted as stars and the former inlet and current in/outlet are illustrated. The aerial photo clearly illustrates inlet channels in the southwestern and northeastern ends of the lake, as well as relict meltwater channels on the delta plain to the southwest of the lake.

Here we use a balance ratio (BR) of 2.1, which is calculated based on annually measured mass balance between 1971 and 1977 (Kjøllmoen et al., 2011). It is uncertain to which degree the BR of Leirdalsbreen has changed through time, yet it is assumed that the BR may have varied temporally within the average calculated for the aforementioned mid- and high-latitude maritime glacier systems (Rea, 2009).

Each calculated ELA estimate, as well as the continuously estimated local TPW-ELA (Figures 9b and c and 10c), is corrected for glacio-isostatic land uplift according to Møller (1989).

Lake sediment cores – Collection and analysis

Three piston cores (VAP 104, VAP 204 and VAP 113) and one gravity core (VAS 113) were collected from the northern sub-basin of Lake Vardfjelltjønna (see Figures 3a and 6a and b for location and bathymetric map). The three piston cores were collected by a raft mounted modified 110-mm piston corer (Nesje, 1992), while VAS 113 was collected with an HTH gravity corer (Renberg and Hansson, 2008). Both VAP 104 and VAP 204 were collected and analysed in 2004, while VAP 113 and VAS 113 were collected and analysed in 2013.

Figure 6.

(a) LOI variability in VAP 104, VAP 204 and VAP 113 is plotted together with dated levels. LOI variability is used to correlate the cores to obtain a master scale. (b) Age–depth relationship based on 18 radiocarbon dates is plotted as a best-fit curve with a 1σ uncertainty interval together with sedimentation rate. The dated samples that apparently give too old ages are rejected as these are either contaminated by inorganic carbon (bulk dates) or redeposited. The date that gives an apparently too young age is possibly contaminated by younger or recent carbon, as this sample is very small.

All cores from Vardfjelltjønna were analysed for loss on ignition (LOI) and dry bulk density (DBD) at an interval of 0.5 cm (n = 1028, 688 and 892 for VAP 104, VAP 204 and VAP 113, respectively). The procedure follows Heiri et al. (2001), where each sample of 1 cm³ is dried at 105°C, slowly heated to 550°C during the course of 1 h and then slowly cooled to room temperature in a desiccator. The sample is weighed before and after every step of the procedure. The dry weight of each 1-cm³ sample constitutes the DBD (g/cm³), while the LOI is defined as the percentage of the weight lost after combustion at 550°C.

Magnetic susceptibility (MS) analysis was carried out on VAP 113 and VAS 113 at an interval of 0.2 cm (n = 2230 and 60, respectively) with a Bartington MS2E sensor. Grain size analysis was conducted on a Micromeritics Sedigraph 5100 and the sample statistics were calculated using Gradistat v 8 (Blott and Pye, 2001; Webb and Orr, 1997). An x-ray fluorescence (XRF) element analysis was conducted on an ITRAX core scanner (Croudace et al., 2006), situated at the Department of Earth Sciences at the University of Bergen. The core VAP 113 was scanned with a Cr-tube at an interval of 500 µm (n = 8978).

All parameters are normalised by subtracting the mean and dividing by the standard deviation, and then smoothed with a moving average smoothing function in AnalySeries 2.0.4.2 (Pailard et al., 1996).

Age–depth relationship

The 24 AMS radiocarbon dates listed in Table 3 were dated at the Poznań Radiocarbon Laboratory and calibrated using the IntCal13 and Marine13 calibration curves (Reimer et al., 2013). The radiocarbon-based age–depth model illustrated in Figure 6b was constructed in Clam 2.2 in the open source software ‘R’ using a spline function with a smoothing (λ) of 0.3, where the point ages for each depth are calculated based on a weighted average of all age–depth curves (Blaauw, 2010). The dates, as well as point estimates from the modelled age–depth relationship, are generally presented as cal. yr BP ± 1σ, or cal. yr AD ± 1σ for more recent ages.

The depth scale of VAP 113 is here used as a master depth scale for all parameters because this core has the most complete unit stratigraphy of the three piston cores. Based on a correlation between the cores, which is illustrated in Figure 6a, the dated levels of VAP 104 and VAP 204 have been recalculated to the master scale using the ‘Linage’ application in AnalySeries 2.0.4.2 (Pailard et al., 1996).

Principal component analysis

Principal component analysis (PCA) is an ordination technique that is commonly applied on multivariate datasets to identify patterns of variability and a ‘common signal’ in the dataset. The technique may be helpful when interpreting sedimentation in complex depositional systems (e.g. Bakke et al., 2013; Birks, 1987; Røthe et al., 2015; Vasskog et al., 2012; Wittmeier et al., 2015).

A PCA in all instances was conducted on the smoothed and normalised dataset of the lacustrine units in VAP 113, including geochemistry (Fe/K, Si, Sr, Ti and Rb), MS, and physical sediment parameters (LOI and DBD) in AnalySeries 2.0.4.2 (Pailard et al., 1996). Compositional data such as grain size percentages were excluded from the analysis to avoid the closure problem (Birks, 1987). Both Fe- and K-count rates were excluded as well, since the variables are directly linked with the Fe/K ratio, which is used in the analysis. K-count rate and Fe-count rate were nevertheless included in a separate PCA analysis and plotted alongside the rest of the variables in order to illustrate these variables’ approximate direction in the PCA plot in Figure 8a.

Results

Geomorphological mapping

The deposits and landforms presented in the geomorphological maps in Figure 3a and b show that most of the sediments in the catchment around Lake Vardfjelltjønna have a glacial origin. A total of 10 terminal moraine ridges (M1–M10) were mapped in the foreland of the outlet glacier Leirdalsbreen. All moraines are sharp crested and boulder rich ridges with asymmetrical distal and proximal sides. M1–M6 can be traced along the northern and southern valley sides to an altitude of 620 m and to 1000 m, respectively. Leading up to the moraines from the proximal side are fluted till surfaces. The mapped moraine sequence on the northern and eastern slopes of Høgtuva (1276 m) indicates the existence of separate glaciers originating from Leirdalsbreen within the catchment of Lake Vardfjelltjønna. The moraine sequence on the northern slope of Høgtuva, however, indicates that these glaciers were connected with the main lobe in Leirdalen valley in the past, and that ice that was accumulated on the northern slope of Høgtuva thus contributed to some extent to form the lobe that deposited the terminal moraines M1, and possibly also M2. The moraines along the valley floor and the moraines on the eastern slope of Høgtuva cannot be successfully paired. The following glacier reconstructions and ELA calculations are therefore made on the area that has evidently contributed to the main glacier lobe situated in the valley floor. The former glacier on the eastern slope of Høgtuva is thus excluded from the glacier reconstruction as the impact on sedimentation of glacially eroded sediments to Lake Vardfjelltjønna from this glacier is assumed to be much less than from the main glacier.

