Abstract

Biological nitrogen (N) fixation plays an important role in terrestrial N cycling and represents a key driver of terrestrial net primary productivity (NPP). Despite the importance of N fixation in terrestrial ecosystems, our knowledge regarding the controls on terrestrial N fixation remains poor. Here, we conducted a meta-analysis (based on 852 observations from 158 studies) of N fixation across three types of ecosystems with different status of disturbance (no management, restoration [previously disturbed], and disturbance [currently disturbed]) and in response to multiple environmental change factors (warming, elevated carbon dioxide [CO2 ], increased precipitation, increased drought, increased N deposition, and their combinations). We explored the mechanisms underlying the changes in N fixation by examining the variations in soil physicochemical properties (bulk density, texture, moisture, and pH), plant and microbial characteristics (dominant plant species numbers, plant coverage, and soil microbial biomass), and soil resources (total carbon, total N, total phosphorus (P), inorganic N, and inorganic P). Human disturbance inhibited non-symbiotic N fixation but not symbiotic N fixation. Terrestrial N fixation was stimulated by warming (+152.7%), elevated CO2 (+19.6%), and increased precipitation (+73.1%) but inhibited by increased drought (-30.4%), N deposition (-31.0%), and combinations of available multiple environmental change factors (-14.5%), the extents of which varied among biomes and ecosystem compartments. Human disturbance reduced the N fixation responses to environmental change factors, which was associated with the changes in soil physicochemical properties (2%-56%, p<.001) and the declines in plant and microbial characteristics (3%-49%, p≤.003) and soil resources (6%-48%, p≤.03). Overall, our findings reveal for the first time the effects of multiple environmental change factors on terrestrial N fixation and indicate the role of human disturbance activities in inhibiting N fixation, which can improve our understanding, modeling, and prediction of terrestrial N budgets, NPP, and ecosystem feedbacks under global change scenarios.

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