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Holocene climate and vegetation change on Victoria Island, western Canadian Arctic
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Quaternary Science Reviews 27 (2008) 235–249
Holocene climate and vegetation change on Victoria Island, western Canadian Arctic Matthew C. Peros, Konrad Gajewski Laboratory for Paleoclimatology and Climatology, Department of Geography, University of Ottawa, Ottawa, ON, Canada K1N 6N5 Received 26 January 2007; received in revised form 2 August 2007; accepted 3 September 2007
Abstract A detailed pollen record from Victoria Island provides the first quantitative Holocene climate reconstruction from the western Canadian Arctic. The pollen percentage data indicate that Arctic herbs increased over the Holocene in response to long-term cooling. The influx of locally and regionally derived pollen grains varies throughout the core and tracks several major changes observed in the biogenic silica record from Arolik Lake, Alaska, and the GISP2 ice-core, suggesting that climate change closely controlled Arctic plant productivity. Using modern analogue and transfer function techniques, we generated quantitative reconstructions of mean July temperature and total annual precipitation for the past 10 000 years, to place recent climate changes within the context of Holocene climate variability. The quantitative reconstructions indicate that July temperature cooled by 1–1.5 1C during the Holocene. The pollenbased reconstructions record an increase in temperature of 0.5 1C over the last 100 years, and the pollen percentage and influx data indicate impacts of recent warming on the regional vegetation. r 2007 Elsevier Ltd. All rights reserved.
1. Introduction A range of measurements and model predictions confirm that Arctic environments are undergoing profound changes in response to global warming (Serreze et al., 2003). Both sea and land ice thickness and extent, for example, have decreased dramatically over the last few decades (Comiso, 2002), with implications for global sea level rise (Peltier, 2004), ocean circulation (Lohmann and Gerdes, 1998), Arctic animal communities (Derocher et al., 2004), regional and global economies (Kerr, 2002), and the traditional lifestyles of indigenous peoples (Tenenbaum, 2005). Aquatic algae and invertebrate communities in many Arctic lakes have also undergone significant and widespread changes over the last century (Smol et al., 2005). The effects of climate change on Arctic plant communities are less clear. The response of vegetation to global warming is expected to involve a combination of range expansion, higher productivity, and increased competition Corresponding author. Tel.: +1 613 562 5800x1734; fax: +1 613 562 5145. E-mail address: [email protected] (M.C. Peros).
0277-3791/$ - see front matter r 2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.quascirev.2007.09.002
(Callaghan and Jonasson, 1995; Cornelissen et al., 2001). However, many Arctic plants are sparsely distributed across large, often circumpolar ranges and have broad ecological tolerances, so the potential impact of climate variations is uncertain. A paleoecological perspective may provide insight into the relative importance of these processes and hence the future of terrestrial Arctic ecosystems. However, fossil pollen studies from the Canadian Arctic are rare, in part because of the low pollen productivity of many Arctic plants (Gajewski, 1995) and chronological problems with many paleolimnological records (Gajewski et al., 1995, 2000). If these problems are surmounted, as we have done here, such studies have the potential to provide information on vegetation history and climate variability that cannot be gleaned from other sources. Using pollen data derived from sediments lifted from a small lake on Victoria Island, in the Northwest Territories, Canada, we provide the first well-dated, temporally detailed record of Holocene vegetation change from the western Canadian Arctic Archipelago. Utilizing data from a new, expanded modern pollen database (Whitmore et al., 2005), we have also developed the first quantitative reconstructions of mean July temperature (TJul) and total
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annual precipitation (PAnn) of the region that enable us to place the rate and magnitude of 20th century climate variability in a long-term context. 2. Study site The lake, unofficially named KR02, is located in the Kuujjua River region of northwestern Victoria Island, Northwest Territories, Canada, at 71.341N, 113.781W, and 299 masl (Fig. 1). Lake KR02 has a surface area of 0.79 ha and a maximum depth of 6.1 m. The lake is located on the junction of the Shaler and Natkusiak Formations; the regional bedrock consists of clastic and carbonate sediments and basalts (Frisch and Trettin, 1991). Victoria Island was glaciated during the Wisconsinan; the Kuujjua River region appears to have been ice-free by 12 ka BP (Dyke, 2004). The surface geology consists of thin and discontinuous till with frequent bedrock outcrops (Fulton, 1995). The closest weather station is at the town of Ulukhaktok (Holman), 150 km from Lake KR02 on the west coast of Victoria Island, where mean January and July temperature are 28.6 and 9.2 1C, respectively, and mean annual precipitation is 162.5 mm (Meteorological Service of Canada, 2006). The vegetation is a prostrate shrub tundra (CAVM, 2003). Edlund (1983) classifies the Kuujjua River valley as Low Arctic, with uplands supporting a Middle Arctic vegetation. The vegetation cover is nearly contin-
uous in the valley, with Dryas, along with various sedges, grasses, Salix, Artemisia and several species of Fabaceae important constituents of the flora (Edlund, 1983). Large willows have been reported in the region (Edlund and Egginton, 1984) and a tree-ring series has been developed from a population of Salix alaxensis in the area of KR02 (Zalatan and Gajewski, 2006). 3. Methods 3.1. Field and laboratory To study past vegetation and climate changes in northwestern Victoria Island, a 411 cm-long sediment core was lifted from the deepest part of Lake KR02 in early summer, 2001, using a modified Livingstone piston corer. The uppermost sediments were sampled using a clear plastic tube fitted with a piston. The upper 20 cm of the core was extruded in the field to preserve the sediment–water interface. We established a chronology using both 210Pb and accelerator mass spectrometry (AMS) 14C techniques. For 210 Pb dating, continuous slices of the upper 21 cm of the core were analyzed and ages were derived by a constant rate of supply (CRS) model. For AMS dating, since no terrestrial macrofossils were identified in the core, subsamples consisted of a range of microfossils (e.g., chironomid head-capsules, moss debris) picked from the
Fig. 1. Location of Lake KR02 (71.341N, 113.78.781W, 299 masl) in the Canadian Arctic Archipelago. The back dots represent the locations of the modern pollen data used in this study (n ¼ 87). Those modern samples that appear as one of the best five analogues in the modern analogue technique (MAT) reconstruction are indicated by a white dot at their center (see Fig. 7). The locations of the GISP2 ice-core site and Arolik Lake, Alaska, discussed later in the text, are also shown.
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sediment matrix or, where these materials were insufficient in quantity, bulk sediment samples. Radiocarbon ages were calibrated using cubic spline fitting (Talma and Vogel, 1993) of the data from the INTCAL 98 data set (Stuiver et al., 1998). Ages were assigned to the core using linear interpolation between all 210Pb and (calibrated) 14C dates. The ages of the sediments deeper than the oldest reliable 14 C date were extrapolated using the oldest interpolated age-depth model value. Magnetic susceptibility was measured downcore at continuous 1 cm intervals using a Bartington MS2 meter. Organic matter and calcium carbonate content were estimated at continuous 0.5–1 cm intervals following ignition of the samples at 500 1C (for 3 h) and 950 1C (for 4 h) (Dean, 1974). Fossil pollen was examined from subsamples taken at intervals of 1–10 cm throughout the core. First, a known quantity of exotic spores was added to each subsample so pollen concentration could be estimated. Then, the fossil pollen was concentrated by treating the sediment with 10% HCl, 10% KOH, HF, and acetolysis solution (Faegri and Iversen, 1989). Most samples also underwent heavy-liquid separation using sodium polytungstate (SPT) to assist in the removal of heavy minerals (Bolch, 1997). Several samples were processed with and without the heavy liquid method and showed no statistical differences in pollen counts (Zabenskie, 2006). Pollen was identified using the Laboratory for Paleoclimatology and Climatology slide reference collection, as well as published atlases (McAndrews et al., 1973; Kapp et al., 2000). In total, 69 levels were counted, with at least 400 pollen and spores enumerated for most subsamples. Pollen influx values were estimated for each subsample by multiplying the pollen concentration by the sediment accumulation rate (SAR) as determined by linear interpolation of the 210Pb and 14C data. To test how sensitive the pollen influx values were to the SAR, we repeated this latter step using a SAR derived from a sixth-order polynomial, which produced similar results. Because the fossil pollen record from Lake KR02 contains high quantities of boreal taxa transported from far to the south, the pollen percentage diagram was constructed using three sums: (1) only local and regional taxa (excluding spores); (2) all long-distance taxa (e.g., Pinus, Picea) as well as those within group (1); (3) the entire assemblage (including unidentifiable/unknown grains).
important for constraining high-latitude plant growth (Billings, 1987). In order to focus on the climate history of northwestern Victoria Island, all long-distance taxa and local spores were removed from the modern and fossil data sets before percentages were calculated. ‘Rare’ pollen taxa were not omitted so we could maintain as high a pollen sum as possible. We undertook reconstructions of both variables using modern analogue (MAT) and transfer-function techniques (Overpeck et al., 1985; Birks, 1995); multiple methods were chosen to determine how reproducible the reconstruction methods are for our data set. Prior to the calculation of the transfer functions, two detrended canonical correspondence analyses (DCCA) were performed on the modern samples to estimate the lengths of the TJul and PAnn gradients. The DCCA analyses generated gradients of 1.016 and 0.712 SD units for TJul and PAnn, respectively, indicating that linear transfer-function techniques would be most appropriate (Birks, 1995). We selected Partial Least Squares (PLS) regression as the linear method, although we also undertook the same procedure using Weighted Averaging Partial Least Squares (WAPLS), a commonly used unimodal-based method (Birks, 1995). For the MAT, we selected the square-chord distance dissimilarity coefficient, a robust ‘signal-to-noise’ metric (Overpeck et al., 1985; Jackson and Williams, 2004). Next, we performed a bootstrap cross-validation using each of the MAT and transfer-function models to identify outliers among the modern samples. On the basis of the cross validation results, one outlier was removed (ID2 4371 from Whitmore et al., 2005). The models were then re-run, again using bootstrap cross-validation to generate samplespecific standard errors and assess model performance, and reconstructions were generated. For the MAT, the unweighted mean of the nearest five best analogues was calculated for each fossil sample. For the transfer functions, 1-, 2-, and 3-component models were generated; we identified the most robust model as having the fewest components, highest bootstrap coefficient of determination (r2(boot)), lowest root mean square error of prediction (RMSEP), and lowest bootstrap mean and maximum biases (Birks, 1998). The DCCAs were performed using CANOCO v4.5 (ter Braak and Sˇmilauer, 2002). The MAT and transfer functions were implemented using C2 v1.4.3 (Juggins, 2003).