There are numerous relict meltwater channels on both the proximal- and the distal sides of the terminal moraines. These indicate that when the glacier front was situated close to the moraines M1–M6, some of the meltwater discharge followed the northern valley side before merging with other meltwater streams further down-valley (Figure 3a and b). This northern drainage was unhindered by lakes acting as sediment traps. Most of the catchment that lies below the mapped moraines is exposed bedrock with scattered boulders. The southernmost part of the study area, that is, the area forming the western edge of the lake, is a glaciofluvial delta. The delta surface is levelled with the present lake level, yet the peat cover on the delta surface suggests that recently and presently active delta progradation only occur at the two southern inlets. There are two distinct channels on the delta surface. The northern channel led meltwater from the main meltwater system into the lake, while the southern channel holds the outlet stream from the lake. The northern inlet channel was artificially blocked in AD 1950 (Eilif Leirånes, personal communication). There is, however, evidence of erosion on the top of the 1.5-m high embankment, which indicates that meltwater has occasionally flooded the embankment. The closure of the main inlet marks a drastic change in the depositional environment in the lake. Before AD 1950, there was a continuous draining of meltwater through the lake. At present, a meltwater plume generally only enters the lake from the southern channel at diurnal high discharges.

The small valley to the northeast of the lake is covered by peat, with water draining through small meandering streams. The valley side along the northwestern margins of the lake is mainly exposed bedrock, except for a small area of the valley side that is draped with a thin, discontinuous layer of coarse-grained colluvial deposits. There are three streams that run down this valley side and draining into the lake, including two streams that partially run through the aforementioned rock fall deposit. These are not considered to be important for the sedimentation in the lake.

From the mapping of the lake and adjacent area, it is shown that the majority of the minerogenic sediment flux in the lake is due to glacial erosion up-valley and subsequent transportation by the meltwater stream through the now closed channel inlet.

Moraine age

Both the largest lichen as well as the mean of the five largest lichen measured on the moraines M1, M2, M3, M4, M6, M8 and M9 are progressively larger with increasing distance from the present glacier terminus (see Table 1). The difference in size between the largest thallus and the mean of the five largest thalli for each moraine ranges between 2.5% and 7.4% for M1, M2, M3, M4 and M6, while the difference is significantly higher for M8 and M9 (30.6% and 12% respectively).

Aerial photos (series 1322, 3821 and 7551) show the extent of the glacier in AD 1962, 1971 and 1982 respectively, while a historical map constructed by Johannesen and Paulsen (1901) shows the extent in 1896 (Table 2 and Figures 2a and 4a).

Table 2.

Reconstructed glacier parameters based on the moraines M1–M10, as well as historical maps and aerial photos.

	M1	M2	M3	M4	M5	M6	M7	M8	1962	M9/1971	M10/1982
Lichenometric age (AD ± 1σ)	1773 ± 29	1793 ± 25	1874 ± 17	1882 ± 16		1916 ± 12		1971 ± 8		1984 ± 2
Historical age (AD)					1896				1962	1971	1982
AABR ELA (m a.s.l. – BR = 2.1)	740	744	755	762	771	778	789	814	834	847	869
AAR ELA (m a.s.l. – AAR = 0.6)	733	736	738	740	742	745	757	795	851	889	894
ΔAABR ELA (m a.s.l. – BR = 2.1)	−129	−125	−114	−107	−98	−91	−80	−55	−35	−22	0
ΔAAR ELA (m a.s.l. – AAR = 0.6)	−161	−158	−156	−154	−152	−149	−137	−99	−43	−5	0
Glacier area (km²)	9.55	9.09	8.85	8.68	8.48	8.24	6.63	4.96	2.78	2.46	2.24
Glacier length (km)	4.87	4.81	4.69	4.55	4.44	4.41	4.25	3.65	3.32	3.04	2.69

AABR: Accumulation × Area Balance Ratio; ELA: equilibrium line altitude; BR: balance ratio.

Glacier- and ELA-reconstruction

Mass balance measurements by the Norwegian Water Resources and Energy Directorate from AD 1971 to 1977 indicate a glacier in equilibrium with climate in this period, with a mean ELA of 847 m, and a mean net-balance of 0.04 m w.e. (Andreassen et al., 2005; Kjøllmoen et al., 2011). The reconstructed AABR ELA for the glacier extent of 1971 suggests that the AABR-method yields accurate estimates when conducted on the reconstructed glaciers presented in this paper.

Lake Vardfjelltjønna

Vardfjelltjønna contains two sub-basins that are separated by a sill at 2-m water depth. The northern basin is viewed as the most favourable for coring because of its geographical location in the backwater relative to the main (now relict) meltwater channel entering the lake (Dahl et al., 2003). The northern basin is in addition somewhat more shielded from possible slumping of the delta front that constitutes the southeastern lakeshore.

Four small non-glacial inlet streams enter the lake in the northern and northwestern part of the lake. These inlet streams run through small catchments with little superficial sediments relative to the catchment of the main inlet. Influx of extra-glacial clastic sediments from these streams is therefore probably very limited relative to the influx of glacially derived clastic sediment flux from the main meltwater system. The stream on the northeastern lakeshore enters the lake through a small lagoon before entering the northern sub-basin (Figure 5). It appears that delta progradation has occurred on the distal side of the lagoon. Since the stream meanders through a bog north of the lake, it is assumed that most of the material transported by this stream is mostly fine-grained organic material.

Age model

The age model’s 95% confidence interval spans from 8 to 370 years, with an average of 160 years, while the 68% confidence interval spans from 2 to 168 years with an average of 81 years. Several of the obtained dates (Poz 9418, Poz 64293, Poz 5439, Poz 5440, Poz 64291, Poz 5442 and Poz 5444) are outliers (Table 3), and are therefore rejected. The three outlying bulk sediment dates (Poz 5439, Poz 5442 and Poz 5444) are rejected from the age model since they yield systematically older ages than the terrestrial macrofossils dated at the same levels. The older age is probably due to a local reservoir age, primarily suggested to be the result of garnet schist in the catchment (Søvegjarto et al., 1988). It is also a possibility that the other rejected dates may have too old apparent ages because of remobilisation of older plant material further up in the catchment prior to final deposition in Lake Vardfjelltjønna. The sample Poz 64291, which yields a young age relative to adjacent dates, is most likely contaminated by younger material. This sample contained only 0.08 µg C, and is therefore theoretically very susceptible to contamination.

Table 3.

Radiocarbon dates from VAP 104, VAP 204 and VAP 113, presented with the original depth scale (*) and the recalculated scale (**).

