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Forest productivity under climate change: a checklist for evaluating model studies

Author

Listed:
  • Belinda E. Medlyn
  • Remko A. Duursma
  • Melanie J. B. Zeppel

Abstract

Climate change is highly likely to impact on forest productivity over the next century. The direction and magnitude of change are uncertain because many factors are changing simultaneously, such as atmospheric composition, temperature, rainfall, and land use. Simulation models have been widely used to estimate how these interacting factors might combine to alter forest productivity. Such studies have used many different types of models with different underlying assumptions. To evaluate predictions made by such studies, it is essential to understand the type of model and the assumptions used. In this article, we provide a checklist for use when evaluating modeled estimates of climate change impacts on forest productivity. The checklist highlights the assumptions that we believe are critical in determining model outcomes. Models are classified into different general types, and assumptions relating to effects of atmospheric CO2 concentration, temperature, water availability, nutrient cycling, and disturbance are discussed. Our main aim is to provide a guide to enable correct interpretation of model projections. The article also challenges modelers to improve the quality of information provided about their model assumptions. WIREs Clim Change 2011 2 332–355 DOI: 10.1002/wcc.108 This article is categorized under: Assessing Impacts of Climate Change > Evaluating Future Impacts of Climate Change

Suggested Citation

  • Belinda E. Medlyn & Remko A. Duursma & Melanie J. B. Zeppel, 2011. "Forest productivity under climate change: a checklist for evaluating model studies," Wiley Interdisciplinary Reviews: Climate Change, John Wiley & Sons, vol. 2(3), pages 332-355, May.
  • Handle: RePEc:wly:wirecc:v:2:y:2011:i:3:p:332-355
    DOI: 10.1002/wcc.108
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    Cited by:

    1. Xie, Yalin & Lei, Xiangdong & Shi, Jingning, 2020. "Impacts of climate change on biological rotation of Larix olgensis plantations for timber production and carbon storage in northeast China using the 3-PGmix model," Ecological Modelling, Elsevier, vol. 435(C).
    2. Yingchang Li & Mingyang Li & Yuehui Wang, 2022. "Forest Aboveground Biomass Estimation and Response to Climate Change Based on Remote Sensing Data," Sustainability, MDPI, vol. 14(21), pages 1-27, October.

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