3.2. Climate reconstruction
4. Results
Pollen percentage and climate data were extracted from the North American Modern Pollen Database (Whitmore et al., 2005). Our modern samples include all lacustrine sites within the western and central ‘Arctic’ biome (4831W), as well as the pollen assemblage from the upper 1 cm of sediment from core KR02 (n ¼ 87) (Fig. 1). We reconstructed mean July temperature (TJul) and total annual precipitation (Pann) because these variables are
4.1. Stratigraphy and chronology Organic matter averages 20% of the dry weight of the core from the interval represented by 5.0–10.5 ka BP, and then steadily increases to 40% by 2.3 ka BP (Fig. 2). The highest values (58%) occur in the most recent sediments in the core. Magnetic susceptibility is low throughout most of the core, although it increases substantially in the
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Fig. 2. Sedimentary characteristics and age-depth model for core KR02. The age-depth model is based on a linear-interpolation between the median values of the 2s error ranges of the AMS dates. The earliest 14C date is at 800 yr BP. The chronology above this level was based on 210Pb dating. The sedimentation rate as determined by a sixth-order polynomial is plotted against the sedimentation rate generated by linear interpolation (see text).
deepest sediments, concurrent with the presence of a sandy unit. With the exception of this basal sand, the core has a uniform color and texture (Podritske, 2006). The 210Pb and 14C results are listed in Tables 1 and 2, respectively. The age-depth model, based on a linear interpolation of these results, shows a fairly linear sediment accumulation rate of 0.037 cm yr1 (Fig. 2). This rate is faster in the upper 20 cm of the core, likely due to limited autocompaction. The ages of pollen samples below the oldest date were estimated by linear extrapolation of the curve. We have rejected a date of 18,9507170 14C yr BP, from 406 to 407 cm (Table 1), as being too old; otherwise we argue that the remainder of the chronology is sound, and in the discussion provide several lines of evidence to support this claim. 4.2. Vegetation history The bottommost pollen assemblage, dated at 10.2 ka BP, contains high quantities of Artemisia, Poaceae and Salix pollen (Fig. 3), indicative of a polar desert (Gajewski, 2002). Both Poaceae and Salix percentages are relatively high until 9.8 ka BP, after which time they are replaced by Cyperaceae, whose values rapidly exceed 90% of the local and regional pollen sum. These percentages
then begin to decrease, slowly at first, and then more rapidly after 5.5 ka BP, although Cyperaceae still remains the dominant pollen type throughout the remainder of the core. Concurrent with this decline in Cyperaceae are increases in Poaceae and several Arctic herbs. Dryas and Saxifraga oppositifolia increase gradually, whereas increases in Artemisia, Oxyria, Poaceae and Papaver are more abrupt, beginning 6.5, 5.2, 2.8, and 1.2 ka BP, respectively. Polypodium and Sphagnum spores, which may have a local origin but were removed from the local and regional pollen sum, show relatively stable percentages throughout the early and middle Holocene, and increase slightly in the late Holocene. The long distance pollen percentages reflect the transport of pollen from regions to the south of Lake KR02. Betula was abundant immediately following deglaciation, and then decreased by 9.5 ka BP. Its percentages continued to slowly decline until 2.2 ka BP, after which time they deceased further, averaging around 20%, until around 100 years ago. Today, shrub birch grows on western Victoria Island, where it is not abundant, and the adjacent mainland (Porsild, 1957), and it seems likely that much of the fossil Betula originated from the shrubs B. glandulosa and B. nana subsp. exilis, which are common in low Arctic tundra. The Alnus profile, consisting largely of pollen from
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Table 1 Radiocarbon dates and calibrated ages (cal yr BP) from the KR02 sediment core Lab code
Depth (cm)
Conventional age (yr BP)
Beta-199874 Beta-199875 Beta-199877 Beta-206009 Beta-199878 Beta-206010 Beta-206011 Beta-213872 Beta-199879 Beta-206012
37.5–39.5 70–73 208–209 241–243 291–293 314–317 333–335 349–351 362–364 404–407
890740 1680750 3500740 4270740 5760750 6150750 7050750 8590740 8730760 189507170
14
C
2-F calibrated age range (cal yr BP)
Median calibrated age (cal yr BP)
d13C
Material
710–920 1500–1710 3670–3870 4820–4870 6430–6670 6890–7200 7760–7960 9520–9570 9550–9920
815 1605 3770 4845 6550 7045 7860 9545 9735 Rejected
27.6 No data 25.5 29.3 30.3 28.1 28.7 29.1 27.1 24.1
Bulk sediment Macrofossils Macrofossils Bulk sediment Bulk sediment Macrofossils Macrofossils Macrofossils Macrofossils Bulk sediment
The date at 404–407 cm was not used in the chronology.
Table 2 Lead-210 dates from the KR02 sediment core Depth (cm)
Year AD at bottom of slice based on CRS model estimate
2.0–3.0 3.0–4.0 4.0–5.0 5.0–6.0 6.0–7.0 7.0–8.0 8.0–9.0 9.0–10.0 12.0–13.0 14.0–15.0 16.0–17.0 18.0–19.0 20.0–21.0
1995 1993 1990 1985 1980 1976 1972 1957 1934 1920 1901 1873 1837
the forest-tundra shrub A. crispa, records values that are initially low, but then undergo a rapid and substantial increase between 8.0 and 7.6 ka BP. Following this rise, Alnus percentages are essentially constant, although decrease in the most recent sediments. Of the tree pollen, Picea grains are present by 9.5 ka BP and gradually increase until 5.0 ka BP, after which time they slowly decrease. Pinus, whose northern limit is farther south, begins to increase around 7.0 ka BP and then levels off. The pollen influx values for most local and regional taxa are high between 9.0 and 10.0 ka BP (Fig. 4). After 8.0 ka BP, the influx of Poaceae, Cyperaceae, and Salix pollen increases in two pulses, each lasting 800 years. Local and regional influx values then remain low, but do vary following these events. While the overall influx patterns are similar between the local and regional and long distance curves, the individual long distance taxa themselves differ. The Betula curve, for example, more closely resembles the local and regional influx data than the curve of Pinus. In large part, these differences likely reflect
the migration history of each plant. However, they may also be due to the proximity of the pollen source to Lake KR02. Much of the Betula pollen likely comes from a closer source area than the Pinus pollen, suggesting that the birch plants from where the Betula pollen are derived responded to the same environmental factors as the local and regional taxa. 4.3. Environmental change over the last 1000 years A closer examination of several of the aforementioned records provides insights into the nature of 19th and 20th century environmental changes (Fig. 5). Organic matter remained relatively constant, at 36% of the dry weight of the core, throughout much of the last millennium, but began a steady increase 130 years ago. Local and regional pollen influx shows a similar pattern, although the timing of the initiation of this increase is difficult to pinpoint given the pollen sample density in this portion of the core. Likewise, percentages of Cyperaceae (typically indicative of Middle Arctic environments; Gajewski, 2002) increase over the last 100 years, concurrent with decreases in Artemisia, Oxyria, and Papaver. All these lines of evidence suggest the onset of warmer conditions beginning around AD 1870. While the resolution of the pollen data is low for this portion of the KR02 record, the temporally detailed organic matter results suggest that the rate and magnitude of this warming is unprecedented over the last 1000 years. 4.4. Climate reconstructions 4.4.1. Model performance Performance statistics of our modern training set are summarized in Table 4. On the basis of the root mean square error of prediction (RMSEP), bootstrap coefficient of determination (r2boot), and maximum bias values, the modern analogue technique (MAT) outperforms both Partial Least Squares (PLS) and Weighted Averaging
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M.C. Peros, K. Gajewski / Quaternary Science Reviews 27 (2008) 235–249 Fig. 3. Pollen percentage values for core KR02. Note that the pollen percentage diagram was constructed using three sums: (1) only local and regional taxa (excluding spores); (2) all long-distance taxa (e.g., Pinus, Picea) as well as those within group (1); (3) the entire assemblage (including unidentifiable/unknown grains). A complete taxon list, along with the sum each species is classified within, is provided in Table 3.
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M.C. Peros, K. Gajewski / Quaternary Science Reviews 27 (2008) 235–249 Fig. 4. Pollen influx values for core KR02 in grains cm2 year1 (bottom axis). Note that the x-axis scale differs for certain graphs. The ‘local and regional’ and ‘long distance’ influx curves are based on the sums of the influx values of the individual taxa within those groups. Curves of the local and regional and long distance pollen concentrations are also plotted and show a similar overall pattern as pollen influx, consistent with the fairly linear sediment accumulation rate.