Core	Depth* (cm)	Depth** (cm)	Lab no.	Sample type	Radiocarbon age	Cal. yr BP ± 2σ	Cal. yr BP ± 1σ	Relative area under 1σ probability curve
VAP 104	415–416	419.1–419.9	Poz 5453	Shell	9190 ± 80	9945 ± 230^†	10,005 ± 125^†	0.68
	472.5–473	444–444.2	Poz 10456	Terrestrial macrofossils	9155 ± 50	10,330 ± 105	10,310 ± 70	0.68
	475–476	444.9–445.3	Poz 5454	Shell	9810 ± 50	10,750 ± 170^†	10,720 ± 80^†	0.68
	485–486	448.5–448.8	Poz 10292	Shell	9830 ± 70	10,790 ± 210^†	10,760 ± 110^†	0.68
VAP 204	40–50	25.2–28.6	Poz 9417	Terrestrial macrofossils	620 ± 30	605 ± 55	615 ± 35	0.53
	104–108	70.6–78.9	Poz 9418	Terrestrial macrofossils	1615 ± 30	1490 ± 75	1535 ± 20	0.35
	130–135	112.1–114.6	Poz 9419	Terrestrial macrofossils	1095 ± 30	1005 ± 55	985 ± 20	0.42
	171–175	134.9–137.2	Poz 9420	Terrestrial macrofossils	1350 ± 30	1275 ± 35	1285 ± 15	0.68
	209–213	156.9–159.3	Poz 9421	Terrestrial macrofossils	1760 ± 30	1655 ± 85	1645 ± 25	0.47
	230–234	168.8–170.8	Poz 9422	Terrestrial macrofossils	1880 ± 30	1805 ± 75	1845 ± 35	0.59
	253–254	206.1–206.8	Poz 5440	Bulk sediment	2640 ± 40	2785 ± 60	2760 ± 20	0.68
	253–254	206.1–206.8	Poz 5439	Terrestrial macrofossils	3890 ± 40	4290 ± 130	4350 ± 60	0.61
	270–274	217.7–220.4	Poz 9423	Terrestrial macrofossils	2290 ± 30	2265 ± 85	2330 ± 20	0.66
	309–313	258.6–262.3	Poz 9424	Terrestrial macrofossils	2730 ± 35	2820 ± 60	2820 ± 35	0.68
	346–347	296.1–297	Poz 5442	Bulk sediment	4020 ± 40	4500 ± 85	4480 ± 45	0.68
	346–347	296.1–297	Poz 5441	Terrestrial macrofossils	3370 ± 40	3625 ± 75	3605 ± 35	0.34
	401–402	343.0–343.4	Poz 5443	Terrestrial macrofossils	6000 ± 50	6850 ± 125	6840± 60	0.65
	401–402	343.0–343.4	Poz 5444	Bulk sediment	6250 ± 50	7140 ± 130	7205 ± 50	0.61
VAP 213	101–103	101–103	Poz 64293	Terrestrial macrofossils	1480 ± 40	1360 ± 60	1365 ± 35	0.68
	200–201	200–201	Poz 64294	Terrestrial macrofossils	2330 ± 70	2425 ± 275	2385 ± 80	0.55
	245–246	245–246	Poz 64295	Terrestrial macrofossils	2590 ± 80	2645 ± 215	2545 ± 50	0.35
	318–319	318–319	Poz 64297	Terrestrial macrofossils	4290 ± 40	4895 ± 75	4850 ± 25	0.68
	368–370	368–370	Poz 64298	Terrestrial macrofossils	7510 ± 50	8300 ± 100	8350 ± 40	0.60
	385–390	385–390	Poz 64291	Terrestrial macrofossils	7160 ± 110	7970 ± 225	7990 ± 70	0.46

Dated terrestrial bulk- and macrofossil samples are calibrated using the IntCal13 calibration dataset, while dated fragments of Macoma calcarea (^†) are calibrated using Marine13 (Reimer et al., 2013). Dates presented in italic are rejected from the age model.

The cores VAP 104, VAP 204 and VAP 113 are very well correlated (Figure 6a). This allows for a recalculation of the dated depth intervals in VAP 104 and VAP 204 to fit the depth scale of the master core VAP 113. The MS variability in VAS 113 and VAP 113 shows a strong correlation, indicating that, although slightly compressed, the sediment surface of Lake Vardfjelltjønna is present in VAP 113. The age model is thus interpolated between the radiocarbon dates and the top of the core. In addition, the construction of the embankment that closed the main inlet in AD 1950 is interpreted as the cause of an abrupt increase in LOI at 3.2 cm in VAP 113. The increase in LOI is therefore used as a time marker in the age–depth model (see section ‘Discussion’).

VAP 104

Three main units are identified in VAP 104, based on LOI, DBD and grain size distribution (Figure 7 and supplementary material, available online). The upper unit, 104-1, is characterised by DBD-values fluctuating around 1.2 g/cm³. LOI remains just above 1% except for a layer with a slightly increased LOI to 3% in the lower half of unit 104-1. The sediment is generally well sorted, although deteriorating upwards in this unit. The percentages of medium and coarse silt generally decrease upward from 29% and 24% to 24% and 21% respectively. This is accompanied by an increase in the amount of clay from 4.5% to 11%.

Figure 7.

Key variables from VAP 113 (left hand side) and VAP 104, VAP 204 (right hand side). The depth scale for VAP 104 and VAP 204 is recalculated to the master scale based on VAP 113. Each core is given an individual unit classification based on the variability of available sediment core parameters. Grey areas represent units of increased minerogenic content.

The transition between units 104-1 and 104-2 is marked by a sharp decrease in DBD to around 0.3 g/cm³ and a corresponding increase in LOI to between 18% and 40%. Two discrete layers of slightly increased DBD to about 0.6 g/cm³ are superimposed near the top of this unit while distinct and abrupt decreases in LOI occur in the middle part of unit 104-2. From the middle part to the bottom of unit 104-2, a steady downwards decrease in LOI from 29% to 1.2% and an inversely reflected downwards increase in DBD from 0.3 to 1.15 g/cm³ occur. Near the bottom of unit 104-2, a slight peak in DBD, accompanied by a slight decrease in LOI, is superimposed on the downwards decreasing LOI and increasing DBD. Mean grain size drops at this interval, mainly because of an increased contribution of clay and very fine silt (supplementary material, available online).

Sorting deteriorates abruptly at the transition between units 104-2 and 104-3, accompanied with an increase in DBD, a decrease in LOI and a shift in grain size distribution, as clay and silt dominate unit 104-3. A distinct peak in LOI occurs near the top of unit 104-3.

VAP 204

Based on LOI, DBD and grain size, four main units are recognised in VAP 204 (Figure 7 and supplementary material, available online). Unit 204-1 consists of well-sorted clastic sediments, dominated by coarse and very coarse silt. The sorting deteriorates upwards in this unit. DBD-values are generally high with values fluctuating around 1 g/cm³. A distinct peak at 1.7 g/cm³ is present in the upper part of unit 204-1. LOI-values remain stable at around 2% throughout this unit.

