Multi-century lake area changes in the Southern Altiplano: A tree-ring-based reconstruction

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Abstract

Size fluctuations in endorheic lakes in northwestern Argentina (NWA) and southwestern Bolivia (SWB) are very sensitive to basin hydrological balances, and consequently, very vulnerable to deleterious effects from climatic changes. The management of these water resources and their biodiversity requires a comprehensive knowledge of their natural variability over multiple timescales. In this study, we present a multi-century reconstruction of past lake-area fluctuations in NWA and SWB. The evidence used to develop and validate this reconstruction includes satellite images and a century-long tree-ring record from P. tarapacana. Inter-annual fluctuations in lake area of nine lakes were quantified based on Landsat satellite images over the period 1975 to 2009. A regional P. tarapacana tree-ring chronology, composite from two sampling sites, was used as predictors in a regression model to reconstruct the mean annual (January-December) lake area from the nine lakes. The reconstruction model captures 62 % of the total variance in lake-area fluctuations and shows adequate levels of cross-validation. This high-resolution reconstruction covers the past 601 years and characterizes the occurrence of annual to multi-decadal lake area fluctuations and its main oscillation modes of variability. Our reconstruction points out that the late 20th century decrease in lake area was exceptional over the period 1407-2007; a persistent negative trend in lake area is clear in the reconstruction and consistent with glacier retreat and other climate proxies from the Altiplano and the tropical Andes. Since the mid 1970s, the Vilama-Coruto lake system recorded an accelerated decrease in area consistent with an increasing recurrence of extremely small lake-area events. Throughout the 601 years, the reconstruction provides valuable information about spatial and temporal stabilities of the relationships between changes in lake area, ENSO, and PDO, highlighting the Pacific influence over most modes of lake area variability. Global and regional climate models for the Altiplano project a marked reduction in precipitation to the end of the 21st century, exacerbating presently dry conditions. These results provide a baseline for the historical range of variability in lake fluctuations and thus should be considered for the management of biodiversity and water resources in the Central Andes during the next decades.

Figures

  • Figure 1. Map showing the Vilama-Coruto lake system in the northwestern Argentina and southwestern Bolivia. Green stars represent the selected tree-ring chronologies used in this study.
  • Table 1. Geographical location and statistics of the Polylepis tarapacana ring width chronologies. Mean RBar and mean EPS were averaged over chronology periods including > 10 tree-ring series.
  • Figure 2. (a) Observed (green line) and tree-ring predicted (blue line) annual lake area (January–December) variations in the NWASWB. Annual lake area expressed as a Z score of the satellitederived 1975–2007 lake area mean. Calibration and verification statistics: the Pearson correlation coefficient (r) between observed and reconstructed values, the coefficient of determination adjusted for the degrees of freedom in the model (R2 adj ) over the calibration period, the F value of regression (the ratio between the explained and the unexplained variability in the model), and the reduction of error (RE). (b) The linear trend of regression residuals (slope: blue line) and the Durbin-Watson (D-W) statistics used to test for firstorder autocorrelation of the regression residuals are shown.
  • Figure 3. Annual (January–December) Vilama-Coruto lake area reconstruction for the period AD 1407–2007. Annual lake area expressed as Z score of the 1975–2007 lake area mean. The 35-year smoothing-spline curve highlights the multi-decadal variability. Significant (95 % cl) regime shifts (blue arrows) and the mean of periods (orange horizontal line) detected by the Rodionov (2004) method (window length= 25 years). Dates of the regime shifts are shown in the figure. Uncertainties of the reconstruction are shown by the light green band (±1 RMSE).
  • Table 2. Lowest and highest non-overlapping averages of the reconstructed (1407–2007) lake area fluctuations for the Vilama-Coruto lake system. Annual lake area expressed asZ score of the 1975–2007 lake area mean. Ranks 1–5 correspond to the five most extreme reconstructed lake area years or set of consecutive years. Rank 1 represents the most important minimum (maximum) lake area record.
  • Figure 4. Changing probability of extreme low values (< 20th percentile; blue line) of the Vilama-Coruto lake area reconstruction from 1407–2007. A kernel smoothing method was used with a bandwidth of 50 years. The shaded represent 95 % confidence interval based on 1000 bootstrap simulations.
  • Figure 6. Blackman-Tukey power spectra analysis of the (a) reconstructed lake area (1407–2007) and (b) the sea surface temperatures from the N3.4 Pacific sector (N3.4-SSTs; 1872-2007). (c) Coherency spectrum of N3.4-SSTs and reconstructed lake area in the Vilama-Coruto region, estimated over the common period 1872– 2007. Short dashed and dotted lines represent the 0.05 probability levels and the red noise band, respectively. Dominant periodicities are indicated in each panels.
  • Figure 5. Spatial correlation patterns over the period 1948– 2006 between the 2.5× 2.5 gridded monthly averaged January– December sea surface temperatures (SSTs) and the reconstructed January–December lake area for the Vilama-Coruto region. Spatial correlations were obtained from the National Oceanic and Atmopheric Administration website (http://www.esrl.noaa.gov/psd/data/ correlation/). The reconstructed lake area region is indicated by the red square.

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CITATION STYLE

APA

Morales, M. S., Carilla, J., Grau, H. R., & Villalba, R. (2015). Multi-century lake area changes in the Southern Altiplano: A tree-ring-based reconstruction. Climate of the Past, 11(9), 1139–1152. https://doi.org/10.5194/cp-11-1139-2015

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