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M.C. Peros, K. Gajewski / Quaternary Science Reviews 27 (2008) 235–249 Table 3 Classification by source area of all pollen taxa identified in core KR02
Fig. 5. Summary diagram highlighting changes over the last 1000 years. Note that organic matter values are percentages; pollen influx is in grains cm2 year1; and the Artemisia, Cyperaceae, Oxyria, and Papaver graphs are percentages based on the local and regional pollen sum. The ages for the last 150 years in this diagram were determined by 210Pb dates, thus year ‘‘0’’ is AD 2001, the year core KR02 was sampled.
Partial Least Squares (WAPLS) transfer functions for both TJul and PAnn. This is not the case for mean bias, however, where PLS seems to produce the best results, with the MAT significantly underperforming for PAnn. Birks (1998) argues that the r2 value is indicative of the strength of the relationship between observed and predicted values and is thus useful when comparing the predictive ability of inference models for different environmental variables. In our case, the r2(boot) values of the transfer functions and MAT are higher for TJul than for PAnn, indicating a greater degree of confidence with the TJul reconstructions. The predictive power of our training set can also be assessed by examining scatter-plots of reconstructed versus observed values (Fig. 6). Ideally, the data points in the two left-hand frames should lie on the diagonal lines, indicating a 1:1 correspondence between predicted and observed values. On the right-hand side, the residuals should show no pattern and lie along the horizontal line. A consistent trend among all reconstructions is the overestimation of low values and underestimation of high values at the ends of the sample gradient. This phenomenon is especially clear when examining the residual plots, and has been observed in numerous other training set reconstructions, using a range of indicators (e.g., Lotter et al., 1997). This ‘edgeeffect’ is characteristic of WA-based transfer function methods, like WAPLS and PLS (Birks, 1998), and appears
Local and regional
Long distance
Apiaceae Artemisia Asteraceae (Liguliflorae) Asteraceae (Tubuliflorae) Brassicaceae Caryophyllaceae Cassiope Cephalanthus Chenopodiaceae Cupressaceae Cyperaceae Dryas Epilobium Ericaceae Fabaceae Oxyria/Rumex Papaver Pedicularis Plantago Poaceae Polygonaceae Polygonum viviparum Potentilla Rosaceae undifferentiated Salix Saxifraga oppositifolia Saxifragaceae other
Abies Alnus Ambrosia Betula Cornus Corylus Juglans Larix Picea Pinus Populus Potamogeton Rubus chamaemorus Shepherdia canadensis Thalictrum Ulmus Other Drypoteris Polypodium Sphagnum Trilete spore Indeterminable/unknown
to be the result of the use of inverse deshrinking regression, which tends to pull the predicted values toward the mean of the training set (ter Braak and Juggins, 1993). With the MAT, however, the ‘edge-effect’ appears to have a different cause; analogues with intermediate TJul and PAnn values appear to be contributing to the reconstructed values for samples at the ends of the gradient, likely because of the large number of samples with intermediate values that can be drawn as one of the top five best analogues. Overall, the plots in Fig. 6 indicate that the MAT, as implemented in this paper, outperforms both transfer functions when reconstructing high and low values, whereas the transfer functions do slightly better for mid-gradient predictions. 4.4.2. Climate reconstruction Our reconstructions show that TJul was 4.0 1C around 10.2 ka BP, and then rose by approximately 2 1C within a few hundred years (Fig. 7). It was highest between 8.7 and 9.7 ka BP (6.0 1C) and then gradually decreased, possibly reaching 4.5 1C during the Little Ice Age. A warming of as much as 1.0 1C occurred during the last 100 years. For both variables, the three methods give comparable results, except for the late Holocene, where the MAT results show more variability. When viewed in light of the calibration results, however, the TJul reconstructions may be underestimated, since the predicted values of the fossil samples generally fall within the high-end of the
ARTICLE IN PRESS M.C. Peros, K. Gajewski / Quaternary Science Reviews 27 (2008) 235–249 Table 4 Performance statistics of the modern training sets as determined by PLS and WAPLS transfer functions and the MAT for the variables TJul and Pann r2(boot)
Mean bias(boot)
PLS-Tjul 1* 2 3
0.353 0.372 0.400
0.006 0.006 0.008
PLS-PAnn 1 2* 3
0.101 0.159 0.154
0.029 0.213 0.342
52.361 46.543 46.334
22.608 22.105 23.169
WAPLS-Tjul 1* 2 3
0.390 0.413 0.421
0.015 0.003 0.002
1.303 1.094 1.047
0.687 0.705 0.712
WAPLS-PAnn 1* 2 3
0.191 0.176 0.176
0.520 0.761 0.933
46.415 43.519 45.537
21.563 23.069 24.679
MAT-TJul
0.571
0.067
0.863
0.642
MAT-PAnn
0.509
2.033
36.686
18.683
Model and component
Maximum bias(boot)
1.1334 1.161 1.151
RMSEP
0.702 0.712 0.696
Mean bias(boot), maximum bias(boot), and RMSEP values for TJul and Pann are in 1C and mm, respectively. The asterisks (*) indicate which transfer function components are plotted in Figs. 6 and 7, based on the selection criteria discussed in Section 3. The mean bias(boot) is the average of the residuals across the bootstrap predicted–observed gradient. The maximum bias(boot) is calculated by dividing this same gradient into ten equal intervals, determining the mean of the residuals within each interval, and then reporting the maximum value.
modern sample gradient. This underestimation for TJul would be greatest during the early Holocene, and possibly on the order of 0.5 1C. In the case of PAnn, most of the reconstructed values fall within the range of 140–160 mm— values where the predicted and observed modern results are in good agreement. The dissimilarity values of the top five closest analogues are also shown in Fig. 7; these values are generally around 0.1, indicating that most of the fossil assemblages have analogues in the modern landscape (Jackson and Williams, 2004). The five closest analogues for the bottommost sample, however, all have dissimilarity values 40.4, suggesting that the Artemisia-Poaceae-Salix tundra inferred for this level is not present in the western and central Canadian Arctic today. This non-analogue situation also means that the inferred temperature increase of 2 1C for this time may be unreliable. In addition, it is also possible that the change from the Artemisia-Poaceae-Salix to Cyperaceae-dominated tundra may reflect more of a successional sequence rather than a shift in climate. Sample-specific standard errors for each reconstruction are shown in Fig. 8. These error values, calculated using the bootstrap procedure, consist of the sum of: (1) the standard
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deviation of all inferred TJul and PAnn values of all bootstrap cycles; and (2), a constant value based on the RMSEP of the training set (Birks et al., 1990). The magnitudes of errors for the KR02 data are proportional to the RMSEP of the training set and, in the case of the PAnn reconstructions, are comparable to the overall variability of the reconstructed values. In spite of this, however, we argue that the reconstructed long-term cooling trend is reasonable since: (1) the pollen percentages show a clear trend through the Holocene of increasing values of taxa typical of the High Arctic at the expense of taxa more abundant in the Middle Arctic (Gajewski, 2002); (2) the pollen influx data also show a long-term decline, similar to the pollen concentration values of modern samples across the High Arctic to Middle Arctic transition (Gajewski, 1995); and (3), the many fossil sample levels, whose reconstructed values are similar, give confidence in the trend. 5. Discussion 5.1. Chronology Despite the problems associated with bulk sediment dates (MacDonald et al., 1991), a number of independent lines of evidence, when considered together, attest to the reliability of the KR02 chronology: (1) there are no 14C inversions; (2) the oldest dates (with the exception of one measuring 18,9507170 14C yr BP) are not older than 12 ka BP, the age of deglaciation of the area (Dyke, 2004); (3) the d13C values of all samples are consistent with those of many terrestrial organic materials, although we acknowledge that d13C values between 30% and 25% could also result from a combination of materials with very enriched and depleted d13C values (Aravena et al., 1992); and (4), the timing of major stratigraphic changes in the pollen stratigraphy of the KR02 record closely match those of other regional proxy records. Regarding this latter point, the timing of major changes in the pollen profiles of Alnus, Picea, and Pinus at Lake KR02 are roughly concurrent with the same transitions at other sites in the Mackenzie Delta region (Ritchie, 1984). The most obvious marker is the Alnus rise—generally recorded as occurring from 6.0 to 7.0 14C ka BP (between 7.2 and 8.0 ka BP), with some variability around this period of time (Ritchie, 1984)—which coincides closely with the timing of the Alnus rise in lake KR02, at 7.8 ka BP. Evidence also comes from a correlation between the KR02 pollen record and changes in the GISP2 ice core record (Alley, 2004), as well as a well-dated lake sediment sequence from Arolik Lake, Alaska (Hu et al., 2003). This relationship is particularly clear during the early Holocene, where periods of elevated pollen production coincide with increases in temperature interpreted from the GISP2 record and enhanced diatom production at Arolik Lake (Fig. 7). It is unlikely that such a relationship, occurring at three
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Fig. 6. Scatter plots showing reconstructions of the modern training set versus observed values for TJul and PAnn, as well as residual (predicted–observed) values, as determined by bootstrap cross-validation. Inverted green triangles, blue circles, and red crosses represent values reconstructed by the MAT, WAPLS, and PLS techniques, respectively. Light gray lines show where ‘ideal’ values should lie. A LOWESS smoother was applied to the datasets in each plot (span ¼ 0.45) according to the color scheme of the respective data points (Juggins, 2003).
different sites across the western Arctic and based on three different proxy indicators, would exist in the face of significant dating uncertainties. Regarding the date of 18,9507170 14C yr BP, we suspect that its old age is due to reworked organic material and/or possibly a hard-water effect. Regional syntheses of paleoenvironmental data (Dyke, 2004), as well as computer model predictions (Peltier, 1994), suggest that northwest Victoria Island was covered by the Innutian Ice Sheet until 12 ka BP. Based on the presence of biologically produc-
tive sediments underlying marine sand, however, Wolfe and King (1999) argue for discontinuous ice cover during mid- to late-glacial times in portions of the eastern Canadian Arctic. In core KR02, the date of 18,9507 170 14C yr BP was made on material from a sandy unit that contained very few diatoms (Podritske, 2006) and virtually no pollen, suggesting a biologically sterile system. Indeed, pollen and diatoms only become abundant at 388 and 376 cm, respectively, consistent with our claim of continuous ice cover until 12.0 ka BP.