The transition between 204-1 and 204-2 is marked by LOI-values increased to 17%, DBD decreased to 0.3 g/cm³ and a decreased mean grain size due to an increased contribution of fine and very fine silt, which account for 21% and 11.5% of the total grain size distribution respectively. In the middle and lower parts of unit 204-3, DBD-values fluctuate around 0.25 g/cm³ and increase gradually upward with some superimposed variation from the middle part of this unit. DBD-values peak in the upper part of unit 204-3. Distinct layers of slightly increased LOI-values occur throughout unit 204-3. The percentage of coarse silt increases upward in this unit, from 20% to 27% except for one layer in the lower half of unit 204-3, where fine and very fine silt dominate the grain size distribution (supplementary material, available online). Unit 204-4 is defined as a poorly sorted organic rich sediment. LOI-values increase downwards to 48–20%, with numerous superimposed sudden drops in the lower half of the unit and accompanied by increasing DBD, medium and fine silt (Figure 7 and supplementary material, available online).

VAP 113

Based on sediment parameters, VAP 113 can be divided into subunits A–U, which constitute the five main units 113-1 to 113-5 (Figure 7). Unit 113-1 is an organic rich layer present in both VAS 113 and VAP 113 (Figure 6a). LOI increases abruptly and continually from 1.1% at the base of the unit to 4.7% at the top. Unit 113-2 is characterised by elevated MS, DBD and K-count rates. The primary sediment structure is disturbed between 20.5 and 42 cm. This disturbance limits the resolution of the interpreted stratigraphy. Still, there are no apparent major changes in the sediment properties compared with the sediment properties above and below the disturbed layer. The disturbed layer is therefore still used in the interpretation of glacier activity as an average of the whole period represented by the disturbed layer. Near the base of the disturbed layer, a distinct and abrupt decrease upwards in LOI, from 0.7% to 3% occurs, accompanied with a lowering of MS, DBD and K-count rate.

Unit 113-3 consists of layers with varying degrees of clastic and organic composition, reflected by shifting LOI, DBD, MS and K-count rate. The subunits 113-3 C, E, G, I, K, M and O have generally elevated LOI-values and low MS, DBD and K-count rate, while the intermediate subunits 113-3 D, F, H, J, L, N and P are on the other hand more minerogenic, with lowered LOI and elevated MS, DBD and K-count rate. Generally, DBD, MS and K-count rate increase upwards in unit 113-3 (Figure 7).

Unit 113-4 comprises an organic sediment type, with generally elevated LOI-values and low levels of minerogenic indicators. This is however interrupted by discrete layers of a more minerogenic nature throughout the unit, similar in magnitude and frequency to those observed in units 104-2 and 204-4 in VAP 104 and 204 respectively. Although DBD, MS and Ca- and K-count rates peak in unit 113-4 R, a distinct drop in the Ca/K ratio occurs in the lower half of unit 113-4 R (Figure 7). A peak in Ca-count rate, DBD and MS occurs in unit 113-4 T, accompanied by lower LOI-values. This variability is not present in the parameters K-count rate or Fe/K ratio. A distinct peak in K-count rate is present at the base of unit 113-4.

Unit 113-4 is correlated with the fine-grained and poorly sorted clastic unit 104-3 in VAP 104. The transition between units 113-4 and 113-5 is marked by a large increase in Ca-count rate in unit 113-5. Ca-count rate increases upwards throughout the unit, with a marked peak occurring in a layer consisting of numerous small shell fragments near the middle of unit 113-5.

Discussion

Moraine age

The lichenometric dates suggest that Leirdalsbreen retreated from the LIA glacier maximum position around AD 1773 ± 29, while readvances or halts during a general retreat culminated around AD 1793 ± 25, 1874 ± 17, 1882 ± 16, 1916 ± 12, 1971 ± 8 and 1984 ± 2.

Figure 2a shows a section of a topographic map (1:50,000), which defines the extent of Leirdalsbreen in AD 1896 (Johannesen and Paulsen, 1901). The mapped glacier front of AD 1896 coincides roughly with the presently mapped moraine M5, and this moraine is therefore presented with the age AD 1896. Yet, this historical date does not prove that M5 was formed in 1896, only that the glacier front was near M6 at the time of mapping regardless of whether the glacier was advancing or retreating. Likewise, aerial photos taken in AD 1962, 1971 and 1982 were used to map the extent of the glacier of those years. The photo-documented glacier extent of AD 1982 is very close to the extent marked by M10 and is therefore correlated to this moraine.

The combined historically dated glacier extents and lichenometrically dated M8, M9 and M10 reveal a sequence of advances and halts during the substantial retreat that has taken place since the LIA. M8, which is dated to AD 1971 ± 8 with lichenometry, is situated outside the historically dated extent of 1962. Similarly, M9 dated to AD 1984 ± 2 is situated outside M10, which is historically dated to 1982. This suggests that the aerial photos taken in 1962 and 1982 portray an advancing glacier during these years, while the lichenometric dated moraines record the retreat of the glacier front from the proximal slope of the subsequently deposited moraines M8, M9 and M10. M7 remains undated, yet the timing of the formation is bracketed between the dated M6 (AD 1916 ± 12) and the photo-documented extent of 1962. Because the aerial photos taken in 1962 most likely portray an advancing glacier, it is more likely that M7 was deposited closer to 1916 ± 12 than 1962.

Interpretation of lithology

The combined PCA axes 1 and 2 for VAP 113 (Figure 8a) explain 92.1% of the variability in the analysed sediment variables, and roughly divide the sediment parameters into three general groups. MS, DBD, and Si-, Sr- and Rb-count rates are indicators of a minerogenic sediment type, while on the contrary, LOI and the Fe/K ratio are indicators of a more organic sediment type. Ti-count rate forms the third group with a high positive score along PCA axis 2. This relationship is also evident from the correlation matrices presented in supplementary material, available online, where MS, and Si-, K-, Sr- and Rb-count rates strongly correlate with each other (ρ > 0.70). Likewise, the Fe/K ratio and LOI correlate very strongly (ρ = 0.83), and these parameters are inversely correlated with MS, and Si-, Sr- and Rb-count rates (ρ < −0.75). Like MS, DBD, and Si-, Sr- and Rb-count rates, the K-count rate is also a good indicator of minerogenic influx, as the K-count rate correlates very strongly with the minerogenic indicators included in the PCA analysis (ρ = 0.70–0.97), as well as with the PCA 1 axis plotted along the master depth scale (ρ = 0.94).

Figure 8.

(a) Fe/K, LOI, Ti, Sr, DBD, Rb, K, Si and MS plotted along PCA 1 and PCA 2. Since Fe/K is dependent on the variables Fe and K, both Fe and K are excluded from the PCA analysis. Fe and K are nevertheless plotted (red) to illustrate the variables’ approximate position. The clusters of samples corresponding to the ‘Holocene Climate Optimum’ (HCO), 8.2-ka event, ‘Medieval Warm Period’ (MWP) and the ‘Little Ice Age’ (LIA) are outlined. (b) The PCA 1 sample scores are plotted against depth alongside K and Fe/K.

