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Ability of the APSIM Next Generation Eucalyptus model to simulate complex traits across contrasting environments

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  • Elli, Elvis Felipe
  • Huth, Neil
  • Sentelhas, Paulo Cesar
  • Carneiro, Rafaela Lorenzato
  • Alvares, Clayton Alcarde

Abstract

Process-based simulation models are promising tools to integrate biophysical process with soil and climate conditions and then simulate genetic and management impacts on forest productivity. The aim of this study was to adapt, calibrate, evaluate and improve the performance of the APSIM Next Generation Eucalyptus model for different major Brazilian Eucalyptus clones. To these ends, experimental stemwood production data from 2012 to 2017 from eight Eucalyptus clones distributed over 23 locations with contrasting environmental conditions in Brazil were used. The APSIM Next Generation Eucalyptus model, when properly adapted and calibrated, performed well in simulating stemwood biomass and volume, basal area and leaf area index in subtropical and tropical regions and for different genetic entries. For stemwood biomass, the R2 ranged from 0.76 to 0.93 and the Willmott Agreement Index ranged from 0.93 to 0.98, indicating satisfactory precision and accuracy, respectively. As the model performed well, it may be a valuable decision support tool to help foresters in matching suitable genotypes to their sites, to simulate the best management strategies and to assist in long-term forest planning.

Suggested Citation

  • Elli, Elvis Felipe & Huth, Neil & Sentelhas, Paulo Cesar & Carneiro, Rafaela Lorenzato & Alvares, Clayton Alcarde, 2020. "Ability of the APSIM Next Generation Eucalyptus model to simulate complex traits across contrasting environments," Ecological Modelling, Elsevier, vol. 419(C).
    • Handle: RePEc:eee:ecomod:v:419:y:2020:i:c:s0304380020300314
    DOI: 10.1016/j.ecolmodel.2020.108959
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    1. Miehle, Peter & Battaglia, Michael & Sands, Peter J. & Forrester, David I. & Feikema, Paul M. & Livesley, Stephen J. & Morris, Jim D. & Arndt, Stefan K., 2009. "A comparison of four process-based models and a statistical regression model to predict growth of Eucalyptus globulus plantations," Ecological Modelling, Elsevier, vol. 220(5), pages 734-746.
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    1. Yang, Xuan & Jia, Pengfei & Hou, Qingqing & Zhu, Min, 2023. "Quantitative sensitivity of crop productivity and water productivity to precipitation during growth periods in the Agro-Pastoral Ecotone of Shanxi Province, China, based on APSIM," Agricultural Water Management, Elsevier, vol. 283(C).

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