SPATIAL PATTERNS OF CLIMATE AND TREE GROWTH VARIATIONS IN SUBTROPICALNORTHWESTERN ARGENTINA

Citation
R. Villalba et al., SPATIAL PATTERNS OF CLIMATE AND TREE GROWTH VARIATIONS IN SUBTROPICALNORTHWESTERN ARGENTINA, Journal of biogeography, 19(6), 1992, pp. 631-649
Citations number
40
Categorie Soggetti
Ecology,Geografhy
Journal title
ISSN journal
03050270
Volume
19
Issue
6
Year of publication
1992
Pages
631 - 649
Database
ISI
SICI code
0305-0270(1992)19:6<631:SPOCAT>2.0.ZU;2-E
Abstract
In order to gain an understanding of the spatial connections between i nstrumental and proxy climatic data in subtropical regions, we investi gated the spatial patterns of climate and tree-growth anomalies in the montane forests of northwestern Argentina. Principal components techn ique was used to identify the dominant spatial patterns of climate and tree growth anomalies. A 43-year data set of monthly total precipitat ion at a selected network of thirty-one stations in northwestern Argen tina was analysed on annual and seasonal basis. The most dominant annu al pattern shows precipitation anomalies of the same sign over practic ally the whole area. The second and third patterns reflect altitudinal and latitudinal rainfall variations across the study area, respective ly. The tree-ring data set consisted of twelve chronologies developed from Juglans australis Griseb., Cedrela angustifolia Sesse Moc., and C edrela lilloi C.DC. The relationships between climatic conditions, sit e characteristics, and tree-ring growth were identified using response functions, correlation functions, and group analysis. These technique s show that tree ring widths in subtropical Argentina are affected by weather conditions from late winter to early summer. Tree-ring pattern s 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. Finally, dif ferent regression models were used to reconstruct annual and seasonal variations in precipitation. On average, 60-80% of the variance in reg ional precipitation is explained using the ring-width chronologies as predictive variables.