Stochastic antecedent modeling of tree growth-climate relationships: lags, legacies, and climatic memory
In this talk, I will present an overview of the stochastic antecedent modeling (SAM) framework (Ogle et al. [2015] Ecology Letters) for quantifying the effects of antecedent (past) climate on annual tree growth (ring widths). The SAM approach allows us to objectively quantify the relative importance of past monthly climate (e.g., precipitation, temperature, drought indices) on annual tree growth, and to identify potential time lags or periods of greatest influence. We apply the SAM approach to a variety of tree-ring data from the Southwest to explore the importance of monthly climate up to four years prior to ring formation. The approach lends new insight into the different time-scales of influence of different climate factors, with implications for how these time-scales and associated climate effects vary spatially (across the Southwest), among species, or during dry vs wet periods.