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.