Ti-count rate is normally a favourable indicator of terrestrial erosion because it is an abundant element, resistant against redox processes and less influenced by biogenic processes (Bakke et al., 2009; Croudace et al., 2006; Haug et al., 2001). Since Ti-count rate correlates poorly with other minerogenic indicators, we argue that the variation in Ti-count rate in the sediments in Lake Vardfjelltjønna is not directly related to the variability in the minerogenic composition and can therefore not be used as a proxy for minerogenic influx. Instead, K-count rate is here viewed as the best indicator of minerogenic variability in the dataset since: (1) the variability in K-count rate may to a far less extent than Si-count rate be influenced by biogenic processes alongside minerogenic input, (2) K-count rate has a much better signal to noise relationship owing to high detection sensitivity relative to Sr- and Rb-count rates, and (3) K-count rate is sampled at higher temporal resolution (0.05 cm) relative to MS, DBD and grain size variables (0.5–2 cm). Since coarse and medium silt in VAP 204 correlate well with PCA 1 (ρ = 0.78 and 0.75 respectively), we argue that these variables also record variability in the minerogenic composition to some degree. On the other hand, very fine silt and clay are inversely correlated with PCA 1 (ρ = −0.73 and −0.84 respectively), suggesting that these variables are good indicators of influx of organic sediments. Furthermore, sorting correlates very strongly inversely with PCA 1, suggesting that a well-sorted sediment is indicative of minerogenic sediment influx.

The Fe/K ratio records the surplus Fe in relation to the more stable minerogenic indicator K. The presence of surplus Fe is likely to be caused by redox related processes (Croudace et al., 2006). The Fe/K ratio is therefore interpreted to record variation in inwash of clastic sediments of an extra-glacial origin from the area surrounding the lake, relative to the influx of glacially derived sediments from the main meltwater system of Leirdalsbreen.

The Ca/K ratio records the surplus of Ca relative to K and is here used to infer the presence of biogenic carbonate in glaciomarine sediments, where high values indicate an increased presence of biogenic carbonates (Croudace et al., 2006).

Since glacier erosion is suggested to be the main primary source of minerogenic sediments that enter the lake, this implies that higher levels of the K-count rate indicate increased glacier activity, while increased LOI and the Fe/K ratio suggest an increased domination of deposition of inwashed extra-glacial sediments and/or increased organic production in the lake, at the expense of glacially derived sediments.

Continuous reconstruction of AABR-based local TPW-ELA

The reconstructed ELA of the glaciers that formed the dated moraines M1–M4, M6 and M8–M9 is linked with the dated variability in K-count rate, which is here used as a proxy for glacier activity following the rationale presented in the previous section. The relationship between the reconstructed local AABR-based TPW-ELA (Dahl and Nesje, 1992; Dahl et al., 1997) for each moraine and the corresponding K-count rate is tested using a simple second-degree polynomial regression analysis (Bakke et al., 2005b), which is presented in Figure 9a. In order to improve the relationship between the variability in K-count rate and local TPW-ELA when the glacier is very small, it is assumed that the theoretical ELA was at or above the top of the backwall during periods when the K-count rate suggests very little or an absence of glacial activity in the catchment. The relationship (R² = 0.996) shows that there is a high level of dependency between the variability in K-count rate and the AABR-ELAs calculated for each of the reconstructed glaciers. The resulting average uncertainty interval of 38 m regarding this relationship is presented as the coloured area in the ELA plots presented in Figures 9b and c and 10c.

Figure 9.

(a) K-counts (Z-score) plotted alongside reconstructed AABR ELA and the 1σ lichenometric age interval based on the moraines M1–M5 and M8 and M9. The insert plot illustrates the relationship between the standardised K-counts and AABR ELA. (b) The reconstructed continuous local TPW-ELA between 9000 cal. yr BP and the present, based on the relationship between standardised K-counts and reconstructed AABR ELA. Point 8 in the biplot in Figure 9a, a deglaciated catchment is plotted on the K curve. (c) Reconstructed continuous local TPW-ELA between 4400 cal. yr BP and the present. The reconstructed ELA for AD 1982 and LIA max is outlined. The presented curves are corrected for a land uplift of in total 81 m since 9300 cal. yr BP (Møller, 1989).

Figure 10.

(a) The ‘Liestøl relationship’ defines the exponential relationship between accumulation-season precipitation and ablation-season temperature with high precision (Dahl and Nesje, 1996; Lie et al., 2003). The relationship is based on 10 Norwegian maritime- to continental-type glaciers: (1) Ålfotbreen, (2) Engabreen, (3) Folgefonna, (4) Nigardsbreen, (5) Tunsbergdalsbreen, (6) Hardangerjøkulen, (7) Storbreen, (8) Austre Memurubreen, (9) Hellstugubreeen and (10) Gråsubreen. After Dahl and Nesje (1996). (b) Reconstructed local TPW-ELA of Leirdalsbreen and calculated winter-balance (blue line) based on tree-ring-based summer temperature from Torneträsk (red line) between AD 500 and 2004 (Grudd, 2008), local TPW-ELA and the Liestøl-relationship. Instrumentally recorded temperature (purple line) and precipitation (yellow line) from Bodø (Norwegian Meteorological Institute, 2015) are presented alongside reconstructed records. (c) Reconstructed TPW-ELA of Leirdalsbreen, reconstructed local TPW-ELA of Austre Okstindbreen (Bakke et al., 2010), Total Solar Irradiance (TSI) reconstructed from ¹⁰Be variability in polar ice (Steinhilber et al., 2009), NAO index reconstructed from lake sediments from Greenland (Olsen et al., 2012), Reconstructed Westerlies from glacier records (Bakke et al., 2008), SST based on planktic foraminifera from the Vøring Plateau (Andersson et al., 2003), tree-ring-based summer-temperature reconstruction from Torneträsk (Grudd et al., 2002) and reconstructed annual temperature based on speleothem ∂¹⁸O from the local cave, Søylegrotta (Lauritzen and Lundberg, 1999).

Paraglacial activity in the form of remobilisation of glacial debris is a common feature in all glaciated areas (Ballantyne, 2002; Church and Ryder, 1972). However, paraglacial activity is most likely a less important contributor of clastic sediments to the lake during periods with increased glacier size, because of the limited area of glacial superficial sediments in the catchment. It is more likely, however, that a paraglacial component in the variability of K-count rate is more dominant during periods of retreating glaciers because of the increased area of exposed unstable glacial sediments in till sheets and moraines that accompanies a retreating glacier front. This may explain the discrepancy between variability in K-count rate and the moraine-based ELA estimates between AD 1850 and 1950, which is represented by points 3, 4 and 5 in Figure 9a. Figure 9a shows that the variability in K-count rate is generally increasing during this period, while moraine-based glacier reconstructions on the other hand imply a generally retreating glacier. Considering the increasing area with freshly exposed glacial debris as the glacier front retreats up-valley, it is suggested that the increasing influx of K is the result of paraglacial activity.

Points 6 and 7 in Figure 9a, which link the dated moraines M8 and M9 with peaks in K-count rate, post-date the closure of the main inlet of the lake. These points are therefore most likely less representative than the other points used to define the relationship between K-count rate and local TPW-ELA. Even though the quality of the aforementioned points 3–7 is most likely less than that of points 1, 2 and 8, they are nevertheless included in the regression analysis that defines the relationship between K-count rate and local TPW-ELA. In that respect, it is suggested that paraglacial activity and the closure of the main inlet are the largest contributor to the uncertainty interval defined by the resulting R². Further uncertainty may surround the accuracy of glacier reconstructions as well as the precision of the AABR-method, as the BR may have changed in the past.

