A meta-analysis of elevated CO2 effects on woody plant mass, form, and physiology.

Quantitative integration of the literature on the effect of elevated CO2 on woody plants is important to aid our understanding of forest health in coming decades and to better predict terrestrial feedbacks on the global carbon cycle. We used meta-analytic methods to summarize and interpret more than 500 reports of effects of elevated CO2 on woody plant biomass accumulation and partitioning, gas exchange, and leaf nitrogen and starch content. The CO2 effect size metric we used was the log-transformed ratio of elevated compared to ambient response means weighted by the inverse of the variance of the log ratio. Variation in effect size among studies was partitioned according to the presence of interacting stress factors, length of CO2 exposure, functional group status, pot size, and type of CO2 exposure facility. Both total biomass (W T) and net CO2 assimilation (A) increased significantly at about twice ambient CO2, regardless of growth conditions. Low soil nutrient availability reduced the CO2 stimulation of W T by half, from +31% under optimal conditions to +16%, while low light increased the response to +52%. We found no significant shifts in biomass allocation under high CO2. Interacting stress factors had no effect on the magnitude of responses of A to CO2, although plants grown in growth chambers had significantly lower responses (+19%) than those grown in greenhouses or in open-top chambers (+54%). We found no consistent evidence for photosynthetic acclimation to CO2 enrichment except in trees grown in pots <0.5 l (-36%) and no significant CO2 effect on stomatal conductance. Both leaf dark respiration and leaf nitrogen were significantly reduced under elevated CO2 (-18% and -16% respectively, data expressed on a leaf mass basis), while leaf starch content increased significantly except in low nutrient grown gymnosperms. Our results provide robust, statistically defensible estimates of elevated CO2 effect sizes against which new results may be compared or for use in forest and climate model parameterization.