Disconnection between plant–microbial nutrient limitation across forest biomes
Nitrogen (N) and phosphorus (P) are essential elements limiting plant–microbial growth in forest ecosystems. However, whether the pattern of plant–microbe nutrient limitation is consistent across forest biomes and the associated potential mechanisms remain largely unclear, limiting us to better unde...
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Published in | Functional ecology Vol. 37; no. 8; pp. 2271 - 2281 |
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Main Authors | , , , , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
London
Wiley Subscription Services, Inc
01.08.2023
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Subjects | |
Online Access | Get full text |
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Summary: | Nitrogen (N) and phosphorus (P) are essential elements limiting plant–microbial growth in forest ecosystems. However, whether the pattern of plant–microbe nutrient limitation is consistent across forest biomes and the associated potential mechanisms remain largely unclear, limiting us to better understand the biogeochemical processes under future climate change.
Here, we investigated patterns of plant–microbial N/P limitation in forests across a wide environmental gradient and biomes in China to explore the divergence of plant–microbial N/P limitation and the driving mechanisms.
We revealed that 42.6% of the N/P limitation between plant–microbial communities was disconnected. Patterns in plant–microbial N/P limitations were consistent only for 17.7% of N and 39.7% of P. Geospatially, the inconsistency was more evident at mid‐latitudes, where plants were mainly N limited and microbes were mainly P limited. Furthermore, our findings were consistent with the ecological stoichiometry of plants and microbes themselves and their requirements. Whereas plant N and P limitation was more strongly responsive to meteorological conditions and atmospheric deposition, that of microbes was more strongly responsive to soil chemistry, which exacerbated the plant–microbe N and P limitation divergence.
Our work identified an important disconnection between plant and microbial N/P limitation, which should be incorporated into future Earth System Model to better predict forest biomes–climate change feedback.
Read the free Plain Language Summary for this article on the Journal blog.
Read the free Plain Language Summary for this article on the Journal blog. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
ISSN: | 0269-8463 1365-2435 |
DOI: | 10.1111/1365-2435.14361 |