A New Framework for Evaluating Estimates of Symbiotic Nitrogen Fixation in Forests

Abstract

Symbiotic nitrogen fixation (SNF) makes atmospheric nitrogen biologically available and regulates carbon storage in many terrestrial ecosystems. Despite its global importance, estimates of SNF rates are highly uncertain, particularly in tropical forests where rates are assumed to be high. Here we provide a framework for evaluating the uncertainty of sample-based SNF estimates and discuss its implications for quantifying SNF and thus understanding of forest function. We apply this framework to field data sets from six lowland tropical rainforests (mature and secondary) in Brazil and Costa Rica. We use this data set to estimate parameters influencing SNF estimation error, notably the root nodule abundance and variation in SNF rates among soil cores containing root nodules. We then use simulations to gauge the relationship between sampling effort and SNF estimation accuracy for a combination of parameters. Field data illuminate a highly right-skewed lognormal distribution of SNF rates among soil cores containing root nodules that were rare and spanned five orders of magnitude. Consequently, simulations demonstrated that sample sizes of hundreds to even thousands of soil cores are needed to obtain estimates of SNF that are within, for example, a factor of 2 of the actual rate with 75% probability. This represents sample sizes that are larger than most studies to date. As a result of this previously undescribed uncertainty, we suggest that current estimates of SNF in tropical forests are not sufficiently constrained to elucidate forest stand-level controls of SNF, which hinders our understanding of the impact of SNF on tropical forest ecosystem processes.

Keywords: adaptive cluster sampling; sampling error; secondary tropical forests; symbiotic nitrogen fixation; tropical forests.