Deglaciation of the area and isolation of Lake Vardfjelltjønna from the sea

The increasing count rate of Ca relative to K upward in the glaciomarine unit U indicates a steadily decreasing minerogenic contribution from terrestrial erosion, relative to deposition of biogenic Ca from 10,650 ± 65 until 9300 ± 75 cal. yr BP. This decrease in K-count rate relative to Ca-count rate most likely records a relative decrease in the deposition of terrestrially eroded K, and thus a decreasing contribution of sediments from a large outlet glacier of the coalesced Svartisen ice caps. This large outlet glacier filled the main valley system subsequent to the separation from the inland ice sheet (Blake and Olsen, 1999) that occurred after the Narvik II glacier advance around 10,460 ± 235 cal. yr BP (recalibrated from Andersen, 1975; Andersen et al., 1995). The deglaciation of Lake Vardfjelltjønna, here dated to 10,650 ± 65 cal. yr BP, indicates a minimum age estimate for the Narvik II readvance, which according to Andersen et al. (1995) and Blake and Olsen (1999) terminated at Altermarka, about 20 km further down-valley, between 10,360 ± 160 and 10,100 ± 320 cal. yr BP.

The abrupt lowering of minerogenic indicators around 9300 ± 75 cal. yr BP, as well as the elevated Ca-count rate relative to other minerogenic indicators in sediments older than 9300 ± 75 cal. yr BP, is suggested to indicate the isolation of Lake Vardfjelltjønna from the sea. The steadily increasing levels of LOI and the Fe/K ratio immediately upwards from the interpreted isolation contact in VAP 113 probably indicate a sedimentation environment in the lake not dominated by glacier activity. Due to the elevated Ca-count rate relative to K-count rate, which is most likely indicative of biogenic carbonate, subunit T (382.5–387.5 cm) is regarded as redeposited marine sediments from the surrounding catchment (Croudace et al., 2006).

Early Holocene

An increased influx of K between 8230 ± 70 and 7920 ± 60 cal. yr BP is suggested to indicate enhanced glacier activity related to the Finse Event/8.2-ka cold event (Alley and Ágústsdóttir, 2005; Alley et al., 1997; Dawson et al., 2011; Klitgaard-Kristensen et al., 1998; Rohling and Pälike, 2005). The local TPW-ELA reconstruction illustrated in Figure 9b suggests an abrupt and severe lowering of the local TPW-ELA of 140 m starting 8230 ± 70 cal. yr BP and culminating at 8080 ± 60 cal. yr BP. Subsequently, a demise of the glacier took place until 7830 ± 60 cal. yr BP. It is, however, likely that a steadily retreating glacier existed in the highest reaches of the catchment between 7830 ± 60 and 7120 ± 45 cal. yr BP.

The period of increased influx of Ca preceding the glacier advance during the Finse Event/8.2-ka event between 8230 ± 70 and 8130 ± 65 cal. yr BP may be linked with an abruptly increased erosion rate of marine sediments situated north of the catchment due to increased precipitation. Yet, interestingly, the peak in Ca-count rate coincides with the date of the well-known Storegga Tsunami that propagated along the coast of western Norway at 8125 ± 55 cal. yr BP (Bondevik et al., 2005, 2012; Dawson et al., 2011; Svendsen and Mangerud, 1990). Hence, we cannot exclude the possibility that the observed Ca-peak represents an increased influx of biogenic carbonates originating from exposed tsunami deposits that were deposited in the lake as aerosols (Reimann et al., 2000).

Holocene Climatic Optimum

In the period between 7120 ± 45 and 4400 ± 45 cal. yr BP, influx of glacially derived clastic sediments in the lake is generally very low. Instead, in situ organic production and extra-glacial inwash dominate the sedimentation in the lake. The only exceptions are three periods of slightly increased influx of K centred between 7090 ± 45 and 6610 ± 45, 6170 ± 50 and 5700 ± 45, and 5340 ± 50 and 4700 ± 50 cal. yr BP, respectively, which may indicate the occurrence of small glaciers in the highest reaches of the catchment. These small glaciers have reconstructed local TPW-ELAs fluctuating between 1020 and 961 m.

Late Holocene–ELA variations during the Neoglaciation

A distinct glacier advance, with a TPW-ELA depression to 920 m, is reconstructed between 4420 ± 45 and 4300 ± 40 cal. yr BP, and is suggested to indicate the start of the Neoglaciation at Høgtuva. After a rise in the reconstructed TPW-ELA to 980 m, the TPW-ELA dropped to 780 m between 3920 ± 35 and 2660 ± 50 cal. yr BP. During this period, especially abrupt and marked drops in the local TPW-ELA occurred between 3830 ± 35 and 3540 ± 40, and 3270 ± 35 and 3065 ± 30 cal. yr BP. From 2660 ± 50 cal. yr BP and onwards to the present, the reconstructed local TPW-ELA of Leirdalsbreen is generally low, with periods of higher TPW-ELAs taking place about 2580 ± 50 to 2520 ± 50, 2390 ± 25 to 2210 ± 50, 2160 ± 50 to 2110 ± 50 (210–160 BC), 1890 ± 30 to 1530 ± 20 (AD 60–420), and 950 ± 40 to 700 ± 45 (AD 1000–1250) cal. yr BP. The significant rise in the local TPW-ELA occurring subsequent to LIA max, here dated to 190 ± 10 cal. yr BP (AD 1773 ± 29 from lichenometry), up to the present is interrupted by a slight depression centred at AD 1930. No independently dated moraines indicate a glacier advance around this time, yet the undated M7 is a possible candidate to represent the glacier extent during this reconstructed lowering of the local TPW-ELA, as the timing of formation of this moraine is bracketed between the dated M6 (AD 1916 ± 12) and the photo-documented extent of the glacier in AD 1962. It cannot be excluded, however, that the reconstructed lowering of the local TPW-ELA during this period is the result of increased paraglacial activity rather than a glacial advance. The latter is in accordance with historical records from the nearby Svartisen plateau glaciers (see Figure 1 for overview), which infer a steady retreat of all recorded glaciers between the last decades of the 19th century and the middle of the 20th century when some outlet glaciers entering Vesterdalen advanced (e.g. Theakstone, 2010).