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Fig. 7. Summary diagram of pollen data from core KR02, alongside central Greenland (GISP2) mean annual temperature reconstruction (Alley, 2004) and biogenic silica data from Arolik Lake, Alaska (Hu et al., 2003). The Arolik data was smoothed using a three-point running mean. Gray bars highlight key periods.
5.2. Arctic ecosystem productivity Variations in local and regional pollen influx may have been controlled by regional climate changes. In instances where pollen percentages remain relatively stable, such as at Lake KR02, fluctuations in pollen influx are likely caused by changes in: (1) plant density; (2) above-ground biomass; and (3), the quantity of pollen produced per plant, along with flower size and number. These physiological and reproductive adaptations are in turn controlled by environmental stresses, such as climate change and herbivory, the effects of which usually vary by species (Chapin and Shaver, 1985; Delph et al., 1997). For example, under higher temperatures, Dryas octopetala generates taller and larger flowers (Welker et al., 1997), whereas Papaver radicatum increases in above-ground biomass and flower intensity (Mølgaard and Christensen, 1997). Fluctuations in local and regional influx rates in the KR02 record therefore appear to be a response to changing environmental conditions, probably due to both changes in individual plant structure as well as changes in plant density and productivity at a landscape scale. The pollen percentages show more gradual changes as a result of long-
term Holocene cooling, illustrated by increases of taxa whose pollen is more abundant in the High-Arctic (e.g., Oxyria, Poaceae) at the expense of those which are more abundant in the Middle-Arctic (Cyperaceae) (Gajewski, 2002). The productivity of various species underwent large fluctuations in response to centennial- to millennial-scale climatic variability, and this is more easily seen in the pollen influx. The relationship between climate and productivity is furthermore supported by possible correlations among the KR02 pollen influx, reconstructed temperature from the GISP2 ice-core (Alley, 2004), and biogenic silica values from Arolik Lake (Hu et al., 2003). The pollen influx values prior to 9.7 ka BP may be partly a product of an artificially high sediment accumulation rate (which at this depth was determined by an extrapolated age-depth value), although high pollen concentrations at this time (Fig. 4) also attest to the productivity of the early Holocene flora. While the relationship between lake KR02 and Arolik Lake appears to be clearest during the early Holocene (as noted above), there may be similar patters after 7.0 ka BP, with the exception of the period around 5 ka BP (Fig. 9). Hu et al. (2003) report that the BSi record from Arolik Lake and
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Fig. 8. Reconstructions showing sample-specific standard errors determined by bootstrap cross-validation.
Fig. 9. Detail of the local and regional pollen influx record from Lake KR02 (red line) and the BSi record from Arolik Lake (blue line; Hu et al., 2003). The influx data was rescaled and detrended to highlight more subtle changes not apparent in Fig. 7.
indicators of solar output (which they claim was an important control on aquatic productivity throughout much of the Holocene) also show a poor fit from 5 to 6 ka BP, suggesting that a more complex set of factors influenced productivity at these two sites during the middle Holocene. A comparison of the TJul and PAnn reconstructions (which are based on percentage data) and the pollen influx data provides greater insight into the impact of climate variability on Arctic ecosystems. While the percentages, the reconstructions, and influx data all record a long-term cooling, they differ in variability at long-term and intermediate scales. Arctic plants tend to have broad and overlapping ranges (Porsild, 1957), so climate changes, unless they are severe or of long duration, probably do not
affect the distribution of these taxa. Our results suggest that pollen influx data may provide a different set of information that supplements the pollen percentage data. That being said, the calculation of pollen influx can be complicated, as it is sensitive to numerous factors, especially chronology. Furthermore, the relationship between pollen influx and climate is likely complex, and we are not yet able to use influx values for quantitative reconstructions, as modern calibration data are available only in percentage form. Thus, more ecological study would be needed to better interpret the fossil influx data. The evidence does suggest, however, that fossil pollen percentages from Arctic regions provide a reasonable estimate of long-term climate changes, whereas influx
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values may provide information on low magnitude, short duration climate changes that affect plant production. 5.3. Arctic environmental change The KR02 record permits us to better understand the spatial and temporal patterns of peak Holocene warmth of the western Arctic, an area with few paleoclimatic data sets. Existing paleoclimatic data indicate that temperatures were 1.670.8 1C higher-than-present during this period, with peak warmth occurring earlier in the western than in the eastern Canadian Arctic (Kaufman et al., 2004). However, neither the magnitude nor the timing of the climate variations are well constrained. The reconstructions from core KR02 indicate that maximum July temperatures occurred 8.7–9.7 ka yr BP (Fig. 7). The timing of the initiation of maximum warmth in core KR02 is consistent with other regional records, but this warm period may have terminated several thousand years earlier that it did at other sites, such as at Banks Island and Prince of Wales Island, where elevated temperatures appear to have ended 2.0 and 4.0 ka BP, respectively (Gajewski et al., 2000; Gajewski and Frappier, 2001). The magnitude of the period of maximum warmth compared to recent temperatures is comparable to the 1.670.8 1C estimate of Kaufman et al. (2004). We are also now better positioned to understand recent climate changes within a broader historical context. The TJul reconstructions (Fig. 7) and pollen influx, percentage, and organic matter data (Fig. 5) suggest that summer temperatures in northwestern Victoria Island over the last several decades were warmer than at any time during the last millennia, and that this temperature increase began sometime in the late 19th century, a finding consistent with diatom studies from lakes throughout the Arctic (Smol et al., 2005). However, recent July temperatures may be at least 0.5 1C lower than during periods in the early Holocene. These early Holocene changes occurred at a time when the ice sheet to the south of the study site was melting, and changes in atmospheric circulation, water outflow from the ice sheet, and ice conditions caused considerable climate variability in the region. The climate was warm and moist enough to cause the productivity of terrestrial Arctic ecosystems to be higher than today. 6. Conclusions In western Victoria Island, NWT, Canada, July temperatures were 4.0 1C around 10.2 ka BP, rose by approximately 2 1C within a few hundred years, were between 8.7–9.7 ka BP (6.0 1C) and then gradually decreased to 4.5 1C during the Little Ice Age, before warming almost 1.0 1C during the last 100 years. These estimates were derived from the calibration of a highresolution, well-dated pollen diagram from lake KR02. Although pollen percentages record changes in the nature of the tundra vegetation through time, changes in pollen
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concentrations and influx may also be used to provide estimates of past pollen production. It will be important for future studies to critically examine pollen influx and concentration values to determine whether general patterns exist between climate and terrestrial productivity, and to help confirm the findings of local-scale studies, such as the present investigation. A general picture of Holocene climate and vegetation change in the Arctic is finally emerging, but we still lack many spatio-temporal details. Outstanding issues include: refining our understanding of the Holocene Thermal Maximum; quantifying Arctic climate variability over multiple timescales; determining the timing, nature, and spatial extent of abrupt, short-duration climate events; and documenting the response of Arctic vegetation to such events. Temporally detailed and well-dated pollen diagrams, like the record we have provided here, provide an excellent means to enable us to fill many of these gaps. In the case of quantitative reconstructions, additional modern sites are needed, and a concerted effort must be made to generate these data. In addition, given the nature of ongoing global warming in the Arctic, high-resolution studies focused on the last several thousand years are also critical to permit an improved contextualization of recent changes in Arctic climates and vegetation communities. Our study provides crucial data with which to address many of these issues. Acknowledgments We thank B. O’Neil for pollen processing, B. Podritske for LOI and magnetic susceptibility results, P. Hamilton, G. Bouchard, and M. LeBlanc for help in the field, and F.S. Hu for providing the Arolik Lake data. We also thank contributors to the modern pollen database. The authors acknowledge financial support from the Natural Sciences and Engineering Research Council of Canada (NSERC) and the Canadian Foundation for Climate and Atmospheric Sciences (CFCAS) and logistic support from the Polar Continental Shelf Project (PCSP; PCSP Contribution no. 021-06). References Alley, R.B., 2004. GISP2 ice core temperature and accumulation data. In: IGBP PAGES/World Data Center for Paleoclimatology Data Contribution Series #2004-013. NOAA/NGDC Paleoclimatology Program, Boulder, CO, USA. Aravena, R., Warner, B.G., MacDonald, G.M., Hanf, K., 1992. Carbon isotope composition of lake sediments in relation to lake productivity and radiocarbon dating. Quaternary Research 37, 333–345. Billings, W.D., 1987. Constraints to plant growth, reproduction, and establishment in arctic environments. Arctic and Alpine Research 19, 357–365. Birks, H.J.B., 1995. Quantitative palaeoenvironmental reconstructions. In: Maddy, D., Brew, J.S. (Eds.), Statistical Modelling of Quaternary Science Data. Quaternary Research Association, Cambridge. Birks, H.J.B., 1998. Numerical tools in paleolimnology—progress, potentialities, and problems. Journal of Paleolimnology 20, 307–332.
