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Spatial Patterns of Climate and Tree Growth Variations in Subtropical Northwestern Argentina

R. Villalba, R. L. Holmes and Jose A. Boninsegna
Journal of Biogeography
Vol. 19, No. 6 (Nov., 1992), pp. 631-649
Published by: Wiley
DOI: 10.2307/2845706
Stable URL: http://www.jstor.org/stable/2845706
Page Count: 19
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Spatial Patterns of Climate and Tree Growth Variations in Subtropical Northwestern Argentina
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Abstract

In order to gain an understanding of the spatial connections between instrumental and proxy climatic data in subtropical regions, we investigated the spatial patterns of climate and tree-growth anomalies in the montane forests of northwestern Argentina. Principal components technique was used to identify the dominant spatial patterns of climate and tree growth anomalies. a 43-year data set of monthly total precipitation at a selected network of thirty-one stations in northwestern Argentina was analysed on annual and seasonal basis. The most dominant annual pattern shows precipitation anomalies of the same sign over practically the whole area. The second and third patterns reflect altitudinal and latitudinal rainfall variations across the study area, respectively. The tree-ring data set consisted of twelve chronologies developed from Juglans australis Griseb., Cedrela angustifolia Sesse Moc., and Cedrela lilloi C.DC. The relationships between climatic conditions, site characteristics, and tree-ring growth were identified using response functions, correlation functions, and group analysis. These techniques show that the ring widths in subtropical Argentina are affected by weather conditions from late winter to early summer. Tree-ring patterns mainly reflect the direct effects of the principal types of rainfall patterns observed, the first in which rainfall conditions are uniform across the study area, and the third in which precipitation anomalies are concentrated in the northeastern part of the region. Finnally, different regression models were used to reconstruct annual and seasonal variations in precipitation. On average, 60-80% of the variance in regional precipitation is explained using the ring-width chronologies as predictive variables.

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