Most North American forests are at some stage of post-disturbance regrowth, subject to a changing climate, and exhibit growth and mortality patterns that may not be closely coupled to annual environmental conditions. Distinguishing the possibly interacting effects of these processes is necessary to put short-term studies in a longer term context, and particularly important for the carbon-dense, fire-prone boreal forest. The goals of this study were to combine dendrochronological sampling, inventory records, and machine-learning algorithms to understand how tree growth and death have changed at one highly studied site (Northern Old Black Spruce, NOBS) in the central Canadian boreal forest. Over the 1999–2012 inventory period, mean tree diameter increased even as stand density and basal area declined significantly. Tree mortality averaged 1.4 ± 0.6% yr−1, with most mortality occurring in medium-sized trees; new recruitment was minimal. There have been at least two, and probably three, significant influxes of new trees since stand initiation, but none in recent decades. A combined tree ring chronology constructed from sampling in 2001, 2004, and 2012 showed several periods of extreme growth depression, with increased mortality lagging depressed growth by ~5 years. Higher minimum and maximum air temperatures exerted a negative influence on tree growth, while precipitation and climate moisture index had a positive effect; both current- and previous-year data exerted significant effects. Models based on these variables explained 23–44% of the ring-width variability. We suggest that past climate extremes led to significant mortality still visible in the current forest structure, with decadal dynamics superimposed on slower patterns of fire and succession. These results have significant implications for our understanding of previous work at NOBS, the carbon sequestration capability of old-growth stands in a disturbance-prone landscape, and the sustainable management of regional forests in a changing climate.