Mammalian herbivores are an essential component of grassland and savanna ecosystems, and with feedbacks to the climate system. To date, the response and feedbacks of mammalian herbivores to changes in both abiotic and biotic factors are poorly quantified and not adequately represented in the current global land surface modeling framework. In this study, we coupled herbivore population dynamics in a global land model (the Dynamic Land Ecosystem Model, DLEM 3.0) to simulate populations of horses, cattle, sheep, and goats, and their responses to changes in multiple environmental factors at the site level across different continents during 1980–2010. Simulated results show that the model is capable of reproducing observed herbivore population dynamics across all sites for these animal groups. Our simulation results also indicate that during this period, climate extremes led to a maximum mortality of 27% of the total herbivores in Mongolia. Across all sites, herbivores reduced aboveground net primary productivity (ANPP) and heterotrophic respiration (Rh) by 14% and 15%, respectively (p < 0.05). With adequate parameterization, the model can be used for historical assessment and future prediction of mammalian herbivore populations and their relevant impacts on biogeochemical cycles. Our simulation results demonstrate a strong coupling between primary producers and consumers, indicating that inclusion of herbivores into the global land modeling framework is essential to better understand the potentially large effect of herbivores on carbon cycles in grassland and savanna ecosystems.

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Published in Journal of Advances in Modeling Earth Systems, v. 9, issue 8, p. 2920-2945.

© 2017. The Authors.

This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

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This study has been supported by US National Science Foundation (1210360 and 1243232), National Key Research and Development Program of China (2017YFA0604702), the Chinese Academy of Sciences STS Program (KFJ-STS-ZDTP-0), SKLURE grant (SKLURE2017-1-6), and Auburn University IGP Program.

Related Content

The model input and output data in this study are archived in International Center for Climate and Global Change Research at Auburn University (http://wp.auburn.edu/cgc/).

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