Leaf and fine root carbon stocks and turnover are coupled across Arctic ecosystems
Abstract Estimates of vegetation carbon pools and their turnover rates are central to understanding and modelling ecosystem responses to climate change and their feedbacks to climate. In the A rctic, a region containing globally important stores of soil carbon, and where the most rapid climate chang...
| Published in: | Global Change Biology |
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| Main Authors: | , , , , |
| Format: | Article in Journal/Newspaper |
| Language: | English |
| Published: |
Wiley
2013
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| Subjects: | |
| Online Access: | http://dx.doi.org/10.1111/gcb.12322 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fgcb.12322 https://onlinelibrary.wiley.com/doi/pdf/10.1111/gcb.12322 |
| Summary: | Abstract Estimates of vegetation carbon pools and their turnover rates are central to understanding and modelling ecosystem responses to climate change and their feedbacks to climate. In the A rctic, a region containing globally important stores of soil carbon, and where the most rapid climate change is expected over the coming century, plant communities have on average sixfold more biomass below ground than above ground, but knowledge of the root carbon pool sizes and turnover rates is limited. Here, we show that across eight plant communities, there is a significant positive relationship between leaf and fine root turnover rates ( r 2 = 0.68, P < 0.05), and that the turnover rates of both leaf ( r 2 = 0.63, P < 0.05) and fine root ( r 2 = 0.55, P < 0.05) pools are strongly correlated with leaf area index ( LAI , leaf area per unit ground area). This coupling of root and leaf dynamics supports the theory of a whole‐plant economics spectrum. We also show that the size of the fine root carbon pool initially increases linearly with increasing LAI , and then levels off at LAI = 1 m 2 m −2 , suggesting a functional balance between investment in leaves and fine roots at the whole community scale. These ecological relationships not only demonstrate close links between above and below‐ground plant carbon dynamics but also allow plant carbon pool sizes and their turnover rates to be predicted from the single readily quantifiable (and remotely sensed) parameter of LAI , including the possibility of estimating root data from satellites. |
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