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Holocene climate and vegetation change on Victoria Island, western Canadian Arctic Matthew C. Peros, Konrad Gajewski Laboratory for Paleoclimatology and Climatology, Department of Geography, University of Ottawa, Ottawa, ON, Canada K1N 6N5 Received 26 January 2007; received in revised form 2 August 2007; accepted 3 September 2007
Abstract A detailed pollen record from Victoria Island provides the first quantitative Holocene climate reconstruction from the western Canadian Arctic. The pollen percentage data indicate that Arctic herbs increased over the Holocene in response to long-term cooling. The influx of locally and regionally derived pollen grains varies throughout the core and tracks several major changes observed in the biogenic silica record from Arolik Lake, Alaska, and the GISP2 ice-core, suggesting that climate change closely controlled Arctic plant productivity. Using modern analogue and transfer function techniques, we generated quantitative reconstructions of mean July temperature and total annual precipitation for the past 10 000 years, to place recent climate changes within the context of Holocene climate variability. The quantitative reconstructions indicate that July temperature cooled by 1–1.5 1C during the Holocene. The pollenbased reconstructions record an increase in temperature of 0.5 1C over the last 100 years, and the pollen percentage and influx data indicate impacts of recent warming on the regional vegetation. r 2007 Elsevier Ltd. All rights reserved.
1. Introduction A range of measurements and model predictions confirm that Arctic environments are undergoing profound changes in response to global warming (Serreze et al., 2003). Both sea and land ice thickness and extent, for example, have decreased dramatically over the last few decades (Comiso, 2002), with implications for global sea level rise (Peltier, 2004), ocean circulation (Lohmann and Gerdes, 1998), Arctic animal communities (Derocher et al., 2004), regional and global economies (Kerr, 2002), and the traditional lifestyles of indigenous peoples (Tenenbaum, 2005). Aquatic algae and invertebrate communities in many Arctic lakes have also undergone significant and widespread changes over the last century (Smol et al., 2005). The effects of climate change on Arctic plant communities are less clear. The response of vegetation to global warming is expected to involve a combination of range expansion, higher productivity, and increased competition Corresponding author. Tel.: +1 613 562 5800x1734; fax: +1 613 562 5145. E-mail address: [email protected] (M.C. Peros).
0277-3791/$ - see front matter r 2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.quascirev.2007.09.002
(Callaghan and Jonasson, 1995; Cornelissen et al., 2001). However, many Arctic plants are sparsely distributed across large, often circumpolar ranges and have broad ecological tolerances, so the potential impact of climate variations is uncertain. A paleoecological perspective may provide insight into the relative importance of these processes and hence the future of terrestrial Arctic ecosystems. However, fossil pollen studies from the Canadian Arctic are rare, in part because of the low pollen productivity of many Arctic plants (Gajewski, 1995) and chronological problems with many paleolimnological records (Gajewski et al., 1995, 2000). If these problems are surmounted, as we have done here, such studies have the potential to provide information on vegetation history and climate variability that cannot be gleaned from other sources. Using pollen data derived from sediments lifted from a small lake on Victoria Island, in the Northwest Territories, Canada, we provide the first well-dated, temporally detailed record of Holocene vegetation change from the western Canadian Arctic Archipelago. Utilizing data from a new, expanded modern pollen database (Whitmore et al., 2005), we have also developed the first quantitative reconstructions of mean July temperature (TJul) and total
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annual precipitation (PAnn) of the region that enable us to place the rate and magnitude of 20th century climate variability in a long-term context. 2. Study site The lake, unofficially named KR02, is located in the Kuujjua River region of northwestern Victoria Island, Northwest Territories, Canada, at 71.341N, 113.781W, and 299 masl (Fig. 1). Lake KR02 has a surface area of 0.79 ha and a maximum depth of 6.1 m. The lake is located on the junction of the Shaler and Natkusiak Formations; the regional bedrock consists of clastic and carbonate sediments and basalts (Frisch and Trettin, 1991). Victoria Island was glaciated during the Wisconsinan; the Kuujjua River region appears to have been ice-free by 12 ka BP (Dyke, 2004). The surface geology consists of thin and discontinuous till with frequent bedrock outcrops (Fulton, 1995). The closest weather station is at the town of Ulukhaktok (Holman), 150 km from Lake KR02 on the west coast of Victoria Island, where mean January and July temperature are 28.6 and 9.2 1C, respectively, and mean annual precipitation is 162.5 mm (Meteorological Service of Canada, 2006). The vegetation is a prostrate shrub tundra (CAVM, 2003). Edlund (1983) classifies the Kuujjua River valley as Low Arctic, with uplands supporting a Middle Arctic vegetation. The vegetation cover is nearly contin-
uous in the valley, with Dryas, along with various sedges, grasses, Salix, Artemisia and several species of Fabaceae important constituents of the flora (Edlund, 1983). Large willows have been reported in the region (Edlund and Egginton, 1984) and a tree-ring series has been developed from a population of Salix alaxensis in the area of KR02 (Zalatan and Gajewski, 2006). 3. Methods 3.1. Field and laboratory To study past vegetation and climate changes in northwestern Victoria Island, a 411 cm-long sediment core was lifted from the deepest part of Lake KR02 in early summer, 2001, using a modified Livingstone piston corer. The uppermost sediments were sampled using a clear plastic tube fitted with a piston. The upper 20 cm of the core was extruded in the field to preserve the sediment–water interface. We established a chronology using both 210Pb and accelerator mass spectrometry (AMS) 14C techniques. For 210 Pb dating, continuous slices of the upper 21 cm of the core were analyzed and ages were derived by a constant rate of supply (CRS) model. For AMS dating, since no terrestrial macrofossils were identified in the core, subsamples consisted of a range of microfossils (e.g., chironomid head-capsules, moss debris) picked from the
Fig. 1. Location of Lake KR02 (71.341N, 113.78.781W, 299 masl) in the Canadian Arctic Archipelago. The back dots represent the locations of the modern pollen data used in this study (n ¼ 87). Those modern samples that appear as one of the best five analogues in the modern analogue technique (MAT) reconstruction are indicated by a white dot at their center (see Fig. 7). The locations of the GISP2 ice-core site and Arolik Lake, Alaska, discussed later in the text, are also shown.
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sediment matrix or, where these materials were insufficient in quantity, bulk sediment samples. Radiocarbon ages were calibrated using cubic spline fitting (Talma and Vogel, 1993) of the data from the INTCAL 98 data set (Stuiver et al., 1998). Ages were assigned to the core using linear interpolation between all 210Pb and (calibrated) 14C dates. The ages of the sediments deeper than the oldest reliable 14 C date were extrapolated using the oldest interpolated age-depth model value. Magnetic susceptibility was measured downcore at continuous 1 cm intervals using a Bartington MS2 meter. Organic matter and calcium carbonate content were estimated at continuous 0.5–1 cm intervals following ignition of the samples at 500 1C (for 3 h) and 950 1C (for 4 h) (Dean, 1974). Fossil pollen was examined from subsamples taken at intervals of 1–10 cm throughout the core. First, a known quantity of exotic spores was added to each subsample so pollen concentration could be estimated. Then, the fossil pollen was concentrated by treating the sediment with 10% HCl, 10% KOH, HF, and acetolysis solution (Faegri and Iversen, 1989). Most samples also underwent heavy-liquid separation using sodium polytungstate (SPT) to assist in the removal of heavy minerals (Bolch, 1997). Several samples were processed with and without the heavy liquid method and showed no statistical differences in pollen counts (Zabenskie, 2006). Pollen was identified using the Laboratory for Paleoclimatology and Climatology slide reference collection, as well as published atlases (McAndrews et al., 1973; Kapp et al., 2000). In total, 69 levels were counted, with at least 400 pollen and spores enumerated for most subsamples. Pollen influx values were estimated for each subsample by multiplying the pollen concentration by the sediment accumulation rate (SAR) as determined by linear interpolation of the 210Pb and 14C data. To test how sensitive the pollen influx values were to the SAR, we repeated this latter step using a SAR derived from a sixth-order polynomial, which produced similar results. Because the fossil pollen record from Lake KR02 contains high quantities of boreal taxa transported from far to the south, the pollen percentage diagram was constructed using three sums: (1) only local and regional taxa (excluding spores); (2) all long-distance taxa (e.g., Pinus, Picea) as well as those within group (1); (3) the entire assemblage (including unidentifiable/unknown grains).
important for constraining high-latitude plant growth (Billings, 1987). In order to focus on the climate history of northwestern Victoria Island, all long-distance taxa and local spores were removed from the modern and fossil data sets before percentages were calculated. ‘Rare’ pollen taxa were not omitted so we could maintain as high a pollen sum as possible. We undertook reconstructions of both variables using modern analogue (MAT) and transfer-function techniques (Overpeck et al., 1985; Birks, 1995); multiple methods were chosen to determine how reproducible the reconstruction methods are for our data set. Prior to the calculation of the transfer functions, two detrended canonical correspondence analyses (DCCA) were performed on the modern samples to estimate the lengths of the TJul and PAnn gradients. The DCCA analyses generated gradients of 1.016 and 0.712 SD units for TJul and PAnn, respectively, indicating that linear transfer-function techniques would be most appropriate (Birks, 1995). We selected Partial Least Squares (PLS) regression as the linear method, although we also undertook the same procedure using Weighted Averaging Partial Least Squares (WAPLS), a commonly used unimodal-based method (Birks, 1995). For the MAT, we selected the square-chord distance dissimilarity coefficient, a robust ‘signal-to-noise’ metric (Overpeck et al., 1985; Jackson and Williams, 2004). Next, we performed a bootstrap cross-validation using each of the MAT and transfer-function models to identify outliers among the modern samples. On the basis of the cross validation results, one outlier was removed (ID2 4371 from Whitmore et al., 2005). The models were then re-run, again using bootstrap cross-validation to generate samplespecific standard errors and assess model performance, and reconstructions were generated. For the MAT, the unweighted mean of the nearest five best analogues was calculated for each fossil sample. For the transfer functions, 1-, 2-, and 3-component models were generated; we identified the most robust model as having the fewest components, highest bootstrap coefficient of determination (r2(boot)), lowest root mean square error of prediction (RMSEP), and lowest bootstrap mean and maximum biases (Birks, 1998). The DCCAs were performed using CANOCO v4.5 (ter Braak and Sˇmilauer, 2002). The MAT and transfer functions were implemented using C2 v1.4.3 (Juggins, 2003).
