Contrasting climate drivers of seasonal growth in western vs. eastern Mexican mountain conifer forests

Abstract

Hydroclimate affects the radial growth responses of trees, but the drivers of their spatial and population variability are not sufficiently understood. We addressed this issue by sampling several conifer populations located at the same latitude, but at different longitude and elevation in western (W) and eastern (E) Mexican regions. We used dendroecology to disentangle how earlywood width (EW), latewood width (LW) and adjusted LW (LWadj), i.e. the residuals after removing EW influences on LW, responded to climate variables (temperature and precipitation), climate indices (Southern Oscillation Index, SOI, Niño 3.4, Pacific Decadal Oscillation, PDO) and a drought index (Standardised Precipitation-Evapotranspiration Index, SPEI). The W species (Pinus herrerae Martínez, Pinus durangensis Martínez, Abies durangensis Martínez and Cupressus lusitanica Mill.) showed lower growth rates than the E species (Pinus hartwegii Lindl., Picea mexicana Martínez, Pseudotsuga menziesii (Mirb.) Franco and Abies vejari Martínez). Growth in W benefits mostly from high precipitation in the prior winter and current spring and it is limited by high temperatures in spring, whereas growth in the E showed similar but weaker responses. Furthermore, positive (negative) correlations were found in radial growth with the Niño 3.4 (SOI) and the PDO from the prior to current autumns, which were again stronger in absolute terms in the W than in the E regions, excepting SOI in summer. In the W, P. durangensis and C. lusitanica were the least and most responsive species to spring drought, respectively; whilst P. menziesii and A. vejari were very responsive to spring drought compared to P. hartwegii in the E. Our results suggest greater responsiveness to hydroclimate and atmospheric patterns in the W than in the E region. These findings allow better interpretations of future changes in growth and composition in Mexican conifer forests, considering that climate models forecast warmer spring conditions and increased water shortage.