Tree demography dominates long-term growth trends inferred from tree rings

Abstract

Understanding responses of forests to increasing CO₂ and temperature is an important challenge, but no easy task. Tree rings are increasingly used to study such responses. In a recent study, van der Sleen et al. (2014) Nature Geoscience, 8, 4 used tree rings from 12 tropical tree species and find that despite increases in intrinsic water use efficiency, no growth stimulation is observed. This challenges the idea that increasing CO₂ would stimulate growth. Unfortunately, tree ring analysis can be plagued by biases, resulting in spurious growth trends. While their study evaluated several biases, it does not account for all. In particular, one bias may have seriously affected their results. Several of the species have recruitment patterns, which are not uniform, but clustered around one specific year. This results in spurious negative growth trends if growth rates are calculated in fixed size classes, as 'fast-growing' trees reach the sampling diameter earlier compared to slow growers and thus fast growth rates tend to have earlier calendar dates. We assessed the effect of this 'nonuniform age bias' on observed growth trends and find that van der Sleen's conclusions of a lack of growth stimulation do not hold. Growth trends are - at least partially - driven by underlying recruitment or age distributions. Species with more clustered age distributions show more negative growth trends, and simulations to estimate the effect of species' age distributions show growth trends close to those observed. Re-evaluation of the growth data and correction for the bias result in significant positive growth trends of 1-2% per decade for the full period, and 3-7% since 1950. These observations, however, should be taken cautiously as multiple biases affect these trend estimates. In all, our results highlight that tree ring studies of long-term growth trends can be strongly influenced by biases if demographic processes are not carefully accounted for.

Keywords: CO2 fertilization; climate change; dendrochronology; growth stimulation; population dynamics; sample bias; tropical forests.