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

Published Date
September 2015, Vol.98:245–254, doi:10.1016/j.techfore.2015.06.003

Author 

Arkady Kryazhimskiy ^a,b,c

Elena Rovenskaya ^a,b,,

Anatoly Shvidenko ^a,d

Mykola Gusti ^a,e

Dmitry Shchepashchenko ^a,f

Victoria Veshchinskaya ^a

• aInternational Institute for Applied Systems Analysis, Schlossplatz 1, A-2361 Laxenburg, Austria
• bLomonosov Moscow State University, Faculty of Computational Mathematics and Cybernetics, 2nd Educational Building, Leninskie Gory, 119991 Moscow, Russia
• cSteklov Mathematical Institute, 8 Gubkina str., 119991 Moscow, Russia
• dSukachev Institute of Forest, Siberian Branch RAS, Akademgorodok, 660036 Krasnoyarsk, Russia
• eDepartment of International Information, Lviv Polytechnic National University, 12 Bandera str., 79013 Lviv, Ukraine
• fMoscow State Forest University, 1 Institutskayastr., 141005 Mytischi, Moscow region, Russia

Received 3 October 2014. Revised 31 May 2015. Accepted 2 June 2015. Available online 27 July 2015. 

Highlights

• We show applicability of a new approach for reconciling different uncertain models.
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  Net primary production (NPP) of Russian forests is used as an example.
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  Alternative estimates of NPP by each bioclimatic zone are integrated into one.
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  Integration method employs principle of posterior compatibility of prior estimates.
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  Integration decreases the variances of the prior estimates.

Abstract

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.

Keywords

Net primary production of forest

Multi-model ensembles

Integration of models

Bayesian approach

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Vitae

Arkady Kryazhimskiy is a Principal Research Scholar at the Steklov Institute of Mathematics of the Russian Academy of Sciences, Moscow, Russia; a Professor at the Lomonosov Moscow State University, Faculty of Computational Mathematics and Cybernetics, Moscow, Russia; and a Senior Research Scholar at the Advanced Systems Analysis Program, International Institute for Applied Systems Analysis, Austria. He is a Full Member of the Russian Academy of Sciences. His research interests include games theory, optimization, and ill-posed problems.

Elena Rovenskaya is the Director of the Advanced Systems Analysis Program at the International Institute for Applied Systems Analysis; she is also a Research Scholar at the Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University, Russia. Her research interests include economic–environmental modeling and optimization.

Anatoly Shvidenko is a Senior Research Scholar at the Ecosystems Services and Management Program, International Institute for Applied Systems Analysis, Austria; he also works at the Sukachev Institute of Forest, Siberian Branch, Russian Academy of Sciences, Krasnoyarsk, Russia His main fields of interest are forest inventory, monitoring, mathematical modeling, global change, and boreal forests.

Mykola Gusti works at the Department of International Information, Lviv Polytechnic National University, Lviv, Ukraine; he is also a Research Scholar at the Ecosystems Services and Management Program at the International Institute for Applied Systems Analysis, Austria. His scientific interests are mathematical modeling and data processing applicable in environment research.

Dmitry Shchepashchenko is a Research Scholar at the Ecosystems Services and Management Program at the International Institute for Applied Systems Analysis, Austria. He also holds position of Professor at the Department of Pedology, Moscow State Forest University, Mytischi, Russia. His recent projects include a full carbon account of Northern Eurasia, remote sensing applications.

Victoria Veshchinskaya is a Research Assistant at the Evolution and Ecology Program and the Advanced Systems Analysis Program, International Institute for Applied Systems Analysis, Austria. Her main fields of scientific interest include optimal-control theory and its applications in biology and ecology.

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  Corresponding author at: International Institute for Applied Systems Analysis, Schlossplatz 1, A-2361 Laxenburg, Austria.

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