Articles | Volume 8, issue 11
Geosci. Model Dev., 8, 3593–3619, 2015
Geosci. Model Dev., 8, 3593–3619, 2015

Development and technical paper 06 Nov 2015

Development and technical paper | 06 Nov 2015

Taking off the training wheels: the properties of a dynamic vegetation model without climate envelopes, CLM4.5(ED)

R. A. Fisher et al.

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Cited articles

Abramowitz, G.: Towards a public, standardized, diagnostic benchmarking system for land surface models, Geosci. Model Dev., 5, 819–827,, 2012.
Abramowitz, G., Leuning, R., Clark, M., and Pitman, A.: Evaluating the performance of land surface models, J. Climate, 21, 5468–5481, 2008.
Anav, A., Friedlingstein, P., Kidston, M., Bopp, L., Ciais, P., Cox, P., Jones, C., Jung, M., Myneni, R., and Zhu, Z.: Evaluating the land and ocean components of the global carbon cycle in the CMIP5 Earth System Models, J. Climate, 26, 6801–6843, 2013.
Anten, N. P. and During, H. J.: Is analysing the nitrogen use at the plant canopy level a matter of choosing the right optimization criterion?, Oecologia, 167, 293–303, 2011.
Arora, V. K. and Boer, G. J.: Simulating competition and coexistence between plant functional types in a dynamic vegetation model, Earth Interact., 10, 1–30, 2006.
Short summary
Predicting the distribution of vegetation under novel climates is important, both to understand how climate change will impact ecosystem services, but also to understand how vegetation changes might affect the carbon, energy and water cycles. Historically, predictions have been heavily dependent upon observations of existing vegetation boundaries. In this paper, we attempt to predict ecosystem boundaries from the ``bottom up'', and illustrate the complexities and promise of this approach.