Towards harmonizing competing models: Russian forests' net primary production case study

This paper deals with the issue of reconciling gaps between stochastic estimates (probability distributions) provided by alternative statistically inaccurate observation/estimation techniques. We employ a posterior reconciliation (integration) method based on selection of mutually compatible test outcomes. Unlike other methods used in this context, the posterior integration method employed does not include assessment of the credibility of the original (prior) estimation sources, which is usually based on analysis of their past performance. The quality of the resulting posterior integrated distribution is evaluated in terms of change in the variance. The method is illustrated by integration of stochastic estimates of the annual net primary production (NPP) of forest ecosystems in seven bioclimatic zones of Russia. The estimates result from the use of two alternative NPP estimation techniques - the landscape-ecosystem approach based on empirical knowledge, and an ensemble of dynamic global vegetation models. The estimates differ by up to 23%. Elimination of these gaps could help better quantify the terrestrial ecosystems' input to the global carbon cycle. The paper suggests a set of candidates for credible integrated NPP estimates for Russia, which harmonize those provided by two alternative sources.