bioRxiv preprint doi: https://doi.org/10.1101/464578; this version posted December 24, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Article A forest model intercomparison framework and application at two temperate forests along the East Coast of the United States Adam Erickson1* , Nikolay Strigul1 1 Department of Mathematics and Statistics, Washington State University, 14204 NE Salmon Creek Avenue, Vancouver, WA 98686, USA; {adam.erickson, nick.strigul}@wsu.edu * Correspondence:
[email protected]; Tel.: +1-360-546-9655 Version December 24, 2018 submitted to Forests 1 Abstract: Forest models often reflect the dominant management paradigm of their time. Until the 2 late 1970s, this meant sustaining yields. Following landmark work in forest ecology, physiology, and 3 biogeochemistry, the current generation of models is further intended to inform ecological and climatic 4 forest management in alignment with national biodiversity and climate mitigation targets. This has 5 greatly increased the complexity of models used to inform management, making them difficult to 6 diagnose and understand. State-of-the-art forest models are often complex, analytically intractable, 7 and computationally-expensive, due to the explicit representation of detailed biogeochemical and 8 ecological processes. Different models often produce distinct results while predictions from the same 9 model vary with parameter values. In this project, we developed a rigorous quantitative approach for 10 conducting model intercomparisons and assessing model performance. We have applied our original 11 methodology to compare two forest biogeochemistry models, the Perfect Plasticity Approximation 12 with Simple Biogeochemistry (PPA-SiBGC) and Landscape Disturbance and Succession with Net 13 Ecosystem Carbon and Nitrogen (LANDIS-II NECN).