3.2. Climate reconstruction
4. Results
Pollen percentage and climate data were extracted from the North American Modern Pollen Database (Whitmore et al., 2005). Our modern samples include all lacustrine sites within the western and central ‘Arctic’ biome (4831W), as well as the pollen assemblage from the upper 1 cm of sediment from core KR02 (n ¼ 87) (Fig. 1). We reconstructed mean July temperature (TJul) and total annual precipitation (Pann) because these variables are
4.1. Stratigraphy and chronology Organic matter averages 20% of the dry weight of the core from the interval represented by 5.0–10.5 ka BP, and then steadily increases to 40% by 2.3 ka BP (Fig. 2). The highest values (58%) occur in the most recent sediments in the core. Magnetic susceptibility is low throughout most of the core, although it increases substantially in the
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Fig. 2. Sedimentary characteristics and age-depth model for core KR02. The age-depth model is based on a linear-interpolation between the median values of the 2s error ranges of the AMS dates. The earliest 14C date is at 800 yr BP. The chronology above this level was based on 210Pb dating. The sedimentation rate as determined by a sixth-order polynomial is plotted against the sedimentation rate generated by linear interpolation (see text).
deepest sediments, concurrent with the presence of a sandy unit. With the exception of this basal sand, the core has a uniform color and texture (Podritske, 2006). The 210Pb and 14C results are listed in Tables 1 and 2, respectively. The age-depth model, based on a linear interpolation of these results, shows a fairly linear sediment accumulation rate of 0.037 cm yr1 (Fig. 2). This rate is faster in the upper 20 cm of the core, likely due to limited autocompaction. The ages of pollen samples below the oldest date were estimated by linear extrapolation of the curve. We have rejected a date of 18,9507170 14C yr BP, from 406 to 407 cm (Table 1), as being too old; otherwise we argue that the remainder of the chronology is sound, and in the discussion provide several lines of evidence to support this claim. 4.2. Vegetation history The bottommost pollen assemblage, dated at 10.2 ka BP, contains high quantities of Artemisia, Poaceae and Salix pollen (Fig. 3), indicative of a polar desert (Gajewski, 2002). Both Poaceae and Salix percentages are relatively high until 9.8 ka BP, after which time they are replaced by Cyperaceae, whose values rapidly exceed 90% of the local and regional pollen sum. These percentages
then begin to decrease, slowly at first, and then more rapidly after 5.5 ka BP, although Cyperaceae still remains the dominant pollen type throughout the remainder of the core. Concurrent with this decline in Cyperaceae are increases in Poaceae and several Arctic herbs. Dryas and Saxifraga oppositifolia increase gradually, whereas increases in Artemisia, Oxyria, Poaceae and Papaver are more abrupt, beginning 6.5, 5.2, 2.8, and 1.2 ka BP, respectively. Polypodium and Sphagnum spores, which may have a local origin but were removed from the local and regional pollen sum, show relatively stable percentages throughout the early and middle Holocene, and increase slightly in the late Holocene. The long distance pollen percentages reflect the transport of pollen from regions to the south of Lake KR02. Betula was abundant immediately following deglaciation, and then decreased by 9.5 ka BP. Its percentages continued to slowly decline until 2.2 ka BP, after which time they deceased further, averaging around 20%, until around 100 years ago. Today, shrub birch grows on western Victoria Island, where it is not abundant, and the adjacent mainland (Porsild, 1957), and it seems likely that much of the fossil Betula originated from the shrubs B. glandulosa and B. nana subsp. exilis, which are common in low Arctic tundra. The Alnus profile, consisting largely of pollen from
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Table 1 Radiocarbon dates and calibrated ages (cal yr BP) from the KR02 sediment core Lab code
Depth (cm)
Conventional age (yr BP)
Beta-199874 Beta-199875 Beta-199877 Beta-206009 Beta-199878 Beta-206010 Beta-206011 Beta-213872 Beta-199879 Beta-206012
37.5–39.5 70–73 208–209 241–243 291–293 314–317 333–335 349–351 362–364 404–407
890740 1680750 3500740 4270740 5760750 6150750 7050750 8590740 8730760 189507170
14
C
2-F calibrated age range (cal yr BP)
Median calibrated age (cal yr BP)
d13C
Material
710–920 1500–1710 3670–3870 4820–4870 6430–6670 6890–7200 7760–7960 9520–9570 9550–9920
815 1605 3770 4845 6550 7045 7860 9545 9735 Rejected
27.6 No data 25.5 29.3 30.3 28.1 28.7 29.1 27.1 24.1
Bulk sediment Macrofossils Macrofossils Bulk sediment Bulk sediment Macrofossils Macrofossils Macrofossils Macrofossils Bulk sediment
The date at 404–407 cm was not used in the chronology.
Table 2 Lead-210 dates from the KR02 sediment core Depth (cm)
Year AD at bottom of slice based on CRS model estimate
2.0–3.0 3.0–4.0 4.0–5.0 5.0–6.0 6.0–7.0 7.0–8.0 8.0–9.0 9.0–10.0 12.0–13.0 14.0–15.0 16.0–17.0 18.0–19.0 20.0–21.0
1995 1993 1990 1985 1980 1976 1972 1957 1934 1920 1901 1873 1837
the forest-tundra shrub A. crispa, records values that are initially low, but then undergo a rapid and substantial increase between 8.0 and 7.6 ka BP. Following this rise, Alnus percentages are essentially constant, although decrease in the most recent sediments. Of the tree pollen, Picea grains are present by 9.5 ka BP and gradually increase until 5.0 ka BP, after which time they slowly decrease. Pinus, whose northern limit is farther south, begins to increase around 7.0 ka BP and then levels off. The pollen influx values for most local and regional taxa are high between 9.0 and 10.0 ka BP (Fig. 4). After 8.0 ka BP, the influx of Poaceae, Cyperaceae, and Salix pollen increases in two pulses, each lasting 800 years. Local and regional influx values then remain low, but do vary following these events. While the overall influx patterns are similar between the local and regional and long distance curves, the individual long distance taxa themselves differ. The Betula curve, for example, more closely resembles the local and regional influx data than the curve of Pinus. In large part, these differences likely reflect
the migration history of each plant. However, they may also be due to the proximity of the pollen source to Lake KR02. Much of the Betula pollen likely comes from a closer source area than the Pinus pollen, suggesting that the birch plants from where the Betula pollen are derived responded to the same environmental factors as the local and regional taxa. 4.3. Environmental change over the last 1000 years A closer examination of several of the aforementioned records provides insights into the nature of 19th and 20th century environmental changes (Fig. 5). Organic matter remained relatively constant, at 36% of the dry weight of the core, throughout much of the last millennium, but began a steady increase 130 years ago. Local and regional pollen influx shows a similar pattern, although the timing of the initiation of this increase is difficult to pinpoint given the pollen sample density in this portion of the core. Likewise, percentages of Cyperaceae (typically indicative of Middle Arctic environments; Gajewski, 2002) increase over the last 100 years, concurrent with decreases in Artemisia, Oxyria, and Papaver. All these lines of evidence suggest the onset of warmer conditions beginning around AD 1870. While the resolution of the pollen data is low for this portion of the KR02 record, the temporally detailed organic matter results suggest that the rate and magnitude of this warming is unprecedented over the last 1000 years. 4.4. Climate reconstructions 4.4.1. Model performance Performance statistics of our modern training set are summarized in Table 4. On the basis of the root mean square error of prediction (RMSEP), bootstrap coefficient of determination (r2boot), and maximum bias values, the modern analogue technique (MAT) outperforms both Partial Least Squares (PLS) and Weighted Averaging
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M.C. Peros, K. Gajewski / Quaternary Science Reviews 27 (2008) 235–249 Fig. 3. Pollen percentage values for core KR02. Note that the pollen percentage diagram was constructed using three sums: (1) only local and regional taxa (excluding spores); (2) all long-distance taxa (e.g., Pinus, Picea) as well as those within group (1); (3) the entire assemblage (including unidentifiable/unknown grains). A complete taxon list, along with the sum each species is classified within, is provided in Table 3.
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M.C. Peros, K. Gajewski / Quaternary Science Reviews 27 (2008) 235–249 Fig. 4. Pollen influx values for core KR02 in grains cm2 year1 (bottom axis). Note that the x-axis scale differs for certain graphs. The ‘local and regional’ and ‘long distance’ influx curves are based on the sums of the influx values of the individual taxa within those groups. Curves of the local and regional and long distance pollen concentrations are also plotted and show a similar overall pattern as pollen influx, consistent with the fairly linear sediment accumulation rate.
