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Physiology-based prognostic modeling of the influence of changes in precipitation on a keystone dryland plant species

  • Physiological ecology - Original research
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Abstract

Fluctuations in mean annual precipitation (MAP) will strongly influence the ecology of dryland ecosystems in the future, yet, because individual precipitation events drive growth and resource availability for many dryland organisms, changes in intra-annual precipitation may disproportionately influence future dryland processes. This work examines the hypothesis that intra-annual precipitation changes will drive dryland productivity to a greater extent than changes to MAP. To test this hypothesis, we created a physiology-based model to predict the effects of precipitation change on a widespread biocrust moss that regulates soil structure, water retention, and nutrient cycling in drylands. First, we used the model to examine moss productivity over the next 100 years driven by alterations in MAP by ±10, 20 and 30 %, and changes in intra-annual precipitation (event size and frequency). Productivity increased as a function of MAP, but differed among simulations where intra-annual precipitation was manipulated under constant MAP. Supporting our hypothesis, this demonstrates that, even if MAP does not change, changes in the features of individual precipitation events can strongly influence long-term performance. Second, we used the model to examine 100-year productivity based on projected dryland precipitation from published global and regional models. These simulations predicted 25–63 % reductions in productivity and increased moss mortality rates, declines that will likely alter water and nutrient cycling in dryland ecosystems. Intra-annual precipitation in model-based simulations was a stronger predictor of productivity compared to MAP, further supporting our hypothesis, and illustrating that intra-annual precipitation patterns may dominate dryland responses to altered precipitation in a future climate.

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Acknowledgments

We wish to acknowledge Steve Ellner for invaluable assistance in the initial development phases of the biocrust moss model as well as subsequent advice on final simulation procedures. We also thank Barbara Bedford, Tom Whitlow, and two anonymous reviewers for extremely valuable feedback on previous versions of this manuscript.

Conflict of interest

The authors declare no conflict of interest with the organizations that sponsored the research.

Ethical standard

The experiments presented in this manuscript comply with the current laws in the USA, where the experiments were performed.

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  1. Kirsten K. Coe

    Present address: Department of Plant Biology, Cornell University, 1132 Comstock Hall, Ithaca, NY, 14853, USA

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  1. Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY, 14853, USA

    Kirsten K. Coe & Jed P. Sparks

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  1. Kirsten K. Coe
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Correspondence to Kirsten K. Coe.

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Communicated by Russell Monson.

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Coe, K.K., Sparks, J.P. Physiology-based prognostic modeling of the influence of changes in precipitation on a keystone dryland plant species. Oecologia 176, 933–942 (2014). https://doi.org/10.1007/s00442-014-3067-7

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