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Global patterns and substrate‐based mechanisms of the terrestrial nitrogen cycle
Author(s) -
Niu Shuli,
Classen Aimée T.,
Dukes Jeffrey S.,
Kardol Paul,
Liu Lingli,
Luo Yiqi,
Rustad Lindsey,
Sun Jian,
Tang Jianwu,
Templer Pamela H.,
Thomas R. Quinn,
Tian Dashuan,
Vicca Sara,
Wang YingPing,
Xia Jianyang,
Zaehle Sönke
Publication year - 2016
Publication title -
ecology letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.852
H-Index - 265
eISSN - 1461-0248
pISSN - 1461-023X
DOI - 10.1111/ele.12591
Subject(s) - biogeochemical cycle , ecosystem , saturation (graph theory) , competition (biology) , nitrogen cycle , cycling , ecology , terrestrial ecosystem , nitrogen , environmental science , substrate (aquarium) , soil science , atmospheric sciences , biology , chemistry , geography , mathematics , physics , organic chemistry , archaeology , combinatorics
Nitrogen (N) deposition is impacting the services that ecosystems provide to humanity. However, the mechanisms determining impacts on the N cycle are not fully understood. To explore the mechanistic underpinnings of N impacts on N cycle processes, we reviewed and synthesised recent progress in ecosystem N research through empirical studies, conceptual analysis and model simulations. Experimental and observational studies have revealed that the stimulation of plant N uptake and soil retention generally diminishes as N loading increases, while dissolved and gaseous losses of N occur at low N availability but increase exponentially and become the dominant fate of N at high loading rates. The original N saturation hypothesis emphasises sequential N saturation from plant uptake to soil retention before N losses occur. However, biogeochemical models that simulate simultaneous competition for soil N substrates by multiple processes match the observed patterns of N losses better than models based on sequential competition. To enable better prediction of terrestrial N cycle responses to N loading, we recommend that future research identifies the response functions of different N processes to substrate availability using manipulative experiments, and incorporates the measured N saturation response functions into conceptual, theoretical and quantitative analyses.