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M.C. Peros, K. Gajewski / Quaternary Science Reviews 27 (2008) 235–249 Table 3 Classification by source area of all pollen taxa identified in core KR02
Fig. 5. Summary diagram highlighting changes over the last 1000 years. Note that organic matter values are percentages; pollen influx is in grains cm2 year1; and the Artemisia, Cyperaceae, Oxyria, and Papaver graphs are percentages based on the local and regional pollen sum. The ages for the last 150 years in this diagram were determined by 210Pb dates, thus year ‘‘0’’ is AD 2001, the year core KR02 was sampled.
Partial Least Squares (WAPLS) transfer functions for both TJul and PAnn. This is not the case for mean bias, however, where PLS seems to produce the best results, with the MAT significantly underperforming for PAnn. Birks (1998) argues that the r2 value is indicative of the strength of the relationship between observed and predicted values and is thus useful when comparing the predictive ability of inference models for different environmental variables. In our case, the r2(boot) values of the transfer functions and MAT are higher for TJul than for PAnn, indicating a greater degree of confidence with the TJul reconstructions. The predictive power of our training set can also be assessed by examining scatter-plots of reconstructed versus observed values (Fig. 6). Ideally, the data points in the two left-hand frames should lie on the diagonal lines, indicating a 1:1 correspondence between predicted and observed values. On the right-hand side, the residuals should show no pattern and lie along the horizontal line. A consistent trend among all reconstructions is the overestimation of low values and underestimation of high values at the ends of the sample gradient. This phenomenon is especially clear when examining the residual plots, and has been observed in numerous other training set reconstructions, using a range of indicators (e.g., Lotter et al., 1997). This ‘edgeeffect’ is characteristic of WA-based transfer function methods, like WAPLS and PLS (Birks, 1998), and appears
Local and regional
Long distance
Apiaceae Artemisia Asteraceae (Liguliflorae) Asteraceae (Tubuliflorae) Brassicaceae Caryophyllaceae Cassiope Cephalanthus Chenopodiaceae Cupressaceae Cyperaceae Dryas Epilobium Ericaceae Fabaceae Oxyria/Rumex Papaver Pedicularis Plantago Poaceae Polygonaceae Polygonum viviparum Potentilla Rosaceae undifferentiated Salix Saxifraga oppositifolia Saxifragaceae other
Abies Alnus Ambrosia Betula Cornus Corylus Juglans Larix Picea Pinus Populus Potamogeton Rubus chamaemorus Shepherdia canadensis Thalictrum Ulmus Other Drypoteris Polypodium Sphagnum Trilete spore Indeterminable/unknown
to be the result of the use of inverse deshrinking regression, which tends to pull the predicted values toward the mean of the training set (ter Braak and Juggins, 1993). With the MAT, however, the ‘edge-effect’ appears to have a different cause; analogues with intermediate TJul and PAnn values appear to be contributing to the reconstructed values for samples at the ends of the gradient, likely because of the large number of samples with intermediate values that can be drawn as one of the top five best analogues. Overall, the plots in Fig. 6 indicate that the MAT, as implemented in this paper, outperforms both transfer functions when reconstructing high and low values, whereas the transfer functions do slightly better for mid-gradient predictions. 4.4.2. Climate reconstruction Our reconstructions show that TJul was 4.0 1C around 10.2 ka BP, and then rose by approximately 2 1C within a few hundred years (Fig. 7). It was highest between 8.7 and 9.7 ka BP (6.0 1C) and then gradually decreased, possibly reaching 4.5 1C during the Little Ice Age. A warming of as much as 1.0 1C occurred during the last 100 years. For both variables, the three methods give comparable results, except for the late Holocene, where the MAT results show more variability. When viewed in light of the calibration results, however, the TJul reconstructions may be underestimated, since the predicted values of the fossil samples generally fall within the high-end of the
ARTICLE IN PRESS M.C. Peros, K. Gajewski / Quaternary Science Reviews 27 (2008) 235–249 Table 4 Performance statistics of the modern training sets as determined by PLS and WAPLS transfer functions and the MAT for the variables TJul and Pann r2(boot)
Mean bias(boot)
PLS-Tjul 1* 2 3
0.353 0.372 0.400
0.006 0.006 0.008
PLS-PAnn 1 2* 3
0.101 0.159 0.154
0.029 0.213 0.342
52.361 46.543 46.334
22.608 22.105 23.169
WAPLS-Tjul 1* 2 3
0.390 0.413 0.421
0.015 0.003 0.002
1.303 1.094 1.047
0.687 0.705 0.712
WAPLS-PAnn 1* 2 3
0.191 0.176 0.176
0.520 0.761 0.933
46.415 43.519 45.537
21.563 23.069 24.679
MAT-TJul
0.571
0.067
0.863
0.642
MAT-PAnn
0.509
2.033
36.686
18.683
Model and component
Maximum bias(boot)
1.1334 1.161 1.151
RMSEP
0.702 0.712 0.696
Mean bias(boot), maximum bias(boot), and RMSEP values for TJul and Pann are in 1C and mm, respectively. The asterisks (*) indicate which transfer function components are plotted in Figs. 6 and 7, based on the selection criteria discussed in Section 3. The mean bias(boot) is the average of the residuals across the bootstrap predicted–observed gradient. The maximum bias(boot) is calculated by dividing this same gradient into ten equal intervals, determining the mean of the residuals within each interval, and then reporting the maximum value.
modern sample gradient. This underestimation for TJul would be greatest during the early Holocene, and possibly on the order of 0.5 1C. In the case of PAnn, most of the reconstructed values fall within the range of 140–160 mm— values where the predicted and observed modern results are in good agreement. The dissimilarity values of the top five closest analogues are also shown in Fig. 7; these values are generally around 0.1, indicating that most of the fossil assemblages have analogues in the modern landscape (Jackson and Williams, 2004). The five closest analogues for the bottommost sample, however, all have dissimilarity values 40.4, suggesting that the Artemisia-Poaceae-Salix tundra inferred for this level is not present in the western and central Canadian Arctic today. This non-analogue situation also means that the inferred temperature increase of 2 1C for this time may be unreliable. In addition, it is also possible that the change from the Artemisia-Poaceae-Salix to Cyperaceae-dominated tundra may reflect more of a successional sequence rather than a shift in climate. Sample-specific standard errors for each reconstruction are shown in Fig. 8. These error values, calculated using the bootstrap procedure, consist of the sum of: (1) the standard
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deviation of all inferred TJul and PAnn values of all bootstrap cycles; and (2), a constant value based on the RMSEP of the training set (Birks et al., 1990). The magnitudes of errors for the KR02 data are proportional to the RMSEP of the training set and, in the case of the PAnn reconstructions, are comparable to the overall variability of the reconstructed values. In spite of this, however, we argue that the reconstructed long-term cooling trend is reasonable since: (1) the pollen percentages show a clear trend through the Holocene of increasing values of taxa typical of the High Arctic at the expense of taxa more abundant in the Middle Arctic (Gajewski, 2002); (2) the pollen influx data also show a long-term decline, similar to the pollen concentration values of modern samples across the High Arctic to Middle Arctic transition (Gajewski, 1995); and (3), the many fossil sample levels, whose reconstructed values are similar, give confidence in the trend. 5. Discussion 5.1. Chronology Despite the problems associated with bulk sediment dates (MacDonald et al., 1991), a number of independent lines of evidence, when considered together, attest to the reliability of the KR02 chronology: (1) there are no 14C inversions; (2) the oldest dates (with the exception of one measuring 18,9507170 14C yr BP) are not older than 12 ka BP, the age of deglaciation of the area (Dyke, 2004); (3) the d13C values of all samples are consistent with those of many terrestrial organic materials, although we acknowledge that d13C values between 30% and 25% could also result from a combination of materials with very enriched and depleted d13C values (Aravena et al., 1992); and (4), the timing of major stratigraphic changes in the pollen stratigraphy of the KR02 record closely match those of other regional proxy records. Regarding this latter point, the timing of major changes in the pollen profiles of Alnus, Picea, and Pinus at Lake KR02 are roughly concurrent with the same transitions at other sites in the Mackenzie Delta region (Ritchie, 1984). The most obvious marker is the Alnus rise—generally recorded as occurring from 6.0 to 7.0 14C ka BP (between 7.2 and 8.0 ka BP), with some variability around this period of time (Ritchie, 1984)—which coincides closely with the timing of the Alnus rise in lake KR02, at 7.8 ka BP. Evidence also comes from a correlation between the KR02 pollen record and changes in the GISP2 ice core record (Alley, 2004), as well as a well-dated lake sediment sequence from Arolik Lake, Alaska (Hu et al., 2003). This relationship is particularly clear during the early Holocene, where periods of elevated pollen production coincide with increases in temperature interpreted from the GISP2 record and enhanced diatom production at Arolik Lake (Fig. 7). It is unlikely that such a relationship, occurring at three
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Fig. 6. Scatter plots showing reconstructions of the modern training set versus observed values for TJul and PAnn, as well as residual (predicted–observed) values, as determined by bootstrap cross-validation. Inverted green triangles, blue circles, and red crosses represent values reconstructed by the MAT, WAPLS, and PLS techniques, respectively. Light gray lines show where ‘ideal’ values should lie. A LOWESS smoother was applied to the datasets in each plot (span ¼ 0.45) according to the color scheme of the respective data points (Juggins, 2003).
different sites across the western Arctic and based on three different proxy indicators, would exist in the face of significant dating uncertainties. Regarding the date of 18,9507170 14C yr BP, we suspect that its old age is due to reworked organic material and/or possibly a hard-water effect. Regional syntheses of paleoenvironmental data (Dyke, 2004), as well as computer model predictions (Peltier, 1994), suggest that northwest Victoria Island was covered by the Innutian Ice Sheet until 12 ka BP. Based on the presence of biologically produc-
tive sediments underlying marine sand, however, Wolfe and King (1999) argue for discontinuous ice cover during mid- to late-glacial times in portions of the eastern Canadian Arctic. In core KR02, the date of 18,9507 170 14C yr BP was made on material from a sandy unit that contained very few diatoms (Podritske, 2006) and virtually no pollen, suggesting a biologically sterile system. Indeed, pollen and diatoms only become abundant at 388 and 376 cm, respectively, consistent with our claim of continuous ice cover until 12.0 ka BP.
