IANIGLA   20881
INSTITUTO ARGENTINO DE NIVOLOGIA, GLACIOLOGIA Y CIENCIAS AMBIENTALES
Unidad Ejecutora - UE
congresos y reuniones científicas
Título:
Climate sensitivity of tropical tree growth: a global meta-analysis based on tree rings
Autor/es:
PIETER A. ZUIDEMA; VALERIE TROUET; FLURIN BABST; PETER GROENENDIJK; MARIA E. FERRERO
Lugar:
San Leucio - Caserta
Reunión:
Conferencia; Tree Rings in Archaeology, Climatology and Ecology - TRACE 2019; 2019
Institución organizadora:
Association for Tree-Ring Research (ATR)
Resumen:
Tropical forests are crucial components of the global carbon cycle. Yet, we poorly understand climatic drivers of tropical tree growth and their responses to climatic shifts. Tree-ring based global analyses of climate sensitivity typically exclude tropical regions due to a lack of data. Here, we help filling this knowledge gap with a meta-analysis of published tropical tree-ring width chronologies. We compiled individual tree-ring measurements from >300 tropical chronologies from an international database (ITRDB) and a large number of collaborators. We included studies from climate zones across the tropics (i.e., between 30°N -30°S). We evaluated i) the main climatic drivers of tropical tree growth and their interactions, ii) how climatic sensitivity of tropical tree growth varies along climatic gradients, and iii) the strength of autocorrelation and lag effects of previous-year climate on tree growth. We found that main drivers of annual variation in tropical tree growth were mean annual precipitation (MAP) and temperature (MAT). The strength of the growth-precipitation correlation decreased with increasing MAP. Increasing MAP also led to lower inter-series correlations and growth variability, but did not affect autocorrelation. The strength of the growth-temperature correlation increased with elevation (i.e., decreasing MAT). Increasing temperature led to lower inter-series correlations and lower autocorrelation. Our study shows that tree-ring studies have high potential to improve our understanding of global tropical forest climate-growth patterns. Our results can be used to benchmark global vegetation modelling and to understand responses of tropical tree species to climate change.