Water variability impacts on conifer growth: Evaluating three multiscalar indices to clarify climate–growth relationships in northwestern Patagonia

Abstract

Understanding how climatic variability affects tree growth is crucial for managing afforestation projects in regions susceptible to water deficits. This study examines the correlation between basal area increment (BAI) and three multiscalar water variability indices — the Standardized Precipitation Evapotranspiration Index (SPEI), the Standardized Precipitation Index (SPI) and the Standardized Soil Moisture Index (SSMI) — in three introduced conifer species (Pinus ponderosa, Pseudotsuga menziesii and Pinus contorta var. murrayana) in northwestern Patagonia, Argentina. Growth chronologies were constructed using tree cores or cross-sections and were validated for each species and site. Spearman correlation analyses were applied across the phenological windows (12 months, July–June) at different temporal scales (1–18 months). The results revealed strong positive correlations between BAI and the water variability indices, particularly during the southern hemisphere´s growing season (October–March), with correlogram patterns suggesting cumulative hydrological effects. Hierarchical cluster analysis identified three groups of sites along a humidity gradient, indicating that sensitivity to water variability depends on local climatic and edaphic conditions. In drier northern sites, tree growth was linked to long-term water availability (6–18 months), whereas in more humid areas, responses were weaker or restricted to short temporal scales (less than five months). P. ponderosa and P. contorta exhibited similar patterns in nearby locations, whereas P. menziesii displayed broader response windows, although the limited number of sites for this species prevents drawing firm conclusions. These findings demonstrate that, while significant, the influence of water variability on introduced conifer growth in Patagonia is spatially heterogeneous, underscoring the importance of multiscalar indices to monitoring for adaptive forest management under future climate scenarios.