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Fig. 7. Summary diagram of pollen data from core KR02, alongside central Greenland (GISP2) mean annual temperature reconstruction (Alley, 2004) and biogenic silica data from Arolik Lake, Alaska (Hu et al., 2003). The Arolik data was smoothed using a three-point running mean. Gray bars highlight key periods.
5.2. Arctic ecosystem productivity Variations in local and regional pollen influx may have been controlled by regional climate changes. In instances where pollen percentages remain relatively stable, such as at Lake KR02, fluctuations in pollen influx are likely caused by changes in: (1) plant density; (2) above-ground biomass; and (3), the quantity of pollen produced per plant, along with flower size and number. These physiological and reproductive adaptations are in turn controlled by environmental stresses, such as climate change and herbivory, the effects of which usually vary by species (Chapin and Shaver, 1985; Delph et al., 1997). For example, under higher temperatures, Dryas octopetala generates taller and larger flowers (Welker et al., 1997), whereas Papaver radicatum increases in above-ground biomass and flower intensity (Mølgaard and Christensen, 1997). Fluctuations in local and regional influx rates in the KR02 record therefore appear to be a response to changing environmental conditions, probably due to both changes in individual plant structure as well as changes in plant density and productivity at a landscape scale. The pollen percentages show more gradual changes as a result of long-
term Holocene cooling, illustrated by increases of taxa whose pollen is more abundant in the High-Arctic (e.g., Oxyria, Poaceae) at the expense of those which are more abundant in the Middle-Arctic (Cyperaceae) (Gajewski, 2002). The productivity of various species underwent large fluctuations in response to centennial- to millennial-scale climatic variability, and this is more easily seen in the pollen influx. The relationship between climate and productivity is furthermore supported by possible correlations among the KR02 pollen influx, reconstructed temperature from the GISP2 ice-core (Alley, 2004), and biogenic silica values from Arolik Lake (Hu et al., 2003). The pollen influx values prior to 9.7 ka BP may be partly a product of an artificially high sediment accumulation rate (which at this depth was determined by an extrapolated age-depth value), although high pollen concentrations at this time (Fig. 4) also attest to the productivity of the early Holocene flora. While the relationship between lake KR02 and Arolik Lake appears to be clearest during the early Holocene (as noted above), there may be similar patters after 7.0 ka BP, with the exception of the period around 5 ka BP (Fig. 9). Hu et al. (2003) report that the BSi record from Arolik Lake and
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Fig. 8. Reconstructions showing sample-specific standard errors determined by bootstrap cross-validation.
Fig. 9. Detail of the local and regional pollen influx record from Lake KR02 (red line) and the BSi record from Arolik Lake (blue line; Hu et al., 2003). The influx data was rescaled and detrended to highlight more subtle changes not apparent in Fig. 7.
indicators of solar output (which they claim was an important control on aquatic productivity throughout much of the Holocene) also show a poor fit from 5 to 6 ka BP, suggesting that a more complex set of factors influenced productivity at these two sites during the middle Holocene. A comparison of the TJul and PAnn reconstructions (which are based on percentage data) and the pollen influx data provides greater insight into the impact of climate variability on Arctic ecosystems. While the percentages, the reconstructions, and influx data all record a long-term cooling, they differ in variability at long-term and intermediate scales. Arctic plants tend to have broad and overlapping ranges (Porsild, 1957), so climate changes, unless they are severe or of long duration, probably do not
affect the distribution of these taxa. Our results suggest that pollen influx data may provide a different set of information that supplements the pollen percentage data. That being said, the calculation of pollen influx can be complicated, as it is sensitive to numerous factors, especially chronology. Furthermore, the relationship between pollen influx and climate is likely complex, and we are not yet able to use influx values for quantitative reconstructions, as modern calibration data are available only in percentage form. Thus, more ecological study would be needed to better interpret the fossil influx data. The evidence does suggest, however, that fossil pollen percentages from Arctic regions provide a reasonable estimate of long-term climate changes, whereas influx
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values may provide information on low magnitude, short duration climate changes that affect plant production. 5.3. Arctic environmental change The KR02 record permits us to better understand the spatial and temporal patterns of peak Holocene warmth of the western Arctic, an area with few paleoclimatic data sets. Existing paleoclimatic data indicate that temperatures were 1.670.8 1C higher-than-present during this period, with peak warmth occurring earlier in the western than in the eastern Canadian Arctic (Kaufman et al., 2004). However, neither the magnitude nor the timing of the climate variations are well constrained. The reconstructions from core KR02 indicate that maximum July temperatures occurred 8.7–9.7 ka yr BP (Fig. 7). The timing of the initiation of maximum warmth in core KR02 is consistent with other regional records, but this warm period may have terminated several thousand years earlier that it did at other sites, such as at Banks Island and Prince of Wales Island, where elevated temperatures appear to have ended 2.0 and 4.0 ka BP, respectively (Gajewski et al., 2000; Gajewski and Frappier, 2001). The magnitude of the period of maximum warmth compared to recent temperatures is comparable to the 1.670.8 1C estimate of Kaufman et al. (2004). We are also now better positioned to understand recent climate changes within a broader historical context. The TJul reconstructions (Fig. 7) and pollen influx, percentage, and organic matter data (Fig. 5) suggest that summer temperatures in northwestern Victoria Island over the last several decades were warmer than at any time during the last millennia, and that this temperature increase began sometime in the late 19th century, a finding consistent with diatom studies from lakes throughout the Arctic (Smol et al., 2005). However, recent July temperatures may be at least 0.5 1C lower than during periods in the early Holocene. These early Holocene changes occurred at a time when the ice sheet to the south of the study site was melting, and changes in atmospheric circulation, water outflow from the ice sheet, and ice conditions caused considerable climate variability in the region. The climate was warm and moist enough to cause the productivity of terrestrial Arctic ecosystems to be higher than today. 6. Conclusions In western Victoria Island, NWT, Canada, July temperatures were 4.0 1C around 10.2 ka BP, rose by approximately 2 1C within a few hundred years, were between 8.7–9.7 ka BP (6.0 1C) and then gradually decreased to 4.5 1C during the Little Ice Age, before warming almost 1.0 1C during the last 100 years. These estimates were derived from the calibration of a highresolution, well-dated pollen diagram from lake KR02. Although pollen percentages record changes in the nature of the tundra vegetation through time, changes in pollen
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concentrations and influx may also be used to provide estimates of past pollen production. It will be important for future studies to critically examine pollen influx and concentration values to determine whether general patterns exist between climate and terrestrial productivity, and to help confirm the findings of local-scale studies, such as the present investigation. A general picture of Holocene climate and vegetation change in the Arctic is finally emerging, but we still lack many spatio-temporal details. Outstanding issues include: refining our understanding of the Holocene Thermal Maximum; quantifying Arctic climate variability over multiple timescales; determining the timing, nature, and spatial extent of abrupt, short-duration climate events; and documenting the response of Arctic vegetation to such events. Temporally detailed and well-dated pollen diagrams, like the record we have provided here, provide an excellent means to enable us to fill many of these gaps. In the case of quantitative reconstructions, additional modern sites are needed, and a concerted effort must be made to generate these data. In addition, given the nature of ongoing global warming in the Arctic, high-resolution studies focused on the last several thousand years are also critical to permit an improved contextualization of recent changes in Arctic climates and vegetation communities. Our study provides crucial data with which to address many of these issues. Acknowledgments We thank B. O’Neil for pollen processing, B. Podritske for LOI and magnetic susceptibility results, P. Hamilton, G. Bouchard, and M. LeBlanc for help in the field, and F.S. Hu for providing the Arolik Lake data. We also thank contributors to the modern pollen database. The authors acknowledge financial support from the Natural Sciences and Engineering Research Council of Canada (NSERC) and the Canadian Foundation for Climate and Atmospheric Sciences (CFCAS) and logistic support from the Polar Continental Shelf Project (PCSP; PCSP Contribution no. 021-06). References Alley, R.B., 2004. GISP2 ice core temperature and accumulation data. In: IGBP PAGES/World Data Center for Paleoclimatology Data Contribution Series #2004-013. NOAA/NGDC Paleoclimatology Program, Boulder, CO, USA. Aravena, R., Warner, B.G., MacDonald, G.M., Hanf, K., 1992. Carbon isotope composition of lake sediments in relation to lake productivity and radiocarbon dating. Quaternary Research 37, 333–345. Billings, W.D., 1987. Constraints to plant growth, reproduction, and establishment in arctic environments. Arctic and Alpine Research 19, 357–365. Birks, H.J.B., 1995. Quantitative palaeoenvironmental reconstructions. In: Maddy, D., Brew, J.S. (Eds.), Statistical Modelling of Quaternary Science Data. Quaternary Research Association, Cambridge. Birks, H.J.B., 1998. Numerical tools in paleolimnology—progress, potentialities, and problems. Journal of Paleolimnology 20, 307–332.
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