Nitrogen effects on plant productivity change at decadal time‐scales

生物群落 灌木丛 生产力 生态系统 环境科学 陆地生态系统 生态学 全球变化 草原 初级生产 土壤水分 气候变化 大气科学 自然地理学 地理 生物 土壤科学 经济 宏观经济学 地质学
作者
Guopeng Liang,Yiqi Luo,Zhenghu Zhou,Bonnie G. Waring
出处
期刊:Global Ecology and Biogeography [Wiley]
卷期号:30 (12): 2488-2499 被引量:9
标识
DOI:10.1111/geb.13391
摘要

Abstract Aim Although some long‐term studies have been conducted to quantify the impacts of nitrogen (N) on plant productivity, uncertainties remain regarding whether these impacts change over time and the underlying mechanisms. By overlooking this, we might over‐ or underestimate the impacts of N on terrestrial ecosystems. Our goal was to determine whether the impacts of N on plant productivity change in the long term and what controls these dynamics. Location Global. Time period 1999–2018. Major taxa studied Effects of N on plant productivity. Methods We synthesized 63 N addition studies with duration ≥ 8 years in natural terrestrial ecosystems. Results Our results showed temporally dynamic impacts of N on plant productivity in terrestrial ecosystems. The interannual coefficient of variation (CV) of N impacts ranged from 19 to 768% across 63 studies, with higher variability in acidic soils. Moreover, a substantial proportion (44%) of studies showed evidence of a consistent directional change in the strength of the impacts of N over time. The direction of change varied with biome type (forests, decrease; grasslands and shrublands, increase). The temporal pattern of the impacts of N was mostly responsive to mean annual precipitation (MAP), mean annual temperature (MAT) and initial soil pH, which accounted for 24%, 19% and 19% of the variation, respectively. Main conclusions Our findings indicate that temporally dynamic impacts of long‐term N addition on plant productivity and large fluctuations of the impacts of N between years are generally observed among studies in terrestrial ecosystems. Therefore, not only the magnitude of N impacts on plant productivity, but also their temporal pattern and variability should be considered in future experimental and model research.
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