Divergent long-term trends and inter-annual variation in ecosystem resource use efficiencies of a southern boreal old black spruce forest 1999-2017.

Long-term trends in ecosystem resource use efficiencies (RUEs) and their controlling factors are key pieces of information for understanding how an ecosystem responds to climate change. We used continuous eddy covariance and microclimate data over the period 1999-2017 from a 120-year-old black spruce stand in central Saskatchewan, Canada, to assess interannual variability, long-term trends, and key controlling factors of gross ecosystem production (GEP) and the RUEs of carbon (CUE = net primary production [NPP]/GEP), light (LUE = GEP/absorbed photosynthetic radiation [APAR]), and water (WUE = GEP/evapotranspiration [E]). At this site, annual GEP has shown an increasing trend over the 19 years (p < 0.01), which may be attributed to rising atmospheric CO2 concentration. Interannual variability in GEP, aside from its increasing trend, was most strongly related to spring temperatures. Associated with the significant increase in annual GEP were relatively small changes in NPP, APAR, and E, so that annual CUE showed a decreasing trend and annual LUE and WUE showed increasing trends over the 19 years. The long-term trends in the RUEs were related to the increasing CO2 concentration. Further analysis of detrended RUEs showed that their interannual variation was impacted most strongly by air temperature. Two-factor linear models combining CO2 concentration and air temperature performed well (R-2~0.60) in simulating annual RUEs. LUE and WUE were positively correlated both annually and seasonally, while LUE and CUE were mostly negatively correlated. Our results showed divergent long-term trends among CUE, LUE, and WUE and highlighted the need to account for the combined effects of climatic controls and the 'CO2 fertilization effect' on long-term variations in RUEs. Since most RUE-based models rely primarily on one resource limitation, the observed patterns of relative change among the three RUEs may have important implications for RUE-based modeling of C fluxes.