The well-established Liestøl-relationship, which defines the exponential relationship between accumulation-season precipitation and ablation-season temperature at the TPW-ELA adjusted for land uplift (Dahl and Nesje, 1996: with references; Lie et al., 2003; Liestøl, 1967), is here applied on the temporal TPW-ELA-variations of Leirdalsbreen and the independent tree-ring-based temperature reconstruction from Torneträsk (Grudd, 2008) in order to estimate the temporally varying winter-balance at the local TPW-ELA since AD 500. We argue that the Torneträsk record is a representative measure of summer temperature for the area after adjusting the variability against the mean temperature during the normal period AD 1961–1990 from the nearby weather station at Mo i Rana airport (Station 79600 – Norwegian Meteorological Institute, 2015). An environmental lapse rate of 0.6°C/100 m and a vertical precipitation increase of 8%/100 m are assumed to be representative for the area, and are used in the calculations (e.g. Dahl and Nesje, 1996). Due to the maritime nature of Leirdalsbreen, changes in precipitation may have a profound effect on the variability on the local TPW-ELA of the glacier. Figure 10 shows that on several occasions, temperature estimates have marked peaks while the reconstructed local TPW-ELAs remain low. The Liestøl-relationship quantifies the combined effects of winter-balance and ablation-season temperature on the local TPW-ELA and hence indicates periods of increased winter-precipitation between AD 675–800, 925–1000, 1300–1325, 1360–1450, 1490–1570 and 1740–1790. In fact, both the Torneträsk time series and the speleothem ∂¹⁸O-record from Søylegrotta indicate that the temperature peaked during the most extensive glacier advances throughout the LIA, as well as during the former part of the ‘Medieval Warm Period’ (Grudd, 2008; Lauritzen and Lundberg, 1999). These glacier advances are therefore most likely the result of increased winter-balance, which is in accordance with mild winters. Hence, the prevailing snow-bearing wind direction during periods with mild winters is suggested to have been dominated by relatively warm and humid subtropical air masses from west–southwest, whereas periods with a lower winter-balance and cold summers/low annual temperatures may have been dominated by drier arctic air masses with a prevailing wind direction from north-northwest. The alternating warm/wet and cold/dry periods is here suggested to reflect a north–south migration of the arctic polar front, as a northward migration of the polar front leads to a dominating warm saturated subtropical air masses from the west–southwest, while a southward migration of the polar front leads to a domination of cold and dry arctic air masses.

Comparison with other sites

Although the Finse Event/8.2-ka cold event is viewed as a cold and dry period in Greenland ice cores (Alley and Ágústsdóttir, 2005; Rohling and Pälike, 2005), the pollen stratigraphy from Vanndalsvatnet in western Norway indicates more humid conditions in that area during the interval 8200–7850 cal. yr BP (Nesje et al., 2006). The ∂¹⁸O-based annual temperature reconstruction from Søylegrotta (Figures 1 and 12c) indicates a temperature drop centred at 8200 cal. yr BP (Lauritzen and Lundberg, 1999), which coincides with a glacier advance at Leirdalsbreen. Yet, the magnitude of the glacier advance is relatively limited compared with Neoglacial advances that occurred during periods with significantly higher reconstructed temperatures relative to the Finse Event/8.2-ka cold event. This implies that a lowering of ablation-season temperature, most likely without a significant intensification in winter-precipitation, caused the glacier advance recorded at Leirdalsbreen.

A continuous Holocene ELA reconstruction of Austre Okstindbreen at Okstindan (see Figure 1 for location map) suggests a severe, yet short-lasting, glacier advance that culminated around 7150 cal. yr BP with an ELA-depression with a similar magnitude as Neoglacial advances (Bakke et al., 2010). This event is without a comparable counterpart at Høgtuva, as fluctuations of only very small magnitude within the very highest reach of the reconstructed local TPW-ELA occurred here between 7920 ± 60 and 4400 ± 45 cal. yr BP. The large difference in reconstructed local TPW-ELA between these two sites is interesting considering the close proximity between the two sites (roughly 60 km). A probable cause for the discrepancy may be a large west–east gradient in ablation-season temperature and/or accumulation-season precipitation around 7150 cal. yr BP. Since Austre Okstindbreen is more continental in nature relative to Leirdalsbreen with average winter-balances of 2.20 and 3.21 m w.e., respectively, Austre Okstindbreen is theoretically more sensitive to changes in glacier size because of variations in ablation-season temperature than Leirdalsbreen (Andreassen et al., 2005; Holmlund and Schneider, 1997; Nesje et al., 2000b). In that respect, one explanation could be that the advance around 7150 cal. yr BP at Okstindan was induced by a reduction in temperature rather than an increase in accumulation-season precipitation.

Glacier advances of similar magnitude are recorded in southern Norway, at continental localities in western Jotunheimen between 7200 and 6900 cal. yr BP, and eastern Jotunheimen between 7500 and 6800 cal. yr BP (Lie et al., 2004; Nesje, 2009), as well as at the semi-continental northern sector of Hardangerjøkulen between 7200 and 6000 cal. yr BP (Dahl and Nesje, 1994, 1996). On the contrary, the more maritime glaciers Sørsendalsbreen, Jostedalsbreen, Northern Folgefonna, and Spørteggbreen were very small or possibly even completely melted away around 7150 cal. yr BP (Bakke et al., 2005a, 2005c, 2013; Laumann and Nesje, 2014; Nesje, 2009; Nesje et al., 2000a).

The comparison between the reconstructed ELA around 7150 cal. yr BP at Leirdalsbreen and at Okstindan is in accordance with this general trend in southern Norway and further implies that the causal climatic forcing leading up to the advance of continental glaciers in southern Norway was most likely active, and possibly even more influential in northern Norway. It is here hypothesised that the maritime–continental gradient in the causal climate-forcing mechanism around 7150 cal. yr BP is mainly related to temperature, rather than winter-balance and was triggered by a general drop in TSI between 7500 and 7100 cal. yr BP. GCM simulations suggest that the climatic response to drops in TSI is differential cooling between maritime and continental regions, as the response of the North Atlantic is relatively more gradual and thus acts as a buffer to high-frequency changes in the TSI (Plunkett and Swindles, 2008). Hence, the irregular glacier advances recorded between maritime and more continental sites in Scandinavia around 7150 cal. yr BP may have been triggered by a cooling induced by a sequence of periods with low TSI recorded between 7400 and 7100 cal. yr BP (Steinhilber et al., 2009). The implications of this hypothesis are that changes in irradiance may cause a continental cooling that is sufficient for large scale glacier advances of continental alpine glaciers, while maritime glaciers are less, if at all, affected because of (1) less severe cooling in maritime regions and (2) that maritime glaciers are less sensitive to changes in temperature (Andreassen et al., 2005; Holmlund and Schneider, 1997; Nesje et al., 2000b).

The reconstructed summer temperature based on tree-ring density from Torneträsk indicates a severe temperature drop between 7400 and 7200 cal. yr BP, while the annual temperature reconstruction based on ∂¹⁸O-fractionation from Søylegrotta indicates only a slight depression in temperature around 7000 cal. yr BP (Hald et al., 2007; Lauritzen and Lundberg, 1999). Hence, regional temperature reconstructions are somewhat differing around this time period, yet generally point in the direction of a cooling in this time period. This may in turn confirm that a period of lower summer temperatures was the cause for the regional advance at semi-continental to continental glaciers.

