Session: Biogeochemistry: Atmospheric N Deposition Effects
Nitrogen effects on plant productivity change at decadal timescales
Wednesday, August 4, 2021
ON DEMAND
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Guopeng Liang, The department of Biology, Utah State University, Logan, UT, Yiqi Luo, Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, Zhenghu Zhou, Center for Ecological Research, Northeast Forestry University, Harbin, China and Bonnie G. Waring, Department of Biology, Utah State University, Logan, UT
Presenting Author(s)
Guopeng Liang
The department of Biology, Utah State University Logan, Utah, United States
Background/Question/Methods Although some long-term studies have been conducted to quantify nitrogen (N) impacts on plant productivity, uncertainties remain regarding whether these impacts change over time and the underlying mechanisms. By overlooking this, we may over- or under-estimate N impacts on terrestrial ecosystems. We synthesized 127 N addition studies with duration ≥ 8 years in croplands and natural terrestrial ecosystems. Results/Conclusions The percentage of studies showing increased, decreased, and unchanged N impacts on plant productivity over time is 20%, 14%, and 66% in croplands, and is 13%, 22%, and 65% in natural ecosystems, respectively. The temporal pattern of N impacts is mostly regulated by N application rate in croplands, but by both initial soil pH (pH) and mean annual precipitation (MAP) in natural ecosystems. More specifically, N impacts in croplands are more likely to decrease with increasing N application rate. In addition, N impacts in natural ecosystems are more likely to decrease under low pH than high pH and under high MAP than low MAP. Our findings indicate that temporally dynamic impacts of long-term N addition on plant productivity are generally observed among studies in terrestrial ecosystems, and the controls on the temporal pattern of long-term N impacts on plant productivity are different between agricultural and natural ecosystems. Therefore, not only the magnitude of N impacts on plant productivity but also their temporal patterns should be considered in future experimental and model research.