In addition to the distinct discrepancy between the ELA records of Leirdalsbreen and Austre Okstindbreen around 7150 cal. yr BP, glacier retreat is recorded at Leirdalsbreen during small glacier advances of Austre Okstindbreen around 6560, 6000, 5150, 3200 and 2200 cal. yr BP. Interestingly, these glacier advances are all synchronous with, or slightly lagging distinct drops in TSI. It is therefore suggested that drops in summer temperature related with TSI variability caused these glacier advances. The timing of the aforementioned glacier advances is on the other hand susceptible to misinterpretation because of the high frequency of change in TSI relative to dating uncertainty. Better age control is thus crucial in order to test hypotheses regarding causal mechanisms to the deviating ELA reconstructions between the maritime Leirdalsbreen and the more continental Austre Okstindbreen.

The distinct glacier advance of Leirdalsbreen at 4420 ± 45 cal. yr BP, which marks the onset of the Neoglacial at Høgtuva, is synchronous with a culminating glacier advance of Austre Okstindbreen at 4420 cal. yr BP (Bakke et al., 2010). The start of the glacier advance at Okstindan is however much earlier than what is observed for Leirdalsbreen. This is possibly due to the higher altitude of Austre Okstindbreen. Furthermore, the local TPW-ELA reconstruction between 4420 ± 45 and 2600 ± 50 cal. yr BP presented here is similar to the reconstruction given in Bakke et al. (2010) for Austre Okstindbreen, although the magnitude of retreats and readvances prior to 2600 ± 50 cal. yr BP have generally higher relative amplitudes in the local TPW-ELA reconstruction presented here, compared with the Okstindan-record (Bakke et al., 2010). These different dynamical responses most likely record the effect of changes in winter-balance on the two glaciers, as the more precipitation-dependent Leirdalsbreen was generally small with superimposed advances during the period between 4420 ± 45 and 2600 ± 50 cal. yr BP, when the westerlies were relatively weak, and larger during the subsequent period when the westerlies intensified (Bakke et al., 2008). In accordance with this hypothesis, the opposite is true for Austre Okstindbreen (Bakke et al., 2010). Leirdalsbreen is hence more sensitive to change because of temporally varying winter-balance (Andreassen et al., 2005; Holmlund and Schneider, 1997; Nesje et al., 2000b).

The abrupt and marked glacier advance of Leirdalsbreen between 3830 ± 35 and 3540 ± 40 cal. yr BP is synchronous with glacier advances at nearby Okstindan, as well as in glacier variation records of Jostedalsbreen and western Jotunheimen in southern Norway (Bakke et al., 2010; Nesje, 2009). The glacier advance is most likely related to a similarly abrupt and short-lasting drop in mean annual temperature reconstructed from local speleothem ∂¹⁸O-variability (Lauritzen and Lundberg, 1999), summer-temperature records from the nearby Vøring Plateau (Hald et al., 2007) and tree-ring studies from Torneträsk (Grudd et al., 2002). The coherency between the aforementioned records confirms that the observed temperature drop was a short-lasting regional phenomenon. Furthermore, the mean annual temperature drop recorded in the Søylegrotta speleothem is apparently more severe than the corresponding drop in summer temperatures from the tree-ring- and marine archive, which may indicate that the temperature drop in this period was more pronounced during winter than summer, consequently.

Conclusion

Based on the above discussion, the following results and implications of local and regional importance are suggested:

Seven moraines were dated by lichenometry with uncertainty estimates based on six growth rate functions constructed for three sites within 43 km of the study area. The combination of lichenometry and historical records constrains the LIA glacial maximum to AD 1773 ± 29 (1σ), while subsequent glacier advances/halts are dated to 1793 ± 25, 1874 ± 17, 1882 ± 16, 1896 and 1916 ± 12. Between AD 1916 ± 12 and 2013, the glacier front has retreated 3 km up-valley, interrupted by two small readvances in the early 1970s and early 1980s respectively.

The variability of K-count rate and the Fe/K ratio in the sediments from the distal fed Lake Vardfjelltjønna are interpreted to record the balance of influx between glacially eroded clastic sediments and extra-glacial inwash. Reconstructed local TPW-ELA is based on the dated moraines and the variability of K, and is thus continuously reconstructed for the last 9300 ± 75 cal. yr BP.

A continuously reconstructed local TPW-ELA suggests a significant glacier advance centred at 8080 ± 60 cal. yr BP. The event lasted for about 300 years before the catchment was probably completely deglaciated throughout the Holocene Climate Optimum (HCO) between 7120 ± 45 and 4400 ± 45 cal. yr BP. Eight separate Neoglacial advances and retreats are identified between 4400 ± 45 cal. yr BP and the present. Both the dated sequence of moraines and the sediments from Vardfjelltjønna suggest that the LIA glacial maximum, here dated to 190 ± 10 cal. yr BP/AD 1773 ± 29, was the most extensive glacier advance during the last 9000 years.

A comparison of the temporally variable local TPW-ELA reconstructions between Leirdalsbreen and Austre Okstindbreen reveals that the amplitude of ELA variation is greater at Leirdalsbreen before 2600 ± 50, whereas the amplitude of ELA variation is greater at Austre Okstindbreen after 2600 ± 50 cal. yr BP. This discrepancy is probably related to each of the glaciers’ susceptibility to changes in ablation-season temperature and accumulation-season precipitation.

TSI variations are proposed as the cause of the deviating glacier variability recorded between maritime and continental regions in Scandinavia about 7150 cal. yr BP. Deviating reconstructed ELA fluctuations between Leirdalsbreen and Austre Okstindbreen at about 6560, 6000, 5150, 3200 and 2200 cal. yr BP were possibly caused by temperature drops related to TSI variability. However, better age control is needed in order to test the latter hypothesis.

The regional summer-temperature proxy based on tree-ring density from Torneträsk, as well as a local mean annual temperature proxy based on ∂¹⁸O, indicates that the most extensive glacier advances since AD 500 occurred during temperature peaks, suggesting that these glacier advances were mainly induced by significant increases in precipitation. Furthermore, calculation of precipitation based on the Liestøl-relationship indicates periods of increased winter-balance between AD 675–800, 925–1000, 1300–1325, 1360–1450, 1490–1570 and 1740–1790. The most extensive Holocene glacier advances occurred during periods with high summer temperature. Hence, significantly increased winter-balance is suggested for these periods. The alternating warm/wet and cold/dry periods are suggested to reflect a north–south migration of the arctic polar front, as a northward migration of the polar front leads to dominating warm saturated subtropical air masses from the west–southwest, while a southward migration of the polar front leads to a domination of cold and dry arctic air masses.

Footnotes

Acknowledgements

We sincerely thank two anonymous reviewers for important advice that allowed us to improve the text. HLJ is thankful for field assistance by Erlend Vikestrand and for fruitful discussions with Sunniva Solheim Vatle. Sincere thanks to Benjamin Aubrey Robson for reviewing the language.

Funding

This research project was funded by The Norwegian Research Council (NFR) and the Meltzer research fund.

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